Crop Productivity, Yield and Technology Adoption Survey of ATASP-1 Small Holder Farmers in Nigeria

AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE ONE

FEDERAL GOVERNMENT OF NIGERIA/ AFRICAN DEVELOPMENT BANK SUPPORTED AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE ONE (FGN/AfDB - ATASP-1)

CROP PRODUCTIVITY, YIELD AND TECHNOLOGY ADOPTION SURVEY (DRY SEASON IRRIGATION FARMING) OF RICE, CASSAVA AND SORGHUM AMONG THE SMALL HOLDER FARMERS OF ATASP-1 IN NIGERIA

June 2020

FEDERAL GOVERNMENT OF NIGERIA/ AFRICAN DEVELOPMENT BANK SUPPORTED AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE ONE (FGN/AfDB - ATASP-1)

CROP PRODUCTIVITY, YIELD AND TECHNOLOGY ADOPTION SURVEY (DRY SEASON IRRIGATION FARMING) OF RICE, CASSAVA AND SORGHUM AMONG THE SMALL HOLDER FARMERS OF ATASP-1 IN NIGERIA ISBN: 978-978-988-460-5 NATIONAL OFFICE

No. 15, Lord Luggard Street, Asokoro, Abuja FCT, Nigeria info@atasp1.gov.ng, atasp1_hq@atasp1.gov.ng 08137208947, 08036551491 www.atasp1.gov.ng www.facebook/ATASPNigeria Twitter @ataspnigeria

June 2020 Yield and Technology Adoption Survey

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ACKNOWLEDGMENT

W

e would like to express our special gratitude to the National Program Coordinator, Agricultural Transformation Agenda Support Program Phase-1 (NPC-ATASP-1); Dr. Muhammad Ibrahim Arabi who gave us the golden opportunity to do this national assignment on the Survey topic (Crop Productivity, Yield and Technology Adoption (Dry season Irrigation farming of Rice, Cassava and Sorghum among the small holder farmers of ATASP-1). Our appreciation goes to National Program Coordinating Team (NPCT) especially the Survey Technical Team that gave us all the necessary support in carrying out this study. We also like to thank our Zonal Offices staff who supported us during the field work.

We are overwhelmed in all humbleness and gratefulness to acknowledge our in-depth appreciation to all those who have contributed in putting this Report. It is evident that the Survey result shows that ATASP-1 intervention using the 3 crops (Sorghum, Rice and Cassava) in the 4 SCPZs of Adani-Omor, Bida-Badeggi, Kano-Jigawa and Kebbi-Sokoto has significantly improved the yield performance of the benefiting farmers.

We would like to thank all the others who contributed to the successful completion of this study.

Thank you and best wishes Shuaibu Abubakar, Ummah Team Leader

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TABLE OF

CONTENTS ACKNOWLEDGEMENT .......................................................................................................ii LIST OF TABLES .................................................................................................................vii LIST OF FIGURES.................................................................................................................ix EXECUTIVE SUMMARY....................................................................................................xii CHAPTER ONE ......................................................................................................................1 1.0 INTRODCUTION ............................................................................................................1 1.1 Background of Study ........................................................................................................1 Rationale: .................................................................................................................................3 1.2 Program Review Agricultural Transformation Agenda Support Program – 1 ..................4 1.3 Goal and Objectives. .........................................................................................................4 1.4 End-Line Outcomes ..........................................................................................................4 1.5 Implementation Strategy ...................................................................................................4 1.6 Program Coverage and Beneficiaries................................................................................5 1.7 Program Components and Description .............................................................................5 Component 1: Infrastructure Development ..........................................................................5 Component 2: Commodity Value Chain Development ........................................................5 Component 3: Program Management...................................................................................6 1.8 Purpose of the Study .........................................................................................................6 1.9 Objectives of the Study .....................................................................................................7 1.10Scope of the study .............................................................................................................8 1.11Limitations of the Study:...................................................................................................8 CHAPTER TWO......................................................................................................................9 2.0 Outreach Contributions to the ATASP-1 Program Development Objectives (PDO) ........9 Outreach Program Specific Objectives ................................................................................9 2.1 Technologies Disseminated and Adoption Strategies .......................................................9 2.1.1 Technologies disseminated to Sorghum farmers are:.................................................9 2.1.2

Technologies disseminated to rice farmers are:..............................................10

2.1.3

Technologies disseminated to Cassava farmers are:.......................................11

2.2 Demonstration Plots ........................................................................................................11 2.3 Innovation Platform ........................................................................................................12 2.4 Farmers Field Days .........................................................................................................12 2.5 Trainings..........................................................................................................................13

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2.6.1

The International Institute of Tropical Agriculture (IITA). ............................13

2.6.2

AfricaRice.......................................................................................................14

2.6.3

ICRISAT .........................................................................................................15

CHAPTER THREE................................................................................................................16 3.0 METHODOLOGY..........................................................................................................16 3.1 Study Area.......................................................................................................................16 3.2 Study Design ...................................................................................................................17 3.3 Sampling Procedure and Sample Selection ....................................................................17 3.4 Methods of Data Collection ............................................................................................18 3.5 Method of Data Analysis.................................................................................................18 3.6 Model Specification ........................................................................................................19 CHAPTER FOUR ..................................................................................................................22 4.0 Results and Findings: ......................................................................................................22 4.1 Socio-Economic Characteristics of the Farmers:............................................................22 4.1.1 Age distribution of respondents: ..............................................................................22 4.1.1.1

Rapid Yield: ....................................................................................................22

4.1.1.2

Technology Adoption: ....................................................................................23

4.1.2 Gender of Respondents: ...........................................................................................25 4.1.2.1

Rapid Yield: ....................................................................................................25

4.1.2.2

Technology Adoption: ....................................................................................26

4.1.3 Marital Status of Respondents: ................................................................................28 4.1.3.1

Technology Adoption: ....................................................................................28

4.1.4 Educational Level of Respondents:..........................................................................28 4.1.4.1 Technology Adoption:.......................................................................................28 4.1.5 Farm Size, structure and experience of Respondents under ATASP-1 ....................29 4.1.5.1a Rapid Yield- Farm Size: .................................................................................29 4.1.5.1b Rapid Yield -Years of Experience in Farming:...............................................30 4.1.5.2

Technology Adoption: ....................................................................................31

4.1.6 Mode of acquisition of the Land:.............................................................................33 4.1.6.1

Technology Adoption: ....................................................................................33

4.1.7 Rapid Yield: Rice .....................................................................................................34 4.1.8 Rapid Yield: Sorghum..............................................................................................35 4.1.9 Rapid Yield: Cassava ...............................................................................................36 4.1.10 Technology Adoption: Extension contact by ATASP-1 participating farmers.........37 4.1.11 Farmers' participation in innovation platform (IP), demonstration plots and field day in the Program areas. ..........................................................................................................38

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4.1.12 Credit information for the last cropping season.......................................................39 4.1.13 Farmers' association membership ............................................................................41 4.1.14 Access to agricultural training .................................................................................42 4.2 Technology Disseminated to Farmers.............................................................................43 4.2.1 Technologies disseminated on cassava ....................................................................43 4.2.2 Technologies disseminated on sorghum production ................................................44 4.2.3 Technologies disseminated on rice production ........................................................45 4.3 Mode of practicing technologies extended .....................................................................47 4.3.1 on cassava production ..............................................................................................47 4.3.2 Sorghum production.................................................................................................51 4.3.3 Rice Production........................................................................................................53 4.4

Reasons for farmers' adoption of Good Agronomic Practices (GAP) .....................57

4.5

Rate of Adoption of Technologies disseminated to farmers in the 4 SCPZs ...........59

4.5.1 Rate of Adoption of technologies disseminated to cassava farmers ........................59 4.5.2 Rate of Adoption of technologies disseminated to Sorghum farmers......................60 4.5.3 Rate of adoption of technologies disseminated to rice farmers ...............................61 4.6 Effects of Adoption of Good Agronomic Practices on Crop Production ........................61 4.7 Effect of GAP on farmers' income (Cassava, Sorghum and Rice farmers) ....................63 4.8 Effects of ATASP-1 on Fabricators output......................................................................64 4.9 Effects of ATASP-1 on Processors output.......................................................................65 4.10Effects of ATASP-1 on the income and wellbeing of participating Fabricators .............65 4.11Effects of ATASP-1 on the income and wellbeing of participating Processors ..............66 4.12Effects of ATASP-1 on Food Security / Overall Economic Development of the Country 67 4.13Factors Influencing Adoption of Technologies ...............................................................68 4.13.1

Factors Influencing Adoption of Cassava Technologies .....................................69

4.13.2 Factors Influencing Adoption of Technologies of Sorghum ....................................71 4.13.3 Factors Influencing Adoption of Technologies of Rice ...........................................74 4.14Constraints militating Against the Adoption of Good Agronomic Practices in ATASP .74 4.14.1 Constraints militating Against the Adoption of Good Agronomic Practices by Cassava Technologies.......................................................................................................................75 4.14.2 Constraints to Adoption of Good Agronomic Practices in Sorghum Technologies by ATASP-1 .............................................................................................................................77 4.14.3 Constraints militating Against the Adoption of Good Agronomic Practices for Rice Production...........................................................................................................................79 4.14.4Constraints militating against the adoption of Good Agronomic Practices by cassava farmers 4.14.5 Constraints militating against the adoption of Good Agronomic Practices among sorghum farmers ................................................................................................................................80

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4.14.6 Constraints militating against the adoption of Good Agronomic Practices for rice farmers ................................................................................................................................81 CHAPTER 5...........................................................................................................................83 5.0 CONCLUSION AND RECOMENDATIONS................................................................83 5.1 CONCLUSION ...............................................................................................................83 5.2 RECOMMENDATIONS ................................................................................................83 ANNEXURE..........................................................................................................................85 REFERENCES

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LIST OF TABLES Table 1: Farmers General Age Grouping by Zone .................................................................23 Table 2: Age Distribution of Farmers by Crops by Gender ..................................................24 Table 3: Gender distribution of Respondents (nos) Surveyed...............................................25 Table 4: Gender of Farmers' Household Head .......................................................................27 Table 5: Technology Adopters by Marital Status by Crop ...................................................28 Table 6: Highest Education of Household Heads by Crop Enterprise ..................................29 Table 7a: Farmers Average Crop Farming Land Size by Zone – Rapid Yield .......................30 Table 8: Experience of Respondents in Crop Production (Years)..........................................31 Table 9: Lead Farmers Average Years of Cropping Experience by Zone ..............................32 Table 10: Mode of Acquisition of Land ................................................................................34 Table 11: Summary of Rice Average Yield Across the Zones (mt/ha) ...................................34 Table 12: Summary of Sorghum Average Yield Across the Zones (mt/ha)...........................35 Table 13: Summary of Cassava Average Yield Across the Zones (mt/ha) ............................36 Table 14: Average Number of Extension Services Visits by Zone by State..........................37 Table 15: Participation in Innovation Platform by Zone.......................................................38 Table 16: Participated in Demonstration Plot by Zone .........................................................39 Table 17: Participated in Farmers' Field Day (FFD) by Zone...............................................39 Table 18: Credit Source by Zone...........................................................................................40 Table 19: Access to Credit for Crop Production ...................................................................40 Table 20: Lead Farmers Mean Credit Required Against Mean Credit Received by State....41 Table 21: Farmers Years of Participation in Farmers Association by Zone ..........................42 Table 22: Lead Farmers had Production Training by Zone...................................................42 Table 23: Technologies Disseminated on Cassava................................................................44 Table 24: Technologies Disseminated on Sorghum ..............................................................45 Table 25: Technologies Disseminated on Rice......................................................................46 Table 26: Mode of Practicing Cassava Technologies............................................................50 Table 27: Frequency of Practicing Sorghum Technologies...................................................52 Table 28: Frequency of Practicing Rice Technologies ..........................................................56 Table 29: Reasons for Farmers' Adoption of Good Agronomic Practices (GAP).................58 Table 30: Rate of Adoption of Cassava Technologies...........................................................59 Table 31: Rate of Adoption of Sorghum Technologies .........................................................61 Table 32: Rate of Adoption of Rice Technologies ................................................................61 Table 33: Effects of Adoption of GAP on Corp Production..................................................62

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Table 34: Fabricators' Mean Seasonal Number of Customers ..............................................64 Table 35: Mean Processed Output Quantity Before and After ATASP-1 by Zone................65 Table 36: Fabricators' Average Income Per Season Before and During ATASP-1 by Zone .66 Table 37:Mean Monthly Income Before and After ATASP-1 ...............................................67 Table 38: Technologies Practiced on Cassava ATASP-1.......................................................70 Table 39: Technologies Practiced on Sorghum ATASP-1 .....................................................71 Table 40: Technologies Practiced on Rice ATASP-1 ............................................................73 Table 41: Adoption of Good Agronomic Practiced Technology on Cassava ATASP-1 ........75 Table 42: Adoption of Good Agronomic Practiced Technology on Sorghum ATASP-1.......77 Table 43: Adoption of Good Agronomic Practiced Technology on Rice ATASP-1..............79 Table 44: Constraints Militating Against the Adoption of Good Agronomic Practices among Cassava Farmers.....................................................................................................................80 Table 45: Constraints militating Against the Adoption of Good Agronomic Practices Among Sorghum Farmers ...................................................................................................................81 Table 46: Constraints Militating Against the Adoption of Good Agronomic Practices Among Rice Farmers...........................................................................................................................82

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LIST OF FIGURES Figure 1: ATASP-1 Map of the Program area in Nigeria .......................................................16 Figure 2: Age of Beneficiary Farmers by Zone .....................................................................23 Figure 3: Age distribution of farmers by crop by gender.......................................................24 Figure 4: Farmers gender distribution by zone ......................................................................26 Figure 5: Farmers gender distribution by crop enterprise ......................................................27 Figure 6: Crop production mean years of experience by zone...............................................33 Figure 7: Technologies disseminated on cassava practiced ...................................................43 Figure 8: Technologies disseminated on sorghum practiced..................................................45 Figure 9: Technologies disseminated on rice practiced..........................................................47 Figure 10: frequency of practicing technologies on cassava..................................................49 Figure 11: frequency of practicing technologies on sorghum ................................................53 Figure 12: frequency of practicing technologies on rice........................................................55 Figure 13: Reasons for adoption of GAP technologies..........................................................58 Figure 14: Frequency of practicing adopted technologies on cassava ...................................60 Figure 15: Frequency of practicing adopted technologies on sorghum .................................60 Figure 16: Mean crop production for non-adopters and adopters..........................................63 Figure 17: Fabricators' mean seasonal number of customers.................................................64 Figure 18: Fabricators' mean monthly income before and after ATASP-1 ............................66 Figure 19: Mean monthly income of processors before and after ATASP-1 .........................67 Figure 20: Technologies practiced on cassava .......................................................................70 Figure 21: Technologies practiced on sorghum .....................................................................72 Figure 22: Technologies practiced on rice..............................................................................73

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LIST OF ANNEXURES Annexure 1: Field Pictures ..............................................................................................85 Annexure 2: Study Executor ...........................................................................................88 Annexure 3: Rapid Yield questionnaire...........................................................................89 Annexure 4: Farmers questionnaire.................................................................................96 Annexure 5: Fabricators FGD questionnaire.................................................................103 Annexure 6: Processors FGD questionnaire..................................................................106

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ACRONYMS FGDs IAR FMARD GAPs ATA ATASP-1 AfDB DRC FAO SCPZs PZs SMEs IITA IFAD AfricaRice AgSS CAADP ECOWAS UA USD LGAs ICRISAT CGIAR PDO HIV/AIDS R4D WARDA NARS UNDP UN

Focus Group Discussions Institute for Agricultural Research Federal Ministry of Agriculture and Rural Development Good Agronomic Practices Agricultural Transformation Agenda Agricultural Transformation Agenda Support Program Phase One African Development Bank Democratic Republic of Congo Food and Agriculture Organization Staple Crop Processing Zones Processing Zones Small and Medium Scale Enterprises International Institute of Tropical Agriculture International Fund for Agriculture and Development Africa Rice Center Agricultural Sector Strategy Comprehensive African Agricultural Development Program Economic Community of West African States Unit of Account United State Dollar Local Government Authority International Crop Research Institute for Semi-Arid Tropic Consultative Group on International Agricultural Research Program development Objectives Human Immune Virus/Acquire Immune Deficiency Syndrome Research for Development West Africa Rice Development Association National Agricultural Research Systems United Nation Development Program United Nation

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EXECUTIVE SUMMARY Crop Productivity, Yield and Technology Adoption Survey (Dry Season Irrigation Farming) of Rice, Cassava and Sorghum Amongst the Small Holder Farmers in Nigeria The Government of Nigeria initiated the Agricultural Transformation Agenda (ATA) program in 2012, deliberately to meaningfully reduce food imports by increasing the production of five key crops: rice, cassava, sorghum, cocoa and cotton. Over the years, the efforts made by the government toward the achievement of the project objectives has shown positive results due to the increased engagements from the project. This level of positive outcome requires continuous and sustained interventions that will spur increase in the production of the three key staple crops rice, sorghum and cassava became necessary. Also, the sustenance of ATASP-1 Program serves as the continued commitment by the Government with a focused effort on interventions that promotes reform in areas that had been identified and the appropriate move towards addressing prior gaps.

Since inception, ATASP-1 has designed many intervention strategies packaged for the rural farmers who have been identified as notable source of food for their locality and region. To date ATASP-1 has disseminated good agronomic practices (GAP) technologies for farmers; and relevant training for fabricators and processors.

The dissemination of GAP and the accompanying training call for continuous monitoring and assessment. To achieve this an annual monitoring and evaluation survey is conducted in the four zones of ADANI-OMOR, BIDA-BADEGGI, KANO-JIGAWA and KEBBISOKOTO named SCPZs where these technologies had been disseminated and the trainings conducted.

This study affirms that technologies and innovations imparted by ATASP-1 on the sampled beneficiaries (farmers, processors and fabricators) impacted tremendously on the yield performance of the farmers as well generated attractive income for the Processors and Fabricator's. Since more than 80% of the beneficiaries are within the age 30-50 years, and this combined with other sociometric attributes of these beneficiaries, could be viewed as a credit to ATASP-1's selection of the profiled farmers to drive the Program towards achieving its goal. Yield data collected for the crops indicated that, across the zones, average yield for rice was 6.12mt/ha; comparatively, an increase of 14.23% above previous year of 5.36mt/ha with a percentage growth rate of 4.74. For sorghum, the overall yield was 1.68mt/ha; an increase of 11.01% above the previous year of 1.51mt/ha with percentage growth rate of 3.67. While an overall average production of 34.0mt/ha was recorded for cassava and result shows a great increase of 97.54% above the previous year of 17.21mt/ha with percentage growth rate of 32.51. These could be Yield and Technology Adoption Survey

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attributed to farmers maximization of practicing the GAP technologies disseminated by ATASP-1.

In this section of the report, the highlights of the findings from the just conducted survey, are itemized as below: FARMERS: •No notable improvement was observed in gender inclusiveness in agriculture as indicated globally for the surveyed farmers at 9.3% for female and 90.7% for male •The youthfulness of the farmers was observed by respondents age distribution as follows. 4.7% below 30 years, 90.7% at 31 – 59 years; and 4.7% at 60 years and over. At 90.7%, the youths are dominant across the zones. This is good for adoption and sustainability.

•The general belief is that most rural farmers are not literate. Responses from the surveyed farmers indicated that 20.9% had primary, 34.9% had secondary / TCII; while 18.6% had tertiary education, and 23.3% had quor'anic, and contrary to the belief, only 2.3% had no education, Education has some role to play in the understanding and practicing of GAP; and the general observation during this study confirmed this with education rated as one of the significant predictors in the set of factors that influence GAP practices (study objective ix in the TOR).

•Access to farmland is crucial for farming. Farm size for the farmers surveyed was globally observed from responses at an average of 1.33ha, and 0.19ha minimum, 5.0ha maximum. ADANI-OMOR recorded 5.0ha maximum farm land; KANOJIGAWA 4.9ha, KEBBI-SOKOTO 2.8ha, and BIDA-BADEGGI 2.2ha.

•The surveyed farmers were asked about mode of acquisition of farmland for each of the crop enterprise. For RICE, 59.2% said inherited, 8.2% purchased, 24.5% Rented; while lease and gift was each at 4.1%. For SORGHUM, 78.1% said Inherited, 9.4% purchased, while rent and lease was each at 6.3%. For CASSAVA, 64.3% said inherited, 7.1% purchased, while rent and lease was each at 14.3% •The household size of the GAP adopting farmers surveyed was at an average size of 10 across the zones; 16 for ADANI-OMOR, 21 for BIDA-BADEGGI; while KANO-JIGAWA and KEBBI-SOKOTO each was 22 at maximum.

•The surveyed farmers who claimed higher yield was the reason for adopting the GAP technologies were, overall, 98.0% for rice enterprise farmer respondents, 96.6% for sorghum and 92.9% for cassava. Higher yield was followed closely by

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soil fertility enhancement, soil moisture retention and soil erosion control. 85.7% of rice enterprise farmer respondents, 82.8% of sorghum and 78.6% of cassava claimed that soil fertility enhancement was the reason; while 79.6% rice enterprise farmers' respondents, 92.6% of Sorghum and 85.7% of cassava claimed that soil erosion control was the reason. Other reasons are labor saving and climate change adaptation with respondents who indicated ranging from 49.0% to 75.9%.

•Access to credit facilities, 51.6% affirmed access to credit; while 48.4% said they did not have access. On ease of access to the credit, 70.5% affirmed that the loan was prompt; while 29.5% claimed that it was delayed. Easy access to loan is crucial to agricultural productivity; because farming is time bomb. Delayed access to the credit would affect the purpose the loan was applied for. Access by farmers from the different crop enterprises indicated that 60% of Rice Enterprise Farmers had access; while 40% did not. 35.7% of Sorghum Enterprise Farmers had access; while 64.3% did not. 53.8% of Cassava Enterprise Farmers had access; while 46.2% did not. The source of credit for those who got it was predominantly from Family and friend at 54.2%; followed by Credit Program at 16.7%while NGOs represent 8.3% of the sources. Cooperatives and Commercial Banks, respectively, represent 6.3% and 4.2%.

•Training on crop production is conducted for adopter farmers by ATASP-1.

97.9% of the adopter farmers surveyed affirmed that they benefited from this training; while 2.1% claimed they did not. Among those who benefitted from the training, 83% indicated satisfaction, while 17% claimed they were not. This is good overall rating of the production training. The training organizers mentioned by the surveyed farmers were ATASP-1 and the ADPs; and 98.9% of the respondents affirmed ATASP-1 as the organizers, while one respondent (1.1%) in ADANI-OMOR claimed ADP as the organizer. This confirms ATASP-1 as the main organizer of training on crop production.

•The adopters of Good Agronomic Practices (GAP) technologies were observed to have obtained remarkable difference in crop production performance compared to their non-adopter counterpart farmers. Also, from the observed regression function, other variables each exercised some influence (positive or negative) at varying magnitudes as the dependent variable (GAP ADOPTED) scales in step of 1.

•The three crop enterprises were assessed and the overall percentage increase in difference between outputs recorded by Adopters of GAP technologies and nonadopters was 93.1% for Rice; 146% for Sorghum; and 74% for Cassava.

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FABRICATORS:

The fabricators who were trained on fabricated equipment extended by ATASP-1 under the intervention Program were sampled during this study in the four SCPZs. Performance in business of these fabricators before and after ATASP-1 intervention were assessed particularly the intervention usefulness, customer patronage, and fabrication quality.

Overall, on the usefulness of the intervention, 92.3% affirmed that the intervention was very useful; while 7.7% claimed that the intervention was useful. Regarding patronage, 92.3% of the sampled fabricators affirmed that they witnessed increase in patronage due to ATASP-1 intervention; while 7.7% claimed no increase. Also improvement on fabrication quality was rated as excellent by 76.9% of the sampled fabricators; while 23.1% rated the improvement as very good.

The percentage difference in mean of seasonal patronage witnessed before and after ATSP-1 intervention by the sampled fabricators was 121.6%; and for the same period, seasonal percentage difference in average income before and after ATASP-1 was 125.0%.

This translates, respectively, to more than double patronage and income due to ATSP-1 intervention; very positive effects.

PROCESSORS:

Under the intervention Program, some processors also benefitted from the processor technologies extended by ATASP-1. Some of these processors were sampled for this study. In like manner as the fabricators, the focus was on performance in business regarding intervention usefulness, monthly customer patronage, output and income.

ATASP-1 support was overall rated by 85.7% of the sampled processors as very useful; while 14.3% claimed that the support was just useful. Customer patronage before ATASP-1 support was rated by 57.1% of the sampled processors as fair; while 42.9% claimed that patronage was poor. Contrary to this assertion; all the sampled processors, 100%, claimed that customer patronage after ATASP-1 support was good. Overall, the percentage difference in mean for output processed before and after ATASP-1 was 170%; and 122% for monthly income. More mean monthly income, KANO-JIGAWA indicated the highest performance increase at 129%, followed closely by BIDA-BADEGGI at 125%, and ADANI-OMOR at 118%; while KEBBI-SOKOTO indicated 82.1%. Overall, there is impressive improvement in performance that could be linked to ATASP-1 intervention Program just as the processors also affirmed.

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CHAPTER

ONE

1.0

INTRODCUTION

1.1

Background of Study Agriculture is an important sector of the economy with high potentials for employment generation, food security and poverty reduction. However, these potentials have remained largely untapped which led to the dwindling performance of the agricultural sector both domestically and in the international trade over years (Federal Ministry of Agriculture and Rural Development, FMARD, 2011). Although, agriculture still remains the largest sector of the Nigerian economy and employs two-thirds of the entire labour force, the production hurdles have significantly stifled the performance of the sector. In the past 20 years, value-added per capita in agriculture has risen by less than 1%annually.

It is estimated that Nigeria has lost USD 10 billion in annual export opportunity from groundnut, palm oil, cocoa and cotton alone due to continuous decline in the production of those commodities. Food (crop) production increases have not kept pace with population growth, resulting in rising food imports and declining levels of national food self-sufficiency (FMARD, 2008).

In spite of the oil, agriculture remains the base of the Nigerian economy, providing the main source of livelihood for most Nigerians. The sector faces many challenges, notably an outdated land tenure system that constrains access to land (1.8 ha/farming household), a very low level of irrigation development (less than 1%of cropped land under irrigation), limited adoption of research findings and technologies, high cost of farm inputs, poor access to credit, inefficient fertilizer procurement and distribution, inadequate storage facilities and poor access to markets have all combined to keep agricultural productivity low (average of 1.2 metric tons of cereals/ha) with high postharvest losses and waste (FAO, 2020). Also, agriculture still remains the largest sector of the Nigerian economy and employs two-thirds of the entire labour force, the production hurdles have Yield and Technology Adoption Survey

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significantly stifled the performance of the sector. Over the past 20 years, value-added per capita in agriculture has risen by less than 1%annually. It is estimated that Nigeria has lost USD 10 billion in annual export opportunity from groundnut, palm oil, cocoa and cotton alone due to continuous decline in the production of those commodities. Food (crop) production increases have not kept pace with population growth, resulting in rising food imports and declining levels of national food self-sufficiency (FMARD, 2008).

Despite the preponderance of hydrocarbons, the agricultural sector continues to play a decisive role in Nigeria's economic development. Nigeria Gross Domestic Product (GDP) at basic constant price (real GDP) grew by 2.27 per cent year-on-year (YoY) from N69.80 trillion in 2018 to N71.39 trillion in 2019 compared to 1.91 per cent in 2018. The growth was largely due to the contributions of the agricultural sector (N10.50 trillion), trade sector (N5.94 trillion) and the information and communication sector (N4.66 trillion) with 25.2 per cent, 16 per cent and 13 per cent shares of the total GDP respectively in 2019. Similarly, the GDP grew by 2.55 per cent (YoY) in real terms in the fourth quarter (Q4) of 2019 to N707.57 billion compared to the N696.78 billion in Q4 2018 when it recorded a growth rate of 2.38 percent. This growth between the two periods which represents an increase of 0.17 per cent points and is largely because of the contribution of the three aforementioned sectors (Business day, Feb, 2020).

The Federal Republic of Nigeria aims at diversifying the economy from reliance on oil, assure food security and create jobs, especially for the youth. In line with this, the Federal Ministry of Agriculture and Rural Development implemented Agricultural Transformation Agenda (ATA) to promote agribusiness, attract private sector investment in agriculture, reduce post-harvest losses, add value to local agricultural produce, develop rural infrastructure and enhance access of farmers to financial services and markets. The ATA sets out to create over 3.5 million jobs along the value chains of the priority crops for Nigeria's teeming youths and women, in particular (African Development Bank, 2013).

The Agricultural Transformation Agenda Support Program, Phase One (ATASP-1) is an agricultural program developed by the African Development Bank (AfDB) in collaboration with Nigeria's Federal Ministry of Agriculture and Rural Development (FMARD) to contribute to food and nutrition security, employment generation, and wealth creation along the rice, cassava, and sorghum value chains (ATASP-1, 2017).The importance of the three key staple food crops namely cassava, rice and sorghum for which ATASP-1 is to bring about increase in production cannot be over emphasized. For instance, cassava (ManihotesculentaCrantz) which has been described as an industrial crop of the future in Africa, with the potential to generate income for poor farmers and a huge number of jobs has enormous potential to improve food security and the livelihoods of people in Africa. Cassava is an important food crop both for urban and rural consumers in Sub-Saharan Africa. Cassava is a basic staple food in Nigeria, Mozambique, Zambia, Democratic Republic of Congo (DRC), Ghana, Malawi, and Tanzania. Recently, cassava has increasingly gained importance as a cash crop for smallholder farmers in the region.

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Africa is the largest cassava producing region in the world accounting for nearly 55%of the world's cassava production. However, Africa's yields are the lowest in the world standing at only 10 tonnes per hectare compared to 26 tonnes per hectare in India (African Agricultural Technology Foundation, AATF, 2017).

Sorghum bicolor is an important food crop in Africa, Central America, and South Asia and is the fifth most important cereal crop grown in the world as well as the most important cereal food in the Northern states of Nigeria that covers the guinea savannah ecological zone (FAO, 2004).

Finally, Nigeria depends on about 3 million tons of parboiled rice imports to meet half of its rice demand (Global Agricultural Information Network, 2014). Rice is a staple food in several African nations and constitutes a bigger portion of the diet on a regular basis. In the last thirty years, rice showed constant increases in sales and its rising significance reflects the strategic food security initiatives adopted in many nations. Aside from a handful of nations that enjoy self-sufficiency in rice cultivation, rice consumption surpasses production and substantial amount of the crop are imported to sustain local demand at the expense of hard earned foreign currency reserves. Throughout the closing decades of the 20th century, Nigeria's rice output reached overwhelmingly high levels.

From the rapid rise in farmland area devoted to rice during that era in Nigeria, the production and consumption increased enormously. However, the growing output has not been adequate enough to meet the rising demand. To bridge such a huge deficit in the face of policy flaws, Nigeria resorted to the massive importation of rice at an unprecedented rate. Given the rising profile of rice as an essential element of Nigeria's food menu and the fact that imported rice accounts for a major portion of the nation's food imports, there is a growing desire among policy makers to boost rice production locally (Meremet al., 2017).

Rationale: The Agricultural Transformation Agenda (ATA) has a great potential in enhancing the role of agriculture as an engine of inclusive growth leading to rural employment, wealth creation, and diversification of the economy. A major policy accomplishment in the sector is the liberation of seed and fertilizer supply, which had hitherto been controlled by the Federal Government, undermined the private sector and did not deliver the inputs to genuine farmers. Since September 2011, fertilizers and seeds are being sold by companies directly to farmers. Lending commitments from commercial banks has been leveraged using guarantees issued by the Ministry of Finance to finance the seed and fertilizer supply.

The Program is also in line with the Bank's Agricultural Sector Strategy (AgSS) (20102014) which emphasizes investment in agricultural infrastructure as means of boosting agricultural productivity, food and nutrition security, and wealth creation; and Bank's Strategy (2013-2022) as it pertains to inclusive growth objective through the involvement of youth, women and skills development. It is also in alignment with Pillar 2 Yield and Technology Adoption Survey

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(improving rural infrastructure and trade-related capacities for market access) and Pillar 3 (increasing food supply and reducing hunger) of the Comprehensive African Agriculture Development Program (CAADP). Furthermore, the Program is relevant to Pillar I (Linking Regional Markets) of the Regional Integration Strategy Paper of March 2011 by potential increase in volumes of processed food commodities transported to landlocked countries such as Niger and Chad through rehabilitated access and trunk roads.

1.2

Program Review Agricultural Transformation Agenda Support Program Phase-1 The ATASP-1 is being implemented duration of 5 - 7 years (2015-2019 and extended to 2021), and it is estimated to cost UA113.54 million (USD174.85 million), with UA98.78 million (USD152.12 million) and UA0.25 million (USD0.385 million) financed from ADF loan and grant resources respectively, in four Staple Crops Processing Zones (SCPZs) of Adani-Omor, Bida-Badeggi, Kano-Jigawa and Kebbi-Sokoto. The Program is presently providing interventions in over 200 rural communities spreading across 33 LGAs in Seven States of Anambra, Enugu, Kano, Kebbi, Jigawa, Niger and Sokoto.

These communities and Local Government Areas of the seven States occupy about 194,426 square kilometre of land area with a population of 32,121,944 people who are nd predominantly farmers and rural entrepreneurs. ATASP-1 Loan was signed on 22 May, th 2014. The Loan was declared effective on 20 February, 2015. The Program was launched on 6th March, 2015 at IITA Station, Kubwa.

1.3

Goal and Objectives.

The main/primary goal of ATASP-1 is to contribute to poverty reduction, employment generation, import substitution, economic diversification and growth of Nigeria, particularly in Adani-Omor, Bida-Badeggi, Kano-Jigawa and Kebbi-Sokoto Staple Crop Processing Zones. The specific development objectives of the program include: to improve food and nutrition security, create jobs and enhance the incomes and shared wealth of the program beneficiaries on a sustainable basis through rice, sorghum and cassava value chains.

1.4

End-Line Outcomes The major outcomes expected from the interventions are: · 20, 000 metric tons of food crops produced per annum · 350, 000 Revised new Jobs created along commodity value chains · 25% Increased Incomes of beneficiaries. · 40, 000 Revised Youths trained on agribusiness and enterprise development

1.5

Implementation Strategy The program implementation strategy is based on commodity value chain development approach. This implementation strategy is geared towards ensuring improved crop productivity and continuous linkages with the off-takers of produce leading to incremental food supply and strong partnership of value chain actors in the Nigeria

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markets, thereby contributing to enhanced food and nutrition security, promoting employment creation, promoting income generation and wealth creation, and reducing hunger in Nigeria.

1.6

Program Coverage and Beneficiaries The target beneficiaries of the program include: farmers and farmers' cooperatives, commodity processors, private sector operators and registered Small and Medium Enterprises (SMEs), input dealers and service providers in the four staple crop processing zones of Adani-Omor, Bida-Badeggi, Kano-Jigawa and Kebbi-Sokoto agricultural production corridors.

1.7

Program Components and Description The Program is made up of three complementary and mutually reinforcing program components, as described below: Component 1: Infrastructure Development Rehabilitation of agricultural and ancillary social infrastructure, namely: irrigation water conveyance canals, various hydraulic structures, feeder roads, primary schools, community health centres, provision of potable water supply and sanitation/hygiene facilities; rehabilitation of demonstration and technology centres, and community produce markets.

Component 2: Commodity Value Chain Development Capacity development for relevant ministries and departments; private and communitybased institutions; training value chain actors in technical and managerial skills; promoting use of science and technology; training in post-harvest reduction methods; business and entrepreneurship training; training of communities and health workers on prevention and management of common diseases, nutrition and hygienic practices; development of market information system (MIS); management of environmental and social impacts; implementation of policies to promote private sector investment in agriculture.

There is an outreach program of ATASP-1, which is embedded in the component 2 of the program, and implemented by IITA and its consortium, comprising IITA, AfricaRice and ICRISAT. The responsibility of implementing Component 2, rest on CGIAR centres in Nigeria and with the objective of transforming Nigeria's cassava, rice, and sorghum sectors with the three CGIAR centres. The mandates of the CGIARs include; IITA for cassava; AfricaRice for rice; and ICRISAT for sorghum with their national partners, and IITA as the prime contractor for executing the outreach program. This Sub-Program has three sub-components as follows: Sub-Component 1: Technology verification and extension with activities on (i) Technology verification, (ii) seed systems, planting material production, and diffusion.

Sub-Component 2: Skill development activities on (i) agribusiness development, (ii) Yield and Technology Adoption Survey

5

processing and marketing, and (iii) promotion of youth entrepreneurship in agriculture.

Sub-Component 3: Effective program management comprising activities such as: (i) M&E studies, (ii) performance management and reporting, (iii) establishment of an appropriate management structure, and (iv) the establishment of Youth Agribusiness Training Centres.

The targeted beneficiaries of the outreach sub-program include; farmers' groups, processor groups, farmer input/service provider groups, sensitized persons (for market information services, open days, mass media), fabricators, marketers and transporters, seed companies, the youths, training participants, and policy makers.

Component 3: Program Management Coordination of program activities; management based on results measurement framework; monitoring and evaluation; implementation of Environmental and Social Management Plan (ESMP); program procurement, disbursement, financial management, audit and reporting 1.8

Purpose of the Study Many technologies have been disseminated to boost cassava, sorghum and rice production through the effort of the intervention ATASP-1 program introduced by the Federal Ministry of Agriculture and Rural Development. The need to gauge how these technologies have really helped to increase crop productivity since inception and the need to increase agricultural productivity through the use of improved agricultural technologies and practices by the smallholder farmers in the face of acute food shortage and worsened living conditions necessitate this study. Nigeria is by far the largest agricultural producer of staple crops in ECOWAS. The most important crops for Nigeria are root crops and tubers on the one hand, and grains on the other. Root crops and tubers of which cassava is paramount account for more than two-thirds of staples grown in Nigeria. Nigeria's is the world's leading producer of cassava. Though, domestic cassava production has increased greatly since the late 1990s primarily due to the expansion/increase of farmed land, but cassava yield has stagnated at a low level (12t/h) on the national average. While the production of staple foods has risen sharply over the last twenty-five years, production cannot yet cover the rising demand for staples, particularly grains. Nigeria alone grows about 50% of the total production in West Africa.

As is the case in nearly all West African countries, rise in grain production is due largely to the expansion of cultivated land than to any significant improvement in yields.

Meanwhile, sorghum yield has stagnated at an average yield of 1-1.5t/ha, rice yield has stagnated at about2 t/ha on the average since 1990 (Inter reseaux, 2015). Low agricultural productivity in Nigeria has been largely due to low, inappropriate and inadequate application of good agronomic practices such as fertilizer, improved seed utilization, and a wide gamut of on-farm and post-farm activities related to food safety, food quality and food security, the environmental impacts of agriculture (Hobbs, 2003; FMARD, 2011).

In order to take corrective measures and achieve the ATASP-1 targets for cassava, rice and sorghum, concerted efforts must be made to provide information on the adoption of Yield and Technology Adoption Survey

6

GAP among the farmers. This study is therefore an attempt to evaluate the progression of adoption of disseminated technologies under ATASP-1 in the various zones and across the entire country.

1.9

Objectives of the Study The major objective of the study is to determine the yield and technology adoption rates and assess the effect of the adoption of Good Agronomic Practices (GAP) of ATASP-1 beneficiary farmers who are supported in rice, cassava and sorghum production under Outreach Program at the Adani-Omor, Bida-Badeggi, Kano-Jigawa and Kebbi-Sokoto Staple Crop Processing Zones (SCPZs). In specific terms, the objectives of the survey are to: (i) Obtain representative yield data of ATASP-1 farmers (for rice, cassava and sorghum) in the Program implementing states across Nigeria; (ii) Compare the yield of the promoted commodities of ATASP-1 across the SCPZs; (iii) Identify and assess the agricultural techniques applied by ATASP-1 farmers in their crop production activities that could affect yield; (iv) Validate the inclusiveness of the ATASP-1 beneficiaries in terms of youth and gender. (v) identify the Good Agronomic Practices extended to the ATASP-1 smallholder famers; (vi) determine the perception of smallholder farmers on adoption of Good Agronomic Practices; (vii) examine the extent of adoption of Good Agronomic Practices; (viii) determine the effects of the adoption of Good Agronomic Practices on crop productivity and production; (ix) Ascertain the factors influencing the adoption of Good Agronomic Practices amongst ATASP-1 farmers; (x) Identify the constraints militating against the adoption of Good Agronomic Practices among farmers, and (xi) Make recommendations for improvement in the adoption of Good Agronomic Practices.

The Program is also in line with the Bank's Agricultural Sector Strategy (AgSS) (20102014) which emphasizes investment in agricultural infrastructure as means of boosting agricultural productivity, food and nutrition security, and wealth creation; and Bank's Strategy (2013-2022) as it pertains to inclusive growth objective through the involvement of youth, women and skills development. It is also in alignment with Pillar 2 (improving rural infrastructure and trade-related capacities for market access) and Pillar 3 (increasing food supply and reducing hunger) of the Comprehensive African Agriculture Development Program (CAADP). Furthermore, the Program is relevant to Pillar I (Linking Regional Markets) of the Regional Integration Strategy Paper of March 2011by potential increase in volumes of processed food commodities transported to landlocked countries such as Niger and Chad through rehabilitated access and trunk roads.

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1.10

Scope of the study The study was conducted in the four Staple Crop Processing Zones (SCPZs), namely Adani-Omor SCPZ (Anambra and Enugu States), Bida-Badeggi SCPZ (Niger State), and Kano – Jigawa SCPZ (Kano and Jigawa States) and Kebbi-Sokoto SCPZ (Kebbi and Sokoto States). While three crops namely cassava, sorghum and rice were the crops promoted by the program across the SCPZ in the North West, North Central and South East, cassava was not part of crops promoted in Kebbi-Sokoto SCPZ and therefore only sorghum and rice farmers were sampled in the zone.

1.11

Limitations of the Study: Obviously ATASP-1 is product of well-researched methodology for rural development; and the management has applied this in good details; such that makes it difficult to shortlist limitations due to managerial gaps. However, the following are listed for notification and where possible to work on it.

1) Covid-19 pandemic, surrounded with precautionary measures including social distancing and face masking generated palpable fear of contracting the diseases.

Nevertheless, there was no report of anyone infected.

2) Obtaining independent views from community leaders and/non-beneficiaries was not incorporated 3) While number of days allocated for fieldwork is enough for some, it wasn't so for others

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CHAPTER

TWO

2.0

Outreach Contributions to the ATASP-1 Program Development Objectives (PDO) The general purpose behind ATASP-1 the Outreach Program is to empower the selected youths in Nigeria through the full assertion of the capability of cassava, rice, and sorghum regard chains for employment/income generation and food security, especially among a bit of the country's least blessed and weakest masses.

Outreach Program Specific Objectives * To identify and promote science-based solutions for cassava, rice, and sorghum value chains through technology verification, production, and diffusion of quality seed and planting material underpinned by sound seed systems. * To enhance skills acquisition and hence job creation through the development of agribusiness, processing, and marketing, and the promotion of youth entrepreneurship. * To ensure effective program management, monitoring, and evaluation using appropriate and quantitative results measurement frameworks to assess progress.

2.1

Technologies Disseminated and Adoption Strategies There are many technologies disseminated by the program on the three crops covered by the program in the four SCPZs across the country to enhance the achievement of goal and objectives of the program. The lists of these technologies transferred to farmers are as discussed below:

2.1.1

Technologies disseminated to Sorghum farmers are: A. Good Agronomic Practices (GAP) This comprises the following: 1.

Variety selection include; SAMSORG17 (SK5912), SAMSORG45 (Improved Deko), SAMSORG46 (Improved Zabuwa), CSR01, CSR02, Yield and Technology Adoption Survey

9

2.

3.

4.

5.

2.1.2

CRS-03H, CRS-04H, SAMSORG14 (KSV-8), SAMSORG 40 (ICSV400), SAMSORG 41 (ICSV111), SAMSOR 44, SAMAORG 43, ZAUN-INUWA, EX-DAC. Seed dressing with Apron Star.

Plant population: 0.75 x 0.3m 2 plants per hill.

Tillage: minimum Tillage (use of herbicides) Vs Conventional.

Fertilizer application: Micro-dosing of organic and inorganic fertilizer.

B.

Mechanization: Hand planter, mechanized thresher, Stover crusher, stover chopper, motorized weeded (starting 2018).

C.

Processing: Pop-sorghum machines, Hammer mills, hammer with cyclone.

1.

Harvesting, threshing, cleaning and packaging of sorghum.

2.

Effective Sorghum drying techniques (i.e of Solar dryer).

3.

Storage of Sorghum grains and flour for enhanced shelf life.

4.

Production of Pop Sorghum.

5.

Production of Sorghum flour using hammer mill with Cyclone.

6.

Production of composite flour using Soybean flour and sorghum flour.

Technologies disseminated to rice farmers are: A. Good Agronomic Practices (GAP) This comprises the following: 1.

Variety selection and sources of seeds (Already selected varieties are Faro 44, Faro52, Faro 60 and Faro 61).

2.

Site/Land Preparation.

3.

Field Preparation.

4.

Seed Preparation.

5.

Determining planting season.

6.

Crop establishment (Direct seeding, nursery bed operations for transplanted rice, seed evaluation, transplanting.

7.

Weed management.

8.

Fertilizer application.

9.

Pests and Diseases control.

B.

Post-Harvest Technology 1.

Seed processing package and storage.

2.

Improved rice processing technology-use of Gem par boiler and rice cooking stove.

3.

Production of high quality rice flour.

4.

Production of rice flour based products (Rice, pancake, biscuit, chinchin, doughnut, short crust pastry, cake.

5.

Production of rice beverages (rice milk, porridge, noodles, Kununshinkafa).

6.

Production of extruded rice snacks (Rice/legumes snacks, noodles,

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cocktail bits, rice threads).

2.1.3

2.2

Technologies disseminated to Cassava farmers are: A. Good Agronomic Practices (GAP) This comprises the following: 1.

Varietal selection: The varieties transferred are TME 419, TMS 30572, TMS 98/0505, TMS 01/1368 and TMS 070539.

2.

Site Selection.

3.

Land Preparation.

4.

Plant Spacing/Population.

5.

Weed Management.

6.

Soil Fertility Management.

7.

Harvesting Market.

8.

Yield Assessment.

9.

Conservation of stems across off-season.

10.

Record keeping.

B.

Processing 1.

Processing of Cassava into garri.

2.

Processing of Cassava and starch.

3.

Production of Cassava chinchin and doughnut.

4.

Production of Cassava/bean crisp and eggroll.

C.

Nutrition and Health 1.

Improved infant and young child feeding practices (exclusive breastfeeding, complementary feeding).

2.

Production of complementary foods. (Rice and bambara nut mix, rice and beniseed groundnut mix, fermented millet, soyabeans and groundnut mix.

3.

Food fortification and Diversification Techniques.

4.

HIV/AIDs Awareness, prevention and management.

Demonstration Plots A demonstration plot/farm is a farm which is used primarily to demonstrate various improved agricultural techniques, with any economic gains being an added bonus.

Demonstration farms are often owned and operated by educational institution or government ministries. It is also common to rent land from a local farmer. The leaser is allowed to perform their demonstrations, while the land owner can be paid for the land usage or may be given the resulting crops.

Many demonstration plots not only have crops, but may also have various types of livestock. Various techniques for feeding and bedding are tested on these farms.

Demonstration farms run by universities are not only used for research, but are also used for teaching purposes.

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The one commonly used to disseminate proven technologies to farmers are on-farm demonstration plot, carried out by researchers on farmer's plot while allowing the farmers and other farmers in the village to observe the technologies so that they can pick up the technologies for their own use. In most cases, the harvested crops are left for the farmers after necessary data have been collected by researchers. It has been one of the methods adopted by the Program and the collaborative institutions to disseminate technologies to participating farmers as well as other non-participants in the areas of coverage.

2.3

Innovation Platform Innovation platforms are widely used in agricultural research to connect different stakeholders to achieve common goals.

An innovation platform is defined as 'a space for learning and change. It is a group of individuals (who often represent organizations) with different backgrounds and interests: farmers, traders, food processors, researchers, government officials etc. The members come together to diagnose problems, identify opportunities and find ways to achieve their goals. They may design and implement activities as a platform, or coordinate activities by individual members.'

Innovation platforms are particularly useful in agriculture because agricultural issues tend to be complex. They involve different biophysical, socioeconomic and political factors, and concern various formal and informal institutions. By bringing together stakeholders in various sectors and from different levels, innovation platforms may be able to identify and address common concerns more effectively. So, we could have innovation platform to solve problems with rice production, processing, input dealers, fabricators, and marketing in such a way that each aspect have stakeholders joining forces with others to address the totality of the problems around this crop. We can also have for cassava, sorghum and other crops.

Innovation platforms can be used to explore strategies that can boost productivity, manage natural resources, improve value chains, and adapt to climate change. Some innovation platforms focus on single issues; others deal with multiple topics.

2.4

Farmers Field Days The traditional role of field days and tours has been to introduce growers and agricultural professionals to new technologies and techniques so that the audience could see how these technologies or techniques could be practically used and applied. Based on this concept, the use of field days or tours to demonstrate the radically new technologies and site-specific management techniques behind precision farming is a perfect application of these tools. Indeed, a survey of precision farming field days held in a number of states found that field days were beneficial in showing growers and agricultural professionals global positioning systems, yield monitoring systems, techniques for grid soil sampling, software for geographic information systems, vehicle guidance systems, variable-rate Yield and Technology Adoption Survey

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application equipment, and a host of other technologies and processes. In particular, hands-on experiences, such as field demonstrations, guided sampling activities, and combine harvesting demonstrations are extremely well received and valuable. Indoor seminars featuring farmer panels, side-by-side software demonstrations, and demonstrations of geographic information systems have received high marks by participants. The survey found that a field day must be centered on a well-defined objective and a thorough understanding of the needs of the audience. Survey respondents unanimously agreed that precision farming field days and tours will be even more important as future advances in technology and management techniques are discovered.

However, future precision agriculture field days or tours must be coupled with other issues or topics where precision agriculture technologies can be used to solve a practical problem and enhance management practices. A field day may include events such as ploughing competitions not usually associated with shows due to the larger space required. The events are good sources of agricultural information, as organizers can arrange for guest speakers to talk on a range of topics.

2.5

Trainings Training is very important in all businesses including agriculture. The implementation of ATASP-1 involved training the participants including youths about all aspects of agriculture like site selection, land preparation, preparation of seeds for planting, planting, weeding, and in fact all good agronomic practices that needs to be followed to ensure that farmers get the best for his efforts. The current farmers under the Programs have been taught formally and practically and the training efforts are beginning to reflect in their performances as will be seen in results presentation in chapter 5.

2.6

Agricultural Research Institutes Supporting ATASP-I There are many international research institutions that have supported this Program.

These research institutions are: 2.6.1

The International Institute of Tropical Agriculture (IITA).

The International Institute of Tropical Agriculture (IITA) is one of the world's leading research partners in finding solutions for hunger, malnutrition, and poverty.

IITA is a non-profit international organization founded in 1967 and governed by a Board of Trustees. Its award-winning agricultural research for development (R4D) addresses the needs of the poor and vulnerable in the tropics. It works with public and private sector partners to enhance crop quality and productivity, reduce risk to producers and consumers, and generate wealth from agriculture.

The Institute's R4D covers the following themes: biotechnology and genetic improvement, natural resource management, plant production and plant health, and social science and agribusiness. For the last 45 years, IITA's agricultural R4D has delivered over 70 per cent of CGIAR impact in sub-Saharan Africa. It has

Yield and Technology Adoption Survey

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achieved this impact by focusing on key tropical food crops, such as banana and plantain, maize, cassava, soybean, cowpea, tree crops, and yam. With the mission to enhance food security and improve livelihoods through R4D, IITA tackles these challenges by pursuing these interrelated objectives: improving food security, increasing the profitability of foods and other agricultural products, reducing risks to producers and consumers, and helping national entities to expand agricultural growth. IITA is the prime contractor for the Program but AfricanRice and ICRISAT were also involved in the midwife of the Program.

IITA was additionally apart from its overall role providing the necessary assistant on cassava while AfricanRice was in charge of rice and ICRISAT was in charge of sorghum.

2.6.2

AfricaRice The Africa Rice Center (AfricaRice) is a leading pan-African rice research organization committed to improving livelihoods in Africa through strong science and effective partnerships. AfricaRice is a CGIAR Research Center – part of a global research partnership for a food-secure future. It is also an intergovernmental association of African member countries.

The Center was created in 1971 by 11 African countries. Today its membership comprises 26 countries, covering West, Central, East and North African regions, namely Benin, Burkina Faso, Cameroon, Central African Republic, Chad, Côte d'Ivoire, Democratic Republic of Congo, Egypt, Ethiopia, Gabon, the Gambia, Ghana, Guinea, Guinea Bissau, Liberia, Madagascar, Mali, Mauritania, Niger, Nigeria, Republic of Congo, Rwanda, Senegal, Sierra Leone, Togo and Uganda.

Recognizing the strategic importance of rice for Africa and the effective geographic expansion of the Center – which was constituted as the West Africa Rice Development Association (WARDA) in 1971 – its Council of Ministers took a historic decision in September 2009 to officially change its name to “Africa Rice Center (AfricaRice)” and to no longer refer to it as WARDA. Its mission is to contribute to poverty alleviation and food security in Africa, through research, development and partnership activities aimed at increasing the productivity and profitability of the rice sector in ways that ensure the sustainability of the farming environment.

The modus operandi of the Center is partnership at all levels. Its research and development activities are conducted in collaboration with various stakeholders—primarily the National Agricultural Research Systems (NARS), academic institutions, advanced research institutions, farmers' organizations, non-governmental organizations, and donors—for the benefit of African farmers, mostly small-scale producers, as well as the millions of African families for whom rice means food.

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AfricaRice headquarters is based in Côte d'Ivoire. Staff is located in Côte d'Ivoire and also in AfricaRice Research Stations in Benin, Ghana, Liberia, Madagascar, Nigeria, Senegal, Sierra Leone and Tanzania. African Rice is providing the needed support for rice in the Program.

2.6.3

ICRISAT The International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) is an international organization which conducts agricultural research for rural development, headquartered in Patancheru (Hyderabad, Telangana, India) with several regional centers in Bamako (Mali), Nairobi (Kenya) and research stations in Niamey (Niger), Kano (Nigeria), Lilongwe (Malawi), Addis Ababa (Ethiopia), Bulawayo (Zimbabwe)). It was founded in 1972 by a consortium of organizations convened by the Ford and the Rockefeller foundations. Its charter was signed by the FAO and the UNDP. Since its inception, host country India has granted a special status to ICRISAT as a UN Organization operating in the Indian Territory making it eligible for special immunities and tax privileges.

ICRISAT is managed by a full-time Director General functioning under the overall guidance of an international Governing Board. The current Director General is Dr. Jacqueline d'Arros Hughes. The current chair of the Board is Prof Chandra Madramootoo.

The Institute's R4D covers the following themes: biotechnology and genetic improvement, natural resource management, plant production and plant health, and social science and agribusiness. ICRISAT is providing the needed technical support for the sorghum component of the ATASP-1 program .

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CHAPTER

THREE 3.0

METHODOLOGY This chapter details the study area, study design and approach, method of data collection, sampling techniques, sample size, methods of data analysis and the tools employed.

3.1

Study Area The survey was implemented in the four SCPZs across the country. These zones are: Adani-Omor covering Anambra and Enugu States in the south east, Bida-Badeggi SCPZ in Niger State in the north central, Kano-Jigawa SCPZ and Sokoto-Kebbi SCPZ these two zones are located in the north western part of the country as shown in the Nigerian map. There is variation in climatic conditions across the zones with Adani-Omor located in the tropical rainforest in the South East, Bida-Badeggi located in the Guinea Savanna while Kano-Jigawa and Sokoto-Kebbi are located in the Sudan Savanna ecological zone of the country.

Figure 1 : ATASP-1 Map of the Program area in Nigeria Source: Agricultural Transformation Agenda Support Program Phase-1

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3.2

Study Design The study focused solely on the program beneficiaries in ascertaining the rates of yield and adoption of technologies disseminated to farmers of the three crops by ATASP-1 and this is complemented by focused group discussions in selected communities for fabricators and processors. A pre and mid-course no control design was also used to allow for the determination of the effect of adoption of good agronomic practices (GAP) on crop production and productivity.

3.3

Sampling Procedure and Sample Selection The multi-stage sampling procedure was used in selecting respondents for the study.

However, given the preponderance of production-based value chain actors for both yield and technology adoption. i.

Stage

Rapid Yield: The first stage is the selection of all the seven (7) states participating in the ATASP-1; the second stage is the selection of three (3) LGAs each from AdaniOmor, Bida-Badeggi and Kebbi-Sokoto Zone and five (5) LGAs from KanoJigawa Zones; the third stage is the selection of one (1) community/cluster from each of the sampled LGAs; lastly, the fourth stage is the selection of respondents from each of the sampled communities on crop basis; (i) Cassava: three (3) respondents from Adani-Omor, three (3) respondents for cassava each from Bida-Badeggi and Kano-Jigawa, (ii) Rice: six (6) respondents each from AdaniOmor andKano-Jigawa; while three (3) in Bida-Baddegi; and four(4) in KebbiSokoto; (iii) Sorghum: two(2) from Adani-Omor; three(3) from Bida-Badeggi; and seven(7) from Kano-Jigawa and five (5) respondents for Sorghum from Kebbi-Sokoto. Thus, a total of forty-five (45) respondents.

No. Sampled

I: State level 7 II: LGA level 14 III: Community/ Cluster level 14 IV: Respondents: Adani-Omor 11 Bida-Badeggi 9 Kano-Jigawa 16 Kebbi-Sokoto 9 TOTAL

Yield and Technology Adoption Survey

Total Zone Program 2 (1) 7 14 3 14 11 9 16 9 45

17

ii.

Technology Adoption: The first stage is the selection of all the seven (7) states participating in the ATASP-1; the second stage is the selection of five (5) LGAs in each of the Zones; the third stage is the selection of one (1) community/cluster from each of the sampled LGAs; lastly, the fourth stage is the selection of six (6) respondents from each of the sampled communities; thus, a total of thirty (30) respondents is to be drawn from each Zone; giving a total sample size of one hundred and twenty (120). Similarly, to ensure that other stakeholders were not left out of the study, 3 respondents each from processors and fabricators groups in each of the SCPZs making 6 per SCPZ and a total of 24 across the zones were included in the sample.

On the whole 96 farmers and a total of 24 fabricators were sampled.

Stage

No. Sampled

I: State level II: LGA level III: Community/ Cluster level IV: Respondents level

7 states 5 per zone 1 per LGA 6 per cluster (6/LGA)

S/N Description

Staple Crop Processing Zones (SCPZs) BidaKebbiAdani-Omor Kano-Jigawa Badeggi Sokoto 24 24 24

1

Farmers

2

Fabricators

3

3

3

Processors

3 30

Total

Total Zone Program 2 (1) 7 5 20 5 20 30 120

Total 24

96

3

3

12

3

3

3

12

30

30

30

120

3.4

Methods of Data Collection Data collection was through primary and secondary data. Primary data were solicited through the use of structured questionnaire. The questionnaires were administered to all value chain actors, comprising producers, processor and fabricators. Data collected covered value chain actors' background information, actors' specific details, institutional information, capacity building, input-output data, technologies disseminated, mode of practicing technology, rates of adoption and constraints to adoption of GAPs.

3.5

Method of Data Analysis Data collected were coded along the line of study objectives and analyzed using SPSS software. Objectives I, VI and VII were analyzed using content and descriptive analysis such as mean, frequency, standard deviation and count. Objectives II and III were analyzed using varied Likert type Scales, covering perception of usefulness of Yield and Technology Adoption Survey

18

technologies, extent of usage of adopted technologies, perception of processing and fabrication technologies and constraints limiting adoption of GAPs. The ratings of perception were: Agree =3, Not sure =2 and Disagree =1. Objective IV was realized through the use of before and after analysis while objectives V was achieved through the use of Logit model.

3.6

Model Specification Logit model was used to ascertain the factors influencing the adoption of good agronomic practices (GAP) among ATASP-1 farmers. The model is specified as follows

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19

Extension Visit

Access to Credit

Association Membership

96

96

96

96

96

96

96

96

Missing

0

0

0

0

0

0

0

0

0

0.307

0.435

5.08714

0.375

1.615

7.758

0.175

0.503

0.144

Std. Deviation

Marital Status

AGE

Education

96

Farm Size

N Valid

Statistics

Gender

Household Size

Standard Deviation

Logistic Regression Analysis Logit and Probit analysis produce similar results. In this case, Logistic Regression Analysis, also called Logit model, was used to ascertain the factors influencing the adoption of Good Agronomic Practices amongst ATASP-1 farmers (Objective ix). The adoption or non-adoption response is captured with a binary variable, coded 0 for not adopted; and 1 for adopted. In this analysis, GAP_ADOPTED is the dependent variable.

Gender and Marital Status variables are dichotomous, Age has been recoded into 3 groups (coded 1, 2, 3). Education is coded 1 to 6; while Household Size and Farm Size was treated as continuous. . . . . . . . . . . . . . . (2) The Binary Logisitic regression analysis which is accepted as robust against multivariate normality and better suitable for small sample size data than Probit model; and has similar output with Probit was used for the regression analysis. This study has a total sample of less than 100; precisely 96 for farmers. The coefficients of the model equation are as shown in the output table below. The dependent nominal variable is GAP_ADOTION (Not Adopted = 1; Adopted =2); and the covariates are GENDER, AGE, EDUCATION, HOUSEHOLD_SIZE, FARM_SIZE, EXTENSION_VISITS, ACESS_TO_CREDIT, and ASSOCIATN_MBR B GENDER AGE EDUCATION HHOLD_SIZE FARM_SIZE ENTENTN_VISITED CREDIT_ACCESS ASSOCIATN_MBR Constant

0.982 -2.18 -0.877 0.08 -0.056 0.199 1.226 1.235 2.136

Yield and Technology Adoption Survey

S.E. 0.962 0.812 0.252 0.049 0.051 1.73 0.584 1.659 4.758

20

Wald 1.04 7.201 12.105 2.636 1.231 0.013 4.409 0.554 0.202

df 1 1 1 1 1 1 1 1 1

Sig. 0.308 0.007 0.001 0.104 0.267 0.908 0.036 0.457 0.654

The first observation made on the output was the pseudo R2, the -2Log likelihood improvement, the minimization criteria used in SPSS. It was observed that the 2 2 Nagelkerke's R is 0.583 which indicates that the model is good. Cox and Snell's R in the th nth root (with this data set, 96 of the -2Log likelihood improvement). This can be interpreted as a 41.2% probability that the event of the covariates influencing the dependent variable (GAP Adoption), is explained by the Logit model. The classification result is at 80.2% which is good.

The output table above shows the variables in the model equation and the coefficients. It generates the regression function: . . . . . . . (3)

This table also shows the test of significance for each of the coefficients in the Logistic 2 regression model. Wald statistics (basically t or chi-square distributed with df = 1) has been used here instead of t-test because of the sample size for which the t-values may not be valid. As observed, AGE and EDUCATION are the most significant respectively at 7.2 and 12.1; while CREDT_ACCESS, HHOLD_SIZE, FARM_SIZE and GENDER are respectively at 4.4, 2.6, 1.2 and 1.04. However, as can be observed from the regression function (3) above, the other variables each exercises some influence, positive or negative at varying magnitudes as the dependent variable scales in step of 1. All these are non-zero influence in the model; which counts.

Weighted Average: Weighted average was also used in the analysis where found useful in obtaining a more accurate look at the set of data than the normal average; weighted average computation was used where doing so could improve the interpretation of how the mean of a subset in a dataset influenced others in the entire set. The general formula for calculating the weighted average is given in (4) below.

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CHAPTER

FOUR

4.0 4.1

Results and Findings: Socio-Economic Characteristics of the Farmers: The socio-economic characteristics of the farmers in the Program areas under study discusses the communal and pecuniary characteristics of farmers across the study areas over the three crops namely Cassava, Sorghum, and Rice. The issues conversed are age, gender, marital status, education, household size, farm size, structure and experience of respondents under ATASP-1, mode of acquisition of lands, land area devoted to crop cultivation (cassava, sorghum and rice), yields of rice, sorghum and cassava, years of experience in farming, extension contact by ATASP-1 participating farmers, farmers' participation in innovation platforms, demonstration plots and field day in the Program areas, credit information for the last cropping season, farmers' Association memberships, access to agricultural training, access to training on production, production information and lastly but the least inputs used in crop production. These variables are very important for good planning and decision making by policy makers and farmers too. The alignment of these variables can also brand or ruin the ability of various actors' effectiveness in production process.

4.1.1

Age distribution of respondents:

4.1.1.1 Rapid Yield: The farmers age grouping across the four Zones indicate that, all the farmers are mostly within the age bracket of 31-59 years with a total of 37 farmers at 82% nationally. BidaBadeggi and Kebbi-Sokoto Zones have the highest percentage each of 78% while for the age bracket ≤ 30 and ≥ 60 both have 2 farmers each at 22%, and in reality this signifies low production (i.e. yield) of the 3 commodities considering their population (counts), therefore there is the need to encourage people within these age brackets particularly those of the age bracket of ≤ 30 years in the Program area under the dry season cropping Yield and Technology Adoption Survey

22

to go into profitable agriculture in order to create wealth and employment. The summation of years of an individual attained in life was supposed to be a solid influence of the production capacity of that individual. This was an indication that, majority of the work force belonged to the age bracket of 31-59 years as shown below in Table 1: Farmers General Age Grouping by Zone. This incidence can be attributed that, the farmers within this age bracket will have advantage over the other 2 age brackets in terms of getting agricultural inputs, enjoying extension services etc. as there is strength in numbers. There is likelihood of the farmers within this age bracket to have reasonable years of farming experience by virtue of their ages (years).

Table 1: Farmers General Age Grouping by Zone Age of beneficiary

Below 30 Years 31 - 59 Years Above 60 Years

Adani-Omor Bida-Badeggi Kano-Jigawa

11 (100)

2 (22.22) 7 (77.78)

2 (12.50) 12 (75.00) 2 (12.50)

Kebbi-Sokoto

Global

7 (77.78) 2 (22.22)

4 (8.89) 37 (82.22) 4 (8.89)

Figures in parentheses are percentages

Figure 2 : Age of Beneficiary Farmers by Zone

4.1.1.2

Technology Adoption: The age structures of farmers across the three crops under ATASP-1 dry season farming are as presented in table 2 below. From the table below, 9 farmers were into cassava production with majority of them male farmers (6) within the age bracket of 31-59 with 66.7% achievement. The scenario was different in the case of Rice and Sorghum within the same age bracket 31-59 years with 14 male farmers at 82.4%.

However, the average age distribution by crop and gender was 37 years with 82% at global level. There was a fairly wide variation between the age distribution at the 4

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23

Zonal levels when compared with the national level by crops and by age groupings.

Furthermore, by implication 37 years was the average age grouping of respondents signaling that the Program has encouraged youth participation in food production as a business and this has a lot of significance for future food production and food security for the country. Also, looking at the farmers within 31-59 years age bracket, this means that if given the necessary technological support there is every possibility for them to improve and sustain food production as they are still strong and agile at this age grouping. In the whole, 45 farmers were found to be adopters across crops and SCP Zones. The significance of the mean age recorded for the Zones comes from the fact that farmers across the Zones are still at their active age of below 50 years and as such can still make meaningful contributions to agriculture and economic activities. The technologies disseminated to the farmers varies from crop to crop but in generally it was on improved seed variety, seed dressing, plant population, minimum tillage, fertilizer application, mechanization, site selection and weed management.

Table 2: Age Distribution of Farmers by Crops by Gender Age < 30

Cassava Female 1(11.1)

Rice Male 1(11.1)

31-59

6(66.7)

> 60

1(11.1)

Overall

1(2.2)

Female 2(10.5)

8(17.8)

2(4.4)

Figures in parenthesis are percentages

Figure 3 : Age distribution of farmers by crop by gender

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24

Sorghum Male

Male

1(5.3)

1(5.9)

15(78.9)

14(82.4)

1(5.3)

2(11.8)

17(37.8)

17(37.8)

4.1.2 Gender of Respondents: The gender of an individual influences the physical and the general production capabilities. Gender is equally believed to affect one's sphere of influence and social standing in some cultures.

4.1.2.1 Rapid Yield: The study shows that yields on plots managed by females are lower than those managed by males. This is not because females are worse farmers than males. Indeed, extensive evidence shows that females are just as efficient as males. They simply do not have access to the same inputs. If they did, their yields would be the same as men's, they would produce more and overall agricultural production would increase. From the Table 3 below, 18% of the male farmers were for cassava and 2% of the farmers were females at the national level. However, 38% of the males farmers were into Rice production and 4% were female farmers from the point of view of global figures obtained. For Sorghum the survey results indicate that, there were only male farmers at 100% in the absence of female farmers producing Sorghum. In the overall total results of gender disaggregation by crop by gender, Adani-Omor Zone has the highest count of female farmers at 2(4%) nationally, which can be attributed to the socio-cultural norms of the Zone where female gender has the right to venture into any economic activities of her choice. Also, worthy of note as an achievement of the ATASP-1 Program was the successful introduction of improved Sorghum varieties to Adani-Omor Zone which is now becoming an economically viable crop. Thus, this was an indication that, closing the gender gap in agriculture can improve agricultural productivity with important additional benefits through raising the incomes of female farmers, increasing the availability of food and reducing food prices, and raising women's employment and incomes.

Table 3: Gender distribution of Respondents (nos) Surveyed Zone

Cassava Female

Rice

Male

Sorghum

Female

Male

Male

2(10.5)

4(21.1)

2(11.8)

ADANI-OMOR

3(33.3)

BIDA-BADEGGI

3(33.3)

3(15.8)

3(17.6)

2(22.2)

6(31.6)

7(41.2)

421.1)

5(29.4)

KANO-JIGAWA

1(11.1)

KEBBI-SOKOTO Overall

1(2.2)

8(17.8)

Figures in parentheses are percentages

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25

2(4.4)

17(37.8)

17(37.8)

Figure 4 : Farmers gender distribution by zone

4.1.2.2 Technology Adoption: The survey attempted to assess whether female farmers are as productive as male farmers. The survey measured productivity in a variety of ways, but most commonly based on output per hectare of land, or yield, comparing yields on men's and women's farms which can reveal differences between the two groups; females typically achieve lower yields than males do. It attempted also to assess whether these differences were caused by differences in input use (improved seeds, fertilizers, tools and technologies or other factors such as access to extension services and education). The gender distribution of the farmers engaged in ATASP-1 Program, Table 4 below revealed that 75% of the male farmers were involved in cassava production, while 25% were females nationally.

Similarly, 49% of the male farmers were engaged in Sorghum production and 51% of the female farmers were also into Sorghum production. This indicates high participation of female farmers in Sorghum production than the male farmers. The story in the case of rice production, was quite different in that, there was high engagement of male farmers at 93% in rice production than the female farmers with only 8%, this can be attributed to the nature of rice production that requires extensive labour and its time consuming nature, where the female folks don't have the luxury of time as they are mostly engaged with the house chores. It is gratifying to note that, nationally the male farmers are more than the female farmers in counts with 158 and 62 respectively.

However, looking at the gender structure by SCPZ, 90% of male in Bida-Badeggi and 10% for female participated in the Program while it was 100% for male in Kano-Jigawa and 75% male and 25% female in Adani-Omor. The non-involvement of women in cassava production in Kano-Jigawa were possibly due to cultural-religious factor as well as the fact that the crop is relatively not as popular as grain crops where women are very much involved in their production and processing.

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26

On the other hand, the gender distribution showed that about 49% of those involved in sorghum production under the Program nationally are men while 51% are women.

Looking at it on zonal basis, it was 20% for men and 80% for female in Sokoto-Kebbi, 95% for men and 5% for women in Badeggi-Bida, 15 % for men and 85% for women in Kano-Jigawa and 65% for men and 35% for women in Adani-Omar. The result showed that there was heavy participation of women in the sorghum production under the Program than men in the north which is the traditional home for sorghum production.

For rice, in Kebbi-Sokoto SCPZ, only 10% of the adopters in rice are women while 90% are male, for Bida-Badeggi SCPZ, only 5% of rice participants are women while 95% are men. However, in Kano-Jigawa SCPZ, there were no women involved in rice production while in Adani-Omor, 15% of rice participating farmer are women while 85% are male.

The national outlook showed that 93% of total participating farmers are men while only 8% are women.

Table 4: Gender of Farmers' Household Head

Crop Enterprise Cassava Sorghum Rice Male 45(75) 39(48.75) 74(92.5) Female 15(25) 41(51.25) 6(7.5) Figures in parentheses are percentages Gender

Figure 5 : Farmers gender distribution by crop enterprise

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27

4.1.3 Marital Status of Respondents: 4.1.3.1 Technology Adoption: The distribution of technology adopters by marital status by crop by Zone as shown in table 5 below. In Adani-Omor out of the 24 Technology adopters 23 were married at 96% were into Cassava and the Single adopter at 4% was into Rice production, in BidaBadeggi, 100% of the 24 adopters were married and no single adopter. On the other hand, in Kano-Jigawa, 100% of the 24 adopters are married but in Kebbi-Sokoto out of the 24 technology adopters 20 adopters at 83% were married and were into rice production, one single at 4% was into Sorghum and 3 others at 13% who were into rice production. The display of the results of the distribution by marital status by crop and by Zone gave 96 for all as expected.

Table 5: Technology Adopters by Marital Status by Crop Zone Marital status Crops Cassava Sorghum Rice

ADANI-OMOR Married Single 23(96) 1(4)

BIDA-BADEGGI Married 24(100)

KANO-JIGAWA Married 24(100)

KEBBI-SOKOTO Married Single Others 20(83.3) 1(4.2) 3(12.5)

24(100)

1(100)

23(75) 1(25)

17(100)

19(86.4)

3(13.6)

Source: June, 2020 Field Data 4.1.4 Educational Level of Respondents: 4.1.4.1 Technology Adoption: The results of the survey indicate that, those household heads with the higher education were those who adopted most of the technologies disseminated on rice, sorghum and cassava crop enterprises. Looking at the Table 6 below, it shows that, out of the 95 households interviewed, 31% of them had Senior Secondary education with 29 household heads in this category, 26% of the household heads had Tertiary education with 25 household heads, then 17% of the household heads had Primary education with 16 household heads, 3% of the household heads had Junior Secondary School in 3 households while 21% of the household heads had Quaranic education in 20 households and 1% of the other household heads had either no formal or informal education in only one household.

In terms of crop enterprise technology adoption, 34% each of the household heads with Junior and Senior secondary education were found to adopt the rice technologies deployed in 17 households each, 31% of the household heads with Quaranic education adopted the Sorghum production technologies in 10 households while 31% of the household heads with Senior Secondary education adopted the cassava production technologies in 4 households. Generally speaking, there was a relationship in the level of technology adoption with the level of education of household heads. This is also in context with one of the most important benefits of education is that it improves personal lives and helps the society to run smoothly.

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Table 6: Highest Education of Household Heads by Crop Enterprise Crop Junior Senior None Quaranic Primary Tertiary Others Total Enterprise Sec Sch Sec Sch Rice 0 7 6 2 17 17 1 50 0% 14% 12% 4% 34% 34% 2% Sorghum 1 10 8 0 8 5 0 32 3% 31% 25% 0% 25% 16% 0% Cassava 0 3 2 1 4 3 0 13 0% 23% 15% 8% 31% 23% 0% Total 1 20 16 3 29 25 1 95 1% 21% 17% 3% 31% 26% 1% 100%

Source: June, 2020 Field Data 4.1.5

Farm Size, structure and experience of Respondents under ATASP-1

4.1.5.1a Rapid Yield- Farm Size: The size of land used in farming plays very important role in the yield performance from the crops per hectare based on the technologies disseminated to the farmers to increase productivity of all the 3 crops in the program under the dry season farming. Farm dimension affects spacing of the crops and so also the crops population per hectare, the structure and the knowledge of the farmer. Table 7a below presents the survey results on farm sizes (Ha) for the farmers across the SCPZ on all the 3 crops (Cassava, Rice and Sorghum) in the program. The farmers average crop farming land size in Adani-Omor Zone for Cassava was 1Ha, for Rice was 1.33Ha and Sorghum 1.25Ha, while in BidaBadeggi Zone the farmers average crop farming land size was 2.57Ha for Cassava, for Rice 2.21Ha and Sorghum 1.58Ha; Kano-Jigawa Zone was 0.36Ha for Cassava, 0.73Ha for Rice and 1.65Ha for Sorghum. There was no respondent in Kebbi-Sokoto Zone for Cassava as the Program does not promote the cultivation of Cassava in the Zone but for Rice was 0.93Ha and for Sorghum was 1.63Ha. The average farmland size cultivated across the 4 Zones under the dry season farming for the 3 commodities (Cassava, Rice and Sorghum) overall indicated that, Cassava has 20,00%, Rice 42.22% and Sorghum has 37.78% meaning that, the average farmland size in percentage that was put into cultivation among the 3 crops in focus Rice has the highest percentage, followed closely

by Sorghum at 37.78%; and Cassava was at 20.00%, the minimum. This development could be in order of importance attached to the crops by the farmers because of their economic value. Farm structures are those buildings, facilities and equipment used for farming operations.

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Table 7a: Farmers Average Crop Farming Land Size by Zone – Rapid Yield Statistics

ZONES ADANI-OMOR BIDA-BADEGGI KANO-JIGAWA KEBBI-SOKOTO

Rice Cultivation N 6 Minimum 1.00 Maximum 3.00 Mean 1.33 Estimated 8.00 Sorghum Cultivation N 2.00 Minimum 1.00 Maximum 1.50 Mean 1.25 Estimated 2.50 Cassava Cultivation N 3 Minimum 1.00 Maximum 1.00 Mean 1.00 Estimated 3.00 Overall 13.50 24.4%

3 1.87 2.88 2.21 6.63

6 0.37 1.67 0.73 4.38

4 0.43 1.45 0.93 3.73

3.00 1.00 2.23 1.58 4.73

7.00 0.55 4.96 1.65 11.57

5.00 0.60 2.80 1.63 8.15

3 1.50 3.80 2.57 7.70 19.06 20.0%

3 0.28 0.45 0.36 1.09 17.03 35.6%

11.88 20.0%

Total 42.22% 19 0.37 3.00 1.20 22.73 37.78% 17.00 0.55 4.96 1.59 26.95 20.00% 9 0.28 3.80 1.00 8.96 45 100%

Source: June, 2020 Field Data 4.1.5.1b Rapid Yield -Years of Experience in Farming: The suitability and adoption of interventions depends on a variety of socioeconomic factors and these factors are influenced by the years of experience of the farmer. A Farmer's years of experience in farming also influence choices of action on other factors such as, soil management and plant spacing, seed quality and fertilizer application which are key points factors in technology adoption that results in increased crop yield. The absence of the above factors acts as major barrier in technology adoption and market innovations that improve farmers' income. Years of experience in farming has impacts on skill sets required for decision making and the overall level of adoption of technology. This more years of experience by the farmers also indicates the level of resilience demonstrated and the likely capacity gaps that requires timely intervention.

The table 8 below shows the summary of Farmers' years of experience in crop production across the 4 zones by respondents in the SCPZ. The survey shows that the minimum years of experience across the 3 crops are Cassava 3 years, Rice and Sorghum 2 years respectively. All these minimum years of experience were obtained from Adani-Omor zone, except for Cassava which was from Kano-Jigawa zone. Further, the maximum years of experience across the 3 crops are 40 years for Cassava and Rice while it was 45 Yield and Technology Adoption Survey

30

years for Sorghum. Similarly, all the maximum yields from the 3 crops were obtained from Kano-Jigawa zone for Cassava and Rice while that of Sorghum was obtained from Kebbi-Sokoto Zone.

Table 8: Experience of Respondents in Crop Production (Years) Minimum (Yrs.) Zone

State

Cassava

Rice

Adani-Omor

Anambra

16

2

Enugu

Kano-Jigawa

2

2

10

7

10 3 3

2

10

15

20

7

10

15

20

3

40

9 9

4 3

40

Kebbi

10

Sokoto

40 10 2

2

Kano Kano-Jigawa Total Kebbi-Sokoto Kebbi-Sokoto Total Grand Total

35 35

Jigawa

16

22

Sorghum

22

Bida-Badeggi Total

2

Rice

2

Niger

20

Cassava

25

Adani-Omor Total Bida-Badeggi

Sorghum

Maximum (Yrs.)

3

Average Experience (Yrs.) Cassava

Rice

18

21

Sorghum

23

2

18

22

2

15

13

13

12

20

15

13

13

12

40

30

16

30

16

20 40

35 35

16

14 22

16 16

25

21

45

17

37

30 25

40 40

32 45

40 23

31 34

40

45

21

19

40

16

Source: June, 2020 Field Data Further findings from the survey shows that the minimum average years of experience across the 4 zones from the 3 crops was 2 years from the Sorghum crop in Adani-Omor and the maximum average years of farming experience was from Rice crop with 40 years farming experience from Kebbi-Sokoto zone. Specifically, the most experienced farmers from each zone according to the State is from Kebbi state for the Sorghum with 45 years farming experience. This was followed by 40 years farming experience from Sokoto State on the Rice crop and 40 years from Kano-Jigawa zone from Cassava crop in Jigawa state respectively.

The higher the level of farming experience is considered to positively influence technology adoption and participation in farming innovation activities. Farmers experience broadens the capacity of the farmer to learn and apply new skills and technologies for improved yield.

4.1.5.2 Technology Adoption: The outcome of this study shows that, the average years of experience of the farmers plays an important role in the cropping enterprise in technology adoption. The farmers' years of experience affects his knowledge in the use of available technologies, management strategies and techniques to increase productivity of all the 3 crops grown under the dry season farming. The Table 9 below describes the average years of experience of the farmers in terms of adoption of the technologies deployed by the Program during the period under review. where the mean years of experience in the adoption of Rice technologies in Adani-Omor Zone was 22 years, Sorghum was also 2 Yield and Technology Adoption Survey

31

years but for Cassava it was 22 years. The mean years of farming experience in BidaBadeggi Zone for Rice was 10 years, for Sorghum was 12 years and Cassava was 13 years. For Kano-Jigawa Zone the mean years of farming experience was 17 years for Rice, 16 years for Sorghum and 15 years for Cassava. In Kebbi-Sokoto Zone for Rice, 23 years and Sorghum 16 years and there was Zero years for Cassava in the zone meaning the Program has not supported the production of Cassava. This was a clear indication that, the mean years of farming experience across the Zone at the national level was encouraging and a good development for increase productivity and production following the GAP technology disseminated.

Table 9: Lead Farmers Average Years of Cropping Experience by Zone Crop Production Mean Years of Experience Rice Sorghum Cassava

ZONE ADANI-OMOR

N

6

2

1

21.5

2

22

Minimum

2

2

22

Maximum

35

2

22

Mean

BIDA-BADEGGII

N

2

3

2

9.5

12.3

12.5

Minimum

7

10

10

Maximum

12

15

15

6

6

3

17

16.2

15

Minimum

1

3

1

Maximum

40

35

40

4

4

22.8

16

Minimum

10

1

Maximum

40

32

N

18

15

6

18.9

13.5

15.33

Minimum

1

1

1

Maximum

40

35

40

Mean

KANO-JIGAWA

N Mean

KEBI-SOKOTO

N Mean

Overall

Mean

Source: June, 2020 Field Data

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Figure 6 : Crop production mean years of experience by zone

4.1.6 Mode of acquisition of the Land: 4.1.6.1 Technology Adoption: Access to farm land is prime among the requirements for farming; and is obviously one of the determinants of how successful; or big a farmer can get. It wouldn't be out of place to link farm size to mode of acquisition. In this study, the major modes of acquisition covered were inheritance, purchase, rent, lease and gift. From table 10 below, responses from the farmers surveyed for the 3 crop enterprises show that for Cassava, 64% affirmed inheritance was mode of farmland acquisition; 7.1% purchase; and 14% each claimed rent and lease. While for Rice, 59.2% affirmed inheritance was mode of farmland acquisition; 8.2% purchase; 25% rent; and 4.1% each claimed lease and gift. For Sorghum, 78.1% affirmed inheritance was mode of farmland acquisition; 9.4% purchase; 6.3% each for rent and lease. The results show that farmland acquisition was predominantly by inheritance at a high 78% for Sorghum; followed close by 64.3% for Cassava; and for Rice at 59.2%. Gift of farmland was captured for only Rice at 4.1%.

Expenses incurring mode of farmland acquisition generally show relatively low percentages; with Rice indicating the maximum at 24.5%; while others range from 4.1% to 14.3%.

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Table 10: Mode of Acquisition of Land GLOBAL N Percentage

Mode of Acquisition Cassava Plot Acquisition Mode Inheritance Purchase Rent Lease Rice Plot Acquisition Mode Inheritance Purchase Rent Lease Gift Sorghum Plot Acquisition Mode Inheritance Purchase Rent Lease Source: June., 2020 Field Data

9 1 2 2

64.3% 7.1% 14.3% 14.3%

29 4 12 2 2

59.2% 8.2% 24.5% 4.1% 4.1%

25 3 2 2

78.1% 9.4% 6.3% 6.3%

4.1.7 Rapid Yield: Rice Technology has been a significant driver of yield improvement in rice production in Nigeria. Table 11 below shows the summary of rice average yield across the 4 zones (mt/ha) by respondents in the SCPZ. The overall, Rice yield was 6.12 mt/ha, with female respondents recording yields of 4.64 mt/ha and male respondents recording 6.30mt/ha respectively. This shows marginal increase of 1.66 mt/ha above the previous yield of 5.36 mt/ha. Overall, Kebbi-Sokoto had the highest yield of 6.53mt/ha, Kano-Jigawa had 6.12mt/ha, Adani-Omor recorded 6.06mt/ha while Bida-Badeggi recorded the lowest yield of 5.54mt/ha. This increased performance is a positive indicator that the participants in the survey have increased the use of the technology.

Table 11: Summary of Rice Average Yield Across the Zones (mt/ha) Zone Adani-Omor Adani-Omor Total Bida-Badeggi Bida-Badeggi Total Kano-Jigawa Kano-Jigawa Total Kebbi-Sokoto Kebbi-Sokoto Total Overall

State Anambra Enugu Niger Jigawa Kano Kebbi Sokoto

Female 4.64 4.64 4.64

Male 5.04 8.49 6.76 5.54 5.54 7.84 4.57 6.21 6.66 6.13 6.53 6.30

Source: June., 2020 Field Data Yield and Technology Adoption Survey

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Overall 4.84 8.49 6.06 5.54 5.54 7.84 4.57 6.21 6.66 6.13 6.53 6.12

The survey results also showed that Rice yield from Adani-Omor SCPZ female respondents was 4.64mt/ha and the male respondents recorded 6.76mt/ha, the zone also recorded the highest yield of 8.49mt/ha from Enugu state. There was no female respondent from the Bida-Badeggi SCPZ while the Rice yield recorded by male respondents was 5.54mt/ha. The record from Kebbi-Sokoto SCPZ showed a yield of 6.53mt/ha with no female respondent from the zone. The Rice yield recorded from KanoJigawa SCPZ showed 7.84 mt/ha from Jigawa state and the lowest yield of 4.57mt/ha from Kano state but the overall yield performance from the SCPZ was 6.53mt/ha.

4.1.8 Yield: Sorghum Sorghum crop plays huge role in food security, livelihood development, and thus requires sustainable technology innovation that is more sustainable in adoption. The participation of the farmer respondents contributes to achieving this goal towards improved yield performance by the respondent in the ATAPS-1 survey innovation and sustainability. The table 12 below shows the summary of average yield across the 4 zones (mt/ha) on Sorghum crop by respondents in the SCPZ. The overall, average Sorghum yield was 1.68 mt/ha, with no female respondent. This shows marginal decline of 0.17 mt/ha below the previous year's yield of 1.51mt/ha. The lowest and highest yield from the survey was from Kano-Jigawa with 0.50mt/ha (Jigawa State) and the highest of 2.45mt/ha from the same SCPZ. Further comparison of the yield performance with previous year also shows that the lowest yield in the previous year was 0.18mt/ha while the lowest yield in the current survey was 0.50mt/ha showing a marginal increase of 0.32mt/ha above previous year's record. Overall zonal result shows that, Kebbi-Sokoto had the next highest yield of 2.07mt/ha, with Kebbi State recording a yield of 2.30mt/ha and Sokoto State 1.72mt/ha.

Bida-Badeggi recorded the low yield of 1.50 mt/ha while Adani-Omor recorded the lowest yield of 1.17mt/ha.

Table 12: Summary of Sorghum Average Yield Across the Zones (mt/ha) Zone Adani-Omor Adani-Omor Total Bida-Badeggi Bida-Badeggi Total Kano-Jigawa Kano-Jigawa Total Kebbi-Sokoto

State Enugu

Male 1.17 1.17 1.50 1.50 0.50 2.45 1.62 2.30 1.72 2.07 1.68

Niger Jigawa Kano Kebbi Sokoto

Kebbi-Sokoto Total Overall

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Overall 1.17 1.17 1.50 1.50 0.50 2.45 1.62 2.30 1.72 2.07 1.68

The survey results also showed that Sorghum yield across the SCPZ had no female respondents. This study shows a need to consider more innovative approaches towards the improvement of Sorghum technology adoption to increase farmers' interest in the crop. This low yield performance may be attributed to lack of adequate attention to the expectations of farmers. Farmers expectations needs to be understood considering demographic growth, rapid urbanization and climate change and type of technology to increase Sorghum productivity and in turn, food security and incomes of small farmers.

4.1.9 Rapid Yield: Cassava Cassava yield improvement requires consistent adoption of technologies such as pestand disease-resistant varieties, storage facilities, cassava planting month, the number of months keeping the cassava in the field, fertilizer investments. Also, the expected improved Cassava yield due to adoption of new technologies stimulates the market operators to recognize the preferences of farmers and consumers on certain technology.

The knowledge of the preferences will enable ATASP-1 Program to adapt and adopt to the farmers' needs and thus the technology and innovation adoption rates are supposed to be higher. Considering the continued stagnation in yield productivity, these have not reached the desired effect. The Cassava data was collected in Kano-Jigawa, BidaBadeggi and Adani-Omor SCPZ only with no respondent from Kebbi-Sokoto SCPZ. The table 13 below shows the summary of Cassava average yield across the 4 zones (mt/ha) by respondents in the SCPZ. Table 13: Summary of Cassava Average Yield Across the Zones (mt/ha) Zone Adani-Omor Adani-Omor Total Bida-Badeggi Bida-Badeggi Total Kano-Jigawa Kano-Jigawa Total Grand Total

State Anambra

Female

Niger Jigawa

35.71 35.71 35.71

Male 34.67 34.67 33.06 33.06 33.54 33.54 33.78

Overall 34.67 34.67 33.06 33.06 34.27 34.27 34.00

Source: June., 2020 Field Data

The overall average, Cassava yield was 34.00 mt/ha, with female respondents recording average yields of 35.71 mt/ha and male respondents recording average yields of 33.78mt/ha respectively. The data further shows that female respondents recorded better yield performance with 1.93mt/ha above the male respondents. This shows marginal increase of 2.08 mt/ha above the previous yield of 17.21mt/ha. The overall zonal yield performance shows that Kano-Jigawa had the highest yield of 35.71mt/ha, Adani-Omor recorded 34.67mt/ha while Bida-Badeggi recorded the lowest yield of 33.06 mt/ha.

Comparative review with previous year's report shows a marginal decline in the overall yield performance for Cassava by 1.2mt/ha from a high of 35.2mt/ha in the previous year to 34.0mt/ha in the current year. Also, the highest average yield in the previous year was from Adani-Omor SCPZ with a highest average of 28.7mt/ha this contrast with the recent Yield and Technology Adoption Survey

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year report of 35.71 mt/ha from Kano-Jigawa SCPZZ and the lowest average yield of 15.3mt/ha from Kano- Jigawa zone in the previous year while the current year result shows the lowest yield of 33.06mt/ha from Bida-Badeggi SCPZ. There was no female respondent from the Bida-Badeggi and Adani-Omor SCPZ. The Cassava yield recorded from Kano-Jigawa SCPZ showed that from Jigawa state the overall yield performance from the SCPZ female respondents was higher than yield performance from the male respondents.

4.1.10 Technology Adoption: Extension contact by ATASP-1 participating farmers The average number of extension contacts conducted by ATASP-1 across the 4 Zones was 16 times based on the survey results under the dry season farming. Adani-Omor Zone had 24 visits with a mean of 3, minimum of 1 and maximum of 10 visits. Bida-Badeggi Zone had 21visits with a mean of 3, minimum of 2 and maximum of 14 visits. For KanoJigawa Zone had 8 visits with a mean of 4, minimum of 2 and maximum of 16 visits.

While for Kebbi-Sokoto Zone had 12 visits with a mean of 3, minimum of 1 and maximum of 6 visits. However, looking at the global outcome which has the total visits of 65, mean of 4, minimum of 1 and maximum of 16 visits. To facilitate the development of the agricultural production in the Program, extension service contact is a sine qua non.

Extension services contacts supports initiatives of the Program under the dry season farming by putting a larger degree of the intervention agenda to provide expertise in the field see table 14 below: Table 14: Average Number of Extension Services Visits by Zone by State ZONE ADANI-OMOR

BIDA-BADEGGI KANO-JIGAWA

KEBBISOKOTO

Total

Average No of Extension Service Visits N Mean Minimum Maximum Median ANAMBRA 9 2.22 1 4 2 ENUGU 15 4.07 1 10 4 Total 24 3.38 1 10 3 NIGER 21 4.38 2 14 3 Total 21 4.38 2 14 3 JIGAWA 7 6.86 2 16 4 KANO 1 2 2 2 2 Total 8 6.25 2 16 3.5

% of Total N 13.8% 23.1% 36.9% 32.3% 32.3% 10.8% 1.5% 12.3%

KEBBI SOKOTO Total ANAMBRA ENUGU JIGAWA KANO KEBBI NIGER SOKOTO Total

15.4% 3.1% 18.5% 13.8% 23.1% 10.8% 1.5% 15.4% 32.3% 3.1% 100.0%

STATE

10 2 12 9 15 7 1 10 21 2 65

3.5 2.5 3.33 2.22 4.07 6.86 2 3.5 4.38 2.5 4.05

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37

6 4 6 4 10 16 2 6 14 4 16

3.5 2.5 3.5 2 4 4 2 3.5 3 2.5 3

4.1.11 Farmers' participation in innovation platform (IP), demonstration plots and field day in the Program areas.

The participation of farmers in innovation platform under the facilitation of the Program was an excellent move in bringing the relevant stakeholders under the same roof for their economic mutual benefit. This is where primary and secondary stakeholders were brought together due to the increasing need for growth and change also provides a great deal of opportunity for viable agribusinesses. Therefore, the Table 15 below indicates the level of participation of the farmers where 24 farmers participated in the innovation platform 23 at 96% said yes and only one at 4% said no to participate in IP in Adani-Omor Zone. In Bida-Badeggi Zone, the story was different as those who said yes to the participation of IP were almost equal to those who said no to the participation of the IP out of the 23, 14 at 61% said yes while 9 said no. Kano-Jigawa Zone with 24 participants out of which 14 said yes and 9 said no. While in Kebbi-Sokoto Zone, 23 participants were recorded out of which are almost formation of 11 said yes and 12 said striking almost a balance in the participation, this can be attributed to the nature of the formation of IP in any setting.

Table 15: Participation in Innovation Platform by Zone ZONE Adani-Omor Bida-Badeggi Kano-Jigawa Kebbi-Sokoto

Count Count % of Total Count % of Total Count % of Total part Count % of Total part

Participated in Innovation Platform No Yes 1 23 4.2% 95.8% 9 14 39.1% 60.9% 10 14 41.7% 58.3% 12 11 52.2% 47.8%

Total 24 100.0% 23 100.0% 24 100.0% 23 100.0%

The level of participation of the Program farmers in the demonstration plots under the dry season farming was impressive and encouraging as most of the farmers that participated in the intervention responded in the assenting were 87 and only 8 were dissenting see Table 20 below. In Adani-Omor Zone 24 at 100% accepted to participate in the demonstration plot and no respondent who did not participate in the Zone. In BidaBadeggi Zone there were 23 respondents out of which 21 at 91% said Yes, they are willing to participate in the demonstration plots trial and only 2 at 9 % of them that said No to participation in demonstration plots trial. There was a total of 24 participants in KanoJigawa Zone but 22 at 92% said yes and 2 at 8% said no to the participation in the demonstration plots conducted. Kebbi-Sokoto Zone has 24 participants in all, 20 at 83% said yes while 4 at 17% said no to participation in demonstration plots trial. It should be noted that, demonstration plots was to demonstrate the value and importance of new or improved varieties of crops, soil management practices and climate adaptability to the 3 crops under review.

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Table 16: Participated in Demonstration Plot by Zone ZONE Adani-Omor Bida-Badeggi Kano-Jigawa Kebbi-Sokoto

Participated in Demonstration Plot No Yes 24 100.0% 2 21 8.7% 91.3% 2 22 8.3% 91.7% 4 20 16.7% 83.3%

Total 24 100.0% 23 100.0% 24 100.0% 24 100.0%

Farmer field days (FFD) were conducted to showcase the potentials of the 3 crops in question on the farmers' plot. The results of the survey show that, 95 field days were conducted both green and brown field days. In Adani-Omor Zone a total of 24 FFD was conducted with the same number accepting to participate in the FFD, Bida-Badeggi Zone conducted 23 FFD and 22 at 96% of the farmers accepted to participate but one farmer at 4% did not participate. In Kano-Jigawa all of the 24 farmers at 100% participated in the FFD, while in Kebbi-Sokoto Zone out of the 24 farmers recorded 23 at 96% participated in the conduct of the FFD the remaining one farmer did not participate. Table 17 below provide the details.

Table 17: Participated in Farmers' Field Day (FFD) by Zone ZONE Adani-Omor Bida-Badeggi Kano-Jigawa Kebbi-Sokoto

Participated in Farmers Field Day No Yes 24 100.0% 1 22 4.3% 95.7% 24 100.0% 1 23 4.2% 95.8% 2 93

Total 24 100.0% 23 100.0% 24 100.0% 24 100.0% 95

Source: June, 2020 Field Data

4.1.12 Credit information for the last cropping season There are several reasons why agricultural credit assists farmers in bringing their products to market. Credit is needed in every type of business and agriculture is no exception. The need for agriculture credit becomes more important when it moves from traditional agriculture to modern agriculture. The capacity of farmers to save and invest is very low. The agricultural productivity is low due to low use of inputs. The farmers, therefore, need credit to increase productivity and efficiency in agriculture. This need is increasing over the years with the rise in use of fertilizers, mechanization and rise in prices. Therefore, access, ease, nature, and source of credit to farmers revealed that, as

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part of the findings, that agricultural credit is an important factor determining growth of agricultural production and development. However, given the short-term nature of credit provision of the banking system, in the face of long gestation period for agricultural production leaves much to be desired. The source of credit to farmers in the Program area expectedly would have come from a credit program, Commercial Bank, NGO, Trader, Agricultural Bank, family and friends, and other sources. The Table 18 below shows that, there were 17 farmers that, benefitted from one source of credit to the other. Six (6) at 35% farmers benefitted from a credit program either by Government or Agencies, 10 at 59% got a credit from families and friends and only one farmer obtained a credit from a cooperative association. Whether credit required was got or not, what was the credit needed for and the amount determines the efficiency and effectiveness of the credit to the farmer.

Table 18: Credit Source by Zone Source of Credit Credit Program 6 100.0% 35.3%

Com. Bank

Coop 1 100.0% 5.9%

NGO

Trader

Agric Bank

Family and Friends 10 100.0% 58.8%

Total Others 17 100.0% 100.0%

Source: June, 2020 Field Data

It is also important, to note the credit used in the production of the 3 crops. For rice production 12 farmers at 86% obtained credit, for Sorghum 8 farmers at 86% while for Cassava the only 4 farmers at 100% captured have no access to credit.

Table 19: Access to Credit for Crop Production Crop Enterprise Rice

Sorghum

Cassava

Access to Credit for Rice No Yes 2 12 14.3% 85.7% 100.0% 100.0% 14.3% 85.7% 3 5 37.5% 62.5% 100.0% 100.0% 37.5% 62.5% 4 100.0% 100.0% 100.0%

Count Count % within STATE % within Access to Credit % of Total Count % within STATE % within Access to Credit % of Total Count % within STATE % within Access to Credit % of Total

Source: June, 2020 Field Data

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Total 14 100.0% 100.0% 100.0% 8 100.0% 100.0% 100.0% 4 100.0% 100.0% 100.0%

The table 20 below gives the comparison of the mean credit required and received by State by the dry season farmers where the minimum credit requirement for Adani-Omor Zone (Enugu State) was N 70,000 but only N 40,000 was received, the maximum credit required was N 200,000 but only N 70,000 was received. Bida-Badeggi Zone (Niger State), the minimum credit requirement was N 50,000 but only N 30,000 was received.

In Kano-Jigawa Zone, the minimum credit requirement was N 30,000 and N 50,000 but the same amount was received while the maximum credit requirement of N 200,000 and maximum received was N 160,000 during the period under review. In Kebbi-Sokoto Zone, the minimum mean credit requirement was N 27,000 and the same amount was received.

Table 20: Lead Farmers Mean Credit Required Against Mean Credit Received by State Mean Credit Required

STATE ENUGU

JIGAWA

KANO

KEBBI

NIGER

SOKOTO

Total

N Mean Minimum Maximum N Mean Minimum Maximum N Mean Minimum Maximum N Mean Minimum Maximum N Mean Minimum Maximum N Mean Minimum Maximum N Mean Minimum Maximum

Mean Credit Received

5 174,000.00 70,000.00 200,000.00

5 60,000.00 40,000.00 70,000.00

6 75,833.33 30,000.00 200,000.00

5 71,000.00 30,000.00 150,000.00

4 137,500.00 50,000.00 200,000.00

4 115,000.00 50,000.00 160,000.00

11 148,545.45 27,000.00 318,000.00

11 290,818.18 27,000.00 2,100,000.00

16 212,500.00 50,000.00 1,000,000.00

16 121,250.00 30,000.00 300,000.00

6 35,000.00 15,000.00 100,000.00

6 35,000.00 15,000.00 100,000.00

48 148,312.50 15,000.00 1,000,000.00

47 137,531.91 15,000.00 2,100,000.00

4.1.13 Farmers' association membership The membership of the farmers in various farmers association across the Zone was encouraging based on the proliferation of the associations a total of 92 Associations was recorded in Adani-Omor Zone, the minimum participation in farmers Association was 1 and maximum of 10 participation. Kano-Jigawa Zone has minimum of 4 and maximum of 20, Kebbi-Sokoto has minimum of 1 and maximum of 15 membership participation.

The table 21 below gives the details.

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Table21: Farmers Years of Participation in Farmers Association by Zone STATE ANAMBRA ENUGU JIGAWA KANO KEBBI NIGER SOKOTO Total

Farmers Years of Participation in Association N Mean Minimum Maximum 9 2.67 1 5 15 4.4 1 10 13 6.92 3 15 10 9.6 4 20 17 7.59 2 20 22 5.68 1 15 6 5.67 1 14 92 6.13 1 20

Source: June, 2020 Field Data

4.1.14 Access to agricultural training The survey results indicate that, 94 farmers received training on various production technologies out of 23 farmers received the training in Adani-Omor and 1 did not participate, all the 23 farmers in Bida-Badeggi Zone participated in capacity enhancement, while in Kano-Jigawa 23 farmers participated with 1 farmer not participating. All the 23 farmers in Kebbi-Sokoto Zone participated in the capacity building activities conducted by the Program as shown in the table 22 below.

Table22: Lead Farmers had Production Training by Zone

Zone Adani-Omor

Bida-Badeggi

Kano-Jigawa

Kebbi-Sokoto

Count Count % within Production Training % of Total Count % within Production Training % of Total Count % within Production Training % of Total Count % within Production Training % of Total

Had Production Training No Yes 1 23 100.0% 4.2%

1 100.0% 4.2%

2

Source: June, 2020 Field Data

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Total 24

100.0% 95.8% 23

100.0% 100.0% 23

100.0% 100.0% 23

100.0% 100.0% 24

100.0% 95.8% 23

100.0% 100.0% 23

100.0% 100.0% 92

100.0% 100.0% 94

4.2

Technology Disseminated to Farmers Under this Program, there are innovation packages with proven effectiveness to enhance farmers' productivity; it could be to reduce drudgeries, boost natural resources, increase farmers sales advantage, and for several others developed to modernize farming activities, such are the ones refer to as technologies. A number of these relevant technologies were selected, well-rehearsed by ATASP-1's Extension Agents (EAs) and were purposely imparted on the respondents (farmers, fabricators and processors) for targeted results. That is, to facilitate the achievement of the Program objectives of substantially improving outputs so as to alleviate poverty and ensure food security in the country. The technologies disseminated on each crops are presented below:

4.2.1

Technologies disseminated on cassava The survey was carried out in three zones out of the four; this might have been due to agro-ecological dictates or scheduling of the pilot Program in manageable phases. The Table 23 below presents technologies disseminated to farmers on cassava by the program. Technologies disseminated to enhance improved productivity in cassava production are the introduction of improved varieties which all the cassava farmers claimed they are aware of. Others are site selection with full awareness by all, land preparation also known to all, 93% accepted awareness of plant spacing/population., weed management known to all the farmers in the project, soil fertility also known to 100% of the farmers, harvesting and marketing, known to about 93%% of the participant, yield assessment, known to all farmers, conservation of stem, known to about 76.9% of the farmers and record keeping also known to all of the participating farmers. The level of awareness of farmers involved in the dissemination of these technologies was found to be very high and this might help to facilitate speedy adoption of these technologies.

Figure 7 : Technologies disseminated on cassava practiced Yield and Technology Adoption Survey

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Table23: Technologies Disseminated on Cassava

Technologies Improved variety Yes No Site selection Yes No Land preparation Yes No Plant spacing/population Yes No Weed management Yes No Soil fertility Yes No Harvesting market Yes No Yield assessment Yes No Conservation of stem across Yes No Record keeping Yes No

4.2.2

Frequency

Percentage 100 100

-

15

100 -

14 15 59 1 14 14

93.3 -

13

92.9 7.1

13 13

100

13 10

100 -

10 3

76.9 23.1

100 100 -

Technologies disseminated on sorghum production The inclusion of sorghum as a critical food security crop in Nigeria cannot be overemphasized. From the table 24 below, all the farmers were aware of improved varieties technology. The second technology was seed dressing with apron plus and 96% of the program participant claimed they know this technology; while the right plant population was also known to all the farmers. The fourth in the list of the technologies was minimum tillage which was known to about 83% of the farmers under the project followed by micro dosing of organic and inorganic fertilizer known to all the farmers in the program and the last but not the least was mechanization known to by about 89% of the farmers involved in the project. The minimum tillage technology known to 83% and microdosing of organic/inorganic fertilization known to 100% of farmers is an indication that there is only little more effort by the extension services to have all the farmers.

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Table24: Technologies Disseminated on Sorghum

Technologies Improved variety

Frequency

Percentage

Yes No

31 -

100 -

Yes No

30 8

96 4

Yes No

31 -

100 -

Yes No Fertilizer application Yes No Mechanization Yes No Wastes Management Source: June, 2020 Field Data

25 6

83.3 16.7

31 -

100 -

23 8 30

88.5 11.5 100

Seed dressing

Plant population

Minimum Tillage

Figure 8 : Technologies disseminated on sorghum practiced

4.2.3

Technologies disseminated on rice production Rice is not only popular staple food crop in Nigeria, its global market demand remains very attractive for foreign exchange earnings and stabilizing foreign reserve of the country. Thus, to boost rice production across the SCPZs, several technologies were disseminated to the rice farmers under the Program as shown in table 25.

From the table 25, all the farmers were aware of improved rice varieties; while site selection for production was known to about 89% of the farmers under the project and 96% were aware of field preparation for rice production. More so, about 98% were aware Yield and Technology Adoption Survey

45

of the right planting season for rice production while about 98% were aware of crop establishment. Other technologies these farmers are familiar with are weed management and fertilizer application method. Pests control is known to about 98% of the participating farmers. It is hoped that these level of awareness will stimulate improved adoption by these farmers and consequently improved level of productivity.

Table25: Technologies Disseminated on Rice

Technologies Improved varieties Yes No Site/Land selection Yes No Field preparation Seed preparation Yes No Planting season Yes No Crop establishment Yes No Weed management Yes No Fertilizer application Yes No Pest and Disease control Yes No Wastes management

Yield and Technology Adoption Survey

Frequency

Percentage

47 -

100 -

47 6

88.8 11.2

42 3

93.3 6.7

46 1

97.9 2.1

43 2

97.5 2.5

47 -

100 -

47 -

100 -

46 1 46

97.9 2.1 100

46

Figure 9 : Technologies disseminated on rice practiced

4.3 4.3.1

Mode of practicing technologies extended on cassava production Functionality of adopted technology is primarily assessed by the rate of utilization. It is therefore logical that after selecting applicable technologies that could enhance farming productivity and presenting each of these at appropriate time and venues to farmers; it becomes very necessary to ascertain the level or rate of utilization of each of the packages.

Therefore, the analysis of the frequency of practicing good agronomic practices delivered to cassava farmers are as presented in table 26 below. From the table, it was found that improved cassava varieties were highly in use by these farmers across the 3 SCPZs as the average weighted score was 4.3 which was by far greater than 3.0 indicating the limit point where the effective usage of this technology begins. For this improved crop varieties, about 64% of the farmers affirmed that they regularly use it, 21% claimed they often use it while about 14% claimed they sometime use it. If we sum these together, we have 100% that were using this particular technology (improve variety) showing that the technology is very popular among the farmers.

On site selection, it also has a weighted average score of 3.7 showing that farmers have keyed into this technology. With about 36% of them claiming that, they regularly use this technology, while about 29% claimed they often use it and about 27 claimed they sometime used the technology and only 7% claimed have never. Summing all of these will give us a total of 100%. This is an indication that, this particular technology has been

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overwhelmingly embraced by the farmers. Land preparation method was another technology disseminated to cassava farmers and this technology also has a weighted score of 4.5 showing its wider applicability among these farmers. From the table 26 above, it was found that 64% of the farmers claimed they regularly make use of the technology while 21% claimed they often use the technology and 14% claimed they sometimes use the technology. It could be concluded that there is overwhelming use of these technology among these farmers. Such will generate expected higher yield to the credit of the Program; hence sustainability will depend largely on available market and processing capacity at immediate disposal Furthermore, plant spacing and the right plant population was another technology disseminated to farmers and this is very important if optimum crop yields are to be obtained from any cropping system. From the table 26 below, it was found that about 43% claimed they regularly use this technology, about 29% claimed they often use it while about 21% claimed they sometimes use it and 6 rarely used it. The weighted score of 4.2 is an indication that farmers are using this technology to the very well.

Weed management is very important because good management of weed could lead to substantial yields while lack of weed management could spell doom for the crop yield.

For this technology, the weighted score was 4.5 showing it has been widely accepted.

About 49% of these farmers claimed they regularly use this technology, about 28% claimed they often use it while about 22 % claimed they sometimes used it and 2% never use it.

Furthermore, soil fertility weighted score was 3.4 and about 33% claimed they regularly use it, about 33% claimed they often use it while 27% claimed they sometimes use it and 7% never used it. There is need to place more emphasis on this technology because the fertility of any soil will determine the output from such soil.

Record keeping was also among the technologies disseminated to farmers in the study area under ATASP-1 Program and this has a weighted score of 3.1 showing its marginal acceptability. This must have strong correlation with educational level of the respondents. From the table, about 20% of these farmers claimed they regularly use this technology; about 20% claimed they often use it while about 27% claimed they sometime use it, 13.3 claimed they rarely and 20% never used it. Of all the ten technologies disseminated on cassava, eight have been widely accepted while two that have weighted score of less than 3.0 have not been widely put into use and these two are yield assessment and proper record keeping. There is need to therefore put more efforts in persuading farmers about these technologies till they are widely accepted.

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Figure 10 : frequency of practicing technologies on cassava

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Table26: Mode of Practicing Cassava Technologies Technologies Improved variety

Site selection

Land preparation

Plant spacing/population

Weed management

Soil fertility

Harvesting market

Yield assessment technique

Conservation of stem across

Record keeping

Extent Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Weighted score Regularly Often Sometime Rarely Weighted score Regularly Often Sometime Rarely Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score

Frequency 9 3 2 4.1 5 4 4 1 4.4 9 3 2 4.7 6 4 3 1 4.3 6 4 3 1 4.5 17 14 15 1 3.4 13 6 11 14 16 2.5 10 10 6 11 23 2.5 15 9 8 8 20 2.8 25 5 5 14 11 3.1

Percentage 64.3 21.4 14.3 4.1 35.7 28.6 28.6 7.1 4.4 64.3 21.4 14.3 4.7 42.9 28.3 21.4 7.1 4.3 28.6 28.6 21.4 7.1 4.5 33.3 33.3 26.7 6.7 3.4 20.0 60.0 13.3 6.7 2.5 13.3 20.0 26.7 33.3 6.7 2.5 26.7 46.7 20.0 6.7 2.8 20.0 20.0 26.7 13.3 20.0 3.1

Note: weighted score less than 3.0 indicates that respondents rarely use the technology

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4.3.2

Sorghum production There were six technologies disseminated to sorghum farmers under ATASP-1 Program as presented in the table 27 below. From the table, improved sorghum variety has a weighted score of 4.4 showing that it is widely accepted by farmers with about 62% of the farmers claimed they regularly make use of this technology, about 31% claimed they often use this technology while about 7% claimed they sometime use this technology.

This is pointing to an overwhelming acceptance of this technology among the participating farmers across the SCPZs of the Program.

Seed dressing with apron star was another technology disseminated to farmers under the Program and result from the table 32 below indicated that the weighted score was 3.35 when the modes of practicing technologies were analyzed. From the analyses, 39% of the farmers claimed they regularly use this technology, about 35% claimed they often use it while about 14% claimed they sometime use this technology; but 13% claimed they never used. The acceptance of this technology rating marginally crosses the border line and there is need to devote more attention to its promotion.

The right plant population was another technology disseminated to these sorghum farmers and the weighted score was 4.2 which are considered to be very high and as such this technology enjoys wider applicability. About 61% of sorghum farmers claimed they use this technology, about 34% claimed they often use it while about 4% claimed they sometime use it.

Fertilizer application employing the micro dosing of organic and inorganic fertilizer is another technology disseminated and it has a weighted score of 4.2 showing its fair acceptance. About 63% of the farmers claimed they regularly use this technology, 30% claimed they often use it while about 7% claimed they sometime use it. Minimum tillage, 29% claimed they regularly used this technology, 48% accepted they often used it, 3% they sometimes 1% rarely used it and 18% maintained they never used it Mechanization, 37% regularly, 39% often used this package and 16% sometimes and 2 rarely used the technology while 5% never used this technology. The last two technologies are just at marginal level of adoption with a weighted score of 2.6.

Therefore, there is the need to intensify efforts at convincing these farmers of the importance of these two technologies so as to change their perception and acceptability

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Table27: Frequency of Practicing Sorghum Technologies

Technologies Improved variety

Extent Frequency Percentage Regularly 71 62.3 Often 17 31.2 Sometime 10 6.5 Rarely Never Weighted score 4.4 4.4 Seed dressing with Apron star Regularly 20 25.0 Often 25 31.3 Sometime 14 17.5 Rarely 7 8.7 Never 14 17.5 Weighted score 3.3 3.3 Plant population Regularly 41 51.2 Often 18 22.5 Sometime 19 23.8 Rarely 2 2.5 Never Weighted score 4.2 4.2 Tillage: minimum Tillage Regularly 14 29.0 Often 15 48.4 Sometime 15 3.2 Rarely 11 1.1 Never 25 18.3 Weighted score 2.7 Fertilizer application Regularly 23 30.3 Often 20 26.3 Sometime 23 30.3 Rarely 10 3.0 Never Weighted score 4.03 4.03 Mechanization Regularly 19 37.6 Often 8 38.7 Sometime 11 16.1 Rarely 11 2.2 Never 31 5.4 Weighted score 2.6 2.6 Note: weighted score less than 3.0 indicates that respondents rarely use the technology

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Figure 11 : frequency of practicing technologies on sorghum

4.3.3

Rice Production Rice production technologies disseminated enjoyed wide acceptability and applicability among farmers under ATASP-1 Program as can be seen in table 28 below as all the nine technologies record well over 4.0 weighted scores from the analyses that were done.

From the table, improved varieties had the highest weighted score of 4.7 indicating that there is overwhelming acceptance and applicability of this technology among rice farmers under the Program. It was observed that about 77% of the farmers claimed they regularly use this technology, about 19% claimed they often use the technology while about 2% claimed they sometimes and 2% never used the technology.

On site selection and land preparation, we have a weighted score of 4.6 showing its wider acceptability and applicability. About 57% of the farmers claimed they use this technology, 34% claimed they often use it while about 4% claimed they sometimes and 2%, 2% rarely use it never used the technology.

More so, field preparation equally has a weighted score of 4.2 showing its wider acceptability and applicability. From the table 28 below, about 35% claimed they regularly use it, about 49% claimed they often use it while about 16% claimed they sometimes use it; 2% claimed they rarely and 2% never used this technology. This was a clear indication of optimum level of acceptance.

Another very important technology disseminated was seed preparation which recorded a weighted score of 4.2 showing its wider acceptability. From the table 28 below, 49% claimed they regularly used this technology, about 34% claimed they often used it while about 12% claimed they sometimes used it and 2% claimed they rarely and never used it respectively. Getting the seed aspect of production right is absolutely important and the acceptance of this technology is very important at setting the production in the right Yield and Technology Adoption Survey

53

path of high productivity.

Determination of the planting season (interpreting rainfall pattern for successful cropping is a vital strategy in coping with challenges of climate change) is another technology disseminated to farmers under ATASP-1 Program as planting at the right time will enhance crop productivity. From the table 33 below, this technology has a weighted score of 3.7 showing its high level of acceptability. From the table 28, 73% of the farmers claimed they used this technology regularly, 24% claimed they used it often while about 2% claimed they sometime 1% used it.

Moreover, crop establishment was another technology disseminated to rice farmers with weighted score of 4.5 .From the table 28 below about 73% claimed they used this technology regularly; about 24 % claimed they used it often while about 2% claimed they sometime used it.

Another important technology disseminated on rice was weed management with a weighted score of 4.5. it was found that, about 74% of the farmers claimed they use this technology regularly, about 25% claimed they use the technology often while about 2% claimed they sometime use this technology. The wider acceptability of weed control technology is of great significant since this will enhance higher yield.

Fertilizer application technology was another very important technology disseminated and it recorded a weighted score of 4.5 showing its wider acceptability and applicability among the farmers. From the table 28 below, about 76% claimed they regularly used it, about 18% claimed they often used it while about 4.1% claimed they sometimes and 2.0% accepted they rarely used it. It is to be noted also that using the right fertilizer in the right quantity is a sure way of boosting rice productivity.

Finally, pest and diseases control is another technology disseminated by ATASP-1 Program to rice farmers in the Program areas and this recorded a weighted score of 4.0.

This showed that this technology has gained wider acceptability among these farmers.

From the table 28 below, about 52% claimed that they regularly used this technology; about 37% claimed they often used it while 7percent claimed they sometime used it, yet 4% affirmed that they rarely used this technology. The acceptance of technology for pest and diseases control is very significant since pest and disease can reduce yield to almost zero when left unchecked. From the results presented here, there was bound to be very significant increase in production of rice nationwide if these promising technologies are extended all rice producing zones in the country.

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Figure 12 : frequency of practicing technologies on rice

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Table28: Frequency of Practicing Rice Technologies Technologies Improved varieties

Site/Land preparation

Seed preparation

Determine planting season

Crop establishment

Weed management

Fertilizer application

Pest and Disease control

Extent Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score

Frequency 36 9 1 1 4.7 27 17 2 1 1 4.6

Percentage 76.6 19.1 2.1 2.1 4.7 57.4 34.0 4.3 2.1 2.1 4.6

Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score

26 10 11 1 1 4.2 17 22 8 1 1 4.2 24 17 6 1 1 4.2 36 12 1 4.5 37 9 2 2 1 4.5 24 17 3 2 2 4.0

53.1 20.4 22.4 2.0 2.0 4.2 34.7 44.9 16.3 2.0 2.0 4.2 49.0 34.7 12.2 2.0 2.0 4.2 73.5 24.5 2.0 4.5 75.5 18.4 4.1 4.3 1.3 4.5 52.2 37.0 6.5 4.3 2.5 4.0

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Acknowledging the fact that farmers are very rational as any other entrepreneurs, they go for best available production permutation among the lots for specific production target; which could be subsistence (for household) or special needs, commercial or trial of a technology among others options under socio-metric considerations) always have reasons for any production decisions they took. Based on the questions posed to these farmers to give reasons for adopting good agronomic practices (GAP) they adopted and their responses are as presented in table 34 below.

4.4

Reasons for farmers' adoption of Good Agronomic Practices (GAP) Acknowledging the fact that farmers are very rational as any other entrepreneurs, they go for best available production permutation among the lots for specific production target; which could be subsistence (for household) or special needs, commercial or trial of a technology among others options under socio-metric considerations) always have reasons for any production decisions they took. Based on the questions posed to these farmers to give reasons for adopting good agronomic practices (GAP) they adopted and their responses are as presented in table 29 below.

From the table 29 below, about 64% of cassava farmers claimed they adopted these agronomic practices because they were considered to be labour saving while 14% claimed they are not sure of the labour saving capability of these practices and about 25% claimed they disagree of this assertion. As for the technologies to enhance higher yield, about 93% of the farmers that participated claimed these practices enhance higher yield while about 7% claimed they disagreed. Furthermore, about 57% of these farmers claimed these practices enhance soil moisture retention while about 43% claimed they were not sure. 86% of these cassava farmers claimed that these practices help to control erosion and about 7% claimed they were not sure; while 7% disagreed with this declaration. Moreover, about 79% of these farmers claimed that, these practices enhance soil fertility while about 14% claimed they are not sure and 7% totally disagreed. Finally, about 71% of these farmers claimed that these practices help crops to adapt to climate change while 29% claimed they were not sure.

Sorghum farmers also have their good reasons for adopting good agronomic practices as shown in table 29 below. From this table, about 69% of the farmers claimed that these practices are labour saving while about 10% claimed they are not sure and 21% claimed that, they disagreed with this statement. On the other hand, 97% of these farmers claimed these practices encourage higher yields and 3% were not sure. That these practices enhance soil moisture retention, about 89% of these farmers agreed to this, and about 11% claimed they were not sure. Also, soil erosion control was one of the attributes of these good agronomic practices and about 93% of these farmers were in affirmative that, these practices enhance erosion control while about 7% claimed they were not sure.

About 83% of these farmers claimed that, these practices enhance soil fertility while about 17% claimed they are not sure. Finally, about 76% of sorghum farmers claimed that, these practices help crops to adapt to climate change while about 25% claimed they were not sure.

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Rice farmers also expressed their opinion on why they adopted good agronomic practices as follows; about 49% claimed these practices are labour saving while about 27% not sure, 26% claimed they disagreed. Also, 98% of these farmers claimed that these practices enhances higher yield; while 2% disagree. About 86% claimed they helped in soil moisture retention while 12% claimed they were not sure, 2% disagreed. Moreover, about 86% of these farmers claimed these practices enhance soil fertility while 10% claimed they were not sure, 4% disagreed. Soil erosion control is equally one of the reasons why farmers adopted these practices as about 80% claimed that, their reason for adopting these practices; while 18% claimed they were not sure and 2% disagreed. For soil fertility, 86% of the respondents affirmed that these technologies indeed boost soil fertility, but 10% were not sure; while 4% disagreed. Lastly, about 61% of rice farmers equally claimed these practices were capable of helping crops to adapt to change in climate challenges while 37% claimed they were not sure and about 2% disagreed.

Table29: Reasons for Farmers' Adoption of Good Agronomic Practices (GAP) Reasons Labour saving

Opinion Agree Not sure Disagree Higher yield Agree Not sure Disagree Soil moisture retention Agree Not sure Disagree Soil erosion control Agree Not sure Disagree Enhancement of soil fertility Agree Not sure Disagree Climate change adaptation Agree Not sure Disagree Figures in parentheses are percentages

Cassava 9(64.3) 2(14.3) 3(21.4) 13(92.9) 1(7.1) 8(57.1) 6(42.9) 12(85.7) 1(7.1) 1(7.1) 11(78.6) 2(14.3) 10(71.4) 4(28.6) 1(1.7)

Sorghum 20(69.0) 3(10.3) 6(20.7) 28(96.6) 1(3.4) 24(96.6) 1(3.4) 25(92.6) 2(7.4) 2(2.5) 25(92.6) 2(7.4) 24(82.8) 31(38.8) 9(11.3)

Figure 13 : Reasons for adoption of GAP technologies Yield and Technology Adoption Survey

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Rice 24(49.0) 13(26.5) 12(24.5) 48(98.0) 1(2.0) 42(85.7) 6(12.2) 1(2.0) 65(79.6) 9(18,4) 1(2.0) 66(85.7) 12(10.2) 30(61.2) 18(36.7) 1(2.0)

4.5

Rate of Adoption of Technologies disseminated to farmers in the 4 SCPZs Delineating between rate of adoption and frequency of adoption is like differentiating between subjective and objective, or passive and active phases of the same event. While rate of adoption explains latent forces of the prospective candidate; frequency presents level of the actual deployment of the technology package.

Rate of adoption presents how much of the package does a respondent accept; this means, the survey considers to ascertain how many of the sampled respondents and to what degree do they accept efficacy of the technology as beneficial to their productive capacity. Whereas, frequency seeks to measure how often is the technology applied.

Rate of adoption is determined by availability and dissemination of the package, often by the Extension agents (EAs) to the candidates: farmers, fabricators, and processors.

But frequency is determined by availability, accessibility and the willingness of the candidate to deploy the technology appropriately in the course of production.

There is the need to constantly monitor the rate of adoption as the Program progresses so as to know what review to undertake to facilitate good level of adoption that will result in the envisaged outcome conceptualized by the Program from the onset. The rate of adoption of technologies under each of the three crops: Cassava, Sorghum and Rice have been captured by the study under this years' dry season and they are as presented below.

4.5.1

Rate of Adoption of technologies disseminated to cassava farmers From table 30 below, there were good levels of adoption of technologies disseminated to cassava farmers in the SCPZs across the country. Improved varieties, site selection, land preparation, soil fertility management and weed management were all effected at 100% by the respondents. On the other hand, plant spacing recorded 92%, record keeping has 77% adoption and yield assessment has 93% adoption rate. Nevertheless, the EAs were expected to do more to sustain adoption level and where need be to increase to maximum possible level. It was also believed that good outcome will definitely spread out to farmers within the communities and beyond.

Table30: Rate of Adoption of Cassava Technologies

S/No

Technologies

1 Improved variety 2 Site selection 3 Land preparation 4 Plant spacing/population 5 Weed management 6 Soil fertility 7 Harvesting market 8 Yield assessment 9 Conservation of stem across 10 Record keeping * Multiple responses were allowed Yield and Technology Adoption Survey

Frequency*

Percentage

15 15 15 14 15 14 15 13 13 10

100 100 100 93.3 100 100 100 92.9 100 76.9

59

Figure 14 : Frequency of practicing adopted technologies on cassava

4.5.2

Rate of Adoption of technologies disseminated to Sorghum farmers There were considerable high levels of adoption of technologies disseminated to Sorghum farmers under ATASP-1 Program as shown in table 31 below.

It was interesting to note that, all the technologies introduced to sorghum farmers such as the improved seed varieties, proper spacing for optimum plant population, fertilizer application each of these were 100% adopted. But minimum tillage and mechanization have 83% and 89% adoption rate respectively. This was very encouraging with respect to the effort of the EAs interacting with farmers; and the farmers too demonstrated their seriousness at achieving cost-effectiveness objectives.

Also, a computed table presenting technologies disseminated to sorghum farmers are as presented in figure 15. From this figure, except mechanization, where the rate of adoption was about 38%, all other technologies have an impressive scores ranging from 60% to 100%. It was an indication that farmers have embraced these technologies and this was expected to lead to substantial increase in output in sorghum production.

Figure 15 : Frequency of practicing adopted technologies on sorghum

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Table31: Rate of Adoption of Sorghum Technologies S/No 1 2 3 4 5

Technologies Improved variety Plant population 0.75 x 0.3m 2 plants per hill Tillage: minimum Tillage Fertilizer application Mechanization

6 Waste Management * Multiple responses were allowed

4.5.3

Frequency* 31 31 25 31 23

Percentage 100 100 83.3 100 88.5

29

100

Rate of adoption of technologies disseminated to rice farmers As observed from table 32, rice recorded very impressive levels of technology adoption under ATASP-1 Program. It was found that, seed dressing recorded 96% adoption and determination of planting season with 98% of adoption are the two technologies with least adoption rate; that is all others recorded 100% adoption. This is very impressive and showing dedication of these farmers to income making venture rather than taking farming as a pastime exercises. Such was raising the hope that the intervention was on course towards making the nation a major rice producing in the continent; that will able to produce enough to meet the domestic demands and good quantity for export, thus conserving our foreign reserve for better use.

Table32: Rate of Adoption of Rice Technologies S/No 1 2 3 4 5 6 7 8 9

4.6

Technologies Improved varieties (Faro 44, Faro 52, Faro 60 and Faro 61 Site/Land preparation Field preparation Seed preparation Determine planting season Crop establishment Weed management Fertilizer application Pest and Disease control

Frequency* 47

Percentage 100

47 45 45 45 46 47 47 46

100 100 95.7 97.9 100 100 100 100

Effects of Adoption of Good Agronomic Practices on Crop Production The ATASP-1 Program disseminated several new technologies to boost the impact of the Good Agronomic Practices to other participants who are not farmers in the choice value chain of the 3 enterprise crops, Sorghum, Cassava and Rice across the SCPZs. These other value chain operators are processors and fabricators within the SCPZ. Essentially, this is one of the many measures to ensure that food production and food security are not adversely affected by environment specific and climate change related realities.

The program objective for the ATASP-1 Program is to improve substantially the productivity and income of the farmers and other participants in the agribusiness value chain.

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The previous years' report indicates that there was strong positive impact made in managing the risks of specific environmental and climate variability and near-term climate change challenges through the technologies disseminated by ATASP-1, however, the sustainability of the technology adoption and adaptations requires continuous improvements. To address the above, ATASP-1 Program embarked on a proactive approach to building the capacity of the participants on adaptive and necessary technological systems, embedded in more robust food production and distribution techniques that are designed to be sustainable in the context of climate change. The technologies extended to the participants covered such farm management and postharvest operations like, pest and disease control, fertilizer application, threshing, cleaning, drying, storage, processing, harvesting, and packaging technologies.

The adoption and the adaptation of technologies that have strong imperative for sustainability of improved quality of life for the farmers and other operators across the value chain depends largely on how the technology mitigates the climate and specific environmental variability risks. This section evaluated the effect of ATASP-1 technologies on the outputs and income of the participants.

The ATASP-1 Program disseminated several Good Agronomic Practices to participating farmers in the production of 3 enterprise crops, Sorghum, Cassava and Rice across the SCPZs. The participating farmers gave responses based on the impact of the technologies extended to them before the adoption of the technologies and after the adoption of the technologies. The technologies disseminated includes farm management and postharvest operations knowledge and skills, pest and disease control, fertilizer application, threshing, cleaning, drying, storage, processing, harvesting, and packaging technologies.

Table 33: Effects of Adoption of GAP on Corp Production Mean Production Non-Adopters Adopters RICE N Mean SORGHUM N Mean CASSAVA N Mean Source: June 2020 Field Data

Difference in Mean

Percentage Difference

30 2458.8333

29 4911.4007

2452.5674

99.7%

28 1464.0714

29 3482.8621

2018.7907

137.9%

96 1089.2917

96 1895.1563

805.8646

74.0%

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Figure 16 : Mean crop production for non-adopters and adopters

The survey result shows that the program objective for the ATASP-1 Program resulted in substantial improvement in the adoption of these technologies across all the 3 enterprise crops. The participating farmers in the Rice crop enterprises showed 99.7% increase in adoption of these technologies from a mean of 2,458 with 30 participants to a high of 4,911 with 29 participants as adopters showing a mean difference of 2,452 higher. The survey result also showed that, the participating Sorghum farmers had a 137.7% increase in technology adoption from 28 participants with 1,464 mean level of non- adopters to a higher of 29 adopters with mean level of increase of 3,482 technology adoption showing an increased mean rate of adoption of 2,018 for Sorghum crop enterprise. The survey report on the Cassava crop farmers showed 74.0% increase in technology adoption from an initial mean rate of non-adopters of 1,084 with 96 participants, which increased to a mean level of adoption of 1,895 showing a mean increased difference in adoption rate of 805. Technology adoption is one of the many measures to ensure that food production and food security are not adversely affected by climate change. The adoption and the adaptation of technologies that have strong imperative for sustainability of improved quality of life for the farmers depends largely on how the technology mitigates the climate variability risks.

4.7

Effect of GAP on farmers' income (Cassava, Sorghum and Rice farmers) The ATASP-1 Program disseminated several Good Agronomic Practices to participating farmers in the production of 3 crops, Sorghum, Cassava and Rice across the SCPZs. The program objective for the ATASP-1 Program is to improve substantially the productivity and income of the farmers and other participants in the agribusiness value chain.

Essentially, this is one of the many measures to ensure that food production and food security are not adversely affected by climate change. The adoption and the adaptation of technologies that have strong imperative for sustainability of improved quality of life for Yield and Technology Adoption Survey

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the farmers depends largely on how the technology mitigates the climate variability risks.

4.8

Effects of ATASP-1 on Fabricators output The output of any business has a direct and causative relationship on the income and livelihood of the person. Fabricators play an important role in shaping the economic environment and conditions of farmers which in turn has impact on food security and livelihood of the nation at large. The table 34 below shows the responses from the field survey.

Figure 17 : Fabricators' mean seasonal number of customers

Table34: Fabricators' Mean Seasonal Number of Customers

ZONE

ADANI-OMOR

Mean Seasonal Number of Customers Before During ATASP -1 ATASP -1 34 94

Difference in Mean

Percentage Difference 60

174.8%

BIDA-BADEGGI

17

46

28

163.5%

KANO-JIGAWA

20

35

15

72.8%

KEBBI-SOKOTO

37

70

33

88.4%

Total

27

59

33

121.6%

Source: June 2020 Field Data

It is evident from Table 38 above that fabricators had improved patronage after adoption of ATASP-1 technologies which is higher than the patronage before adoption of the ATASP-1 technologies. This was shown from the responses received on their patronage before TASP-1 technologies were introduced and the outputs received after the receipt of ATASP-1 technologies. The mean average output before the adoption of ATASP-1 technologies was 27 across all SCPZ. The mean output after adoption of ATASP-1 technologies was 59 showing a 121.6% increase in output by the participating Yield and Technology Adoption Survey

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Fabricators in all the SCPZs. The survey found that the Fabricators who participated in ATASP- capacity building and adopted the technologies claimed increase in patronage from farmers. The 121.6% increase in patronage could be attributed to the supports provided by ATASP-1 through technology adoption and capacity building given to these Fabricators as actually affirmed by the respondents.

4.9

Effects of ATASP-1 on Processors output The processors play significant role in the agribusiness and farming value chain.

Processors serve as off takers which is an important role in shaping the economic environment and conditions of farmers and fabricators in like manner which in turn has impact on food security and livelihood of the participating economic actors. Table 35 below shows the result obtained from the field survey.

Table 35: Mean Processed Output Quantity Before and After ATASP -1 by Zone Quantity of Processed output (Kg)

ZONE

Difference in Mean

Percentage Difference

ADANI-OMOR BIDA-BADEGGI KANO-JIGAWA KEBBI-SOKOTO

Mean Mean Mean Mean

Before ATASP -1 3,166.7 691.7 67.6 1,251.7

After ATASP -1 7,000 3,783.3 514.8 2470

3,833.33 3,091.67 447.2 1,218.33

121% 447% 662% 97%

Total

Mean

1,119.1

3,023.9

1,904.71

170%

Source: June 2020 Field Data

It is evident from Table 35 above that the processors had improved patronage after adoption of ATASP-1 technologies which is higher than the patronage before adoption of the ATASP-1 technologies. The mean average patronage before the adoption of ATASP-1 technologies was 1,119.1kg across all SCPZs. The mean patronage after adoption of ATASP-1 technologies stood at 3,023.9kg showing a 170% increase in patronage by the participating Processors in all the SCPZs. The survey found that the Processors who participated in ATASP-1 capacity building and adopted the technologies claimed increase in outputs. The mean difference of 1,904 increase in patronage is could be attributed to the supports provided by ATASP-1 through technology adoption and capacity building given to these Processors as affirmed by the respondents.

4.10

Effects of ATASP-1 on the income and wellbeing of participating Fabricators There are ranges of possible positive impacts of increased outputs from the farmers on the Fabricators (i) improved incomes and social wellbeing; (ii) improved national income and reducing trade imbalance; (iii) creation of employment opportunities through equipment fabrications for farmers and processing. These are some of the direct and causative relationship on the income and livelihood of the person. Table 36 below shows output from the analysis of the responses from the fabricators.

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Table36: Fabricators' Average Income Per Season Before and During ATASP -1 by Zone Average Income Per Season (? )

ZONE

Before ATASP -1

During ATASP -1

Income Difference

Percentage Difference

ADANI-OMOR

255,000.00

700,000.00

445,000.00

174.5%

BIDA-BADEGGI

400,000.00

866,666.67

466,666.67

116.7%

KANO-JIGAWA

30,530.00

55,051.25

24,521.25

80.3%

KEBBI-SOKOTO 217,466.67 Total 210,732.31 Source : June 2020 Field Data

414,453.33 474,120.38

196,986.66 263,388.07

90.6% 125.0%

It is evident from Table 36 above that those who fabricators who benefited from ATASP1 technologies had higher incomes and improved livelihoods than those who did not. The mean average income of the participant Fabricators before the adoption of ATASP-1 technologies was ? 210,732.31 per month across all SCPZ. The mean income after adoption of ATASP-1 technologies was N 474,120.38 showing a 125% increase in income with a mean difference of ? 263,388.07 across the SCPZs. This increase shown from the responses received on their incomes before ATASP-1 technologies were introduced and the incomes received after the receipt of ATASP-1 technologies confirm that the Fabricators who participated in ATASP-1 capacity building and adopted the technologies claimed increase in their incomes and subsequently livelihoods.

4.11

Effects of ATASP-1 on the income and wellbeing of participating Processors The processors play significant role in the agribusiness and farming value chain including improved nutrition and food security in the country; (v) improvement of environmental conditions through specific value chain management activities; (vi) improved infrastructure through development and repairs of market channels and networks; (vii) capacity building targeting local markets, through value addition in processing and entrepreneurial skills development. Processors as off takers shape the economic environment and conditions of farmers which in turn has impact on food security and livelihood of the participating economic actors. Table 37 below shows the result obtained from the field survey.

Figure 18 : Fabricators' mean monthly income before and after ATASP-1 Yield and Technology Adoption Survey

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Table37:Mean Monthly Income Before and After ATASP -1 ZONE

Mean Monthly Income (? ) Before ATASP -1

After ATASP -1

Difference in Mean

Percentage Difference

ADANI-OMOR

183,333.33

190,000.00

6,666.67

3.6%

BIDA-BADEGGI

143,333.33

233,888.89

90,547.56

38.7%

KANO-JIGAWA

24,000.00

61,100.00

37,100.00

154.6%

9,333.33

17,000.00

7,666.67

82.1%

80,571.43

366,892.86

286,321.43

KEBBI-SOKOTO Total

355.4%

Source: June 2020 Field Data

Figure 19 : Mean monthly income of processors before and after ATASP-1

Evidence from Table 37 above shows that those processors that benefited from ATASP-1 technologies had higher incomes after the adoption of the ATASP-1 technologies. The mean average income before the adoption of ATASP-1 technologies was ? 80,571.43 per month across all SCPZ. The mean income after adoption of ATASP-1 technologies stood at ? 366,892.86 showing a 355% increase in income by the participating Processors in all the SCPZs. The survey found that the Processors who participated in ATASP-1 capacity building and adopted the technologies claimed to have increase in income and wellbeing.

The mean difference in income of ? 286,321.43 as an increase in income could be attributed to the supports provided by ATASP-1 through technology adoption and capacity building given to these Processors.

4.12 Effects of ATASP-1 on Food Security / Overall Economic Development of the Country Judging from the evidence of improved performance and increase in production and income of the three categories of beneficiaries; farmers, fabricators and processors as has been observed in the trends of analysis outputs on income and production related variables which are quite impressive, it can be affirmed that the adoption of good agronomic practices (GAP) disseminated by ATASP-1 is a dominant factor with Yield and Technology Adoption Survey

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significant effect on increased production of farmers, outputs of processors, and patronage of fabricators.

The predominant source of livelihood of rural dwellers in this country is farming; and in communities where ATASP-1 has disseminated GAP, the crop enterprises (Rice, Sorghum and Cassava) are dominant with notable performance. The place of farm produce in the economic development of the country is discussed here. Farm produce contribute to economic development of any society in the following ways: • Provision of food for all and raw materials for agro-related businesses.

• There are diversifications in the means of livelihood of the farmers, farmers' groups and association as they branch-off into agro-based value addition enterprises like processing and farm produce marketing.

• Farming and interlinked activities like fabricating and processing have become profitable ventures providing employment and secured means of livelihood for the uneducated and unskilled rural dwellers; and the educated alike.

• The transporters who move farm produce from the rural farmers to urban markets also benefit from increase in farmers' productivity through their engagement.

• In the rural areas, increase in farmers' productivity has in turn improve their purchasing power which translates into improvement in social welfare and the living standard of the rural masses as they are able to afford and consume more nutritious diets richer in protein; and acquisition of better assets like motorcycle, television, house and even dresses.

• Increase in purchasing power of the rural farmers prepare them as contributors to other sectors of the rural economy • Some state governments and other stakeholders, reacting to increase in the volume of farm produce business in some communities have embark on the improvement of road networks to such communities to open them up for easier farm produce movement and communication. Good road network can contribute to the economic development of a community and the country at large.

Agricultural or farming related growth has long been recognized as an important instrument for poverty reduction and contributor to the economic growth of local communities and nations; including this country. The effects of ATASP-1 on Food Security and the overall economic development of the country is notable and conclusive from the observations listed above which are outcome of the survey conducted across the zones where ATASP-1 had disseminated the GAP technologies; and trainings to fabricators and processors.

4.13

Factors Influencing Adoption of Technologies There were several technology interventions delivered by ATASP-1 Program through a demand driven bottom up and top down approach. These technologies resulted in the significant yield improvement in all the 3 crops across all the SCPZ within the period

Yield and Technology Adoption Survey

68

under review. These technologies are, improved crop variety, site and land preparation, field preparation, seed preparation, crop establishment, weed management, fertilizer application and disease and pest control.

2

However, the first observation made on the output was the pseudo R , the -2Log likelihood improvement, the minimization criteria used in SPSS. It was observed that the 2 2 Nagelkerke's R is 0.583 which indicates that the model is good. Cox and Snell's R in the nth root (with this data set, 96th of the -2Log likelihood improvement). This can be interpreted as a 41.2% probability that the event of the covariates influencing the dependent variable (GAP Adoption), is explained by the Logit model. The classification result is at 80.2% which is good.

The output table above shows the variables in the model equation and the coefficients. It generates the regression function:

This table also shows the test of significance for each of the coefficients in the Logistic regression model. Wald statistics (basically t2 or chi-square distributed with df = 1) has been used here instead of t-test because of the sample size for which the t-values may not be valid. As observed, AGE and EDUCATION are the most significant respectively at 7.2 and 12.1; while CREDT_ACCESS, HOUSEHOLD_SIZE, FARM_SIZE and GENDER are respectively at 4.4, 2.6, 1.2 and 1.04. However, as can be observed from the regression function (3) above, the other variables each exercises some influence, positive or negative at varying magnitudes as the dependent variable scales in step of 1.

All these are non-zero influence in the model; which counts. The assessment conducted provided information factors that influence the adoption of these technologies across the Program SCPZ. 4.13.1 Factors Influencing Adoption of Cassava Technologies Table 38 below shows the responses from the adopters of the 10 technologies capacity building given to the Cassava farmers across the selected SCPZ of ATASP-1 Program.

Table 41 indicates that improved varieties, site selection, land preparation, weed management and market harvest accounted for 11.8% technology adoption, for Cassava farmers. Also, 10.1% of the participants confirmed that soil fertility and plant spacing practice had effect on technology adoption in Cassava farmers and also yield assessment and record keeping 9.4% and 7.2% respectively.

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26.7% BIDA-BADEGGI KANO-JIGAWA TOTAL

26.7%

5 33.3%

26.7%

28.6%

5 33.3%

6

5 33.3%

40.0%

15 10.8%

10.8%

6 40.0%

15

15 10.8%

21.4% 5

33.3%

5 40.0%

14 10.1%

10.8%

35.7% 6 14 10.1%

3 23.1%

4 30.8%

6 46.2%

15 10.8%

9.4%

38.5% 5

35

5

49

3

55

10

139 100.0%

30.0% 13

9.4%

2

50.0%

38.5% 13

Total

20.0% 5

6

40.0%

Record Keeping

Stems Conserva- tion

3

23.1%

5 33.3%

42.9% 15

4

26.7% 5

6

35.7%

3

Yield Assess-ment

4

26.7%

5 35.7%

6

40.0%

4

Soil Fertility Management

4

Weed Management

4

Plant Spacing

4

Site Selection

Improved Variety

ADANI-OMOR

Land Preparation

GAP Technologies Practiced on Cassava

ZONE

Market Harvesting

Table38: Technologies Practiced on Cassava ATASP -1

7.2%

Source: June., 2020 Field Data The improved technology which is the improved method of processing cassava conserves energy and is more hygienic. This improved processing equipment include: peeler, grater, hydraulic press, granulator, dryer, fryer, sifter, fermentation tank, hammer mill and grinder, which are capable of enhancing acceptability of cassava products.

Cassava processing using the traditional methods is not too efficient because of tremendous losses during processing and high labour inputs. These problems persist primarily due to the lack of appropriate postharvest facilities. It has been commonly shown that acceptance of new technology practices take place over time. Continuous capacity building play indispensable role in solving many problems that constitute bottlenecks in smallholder farming systems especially weeding, harvesting, processing and storage.

Figure 20 : Technologies practiced on cassava Yield and Technology Adoption Survey

70

4.13.2Factors Influencing Adoption of Technologies of Sorghum The table below shows the effect of good agronomic practices based on the adoption of technologies from responses of the participants on the 7 technologies in which capacity building was given to the Sorghum farmers across the selected SCPZ of ATASP-1 Program.

Table 39 indicates that improved seed, plant population and fertilizer application accounted for 15.5% technology adoption, for Sorghum farmers. Also, 15% of the participants confirmed that seed dressing practice had effect on technology adoption in Sorghum farmers and other respondents represented that 14.5% confirmed waste management, 12.5% minimum tillage and 11.5% mechanization, respectively.

Table39: Technologies Practiced on Sorghum ATASP -1 ZONE

Improved Seed

Seed Dressing

4

4

ADANIOMOR 12.9% BIDABADEGGI

13.3% 8

25.8% KANOJIGAWA

8

9

KEBBISOKOTO TOTAL

10

31 15.5%

10 32.3%

30 15.0%

31

25

Source: June., 2020 Field Data

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71

50

9

54

10

69

31.0% 9

39.1% 31

15.5%

34.5% 23

11.5%

27

6

6

10

Total

20.7%

26.1%

32.3%

12.5%

4

9

10

Waste Management 4 13.8%

17.4%

29.0%

40.0%

15.5%

8

4 16.0%

4 17.4%

25.8%

9 29.0%

33.3%

8 32.0%

Mechanization

4 12.9%

8

8

10

3 12.0%

25.8%

26.7%

32.3%

4 12.9%

26.7%

29.0%

GAP Technology Practiced on Sorghum Plant Minimum Fertilizer Population Tillage Application

29 14.5%

200 100.0%

Figure 21 : Technologies practiced on sorghum

The effect of good agronomic practice on technology adoption on sorghum farmers shows that mechanization and minimum tillage had the lowest effect across all the SCPZ for sorghum farmers. However, the lowest effect was associated with minimum tillage which accounted for 11.5%. This implied that framers are still highly in need of more awareness of the need to focus on high quality minimum tillage as good agronomic practice that influence technology and supports improved livelihood and income in sorghum crop production.

4.13.3 Factors Influencing Adoption of Technologies of Rice Table 40 below shows the responses from the participants on the 9 technologies capacity building given to the Rice farmers across the selected SCPZ of ATASP-1 Program. Table 43 indicates that improved varieties, site preparation, planting season, weed management, fertilizer application, and pest and disease control accounted for 11.12% technology adoption, for Rice farmers. Also, 10.91% of the participants confirmed that field preparation practice had effect on technology adoption in Rice farmers and seed preparation accounted for 10.61%.

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Table40: Technologies Practiced on Rice ATASP -1

Yes 16

34.0%

34.0%

BIDA-BADEGGI 17.0%

17.0%

KEBBI-SOKOTO

13 27.7% 37

13 37

7

13 36 10.91%

13

13

37

71

9

86

13

117

19.6% 13

27.7% 37

8 17.4%

21.3%

11.21%

142

10

13

37 11.21%

17.0%

27.7%

16 34.8%

8

10 21.3%

28.3%

10.61% 11.21%

34.0%

17.0%

Total

Yes 16

8

9 19.6%

28.3%

35

34.0%

17.4%

19.6%

Yes 16

8

9

Pests/ Diseases Control

Weed Management

Crop Establishment

34.8%

17.4%

13 28.9%

Yes 16

8

10 22.2%

28.9%

Yes 16

34.8%

15.6% 9

20.0%

11.21%

Planting Season

Seed Preparation

17.8%

27.7%

11.21%

8

10 21.3%

Yes 15

33.3%

8

10 21.3%

Yes 15

33.3%

8

KANO-JIGAWA

TOTAL

Yes 16

Fertilizer Application

Yes ADANI-OMOR

Field Preparation

ZONE

Site/Land Preparation

Improved Varieties

GAP Technologies Practiced on Rice

28.3% 37

11.21%

37 11.21%

330 100.00%

Source: June., 2020 Field Data

Figure 22 : Technologies practiced on rice

The overall result shows that the seven good agronomic practices all had combined effects on technology adoption by farmers across all the SCPZ. However, the lowest effect was associated with seed preparation which accounted for 10.1%. This implied that framers are still highly in need of more awareness of the need to focus on high quality seed preparation as good agronomic practice that influence technology and supports improved livelihood and income.

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4.14 Constraints militating Against the Adoption of Good Agronomic Practices in ATASP The study identified 29 main constraints across the SCPZ on the 3 enterprise crops based on the previous years' report. The previous year's report also indicates that ATASP-1 Program made strong positive impact on the participants through various technologies disseminated.

From the tables below, we have constraints that had effects that were (1) very severe, (2) severe (3) mildly severe, (4) not severe and (5) not a problem. The list of identified constraints covered climatic and environmental factors, economic and political factors, social and cultural factors, and human factors.

To address the above 29 constraints identified across the SCPZ, ATASP-1 Program categorized these 29 constraints specific to each of the focal crop. The Cassava crop enterprise had 8 constraints associated with it, Rice crop enterprise had 12 constraints and Sorghum crop enterprise had 9 constraints associated to it, respectively. The survey used the 5-point Linkert analysis as a proactive approach adaptive to the Program and the technologies disseminated to capture the responses of the participants.

The responses from the survey concluded that ATASP-I Program approach helped reduced the effects of these constraints as the participants were equipped with skills and technologies required for continuous improvements.

4.14.1 Constraints militating Against the Adoption of Good Agronomic Practices by Cassava Technologies Table 41 below shows the responses on the 9 constraints on Cassava farmers under ATASP-1 Program. From the table, there were 9 main constraints identified that hinders adoption of technologies disseminated to cassava farmers under the Program. These constraints are, labour shortage, inadequate stakeholders' network, socio-cultural factors, physical factors, poor record keeping, poor understanding of technology, conflicts and inadequate safety awareness.

The Cassava farmers identified that socio-cultural practices had no severe impact on the adoption of Good Agronomic Practices on Cassava farmers, with 53% of the participants confirmed that socio-cultural practice is not a problem, while 18.4% of the participants confirmed that socio-cultural practices had no severe effects and another 18.4% confirmed that it had mildly severe effect on technology adoption. 10.2% of the participants also agreed that socio-cultural practice had severe effect on technology adoption.

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Table41: Adoption of Good Agronomic Practiced Technology on Cassava ATASP -1 Technology

Constraint Not Mildly Severe Severe

Not a Problem

Cassava Safety Awareness

14 28.6%

Poor Understanding of Technology

13 26.5%

19 38.8% 36.7%

9

14.3% Physical/Climatic Factors

3 6.1% 26

Socio-Cultural 53.1%

15

Labour Shortage 31.2% Stake Holders Networking

12 24.5% 31.8%

18.8%

32.7%

11 22.9%

10.2%

22.7%

5

5

10

8 16.7%

12 24.5%

5 11.4%

6 12.2%

10.2% 9

16

14

Conflict

12

9

5

7 14.3%

24.5%

18.4%

10.4%

9

13

9

7 14.3%

18.4%

26.5%

18.4%

5

10

15

4 8.2%

10.2%

20.4%

30.6%

11

6

16

1 2.0%

22.4%

12.2%

32.7%

16

6

13

Very Severe

32.7%

12.2%

26.5% 7

Human Factors

5 10.2%

18.4% 18

Poor Record Keeping

Severe

4 8.2%

8 18.2%

7 15.9%

Source: June., 2020 Field Data However, the survey results from the respondents on the 5 points scale indicated that majority of farmers 31.8% had no problems with the listed constraints in adoption of Cassava technology, 22.7% confirmed that these constraints were not severe in the adoption of technology, 11.4% confirmed a mildly severe effect on the adoption of technology, 18.2% confirmed severe effect while 15.9% showed very severe effect.

15.9% of the Cassava farmers showed that conflict had very severe effect on adoption of technology. 14.3% of the respondents confirmed that Poor record keeping, and human factors were very severely significant to the adoption of Cassava technology, and 12.2% confirmed that physical and climatic factors also had very severe impact on technology adoption.

More effort needs to be put in place by policy makers and the Program in encouraging cassava farmers towards a higher appreciation of technology adoption and the reduction of the effects of these constraints on Cassava farmers.

4.14.2 Constraints to Adoption of Good Agronomic Practices in Sorghum Technologies by ATASP-1 There are 16 key constraints identified from last ATASP-1 Program report on Sorghum

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75

crop enterprises, however these 16 constraints have been reduced to 12 main constraints specific to the Sorghum crop enterprises within the SCPZ in the period under review.

Table 42 below shows the responses on these 12 constraints on Sorghum farmers under ATASP-1 Program. Also, the table indicates that the 12 main constraints identified that hinders adoption of technologies disseminated to Sorghum Crop enterprises and the farmers under the Program. These identified constraints are, market distance, low price for Sorghum, high transport cost, low market /demand for products, unavailability of extension services, lack of effectiveness, long distance to extension workers, pest and disease control, poor road network, inadequate capital, inadequate land and inadequate large export market.

The Sorghum crop enterprises farmers identified that poor road network had very severe impact on the adoption of Good Agronomic Practices on Sorghum farmers, with 33.3% responses from the adopters 16.7% of the participants confirmed that market distance had very severe effects and this is consistence with the approval of 33.3% shown on poor road network. High transport cost had 13.8% very severe effect while 10% confirmed that low price of Sorghum and pest and disease controls had very severe effect on technology adoption respectively. Inadequate large export market and low market and product demand accounted for a low of 7.4% and 6.7% very severe constraints on adoption of Sorghum technologies respectively.

The survey results in the table indicate that the ATASP-1 Program demonstrated the capacity to sustainably scale up engagement in the rapid yield Program across all the zones with 83.9% of the respondents showing that extension services unavailability is not a problem and another 77.45 respondents showing that lack of effectiveness is not a problem. Other constraints recorded such as inadequate land and inadequate capital had severe impact, with a response of 43.3% and 13.3% respectively. The result from the respondents showed that 43.3% had no problems with Market distance. Lack of coordination, insufficient dialogue, insufficient outreach, and poor understanding of GAP have been effectively corrected by the ATASP-1 Program from past and existing works. A high of 54.8% of the Sorghum crop enterprises farmers showed that long distance to extension workers was not a problem on adoption of technology. This indicates that lack of capital, poor road network, inadequate large export markets and low prices for Rice are the leading constraints to the adoption of technology.

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Table42: Adoption of Good Agronomic Practiced Technology on Sorghum ATASP -1 Technology

Constraint Not Severe Mildly Severe

Not a Problem

Severe

Very Severe

Sorghum Market Distance

13 43.3%

3 10.0%

13

Low Price for Sorghum 43.3%

3 10.0%

9

High Transport Cost 31.0% 46.7% 83.9%

11 35.5%

9 30.0%

5

3

46.7%

4

10 33.3%

7 23.3%

11 40.7%

5 16.7%

13.3% 14

Inadequate Large Export Market

6 20.0%

16.7%

10.0%

3

2

6

Inadequate Land

2 6.7%

9.7%

6.7%

20.0% Inadequate Capital

5 16.7%

7

17

Poor Road Network

5

4 13.8%

22.6%

54.8% Pest and Diseases Problem

8 27.6%

16.1%

77.4% Long Distance to Extension Worker

3 10.0%

5

24

Lack of Effectiveness

8

3

16.7%

5 16.7%

26.7%

10.3% 4

26

Extension Service Unavailable

3

5

13.3%

5 16.7%

10.0%

17.2% 14

Low Market/Demand for Product

4 13.3%

5 16.7%

5 18.5%

1 3.7%

10 33.3% 4 13.3% 13 43.3% 4 13.3% 8 29.6%

3 10.0% 10 33.3%

2 7.4%

Source: June., 2020 Field Data 4.14.3 Constraints militating Against the Adoption of Good Agronomic Practices for Rice Production

The report from the previous years' showed 16 key constraints, however these 16 constraints have been reduced to 12 main constraints specific to the Rice crop enterprises within the SCPZ in the period under review. Poor understanding of GAP, and lack of coordination, insufficient dialogue and insufficient outreach have been effectively corrected by the ATASP-1 Program from past and existing works. The table 43 below shows the responses on these 12 constraints on Rice farmers under ATASP-1 Program.

The table indicates that the 12 main constraints identified that hinders adoption of technologies disseminated to Rice Crop enterprises and the farmers under the Program.

These constraints are, market distance, low price for Rice, high transport cost, low market /demand for products, unavailability of extension services, lack of effectiveness, long distance to extension workers, pest and disease control, poor road network, inadequate capital, inadequate land and inadequate large export market.

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The Rice farmers identified that Inadequate Capital had very severe impact on the adoption of Good Agronomic Practices on Rice Crop Enterprises, with 40.4% responses from the participants. This further affirmed the impact of policy and socio-cultural practice on the Rice crop enterprise. 37.5% of the participants confirmed that poor road network had very severe effects, inadequate large export market had 21.1% very severe effect and another 20.5% confirmed that low price of Rice had very severe effect on technology adoption. Other constraints recorded such as inadequate land 19.1% very severe impact, pest and diseases problem had 17% very severe effect, respectively on the adoption of technologies by Rice crop enterprises farmers. Extension services unavailability with a 2.1% had the lowest response on the very severe effects, this was followed by low market demand for the products at 2.3%. Market distance and lack of effectiveness recorded a 6.2% very severe effect of technology adoption by Rice crop enterprises farmers. Long distance to extension services recorded a 6.5% response on the very severe effect and high cost of transportation accounted for 8.9% of the very severe constraints on the adoption of technology by Rice crop enterprises farmers respectively.

Further, the survey results from the respondents on the 5 points scale indicated that majority of Rice crop enterprises farmers at 21.1% had no problems with the listed constraints in adoption of Rice technology, 15.8% confirmed that these constraints were not severe in the adoption of technology, 21.1% confirmed a mildly severe effect on the adoption of technology, 21.1% confirmed severe effect while 21.1% showed very severe effect.

A very high 56.2% of the Rice crop enterprises farmers showed that market had no problems on adoption of Rice technology. 79.2% of the respondents confirmed that extension services unavailability was not a problem, 64.6% and 63% respondents confirmed that lack of effectiveness and long distance to market were not problems to the adoption of Rice technology. This indicates that lack of capital, poor road network, inadequate large export markets and low prices for Rice are the leading constraints to the adoption of technology.

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Table43: Adoption of Good Agronomic Practiced Technology on Rice ATASP -1 Technology

Constraint Not Mildly Severe Severe

Not a Problem

Rice Market Distance

27 56.2%

4 8.3%

12

Low Price for Rice 27.3%

39.5% 38

4

31

Lack of Effectiveness 64.6% Long Distance to Extension Worker

18.8%

63.0%

19.6% 2

Pest and Diseases Problem 4.3%

7

Poor Road Network 14.6%

8 16.7%

1

Inadequate Capital 2.1%

10.6%

25.5% 21.1%

15.8%

18 37.5%

12 25.5%

14.9%

8 17.0%

10

7

19 40.4%

12 25.5%

8 21.1%

6.5%

20.8% 10

6

3

10 21.3%

21.3%

14.9% 8

Inadequate Large Export Market

3

5

7

3 6.2%

6.5%

10.4% 5

12

Inadequate Land

2

23 48.9%

1 2.1%

4.2%

4.3%

8.5%

4

2

4

1 2.3%

8.3% 3

9

8.9%

18.6%

6.2%

4

8

1

9

29

26.7%

2.1%

9 20.5%

12

7 16.3%

8.3%

6.2%

6.8%

28.9%

3

3

13

10 23.3%

79.2%

10.4%

20.5%

13.3%

Very Severe

5

9

6

17

Extension Service Unavailable

18.8%

25.0%

22.2% Low Market/Demand for Product

9

11

10

High Transport Cost

Severe

9 19.1%

8 21.1%

8 21.1%

Source: June., 2020 Field Data 4.14.4 Constraints militating against the adoption of Good Agronomic Practices by cassava farmers There were many constraints that could possibly be limiting the adoption of good agronomic practices by cassava farmers under ATASP-1 Program as abstracted in the study. From the analyses in the Table 44 below, it was found that out of the fifteen (15) constraints analyzed, eleven (11) were found not to be very severe in their ability to hinder adoption of good agronomic practices among cassava farmers that were sampled.

For the purpose of understanding these analyses, weighted score that are less than 3 indicates not severe. From this, we have those constraints that were mildly severe at weighted score of 2.7. These include human factor, poor networking, pests and diseases infestations and poor road linkage. The severe (at 3.0 weighted score) ones were: inadequate capital, transportation cost, low price of the commodity and accessibility of labour. While the possible limiting factors were very few; yet, they remain critical to adoption and high productivity as well as the income earning of the farmers. Therefore, there is the need for the Program to work harder to address these constraints to enhance optimal productivity of cassava farmers. Saliently, the same factors affect producers of many other staple crops in the country.

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Table 44: Constraints Militating Against the Adoption of Good Agronomic Practices among Cassava Farmers Constraints Very Severe Mild Not Not a Weighted severe severe severe problem score Insufficient safety 2(14.3) -(-) 2(14.3) 5(35.7) 5(35.7) 2.7 awareness Poor understanding of -(-) (-) 1(7.1) 6(42.9) 7(50.0) 2.2 technology Poor record keeping 2(14,3) 1(7.1) 3(21.4) 2(14.3) 6(42.9) 2.4 Human Factor 1(7.1) 3(21.4) 4(28.6) 3(21,4) 3(21.4) 2.8 Physical/climatic factors -(-) 3(21.4) 4(28.6) 2(14.3) 5(35.7) 2.4 Sociocultural -(-) 3(21.4) 1(7,1) 2(14.3) 8(57.1) 1.9 Labour shortage 1(7.1) 2(14.3) 8(57.1) -(-) 3(21.4) 3.0 Stakeholders networking 1(7.1) 3(21.4) 4(28.6) 1(7.1) 16(35.7) 2.7 Conflict -(-) -(-) -(-) 5(35.7) 9(64.3) 1.6 Low price 2(14.3) 3(21.4) 5(35.7) -(-) 4(28.6) 3.0 High cost of transport 1(7.1) 7(50.0) 2(14.3) -(-) 4(28.6) 3.4 Pests and diseases 2(14.3) -(-) 5(35.7) 6(42.9) 1(7.1) 2.8 Inadequate capital 8(57.1) 5(35.7) -(-) -(-) 1(7.1) 3.6 Inadequate land 3(21.4) 3(21.4) 1(7.1) 2(14.3) 5(35.7) 2.6 Poor road network 14(28.6) -(-) 3(21.4) 4(28.6) 3(21.4) 2.8.

Figures in parentheses are percentages Note: weighted score less than 3.0 indicates not severe

4.14.5 Constraints militating against the adoption of Good Agronomic Practices among sorghum farmers There are 16 envisaged constraints that could militate against adoption of good agronomic practices by sorghum farmers in various zones under the Program. These constraints are presented in the Table 45 below. From the table, all but one has weighted scores that were less than 3; meaning that only one of them posed severity that could hamper adoption of agronomic practices disseminated to sorghum farmers. However, those with 2.7 weighted scores and above should be given due attention because they are critical to productivity and as well to farmers' income earning prospect. Low capital for investment having above 3.0 weighted score should be handle with carefulness, since the Program does not disburse fund nor included such in the package for the selected farmers.

It will be reasonable to the Program if linking up the farmers with credit institutions is integrated into the intervention in all the Zonal levels.

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Table45: Constraints militating Against the Adoption of Good Agronomic Practices Among Sorghum Farmers Constraints

Very severe

Severe

Mild severe

Not severe

Not a problem

Weighted score

Safety awareness

-(-)

2(6.7)

1(3.3)

10(33.3)

17(56.7)

1.8

Poor understanding of technology

1(3.3)

1(3.3)

1(3.3)

5(16.7)

22(73.3)

1.7

Poor record keeping

2(6.7)

4(13.3)

7(23.3)

4(13.3)

13(43.3)

2.7

Human factor

1(3.3)

3(10.0)

5(16.7)

7(23.3)

14(46,7)

2.4

Physical/Climatic factors

3(10.3)

4(13.8)

7(24.1)

7(24.1)

8(27.6)

2.5

Sociocultural

3(10.3)

1(3.3)

2(6.7)

9(30.0)

18(60.0)

1.9

Labour shortage

2(6.7

4(13.3)

3(10.0)

6(20.0)

15(50.0)

2.2

Stakeholder networking

2(6.7)

4(13.3)

3(10.0)

6(20.0)

15(50.0)

2.2

Conflict

1(3.3)

2(6.7)

1(3.3)

10(33.3)

18(60.0)

2.0

Low price

3(10.0)

8(26.7)

3(10.0)

3(10.0)

13(43.3)

2.7

Pests and diseases

13(10.0)

10(33.3

6(20.0)

2(6.7)

9(30)

2.8

Poor road network

10(33.3)

4(13,3)

5(16.7)

5(16.7)

6(20.0)

2.6

Inadequate capital

-(-)

13(43.3)

10(33.3)

4(13.3)

3(10.0)

3.1

Inadequate land

-(-)

4(13.3)

5(16.7)

7(23.3)

14(46.7)

2.5

High cost transport

4(13.8)

8(27.6)

4(10.3)

5(17.2)

9(31.0)

2.7

Insufficient outreach and lack of coordination in training

-

16(20)

13(16.25)

9(11.25)

42(52.5)

2.025

Figures in parentheses are percentages

Note: weighted score less than 3.0 indicates not severe 4.14.6 Constraints militating against the adoption of Good Agronomic Practices for rice farmers There 15 envisaged constraints that could militate against the adoption of good agronomic practices introduced to rice farmers are presented in the Table 46 below. From the table, only three of the constraints; pests and diseases infestation, low capital for investment and high cost of transportation crossed the threshold of 3.0, whereas, effect of climate change, accessibility of labour and poor pricing are considered mildly severe; yet they require prompt attention through dialogue and fiduciary establishment. Nigeria being the largest market for rice in Africa, there is the need to upscale our production in terms of quantity and quality to enable us meet domestic demand and possibly for export.

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Table46: Constraints Militating Against the Adoption of Good Agronomic Practices Among Rice Farmers Constraints

Very severe

Severe

Mild severe

Not severe

Not a problem

Weighted score

Insufficient awareness about safety

1(2.0)

16(32.7)

5(10.2)

13(26.5)

14(28.6)

2.7

Poor record keeping

7(14.3)

5(10.2)

6(12.2)

13(26.5)

18(36.7)

2.6

Poor understanding of technology

4(8.2)

11(22.4)

6(12.2)

9(18.4)

19(38.8)

2.3

Human factor

6(12.2)

12(24.5)

8(10.0)

16(32.7)

7(14.3)

2.5

Physical/Climatic factors

6(12.2)

12(24.5)

13(26.5)

15(30.6)

3(6.1)

2.7

Sociocultural

--

5(10.2)

9(18.4)

9(18.4)

26(53.1)

2.2

Labour shortage

8(16.7)

11(22.9)

9(18.8)

5(10.4)

15(31.2)

2.8

Conflict

7(15.9)

8(18.2)

5(11.4)

10(22.7)

14(31.8)

2.7

Market distance

3(6.2)

5(10.4)

9(18.8)

4(8.3)

27(56.2)

2.2

Low price

4(8.9)

12(26.7)

9(20.5)

11(25.0)

12(27.3)

2.9

Pest and Disease problem

8(17.0)

10(21.3)

23(48.9)

4(8.5)

2(4.3)

3.0

Inadequate capital

19(40.4)

12(25.5)

10(21.3)

5(10.6)

1(2.1)

3.7

Inadequate land

9(19.1)

12(25.5)

7(14.9)

7(14.9)

8(25.5)

2.8

High cost of transport

4(8.9)

12(26.7)

13(28.9)

6(13.3)

10(22.2)

3.3

Low stakeholders networking

2(8.2)

12(24.5)

5(10.2)

16(32.7)

33(24.5)

2.2

Figures in parentheses are percentages Note: weighted score less than 3.0 indicates not severe

From the foregoing, we should have acknowledged three phases that make up adoption. These are: awareness, domestication, and deployment. Since, deployment is observed phase among the three, therefore, future survey should dwell much more on assessing domestication as understood by the sample farmers; because, domestication deals with rural education. Thus, where the farmers can explain the process and objectives of a technology, the goal of the package has to a very large extent accomplished. Deployment on the other hand depends on the willingness of the farmer against the backdrop that such package is available and accessible.

Adoption: Awareness

Domestication

Deployment Willingness Availability Accessibility Skills

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CHAPTER

FIVE

5.0 CONCLUSION AND RECOMENDATIONS 5.1 CONCLUSION This current level of performance by ATASP-1 Program will foster sustainable food production and knowledge transfer from the older generation of farmers to the younger generation of farmers. The significance of the Program is consistent with the structure of outcomes recorded across all the Program zones which is indicative of a meaningful Program technology transfer and knowledge management success.

One major element in sustaining food production is to improve the living conditions of rural farmers in the Program zones by assisting them to increase farmer productivity and their income and to provide access to markets. This survey result shows that ATASP-1 interventions across the 3 crops in the 4 zones has significantly improved the yield performance of the farmers across all the crops promoted by ATASP-1 across the SCPZs. Despite this improved performance, the ATASP-1 survey was not without some challenges and top amongst was the constraints poised by the COVID-19 pandemic.

Other challenges are late commencement, considering the timing of harvest of the crops and shortness of the timeline within which the survey had to be conducted, hence the survey was a rapid one. This significant improvement is further evidence of the need to ensure a continuous intervention from ATASP-1Programs to deepen sustainability of the Program impacts in areas of need.

5.2 RECOMMENDATIONS The results of the findings above and other factors such as the current reality caused by COVID19 and the observations in the field from the ongoing ATASP-1 interventions, below are the recommended areas for improvement in the subsequent yield surveys that would be conducted by ATASP-1: a) Sustainability in Food Security and livelihood improvement Yield and Technology Adoption Survey

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In line with the principles of early warning systems of monitoring, there is a need for the survey scheduled and conducted to target the harvest period of each of the crops promoted by the ATASP-1 Program. This principle supports the philosophy of sustainability in Food Security and livelihood improvement which forms strong pillars of the 17 UN- SDGs. b)

Improvement in Regulatory Policy and Enabling Environment The ATASP-1 Program needs to focus more efforts on interventions that promotes reforms in areas of policy and regulatory environment and adequately allot more technical experts to conduct the survey and provide wider coverage to the Program beneficiaries.

c)

Reduction of poverty through rural economic development The design of the ATASP-1 study requires increased attention on strategies that reduce poverty and support interventions from ATASP-1 Programs towards increased market access. It may be necessary to build the capacity of the field personnel in ATASP-1 Zonal Offices on the yield survey process.

d)

Reduction of the impact of climate change on Agricultural Environment ATASP-1 Programs have proven interventions that adequately impact on climate change but there are gaps in capacity across the Program zones and these require additional resources to retool and upskill the participants. The scope and sample size of the survey should be enlarged to accommodate other categories of beneficiaries.

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ANNEXURE

REVIEW MEETING OF THE INSTRUMENT FOR CROP YIELD AND TECHNOLOGY ADOPTION SURVER

ADANI-OMOR STAPLE CROP PROCESSING ZONE

The team administering Questionnaire to Farmers and Processor at Adani-Omor SCPZ

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BIDA-BADEGGI STAPLE CROP PROCESSING ZONE

Cross section of the team at Bida-Bedeggi Zone with the Zonal Program Coordinator, Engr. Ibrahim Manta

The team administering Questionnaire to the Program beneficiaries at Bida-Badeggi SCPZ

The team administering Questionnaire to the Program beneficiaries at Bida-Badeggi SCPZ

KANO-JIGAWA STAPLE CROP PROCESSING ZONE

Team at Bunkure L.G.A, Kano State

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Team at Auyo L.G.A, Jigawa State

86

Team at Gwaram L.G.A, Jigawa State

KEBBI-SOKOTO STAPLE CROP PROCESSING ZONE

Zonal Program Coordinator, Dr. Aliyu Addaji addressing the team on arrival at Kebbi-Sokoto Zonal Office.

Team at Kware L.G.A validating data from Sokoto.

The team administering Questionnaire to a female Processor at Kebbi

The team administering Questionnaire to a Fabricator at Kebbi

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Survey Team

IBRAHIM M. ARABI National Program Co-ordinator

Engr. Ibrahim Manta

Alh. Auwalu Ado Shehu

Dr. Aliyu Addaji

Zonal Program Co-ordinator Bida-Badeggi SCPZ

Zonal Program Co-ordinator Kano-Jigawa SCPZ

Zonal Program Co-ordinator Kebbi-Sokoto SCPZ

CONSULTANT

Mr. Romanus Egba Zonal Program Co-ordinator Adani-Omor SCPZ

Dr. Uche Abiodun Akungudo

Mr. Peter S. Olorunfemi

Mr. Benserah Aromolaran

Team Leader

Member

Member

Member

Mr. Akintunde Akinwale P.

Mr. Chukwuma Ejiogu

Mrs. Falmata Zanna G

Mr. Ugochukwu Nnanna

TECHNICAL TEAM ATASP-1

Dr. Shuaibu Abubakar Ummah

Survey Co-ordinator

Member

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Member

88

Member

FEDERAL MINISTRY OF AGRICULTURE AND RURAL DEVELOPMENT AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE-1 (ATASP-1) Survey Questionnaire for the Rapid Yield amongst ATASP-1 Beneficiaries in Nigeria Rapid Yield Questionnaire (Lead Farmer)

1. IDENTIFICATION DETAILS

CODE 1.1 SERIAL NUMBER :

/..../...../...../...../...../...../...../

1.2 YEAR: 1.3 ZONE: 1.4 STATE: 1.5 LGA: 1.6 CLUSTER/COMMUNITY: 1.7 NAME OF BENEFICIARY/FARMER : 1.8 PHONE NO OF BENEFICIARY 2.

/...../....../ /...../....../ /...../....../ /...../....../ /...../....../....../ /...../....../....../

DEMOGRAPHIC DATA

2.1) Gender

Male ?

2.2) Household Size (Number)

Male members =

Female ? ; Female members =

;Total =

Below 30yrs ?

2.3) Age of Beneficiary/Farmer (Years) 2.4) Highest Education Attained:

Between 31-59yrs ?

Above 60yrs ?

(0) No school at all (3)Tertiary education (5)Quoranic

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(1) Primary

(2) Secondary/TC II

(4) Non-Formal education

3.

HOUSEHOLD’S CULTIVATED PLOTS DETAILS: (Respondent is the head of household)

Number of plots cultivated: /........./ Plot Detail 1

2

3

4

5

GROWING SEASON : (1 = RAINFED, 2 = DRY SEASON/IRRIGATED)

GPS COORDINATES (IN DEGREES): To be filled in for only the plot visited by the team Latitude: Longitude: PLOT AREA (HA) : CROPS IN PLOT:

Tick as applicable

RICE SORGHUM CASSAVA 3.b) Years engaged in production of these crops RICE No of years engaged in these crops production

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SORGHUM

CASSAVA

Total

4.

CROP VARIETIES PLANTED (For crops currently growing on plots)

CASSAVA VARIETY

TICK (IF USED)

RICE VARIETY

TICK (IF USED)

SORGHUM VARIETY

TMS 30572

Faro 44

CSR-01

TME 419

Faro 52

SAMSORG 17

TMS 98/0505

Faro 60

ICSV-400

TMS 07/0593

Faro 61

SAMSONG 14

TMS 01/1368

Faro 62

ICSV-111

TICK (IF USED)

KSV-8

List of Varieties to be provided by ATASP -1 HQ

5.

INPUTS USAGE (For crops currently growing on plots)

5.1) Was this input used? (1= YES, 0 = NO) CROP NAMES ITEMS RICE USE OF INORGANIC FERTILIZER USE OF ORGANIC FERTILIZER USE OF AGRO-CHEM USE OF IMPROVED SEED/CASSAVA CUTTING TRACTOR (for any operation)

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SORGHUM

CASSAVA

5.2) Quantity of input used and source (For crops currently growing on plots) CROP, INPUT QUATITY, SOURCE OF INPUT INPUTS USED

INORGANIC FERTILIZER (Kg) (Tick as applicable)

ORGANIC FERTILIZER (Kg) (Tick as applicable

AGRO-CHEMICAL (Kg/Lt) (Tick as applicable)

RICE:

SORGHUM:

CASSAVA:

Quantity:

Quantity:

Quantity:

Source of Inputs: ATASP -1 ADP Ag-Input Dealer Input Companies 5 Others Other:

Source of Inputs: 1 ATASP -1 2 ADP 3 Ag-Input Dealer 4 Input Companies 5 Others Other:

Source of Inputs: 1 ATASP -1 2 ADP 3 Ag-Input Dealer 4 Input Companies 5 Others Other:

Quantity:

Quantity:

Quantity:

Source of Inputs:

Source of Inputs:

Source of Inputs:

1 2 3 4

ATASP -1 ADP Ag-Input Dealer Input Companies 5 Others Other:

ATASP -1 ADP Ag-Input Dealer Input Companies 5 Others Other:

ATASP -1 ADP Ag-Input Dealer Input Companies 5 Others Other:

Quantity:

Quantity:

Quantity:

Source of Inputs:

Source of Inputs:

Source of Inputs:

1 2 3 4

1 2 3 4

ATASP -1 ADP Ag-Input Dealer Input Companies 5 Others

1 2 3 4

1 2 3 4

1 2 3 4

1 2 3 4

Other:

Other:

Other:

ATASP -1 ADP Ag-Input Dealer Input Companies 5 Others

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ATASP -1 ADP Ag-Input Dealer Input Companies 5 Others

TOTAL INPUT

INPUTS USED

IMPROVED SEEDS/ CUTTINGS (Kg/Bundle) (Tick as applicable)

6.

RICE:

SORGHUM:

CASSAVA:

Quantity:

Quantity:

Quantity:

Source of Inputs:

Source of Inputs:

Source of Inputs:

1 2 3 4

1 2 3 4

ATASP -1 ADP Ag-Input Dealer Input Companies 5 Others

1 2 3 4

Other:

Other:

Other:

ATASP -1 ADP Ag-Input Dealer Input Companies 5 Others

TOTAL

ATASP -1 ADP Ag-Input Dealer Input Companies 5 Others

Application of Good Agronomic Practices (GAP): Which of these Good Agronomic Practices (GAP) did you adopt/apply? (Tick as applicable)

S/N 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

Tick

Practice

Use of improved varieties Seed dressing with Apron Star Plant population: 0.75 x 0.3m 2 plants per hill.

Tillage: minimum Tillage (use of herbicides) Fertilizer application: Micro-dosing of organic and inorganic fertilizer Mechanization Improved varieties (Faro 44, Faro52, Faro 60 and Faro 61) Site/Land Preparation Field Preparation Seed Preparation Determining planting season Crop establishment Weed management Fertilizer application Pests and Diseases control Use of improved varieties Site Selection Land Preparation Plant Spacing/Population Weed Management Soil Fertility Management Harvesting Market Yield Assessment Conservation of stems across off-season Record keeping Waste Management System (WMS)

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7.

HARVEST DATA

(Crops to be harvested and weighed) STATE OF CROP RICE

SORGHUM

CASSAVA

a) Type of harvest (1 = Whole Plot; 2 = Sub Plot; 3 = Sub-sub Plot) b) STATE OF CROP AT HARVEST (Use the Codes below)

Codes for state of crop at harvest: 1 Dry on head/panicle 2 Fresh on head/panicle 3 Tuber 7.c) HARVESTED CROP WEIGHT CROP HARVESTED CROP WEIGHT

RICE

SORGHUM

CASSAVA

Whole plot weight (Kg) un-threshed Triangle weight (Kg) un-threshed Sub-triangle weight (Kg) un-threshed Sub-Triangle weight (Kg) threshed Threshing %

7.d)

Harvest of 2019/20 dry season compared to 2018/19

Generally, how do you compare the 2019/20 harvest with the 2018/19 harvest?

Higher

CROP RICE

Lower Same Don’t know

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SORGHUM

CASSAVA

Survey Questionnaire (DEMONSTRATION PLOTS) 1.

IDENTIFICATION DETAILS 1.3 ZONE: 1.4 STATE: 1.5 LGA:

/...../....../ /...../....../ /...../....../

1.6 CLUSTER/COMMUNITY: 2.

/...../....../....../

PLOTS DETAIL: RICE

SORGHUM

CASSAVA

Lat: (GPS COORDINATE) Long: (GPS COORDINATE) PLOT AREA (HA) :

3.

CROP VARIETIES PLANTED

RICE

4.

SORGHUM

CASSAVA

HARVEST DATA RICE

a) Type of harvest (1 Whole Plot; 2. Sub Plot; 3. Sub-sub Plot) b) state of crop at harvest (Use the Code) c) HARVESTED CROP WEIGHT Whole plot weight (Kg) un-threshed Triangle weight (Kg) un -threshed Sub-triangle weight (Kg) un-threshed Sub-Triangle weight (Kg) threshed Threshing %

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SORGHUM

CASSAVA

FEDERAL MINISTRY OF AGRICULTURE AND RURAL DEVELOPMENT AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE-1 (ATASP-1) Survey Questionnaire for the Assessment of Adoption of Improved Technologies amongst ATASP -1 Beneficiaries in Nigeria

FARMERS QUESTIONNAIRE: (A)

Background Information

A.1 A.2 A.3 A.4 A.5 A.6

Questionnaire number……………………………………………………..

Name of farmers (optional)………………………………………………

Name of Group…………………………………………………………………

Name of Group Leader…………………………………………………….

Phone Number ………………………………………………………………

Cropping Enterprise: Crop Yes No Rice Sorghum Cassava

A.7 SCPZ:…………………………………………….

A.8 State…………………………………………….

A.9 LGA……………………………………….

A.10 Community……………………………………………

A.11 Cluster …………………………………………….

A.12 Interview date: .........................................................….../__/__/__/__/__/__/__/__/ (ddmmyyyy) A.13 Name of the Enumerator ………………………………………………………………….

A.14 Phone Number ……………………………………………………………….

A.15 GPS Coordinate: Latitude:…………………………………………………………

Longitude:………………………………………………………

(B) Socio-economic characteristics of farmers B.1Household structure Gender 1= male 2=female

Age of Household (HH) Head (years)

Marital Status 1=Married 2= Single 3=Others

Education level of HH Head (code1)

Household size (number)

Wife/wives

Number of Children 0-18yrs

Number of adult children 19yrs and above

Others living with you

Code1: Education level 0=none ; 1= Koranic ; 2=primary, 3=junior secondary school, 4=senior secondary school, 5=tertiary, 6= other (specify)

B 2) Information on farmers’ plot B2.1 What cropping practices did you use? Sole cropping [ ] Mixed cropping [ ] B2.2 What is the total size of your farm holding?………………………………………….ha Complete the table below on your farm size and experience

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Crop

1

Mode of acquisition

Size of land (ha)

Years of cropping experience

Cassava Rice Sorghum 1 Mode: 1 = Inheritance 2=Purchase 3 = Rent 4=Lease 5 =Gift 6=Others (specify) Others:

Conversion: ha: enumerators should be mindful of conversion 2.3 acre = 1ha,

about 7000 big heaps = 1ha,

10000 small heaps = 1ha

B3 Extension Contact B3.1 Did extension staff visit you last growing season? Yes [ ]

No [ ]

B3.2 If yes, how OFTEN did extension staff visit you last cropping season.........................

B3.3Did you participate in the Innovation Platform? Yes [ ] No [ ] B3.4 Did you participate in demonstration plots? Yes [ ] No [ ] B3.5 Did you participate in farmers’ field day? Yes [ ] No [ ] B4.Credit information for the last cropping season Access Ease of Access 1Source of Credit to credit required (N) If Yes credit

Credit received (N)

Nature of credit

2

What Level of was the loan money repayment used for?

Yes = 1 Prompt = 1 Cash=1 No = 0 Delayed = 2 Kind=2 1 Source of credit: 1=credit program, 2= commercial bank, 3=cooperatives 4=NGO, 5=traders, 6=agricultural bank 7=family and friends 8= other (specify) 2 What was the money used for : 1=input purchase, 2=agricultural activity, 3=commerce, 4=health care, 5=purchase of food, 6=social functions, 7=other expenses (specify)

B5. Farmers’ association Membership Name of the Yes = 1 No = 0 association

1

2 Level of Years of Benefit derived Bankable registration participation from the association Yes = 1 or No = 0

1

Level of registration: LGA = 1, SG = 2, FGN = 3 Yield and Technology Adoption Survey

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2

Benefit: 1 = Access to inputs, 2 = Credit, 3 = training, 4 = Labour, 5 = Information, 6=Marketing, 7= Others (specify) Others:

B6. Access to training on production Have you ever when did you get Where did you 1Who Were you satisfied had any training the training get training? organized with the training on production?

(Year/s) the training? received [ ] Yes = 1 [ ] Yes = 1 [ ] No = 0 [ ] No = 0 1 Who organized the training: ATASP -1 = 1, ADP = 2, NGOs = 3 & Others = 4 (Specify) Others: C. Production information C1.Input used S/NO 1

* 2

* 3

*

DESCRIPTION Sorghum Seed (Kg) Insecticides (Litre) Herbicides (Litre) Hired Labour (Each) Family Labour (Each) Fertilizer (Kg) OUTPUT (Kg) Rice Seed (Kg) Insecticide (Litre) Herbicide (Litre) Hired Labour (Each) Family Labour (Each) Fertilizer (Kg) YIELD (Kg) Cassava Cuttings (Bundle) Insecticide (Litre) Herbicide (Litre) Hired Labour (Each) Family Labour (Each) Fertilizer (Kg) YIELD (Kg)

VARIETY/TYPE

QUANTITY

D1. Indicate the quantity of fertilizer used ……………………… (Kg) D2. Cost per Kg___________Naira E1. Improved Technologies Disseminated on Sorghum E1.1.Are you aware of any of the following technologies?

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UNIT PRICE (?)

TOTAL ( ?)

S/N

Technologies Disseminated

Awareness Status (Yes =1; No=0)

1

Source of awareness

Indicate(Yes/No) if you practice any

2

Perception of usefulness of Technology

Sorghum Improved seed variety 1 (Specify) Seed dressing with Apron 2 Star Plant population: 0.75 x 3 0.3m 2 plants per hill.

4

Tillage: minimum Tillage (use of herbicides)

Fertilizer application: Micro5 dosing of organic and inorganic fertilizer 6 Mechanization 7 Waste Management System

Rice Improved varieties (Faro 1 44, Faro52, Faro 60 and Faro 61) 2 Site/Land Preparation 3 Field Preparation 4 Seed Preparation Determining planting 5 season 6 Crop establishment 7 Weed management 8 Fertilizer application Pests and Diseases 9 control Cassava 1 Use of improved varieties 2 Site Selection 3 Land Preparation 4 Plant Spacing/Population 5 Weed Management 6 Soil Fertility Management 7 Harvesting Market 8 Yield Assessment Conservation of stems 9 across off-season 10 Record keeping 1

Source: ATASP_1 = 1, ADP = 2, NGOs = 3, Other Farmers = 4 , Others (Specify) = 5 Very Useful = 4, Useful = 3, Rarely Useful = 2, Not Useful = 1

2Perception of Usefulness:

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Others (Specify)

F1. Indicate Frequency of practicing these extended technologies on sorghum, rice and cassava production S/N TECHNOLOGIES Frequency of practice (code) Sorghum: 1 Improved seed variety (Specify) 2 Seed dressing with Apron Star 3 Plant population: 0.75 x 0.3m 2 plants per hill.

4 Tillage: minimum Tillage (use of herbicides) Fertilizer application: Micro-dosing of organic and 5 inorganic fertilizer 6 Mechanization Others Specify I Ii iii.

Rice: Improved varieties (Faro 44, Faro52, Faro 60 and 1 Faro 61) 2 Site/Land Preparation 3 Field Preparation 4 Seed Preparation 5 Determining planting season 6 Crop establishment 7 Weed management 8 Fertilizer application 9 Pests and Diseases control Others (specify) I Ii iii.

Cassava: 1 Use of improved varieties 2 Site Selection 3 Land Preparation 4 Plant Spacing/Population 5 Weed Management 6 Soil Fertility Management 7 Harvesting Market 8 Yield Assessment 9 Conservation of stems across off-season 10 Record keeping Others (specify) I Ii iii.

Code: 5 = Regularly, 4 = often, 3 = sometime, 2 = rarely, Yield and Technology Adoption Survey

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1 = never

G. Reasons for Adoption of Technologies (Good Agronomic Practices, GAP) were based on the following: GAP Rank (Code) Labour saving Higher yield Soil moisture retention Soil erosion control Enhancement of soil fertility Climate change adaptation Others (specify) Rank Code: 3 = agree, 2 = Not sure, and 1 = disagree H. Constraints to adoption of Technologies (Good Agronomic Practices, GAP) Constraints Rank (Code) Knowledge: Insufficient awareness about safety Poor understanding of technology (GAP) requirements, Poor record keeping, Environmental: Human factors Physical/Climatic factors Social: Socio-cultural (Religious belief/Tradition ) shortage of labour, insufficient networking with stakeholders, Conflict Production Constraints - Product market: Long distance to market Low prices for rice Low price for cassava Low price for sorghum High transport cost Lack of market/demand for product Extension services: Unavailability of extension services Lack of effectiveness Long distance to the extension workers Others: Problem of pest and diseases Poor roads network Inadequate capital Inadequate land Inadequate large export market Rank Code: 5 = very severe, 4 = severe, 3 = mildly severe, 2 = not severe, 1 = not a problem I. Output from Crop Enterprise Yield and Technology Adoption Survey

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S/No

Crops

1

Rice

2

Sorghum

3

Cassava

Unit of measurement (Kg) (Non-Adopters)

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Unit of measurement (Kg) (Adopters)

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FEDERAL OF MINISTRY AGRICULTURE AND RURAL DEVELOPMENT AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE-1 (ATASP-1) Survey Questionnaire for the Assessment of Adoption of Improved Technologies amongst ATASP -1 Beneficiaries in Nigeria Survey checklists for the assessment of the adoption of improved technologies amongst Fabricators under ATASP -1 Focus Group Discussion

FABRICATORS QUESTIONNAIRE: (A)

Background Information i. Questionnaire number…………………………………………………….. ii. Name of Group………………………………………. iii. Name of fabricator……………………………………………………………………………………………..

Phone number of ………………………………………………………….. iv. Name of the Enumerator ………………………………………………………………………………….

Phone number of Enumerator………………………………………………………….. v. SCPZ:…………………………………………….

State…………………………………………….

LGA……………………………………….

Community…………………………………..

Cluster:………………………………… vi. Interview date: ................................................….../__/__/__/__/__/__/__/__/ (ddmmyyyy) vii. GPS Coordinate: Latitude:…………………………………………………………

Longitude:………………………………………………………

(B)

DEMOGRAPHIC DATA

2.1) Gender

Male ?

2.2) Household Size (Number)

Male members =

Female ? ; Female members =

;Total =

Below 30yrs ?

2.3) Age of Beneficiary/Farmer (Years) 2.4) Highest Education Attained:

Between 31-59yrs ?

Above 60yrs ?

(0) No school at all (3)Tertiary education (5)Quoranic

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(1) Primary

(2) Secondary/TC II

(4) Non-Formal education

CHECKLISTS FOR FABRICATORS 1.

Fabricated equipment extended by ATASP -1

S/N

List of Technologies

How long Participation 1 Source of have you in training been in the Training (Tick) system

Production (Yes = 1, No = 0)

Number Number produced sold

Sorghum: Mechanized 1 thresher 2 Stover crusher 3 Stover chopper Rice: Mechanized 4 weeder 5 Hand planter 6 Rice parboiler Cassava: 7 Cassava presser 8 Cassava sifter Cassava roasting 9 tray Cassava burr 10 grinder Cassava 11 combine dryer 12 Cassava grater 13 Cassava peeler Cassava cabinet 14 dryer 1Source:

ATASP – 1 =1, ADP = 2, NGOs = 3, Other Processors = 4, 5 = Others (Specify)

Other Trainers: 2.

Have you received any other support from ATASP -1? [ ] 1 = Yes [ ] 0 = No …………….………………………………………………………………………………..………………………… ………………………………………………………………………………………………………………………… …………………………………………………………………………………………………………………………

3.

How useful is the support received under ATAP -1? ……………

Code: Very useful = 3, Useful = 2, Not Useful = 1

4.

Patronage and Income from Fabrication Enterprise: i. Did you experience increase in patronage due to ATASP -1 intervention? [ ] 1 = Yes [ ] 0 = No Yield and Technology Adoption Survey

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i.

What was the number of customers per season before ATASP -1 intervention?………………..

ii. What is number of customers per season during ATASP -1 intervention? ………………. iii. What was your average income per season before ATASP -1 intervention? ………………. iv. What is your average income per season during ATASP -1 intervention? …………………….

1.

Has ATASP -1 training improved the quality of your fabrication operation ………………

(1) Excellent (2) Very Good (3) Good (4) Fair (5) Poor

2.

What are the constraints to the production of ATASP -1 fabricated equipment? …………………………………………………………………………………………………………………………………………. …………………………………………………………………………………..…………………………………………………….. ……………………………………………………………………………………….…………………………………………………

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FEDERAL MINISTRY OF AGRICULTURE AND RURAL DEVELOPMENT AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE-1 (ATASP-1) Survey Questionnaire for the Assessment of Adoption of Improved Technologies amongst ATASP -1 Beneficiaries in Nigeria Survey checklists for the assessment of the adoption of improved technologies amongst Processors under ATASP -1 Focus Group Discussion

PROCESSORS QUESTIONNAIRE: (A)

(B)

Background Information i. Questionnaire number…………………………………………………….. ii. Name of Group………………………………………. iii. Name of Processor:…………………………………………………………………..

Phone Number:………………………………………………………………............ iv. Name of the Enumerator ………………………………………………………………….

Phone Number:……………………………………………………………… v. SCPZ:…………………………………………….

State……………………………………………. LGA……………………………………….

Community………………………………….. Cluster…………………………………….

Interview date: ...................................................….../__/__/__/__/__/__/__/__/ (ddmmyyyy) vi. GPS Coordinate: Latitude:…………………………………………………………

Longitude:………………………………………………………

DEMOGRAPHIC DATA

2.1) Gender

Male ?

Female ?

2.2) Household Size (Number)

Male members =

; Female members =

;Total =

Below 30yrs ?

2.3) Age of Beneficiary/Farmer (Years) 2.4) Highest Education Attained:

Between 31-59yrs ?

Above 60yrs ?

(0) No school at all (3)Tertiary education (5)Quoranic

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(1) Primary

(2) Secondary/TC II

(4) Non-Formal education

CHECKLISTS FOR PROCESSORS 1.

Awareness and usage of Processing Technologies extended by ATASP -1 1 Sources of 2Extent of Awareness of awareness Others S/N List of Technologies Technologies usage of of (Specify) (Yes=1,No=2) Technologies technologies Sorghum Harvesting, threshing, cleaning and 1 packaging of sorghum Effective Sorghum drying techniques 2 (i.e of Solar dryer) Storage of Sorghum grains and flour 3 for enhanced shelf life 4 Production of Pop Sorghum Production of Sorghum flour using 5 hammer mill with Cyclone Production of composite flour using 6 Soya bean flour and sorghum flour 7 Other: Specify Rice Seed processing package and storage 1 2

Improved rice processing technology

3

5 6

Production of high quality rice flour Production of rice flour based products Production of rice beverages Production of extruded rice snacks

7

Other: Specify

4

Cassava Processing of Cassava into garri 1 Processing of Cassava and starch 2 Production of Cassava chin -chin and 3 doughnut Production of Cassava/bean crisp and 4 eggroll Other: Specify 5 1 2

Source: ATASP – 1 =1, ADP =2, NGOs =3, Other processors =4, Others (specify) =5 Extent of usage of Technologies: Always = 3, Sometime = 2, Never = 1

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1. What support have you received from ATASP -1? …………………………………………………………………………………………………… …………………………………………………………………………………………………… …………………………………………………………………………………………………… …………………………………………………………………………………………………… …………………………………………………………………………………………………… ……………………………………………………………………………………………………

2. Rate the usefulness of the support received under ATAP -1? ……………

Code: Very useful = 3, Useful = 2, Not Useful = 1 3. What value chain are you involved in? ………………………………………………………………………………………….

4. Output from processing enterprise. ………………………………………………….Kg/Mt 5. What was the level of patronage before ATASP -1 ? ……………………….

Code: Good = 3, Fair = 2, Poor = 1 6. What is the level of patronage after ATASP -1 intervention …………………

Code: Good = 3, Fair = 2, Poor = 1 7. What was the quantity of output processed before ATASP -1 intervention? ……… Kg 8. What is the quantity of output processed after ATASP -1 intervention …………… Kg 9. What was your income per month before ATASP -1 intervention? ……………… Naira 10. What is your income per month after ATASP -1 intervention ………………… Naira 11. What is your perception of the processing technologies extended by ATASP -1 ?

S/N

TECHNOLOGIES

Satisfied

Sorghum Harvesting, threshing, cleaning and packaging of 1 sorghum Effective Sorghum drying techniques (i.e of Solar 2 dryer) Storage of Sorghum grains and flour for enhanced 3 shelf life 4 Production of Pop Sorghum 5

Production of Sorghum flour using hammer mill with Cyclone

6

Production of composite flour using Soya bean flour and sorghum flour

7

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Fairly Not Satisfied Satisfied

Rice 1

Seed processing package and storage

2

Improved rice processing technology

3

Production of high quality rice flour

4

Production of rice flour based products

5

Production of rice beverages

6

Production of extruded rice snacks

7

Waste Management Technique Cassava

1

Processing of Cassava into garri

2

Processing of Cassava and starch

3

Production of Cassava chin -chin and doughnut

4

Production of Cassava/bean crisp and eggroll

5

Waste Management Technique

1. Has the nutritional quality of your processed products improved under ATASP -1?

Yes = 1 [ ] OR No = 0 [ ] 2. What are the constraints to the usage of ATASP -1 Processing technologies? ………………………………………………………………………………………………… ………………………………………………………………………………………………… …………………..…………………………………………………………………………… ……………………………………………………………………………………………..…

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REFERENCES African Agricultural Technology Foundation, AATF (2017).Cassava Mechanization and Agroprocessing Program. Retrieved on 4/11/17 from https://www.aatf-africa.org/CassavaMechanizsation-Agro-Processing-Program African Development Bank (2013). Agricultural Transformation Agenda Support Program – Phase 1 Strategic Environmental and Social Assessment. Retrieved on 10/3/2018 from https://www.afdb.org/fileadmin/uploads/afdb/Documents/Environmental-and-SocialA s s e s s m e n t s / N i g e r i a % 2 0 %20Agricultural%20Transformation%20Agenda%20Support%20Program%20%E2% 8 0 % 9 3 % 2 0 P h a s e % 2 0 1 % 2 0 % 2 8 ATA S P - 1 % 2 9 % 2 0 %20Executive%20SESA%20Summary.pdf African Development Bank (AfDB), (2013). Agricultural Transformation Agenda Support Program Phase 1, Strategic Environmental and Social Assessment.

ATASP-1 (2017).ATASP-1 News, January – March, 2017. Retrieved on 11/3/2018 from http://www.iita.org/wp-content/uploads/2017/05/ATASP-news_Jan-March-2017.pdf Business day (2020). The leading contributing sectors to GDP in 2019: Retrieved on the 11/7/2020 from https://businessday.ng/research-reports/article/the-leadingcontributing-sectors-to-gdp-in-2019/ FAO, (2004).United Nations Food and Agriculture Organization. Retrieved from http://faostat.fao.org.

FAO, (2020). Nigeria at a glance. Retrieved from http://www.fao.org/nigeria/fao-innigeria/nigeria-at-a-glance/en/ Federal Ministry of Agriculture & Rural Development, (2011). Agricultural Transformation Agenda: We Will Grow Nigeria's Agriculture Sector.

Federal Ministry of Agriculture & Rural Development, (2016). Agriculture Promotion Policy 2016-2020, Area 11, FCT, Abuja.

Federal Ministry of Budget and National Planning, (2017).Economic Recovery and Growth Plan, FCT Abuja, Nigeria.

Merem, E. C., Twumasi, Y., Wesley, J., Isokpehi, P., Shenge, M., Fageir, S., Crisler, M., Romorno, C., Hines, A., Hirse, G., Ochai, S., Leggett, S. &Nwagboso, E. (2017).Analyzing Rice Production Issues in the Niger State Area of Nigeria's Middle Belt.Food and Public Health 7(1): 7-22.

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NOTE

Yield and Technology Adoption Survey

NATIONAL OFFICE

No. 15, Lord Luggard Street, Asokoro, Abuja FCT, Nigeria info@atasp1.gov.ng, atasp1_hq@atasp1.gov.ng 08137208947, 08036551491 www.atasp1.gov.ng Facebook/ATASPNigeria Twitter @ataspnigeria

ZONAL OFFICES ADANI-OMOR SCPZ

BIDA-BADEGGI SCPZ

ADP Complex, KM 41, Enugu-Onitsha Express way, Kwata Junction, Awka, Anambra State. a.omor_scpz@atasp1.gov.ng 07081037456

Farm Institute, Ministry of Agriculture and Rural Development, KM 12, Bida-Lemu Express way, Bida, Niger State. b.badeggi_scpz@atasp1.gov.ng, ataspbidazone@yahoo.com 08132756066

KANO-JIGAWA SCPZ

KEBBI-SOKOTO SCPZ

No. 9, Ahmadu Bello Way, Servicom Center, Kano, Kano State. k.jigawa_scpz@atasp1.gov.ng 08036923665, 08052683453

KM 11, Kalgo Junction, Bernin Kebbi-Jega Road, Bernin Kebbi, Kebbi State. k.sokoto_scpz@atasp1.gov.ng, kbsoatasp1@gmail.com 07037777213

PROGRAM PARTNERS: