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PFR SPTS No. 12759

ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results Everett KR, Woolf AB, Burdon JN, Pushparajah IPS, Billing DP, Wohlers MW, Olsson SR, Feng J, Richards KK, Barefoot MD March 2016


Confidential report for: Asociación de Productores de Palta Hass del Perú- ProHass

DISCLAIMER Unless agreed otherwise, The New Zealand Institute for Plant & Food Research Limited does not give any prediction, warranty or assurance in relation to the accuracy of or fitness for any particular use or application of, any information or scientific or other result contained in this report. Neither Plant & Food Research nor any of its employees shall be liable for any cost (including legal costs), claim, liability, loss, damage, injury or the like, which may be suffered or incurred as a direct or indirect result of the reliance by any person on any information contained in this report. LIMITED PROTECTION This report may be reproduced in full, but not in part, without prior consent of the author or of the Chief Executive Officer, The New Zealand Institute for Plant & Food Research Ltd, Private Bag 92169, Victoria Street West, Auckland 1142, New Zealand. CONFIDENTIALITY This report contains valuable information in relation to the ProHass Avocado Multi-Year Fruit Quality Research programme that is confidential to the business of Plant & Food Research and Asociación de Productores de Palta Hass del Perú. This report is provided solely for the purpose of advising on the progress of the ProHass Avocado Multi-Year Fruit Quality Research programme, and the information it contains should be treated as “Confidential Information” in accordance with the Plant & Food Research Agreement with Asociación de Productores de Palta Hass del Perú PUBLICATION DATA Everett KR, Woolf AB, Burdon JN, Pushparajah IPS, Billing DP, Wohlers MW, Olsson SR, Feng J, Richards KK, Barefoot MD. March 2016. ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. A Plant & Food Research report prepared for: Asociación de Productores de Palta Hass del Perú- ProHass Milestone No: 66530. Contract No: 29828. Job code: P/345107/01. SPTS No: 12759. Report approved by: Kerry Everett Scientist, Plant Pathology March 2016 Suvi Viljanen-Rollinson Science Group Leader, Plant Pathology March 2016

This report has been prepared by The New Zealand Institute for Plant & Food Research Limited (Plant & Food Research). Head Office: 120 Mt Albert Road, Sandringham, Auckland 1025, New Zealand, Tel: +64 9 925 7000, Fax: +64 9 925 7001. www.plantandfood.co.nz

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

CONTENTS PART 1. ORCHARD QUALITY EXPERIMENTS ......................................................................... 1 Part 1. Executive summary ........................................................................................................ 2 Overview of experiments ............................................................................................................ 8 1

Summary of Methods ..................................................................................................... 8 1.1 Methodology ............................................................................................................ 8 1.2 Comments on methodology ................................................................................... 11

2

Year 1 (2013) .................................................................................................................. 13 2.1 Comparison of results from different orchards ...................................................... 13 2.2 Overall discussion of experimental results ............................................................ 13 2.3 Management practices recommended for orchard C3 only .................................. 15 2.4 Causes of quality issues ........................................................................................ 15 2.5 Conclusions and recommendations ...................................................................... 15

3

Year 2 (2014) .................................................................................................................. 16 3.1 Black spot .............................................................................................................. 16 3.2 Lenticel damage .................................................................................................... 19 3.3 Postharvest rots ..................................................................................................... 21 3.4 Grey pulp ............................................................................................................... 23 3.5 Other postharvest disorders .................................................................................. 23 3.6 Dry matter and oil accumulation in different climatic zones in Peru ..................... 24 3.7 Conclusions and recommendations ...................................................................... 24

4

Year 3 (2015) .................................................................................................................. 31 4.1 Black spot .............................................................................................................. 31 4.2 Lenticel damage .................................................................................................... 31 4.3 Postharvest rots ..................................................................................................... 31 4.4 Grey pulp ............................................................................................................... 32 4.5 Other postharvest disorders .................................................................................. 32 4.6 Dry matter and oil accumulation in different climatic zones in Peru ...................... 32 4.7 Conclusions and recommendations ...................................................................... 32

Individual Experiments ............................................................................................................. 36 5

Experiment 3.3 Fungal isolations and phylogenetic analysis .................................. 36 5.1 Aim ......................................................................................................................... 36 5.2 Introduction ............................................................................................................ 36 5.3 Methodology .......................................................................................................... 36 5.4 Results ................................................................................................................... 40

6

Experiment 4.1. Controlled Atmosphere Storage ...................................................... 52 6.1 Aim ......................................................................................................................... 52 6.2 Introduction ............................................................................................................ 52 6.3 Scientific paper ...................................................................................................... 52

7

Experiment 4.2 Grey pulp susceptibility (Library trays) ........................................... 61 7.1 Aim ......................................................................................................................... 61 7.2 Procedures ............................................................................................................ 61 7.3 Results ................................................................................................................... 62

8

References ..................................................................................................................... 64

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Appendix 1.1. General Experimental Design and Assessment protocol ........................... 66 Appendix 1.2. Statistical analyses .......................................................................................... 76 Appendix 1.3. Detailed Protocols for Orchard Quality Experiments ................................... 77 PART 2. DRY MATTER AND MATURITY OF PERUVIAN AVOCADOS ............................... 116 Part 2. Executive summary .................................................................................................... 117 9

General Introduction ................................................................................................... 119

Summary of last season’s work (2014) ................................................................................. 121 10

Trial 5.1. Changes in dry matter over time ............................................................... 121

11

Trial 5.2. Effect of fruit size on dry matter ................................................................ 121

12

Trial 5.3. Effect of maturity on storage and fruit quality ......................................... 121

13

Trial 5.4. Individual fruit dry matter ........................................................................... 122

14

Trial 5.5. Correlation of oil content with dry matter ................................................ 122

This season’s work (2015) ...................................................................................................... 122 15

General methods ......................................................................................................... 123

16

Trial 5.1. Changes in dry matter over time ............................................................... 124 16.1 Introduction ........................................................................................................ 124 16.2 Aim .................................................................................................................... 125 16.3 Methodology ...................................................................................................... 125 16.4 Results and discussion ...................................................................................... 125 16.5 Conclusions and recommendations .................................................................. 128

17

Trial 5.2. Effect of fruit size on dry matter ................................................................ 130 17.1 Introduction ........................................................................................................ 130 17.2 Aim .................................................................................................................... 130 17.3 Methodology ...................................................................................................... 130 17.4 Results and discussion ...................................................................................... 130

18

Trial 5.3. Effect of maturity on storage and fruit quality ......................................... 132 18.1 Introduction ........................................................................................................ 132 18.2 Aim .................................................................................................................... 132 18.3 Methodology ...................................................................................................... 132 18.4 Results and discussion ...................................................................................... 133

19

General discussion ..................................................................................................... 135 19.1 Conclusions and recommendations .................................................................. 135

20

References ................................................................................................................... 136

Appendix 2.1. Final protocol for maturity trial ..................................................................... 138 Appendix 2.2. Graphs of dry matter values for each Peruvian avocado orchard over the 2015 season (Trial 5.1) ............................................................................................. 148 Appendix 2.3. Graphs for effect of Peruvian avocado fruit size on dry matter (Trial 5.2) .................................................................................................................................. 151

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

PART 1. ORCHARD QUALITY EXPERIMENTS

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

PART 1. EXECUTIVE SUMMARY Orchard Quality Experiments Everett KR, Woolf AB, Burdon JN, Pushparajah IPS, Billing DP, Wohlers MW, Barefoot MD 2 1

Plant & Food Research, New Zealand Plant & Food Research, USA

2

March 2016

Introduction ProHass commissioned The New Zealand Institute for Plant & Food Research Limited to design and analyse trials to be conducted by orchards throughout the climatic zones of Peru. These trials would identify and investigate several postharvest quality problems (black spot, lenticel damage and stem-end rots), and determine optimal harvest maturity indicators. This report summarises the results of trials on postharvest quality issues conducted by 11 orchards over the 2013, 2014 and 2015 avocado seasons. Aim To identify the cause(s) of lenticel damage and black spot, and to determine management practices that ameliorate these disorders and also stem-end rots. Summary of experiments Experiments were designed to determine the effect of several factors on the incidence and severity of black spot and lenticel damage on ‘Hass’ avocados grown in Peru. Those factors were identified during a preliminary examination of the data and avocado growing systems, and from experiments conducted by orchard C3 during the 2012 season. The experiments aimed to determine the effect of dehydration on incidence and severity of black spot and lenticel damage by: 1.1 Turning off irrigation in the orchard for periods of several hours to several days (dependent on soil type) prior to harvest 1.2 Harvesting fruit at two or three different times during the day 2.1 Keeping fruit in different holding conditions for 24 hours after harvest 2.2 Pre-cooling fruit at different temperatures (3, 6 and 9°C) and duration (3, 6 and 9 h) after packing and prior to storage. Black spot may have been caused by fungal pathogens. To investigate this hypothesis, three other experiments were conducted: 3.1. Postharvest treatment with fungicides 3.2. Fungicide spray trial in the orchard 3.3. Isolations from black spot symptoms.

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To investigate the effect of different controlled atmosphere conditions (CA) on Peruvian fruit, a series of CA trials were conducted. 4.1 Controlled atmosphere trials The quality issues of ‘run of crop‘ (commercial) fruit were also evaluated by examining the quality of fruit during 6 weeks of coolstorage: 4.2 Library trays (Grey pulp susceptibility) Results Year 1 (2013)  Four companies conducted trials during the latter part of the avocado season in 2013.  Black spot and lenticel damage were unrelated, disproving the hypothesis that black spot was caused by a severe collapse of lenticels damaged during harvesting.  There was a strong relationship between fruit weight (as an indicator of turgidity) and lenticel damage. Higher fruit weight (more turgidity) resulted in more lenticel damage.  Fruit harvested from irrigated trees showed more severe symptoms of stem-end rots and grey pulp.  Fruit harvested from irrigated trees first thing in the morning were less affected by lenticel damage than those harvested later in the day.  Fruit harvested on consecutive days showed that the incidence of black spot was strongly positively related to maximum humidity and wind velocity. Almost all the variation in the data (R2 = 96%) was able to be explained by these two variables.  It is possible that wind movement of adjacent leaves, twigs and fruit damaged the fruit surface, allowing access to fungal pathogens or damaging tissue that physically collapsed in the coolstore. Movement of sand to directly damage the fruit or contaminate the picking bins and bags is also possible; wind velocities of up to 14.5 km/h were recorded. Because high humidity facilitates fungal spore germination and penetration of fruit, it is possible that the cause of black spot is a fungal pathogen and the wind may simply have been aiding dissemination of the fungal spores onto the fruit in foggy conditions.  Fruit stored in open-sided sheds in the orchard had less lenticel damage than any other treatment. However, stem-end rots were significantly more severe in fruit stored in this way than in fruit placed immediately in the coolstore. Both stem-end rots and lenticel damage were reduced by storage in a refrigerated receiving area in the main packhouse.  Black spot severity was related to temperature in the pre-cooler, and was significantly more severe when fruit was pre-cooled at 3°C than all other treatments. Grey pulp and stem-end rots were most severe when fruit was pre-cooled at 9°C. A pre-cooler temperature of 6°C resulted in fruit with the best overall quality. Year 2 (2014)  Experiments were conducted by 11 avocado growing companies in Peru. Black spot  Black spot was found on 5% or less of the fruit from all participating orchards except for C1. On this one orchard, black spot affected 20% of the evaluated fruit, and was associated with the fungus Cladosporium.  There were at least three different symptom types described as black spot: [3]

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 Nodule damage (caused by physical injury)  Fuzzy blotches (associated with a fungus)  Blotches with sharp borders (associated with chilling injury).  Nodule damage can be reduced by ensuring roads in the orchard and between the orchard and the packhouse are smooth, that the fruit dump onto the packing line is as gentle as possible, and that there are no drops, impacts or sharp turns on the packing line  Fuzzy blotches may be able to be reduced by:  Postharvest application of a fungicide (e.g. prochloraz)  Placing fruit in the coolstore immediately after harvest  Blotches with sharp borders can be reduced by:  Determining the correct storage temperature for Peruvian fruit from different regions, if it is not already known  Strictly adhering to the correct storage temperatures for Peruvian fruit, by using temperature probes with alarms and by regular maintenance of chillers, refrigerated trucks and containers. Assessments

Lenticel damage, nodule damage, chilling injury and ‘fuzzy’ black spot should be clearly and reliably distinguished.

Industry-produced posters and evaluation guidelines should be distributed to all packhouses for use by quality control managers.

If there is a problem on arrival in the marketplace, high-resolution single-fruit photographs of affected fruit should be sent to a trained evaluator.

Clear separation of these symptom types should enable the appropriate remediation method to be used.

Lenticel damage  Lenticel damage was common on all orchards, and affected 79-99% of Peruvian fruit in these experiments.  Lenticel damage can be reduced by:  Turning off irrigation before harvest

Harvesting fruit later in the day.

Stem-end rots

Stem-end rots were present in 23% of ripened, coolstored fruit in these experiments, and are likely to cause issues with consumers in the marketplace.

Postharvest application of a fungicide (e.g. prochloraz, thiabendazole (TBZ)) will reduce the incidence of stem-end rots: a. b.

[4]

Fungicides should be applied immediately after the fruit arrive in the packing shed, preferably within 24 hours of harvest Maximum Residue Limits (MRLs) appropriate for the intended market need to be strictly met

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c.

Postharvest dipping of bins of fruit by immersing the bin in a tank as soon as it arrives in the packing house is the most effective way of applying fungicides. The fungicide needs to be regularly replenished to prevent ‘stripping’ as more fruit pass through the dipping solution.

 

Placing fruit in the coolstore immediately after harvest will reduce postharvest rots.

Shortening the time for fruit to ripen, e.g. by ethylene treatment, will reduce postharvest rots.

Application of copper fungicides in the orchard at monthly intervals should reduce postharvest rots.

Grey pulp Grey pulp symptoms were more prevalent with longer storage. The time to expression may best be delayed by the use of controlled atmosphere storage (CA). Year 3 (2015)  Eight companies conducted avocado research during this season, but not all companies conducted all the experiments. Black spot  Black spot occurrence was too low for analysis except for orchard C1.  Fruit harvested from trees that were not irrigated showed significantly less black spot than those from irrigated trees, in contrast to the results from the previous year’s experiment (2014). It is possible that this type of black spot was severe lenticel damage.  There was no significant reduction of black spot following application of fungicides compared with controls This suggests that any fungi associated with black spot symptoms are present as secondary invaders, and that the primary cause is physiological. . Lenticel damage  Lenticel damage was generally more severe on fruit harvested from irrigated trees than from trees that were not irrigated, confirming the hypothesis that lenticel damage is more severe on turgid fruit.  For irrigated trees, the best time to harvest fruit in order to minimise lenticel damage was generally at midday. For fruit from non-irrigated fruit, the pattern was different for each orchard, presumably because of different soil types, and possibly climatic factors. For two of the four companies fruit was less affected by lenticel damage when harvested later in the day, presumably without irrigation the fruit lost water during the day and became increasingly less susceptible to lenticel damage.  The fruit weights did not seem to accurately reflect the water status of the fruit. It is unlikely that differences of 30 to 90 g between the lightest and heaviest fruit weights were solely due to water uptake or loss. This measure of turgidity of fruit is not reliable unless the same size fruit are harvested at each time. An easier measure such as dry weight/fresh weight ratios may determine turgidity more accurately.

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Postharvest rots  Stem-end rots were significantly more severe in fruit harvested in the morning, as was lenticel damage, for C2 and C10. For these orchards, harvesting at 8 am in the morning should be avoided.  Generally, turning off the irrigation did not affect postharvest rots.  Postharvest application of prochloraz significantly reduced the severity of body rots for one orchard (C7).  Applying copper on trees in the orchard resulted in a significant reduction of stem-end rot severity for one orchard (C1).  Because postharvest assessments were not carried out correctly, the apparent lack of control of rots by postharvest and orchard fungicide applications by several orchards is not an indication that the method has failed. Instead, the control of rots by two orchards is a remarkable result, and shows the efficacy of these solutions despite the use of incorrect procedures for assessing rots. Grey pulp  On orchard C2, grey pulp was less severe when fruit were harvested late in the day.  Fruit from orchard C1 was significantly less affected (both incidence and severity) by grey pulp when treated postharvest with prochloraz than were water treated controls. This is an odd result, and may be due to incorrect categorisation of body rots as grey pulp. Whatever the reason, application of prochloraz was shown to be effective at improving postharvest quality of avocado fruit from this orchard.  There was no effect of orchard application of fungicides on grey pulp. Other postharvest disorders There were no effects on the other disorders, except for vascular browning for the postharvest fungicides treatment for one orchard. All treatments, including water, increased the severity of vascular browning. This could be an anomaly due to the assessment methodology used. Controlled atmospheres (CA)  The effect of four CA regimes on fruit quality was examined: 2% O2 / 2% CO2; 2% O2 / 10% CO2; 4% O2 / 6% CO2; and 4% O2 / 10% CO2.  Fruit ripened c. 2 days later in high CO2 atmospheres  For the fruit used in the trial, there was little difference between the four CA regimes in their impact on the quality of the fruit after storage and when ripe. Recommendations and Conclusions  Lenticel damage is exacerbated by fruit turgidity, which has been shown for each of the three years of this study.  Black spot and lenticel spot are unrelated, which means that black spot is not affected by high fruit turgidity resulting from irrigation.  Black spot is exacerbated by low temperatures, pointing to skin injury or a fungal pathogen as possible causes. Low temperatures may damage the skin directly to cause these symptoms, or damaged symptomless skin could allow entry to a fungal pathogen resulting in these symptoms.  The fungus Cladosporium sp. was associated with black spot symptoms, but postharvest application of fungicides did not convincingly control this disorder. It is more likely that

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

black spot is due to chilling injury that is exacerbated by damage to the skin in the orchards during periods of high wind. Damage by sand abrasion on trees is possible, but sand may also be blown into the picking bins and damage the fruit during the packing process (like rubbing with sandpaper). Ensuring that picking bins in the orchards are lined and covered to prevent the entry of wind-blown sand may help alleviate this issue. It is also important to ensure that the fruit are not subject to temperatures likely to cause chilling injury. Correct diagnosis of the ‘black spot’ symptom will also help alleviate the problem. Some ‘black spot’ may instead be lenticel damage, or nodule damage. These latter two disorders can be remediated by, respectively, turning off the irrigation before harvest, and by ensuring that the fruit are treated as gently as possible during picking, transport, and packing. Body rots and stem-end rots have consistently been the most common disorders of ripened fruit during the three years of this study. For general improvement of the quality of Peruvian avocados, an effective orchard fungicide programme needs to be designed and tested. Applying fungicides in the orchard is less likely to endanger market access due to residue issues. However, the postharvest assessment methodology needs to be strictly adhered to ensure good results from fungicide trials. So far the Peruvian companies have not been able to conduct consistently good postharvest assessments. Intensive training is required, and/or appointment of a dedicated technician on each orchard whose only job is to assess fruit postharvest, and who is available for weekend work when necessary. Further trial work on the best practice for fungicide application will be severely compromised if the assessments continue to be conducted incorrectly. Grey pulp symptoms were more prevalent with longer storage. The time to expression may best be delayed by the use of controlled atmosphere storage (CA).

This study has identified issues for Peruvian avocado fruit that are likely to cause problems in the marketplace, and has provided recommendations for practices to mitigate these issues. More specific recommendations for better management practices and suggestions for continued research in a number of areas can be found in more detail in Sections 2–4 of this report.

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Overview of experiments 1

SUMMARY OF METHODS

1.1

Methodology

Four experiments aimed to determine the effect of dehydration on incidence and severity of black spot and lenticel damage, by: 1.1.

Turning off irrigation in the orchard for periods of several hours to several days (dependent on soil type) prior to harvest

1.2.

Harvesting fruit at three different times during the day on up to three consecutive days

2.1.

Keeping fruit in different holding conditions for 24 hours after harvest (field shed, packhouse reception at 15°C, packhouse reception at ambient) and comparing with placing fruit in the coolstore immediately after harvest

2.2.

Pre-cooling fruit with air at different temperatures (3, 6 and 9°C) and duration (3, 6 and 9 h) after packing and prior to storage.

Black spot may have been caused by fungal pathogens. To investigate this hypothesis, three other experiments were conducted: 3.1.

Postharvest treatment with fungicides (prochloraz, chlorine dioxide, thiabendazole (TBZ))

3.2.

A fungicide spray trial in the orchard was conducted

3.3.

Isolations from black spot symptoms followed by DNA analysis.

4.1.

The effect of different controlled atmospheres on fruit quality was investigated.

The quality issues of ‘run of crop’ (commercial) fruit were also evaluated by examining the quality of fruit during 6 weeks of coolstorage by taking library trays: 4.2

Library trays (Grey pulp susceptibility)

These orchard experiments were conducted by 11 companies situated throughout the avocadogrowing climatic zones of Peru (Table 1.1, Figure 1.1.).

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Figure 1.1. The location of the avocado orchards that participated in the experiments in Peru.Avocado symbols are adjacent to the regions where experiments were conducted.

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Table 1.1. List of Peruvian avocado companies and participants by experiment, 2013–15. Company code

Experiment number

2013 1.1

1.2

C2

+

+

C3

+

+

C4

+

+

C6

+

+

2.1

2.2

+

+

3.1

3.2

3.3

4

+

2014 1.1

1.2

2.1

C1

+

+

+

C2

+

+

C3

+

C4

+

C5

+

C6

+

3.3

4

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

C7

+

+

+

C8

+

+

+

+

2.2

+

3.1

+

3.2

+

C9 C10

+

+

+ +

+

+

+

+

C11

+

2015 1.1 C1 C2

1.2

2.1

2.2

3.1

3.2

3.3

+

+

+

C3

+

C4 +

C6

+

C7

[10]

+ +

C5

C10

4

+ + +

+

+

+

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+


ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

The experiments were conducted during the 2013-15 avocado seasons from March to September (Table 1.2). Table 1.2. The time of harvest for avocado fruit from Peruvian orchards from the different regions participating in the experiments. Month when experiments were conducted 2013 Orchard

March April

May

June

July

August

Septem ber

July

August

Septem ber

August

Septem ber

C3 C4 C6 C2 2014 Orchard

March April

May

June

March April

May

June

C7 C3 C8 C1 C4 C10 C3 C6 C2 C5 2015 conducted Orchard

July

C7 C3 C1 C10 C6 C2 C5

1.2

Comments on methodology

1.2.1

Weight

Fruit were weighed to assess water status. The assumption was made that when the irrigation was turned off for several days, the fruit from these trees should weigh less than fruit from irrigated trees. Although this method worked well when fruit were weighed before and after treatment (Experiments 2.1 and 2.2), and in one previous orchard experiment, it was not always applicable to fruit measured at harvest because of the relatively large inherent variability in fruit weight. Every effort needs to be made to harvest fruit that are of the same size, or to weigh all the fruit in the experiment. Fruit also need to be weighed as soon as possible after removal from the tree, and harvested into sealed plastic bags to minimise water loss until the fruit are weighed. However, it may be necessary to use alternate, more precise methods for an accurate evaluation of fruit water status in the orchard.

[11]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

1.2.2

Postharvest assessments

It is extremely important that fruit are assessed as soon as they become ‘eating ripe’. This is because the severity and incidence of rots and some other disorders (e.g. grey pulp) are affected by ripeness of the fruit when it is assessed. Variability in fruit ripeness at assessment can obscure treatment effects. Because postharvest assessments were often not conducted on optimally ripe fruit, further analysis was not always conducted.

[12]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

2

YEAR 1 (2013)

2.1

Comparison of results from different orchards

Some orchards did not collect all the requested data, which made analysis either not possible or difficult. There were some results that were difficult to interpret that could have been because of confusion between lenticel damage symptoms and black spot. These two symptom types are illustrated and described in Everett et al. (2008). The ‘measles’ symptom described in Everett et al. (2008) shows a ‘fuzzy’ edge and is similar to black spot. The irrigation that was turned off either did not affect fruit weight, or fruit weight was affected in the opposite pattern to what was expected. This way of determining water loss depended on fruit of the same size being harvested, and was technically difficult. Other ways of determining fruit water content could be considered for future experiments.

2.2

Overall discussion of experimental results

Because of the reasons itemised above, only the results from C3 are discussed for Experiment 1.1 and 1.2. Results from C3 and C6 are discussed for Experiment 2.1, and only C3 conducted Experiment 2.2.

2.2.1

Experiment 1.1 Effect of fruit water status – irrigation

There was a strong relationship between fruit weight at different times during the day and lenticel damage. Fruit weight is an indication of hydration, and for both irrigated and nonirrigated trees fruit lost weight (water) during the day falling to a minimum weight at 12pm, then recovered weight towards the end of the day. This relationship was also strongly related to solar radiation and evapotranspiration. Solar radiation would have been expected to drive transpiration and thus water loss, and is the expected reason for the strong relationship between solar radiation, evapotranspiration and weight. The strong relationship between fruit weight and lenticel damage confirms earlier laboratory work (Everett et al. 2008) that lenticel damage is associated with degree of turgidity (hydration) of avocado fruit. It also confirms the results from last season (2012) on the same orchard (Everett et al. 2013). In contrast to last season (2012), black spot symptoms were expressed in the fruit during storage, and it is now clear that black spot and lenticel damage are unrelated. This disproves the hypothesis that black spot is caused by a severe collapse of lenticels damaged during harvesting on this orchard (C3). Despite a lack of evidence that turning off the irrigation had an effect on fruit hydration, fruit harvested from irrigated trees showed more severe symptoms of stem-end rots and grey pulp. A further season’s data will provide confirmation or otherwise of this effect.

2.2.2

Experiment 1.2 Effect of fruit water status – harvest time

Fruit harvested from irrigated trees were less affected by lenticel damage when harvested first thing in the morning than later in the day. Overall, fruit from irrigated trees were heavier at the end of the day, confirming our findings that lenticel damage is more severe on turgid fruit. [13]

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Fruit harvested on consecutive days showed different amounts of black spot that was strongly related to maximum humidity and wind velocity. Almost all the variation in the data was able to be explained by these two variables. It is possible that wind movement of adjacent leaves, twigs and fruit damaged the fruit surface, allowing access to fungal pathogens or damaging tissue that physically collapsed in the coolstore. Movement of sand to directly damage the fruit or contaminate the picking bins and bags is also possible; wind velocities of up to 14.5 km/h were recorded. Studies on susceptibility to citrus canker have shown that wind can directly damage leaf tissue, resulting in a higher incidence, and that sand abrasion doubles the incidence (Bock et al. 2013). Because high humidity facilitates fungal spore germination and penetration of fruit (Estrada et al. 2000), it is possible that the cause of black spot is a fungal pathogen and the wind may simply have been aiding dissemination of the fungal spores onto the fruit in foggy conditions. Before conclusions can be made concerning the cause of black spot in the orchard, this same result needs to be achieved in different seasons, and further evidence is required. Isolations need to be made from black spot symptoms, as planned, to determine whether there are fungi consistently associated with the symptoms. The planned postharvest fungicide dipping trials and on orchard spray trials should also help determine if black spot has a fungal cause and, if so, provide management tools to reduce the incidence of this disorder.

2.2.3

Experiment 2.1 Effect of holding fruit after harvest on quality

Fruit stored in open-sided sheds in the orchard (C3) had less lenticel damage than any other treatment although the difference was only a rating of 0.5 lower than fruit placed directly into coolstore, and the difference was not significantly different from the refrigerated area of the packhouse. However, stem-end rots were significantly more severe in fruit stored in this way than in fruit placed immediately in the coolstore. Stem-end rots were also most severe for the equivalent storage regime at C6, but lenticel damage was not assessed. A similar result was achieved for C3 during 2012 (Everett et al. 2013), lenticel damage was least severe for fruit stored in the open-sided shed in the orchard before placement in the coolstore than all other treatments. As found in 2012, no significant incidence of black spot was observed. Overall, the fruit quality was maintained best by storing the fruit in the refrigerated receiving area in the main packhouse (particularly for grey pulp – 3% lower than control). Results from AGK showed that using this storage method resulted in an equivalent degree of lenticel damage to open-sided sheds, and fruit from both C3 and C6 had either the lowest, or second lowest, incidence and severity of stem-end rots when stored in this way. However, because the fruit were harvested by C3 on two different occasions, the robustness of the results needs to be confirmed by a further year’s experimentation when fruit are weighed both before and after placement in the different holding environments (to determine weight loss during the holding period), and fruit for all four treatments are harvested at the same time.

2.2.4

Experiment 2.2 The effect of pre-cooling on quality

In this experiment, black spot was related to temperature in the pre-cooler, and was significantly more severe when fruit was pre-cooled at 3°C than all other treatments. Grey pulp and stemend rots were most severe when fruit was pre-cooled at 9°C. A pre-cooler temperature of 6°C resulted in fruit with the best overall quality.

[14]

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It is possible that the fruit pre-cooled at 3°C was damaged by the low temperature. Further investigation is required to determine if fungal pathogens cause or exacerbate black spot symptoms, or whether these symptoms are caused by chilling injury in this instance. Whatever the reason, cooling fruit more rapidly resulted in better quality (fewer stem-end rots and less grey pulp), and the pre-cooler should be set to a temperature of 6°C to maintain the best overall fruit quality.

2.3

Management practices recommended for orchard C3 only

 Fruit from well irrigated trees should be harvested early in the day to minimise lenticel damage  Fruit should be stored in the refrigerated receiving area in the main packhouse immediately after harvest for 24 hours prior to placing in the coolstore to maintain best overall quality  Fruit should be pre-cooled at 6°C before placement in the coolstore for maintenance of best overall quality, and a duration of 6 h seems to be the most effective.

2.4

Causes of quality issues

 Lenticel damage is exacerbated by turgidity  Black spot and lenticel spot appear to be unrelated, which means that black spot is not affected by turgidity (irrigation)  Black spot is exacerbated by wind and high humidity, pointing to possible skin injury facilitated by wind, sand and/or a fungal pathogen as the cause  Black spot is exacerbated by low temperatures, pointing to skin injury or a fungal pathogen as possible causes. Low temperatures may damage the skin directly to cause these symptoms, or damaged symptomless skin could allow entry to a fungal pathogen resulting in these symptoms.

2.5

Conclusions and recommendations

There were very good practical outcomes from trials this year that can either be immediately applied to improve fruit quality, or that have helped elucidate the causes of fruit quality issues such as lenticel damage and black spot. Knowledge of the factors that exacerbate these two problems will enable practical management solutions to be devised and applied. However, the results from only one orchard (C3) were of sufficient quality to be comprehensively analysed and that means that any change of practice can only be confidently recommended for that one orchard.

[15]

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3

YEAR 2 (2014)

3.1

Black spot

One of the aims of the current study was to investigate the cause of ‘black spot’ symptoms, which may be due to physiological and/or biological factors. Black spot was not reported from any of the experiments on three orchards (C6, C7, C10), and on only six out of 2800 fruit for C8. C10 and C8 did not report black spot in library trays (Experiment 4), whereas C5 and C3 did (Table 1.3). Fruit with symptoms of black spot were supplied from orchards C1, C2, C3, C4, C5, C6, C8, C9 and C11 for Experiment 3.3 (isolation from symptoms).

3.1.1

Results of isolations

There were at least three different symptom types of ‘black spot’ (Figure 1.2) submitted for isolations conducted in July 2014 (Experiment 3.3). 1. Damaged nodules (brown sunken lesions on protuberances) 2. External chilling injury (blotches with sharp borders; ‘discrete skin discolouration’ – Page 32–33 of White et al. (2009) 3. Blotches with fuzzy borders; ‘measles’ of Everett et al. (2008), external rots – Page 26–27 of White et al. (2009). Because of this degree of complexity, the results were difficult to interpret. It is likely that the ‘black spot’ had occurred at different times under different conditions with potentially different causes, even on the same orchard. It is therefore important that the Peruvian avocado industry becomes very familiar with the different symptom types, so that appropriate measures can be taken to limit damage. Damaged nodules appeared to be a common problem on fruit from all orchards. Modifications to the harvesting procedures may avoid this issue. For instance, ensuring that the roads on which the fruit are transported are smooth without unnecessary bumps, that the means of offloading the fruit onto the packing line are as gentle as possible, and that there are as few drops or impacts as possible in the packing lines. Chilling injury occurs when the fruit are cooled to a temperature that is too low (generally less than 3°C; White et al. 2009). This critical temperature for fruit may change during the season, and may be different for fruit from different climatic zones. Therefore the ideal storage temperatures for Peruvian avocados from different climatic zones may need to be determined, or rigorously adhered to by using temperature probes and alarms.

[16]

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Blotches with fuzzy borders. For two orchards (C1 and C4), there were more isolations of the fungus Cladosporium from surface-sterilised black spot-affected tissue than there were from adjacent ‘green’ tissue on the same fruit. There was no difference of numbers of fungal isolations from black spots and green tissue for fruit from the other sampled orchards (C2, C3, C5, C6, C8, C9 and C11). This evidence from isolations suggests that black spot on fruit from two orchards that conducted trials (C1 and C4) may be associated with a fungal pathogen (Cladosporium cladosporioides) (Table 1.4).

a)

b)

[17]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

c) Figure 1.2. Symptoms of a) damaged avocado fruit nodules (brown sunken lesions on protuberances), b) chilling injury (blotches with sharp borders) and c) blotches (fuzzy borders).

Identification by culture morphology was confirmed by DNA sequence analysis. The symptom type that was more common on fruit from these orchards was of blotches with fuzzy borders, but this symptom was also found on fruit from C3. Cladosporium has been reported to cause decay or surface moulds on melons (Suslow et al. 1997), but elsewhere the primary cause was attributed to physical or chilling injury, and colonisation by Cladosporium was as a secondary invader (Zitter et al. 1996). Its status on avocados in Peru is not known. It would require testing Koch’s Postulates (Agrios 1997) to determine if Cladosporium was a pathogen of avocado.

3.1.2

Results from orchard experiments

Black spot A common feature for all the experiments conducted in Peru (1.1, 1.2, 2.1, 3.1, 4.1) was that black spot symptoms generally took 28 days to appear on fruit in the coolstore, although occasionally symptoms were apparent after 10–14 days. This delay in symptom expression may have been due to growth of fungi that latently infected fruit in the orchard, and/or that damage was caused by chilling injury during coolstorage. Black spot on fruit from orchards C1 and C4 When the fruit from C1 were stressed by stopping the irrigation before harvest (Experiment 1.1), the black spot was more severe. It was also more common in fruit harvested in the afternoon than early in the day (Experiments 1.1 and 1.2). This pattern was the opposite from that observed with lenticel damage, which decreased in severity when fruit were harvested later in the day. There was no effect of different holding environments on black spot incidence (Experiment 2.1). Fruit from another orchard (C4) with black spot symptoms associated with a fungal pathogen (from the results of isolations) had a very low incidence of black spot in Experiment 1.1 (turning off the irrigation) and Experiment 2.1 (holding environment). Because of this, the differences between treatments could not be analysed.

[18]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Black spot on fruit from orchards C2, C3, C5, C8, C9 and C10 Black spot on some of the other participating orchards was not affected by turning off the irrigation (C2, C3, C5) (Experiment 1.1), or by time of harvest (C2, C3) (Experiment 1.2). C9 did not participate in any orchard experiments and C5 did not participate in Experiment 1.2. There was no black spot on fruit from C8 in Experiments 1.1 or 1.2. There were too few fruit with black spot symptoms for analysis from orchards C2, C3, C7, C8, and C10 participating in Experiment 2.1 (holding environment). Black spot symptoms were not observed on fruit in the pre-cooling Experiment 2.2.

3.2

Lenticel damage

Usually lenticel damage increased in both incidence and severity during coolstorage, but, in contrast to black spot symptoms, lenticel damage was always present even when fruit were assessed after 4 days. Lenticel damage severity was significantly lower on fruit from trees on which the irrigation was turned off before harvest (Experiment 1.1) to at least some degree on fruit for six of the 10 experiments (C1, C2, C4, C5, C8 and C10). Lenticel damage was generally less severe when fruit were harvested later in the day in Experiment 1.1 on orchards C1, C2, C3 (early and late), C4, C6 and C7. Fruit harvested later in the day in Experiment 1.2 had less lenticel damage on orchards C1, C8 and C10. The interaction between day and time of harvest was significant for orchards C4 and C10; there was less lenticel damage on fruit harvested later in the day from those two orchards. The interaction between time during the day of harvest and day of harvest was significant for orchard C6, but the time of harvest that lenticel damage was least severe was variable. A lower water content might be expected for fruit harvested from trees that were not irrigated, and for fruit harvested later in the day on trees that were not irrigated. Therefore fruit from trees that were not irrigated were likely to be less turgid and, in the absence of irrigation for those trees, the water content of those fruit is likely to decrease during sunlight hours because of evapotranspiration. Thus lenticel damage was less severe on fruit that were probably less turgid, confirming this same result from laboratory experiments (Everett et al. 2008). However, for Experiment 1.2, the severity of lenticel damage was not consistently related to the time of day at which the fruit were harvested for C2, C3 (early and late), and C6. This may be because of a greater holding capacity of soil types on these orchards, or because of irrigation timing. From results of this experiment, fruit from orchard C2, C3 (late) and C6 could be harvested at any time during the day with little effect on lenticel damage, and fruit from C3 (early) harvested in the middle of the day showed the least severe lenticel damage. In practice these results would need to be applied to harvesting fruit from these orchards when the irrigation is not turned off. Fruit from two orchards (C1, C4) placed directly into the coolstore showed the least severe lenticel damage compared with that in the other holding environments, similarly to results for postharvest fruit rots. Black spot on fruit from these orchards yielded Cladosporium in Experiment 3.3. It is therefore possible that this type of lenticel damage may be associated with a fungus. Isolations from these symptoms would be required to resolve the cause of this type of ‘lenticel damage’. [19]

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Holding fruit in the packinghouse reception area for 24 hours after harvest resulted in the least lenticel damage for fruit in three of the eight orchards on at least one assessment date (C2, C6, C7). Because lenticel damage has been shown to be less in dehydrated fruit (Everett et al. 2008), it is possible that holding fruit in the packinghouse reception area may have resulted in greater water loss than in the other holding environments, leading to this result. This hypothesis was not upheld by the results for fruit from C7, where weight loss was not consistently related to lenticel damage severity. Technicians at orchards C2 and C6 did not weigh the fruit. Placing fruit from all the remaining orchards except C5 (C1, C3 (early and late), C4, C8 and C10) into the coolstore immediately after harvest resulted in the least lenticel damage. There were no significant differences between treatments for fruit from orchard C5. The differences in lenticel damage severity between fruit placed directly in the coolstore and the other treatments showing the most severe lenticel damage ranged from 0.2 (C3 early and late), 0.6 (C8), 1.2 (C10), 1.6 (C4) to 1.7 (C1). The fruit should have been ‘jostled’ before being placed directly in the coolstore, but if they were not, this could explain some of the large differences in lenticel damage severity between fruit placed directly in the coolstore and those in other holding environments. If symptoms were caused by a fungus, placing fruit in the coolstore could have inhibited spore germination, leading to less infection. Isolations from the ‘lenticel damage’ symptom that was remediated by placing fruit directly into coolstorage might resolve the cause of this symptom type. Lenticel damage was significantly affected by temperature in the pre-cooler (Experiment 2.2), and was least severe at 9°C compared with at 3°C and 6°C. There was no significant effect due to weight loss or time in the pre-cooler. Based on our results this season (2014) and last (2013) the weight loss component of pre-cooling did not affect lenticel damage, and although the effect of temperature on lenticel damage was not large, a temperature of 9°C may be a better temperature for using in the pre-cooler than 6°C. Effect of postharvest fungicide treatments on black spot and lenticel damage Postharvest application of TBZ and chlorine dioxide appeared to increase black spot incidence on fruit from C1, and TBZ increased black spot severity on fruit from C4 and C5. There were two instances of fungicides increasing lenticel damage severity compared with the incidence in the water controls: TBZ for C1 and chlorine dioxide and prochloraz for C6. It is possible that application of these fungicides may have damaged the avocado skin, explaining the increase in black spot incidence and severity, and in lenticel damage severity on fruit from these orchards. Prochloraz does not usually damage avocado skin, and any damage may be due to exceeding the recommended application rates, or some other unknown factor. There were also examples of fungicides reducing lenticel damage severity compared with that in the water controls e.g. chlorine dioxide, prochloraz and TBZ (C7), prochloraz and chlorine dioxide (C8), and incidence by prochloraz (C10). It is unexpected that application of fungicides would reduce lenticel damage, but one explanation could be that these symptoms were caused by a fungus. Isolations from these symptoms are required to elucidate the cause further. There also appeared to be some effect of fungicides on lenticel damage compared with that in untreated controls (C8, C10), but this may simply have been because untreated control fruit were not jostled as much as fruit treated with fungicides. For the remaining orchards (C2, C3 early and late, C4, and C5), it was not unexpected that lenticel damage, which has been shown to be caused by physical damage (Everett et al. 2008), was not affected by fungicide application.

[20]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Postharvest application of fungicides to the two orchards (C1 and C4), from which more Cladosporium was isolated from black spot symptoms than from adjacent green skin, were not able to provide any further evidence of a fungal cause for this symptom. This was because there were no significant effects of postharvest application of fungicides for fruit from orchard C4, because there were too few fruit with black spot symptoms to allow statistical analysis. The postharvest application of fungicides to fruit from C1 produced results on black spot incidence and severity that were very difficult to explain, because black spot was completely absent on fruit treated with water alone, but present on all other treated fruit.

3.3

Postharvest rots

3.3.1

Fungal isolations

Rots were found in fruit from seven out of eight lines of fruit that were ripened at 20°C (Experiment 3.3). Overall, 37% of the 470-fruit sample was affected by rots, and rot incidence in these eight lines of fruit ranged from 0 to 89% (Table 1.5). Fruit from one orchard (C2) had no rots, but fruit from all other orchards were affected by stem-end rots (C3, C4, C5, C6, C8, C10 and C11) and from three orchards (C4, C5 and C6) by body rots. Lasiodiplodia theobromae was the fungus most commonly isolated from stem-end rots, and Colletotrichum gloeosporioides was most commonly isolated from body rots. These identifications were confirmed by sequence analysis of the inter-transcribed spacer region of ribosomal DNA of 58 representative isolates. Of these sequenced isolates, 47 were L. theobromae, nine were C. gloeosporioides, one isolate was Botryosphaeria parva, and one isolate was Pestalotiopsis sp.

3.3.2

Orchard experiments

Fruit from all participating orchards were affected by both body and stem-end rots after coolstorage for 28 days and evaluation at 20°C (Experiments 1.1, 1.2, 2.1, 2.2, 3.1, and 4.1). In Experiments 1.1 to 3.1 rots affected 23% of 22,162 evaluated fruit (Table 1.6). There were fewer rots in these fruit that were coolstored, then ripened at 20°C, than in the fruit stored and ripened at 20°C. This is in agreement with results from New Zealand; rots were fewer in coolstored fruit than in fruit held and ripened at 20°C, or at ambient temperature (Everett & Korsten 1996; Everett & Pak 2001). Postharvest evaluations were conducted inconsistently for these experiments. Fruit need to be evaluated when they are ‘eating ripe’ for an accurate assessment of rots. For avocados, this requires assessment every day for up to 14 days (sometimes longer) and this was not always done. However, there were some statistically significant differences, but because of problems with the assessments, only the most reliable are described here. Both stem-end rots and body rots were positively related to days to ripen (R 2 = 96% and 87%, respectively) for C1 in Experiment 1.1. Stem-end rots were positively related to days to ripen for C1 in Experiment 1.2 (R2 = 43%), and for C7 in Experiment 2.1 (R2 = 94%). This is in agreement with other studies on stem-end rots (Hartill & Everett 2002). [21]

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The holding environment (Experiment 2.1) significantly affected stem-end rots in fruit from C7. Stem-end rots were fewer when fruit were placed directly into the coolstore. Stem-end rot fungi have been shown to contaminate the stem-end wound during harvest (Hartill & Everett 2002). Therefore placing fruit into the coolstore immediately after harvest may have inhibited germination and penetration of these fungi into the stem-end wound, thus decreasing the number of infections. Holding fruit at ambient temperature, or even at 15°C, may have allowed the spores to germinate and begin penetrating the stem before placement in the coolstore, resulting in higher rot incidence. An alternate mechanism could be related to the post-coolstorage ripening time of fruit placed in different holding environments prior to coolstorage. The ripening time after removal from the coolstore was longest for fruit that were held in the field shed for 24 hours after harvest before placement in the coolstore. Stem-end rots were more common in fruit from this treatment. Fruit that had been placed in the coolstore immediately after harvest ripened the most rapidly when removed from the coolstore after 28 days. Because stem-end rot incidence is positively related to the time fruit take to ripen, the reason that rots were least common on fruit placed directly in the coolstore may have been the effect of this treatment on the post-coolstorage ripening time. A combination of the effect on ripening time, and cold temperatures inhibiting fungal growth, may have a combined effect on reducing fruit rot incidence in fruit that had been placed into the coolstore immediately after harvest. This result is supported by studies showing the reduction of rot incidence following coolstorage compared with fruit that were stored and ripened at ambient temperatures (Everett & Korsten 1998; Everett & Pak 2002). As was expected, the application of postharvest fungicides (Experiment 3.1) significantly reduced rots: all fungicides (chlorine dioxide, prochloraz and TBZ) significantly reduced the incidence of body rots compared with that in the untreated controls for fruit from C1; TBZ significantly reduced the incidence of stem-end rots for fruit from C4, and the severity of stemend rots for fruit from C6. The application of prochloraz significantly reduced the incidence of body rots for fruit from C3 (mid season) and C7, and the severity of stem-end rots for fruit from C6. Chlorine dioxide was effective when used on only one orchard (C1). Unexpectedly, application of some fungicides resulted in a higher incidence and/or severity of rots: prochloraz for stem-end rot severity (C1) and chlorine dioxide for stem-end rot incidence and severity (C3). Although the differences for orchard C2 were not statistically significant because of issues with the postharvest assessment methodology, the incidence of stem-end rots was lowest for fruit treated with prochloraz and TBZ, and body rot severity was lowest for fruit treated with prochloraz, Chlorine dioxide is a sanitiser and would be expected to eliminate spores on the surface of the fruit, but would not have any effect on latent infections in the avocado skin, or on spores that had penetrated into the vasculature of the stem-end. Application of chlorine dioxide did significantly reduce the incidence of mycelial tufts that were found on fruit from C7, suggesting that this problem is caused by spores contaminating the picking wound at harvest. However, there was no difference to the incidence in the water control, so the reduction of incidence of this disorder by chlorine dioxide may have been due solely to washing spores off the wound. In contrast, application of prochloraz, which has some systemic activity, completely prevented these symptoms developing on fruit during coolstorage. Likewise, application of TBZ, also with systemic activity, significantly reduced the incidence of mycelial tufts developing on fruit during coolstorage compared with the incidences in both the water and the untreated controls.

[22]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

TBZ has a maximum residue limit (MRL) on avocado fruit for the USA, and is able to be used on fruit for that marketplace. Prochloraz should be used for fruit in the domestic Peruvian marketplace, or for markets that have MRLs or allowances for postharvest application of this chemical.

3.4

Grey pulp

Grey pulp is often referred to as a chilling disorder of the fruit pulp. However, it does not follow the ‘textbook’ conditions for a chilling disorder, in which the disorder is more or less prevalent based on a time x temperature relationship – i.e. a shorter time is required at a lower temperature for expression. Instead, grey pulp (also termed diffuse flesh discoloration) appears to be caused by the fruit starting the ripening process whilst still at storage temperatures. Evidence for this is that grey pulp symptoms were more prevalent after longer storage durations, in late-harvested fruit (Dixon et al. 2003 ) and after exposure to ethylene during storage (Pesis et al. 2002). Conversely, expression of grey pulp symptoms are delayed by storing at lower temperatures (Kok et al. 2011 ), treatment with 1-MCP (Pesis et al. 2002) or the use of controlled atmospheres (Spalding & Reeder 1975 ). As a result, grey pulp is often regarded commercially as indicative of the fruit having been stored for too long. While this description accounts for grey pulp symptoms seen, it does not preclude other causes for flesh discoloration. The duration of coolstorage (28 days) for most of the experiments (1.1, 1.2, 2.1, 2.2, 3.1) was insufficient to induce grey pulp. The extended coolstorage up to 6 weeks of the library trays Experiment 4.2 was designed to show the symptoms by storing for longer periods. In agreement with examples from the literature, generally in the samples assessed in library trays (Experiment 4.2), grey pulp tended to be found in fruit from the later storage assessments, although symptoms in fruit that had not been stored, or had only been in store for a short time, were also recorded. Whilst similar symptoms have been noted from other cultivars direct from the tree, it is not normal for ‘Hass’. However, there were problems with the ripe fruit assessments that may have influenced these results.

3.5

Other postharvest disorders

Examination of all evaluated postharvest disorders (Table 1.6) showed that stem-end rots were the most common. Some postharvest disorders may have been common because fruit were evaluated when under-ripe (flesh adhesion, uneven ripening, stringy vasculature, peelability), or when over-ripe (grey pulp). Flesh bruising was also common on some orchards, and may have been a result of rough handling of ripened fruit. Bruising was related to fruit number on some orchards, which shows that fruit sustained more damage when they were riper, suggesting rough handling during evaluation as the cause. Vascular browning is a symptom that is easy to confuse with stem-end rots, and was generally common when stem-end rots were common. One orchard had a high incidence of stringy vasculature (C6) for fruit in all orchard experiments in which they participated (Experiments 1.1, 1.2, 2.1, and 3.1). These fruit were either evaluated on one day (day 4, Experiment 1.2; day 7 Experiment 3.1) or the assessment date was not recorded (Experiments 1.1, 2.1). It is possible that this symptom was prevalent because the fruit were assessed when they were under-ripe. Results for Experiment 1.1 for fruit from this orchard showed that as fruit number increased, symptoms of stringy vasculature declined, as would be expected if it were a symptom associated with under-ripe fruit. [23]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

3.6

Dry matter and oil accumulation in different climatic zones in Peru

A summary and full report can be found in the associated Part 2 of this report.

3.7

Conclusions and recommendations

Black spot  Black spot was found on 5% or less of the fruit from all participating orchards except for C1. On this one orchard, black spot affected 20% of the evaluated fruit, and was associated with the fungus Cladosporium.  There were at least three different symptom types described as black spot:  Nodule damage (caused by physical injury)  Fuzzy blotches (associated with a fungus)  Blotches with sharp borders (associated with chilling injury).  Nodule damage can be reduced by ensuring roads in the orchard and between the orchard and the packhouse are smooth, that the fruit dump onto the packing line is as gentle as possible, and that there are no drops, impacts or sharp turns on the packing line  Fuzzy blotches may be able to be reduced by:  Postharvest application of a fungicide (e.g. prochloraz)  Placing fruit in the coolstore immediately after harvest  Applications of copper fungicides in the orchard at monthly intervals are also likely to reduce the incidence of this type of black spot.  However, the pathogenicity of Cladosporium and the involvement of fungi in some symptom types described as lenticel damage need to be investigated further before firm recommendations can be made.  Blotches with sharp borders can be reduced by:  Determining the correct storage temperature for Peruvian fruit from different regions, if it is not already known  Strictly adhering to the correct storage temperatures for Peruvian fruit, by using temperature probes with alarms and by regular maintenance of chillers, refrigerated trucks and containers. Lenticel damage  Lenticel damage was common on all orchards, and affected 79-99% of Peruvian fruit in these experiments.  Lenticel damage can be reduced by:  Turning off irrigation before harvest

[24]

Harvesting fruit later in the day.

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Stem-end rots

Stem-end rots were present in 23% of ripened, coolstored fruit in these experiments, and are likely to cause issues with consumers in the marketplace.

Postharvest application of a fungicide (e.g. prochloraz, TBZ) will reduce the incidence of stem-end rots:

Fungicides should be applied immediately after the fruit arrive in the packing shed, preferably within 24 hours of harvest

Postharvest dipping of bins of fruit as soon as they arrive in the packing house is the most effective way of applying fungicides. The fungicide needs to be regularly replenished to prevent ‘stripping’ as more fruit pass through the dipping solution

Maximum residue limits (MRLs) for these fungicides in the target market need to be strictly met.

 

Placing fruit in the coolstore immediately after harvest will reduce postharvest rots.

Shortening the time for fruit to ripen, e.g. by ethylene treatment, will reduce postharvest rots.

Application of copper fungicides in the orchard at monthly intervals should reduce postharvest rots.

Grey pulp Grey pulp symptoms were more prevalent with longer storage. The time to expression may best be delayed by the use of controlled atmosphere storage (CA). Assessments

Lenticel damage, nodule damage, chilling injury and ‘fuzzy’ black spot should be clearly and reliably distinguished.

Industry produced posters and evaluation guidelines should be distributed to all packhouses for use by quality control managers.

If there is a problem on arrival in the marketplace, high-resolution single-fruit photographs of affected fruit should be sent to a trained evaluator.

Clear separation of these symptom types should enable the appropriate remediation method to be used.

Further research  The results from this project have for the first time given a broad overview of the quality issues for Peruvian avocado fruit that are likely to cause problems in the marketplace.  This information allows the industry to identify issues towards which future research needs to be directed. It is clear that there are quality problems that may be caused by fungal pathogens that need to be resolved by further isolations, and by inoculation experiments to prove Koch’s Postulates. Our recommendation for this technically demanding research is that a trained plant pathologist domiciled in Peru conducts the study either independently, or in collaboration with Plant & Food Research plant pathologists.  Postharvest assessments were clearly a challenge for the packhouse and orchard participants during these experiments. Our recommendation is that in future ProHass engages a Peruvian research company or university to conduct the postharvest assessments. [25]

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 For confirmatory or future research in this area, the quality of the data may be improved by conducting the study on fewer orchards, and by conducting fewer experiments each season. This season (2015) nine companies have followed these recommendations by assessing only the disorders that are important, by conducting fewer assessments and by conducting fewer experiments per company. Robust data from those trials will be analysed and reported later in 2015.

[26]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Table 1.3. Total number of Peruvian avocado fruit and percentage of total fruit with lenticel damage and black spot after coolstorage for 28 days for on-orchard experiments. Assessments were of the external quality of unripe fruit. Number of fruit affected Experiment

1.1

1.2

2.1

Percentage of fruit affected 2.2

1.1

1.2

2.1

Total no.

2.2

Total %

3.1

Orchard

LD

BS

Tot

LD

BS

Tot

LD

BS

Tot

LD

BS

Tot

LD

BS

LD

BS

LD

BS

LD

BS

LD

BS

Fruit

LD

BS

C1

788

197

789

480

74

480

639

127

639

347

48

365

100

25

100

15

100

20

95

13

2254

446

2274

99

20

C2

384

9

384

720

16

720

639

0

640

398

0

400

100

2

100

2

100

0

100

0

2141

25

2144

100

1

C3(early)

960

22

960

720

37

720

640

2

640

362

1

399

100

2

100

5

100

0

91

0

2682

62

2719

99

2

2720

100

2

2509

100

3

1671

100

5

100

0

C3(late) C4 C5

960 751 634

14 5 24

960 751

720 720

30 37

720 720

634

C6

800

0

800

C7

603

0

608

C8

640

0

C10

564

0

Total fruit

634 637

720

0

720

640

640

0

640

640

671

0

720

7166

640

5440

18 11 37

LD

BS

Tot

640

400

638

400

637

480

0

480

762

0

800

560

0

560

616

0

640

400

560

6314

LD = lenticel damage, BS = black spot

[27]

3.1

THE NEW ZEALAND INSTITUTE FOR PLANT & FOOD RESEARCH LIMITED (2016)

0

560

560

4 19 19

400 400 400

400

0

400

346

0

400

6

41

0

100 100 100

1 1

100

4 5

4

100

0

384

99

0

400

100

392

88

3941

100

100 99 100

LD

BS

3

100

2

100

6

100

0

100

0

95

0

0

100

0

100

0

0

93

0

96

0

100

100

0

1 5 5

2720 2505 1671

66 72 80

100

0

2400

0

2400

90

0

1711

0

1792

95

0

100

2

2800

6

2800

100

0

10

0

1892

0

2392

79

0

23421


ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Table 1.4. Isolations from black spot symptoms and from symptomless green skin on the same Peruvian ‘Hass’ avocado fruit. Fungal cultures were identified by morphology, and representative isolates were DNA sequenced for confirmation. Fruit were sampled when unripe. P values are the result of a chi-squared analysis. Isolations from black spot No. of fruit

Clad.

C2

1

1

C3

29

18

C4

22

38

C5

5

3

C1

33

18

C6

11

23

C8

73

89

C9

15

33

C11

14

15

1

Total

203

238

6

Orchards

Alt.

1

Cg

LD

4

Bot

Isolations from green skin

Pen

1

2 1

3

1

2

5

2

2

10

1

6

3

1

Total

Clad.

Alt.

Cg

1

2

1

1

24

16

2

4

38

LD

Bot

Pen

Fus.

Nig.

Pest.

Total

P

4

n.s.

23

n.s.

18

18

0.0075

5

3

3

n.s.

20

8

9

0.0499

23

21

23

n.s.

101

87

5

4

109

n.s.

36

26

2

1

29

n.s.

16

13

1

14

n.s.

264

194

12

1

1 1

11

1 4

4

5

5

1

2

1

1

1

2

2

232

Clad. = Cladosporium, Alt. = Alternaria, Cg = Colletotrichum gloeosporioides, LD = Lasiodiplodia, Bot. = Botrytis, Pen = Penicillium, Fus. = Fusarium, Nig. = Nigrospora, Pest.= Pestalotiopsis. n.s. = not significant.

[28]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Table 1.5. Isolations from rots that developed in ‘eating ripe’Peruvian avocado fruit. Fruit were stored at 20°C and internal quality assessed when ripe. Fungal cultures were identified by morphology and representative isolates were DNA sequenced for confirmation.

Orchard

Date harvested

No. of fruit sampled

Ripening time (days)

No. of body rots

No. of stem-end rots

% rots

C.g.2.

L.t.

C2

1/7/2014

67

9.8 ± 0.27

0

0

0

0

0

C3

27/6/2014

70

10.8 ± 0.07

0

62

88.6

1

60

C4

25/6/2014

69

16.7 ± 0.32

1

27

40.6

1

18

C5

25/6/2014

65

15.1 ± 0.17

9

24

50.8

7

24

C6

2/7/2014

39

13.3 ± 0.43

2

3

12.8

? 1.

? 1.

C8

26/6/2014

64

14.0 ± 0.19

0

25

39.1

0

23

C10

31/6/2014

62

18.1 ± 0.28

0

7

11.3

0

? 1.

C11

1/7/2014

34

18.3 ± 0.50

0

14

41.2

0

1

12 2.6

162 34.5

37.0

9 7.3

126 92.6

Total no. %

470

1. Fungi were not isolated from these fruit. 2.

[29]

C.g. = Colletotrichum gloeosporioides, L.t. = Lasiodiplodia theobromae

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Table 1.6. Total number of Peruvian avocado fruit and percentage of total fruit with rots and physiological disorders after coolstorage for 28 days for on-orchard experiments. Assessments were of the internal quality of fruit that were ripened at 20°C.

Total number fruit with disorders

Percentage of fruit with disorders

Orchard

FA

UR

VB

GP

P

SB

FB

SV

BR

SER

Total fruit

FA

UR

VB

GP

C1

385

179

226

142

113

51

143

1

281

424

2273

17

8

10

6

C2

29

7

449

214

80

22

334

7

229

445

1673

2

0

27

C3(early)

3

0

65

29

47

61

13

3

309

189

2716

0

0

C3(late)

0

0

153

133

78

3

39

0

268

229

2528

0

C4

309

58

132

76

456

231

170

702

70

913

2429

C5

157

4

2

75

16

1

3

315

2

67

C6

214

29

0

7

17

0

5

1366

12

C7

180

443

30

884

460

177

109

30

C8

9

2

1

33

2

18

17

C10

25

171

23

10

10

24

Total

1311

893

1081

1603

1279

588

SB

FB

SV

5

2

6

13

5

1

2

1

2

0

6

5

13

2

5

1604

10

0

443

1999

11

723

356

1788

2

67

76

138

78

8

971

2504

1969

BR

SER

TOT

0

12.4

18.7

31.0

20

0

13.7

26.6

40.3

2

0

0

11.4

7.0

18.3

3

0

2

0

10.6

9.1

19.7

3

19

10

7

29

2.9

37.6

40.5

0

5

1

0

0

20

0.1

4.2

4.3

1

0

0

1

0

0

68

0.6

22.2

22.8

10

25

2

49

26

10

6

2

40.4

19.9

60.3

2766

0

0

0

1

0

1

1

0

2.4

2.7

5.2

49

2386

1

7

1

0

0

1

6

3

0.3

2.1

2.4

3191

22162

6

4

5

7

6

3

4

11

8.9

14.4

23.3

NB. Not all evaluations were conducted on ‘eating ripe’ fruit, which does not allow an accurate comparison of the amount of disorders in fruit from different orchards. FA = flesh adhesion, UR=uneven ripening, VB = vascular browning, GP = grey pulp, P = peelability, SB=seed browning, FB = flesh bruising, SV= stringy vasculature, BR = body rots, SER = stem-end rots, TOT = total rots.

[30]

THE NEW ZEALAND INSTITUTE FOR PLANT & FOOD RESEARCH LIMITED (2015)

P


ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

4

YEAR 3 (2015)

4.1

Black spot

Black spot occurrence was too low for analysis except in orchard C1 (Table 1.7). Fruit harvested from trees that were not irrigated showed significantly less black spot than those from irrigated trees, in contrast to the results from the previous year’s experiment (2014). These results suggest that the symptoms described as black spot may instead have been severe lenticel damage. There was no significant reduction of black spot following application of fungicides compared with controls.

4.2

Lenticel damage

Lenticel damage was generally more severe on fruit harvested from irrigated trees than from trees that were not irrigated, for three of the four companies that conducted assessments of unripe fruit this season, agreeing with results from 2014. For irrigated trees, the best time to harvest fruit to minimise lenticel damage was generally at midday (for three of four companies). For fruit from non-irrigated fruit, the pattern was different for each orchard, presumably because of different soil types, and possibly because of differences in climate. For two of the four companies, fruit were less affected by lenticel damage when harvested later in the day, in agreement with results from 2014. The fruit weights did not seem to reflect the water status of the fruit accurately. It is unlikely that differences of 30 to 90 g between the lightest and heaviest fruit weights were solely due to water uptake or loss. This measure of turgidity of fruit is not reliable unless the same sized fruit are harvested at each time. An easier measure, such as the fresh weight/dry weight ratio, may determine water content, and therefore turgidity, more accurately.

4.3

Postharvest rots

Assessments of ripe fruit were again fraught with difficulties. The correct methodology to obtain robust information on fruit quality requires that avocados are assessed at exactly the same stage of ripeness, mainly because fruit rots and other disorders increase significantly with ripeness. Thus, fruit should be gently hand squeezed every day starting 2–3 days after removal from the coolstore, and any fruit that are eating ripe should be cut and assessed. This was generally not done well by the companies. This means that the assessments were not sufficiently robust to be able to draw extremely robust conclusions from the data. However, despite this, there were some results that did show significant differences between treatments. Stem-end rots were significantly more severe in fruit harvested in the morning, as was lenticel damage, for orchards C2 and C10. For these companies, harvesting at 0800 h should be avoided. However, generally, turning off the irrigation did not affect postharvest rots. Postharvest application of prochloraz significantly reduced the severity of body rots for one orchard (C7). There were no significant differences in the amount or the severity of rots between treatments for the other three orchards. This is a surprising result because of the demonstrated efficacy of postharvest application of fungicides against avocado rots (Everett 2002; Everett & Korsten 1996). However, because rot incidence and severity is affected by the [31]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

degree of ripeness of the fruit when they are assessed (Everett & Pak 2002), and because the fruit were assessed at varying degrees of ripeness, any fungicidal effect on rots was probably obscured. Applying copper on trees in the orchard resulted in a significant reduction of stem-end rot severity for one orchard (C7). Rots were too few for statistical analysis for the other participating orchards.

4.4

Grey pulp

There was a statistically significant effect of time of harvest on severity of grey pulp on fruit from one orchard. On this orchard (C2), grey pulp was less severe when fruit were harvested late in the day. Fruit from orchard C1 were significantly less affected (both incidence and severity) by grey pulp when treated postharvest with prochloraz than were water-treated controls. There was no effect of orchard application of fungicides on grey pulp. The results from the library trays were similar to those of 2014, please refer to the 2014 Grey pulp section (page 23) for further comments.

4.5

Other postharvest disorders

There were no effects on the other disorders, except for vascular browning, from the postharvest fungicides treatment. All treatments, including water, increased the severity of vascular browning.

4.6

Dry matter and oil accumulation in different climatic zones in Peru

A summary of the 2014 results and full report for 2015 can be found in Part 2 of this report.

4.7

Conclusions and recommendations

Black spot Black spot incidence decreased when chlorine dioxide was applied postharvest, but not at a statistically significant level. Black spot incidence was not decreased by the other fungicides used (prochloraz and thiabendazole). Overall these results suggest that fungal infection was not important in the development of black spot during storage, but rather that any fungi associated with these symptoms were secondary invaders, and that the primary cause of black spot was physiological. Lenticel damage  Lenticel damage was generally more severe on fruit harvested from trees that were irrigated compared with on fruit from trees that were not irrigated, supporting the hypothesis that more turgid fruit are more susceptible to lenticel damage.

[32]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

 To minimise lenticel damage, the irrigation could be turned off for 1-several days before harvest. Stem-end rots  Stem-end rots were present in 21.4% of 5182 evaluated fruit, and, similarly to 2014, were the most common defect in ripened fruit  Results were similar to 2014, and further comments and recommendations are in the 2014 section (page 25). Grey pulp  Results were similar to the previous year (2014). Further comments and recommendations are in the 2014 section (page 25). Stringy vasculature  Stringy vasculature was very common on fruit from one orchard only (C6) similar to last year’s results (2014). Although this was probably a result of fruit that were assessed before they were eating ripe, because of the high prevalence of this disorder, there may be a problem in the orchard management.  Assessment of fruit from orchard C6, making certain that they are optimally (eating) ripe, will be the most efficient means of determining if the high incidence of stringy vasculature on this orchard is a result of incorrect assessments, or is caused by an unknown orchard factor. Assessments  The ripe fruit assessments were generally not done well. Fruit were not assessed when they were optimally ripe.  Fruit ripeness needs to be assessed every day starting 2–3 days after the fruit are removed from the coolstore, The last fruit to ripen should be 7–14 days after removal from the coolstore.  The results from the postharvest and orchard application of fungicides were compromised because the assessments were not done correctly.  There was some significant control of rots following application of fungicides both postharvest and in the orchard, despite these limitations. Quality issues in ripened fruit  Although stringy vasculature affected 24.9% of the 5182 evaluated fruit, most of these fruit were from one orchard (C6).  Orchard C6 need to further investigate stringy vasculature in their fruit, because fruit from this orchard also had a high incidence of stringy vasculature last season (2014). Whether this is due to assessment of the fruit before it was ripe, or to some other factor such as poor nutrition, needs to be examined.  The incidence of stringy vasculature in the remaining 3982 fruit was 2.4%, and therefore a minor disorder.  Overall, stem-end rots (21.4%) and body rots (20.6%) were the most common disorders of ripened fruit (Table 1.8).  Postharvest or orchard application of fungicides should be considered as a routine practice for controlling postharvest rots of Peruvian avocados to increase the fruit quality.

[33]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Table 1.7. Total number of Peruvian avocado fruit and percentage of total fruit with lenticel damage and black spot after coolstorage for 28 days for on-orchard experiments conducted in 2015. Assessments were of the external quality of unripe fruit.

Number of fruit affected Experiment

1.1

3.1

Orchard

LD

BS

Tot

LD

BS

Tot

C1

740

151

795

378

95

400

C2

446

4

461

3.2

C3

LD

400

C5

637

16

639

C6

800

0

800

C7

384

111

19

1

1.1 BS

0

Tot

400

THE NEW ZEALAND INSTITUTE FOR PLANT & FOOD RESEARCH LIMITED (2016)

3.1

LD

BS

LD

BS

93.1

19.0

94.5

23.8

96.7

0.9

400

0

400

51

0

120

LD

100 99.7

2.5

100.0

0.0

96.2

27.8

Total %

Total no.

3.2

400

399

LD = lenticel damage, BS = black spot

[34]

Percentage of fruit affected

BS

0

4.8

0.3

LD

BS

Fruit

LD

BS

1118

246

1195

93.6

20.6

446

4

461

96.7

0.9

400

0

400

100.0

0.0

1021

35

1038

98.4

3.4

100

0

1200

0

1200

100.0

0.0

42.5

0

162

1

520

31.2

0.2


ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Table 1.8. Total number of Peruvian avocado fruit and percentage of total fruit with rots and physiological disorders after coolstorage for 28 days for on-orchard experiments for 2015. Assessments were of the internal quality of fruit that were ripened at 20°C. Experiment

Total number of fruit with disorders

Percentage of fruit with disorders

Orchard

FA

UR

VB

GP

P

SB

FB

SV

BR

SER

Total fruit

FA

UR

VB

GP

P

SB

FB

SV

BR

SER

Total

C1

87

5

89

129

4

66

18

1

81

212

1191

7.3

0.4

7.5

10.8

0.3

5.5

1.5

0.1

6.8

17.8

40.8

C2

0

0

5

21

0

0

0

0

171

57

445

0.0

0.0

1.1

4.7

0.0

0.0

0.0

0.0

38.4

12.8

43.8

C3

0

0

1

4

10

4

1

6

3

1

200

0.0

0.0

0.5

2.0

5.0

2.0

0.5

3.0

1.5

0.5

13.0

C5

0

0

77

74

0

0

0

0

421

270

1037

0.0

0.0

7.4

7.1

0.0

0.0

0.0

0.0

40.6

26.0

52.1

C6

6

1

42

48

0

1

20

1197

7

0

1200

0.5

0.1

3.5

4.0

0.0

0.1

1.7

99.8

0.6

0.0

99.8

C7

2

0

183

153

77

9

6

49

297

181

385

0.5

0.0

47.5

39.7

20.0

2.3

1.6

12.7

77.1

47.0

92.5

C10

33

0

190

105

48

1

25

38

90

389

724

4.6

0.0

26.2

14.5

6.6

0.1

3.5

5.2

12.4

53.7

64.9

Total

128

6

587

534

139

81

70

1291

1070

1110

5182

2.5

0.1

11.3

10.3

2.7

1.6

1.4

24.9

20.6

21.4

63.1

N.B. Not all evaluations were conducted on ‘eating ripe’ fruit, which does not allow an accurate comparison of the amount of disorders in fruit form different orchards. FA= flesh adhesion, UR=uneven ripening, VB=vascular browning, GP=grey pulp, P = peelability, SB=seed browning, FB = flesh bruising, SV = stringy vasculature, BR = body rots, SER = stem-end rots, Total = total percent fruit affected by disorders.

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INDIVIDUAL EXPERIMENTS 5

EXPERIMENT 3.3 FUNGAL ISOLATIONS AND PHYLOGENETIC ANALYSIS

5.1

Aim

To determine if black spot of avocado is caused by a fungus, and to identify fungi causing rots in Peru.

5.2

Introduction

Most fungal pathogens of avocados produce spores that are dispersed by rain splash (Everett et al. 2007). Because of the lack of rainfall in Peruvian avocado-growing regions, fungi might not be as common as in growing regions with high rainfalls. Quantification of rots, and identification of the causal organisms, are required to determine if rots are a problem, and if there are any differences in fungal populations in different regions of Peru. Fungicides appropriate for specific fungal groups may be required for effective fungal control. The symptoms of ‘black spot’ on Peruvian avocados are similar to a symptom called ‘measles’ in New Zealand that is caused by fungal infections. In New Zealand these fungi are Colletotrichum acutatum and Phomopsis sp. (Everett et al. 2007). A comparison of fungi isolated from black spot symptoms and asymptomatic tissue was expected to provide evidence supporting or refuting a fungal cause for black spot.

5.3

Methodology

5.3.1

Isolations

Black spot Fruit showing symptoms of black spot were sourced from nine orchards, a total of 203 fruit (Table 1.10). Isolations were made from symptomatic and non-symptomatic skin on every fruit. Fruit were wiped with 70% ethanol before a small piece of skin was aseptically excised with a sterile scalpel blade and placed on Difco® potato dextrose agar (PDA). A symptomless skin sample from the same fruit was sampled in the same way. Six tissue pieces in total were excised from every fruit. Postharvest rots Additional fruit were sourced from eight of the study orchards for assessment of postharvest rots. These fruit were placed at 20°C and assessed when ripe, determined by gentle hand squeezing. Fruit were then cut in quarters and peeled. Rots were assessed according to the PFR-ProHass Scales 2 and 3 (Appendix 1.1). Isolations from rots were made aseptically after cutting and peeling each fruit.

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5.3.2

Identification

Fungal cultures were identified by morphology, and a sample of representative fungi was subcultured and taken to New Zealand for DNA analysis. Cultures for DNA extraction were grown on PDA for 2–3 weeks at ambient temperature (approximately 20°C). DNA was extracted from approximately 1 cm 2 mycelium by using the DNeasy® Tissue kit (Qiagen). The ITS regions ITS1 and ITS2 and the 5.8S gene were amplified using the primer set ITS1/4 (White et al. 1990). The PCR reaction mixture (25 µL final volume) contained approximately 5 ng of template DNA, 0.5 µM of each primer, 400 µM of each dNTP, 1 U Platinum Taq DNA Polymerase buffer and 3 mM Mg Cl2. The thermocycling (Techne, Cambridge, UK) conditions were an initial denaturation of 95°C for 4 min, followed by 35 cycles at 95°C for 30 s (denaturing), 55°C for 30 s (annealing) and 72°C for 45 s (elongation). A final elongation was allowed for 10 min at 72°C. The PCR products were purified by gel electrophoresis (1% agarose) followed by the Wizard R SV Gel and PCR Clean-Up system (Promega (Madison, WI, USA). The PCR products were sequenced in both directions by Macrogene Inc. All sequences were edited manually using Vector NTI 8 (InforMax Inc., Bethesda, MD, USA) and ambiguous regions on both sides of the sequences were excluded from the analysis. A neighbour joining (NJ) analysis (Saitou & Nei 1987) was performed with Molecular Evolutionary Genetics Analysis (version 6) software (Tamura & Nei 1993; Tamura et al. 2013), using the heuristic search option, and 1,000 random addition sequence replicates were used. The bootstrap values were evaluated by using 1,000 replicates to test the branch strength (Felsenstein 1985). A Puccinia graminis sequence was used as the outgroup (GenBank accession number JX047482). The Basic Local Alignment Search Tool (BLAST, www.ncbi.nlm.nih.gov/blast) was used to find sequences that were homologous to those derived from the isolates from Peru (Table 1.9)and included in the phylogenetic analysis.

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Table 1.9. Sequences of the inter transcribed spacer (ITS) region (ITS1, 5.8S and ITS2 regions) downloaded from the National Centre of Biological Information (NCBI) and included in the phylogenetic analysis of rots from Peruvian ‘Hass’ avocado fruit. Accession No./strain

Host/ Substrate

Country

NCBI No.

Reference

Journal

Authors

H2E

potato

Mexico

JQ994286

Alternaria alternata, an important pathogen of wild potatoes in Mexico

unpublished

Avina-Padilla K, Pina-Rodriguez L, Ochoa-Sanchez JC, MartinezSoriano JP

UCR454

avocado

USA

HQ529751

Botryosphaeriaceae species associated with avocado branch cankers in California

Plant Disease 95: 1465-1473 (2012)

McDonald V, Eskalen A

DAR 45915

avocado

Australia

EF173925

Diversity of Botryosphaeria species on horticultural plants in Victoria and New South Wales

Aust. Plant Pathology 36: 157-159 (2007)

Cunnington JH, Priest MJ, Powney RA, Cother NJ

Cladosporium cladosporioides

B111

grass

UK

AF538619

Taxonomic biodiversity and community structure of saprotrophic fungi in an ‘improved’ and unimproved upland grassland

unpublished

Pryce Miller EJ, Bainbridge BW, Robinson CH

Cladosporium cladosporioides

CATASHN0 1

mango

China

HM856622

First report of mango dew spot by Cladosporium cladosporioides in China

unpublished

Zhang H, Pu J, Zhang X, Qi Y, Xie Y

Colletotrichum gloeosporioides

CG406

avocado

South Africa

AY177315

A comparative morphological study of South African avocado and mango isolates of Colletotrichum gloeosporioides

Can. J. Bot. 81: 877-885 (2003)

Sanders GM, Korsten L

C1072.7

avocado

New Zealand

JX010216

The Colletotrichum gloeosporioides species complex

Stud. Mycol. 73:115-180 (2012)

Weir BS, Johnston PR, Damm U

CP/HSR-13

avocado

Mexico

EF221829

First report of the anamorph of Glomerella acutata causing anthracnose on avocado fruits in Mexico

Plant Disease 91:1200 (2007)

Avila-Quezada G, Silva-Rojas HV, Teliz-Ortiz D

CMM3998

mango

Brazil

JX464059

Species of Lasiodiplodia associated with mango in Brazil

Fungal Diversity (in press)

Marques MW, Michereff SJ, Phillips AJL, Camara MPS

Species Alternaria alternata

Botryosphaeria dothidea Botryosphaeria parva

Colletotrichum gloeosporioides (species complex) Colletotrichum gloeosporioides Lasiodiplodia iranensis

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Accession No./strain

Host/ Substrate

Country

NCBI No.

Reference

Journal

Authors

Lasiodiplodia theobromae

BL187

grapevine

Italy

KJ638321

Species diversity of Botryosphaeriaceae associated with grapevine and other woody hosts in Italy, Algeria and Tunisia, with descriptions of Lasiodiplodia mediterranea and Lasiodiplodia exigua sp. nov.

unpublished

Linaldeddu BT, Deidda A, Scanu B, Franceshini A, Serra S, Berraf-Tebbal A, Zouaoui Boutiti M, Ben Jamaa ML, Phillips AJL

Lasiodiplodia theobromae

DB 101011

avocado

Italy

JN849098

First report of postharvest fruit rot in avocado (Persea americana) caused by Lasiodiplodia theobromae in Italy

Plant Dis. 96:460 (2012)

Garibaldi A, Bertetti D, Amatulli MT, Cardinale AJ, Gullino ML

Lasiodiplodia theobromae

CMW9074

Pinus sp.

Mexico

AY236952

Combined multiple gene genealogies and phenotypic characters differentiate several species previously identified as Botryosphaeria dothidea

Mycologia 96:83-101 (2004)

Slippers B, Crous PW, Denman S, Countinho TA, Wingfield BD, Wingfield MJ

Lasiodiplodia theobromae

CMW18422

Pinus patula

South Africa

DQ103544

Three new Lasiodiplodia spp. from the tropics, recognized based on DNA sequence comparisons and morphology

Mycologia 98:423-435 (2006)

Burgess TI, Barber P. Mohali S, Pegg G, de Beer W, Wingfield M

Lasiodiplodia theobromae

B961

mango

Taiwan

GQ502453

Fruit rot disease of mango caused by Lasiodiplodia theobromae

unpublished

Ni H-F, Yang H-R

Lasiodiplodia pseudotheobromae

CMM3887

Jatropha curcas

Brazil

KF234559

Phylogeny, identification and pathogenicity of the Botryosphaeriaceae associated with collar and root rot of the biofuel plant Jatropha curcas in Brazil, with a description of new species of Lasiodiplodia

Fungal Diversity (in press)

Machado AR, Pinho DB, Pereira OL

Pestalotiopsis clavispora

PALUC-12

avocado

Chile

HQ659767

First report of Pestalotiopsis clavispora and Pestalotiopsis spp. causing postharvest stem-end rot of avocado in

Plant Disease 95: 492 (2011)

Valencia AL, Torres R, Latorre BA

671

Berberis sp.

Sweden

JX047482

Taxonomic and phylogenetic study of rust fungi forming aecia on Berberis spp. in Sweden

unpublished

Kyiashchenko I, Berlin A, Yuen J

Species

Puccinia graminis

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5.4

Results

5.4.1

Black spot isolations

Cladosporium sp. was the most common fungus isolated from both black spot symptoms and symptomless fruit skin (Table 1.10). There were more isolations of Cladosporium sp. from black spot symptoms than from symptomless tissue on fruit from two orchards (C1 and C4). There was no difference in the numbers of isolations from black spot symptoms and from symptomless green avocado fruit skin for the other six orchards (C2, C3, C5, C6, C8, C11). Isolations from black spot symptoms on fruit from C5 yielded C. gloeosporioides, which was not isolated from symptomless tissue, but numbers of isolations of this fungus were almost the same from black spot and symptomless tissue on fruit from C3, C8 and C9. Some symptoms on fruit from C1 and C4 were different from those on fruit from the other six orchards. These symptoms were of diffuse black/brown blotches (Figure 1.3). There were similar symptoms on fruit from these other orchards, but the margins of the black/brown blotches were discrete (Figure 1.4), except for in seven out of 29 fruit from C3. Symptoms of sunken darkened nodes were found on fruit from all orchards (Figure 1.5). Two orchards had only these symptoms on their fruit (C6 and C11). There was no black spot on fruit from C10.

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Table 1.10. Isolations from black spot symptoms and from symptomless green skin on the same Peruvian ‘Hass’ avocado fruit. Fungal cultures were identified by morphology, and representative isolates were DNA sequenced for confirmation. P values are the result of a chi-squared analysis. Isolations from black spot Orchards

No. of fruit

Clad.

Alt.

C1

33

18

1

C2

1

1

C3

29

18

C4

22

38

C5

5

3

C6

11

23

C8

73

89

C9

15

33

C11

14

15

1

Total

203

238

6

1

Cg

LD

Bot

Isolations from green skin Pen

1

4

1

2

3

2

5

2

2

10

1

6

3

1

Total

Clad.

Alt.

Cg

20

8

1

1

2

1

1

24

16

2

4

38

LD

Bot

Total

P

9

0.0499

4

n.s.

23

n.s.

18

18

0.0075

5

3

3

n.s.

23

21

Fus.

Nig.

Pest.

23

n.s.

101

87

5

4

109

n.s.

36

26

2

1

29

n.s.

16

13

1

14

n.s.

264

194

12

1

1

11

Pen

1 4

4

5

5

1

2

1

1

1

2

2

232

Clad. = Cladosporium, Alt. = Alternaria, Cg = Colletotrichum gloeosporioides, LD = Lasiodiplodia, Bot. = Botrytis, Pen = Penicillium, Fus. = Fusarium, Nig. = Nigrospora, Pest.= Pestalotiopsis. n.s. = not significant

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Figure 1.3. Peruvian ‘Hass’ avocado fruit showing symptoms of diffuse brown blotches.

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Figure 1.4. Peruvian ‘Hass’ avocado fruit showing symptoms of brown blotches, with distinct margins.

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Figure 1.5. Peruvian ‘Hass’ avocado fruit showing symptoms of damaged nodules.

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5.4.2

Quantification and isolations from postharvest rots

The number of fruit with rots varied between the orchards sampled, from zero (C2) to 89% (C3) (Table 1.11). The percentage of fruit with body rots was fewer than those with stem-end rots (2.6 compared with 34.5). Five orchards had no fruit with body rots, and fruit from one orchard had no rots. Fruit from two orchards took an unusually long time to ripen (C10 and C11). The total proportion of fruit with rots was 37%. Table 1.11. Isolations from rots that developed in ripened Peruvian ‘Hass’ avocado fruit. Fungal cultures were identified by morphology, and representative isolates were DNA sequenced for confirmation.

Orchard

Date harvested

No. of fruit sampled

Ripening time (days)

No. of body rots

No. of stemend rots

% rots

C.g.

L.t.

C2

1/7/2014

67

9.8 ± 0.27

0

0

0

0

0

C3

27/6/2014

70

10.8 ± 0.07

0

62

88.6

1

601.

C4

25/6/2014

69

16.7 ± 0.32

1

27

40.6

1

181.

C5

25/6/2014

65

15.1 ± 0.17

9

24

50.8

7

24

C6

2/7/2014

39

13.3 ± 0.43

2

3

12.8

? 1.

? 1.

C8

26/6/2014

64

14.0 ± 0.19

0

25

39.1

0

231.

C10

31/6/2014

62

18.1 ± 0.28

0

7

11.3

0

? 1.

C11

1/7/2014

34

18.3 ± 0.50

0

14

41.2

0

11.

12 2.6

162 34.5

37.0

9 7.3

126 92.6

Total %

470

1. Fungi were isolated from a fruit sub-sample dependent on whether fruit were ripe during the pathologist visit. Rot

assessments were completed by ProHass. C.g. = Colletotrichum gloeosporioides, L.t. = Lasiodiplodia theobromae.

Colletotrichum gloeosporioides was isolated from eight body rots (Figure 1.6) and one stem-end rot, and Lasiodiplodia theobromae from 124 stem-end rots (Figure 1.7) and one body rot. Lasiodiplodia theobromae was the most common fungus, comprising 92.6% of those fungi isolated from rots. Fruit from C1 was not ripe during the pathologist visit and could not be isolated from.

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Figure 1.6. Body rots symptoms on Peruvian ‘Hass’ avocado fruit from which Colletotrichum gloeosporioides was isolated.

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Figure 1.7. Stem-end rot symptoms on Peruvian ‘Hass’ avocado fruit from which Lasiodiplodia theobromae was isolated.

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5.4.3

Isolations from mycelial tufts on the stem-end

Several fruit showed symptoms of white mycelial tufts on the stem-end (Figure 1.8). The fungi isolated were identified by morphology as Alternaria sp. or Cladosporium sp. Isolations from the subsequent rots that developed at the stem-end were identified as Alternaria sp.

5.4.4

Confirmation of identifications by DNA sequencing

All except one of the fungal isolates that were identified by culture morphology as Lasiodiplodia theobromae were confirmed by sequence analysis (Figure 1.9). One isolate was identified as Botryosphaeria parva. There were no isolates of B. dothidea. All isolates identified by culture morphology as Colletotrichum were identified as C. gloeosporioides by sequence analysis. All those cultures identified as Cladosporium by morphology were confirmed to be C. cladosporoides. There was one isolate of Pestalotiopsis, four isolates of Nigrospora, and six isolates of Alternaria (Figure 1.10) that were also correctly identified by culture morphology. The isolations of white tufts of mycelium taken from the stem end were identified by sequence analysis as Alternaria sp. and Cladosporium, and the fungi isolated from the stem-end rots that subsequently developed were all Cladosporium.

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Figure 1.8. White mycelial tufts growing on the stem-end of Peruvian ‘Hass’ avocado fruit from which Alternaria and Cladosporium were isolated.

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Figure 1.9. The results of a neighbour-joining phylogenetic analysis using the Tamura-Nei method (Tamura & Nei 1993) for postharvest rot fungi from Peruvian ‘Hass’ avocado fruit. The optimal tree with the sum of branch length = 1.3 is shown. The percentage of replicate trees >55 in which the associated taxa clustered together in the bootstrap test (1,000 replicates) is shown next to the branches. The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances are in the units of the number of base substitutions per site. The analysis involved 76 nucleotide sequences. All positions containing gaps and missing data were eliminated. There were a total of 357 positions in the final dataset. Evolutionary analyses were conducted in MEGA6. Representative labelled isolates on potato dextrose agar are included. [50]

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Figure 1.10. The results of a neighbour-joining phylogenetic analysis using the Tamura-Nei method (Tamura & Nei 1993) for fungi isolated from Peruvian ‘Hass’ avocado fruit with black spot symptoms. The optimal tree with the sum of branch length = 1.0 is shown. The percentage of replicate trees >55, in which the associated taxa clustered together in the bootstrap test (1000 replicates) is shown next to the branches. The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances are in the units of the number of base substitutions per site. The analysis involved 47 nucleotide sequences. All positions containing gaps and missing data were eliminated. There were a total of 309 positions in the final dataset. Evolutionary analyses were conducted in MEGA6.

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6

EXPERIMENT 4.1. CONTROLLED ATMOSPHERE STORAGE

6.1

Aim

To determine the effect of different controlled atmospheres on avocado fruit quality

6.2

Introduction

The effect of different controlled atmospheres (CA) used commercially was to be assessed by examining the quality of fruit upon arrival at destination ports. However, although the CA conditions are logged during transit, the companies do not disclose these. Therefore the aims of the project could not be met using this methodology. Instead a series of controlled experiments were conducted in Peru examining the effects of different controlled atmospheres on fruit quality. This report is written in the form of a scientific publication to allow easy dissemination of the results to growers and exporters in Peru, possibly by inclusion in an industry magazine.

6.3

Scientific paper

The Response of Peruvian ‘Hass’ Avocado Fruit to Controlled Atmosphere Storage V. Escobedo1, K. Vasquez1, D. Billing2, J. Burdon2 1. Asociación de Productores de Palta Hass del Perú- ProHass, Lima, Peru. 2. The Plant and Food Research Institute of New Zealand Ltd., Auckland, New Zealand. Abstract Peruvian ‘Hass’ avocado fruit are exported globally, with shipping times of up to 35 days to reach markets. It is common to use controlled atmosphere (CA) refrigerated containers to reach these markets, although atmospheres recommended or offered by the container suppliers can differ markedly. In this research, the impact of four CA regimes on fruit quality was examined: 2% O2 / 2% CO2; 2% O2 / 10% CO2; 4% O2 / 6% CO2; and 4% O2 / 10% CO2. Fruit quality was assessed immediately after 4 or 6 weeks of storage and when the fruit had ripened at 20°C. Overall, the incidence of disorders and rots was low, with few consistent differences among the CA treatments, although the high CO2 CA regimes tended to extend the fruit ripening time by up to 2.2 days. The exception was the high incidence of lenticel damage in all fruit, irrespective of CA treatment. It is concluded that for the fruit used in the trial, there was little difference between the four CA regimes in their impact on the quality of the fruit after storage and when ripe. 1. Introduction Exports of ‘Hass’ avocado fruit from Peru have reached 170,000 tons in 2015. Major markets for Peruvian fruit include Europe, USA, Japan and China, with shipping taking between 15 and 35 days to reach these markets. The shipping conditions under which fruit are exported are critical to the quality of the fruit that arrives at the importer, with the suggestion that refrigerated storage may keep ‘Hass’ avocado fruit in good condition for up to four weeks, but that disorders become more apparent with longer storage (Dixon et al., 2003). Major markets are thus on the limit of refrigerated storage life for quality and hence it is normal practice for Peruvian avocado exporters to utilize controlled atmosphere (CA) containers to extend the fruit’s storage life whilst maintaining the quality. The beneficial effects of CA storage on the storage life and quality of avocado fruit have long been recognized, (references listed in Thompson, 2010; Kader 2003), including the prolonging [52]

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of storage and reduction in rots and disorders. However, the research reported was undertaken on a range of cultivars, or on the same cultivar in different countries (growing environments). The CA conditions reported, or recommended, therefore should be considered in the context under which the research was conducted before being extrapolated to commercial situations. While recommendations exist for CA conditions for ‘Hass’ avocado fruit, (eg. Kader, 2003) these may not always be practical i.e. given as a wide range (2-5% O2 and 3-10% CO2) or if more specific, may not always be achievable within all CA shipping containers, dependent on the CA system utilized. Also, more recently, the impact of growing region on the storage performance of fruit in CA has been highlighted by the findings from New Zealand (Burdon et al., 2008), whereby the best quality seems to be achieved by an atmosphere of 2% O 2 and 2% CO2, whereas previously a 5% O2 / 5% CO2 atmosphere was used. This research has highlighted the need to optimize both oxygen and carbon dioxide concentrations within a CA regime and has highlighted the role of high CO2 concentrations in the prolonging of storage, retardation of ripening, and in New Zealand fruit, an increase in rot incidence (Burdon et al., 2008; 2010). Despite the reliance of the Peruvian avocado export industry on CA shipping containers, there appears to be no published information on the response of Peruvian ‘Hass’ avocado fruit to CA, or any reference to optimal CA conditions for these fruit. The aim of this study was to determine the response of Peruvian-grown ‘Hass’ avocado fruit to different CA regimes, with O2 concentrations of 2 or 4% and CO2 concentrations of 2 – 10%. 2. Materials and Methods 2.1 Fruit Fruit were commercially harvested from four orchards (designated O1 – O4) in mid-July 2015 when at ~23 - 24% dry matter. The fruit were from orchards ~200 km south of Lima (O1 and O2) and ~200 km north of Lima (O3 and O4). The fruit were commercially packed and transferred to the coolstore at the Instituto Nacional de Investigación Agraria (INIA) research facility at Huaral. For each orchard, a total of 24 packs, each of 16 – 20 fruit, were used for the trial. Packs were randomly allocated to each of the four treatments (CA regimes) and placed into coolstore at 6°C on the day of packing. This was the same coolstore in which the CA tents were operated. Before placing into coolstore, fruit were numbered and weighed so that weight loss could be determined throughout the trial. The fruit were supplied by four different packhouses and arrived at different times before the commencement of CA: O1 – 6 days; O2 – 4 days; O3 – 9 days and O4 – 8 days. As a consequence, fruit from the different orchards were at a different age post-harvest when CA was commenced. 2.2 Treatments Four CA regimes were established in ~ 2.6 m3 tents: Regime 1: 2% O2 / 2% CO2 (designated 2/2) Regime 2: 2% O2 / 10% CO2 (designated 2/10) Regime 3: 4% O2 / 6% CO2 (designated 4/6) Regime 4: 4% O2 / 10% CO2 (designated 4/10) Atmospheres were established over a period of 24 h, both at the start of the trial and also after removal of half the fruit after 4 weeks of storage, using humidified bottled gases (air, nitrogen and carbon dioxide) at a total flow rate of ~500 mL/min. 2.3 Assessments Fruit were removed from CA after 4 and 6 weeks for evaluation immediately (Green or unripe assessment) and also when ripe (fruit assessed as ripe by firmness). Fruit were allowed to ripen at 20°C without application of ethylene. Green (unripe) Immediately out of CA, the fruit were assessed for the following: Skin colour. A 1-6 scale where 1= emerald green; 2= forest green; 3= ~25% coloured; 4= ~75% coloured; 5= purple; 6= black; as defined by White et al. 2009. Lenticel damage. A 0-100 scale based on the proportion (%) of the fruit surface affected. Note in this case it is not all the surface, but only the lenticels that were considered. Black spot. A 0-100 scale based on the proportion (%) of the fruit surface affected. Surface mycelial growth. Scored as present or absent. [53]

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Ripe The fruit out of CA were left to ripen at 20°C and assessed for the following: Days to ripen at 20°C. Ripeness determined by the fruit firmness. Skin colour when ripe. A 1-6 scale where 1= emerald green; 2= forest green; 3= ~25% coloured; 4= ~75% coloured; 5= purple; 6= black; as defined by White et al., 2009. Body rots. A 0-100 scale based on the proportion (%) of the fruit affected. Stem-end rots. A 0-100 scale based on the proportion (%) of the fruit affected. Grey pulp. A 0-100 scale based on the proportion (%) of the fruit affected. 2.4 Data analysis Data have been described by the sample means and standard error of means (s.e.m.). Statistical separation of treatment means was by analysis of variance (ANOVA) using GenStat Release 14.2 [(PC/Windows XP) Copyright 2011, VSN International Ltd]. Multiple comparisons have been made using Fisher’s Protected LSD test at P=0.05. The incidences of disorders were angular transformed (arcsin(sqrt(x)) before analysis, with replication at the pack or orchard level. Data in the tables of disorder incidence are untransformed. Graphs were created using Origin v8.5 (OriginLab Corporation, One Roundhouse Plaza, Northampton, MA01060, USA).

3. Results 3.1 Green (unripe) Skin colour There was no difference in the skin colour of the fruit from the four CA treatments after 4 and 6 weeks of storage, with all treatment mean values being ~ 2.0 (Table 1). In addition, there was no progression of skin colour when the fruit were stored for six weeks compared with four weeks. Table 1. Skin colour of ‘Hass’ avocado fruit after storage in controlled atmospheres (2% O 2 / 2% CO2, 2% O2 / 10% CO2, 4% O2 / 6% CO2 and 4% O2 / 10% CO2) at 6°C for four and six weeks. Each value is the mean of four orchards, six packs each of 16-20 fruit per orchard. Treatment Skin colour (1-6 scale) after 4 weeks 6 weeks 2% O2 / 2% CO2 2.1 2.0 2% O2 / 10% CO2 2.0 2.0 4% O2 / 6% CO2 2.1 2.0 4% O2 / 10% CO2 2.0 2.0 Statistical analysis: ANOVA P-values Treatment 0.112 Week 0.657

Lenticel damage The incidence of lenticel damage was high, with an average incidence of >96% for all CA treatments and no statistically significant differences among treatments (Table 2). The average severity of lenticel damage for all CA treatments was in the range 36 – 42, with no statistically significant difference among treatments. The difference in the mean severity between fruit stored for four weeks and six weeks, whilst statistical, is unlikely to be real as the severity of damage is unlikely to be less with longer storage. The creation of lenticel damage is dependent on the state of the fruit at harvest combined with fruit handling practices, with expression then occurring during packing and storage.

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Table 2. Incidence and severity of lenticel damage on ‘Hass’ avocado fruit after storage in controlled atmospheres (2% O2 / 2% CO2, 2% O2 / 10% CO2, 4% O2 / 6% CO2 and 4% O2 / 10% CO2) at 6°C for four and six weeks. Each value is the mean of four orchards, six packs each of 16-20 fruit per orchard. Treatment Lenticel damage Incidence (%) after Severity (%) after 4 weeks 6 weeks 4 weeks 6 weeks 2% O2 / 2% CO2 96.4 98.5 37.8 35.9 2% O2 / 10% CO2 99.5 100.0 39.5 36.4 4% O2 / 6% CO2 95.9 99.0 40.5 35.9 4% O2 / 10% CO2 99.8 99.7 42.3 36.8 Statistical analysis: ANOVA P-values Treatment 0.058 0.298 Weeks 0.085 <0.001 Black spot The overall incidence of black spot on fruit from the four CA treatments was very low, with only five fruit from all treatments showing the disorder, with an overall average severity of 20 (data not presented). Surface mycelial growth On almost all fruit, there was a small amount of mycelial growth on the surface of the fruit on and around the cut pedicel. This growth did not penetrate the fruit and is therefore not classified as a stem-end rot, but is likely the result of the high humidity created by the CA system and not related to the use of CA per se. Table 3. Incidence of surface mycelial growth on ‘Hass’ avocado fruit after storage in controlled atmospheres (2% O2 / 2% CO2, 2% O2 / 10% CO2, 4% O2 / 6% CO2 and 4% O2 / 10% CO2) at 6°C for four and six weeks. Each value is the mean of four orchards, six packs each of 16–20 fruit per orchard. Treatment Incidence (%) of surface mycelial growth after 4 weeks 6 weeks 2% O2 / 2% CO2 99.7 100.0 2% O2 / 10% CO2 100.0 100.0 4% O2 / 6% CO2 99.5 100.0 4% O2 / 10% CO2 100.0 100.0 Statistical analysis: ANOVA P-values Treatment 0.493 Weeks 0.169

Weight loss The amount of weight lost by fruit during storage was low, on average 2.2% of initial weight after 4 weeks of storage and 2.9% after 6 weeks of storage (Figure 1). There were no statistically significant differences in weight lost among the CA treatments (P=0.116). The low weight loss is the result of the use of a high humidity system to create the CA conditions.

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4 weeks A

6 weeks B

4

4

3

Weight Loss (%)

Weight Loss (%)

3

2

1

0

2

1

0 2/2

2/10

4/6

4/10

2/2

Oxygen / Carbon dioxide

2/10

4/6

4/10

Oxygen / Carbon dioxide

Figure 1. Weight lost from ‘Hass’ avocado fruit during storage for 4 or 6 weeks at 6°C in controlled atmosphere conditions. Controlled atmosphere conditions were: 2% O 2 / 2% CO2 (2/2); 2% O2 / 10% CO2 (2/10); 4% O2 / 6% CO2 (4/6); 4% O2 / 10% CO2 (4/10). Each value is the mean of 4 orchards, 5 fruit from 6 packs per orchard, ± s.e.m.

While there were no significant differences in the weight loss among CA treatments, there were differences among orchards (Figure 2). The weight lost from O1 and O2 was less than from O3 and O4. This difference is likely the result of the fruit from O1 and O2 being in coolstore for a shorter period of time than fruit from O3 and O4 before the commencement of CA conditions, and the subsequent high humidity environment.

4 weeks A

6 weeks B

5

5

4

Weight Loss (%)

Weight Loss (%)

4

3

2

1

3

2

1

0

0 O1

O2

O3

O4

Orchard

O1

O2

O3

O4

Orchard

Figure 2. Weight lost from ‘Hass’ avocado fruit from four orchards (O1-O4) during storage for 4 or 6 weeks at 6°C in controlled atmosphere conditions. Each value is the mean of four CA treatments (2% O2 / 2% CO2 ; 2% O2 / 10% CO2 ; 4% O2 / 6% CO2 ; and 4% O2 / 10% CO2 ), ± s.e.m.

3.2 Ripe Time to ripen The time taken to ripen after CA storage was affected by the CA conditions (P<0.001; Figure 3). After four weeks of storage, the average time to ripen was between 4.7 days (2/2 atmosphere) and 7.3 days (4/10 atmosphere) and after six weeks of storage, ripening times had decreased (P<0.001) to between 3.2 days (2/2 atmosphere) and 5.9 days (4/10 atmosphere). The relativity in ripening times among the CA treatments was maintained between 4 and 6 weeks of storage, with fruit in the 2/2 atmosphere ripening fastest and fruit in the 4/10 atmosphere ripening slowest, although for each treatment the time to ripen reduced with increased storage. The time [56]

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taken for the slowest ripening fruit was ~ 2.5 days longer than for the quickest. This difference was consistent after both four and six weeks of storage. Overall, there appeared to be an effect of high CO2 increasing the time required for fruit to ripen after storage. For fruit stored at 2% O2, the difference in time to ripen between fruit stored in 2/2 and 2/10 was 1.4 days after four weeks and 2.2 days after 6 weeks – presumably the difference is the result of the CO2 being at 2% or 10%. Likewise, for fruit stored at 4% O2, the difference in time to ripen between fruit stored in 4/6 and 4/10 after four weeks was 1.2 days and after 6 weeks 1.1 days, presumably this difference is the result of the CO2 being at 6% or 10%. 4 weeks 6 weeks c

7 b

b

6

c

Days to ripen

bc

5

b

a

4 a

3 2 1 0 2/2

2/10

4/6

4/10

Oxygen / Carbon dioxide

Figure 3. Time taken for ‘Hass’ avocado fruit to ripen at 20°C following four or six weeks of storage under controlled atmosphere conditions. Controlled atmosphere conditions were: 2% O2 / 2% CO2 (2/2); 2% O2 / 10% CO2 (2/10); 4% O2 / 6% CO2 (4/6); 4% O2 / 10% CO2 (4/10). Each value is the mean of four orchards, six packs of 16-20 fruit per orchard. Data within a storage period not sharing a common letter differ at P=0.05 Body rots The average incidence of body rots in the four CA treatments were all ~ 6% or less, with no statistically significant differences among the treatments (P=0.416; Figure 4). The average incidence of body rots after six weeks of storage was lower (P=0.006) than after four weeks of storage; 1.8% and 4.6% respectively. The severity of the body rots that were present tended to mostly be ~ 8% or less, with no statistically significant effects of CA treatment (P=0.067) or storage period (P=0.773). Overall, whilst not statistically significant, there was a trend after four and six weeks of storage for the most severe body rots to be in the 4/6 CA treatment. Incidence Severity A B 10 20 4 weeks 6 weeks

4 weeks 6 weeks

Severity of BR (0-100)

Incidence of BR (%)

8

6

4

2

0

15

10

5

0 2/2

2/10

4/6

4/10

Oxygen / Carbon dioxide

2/2

2/10

4/6

4/10

Oxygen / Carbon dioxide

Figure 4. Incidence (A) and severity (B) of body rots (BR) on ripe ‘Hass’ avocado fruit following storage for four or six weeks in controlled atmosphere conditions followed by ripening at 20°C. Controlled atmosphere conditions were: 2% O2 / 2% CO2 (2/2); 2% O2 / 10% CO2 (2/10); 4% O2 / 6% CO2 (4/6); 4% O2 / 10% CO2 (4/10). Each value is the mean of four orchards, six packs of 16-20 fruit per orchard. Data within a storage period not sharing a common letter differ at P=0.05. [57]

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Stem-end rots The incidence of stem-end rots from all CA treatments after four or six weeks of storage were in the range 2 – 5% (Figure 5) with no statistically significant differences among treatments (P=0.213) or effect of storage duration (P=0.563). The severity of stem end rots was not consistent between 4 and 6 weeks of storage. Whilst after 4 weeks, the severity of stem end rots from 4/10 was significantly worse than for fruit from 2/10 and 4/6, this difference was not present after 6 weeks. Thus, overall, there was no significant difference in the severity of stem end rots among CA treatments (P=0.209) or with storage duration (P=0.971). Incidence A

Severity B

6

25

4 weeks 6 weeks

4 weeks 6 weeks

Severity of SER (0-100)

Incidence of SER (%)

20 4

2

0

b

15

10

ab a

a

5

0 2/2

2/10

4/6

4/10

Oxygen / Carbon dioxide

2/2

2/10

4/6

4/10

Oxygen / Carbon dioxide

Figure 5. Incidence (A) and severity (B) of stem end rots (SER) on ripe ‘Hass’ avocado fruit following storage for four or six weeks in controlled atmosphere conditions followed by ripening at 20°C. Controlled atmosphere conditions were: 2% O2 / 2% CO2 (2/2); 2% O2 / 10% CO2 (2/10); 4% O2 / 6% CO2 (4/6); 4% O2 / 10% CO2 (4/10). Each value is the mean of four orchards, six packs of 16-20 fruit per orchard. Data within a storage period not sharing a common letter differ at P=0.05.

Grey pulp The incidence of grey pulp in fruit from all CA treatments after four or six weeks of storage was low at < 3% (Figure 6). There was no statistically significant difference among CA treatments (P=0.507) or storage duration (P=0.567) for the incidence of grey pulp. Overall, there was a significant difference among CA treatments on the severity of grey pulp (P<0.001), largely a result of the six week data (P=0.008) in which the 4/6 severity data was significantly higher than that for the 2/2, 2/10 and 4/10 atmospheres (Figure 6). There was also an overall effect of increased severity after six weeks of storage compared with four weeks (P=0.007).

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Incidence A

Severity B

b

4 weeks 6 weeks

50

Severity of Grey Pulp (%)

Incidence of Grey Pulp (%)

3

2

1

0

4 weeks 6 weeks

40 30 a

20 a

a

10 0

2/2

2/10

4/6

4/10

Oxygen / Carbon dioxide

2/2

2/10

4/6

4/10

Oxygen / Carbon dioxide

Figure 6. Incidence (A) and severity (B) of grey pulp in ripe ‘Hass’ avocado fruit following storage for four or six weeks in controlled atmosphere conditions followed by ripening at 20°C. Controlled atmosphere conditions were: 2% O2 / 2% CO2 (2/2); 2% O2 / 10% CO2 (2/10); 4% O2 / 6% CO2 (4/6); 4% O2 / 10% CO2 (4/10). Each value is the mean of four orchards, six packs of 16-20 fruit per orchard. Data within a storage period not sharing a common letter differ at P=0.05. 4. Discussion There was little difference in the quality of fruit from the four CA treatments when assessed immediately after four or six weeks of storage. For fruit from all treatments, there was little change in skin colour from harvest and there was only a low incidence of black spot. The major feature of the fruit at this time was the high incidence of lenticel damage in fruit from all treatments. The CA treatments significantly affected the time taken for fruit to ripen after storage, with fruit from high CO2 treatments taking longer to ripen. Overall, the fastest and most uniform ripening occurred in fruit from the 2/2 treatment. Once ripe, the incidence of rots and grey pulp were low and sporadic across the CA treatments, with few statistically significant differences. Despite the lack of treatment effects immediately out of storage, there are a few aspects of significance for the utilisation of CA storage and the quality of the fruit. The most significant aspect of fruit quality was the high incidence of lenticel damage. This arises as a result of the water status of the fruit at harvest in conjunction with handling that causes damage to the turgid cells of the lenticels (Everett et al. 2008). This aspect of fruit quality is not a result of, or affected by, CA storage, rather it requires management of the timing of fruit harvest with respect to the turgidity of the fruit, in particular after rainfall or irrigation which leaves the fruit turgid and the lenticels susceptible to damage. The lack of a change in skin colour from harvest is suggestive of the fruit development not having progressed excessively towards ripening during the storage period. It also suggests that despite the difference in the postharvest age of the fruit when CA was commenced, (between 5 and 10 days after harvest) this difference in the fruit did not affect the quality of the fruit at the end of storage. This suggests that fruit could possibly be stored for longer; a suggestion also supported by the relative lack of grey pulp in the fruit when ripe. Delaying the application of CA has previously (Burdon et al. 2008) been reported to have a negative impact on the quality of fruit after storage, by reducing the time taken in storage for the fruit to commence ripening, and thereby result in grey pulp (also called diffuse flesh discoloration) in the ripe fruit. Commercially, there will always be a degree of delay dependent on harvest and load-out schedules, although the degree of impact on fruit quality is rarely investigated, possibly only becoming significant when storage life is extended beyond six weeks. The different CA treatments markedly affected the time taken for fruit to ripen after storage, with the higher CO2 atmosphere prolonging the ripening time. The ripening time for avocado fruit has been associated with two aspects of quality: the uniformity of ripe fruit within a pack and the incidence of rots. The longer the ripening time, the greater the variability among individual fruit that can lead to what is called a checker-board appearance in the pack – i.e. a mix of green and black skinned fruit in the same pack. In addition, the longer the time taken for fruit to ripen, the greater the opportunity for the fruit to rot. This association between increased ripening time and [59]

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increased rot expression has been suggested previously (Everett and Pak 2002; Burdon et al. 2008), although how much of the difference was due to ripening time and how much due to some other effect of CO2 was not clear. Previously, the application of high CO2 CA regimes has been reported to reduce the incidence of rots (Spalding and Reeder, 1975; Prusky et al. 1993). Also, in other circumstances where differences in rot expression and ripening time have been noted, there were also other factors such as ripening temperature to consider (Hopkirk et al. 1994). The incidences of disorders and rots in the ripe fruit were low and sporadic across CA treatments, with few statistically significant treatment effects. The overall low incidence of rots suggests that considerations of CA atmospheres that may stimulate or inhibit rot expression may not be so significant in the storage of Peruvian ‘Hass’ avocado fruit. The main physiological disorder of concern in stored avocado fruit is grey pulp, which is a symptom that develops when fruit are held at storage temperatures for too long and the fruit starts to ripen. The low incidences of grey pulp across all CA treatments suggests that there may be potential for fruit to have been stored for longer, at which time differences among the CA treatments may be visible. In particular, the longer ripening times of fruit from the high CO 2 CA treatments may also relate to later development of grey pulp in storage. Conversely, the use of high CO 2 CA for only short periods of storage may leave the fruit susceptible to variability and development of checkerboarding if the fruit then ripen over a protracted period without ethylene. It is concluded that for the fruit used in this trial, the four CA treatments used for four or six weeks of storage made little difference to the fruit quality when assessed either immediately out of storage, or when ripe. However, what is obvious, but not related to CA, is the need for lenticel damage to be considered and managed when harvesting and handling the fruit. Acknowledgements The authors gratefully acknowledge the assistance of the following: INIA – Donoso, for access to coolstore facilities, Edwin Campoa for technical assistance with evaluations and Oxitec company for construction of the gas mixing equipment. This work was funded by ProHass. References Burdon J, Lallu N, Haynes G, McDermott K, Billing D. 2008. The effect of delays in establishment of a static or dynamic controlled atmosphere on the quality of ‘Hass’ avocado fruit. Postharvest Biol. Technol. 49, 61-68. Burdon J, Lallu N, Haynes G, Pidakala P, McDermott K, Billing D. 2010. Dynamic controlled atmosphere storage of New Zealand-grown ‘Hass’ avocado fruit. Acta Hortic. 876, 47-54. Dixon J, Pak HA, Mandemaker AJ, Smith DB, Elmsly TA, Cutting JGM. 2003. Fruit age management: the key to successful long distance export of New Zealand avocados. NZ Avocado Growers’ Association Annual Research Report, 3, 60-65. Everett KR, Pak HA. 2002. Patterns of stem-end rot development in coolstore. NZ Avocado Growers’ Association Annual Research report, 2, 1-9. Everett KR, Hallett IC, Rees-George J, Chynoweth RW, Pak HA. 2008. Avocado lenticel damage: the cause and the effect on fruit quality. Postharvest Biol. Technol. 48, 383-390. Hopkirk G, White A, Beever DJ, Forbes SK. 1994. Influence of postharvest temperatures and the rate of fruit ripening on internal postharvest rots and disorders of New Zealand ‘Hass’ avocado fruit. NZ J Crop Hort Sci 22, 305-311. Kader AA. 2003. A summary of CA requirements and recommendations for fruits other than apples and pears. Acta Hort 600: 737-740. Prusky D, Plumbley RA, Kobiler I, Zauberman G, Fuchs Y. 1993. The effect of elevated CO2 levels on the symptoms expression of Colletotrichum gloeosporiodes on avocado fruits. Plant Pathol., 42, 900-904. Spalding DH, Reeder WF. 1975. Low oxygen high carbon dioxide controlled atmosphere storage for control of anthracnose and chilling injury of avocados. Phytopathology, 65, 458-460. Thompson AK. 2010. Controlled atmosphere storage of fruits and vegetables. 2 nd Edition. CABI, UK. White A, Woolf A, Hofman P, Arpaia ML. 2009. The International Avocado Quality Manual. The New Zealand Institute for Plant and Food Research. ISBN 0-478-06845-X. pp 10-11.

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7

EXPERIMENT 4.2 GREY PULP SUSCEPTIBILITY (LIBRARY TRAYS)

In this experiment, commercially packed fruit were held in coolstore for up to 6 weeks and the quality of the fruit assessed immediately on removal from storage and also after ripening. The results from the trial were thus dependent on the correct assessment of the fruit and, for the ripe fruit, the timing of when to assess the fruit was dependent on the fruit being “ripe soft”, but not under- or over-ripe. Given the rate at which ‘Hass’ avocado fruit ripen, fruit needed to be checked daily for ripeness. 12 Aim

7.1

Aim

To understand the behaviour of export avocados from different growing areas in Peru, with special reference to grey pulp and stem-end rot, through use of a library tray system

7.2

Procedures

12.2 Procedures Commercially harvested and handled fruit (10 packs) were removed from the packing line and stored for 0, 2, 4, 5 or 6 weeks before removal from storage and assessment immediately out of store (Unripe assessment) and again when ripe (Ripe assessment). Two packs of fruit were removed at each storage assessment and the fruit were ripened at 20ºC without ethylene. he Unripe assessment involved a visual examination of the whole fruit, whereas the Ripe assessment comprised both a visual assessment of the whole fruit and also a destructive assessment of the internal quality of the fruit after quartering and peeling the fruit. The Ripe assessment was done when the fruit had reached ‘eating ripeness’, as determined by the fruit firmness in the hand. The scales and abbreviations for skin colour, disorders and rots are given in Table 12. The incidence of fruit with disorders and rots were recorded. The average severity data presented are for those fruit with the disorder or rot, excluding sound fruit. Vascular browning was recorded as present or absent. Table 12. Skin colour, disorders and rots of Peruvian ‘Hass’ avocado fruit assessed immediately out of storage (Unripe) and when ripe (Ripe). Assessment Unripe

Ripe

Factor/disorder/rot

Abbreviation

Scale

Skin colour

SC

1-6

Lenticel damage

LD

0-100

Black spot

BS

0-100

Skin colour

SC

1-6

Body rot

BR

0-100

SER

0-100

Grey pulp

GP

0-100

Vascular browning

VB

Present/absent

Stem end rot

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7.3

Results

7.3.1

Year 2-3 Summary and overview of data

The observations from 2014 and 2015 were essentially similar. Where given, the dry matter data suggest that all fruit used in the trial were in the range 24–28% dry matter for 2014. For 2015, the dry matter data show that the batch averages for the fruit used in the trial were in the range 20–28% dry matter. While there were no individual fruit dry matter data, with batch averages as low as 20% it is likely that there were significant numbers of fruit with dry matter < 20% in those samples that had dry matter averages of 2021% (company C7). It is of interest that the fruit with these low dry matters (20-21%) took a long time to ripen and also had low incidences of sound fruit when ripe. The inclusion of data on the incidence of sound fruit when ripe refers only to fruit with or without ripe fruit disorders. This is because lenticel damage affected the majority of the fruit, and thus lenticel damage would mask other aspects of fruit quality. Weight loss would be expected to increase with time in storage, and the range of weight loss seen after 6 weeks was 3.7%–7.8%. In most samples there was an increase with increased time in storage, with the differences in the degree of water loss likely to be largely due to the holding environment, with minor variations due to orchard and/or fruit maturity. The Unripe assessment of fruit immediately out of storage was more straightforward than that for the Ripe fruit, for which optimal ripeness for evaluations (‘eating ripeness’) had to be assessed. For most samples, the scoring of skin colour out of storage at 1–2 seems correct, especially with a slight increase in skin colour score in the longer-stored fruit, as would be expected from the progression towards ripening that occurs during storage. Lenticel damage tended to be present at a similar incidence for all storage times, including in fruit that had not been cool stored. These incidence data, in conjunction with the severity data remaining similar, or increasing slightly, during storage, are indicative of the damage occurring at harvest and not being the result of storage. The fact that the majority of the fruit in the trial showed some degree of lenticel damage suggests that the water status of the fruit at harvest should be considered in the timing of harvest, along with the handling of the fruit at, and after, harvest. Black spot incidence and severity data contrasted with lenticel damage in that black spot tended to appear after a period of storage and in some instances was not seen, irrespective of storage period. This suggests the disorder was caused by storage conditions, but that not all fruit were susceptible. An alternative explanation is that the absence of black spot may have been due to different storage conditions among the samples. This is where a common storage environment would allow for increased comparability among samples of fruit. In summary, data from ripe fruit assessments depend on the accuracy with which fruit ripeness is assessed, and hence when fruit are assessed for disorder and rots. Without storage, sample average fruit ripening times were between 8 and 34 days. The ripening times declined with increased time in storage. A ripening time of 34 days seems excessive, although these were fruit that had a low average dry matter at harvest. A protracted ripening time is also seen in fruit treated with 1-MCP, although there was no record of 1-MCP use in this trial. It is generally accepted that the longer the ripening time, the greater the opportunity for rots to develop on the

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fruit, possibly contributing to the low incidence of sound ripe fruit in these samples that took so long to ripen. Despite the inconsistencies due to timing of the assessment of ripe fruit, some aspects of the data can be linked to existing knowledge. The presence of stem-end and body rots tends to depend on the amount of inoculum on the fruit from the orchard; thereafter, rot expression can depend on the time in storage and the time taken to ripen. Hence, there may be a U-shaped incidence of rot in association with storage, high when ripened without storage, a reduced incidence after 1–2 weeks of storage when fruit ripen more quickly out of store, and then an increase in incidence when fruit have been stored for 4+ weeks. The occurrence of grey pulp in fruit tends to be regarded as a sign that fruit have been stored for too long, and that ripening has started whilst the fruit were still in coolstorage. Generally, from the samples assessed, grey pulp tended to be found in fruit from the later storage assessments, although symptoms in fruit that had not been stored, or had only been in store for a short time, were also recorded. Whilst similar symptoms have been noted from other cultivars direct from the tree, this is not normal for ‘Hass’. The minor disorders of ripe fruit were sporadic in occurrence. Overall, a library tray system of looking at the quality of the exported fruit shows up any issues of disorders and rots at a gross scale. While it is indicative of the quality of the fruit, it does not equate exactly to the performance of the exported fruit, since fruit are exported under controlled atmosphere (CA) conditions. The use of CA delays the time at which ripening starts in coolstorage, and this therefore affects some elements of quality. However, the system can provide good information on the comparative performance of fruit from a single orchard through the harvest season, and also among orchards, especially where environmental conditions may vary. The validity of a library tray system largely depends on being able to make the ripe fruit assessment at the correct stage of development; assessing fruit when under-ripe or over-ripe will affect the incidence and severity of disorders. A record of both incidence and severity for disorders and rots is essential to fully describe the quality issues. The creation of an overall sound or unsound category with which to compare the quality of fruit may require further development with respect to thresholds of severity for inclusion. Scientifically, the full severity data are useful to understand the underlying biology. However, commercially, it may be better only to score as unsound those disorders or rots for which the severity exceeds that which is commercially relevant.

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8

REFERENCES

Agrios G 1997. Plant Pathology (4th Ed.). San Diego, London, Academic Press. Bock CH, Graham JH, Cook AZ, Parker PE, Gottwald TR 2013. Predisposition of citrus foliage to infection with Xanthomonas citri subsp. citri. Journal of Plant Pathology 95(1): 99-106. Dixon J, Pak HA, Smithy DB, Elmsly TA, Cutting JGM 2003 New Zealand avocado fruit quality: The impact of storage temperature and maturity NZ Avocado growers’ Association Annual Research Report 3: 48-53. Estrada AB, Dodd JC, Jeffries P 2000. Effect of humidity and temperature on conidial germination and appressorium development of two Philippine isolates of the mango anthracnose pathogen Colletotrichum gloeosporioides. Plant Pathology 49(5): 608-618. Everett KR 2002. Avocado fruit rots: A review of industry funded research. In: Pak HA ed. NZ Avocado Growers' Association Annual Research Report. Tauranga, Avocado Growers' Association. Pp. 8-16. Everett KR, Barefoot MD, Requejo-Jackman C, Woolf AB 2013. External and internal quality of 'Hass' avocados- Analysis of results of experiments for Agrokasa, Peru. prepared for Sociedad Agricola Drokasa, S.A. Contract No. 27812. SPTS No. 7976. Everett KR, Boyd LM, Pak HA, Cutting JGM 2007. Calcium, fungicide sprays and canopy density influence postharvest rots of avocado. Australasian Plant Pathology 36(1): 22-31. Everett KR, Hallett IC, Rees-George J, Chynoweth RW, Pak HA 2008. Avocado lenticel damage: the cause and the effect on fruit quality. Postharvest Biology and Technology 48(3): 383-390. Everett KR, Korsten L 1996. Postharvest rots of avocados : improved chemical control by using different application methods. Proceedings of the Forty Ninth New Zealand Plant Protection Conference, Quality Hotel Rutherford, Nelson, New Zealand, 13-15 August, 1996. Pp. 37-40. Everett KR, Korsten L 1998. The effect of six postharvest management regimes on ripe rots of 'Hass' avocado. Proceedings of the Fifty First New Zealand Plant Protection Conference, Quality Hotel, Hamilton, New Zealand, 11-13 August, 1998: 112-116. Everett KR, Pak HA 2001. Orchard survey: effect of pre-harvest factors on postharvest rots. NZ Avocado Growers' Association Research Report. Pp. 12-17. Everett KR, Pak HA 2002. Patterns of stem-end rot development in coolstorage. NZ Avocado Growers' Association Research Report 2: 68-74. www.avocadosource.com. Felsenstein J 1985. Confidence limits on phylogenies: An approach using the bootstrap. Evolution 39: 783-791. Hartill WFT, Everett KR 2002. Inoculum sources and infection pathways of pathogens causing stem-end rots of 'Hass' avocado (Persea americana). New Zealand Journal of Crop and Horticultural Science 30(4): 249-260. Kok RD, Bower JP, Bertling I 2011 Enhancement of ‘Hass’ avocado shelf life using ultra-low temperature shipping or 1-MCP treatment and cold chain management VII World Avocado Congress. 5-9 September, Cairns Convention Centre. Cairns, Australia.

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Pesis E, Ackerman M, Ben-Arie R, Feygenberg O, Feng X, Apelbaum A, Goren R, Prusky D 2002. Ethylene involvement in chilling injury symptoms of avocado during cold storage. Postharvest Biology and Technology 24 171-181. Saitou N, Nei M 1987. The neighbor-joining method: A new method for reconstructing phylogenetic trees. Molecular Biology and Evolution 4: 406-425. Spalding DH, Reeder WF 1975 Low-oxygen high-carbon dioxide controlled atmosphere storage for control of anthracnose and chilling injury of avocados Phytopathology 65: 458-460. Suslow TV, Cantwell M, Mitchell J 1997. Honeydew: Recommendations for maintaining postharvest quality. Perishables Handling #89. Davis, University of California. http://postharvest.ucdavis.edu/PFfruits/Honeydew/. Tamura K, Nei M 1993. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Mol. Biol. Evol. 10: 512-526. Tamura K, Stecher G, Petersen D, Filipski A, Kumar S 2013. MEGA6: Molecular evolutionary genetics analysis version 6.0. Mol. Biol. Evol. 30: 2725-2729. White A, Woolf A, Hofman P, Arpaia M-L 2009. The International Avocado Manual. Auckland, New Zealand, The New Zealand Institute for Plant and Food Research Limited. White T, Bruns T, Lee S, Taylor J 1990. Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics In: Innes M, Gelfand D, Sninsky J, White T eds. PCR Protocols: A Guide to Methods and Applications. San Diego, CA, USA: Academic Press. Pp. 315-22. Zitter TA, Hopkins DL, Thomas CE 1996. Compendium of Cucurbit Diseases. St. Paul, MN, APS Press.

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APPENDIX 1.1. GENERAL EXPERIMENTAL DESIGN AND ASSESSMENT PROTOCOL

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APPENDIX 1.2. STATISTICAL ANALYSES The statistical analyses for Experiments 1.1, 1.2, and 2.1 were conducted in SAS 9.4. All incidence data were analysed using a logistic regression, with the various treatments and their interaction effects included in the model. Additionally box effects were included, as were tree and row effects where appropriate. Firthâ&#x20AC;&#x2122;s penalised likelihood was used to address the possible bias in the model parameter estimates due to the rare (black spot) or extremely frequent (lenticel damage) observations. A scale parameter was estimated using the deviance to account for possible overdispersion. The severity scores for fruit with the respective defect present were analysed using a mixed model with the treatments and their interaction effects treated as fixed, and with the box, tree, and rows, where present in the sampling plan, as random effects. This allowed for the study design to be taken in account when constructing the statistical tests. The statistical significances of the treatment and interaction effects were tested at the 5% level. For Experiments 2.2, 3.1 and 4, statistical separation of treatment means was by analysis of variance (ANOVA) using GenStat Release 14.2 [(PC/Windows XP) Copyright 2011, VSN International Ltd]. The incidences of disorders were angular transformed (arcsin(sqrt(x)) before analysis, with replication at the pack level. Data in the tables of disorder incidence are untransformed. Graphs were created using Origin v8.5 (OriginLab Corporation, One Roundhouse Plaza, Northampton, MA01060, USA). For Experiment 3.3, the R (R Core Team 2014) package was used to perform chi-square tests.

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APPENDIX 1.3. DETAILED PROTOCOLS FOR ORCHARD QUALITY EXPERIMENTS

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PART 2. DRY MATTER AND MATURITY OF PERUVIAN AVOCADOS

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PART 2. EXECUTIVE SUMMARY

Dry matter and maturity of Peruvian avocados Woolf AB, Olsson SR, Feng J, Richards KK, Wohlers MW Plant & Food Research Auckland March 2016

Introduction Dry matter (DM) accumulation is the internationally accepted technique used to determine timing of harvest for avocado fruit. The Peruvian industry has recently adopted a recommended (Servicio Nacional Agraria de Peru – SENASA) minimum DM of 21.5% for exported ‘Hass’ fruit. However, although many companies in Peru carry out routine DM measurements, there has been no comprehensive and consistent study of changes across the diverse growing regions of Peru throughout the season. Also, DM sampling tends to cease once commercial harvest occurs, and thus there is little information on DM changes after this point. Some industry personnel believe that the fruit from their region have different oil contents at a given DM and that their fruit will be of superior flavour (thus justifying earlier harvest than that based on DM alone). Other aspects that are of interest are whether fruit of different sizes have different DM, and the variability in dry matter between individual fruit. Over two seasons (2014 and 2015), avocado fruit for DM analysis were sampled on a fortnightly basis from 7–10 export companies across 14 regions in diverse latitudes and environments, including altitudes up to 2300 m. Each company sampled from one to three orchards or blocks in their regions, leading to a total of 27 and 20 (2014 and 2015, respectively) maturity areas. In 2014, fewer samples were collected and sampling commenced not as early as in 2015. Oil content was determined in the 2014 season on a subset of dried tissue samples using petroleum ether in a Soxhlet system. Some orchards measured dry matter in small and large fruit, and in 2014, some orchards examined dry matter of 21 individual fruit to examine the fruitto-fruit DM variability. Results 

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The data from the 2014 season were less reliable than those from 2015 because of the lower sample numbers (e.g. 3-5 compared with 6-12). For data showing acceptable fit, the average rate of DM accumulation was ≈ 1.4%/month for 2014, and 2.2%/month for 2015. There were large differences in rate of DM accumulation between orchards (1.26–3.81% DM/month). For a few orchards, there was an indication that DM levelled out at ≈ 30% later in the harvest season. Most orchards reached the SENASA-recommended minimum commercial maturity (currently 21.5% DM) in May or June. However, some orchards reached commercial maturity as early as February 1, and others as late as the end of June. Although the average time to reach commercial maturity did not differ between seasons, some orchards showed significant differences (up to 5 weeks), thus emphasising the need to monitor every season. Some of these differences in timing may be due to flowering date, or rate of accumulation.

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 

The variation of DM within a 21-fruit sample was not strongly affected by maturity (i.e. a sample with a lower average DM was only slightly more variable than a sample with a higher average DM). Using a lower DM cut-off of 18% rather than 21.5%, up to three fruit in a 21-fruit sample (i.e. 15% of the fruit) would be deemed unacceptable by a consumer (based on a Californian sensory study). For some orchards, there were differences in DM with fruit size (particularly large v. small fruit) although these differences varied between orchards/companies. Fruit quality of stored fruit harvested across a range of DM values (17-27%) showed that disorders such as stem-end rots, body rots and vascular browning were higher at lower DM and reduced to negligible above after 24% DM. The correlation of oil content with DM (examined in 2014 only) showed a strong linear relationship typical of ‘Hass’ observed in other countries, with no consistent effect of orchard (e.g. altitude) observed.

These results provide a strong benchmark on the pattern of DM accumulation in most growing regions, the effect of fruit size on DM, the effect of DM on ripe fruit quality, and demonstrate the typical relationship of DM with oil content. Conclusions and recommendations  All companies should consider undertaking routine DM monitoring on a fortnightly basis to better predict timing of the minimum commercial maturity (currently 21.5%).  DM sampling should begin 2.5–3 months before the historical commercial harvest time, with at least 10 harvests carried out over the season.  The current sampling protocol (21 fruit) is sufficient to provide robust data.  There was some effect of fruit size on DM. While fruit size, particularly extremes, can influence fruit DM, we see no need to change the recommendations of harvesting “medium” sized fruit when monitoring, although if possible smaller fruit (<150 g) should be avoided.  The industry should consider setting up a number of standard monitoring orchards to provide ongoing data to compare across seasons.  Industry minimum harvest could include a lower DM fractile criterion (as used in New Zealand) to reduce the proportion of low DM fruit in the population that are likely to be poor-tasting fruit.  The effect of DM on ripe fruit quality after storage shows the important negative impact that low DM content at harvest has on quality of fruit after storage and ripening. This lends support to increasing the minimum standard to improve outturn quality in the market.  Oil content (carried out in 2014 only) showed a linear and strong correlation to DM, which is typical of that found internationally. There was no effect of growing environment on the relationship between DM and oil content; therefore, DM continues to be the only recommended measure of maturity.  Results in the 2015 season lend support for increase of the commercial minimum DM value above 21.5% based on the ripe fruit quality after storage (Section 2.5), and knowledge of sensory responses to DM. Such an increase in minimum DM value will likely improve taste and fruit quality in international markets, which will improve market and consumer perception of Peruvian avocados.

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9

GENERAL INTRODUCTION

Measuring maturity is a key issue in any fruit crop, and the only simple tool for avocado is that of dry matter (DM). With the instigation of a new minimum DM level for harvest in Peru, there is increasing focus on this area. This area of the ProHass-funded research seeks to increase our understanding in this area by examining maturity over as many growing regions in Peru as possible while examining other aspects such as effects of fruit size and DM variability within a sample.

9.1.1

Measures of maturity in avocado

The decision when to harvest is an important issue for any fruit crop and is generally decided on by selecting a time when fruit reach a given maturity. However, maturity has a range of definitions and is not a simple definitive meaning, but rather is relatively “grey”. (It is important to note too that in English “maturity” and “ripeness” (softening) mean very different things, something that is generally not translated in Spanish.) One definition of maturity is “horticultural maturity” where the fruit is harvested at a stage of development that aims to meet consumer requirements (e.g. ripen to an acceptable taste and general quality), while the other definition is more scientific, that of “physiological maturity” where the fruit will continue to physiologically develop (ripen for seed dispersal) after harvest (Watada et al. 1984). Avocados are unique in that they do not ripen while attached to the tree, which means fruit can be held on the tree for a considerable time after reaching physiological maturity (i.e. have the ability to ripen when removed from the tree), and this can be as long as a year in some countries. Another point of difference in avocado are that they continue to develop new cells over the season (Schroeder 1985), something which is very different to most fruit which have distinct phases of cell division and a final cell expansion phase (near harvest). Although fruit do not ripen on the tree, changes occur in the avocado including increased oil and dry matter content, reduced shelf life (time to ripen), and once past a minimum maturity, generally a decrease in long-storage life (due to increased flesh greying and/or rots). In most other fruit crops there are obvious or easily measured maturity changes such as fruit colour, ethylene production, soluble solids content (%SSC or Brix°), fruit firmness, starch, or other factors. For example apples have at least five maturity indices used to decide on a harvest date. However, although much research has been carried out, avocados basically have only one ready measure dry matter (or the inverse - moisture content) which is measured by simply drying a sample of tissue to a constant weight and expressing the value on a percent of its initial (wet) weight. Avocado maturity indices were initially based on oil content, but DM has become the standard because it is more rapid, cheaper, safer (no toxic solvents required) and more suitable for packhouses for monitoring maturity than oil content (Lewis 1978; Ranney et al. 1992). Oil content and DM are highly correlated and work in the 1980s has led to the adoption of DM as the international standard.

9.1.2

Selection of a minimum DM value for harvest

Avocado industries around the world use DM and generally define a minimum DM level for each cultivar at which fruit can be harvested for marketing. For ‘Hass’ the range of minimum DM values ranges from 20.8% (USA), to as much as 24 or 25% (New Zealand and South Africa, respectively; http://www.avocadosource.com/). In late 2014, the Peruvian avocado industry adopted a minimum value of 21.5%. While most industries use an average DM value, the New Zealand industry employs a lower fractile system where the DM on 20 fruit are [119]

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determined individually, and no two fruit may fall below 18% DM. This endeavours to reduce the proportion of very low DM fruit. Many countries carry out routine DM monitoring as an industry. For example, even the relatively small industry in New Zealand has monitored the same five orchards every year in three growing regions for over 12 years. DM measurements are made on an individual fruit basis to determine the spread of DM. This involves up to 5000 dry matter measurements, and demonstrates the industryâ&#x20AC;&#x2122;s commitment and rigour to this important area. It is important to note the significant variation between regions and seasons. For example, the 2005 season was significantly later than 2002, 2004 and 2006, and the rate of DM increase was much slower in 2003, particularly for the Bay of Plenty region. Although many companies in Peru carry out routine measurements of DM, there has been no comprehensive and consistent study of changes in DM across the diverse growing regions of Peru. Routine monitoring allows the industry and exporters to plan harvest and marketing effectively and ultimately will lead to greater returns to the industry as a whole. While DM is one measure of maturity that is readily determined, other measures are required to determine where fruit quality problems occur following typical storage periods used for export. Work by Ranney (1991) and other more recent examples (Pak et al. 2003) examine the effect of minimum maturity on ripe fruit quality. Problems observed with storage of low DM fruit are disorders such as uneven ripening (hard flesh spots), stringy vascular, higher body and stemend rots. Pak found that the minimum DM levels (i.e. not the average) best predicted poor quality.

9.1.3

Overview of work carried out

This work provides robust information on changes in DM over the season, within and between orchards/blocks, in seven regions, diverse growing environments and elevations. There is a belief in Peru that fruit size influences dry matter, and so we also examined this aspect. The variability of dry matter among individual fruit was also examined. This provides some useful information on what proportion of fruit might be considered below acceptable maturity at a given average maturity. Finally, while previous work has shown oil content and DM to be highly correlated (Lewis 1978; Ranney et al. 1992; Woolf et al. 2009) some Peruvian industry personnel believe that the fruit from their region have different oil contents at a given DM and that this is the reason for their fruit to have superior flavour, and that this warrants harvesting at an earlier date. Thus, we sought to examine the correlation of dry matter and oil content in the 2014 season. Determining taste acceptability is a more problematic research area due to the high cost, variability of consumer response, and logistical challenges (tasting through a season). This area was not carried out due to the cost, and lack of sensory skills in Peru.

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SUMMARY OF LAST SEASON’S WORK (2014) The work carried out last season (covering the 2014 season) was divided into five areas as follows: Trial 5.1

Measuring dry matter over a long period (6-10 months) using fruit of medium size

Trial 5.2

Measuring dry matter of a range of fruit sizes around the main harvest period

Trial 5.3

Collecting fruit at a range of fruit maturities and storing the fruit to determine the effect of maturity on ripe-fruit quality (e.g. stem-end rots, vascular strands)

Trial 5.4

Measuring DM of individual fruit on three occasions (around the main harvest season), to understand fruit-to-fruit variability of DM

Trial 5.5

Correlation of oil and dry matter.

10

TRIAL 5.1. CHANGES IN DRY MATTER OVER TIME

The rate of DM accumulation was generally similar for each orchard, with an average DM accumulation of ≈ 1.4%/month. However, some orchards had significantly faster or slower DM accumulation rates, ranging from 1.3%/month to 3.2%/month. However, some of these lower rates may be due to vagrancies of sampling, i.e. significantly higher initial, or later DM values resulted in “flatter” line fits. Fruit grown at higher altitude tended to have a higher rate of DM accumulation. For a few orchards, there was an indication that DM levelled out at ≈ 30%. Most orchards reached the SENASA-recommended minimum commercial maturity (currently 21.5% DM) in May or June. However, a cluster of five orchards were significantly earlier (i.e. JAC, JPP, JPR, JPH and EC), reaching commercial maturity in March. It was recommended that sampling earlier in the season would have provided more robust data for many orchards.

11

TRIAL 5.2. EFFECT OF FRUIT SIZE ON DRY MATTER

For some orchards, there were differences in DM with fruit size, but the differences were generally not large (average of 1-2%). However, sampling earlier in the season from a diverse range of fruit sizes could yield a statistically significant effect, although these differences will vary between orchards/companies.

12

TRIAL 5.3. EFFECT OF MATURITY ON STORAGE AND FRUIT QUALITY

This was not analysed, as sampling times and quality of ripe fruit data were not acceptable and it was recommended that this area was repeated in the 2015 season.

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13

TRIAL 5.4. INDIVIDUAL FRUIT DRY MATTER

The variation of DM within a 21-fruit sample was not strongly affected by maturity (i.e. a sample with a lower average DM was only slightly more variable than a sample with a higher average DM). Using a lower DM cut-off of 18% rather than 21.5%, up to three fruit in a 21-fruit sample (i.e. 15% of the fruit) would be deemed unacceptable by a consumer (based on a Californian sensory study).

14

TRIAL 5.5. CORRELATION OF OIL CONTENT WITH DRY MATTER

The correlation of oil content with DM showed a strong linear relationship typical of ‘Hass’ observed in other countries, with no consistent effect of orchard (e.g. altitude) observed. There was thus no reason to carry out further oil analysis in the 2015 season. Overall the results in 2014 formed a strong initial base of data which showed effects of DM changes over the season, orchard differences, fruit size effects, variability between individual fruit DM, and confirmed the robust correlation of oil with DM.

THIS SEASON’S WORK (2015) ProHass and most companies were willing to repeat and extend the sampling of many aspects of these Trials. Thus, this season (2015), four of the five areas carried out last year were repeated. For each Trial below, we note comparison of the effort compared with that for last season’s work and outline what data are presented in this report: Trial 5.1

Measuring dry matter over a long period (6–10 months) using fruit of medium size: In 2015 this was carried out with seven companies (compared with 10 in 2014), but, significantly, sampling was started earlier and carried out over a longer period. This yielded significantly better results.

Trial 5.2

Measuring dry matter of a range of fruit sizes around the main harvest period: In 2015 this was carried out with seven companies (compared with 10 in 2014), but on fewer occasions than in 2014.

Trial 5.3

Collecting fruit at a range of fruit maturities and storing the fruit to determine the effect of maturity on ripe-fruit quality (e.g. stem-end rots, vascular strands): Much greater effort was put into this area in 2015 with most companies. Although much of the data was not of acceptable quality, enough data were collected to make some preliminary conclusions.

Trial 5.4

Measuring DM of individual fruit on three occasions (around the main harvest season), to understand fruit-to-fruit variability of DM: Only one company carried out this work in 2015, and thus no data will be presented.

Trial 5.5

Correlation of oil and dry matter: Because the results in 2014 were so conclusive (i.e. a high correlation of dry matter to oil content), this work was not repeated in 2015.

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15

GENERAL METHODS

The full detailed methodology, which was translated into Spanish and provided to all companies, with associated training by ProHass staff, can be found in Appendix 1. Fruit were sampled from seven different companies (Table 2.1) spread over ten regions of Peru (Figure 2.1). This season (2015) three orchards did not participate in these DM trials, and for some orchards only two blocks were sampled, while one used three blocks where last season it used one. The companies and orchards examined are summarised in Table 2.1 with comparison to the 2014 season, and there were a total of 20 sites (company, orchard or blocks within orchards) compared with 27 last season. A spreadsheet was developed with sampling times and frequencies (Appendix 2 of Woolf et al. 2015), and spreadsheets were provided for data capture (data not shown). Because each region is different, and packhouses/companies had differing resources, the experiments were tailored to each company. Harvests involved measuring maturity once every two weeks beginning after the main flowering period, and storing the dried tissue for subsequent oil extraction of selected samples:  Tree and fruit selection: Block/tree age, block selection, tree selection (age, vigour, location in the block, edge effects)  Fruit selection: height, location around the tree  Fruit transport  A choice of two standard ways of sampling and drying tissue  A detailed spreadsheet was provided for recording results. While recommendations were made regarding which of the sub-experiments should be carried out, each orchard/company made their own decision on which of the trials were carried out, and how often the samples were taken. Table 2.1. Names of Peruvian avocado companies/orchards sampled for maturity/dry matter (DM) research in the 2015 season, including orchard elevation. The codes show in the map in Figure 2.1. Companies carrying out DM work in either of the two last seasons (2015 or 2014) are indicated by “X”. Company

Region

Code

Elevation x

2014

2015

Ecoacuicola

Piura

EC

35 m

X

X

Cerro Prieto

Chiclayo

CP

50 m

X

X

Y

Barranca

AB

290 m

X

X

Duna Corp

Santa Rosa

DC

450 m

X

X

Santa Patricia

Huaral

SP

212 m

X

Agrokasa

Lorca

Canete

AL

150 m

X

Hoja Redonda

Chincha

AHR

52 m

X

X

Don Ricardo

Ica

ADR

532 m

X

X

Pampa Baja

Arequipa

PB

1100 m

X

2300 m

X

X

Ayacucho JCC

JAC

z

Pisco-Patipampa

JPP

1300 m

X

X

Pisco-Reposo

JPR

1000 m

X

X

Pisco-Humay

JPH

400 m

X

X

Lomas de Chilca

JLC

80 m

X

Metres above sea level; yCoded AGK in Section 1; ZSometimes referred to as “JCC-JAC”, and similarly for the following orchards.

x

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ZONES

COMPANIES

Tacna

none

Ica

Don Ricardo

Chincha

Hoja Redonda

CaĂąete

Lorca

Huaral

Santa Patricia

Santa Rosa

Duna

Barranca

Agrokasa

Casma

none

Trujillo

Camposol

Chiclayo

Cerro Prieto

Piura

Ecoacuicola

Arequipa

Pampa Baja

Ayacucho

Ayacucho

Moquegua

none

Cajamarca

none

Figure 2.1. Map and names of Peruvian avocado companies/orchards sampled for maturity/dry matter research in the 2014 and 2015 seasons. Further details are provided in Table 2.1.

16

TRIAL 5.1. CHANGES IN DRY MATTER OVER TIME

16.1

Introduction

To understand changes in maturity for avocados grown in Peru, it is critical to carry out studies across a range of regions, soil types and environments, and over a long period of time i.e. not just near the current commercial harvest period. If results are to be compared, it is very important that the system of selecting fruit from the orchard, and the way fruit tissue is sampled and dried, are carried out in the same manner. Results from last season gave us overall confidence in the sampling system, number of fruit, and the drying of tissue. A key shortfall for some companies last season was late commencement of sampling, or collecting too few samples. This season we aimed to repeat the sampling carried out in 2014, but extend the sampling of DM to commence significantly earlier, with lower initial DM values.

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16.2

Aim

The main aim of this work was to initiate a monitoring programme that would provide clear patterns of DM accumulation over the season for orchards across nearly all growing regions of Peru, commencing earlier than in 2014.

16.3

Methodology

This work was carried out on seven companies located across 10 regions in Peru (see the map in Figure 2.1) and included a range of elevations (35 m to 2300 m above sea level). In addition, for each company one to three blocks or orchards were sampled. The aim was to commence dry matter monitoring 3 months before the standard commercial harvest time and continue for 2 months after the completion of commercial harvesting (Appendix 2.1). Sampling of fruit for DM measurement was recommended to be carried out every two weeks. Fruit selected were recommended to be of medium size, and it is acknowledged that size might vary among orchards/regions and over time, particularly given the early sampling times and very long sampling periods for some orchards. Each packhouse (or region) carried out the dry matter analysis, using one of the two standard ways of preparing dry matter samples (slices or coring), and one of the three standard ways to dry the fruit (oven, dehydrator or microwave). All these methods are accepted international standard methods, and will ensure accurate and comparable results. Linear regression lines were fitted to the initial linear sections of the graphs using a cut-off of up to 25% DM. This was carried out to exclude later samples where DM tends to be variable (e.g. Appendix 2.2, Figure 1A), or level out with late maturity (e.g. Appendix 2.2, Figure 3A-PA2 and 5A).

16.4

Results and discussion

Overview of data. Figure 2.2 shows a scatter plot of the DM data for all orchards, and the DM data for individual orchards and average fruit size at each sampling is presented in Appendix 2.2. This season nearly all companies started sampling at, or before, 15-17% DM except JAC (JCC-Ayacucho). This was generally 1â&#x20AC;&#x201C;3 months before commercial harvest, and generally 2â&#x20AC;&#x201C;3 months after. These longer sampling times resulted in clearer trends and allowed better fitting of data and confident prediction of both rate of DM accumulation and the time to achieve the current minimum commercial dry matter (21.5%) as presented in Table 2.2. The number of sampling occasions for DM measurement ranged from 6 to 12 depending on site, with an average of 8.4 sampling occasions for the 20 sites. This was a significant improvement in sampling over last season, where many companies collected as few as 3-5 samples, and the average number of collected samples was 7.7. The result of this significant improvement in timing and number of sampling points was robust data with clear trends and few outliers or data that made no physiological sense (Appendix 2.2). Figure 2.2 presents all data and it is clear that, overall, nearly all orchards followed a strong linear increase in dry matter, and the slope was relatively similar (see below for further [125]

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discussion of dry matter increase). A strong outlier in the data was JCC-JAC (Ayacucho region), where DM was significantly higher very early in the season. Time to achieve minimum commercial maturity (21.5%) for most orchards clustered between 1 April and 1 June (i.e. 2 months), with ADR (Ica region) orchards being the latest to reach 21.5%. Fruit weight (Appendix 2.2, right hand column of graphs) showed that, as expected when starting sampling as early as was carried out this year, fruit size tended to increase over time. However, this effect was less obvious where fruit sampling started nearer to 20% DM (e.g. Appendix 2, Figure 4B (JCC-JAC-Ayacucho), Figure 5B (AHR-Chincha) and Figure 6B (ADR-Ica)). Rate of DM accumulation. Regression analysis of DM changes over time (ISO week calculated as days of the year divided by 7) was undertaken separately for each of the 20 sites, and key results are presented in Table 2.2. The fit this year was much better than last year’s, with R2 values ranging from 0.73 to 0.99, and 13 out 20 values (65%) were over 0.90. This compares favourably with last season (2014), where values were as low as 0.32 and only 14 out of 27 values (52%) were over 0.90 (Woolf et al. 2015). The improvement in fit of the data also gives us confidence in the reliability of the rate of DM accumulation. The rate of DM/week ranged significantly between orchards, with a minimum of 0.29 and maximum of 0.88% DM/week (1.26-3.81% DM/month; Table 2.2). The average rate of DM accumulation (average of rate for all orchards was 0.52% DM/week (2.21% DM/month), while linear fit to all data showed an accumulation of 0.33% DM/week (1.43% DM/month). The range of rates of accumulation was similar to that observed last season (when poor data sets are excluded). Although there was variation between blocks, the rate of DM accumulation observed here is similar to that in New Zealand, where three regions varied between ≈ 1.7 and 2.4%/month (Pak et al. 2003). Excluding data where too few samples were collected (e.g. EC) or unexpected patterns (coloured blue in Table 2.2), the rate of DM accumulation (slope of the regression line) ranged from 0.25% DM per week (1.1%/month for AL-4) to as much as 0.74% DM per week (or 3.2%/month, for AB-11). The average rate of accumulation for all sites was 0.32/week, or 1.4%/month. The rate of DM accumulation in New Zealand in three regions is shown in Pak et al. (2003) and varies between ≈ 1.7 and 2.4%/month. Time to reach 21.5% DM. Based on the intercepts and slopes of the regression lines, ISO21.5, the calculated time when average DM for each site reached the current industry minimum maturity of 21.5% DM (ISO21.5=(21.5-Intercept)/Slope) ranged from 1 February to 20 June 23 in 2015. For JAC (the first to reach commercial maturity), the date of 1 February was significantly earlier than in 2014 (25 March), thus emphasising the differences between seasons. The calculated ISO21.5 listed in Table 2.2 could be used as a guideline for DM monitoring in the future (e.g. start measure DM 2-3 months before the time listed). To gain an overall view of change in DM over time for the whole avocado industry in Peru (based on the orchards sampled in this study), data from all the 20 orchard sites were combined together for regression analysis: Fruit across all sites accumulated DM at a rate of 1.43% DM/month (similar to last season) to reach an average DM of 21.5% DM on 14 May, almost the identical data for the 2014 season.

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CP-M3V14 CP-M4V13 CP-M6V5 EC-V1 EC-V2 EC-V3 DC-PA2 DC-PA3 JCC-JPP JCC-JPR JCC-JPH JCC-JAC AHR-Ana María AHR-San Borja AHR-San Fortunato ADR-YP2 ADR-YP4 AB-11 AB-12 AB-16

34 32 30

Dry Matter (%)

28 26 24 22 20 18 16 14

1/11/2015

1/10/2015

1/09/2015

1/08/2015

1/07/2015

1/06/2015

1/05/2015

1/04/2015

1/03/2015

1/02/2015

1/01/2015

1/12/2014

12

Calendar Date Figure 2.2. Scatter plot of ‘Hass’ avocado fruit dry matter (DM) samples measured on 20 orchard sites over the 2015 maturation season across Peru. Each point represents a mean of three replicates sampled from 21 fruit harvested from one site on a particular date. See Appendix 2 for full data set for each orchard. The horizontal red line is the Peruvian industry SENASA-recommended minimum commercial maturity (21.5%). See Table 2.1 for information on the orchards sampled. [127]

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16.5

Conclusions and recommendations

Clearly the wide variation in rate of DM accumulation and time to achieve a given minimum commercial maturity (e.g. 21.5%) means that orchards blocks should be monitored individually by each company. The very large size of the orchards in Peru (some in the many hundreds of hectares) means that thought needs to be given to what areas are monitored to yield the greatest information. It is probably reasonable to assume that if the land is very flat with similar soils, fewer areas need monitoring. However, if there is significant variation in soil type, topography, elevation or microclimate, more areas should be sampled. As noted last year, the system used in this work seems appropriate and is similar to that used internationally by other avocado industries. As found this year, starting monitoring well before predicted commercial harvest is important, and at least 4 or 5 fortnightly samples before the minimum commercial harvest will give more accurate prediction. This means starting sampling 2â&#x20AC;&#x201C;3 months before expected harvest dates. As noted last year, an industry-wide maturity monitoring programme (as used by the New Zealand industry) would provide direction for all growers, using an industry website with seasonal comparisons. In summary, running a standardised DM monitoring system every year will build understanding and confidence to plan harvest and marketing plans, all which have significant logistical and economic impacts on a company.

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Table 2.2. Data matrix for 2015 for Peruvian avocado orchard/blocks showing fitted linear model between dry matter (DM) and ISO week, the resulting regression model, slope (DM/week & DM/month), and predicted date to reach the SENASA-recommended minimum commercial maturity (21.5% DM), as well as the number of DM data points used for modelling (N) and R2 for model fitting of each orchard. Orchard & block

Altitude (m)

Latitude (°)

Longitude (°)

Regression model*

Slope (DM/week)

DM% increase / month

Date when 21.5% DM

N

R2

EC V1

35

4.2

70.6

DM=15.3 + 0.36 · ISO week

0.36

1.56

1-May

7

0.90

EC V2

35

4.2

70.6

DM=15.3 + 0.39 · ISO week

0.39

1.69

22-Apr

10

0.98

EC V3

35

4.2

70.6

DM=15.5 + 0.38 · ISO week

0.38

1.65

21-Apr

10

0.97

AB-11

356

10.7

77.7

DM=8.6 + 0.65 · ISO week

0.65

2.82

19-May

9

0.97

AB-12

429

10.7

77.6

DM=7.6 + 0.74 · ISO week

0.74

3.21

12-May

9

0.93

AB-16

290

10.7

77.7

DM=7.4 + 0.78 · ISO week

0.78

3.38

7-May

8

0.94

DC-PA 2

450

11.2

77.4

DM=12.1 + 0.55 · ISO week

0.55

2.38

30-Apr

9

0.97

DC-PA 3

450

11.2

77.4

DM=10.2 + 0.51 · ISO week

0.51

2.21

5-Jun

12

0.99

CP- M3V14

104

7.5

79.5

DM=15.2 + 0.41 · ISO week

0.41

1.78

18-Apr

12

0.92

CP-M4V13

95

7.1

79.5

DM=14.6 + 0.41 · ISO week

0.41

1.78

28-Apr

11

0.85

CP-M6V5

104

7.1

79.5

DM=13.8 + 0.45 · ISO week

0.45

1.95

30-Apr

10

0.85

AHR-Ana María

52

13.5

76.1

DM=14.9 + 0.37 · ISO week

0.37

1.60

5-May

6

0.77

AHR-San Borja

52

13.5

76.1

DM=14.6 + 0.37 · ISO week

0.37

1.60

11-May

7

0.96

AHR-San Fortunato

52

13.5

76.1

DM=15.3 + 0.34 · ISO week

0.34

1.47

8-May

6

0.83

ADR-YP2

482

14.0

75.7

DM=14.6 + 0.29 · ISO week

0.29

1.26

16-Jun

8

0.92

ADR-YP4

487

14.0

75.7

DM=14.3 + 0.29 · ISO week

0.29

1.26

23-Jun

6

0.73

JAC

2300

8.6

73.6

DM=19.6 + 0.42 · ISO week

0.42

1.82

1-Feb

7

0.95

JPP

1300

13.6

75.5

DM=12.3 + 0.85 · ISO week

0.85

3.68

17-Mar

6

0.97

JPR

1000

13.6

75.6

DM=10.5 + 0.88 · ISO week

0.88

3.81

29-Mar

6

0.99

JPH

400

13.7

75.9

25-Apr

8

0.95

14-May

7.7

0.62

Overall

DM=10.5 + 0.67 · ISO week

0.67

2.90

Average of all values

NA

0.51

2.2

Linear fit to all data

DM=15.2 + 0.33 · ISO week

0.33

1.43

*Line fit formula for each site uses the ISO week in which the DM was assessed Slope = Rate of DM increase per week (%DM/week) Date when 21.5% DM = Predicted date in 2015 to reach 21.5% DM for each orchard N= Number of DM data available for model fitting (the number of times DM was measured on each orchard/block)

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17

TRIAL 5.2. EFFECT OF FRUIT SIZE ON DRY MATTER

17.1

Introduction

As with many crops, avocado flowering is spread out, occurring over a period of weeks. Thus there are a range of fruit sizes, and because avocado fruit do not ripen on the tree, avocado can be selectively harvested over time. The effect of fruit size on DM is an important aspect since delivering all fruit with acceptable maturity and quality is clearly an important commercial outcome. Other than its implications for commercial harvests, if fruit size is an important factor, it could have a significant impact in terms of sampling fruit to understand maturity changes and deciding on the timing of harvest. The research last season found that, in a given batch of average-sized fruit, fruit size did not have a significant effect on DM (Woolf et al. 2015). But differences were found between fruit of very different sizes (large v. small). Thus, sampling earlier in the season from a diverse range of fruit sizes would probably yield a statistically significant effect, although these differences would vary between orchards/companies.

17.2

Aim

This section of work aimed to determine changes in dry matter over time in fruit of different sizes.

17.3

Methodology

At the same time that medium-sized fruit were harvested to monitor changes in dry matter over time (Section 2.3), two other fruit sizes (small and large) were also harvested on some orchards and not all on all the harvest dates used in Trial 5.1. This was undertaken by five companies, and 20 orchards. It was suggested that harvesting fruit of two different sizes commence one month before the expected commercial harvest, and then at fortnightly intervals. The choice of fruit size was determined by the average fruit size for each company and therefore was expected to vary between regions. Other than the above points, standard fruit sampling and tissue preparation were carried out as described in Appendix 1.

17.4

Results and discussion

Graphs of the trends of DM and fruit size are provided in Appendix 3 (right hand side figures labelled “B”). The two sizes of fruit harvested were generally well differentiated, with the large fruit tending to be between 250 and 350 g, and the small fruit 150–250 g, resulting in a consistent difference in fruit size of 100–150 g at any given harvest date.

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The graphs in Appendix 3 (left hand side figures labelled “A”) show the variable effects of fruit size on dry matter: the PA orchard showed relatively small DM differences (1-2%), while AHR showed differences of as much as ≈ 5%, with differences on the AB and JCC orchards intermediate. A similar analysis to that carried out for Trial 5.1 was carried out on this fruit sized data, with linear regression lines fitted to the data from each orchard (Table 2.3). Dry matter increase per week for large fruit ranged between 0.23 and 0.79% DM/week, while small fruit were 0.33 to 0.97% DM/week. The time to reach commercial maturity (21.5%) calculated from the linear regression models indicated that large fruit reached maturity 5.8 weeks earlier than smaller fruit on average across the 12 orchards assessed. The differences between large and small fruit of the same orchard was relatively small (1.4-3.6 weeks) for JCC orchards, and much larger (up to ≈ 14 weeks) for AHR orchards. The difference for the remainder of companies ranged from ≈ 3 to ≈ 8 weeks. While New Zealand research has found no significant effect of size on DM, the research here and results from California (Barmore 1976; Lewis 1978) and Australia (Hofman and JobinDecor, 1991) agree with an effect of fruit size on DM. Conclusion. While fruit size, particularly extremes, can influence fruit DM, we see no need to change the recommendations of harvesting “medium” sized fruit when monitoring, although if possible smaller fruit (<150 g) should be avoided. Table 2.3. Comparison of large and small avocado fruit. Data matrix for 13 Peruvian avocado orchard/blocks showing fitted linear model between dry matter (DM) and ISO week in 2015, the resulting regression model, slope (DM/week & DM/month), and predicted date to reach the SENASArecommended minimum commercial maturity (21.5% DM), as well as the number of DM data points used for modelling (N) and R2 for model fitting of each orchard. Large fruit

Small fruit

Intercept (% DM)

DM% increase / week

Time to 21.5% DM (ISO week)

Difference in time to 21.5%DM (Week)

16.8

11.8

0.46

21.0

4.2

0.66

16.2

6.9

0.74

19.7

3.4

11.3

0.64

16.0

13.0

0.45

19.1

3.0

EC-2

17.2

0.38

11.3

13.9

0.43

17.8

6.5

CP- M3V14

11.3

0.73

14.0

10.1

0.63

18.0

4.0

CP-M4V13

16.8

0.42

11.2

9.0

0.64

19.5

8.4

CP-M6V5

16.5

0.41

12.3

13.5

0.45

17.8

5.5

AHR-Ana María

19.0

0.31

8.2

11.0

0.49

21.4

13.1

AHR-San Fortunato

20.6

0.23

4.1

15.3

0.33

18.8

14.7

JAC

20.0

0.45

3.3

17.6

0.57

7.0

3.6

JPP

15.4

0.67

9.0

11.1

0.97

10.7

1.8

JPR

12.8

0.79

11.0

13.1

0.67

12.5

1.4

Overall

15.9

0.52

11.1

12.6

0.57

17.1

5.8

Intercept (% DM)

DM% increase / week

Time to 21.5% DM (ISO week)

AB-11

12.6

0.53

AB-12

10.7

AB-16

Orchard & block

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18

TRIAL 5.3. EFFECT OF MATURITY ON STORAGE AND FRUIT QUALITY

18.1

Introduction

One of the factors that should contribute to deciding on a minimum maturity threshold (i.e. DM) for harvesting avocados is the quality of ripe fruit. Since fruit from Peru are exported, the effect of DM content on ripe fruit quality after coolstorage should be examined. Research in New Zealand (Pak et al. 2003) showed a high rate of the following disorders in fruit harvested at low DM content (16-18%): body rots, stem-end rots, stringy vascular strands, and “checker boarding” (large fruit-to-fruit variability in ripening within a tray of fruit). As maturity increased, the incidences of these disorders decreased. However, the rate of decrease was different for different disorders. Significant incidences of disorders were present at 21% DM, and many did not decline to minimum until DM was over 22 or even 24%. The minimum dry matter for harvest in Peru was recently instituted at 21.5%. Thus the DM contents for harvesting fruit for assessment of ripe fruit quality after storage were selected to span this value.

18.2

Aim

Determine the effect of fruit maturity at harvest (as measured by DM) on ripe fruit quality of avocados after coolstorage

18.3

Methodology

The DM contents targeted at which to carry out sampling for storage were 17, 19, 21, 23 and 25%. Fruit of medium size were harvested from trees close to (i.e. beside) trees that had been tagged for monitoring changes in DM across the season (i.e. Section 2.3) but NOT FROM the tagged trees. Fruit were harvested from three orchard blocks. For each block, eight trays of fruit (each with ≈ 16 fruit/tray) were harvested: six trays for coolstore and two trays for measuring DM, where 21 fruit (three replicates of seven fruit) were used to determine DM at harvest. Fruit quality assessments: After 4 weeks of storage at 6°C, fruit were ripened at 20°C. Once fruit were deemed fully ripe (hand rating of 5; White et al. 2009), the incidence and severity of disorders were assessed: body rots, stem-end rots, vascular browning, diffuse flesh discolouration (flesh greying), stringy vascular, flesh adhesion to the seed, and peelability. Body rots, stem-end rots and diffuse flesh discolouration (flesh greying) were assessed using the PFR-ProHass assessment protocol. All other disorders were assessed using the International Avocado Quality Manual (White et al. 2009).

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Statistical analysis. Histograms of days to ripen by company and dry matter were used to determine which companies proceeded into the second stage of analysis (companies 1, 3, 4, 5 and 8 retained, with company 5 having 4 fruit removed with ripening times of 46 days). Those companies were then combined for each defect of interest and a generalised linear model with a binomial distribution applied to investigate the overall trend (R, version 3.2.2). These results are presented as a scatter plot of all companies with the overall trend.

18.4

Results and discussion

This season there was a significant improvement over the 2014 season, with many more DM contents/times of harvests carried out, and many more companies attempted to carry out the trial. However, as found for other ripe fruit quality work (Section 2.1), the data showed that timing of fruit assessment was not carried out as prescribed in the methodology. An example of excellent distribution of ripening is shown in Figure 2.3A, where the expected pattern of ripening is shown where a few fruit commence ripening, then a peak occurs and a tailing off. This bell curve is the expected pattern of ripening if assessments are carried out properly, i.e. when each fruit reaches a fully ripe stage. Figure 2.3B shows an example of incorrect assessment where fruit were cut on only days 14 and 18.

A

B

Figure 2.3. Examples of good technique (A), or poor technique (B) avocado fruit quality assessment results. Good technique should result in a ‘bell curve’ over assessment time.

Given the significant effort put into the work, we endeavoured to obtain some results from the data. Thus, our scientists and statisticians made a series of decisions on what companies, DM assessment times, and particular fruit data could reasonably be included in the analysis. Exclusions included fruit that took far too long to ripen (e.g. 30–45 days), or where patterns of assessment showed very poor technique. This left data from five companies, and disorders with data that were expected on previous research (e.g. Pak et al. 2003) and other international commercial understanding (e.g. out of South Africa) are presented in Figure 2.4.

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Figure 2.4. Effect of dry matter (DM) at harvest on Peruvian ripe avocado fruit quality after storage for four weeks at 6°C and ripening at 20°C, 2015. A; stem-end rots B; body rots; C: vascular browning disorders are presented. Lines represent regression models across all companies.

While there are many caveats for the data used for this work (mostly poor assessment technique) and there was variation between companies, overall there was a clear reduction in the three disorders presented here as DM at harvest increased (Figure 2.4A, B & C). There was variation in the data across companies, with some companies showing little or no incidence of disorders (companies 2 & 8), while others had up to 40-50% incidence. These trends tended to hold across the three disorders. The overall pattern of data was very similar for the two rots (body and stem-end rots), with a cluster of higher incidence data (20 to ≈ 40%) below 24% DM, and less than 10% incidence above 24%. Rates of vascular browning were lower - generally less than 20% across all DM harvests. These results are in agreement with those found by Pak et al. (2003) in New Zealand, with very similar patterns of reduction in rots and vascular browning with increased DM at harvest. At 21.5% DM (the minimum commercial harvest maturity in Peru), there was still a significant proportion of disorders overall, with some companies recording stem-end rots over 40% and body rots over 20% (e.g. Figure 2.4A & B). If a cut-off of 10% is used, then a DM of 24% is

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needed to ensure that no company harvests fruit with disorders above this rate – even though the average response (fitted line) suggests a lower DM value. This work should be repeated using better fruit quality assessment systems (preferably one single assessor team), and the issue of fruit-to-fruit variability of ripening (“checkerboarding”) should be measured by noting fruit firmness and colour differences at ≈ 3 days after removal from coolstore. Although this work is preliminary, it shows the important negative impact that low DM content at harvest has on quality of fruit after storage and ripening. It lends support to increasing the minimum standard to improve outturn quality in the market.

19

GENERAL DISCUSSION

The work this season has, broadly, confirmed the results of last season for two trials measuring DM of fruit over the season (Trial 5.1) and for fruit of different sizes (Trial 5.2), with additional work on fruit quality of stored fruit from a wide range of harvest DM values (Trial 5.3). The improved sampling this season allowed more confident prediction of the rate of DM accumulation, which ranged widely between orchards (between 1.26 and 3.81% DM/month with an average of 2.21% DM/month). Although the time to reach the minimum commercial maturity was similar to that of last year, there were significant differences for some companies. These results highlight the need to monitor DM routinely on representative orchards for each company, so that harvest can be predicted and planned to result in the best fruit harvested. An important step this year was carrying out a series of consecutive harvests of fruit with different DMs, starting at very immature (17%) up to ≈ 27% (Section 2.5; Trial 5.3). Although some data were suboptimal because of poor assessment technique, the results show that fruit quality of stored fruit from lower DM was worse than that of fruit with higher DM. Significantly, at the current minimum commercial standard (21.5%), there were fruit from some companies that showed significant rates of disorders. This highlights the benefit of increasing the minimum commercial maturity above the current 21.5%. While not examined here, this will also likely increase consumer acceptability of the fruit (i.e. sensory quality) as discussed in the General Discussion last season (Woolf et al. 2015).

19.1

Conclusions and recommendations

All companies should consider undertaking routine DM monitoring on a fortnightly basis to better predict timing of the minimum commercial maturity (currently 21.5%). DM sampling should begin 2.5 – 3 months before the historical commercial harvest time, with at least 10 harvests carried out over the season. The current sampling protocol (21 fruit) is sufficient to provide robust data. There was some effect of fruit size on DM. While fruit size, particularly extremes, can influence fruit DM, we see no need to change the recommendations of harvesting “medium” sized fruit when monitoring, although if possible smaller fruit (<150 g) should be avoided. The industry should consider setting up a number of standard monitoring orchards to provide ongoing data to compare across seasons.

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Industry minimum harvest could include a lower DM fractile criterion (as used in New Zealand), to reduce the proportion of low DM fruit in the population that are likely to be poor-tasting fruit. The effect of DM on ripe fruit quality after storage shows the important negative impact that low DM content at harvest has on quality of fruit after storage and ripening. This lends support to increasing the minimum standard to improve outturn quality in the market. Oil content measurement (carried out in 2014 only) showed a linear and strong correlation to DM, which is typical of that found internationally. There was no effect of growing environment on the relationship between DM and oil content; therefore, DM continues to be the only recommended measure of maturity. Results in the 2015 season lend support for increase of the commercial minimum DM value above 21.5% based on the ripe fruit quality after storage (Section 2.5), and knowledge of sensory responses to DM. Such an increase in minimum DM value will likely improve taste and fruit quality in international markets, which will improve market and consumer perception of Peruvian avocados.

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20

REFERENCES

Barmore CR 1976. Avocado fruit maturity. In: Sauls JW, Phillips RL, Jackson LK ed. Proceedings of the first international tropical fruit short course: the avocado. Gainesville, Fruit Crops Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Hofman PJ, Jobin-decor, M 1999. Effect of fruit sampling and handling procedures on the percentage dry matter, fruit mass, ripening and skin colour of ‘Hass’ avocado. J. Hortic. Sci. Biotech. 74: 277–282. Lewis CE 1978. The maturity of avocados - a general review. Journal of the Science of Food and Agriculture 29(10): 857–866. Pak HA, Dixon J, Cutting JC 2003. Influence of early season maturity on fruit quality in New Zealand 'Hass' avocados. Proceedings of the fifth world avocado congress: 635–640. Ranney C 1991. Relationship between physiological maturity and percent dry matter of avocados. California Avocado Society Yearbook 75: 71–85. Ranney C, Gillette G, Brydon A, McIntyre S, Rivers O, Vasquez CA, Wilson E 1992. Physiological maturity and percent dry matter of California avocado. Proceedings of the second world avocado congress: 379–385. Schroeder CA 1985. Physiological gradient in avocado fruit. California Avocado Society Yearbook 69: 137–143. Watada AE, Herner RC, Kader AA, Romani RJ, Staby GL 1984. Terminology for the descriptionof developmental stages of horticultural crops. HortScience 19(1): 20–21. White A, Woolf AB, Hofman PJ, Arpaia ML. 2009. The International Avocado Quality Manual (English). ISBN 0-478-06845-X. pp70. Woolf A, Olsson S, Feng R, Requejo-Jackman C, White A. June 2015. Dry matter, oil content and maturity of Peruvian avocados: Section 2. A Plant & Food Research report prepared for: ProHass. Milestone No. 63285. Contract No. 29828 var2. Job code: P/345107/01. PFR SPTS No. 11699.

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APPENDIX 2.1. FINAL PROTOCOL FOR MATURITY TRIAL PFR-ProHass Experimental Protocol Trial #5. Title: Measuring avocado maturity by dry matter and oil Thursday, 19 December 2013 PFR Trial Leader: Allan Woolf ProHass Leader: Victor Escobedo Introduction

The decision when to harvest is an important issue for any fruit crop. For avocado, maturity is based on the measure of dry matter (DM). Although many companies in Peru carry out routine measurements of dry matter, there has been no comprehensive and consistent study of changes in DM across the diverse growing regions of Peru. This work will provide a solid foundation on changes in dry matter over the season, within orchards, between regions, the influence of fruit size, the variability of dry matter within a harvest, the correlation of dry matter and oil content, and the influence of dry matter on fruit quality following coolstorage. Many countries carry out routine DM monitoring as an industry. For example, New Zealand has monitored the same 5 orchards every year in three regions for over 12 years, and carries this out on an individual fruit basis to determine the spread of maturity. This involves up to 3-5000 dry matter measurements and shows the industries commitment and rigour to this important area. Each packhouse (or region) should carry out the dry matter analysis. Each packhouse should use one of the two standard ways of preparing dry matter samples (slices or coring), and use one of the three standard ways to dry the fruit. All of these methods are accepted international standard methods, and will ensure accurate and comparable results. As each packhouse may use somewhat different systems the following experiments will need to be “tailored” to each company. A summary of the timing of this trial is provided in a spreadsheet. The exact timing f the work will need to be discussed with Victor Escobedo (ProHass) and Allan Woolf (PFR). Oil extraction will be carried out at one laboratory in Lima. Aim

Measure changes in maturity using dry matter and oil content over 2 seasons by enabling all packhouses to work with an agreed standard method(s) of sampling fruit and measuring dry matter, and one laboratory partner for measuring oil content. This will also determine the correlation of dry matter and oil content for each region. Methodology General description

Harvests will involve measuring maturity once every two weeks and storing the dried tissue for subsequent oil extraction. We will also examine other factors such as the effect of fruit size, variability between fruit and examining fruit quality after storage at a range of DM levels that are well below and above the current minimum.

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The data from both 2013/2014 and 2014/2015 season work will provide solid data for presentation at the World Avocado Congress in 2015 and give solid data of seasonal, regional and orchard differences in maturity. The fruit quality work will also provide solid data on the effect of maturity on ripe fruit quality following storage which may influence decisions on the best time to harvest fruit for the export market. This trial has four areas: 5.1

Measuring dry matter over a long period (6-10 months) using fruit of medium size

5.2

Measuring dry matter of a range of fruit sizes around the main harvest period

5.3

Collecting fruit at a range of fruit maturities and storing the fruit to determine the effect of maturity on ripe-fruit quality (e.g. stem-end rots, vascular strand, etc.)

5.4

Optional trial: Measuring DM of individual fruit on 3 occasions (around the main harvest season) to understand fruit-to-fruit variability of DM.

Tree and fruit selection:

A) For parts 5.1, 5.2 and 5.4 (see below for details of these trials) trees/fruit should be selected as follows:  Block/tree age: The blocks of trees should be older than 5 years if at all possible. If not, then chose the oldest trees NB: Because younger trees typically show earlier maturity, it should be noted that the results from this work will reflect tree age as well as regional effects (i.e. there will be some confounding of orchard location with tree age) because not all orchards will have trees of the same age.  Block selection: Choose three blocks in the orchard that best reflect the diversity of the orchard in terms of time to mature (early, mid and late) and if possible soil type etc. While the blocks should be diverse, they should NOT be extreme examples in the orchard, i.e., the three blocks should aim to reflect the majority of trees in the orchard. Selection should be based on the managers/staff knowledge of topography (slope orientation – north / south etc.), soil type and historical differences in terms of maturity differences and/or harvest timing. The final block selection should be discussed with Victor Escobedo using a plan/map of the orchard that indicates tree age and if possible topography/soil type.  Tree selection: For each block, select trees as follows:  21 trees should be selected in a way that takes a reasonable sample of the block area yet is done in a way that trees can be readily found/located by staff. For example, for very large blocks (1x0.5km), this will probably mean not taking fruit across the whole block.  Trees selected should be as “typical” as possible, of average vigour, and show no signs of root rot, nutritional or other disorders  The “edges” of the block should be avoided, i.e. at least 5 trees in from the end of the row, and at least 2 rows in from the side of the block.  Areas of high wind should be avoided  Two strategies could be used:  A) For smaller blocks, select trees diagonally across the block: Thus, starting 3 rows in from the left hand side of the block at 10 trees into the block, select a tree, then move across one or two rows and forward one – two trees, select a tree, and repeat.  B) For very large blocks, select trees going across one end of the block: Choose one end of the block that is less affected by wind etc. Starting 3 rows (or more) [139]

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from the side of the block, move 15 trees into the block, select that tree, then move right one or two rows (but still 15 trees into the block) and select that tree. Repeat moving across the block.  Below are diagrams to indicate the tree selection system. Note that these are not drawn to scale.

Rows

Diagonal sampling system (for smaller blocks)

Rows

“Across end” sampling system (for larger blocks)

 Tree tagging/labelling. The selected trees should be tagged in such a way that the picking teams do not accidentally harvest the fruit from these trees. Hanging lengths of coloured tape from branches on several sides of the tree (recommend 4), or wrapping a length of brightly coloured tape around the entire tree canopy can help.  Fruit selection (i.e. what fruit to harvest from the tree): [140]

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 Fruit should be harvested from the MAIN flowering shoots. To keep the number of samples to a reasonable level we are not including the early or late flowering types, nor the “loco” flowering.  Fruit should be harvested in general from the middle of the tree and harvested randomly around all sides of the tree (i.e. North/East/South/West).  Fruit to avoid include the very low and very high fruit, and sun-exposed fruit (those showing bleaching / yellowing of the skin).  Harvesting fruit: Early in the morning (e.g. 9 am) sample 21 fruit per fruit size from each block per sampling time. Fruit should be taken randomly from the selected trees (1 fruit per tree). Fruit should be harvested in the standard manner (cut from tree with clippers with short/ flat “button” / stem). Place the 21 fruit per fruit size in a plastic bag for processing (i.e. sampling tissue and drying etc.)  Fruit transport: Fruit samples should be taken as soon as possible to the laboratory for analysis. Fruit should not be left in the sun and if possible insulated from temperature extremes. If processing cannot be carried out on the day fruit are sampled, hold fruit in an air-conditioned room overnight. B) For experiment 5.3 (fruit maturity and ripe fruit quality) fruit should be sourced as follows:  Experiment 5.3 is about taking fruit from different trees that are close to the tagged trees once the results of 5.1 reach the following DM levels; 17, 19, 21, 23 and 25%. The fruit that will be used to assess ripe fruit quality (i.e. 8 trays) should be harvested from these different trees that are close to the tagged trees.  From these 8 trays we will take 21 fruit and measure DM on three groups of 7 fruit. The method for measuring dry matter (tissue sampling and drying) is described further below.

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Introduction to the Excel spreadsheet for these trials For this and the following trial we have developed an Excel file - Filename is: ! Trial 5 (Dry Matter)- Sampling times for 2014 v8 Final.xlsx. The first sheet provides a useful overview by outlining the suggested timing of sampling for DM for each of the companies/orchards and includes the trial number (i.e. 5.1, 5.2 etc.). A tally of the number of harvests and samples is provided on the right of the spreadsheet. Comments are also inserted (to read the comments, position the cursor over the cell with red labels). The second sheet contains a map of the country and the location of participating orchards/companies. The third sheet shows how New Zealand carries out its routine monitoring (for the industry) and how this provides a benchmark every year. They measure 20 individual fruit on a fortnightly basis and commercial harvest commences at 24%. The fourth sheet is for recording data from trial 5.1 Main maturity trial: Dry matter and oil, medium fruit size. The fifth sheet is for recording data from trial 5.2 Fruit size and dry matter. The sixth sheet is for recording data from trial 5.3 Fruit quality trial. The seventh sheet is for recording data from trial 5.4 Individual fruit dry matter (Optional trial).

Trial 5.1. Main maturity trial: Dry matter and oil, medium-sized fruit. Introduction

In order to understand changes in maturity for avocados grown in Peru it is critical to carry out studies over a range of regions, soil types, and over a long period of time i.e. not just near to the current commercial harvest period. This should include understanding changes in maturity well before and also after commercial harvest. If results are to be compared, it is very important that the sampling system from the orchard and the way fruit tissue is collected and dried is carried out in the same manner. Dry matter has been found to be highly correlated to oil content in ‘Hass’ avocados grown in NZ, Australia and USA (Woolf et al. unpublished data). This study aims to confirm this finding for fruit grown in a range of environments across Peru, including at higher elevations. Aim

The main aim of this work is to start a monitoring programme that will provide clear patterns of DM accumulation over the season for orchards across nearly all growing regions of Peru. The correlation of DM to oil content will also be examined by extracting oil from selected DM samples. Methodology

 This work will be carried out in 15 orchards which are located across a very wide range of areas in Peru (see “map” in sheet 2 of the excel file) including higher elevations (up to 2500m).

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

 Starting 3 months before the standard commercial harvest time, fruit for DM measurement should be harvested every two weeks (this is indicated by the “2” in the spreadsheet, i.e. two samples/month)  Sampling should continue on for 2 months after the completion of commercial harvesting. This will require making sure that fruit on the tagged trees are NOT harvested during the commercial season!  For this trial, only medium-sized fruit will be harvested i.e. the average size on the fruiting shoot. Medium size is likely to be different between orchards/regions. Data

Enter data into the Excel spreadsheet “! Trial 5 (Dry Matter)- Sampling times for 2014 v8 Final.xlsx” into the sheet “Data-5.1 Main trial”

Trial 5.2. Fruit size and dry matter Introduction

It seems that (contrary to experience in some countries), there are significant differences in the dry matter level in different sized fruit in Peru. This is significant in terms of deciding on the timing of harvest, and in terms of sampling fruit to understand maturity changes. Aim

This section of work will determine the effect of time of harvest on dry matter changes in fruit of different sizes. Methodology

 At the same time that fruit are harvested for 5.1 (medium sized fruit), two other fruit sizes (smaller and larger) will also be harvested.  However, harvests will not be carried out at every sampling time of 5.1 (as this would result in far too many samples). We suggest harvesting commence one month before the expected commercial harvest, and then at fortnightly intervals (thus the “2” and “4” in the spreadsheet). The choice of fruit size will be determined by the average fruit size for each company and may vary between regions. Data

Enter data into the Excel spreadsheet “! Trial 5 (Dry Matter) – Sampling times for 2014 v8 Final.xlsx” into the sheet “Data-5.2 Fruit size”

[143]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

Trial 5.3. Storage and Fruit quality trial Introduction

One of the factors that should contribute to deciding on a minimum maturity level (i.e. DM) for harvesting avocados is the ripe fruit quality. Since fruit from Peru is exported, the effect of lower DM levels on ripe fruit quality after coolstorage should be examined. Research in New Zealand (Pak et al., 2003) showed a high level of the following disorders in fruit harvested at low DM levels (16-18%): Body rots, stem-end rots, stringy vascular strands, and checkerboarding (large fruit-to-fruit variability in ripening within a tray of fruit). As maturity increased, these disorders decreased. However, the rate of decrease was different for different disorders. Significant levels of disorders were present at 21%DM, and many did not decline to minimum levels until DM was over 22 or even 24%. The minimum dry matter level for harvest in Peru was recently moved to 21%. Thus the DM levels to harvest fruit at for assessment of ripe fruit quality after storage were selected to span this value. Aim

Determine the effect of fruit maturity (as measured by DM) on ripe fruit quality of avocados. Methodology

 Use results from 5.1, to determine when to harvest fruit to achieve the targeted DM levels.  The target levels of DM at which to carry out sampling for storage is 17, 19, 21, 23 and 25%.  Fruit should be harvested from trees close to (i.e. beside) trees that are tagged (i.e. 5.1) but NOT FROM the tagged trees.  Fruit should be harvested from 3 orchard blocks.  For each block, harvest 8 trays of fruit (each with ≈ 16 fruit / tray): 6 for coolstore and 2 for measuring DM.  One fruit size (medium sized fruit).  Label the 6 trays for coolstorage with:    

Block Estimated dry matter level Date and time of harvest Replicate (tray) number (i.e. 1-6).

 Store fruit at 6 °C for 4 weeks.  Dry matter measurement. Use 21 fruit (3 reps of 7 fruit) to determine the dry matter at the point of harvest since these fruit are likely to have been harvested the week after the sample from 5.1 (i.e. when the target dry matter level for storage has been reached).  Fruit quality assessments:  5 days after removal from storage, rate the external colour of the fruit (this will be used to highlight any “checkerboarding” along with the time it takes for fruit to be fully ripe)  Ripen fruit using standard procedures (i.e. 20 °C ripening room)  Once fruit are fully ripe (hand rating of 5), assess the main disorders: body rots, stemend rots, vascular browning, diffuse flesh discolouration (flesh greying) as well as less common disorders: stringy vascular, flesh adhesion to stone and peelability. For the body rots, stem-end rots and diffuse flesh discolouration (Flesh greying), use the PFR-

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

ProHass assessment protocol. For the other disorders use the International Avocado Quality Manual (White et al., 2009; see the excel spreadsheet and the sheet “Data-5.3 Fruit Quality”). Data

Enter data into the Excel spreadsheet “! Trial 5 (Dry Matter)- Sampling times for 2014 v8 Final.xlsx”. For DM enter data into the sheet labelled “Data-5.3 Fruit quality-DM” and the fruit quality results into “Data-5.3 Fruit Quality”

Trial 5.4. Individual fruit dry matter (Optional trial) Introduction

While the average dry matter in a batch of fruit is important, it is also very useful to understand the variability between fruit since the consumer ultimately consumes only one fruit. Thus, while the average may be “acceptable” at say 25% DM, there may be fruit harvested in the same batch which are at a low DM level that a consumer may find “unacceptable”. For example, in New Zealand, even when a batch of fruit have an average dry matter of ~26%, there are some fruit with a DM of only 18-20% (see figure below), and these are likely to be of poor eating quality.

Proportion of fruit in DM range (%)

25

October 23 January 30

20

15

10

5

>4 4

18 -20 20 -22 22 -24 24 -26 26 -28 28 -30 30 -32 32 -34 34 -36 36 -38 38 -40 40 -42 42 -44

0

Dry matter range (%) By carrying out a measure of individual fruit DM over the season we will be able to understand the between-fruit variability in dry matter and determine whether this might be important to the exporter in terms of fruit quality, and most likely to the consumer.

This part of the maturity trial is OPTIONAL, i.e. it is up to the company to determine whether they would like to take part. Aim

Determine the individual dry matter level of fruit over the commercial season. Methodology

 At three times in the season (early, mid and late), as indicated in the spreadsheet for each company, harvest 1 fruit from each of the 21 tagged trees.  Blocks: The company should decide whether this is carried out on 1 or 3 blocks.  Dry matter is determined for each fruit on an individual basis i.e. tissue is sampled and dried for each fruit, and is not “pooled” into three replicates of 7 fruit. [145]

THE NEW ZEALAND INSTITUTE FOR PLANT & FOOD RESEARCH LIMITED (2016)


ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

 Take approximately 10g of tissue from each fruit to carry out the dry matter measurement (because the weight is recorded you do not need exactly 10g). In order to get 10 g of tissue from each fruit, more tissue will need to be taken than in the other work. Thus, for the Hofshi coring system, this will mean removing another plug of tissue (at 90 degrees to the first plug), and for the peeling system, taking more slices / fruit. Data

Enter data into the Excel spreadsheet “! Trial 5 (Dry Matter)- Sampling times for 2014 v8 Final.xlsx” on the sheet labelled “5.4 Individual fruit DM”

Dry matter measurement: On receiving fruit in the packhouse laboratory

 Weigh 21 fruit together to obtain total weight (and thus obtain average fruit weight by dividing by 21). Do this for each of the three fruit sizes (for Trial 5.3).  Hold fruit in the plastic bags in coolstore if fruit cannot be processed on the day of harvest, but process within 36 hours of harvest.  For each fruit size, randomly divide the 21 fruit into 3 replicates (groups) of 7 fruit. From each of the 7 fruit, carry out tissue sampling (see below) and combine tissue from that replicate. Thus, there will be 3 samples (a, b and c) which will be made up of 7 fruit.  There is a range of ways of measuring dry matter, each with pros and cons. It is a balance of obtaining a representative sample from the fruit (which have LARGE variation in dry matter around the fruit), and the time it takes to prepare samples, and staff safety. Obtaining tissue sample

 Two methods are recommended. Either one may be used. 1. Core system using Hofshi plugger (used in New Zealand and USA)  Use a Hofshi plugger or core borer to remove a core sample from the fruit at the equator  Remove skin, seed and seed coat and cut the remaining flesh core sample into pieces 2. Quarter fruit “potato peeler” system. Used in New Zealand (slower than #1).  Cut fruit in quarters  Peel skin and seed coat off one of the quarters  Use a peeler or knife to cut thin slices from the side of the fruit quarter  A two decimal place digital balance is recommended with connection to computer (saves time and data entry errors). Record the data in the appropriate sheet of the excel file ! Trial 5 (Dry Matter)- Sampling times for 2014 v8 Final.xlsx .  Label and pre-weigh dishes. These should be temperature resistant and care taken as plastic trays (petri dishes) may melt in some drying systems. Record the weight of the dish (Dish empty).  Place fruit tissue that is free of skin (peel) and seed-coat onto dish. Re-weigh the dish with the tissue and record the weight (Dish & FRESH tissue). Drying tissue sample

 There are a range of methods for drying tissue samples, but the main aim is to dry the sample to a constant weight. Key things to avoid are not drying it completely (which will give errors in dry matter figures), and burning the sample. Thus, temperature of ≈65°C for 48 hours is generally recommended. However, each system should be experimented with [146]

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

to determine the conditions / time needed to achieve a constant weight. This involves initially carrying out repeat weighing of samples (say 3 times a day) to determine the time taken to achieve constant weight (no further decrease in weight).  Microwave drying can be used, but this involves a lot of man power / time. While this does give rapid answers (same day), using a drying oven or domestic dehydrator will generally give results in 1-2 days with minimal labour.  After drying to a constant weight, reweigh the dish and fruit tissue. Record the weight in the excel file (Dish & FRESH tissue). Dry matter (%) will be automatically calculated. Dried tissue for later oil analysis

 Immediately after drying and re-weighing the samples (for dry matter), place the tissue (not the dish) in a clip-seal bag (which is well labelled), and store in a standard domestic freezer (≈ -20°C).  Label all bags sequentially starting from 1 (i.e. a discrete number for each harvest), but use “a” b” and “c” for the replication. Thus, 1a, 1b and 1c are harvest one, replicate 1, 2 and 3. Also label the bag with the year and the 2 or 3 letter code for each of the companies (e.g. ADR, for Agricola Don Ricardo). For the list of codes see either the “map” sheet of the excel file “! Trial 5 (Dry Matter)- Sampling times for 2014 v8 Final.xlsx”, or the ProHass0020Assessment Protocol.  Thus each bag will have: 1. Year: e.g. 2013/2014 (i.e. the 2013/2014 season) 2. Company: e.g. ADR (for Agricola Don Ricardo) 3. Sample number and replication letter: E.g. 12b (for sample #12, replicate b) Oil content measurement

A standard system of oil extraction will be agreed on with one laboratory. Oil analyses will be done for each sample, or a selection of samples, in 2014 that will cover the season and regional variability. References

Pak HA, Dixon J, Cutting JC 2003. Influence of early season maturity on fruit quality in New Zealand 'Hass' avocados. Proceedings of the fifth world avocado congress: 635–640.

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ProHass Avocado Multi-Year Fruit Quality Research. Year 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

APPENDIX 2.2. GRAPHS OF DRY MATTER VALUES FOR EACH PERUVIAN AVOCADO ORCHARD OVER THE 2015 SEASON (TRIAL 5.1) Trial 5.1; Section 2.3. Changes in dry matter (DM; coded “A”) and fruit size (coded “B”) during the 2015 season for seven Peruvian avocado companies. The two- or three-letter code designates the company code; see Table 2.1 for orchard details, and Figure 2.1 for location of orchards on map of Peru. Mean DM data ± Standard error of the mean (SEM), N=3.

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35

PA2 PA3

25

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Piura

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30

25

20

15

Santa Rosa - Huaral

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Chiclaya

Average fruit weight (g per fruit)

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THE NEW ZEALAND INSTITUTE FOR PLANT & FOOD RESEARCH LIMITED (2016)

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1â&#x20AC;&#x201C;3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

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Barranca

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1/11/2015

1/10/2015

1/09/2015

1/08/2015

1/07/2015

1/06/2015

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1/09/2015

1/08/2015

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1/06/2015

1/05/2015

1/04/2015

1/03/2015

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1/10/2015

1/09/2015

1/08/2015

1/07/2015

1/06/2015

1/05/2015

1/04/2015

1/03/2015

1/02/2015

JJC

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350

Ica

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Patipampa Reposo Ignacio SanJCP Ayacucho JPR

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1/05/2015

25 350

1/03/2015

30

300

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40

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10

1/02/2015

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350

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40

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10

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15

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20

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15

1/12/2014

20

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25

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JPP JAC

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Average fruit weight (g per fruit)

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1/10/2015

1/09/2015

1/07/2015

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Ana María Chincha San Borja San Fortunato

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1/06/2015

1/04/2015

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35

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1/07/2015

1/06/2015

1/05/2015

1/03/2015

Patipampa Reposo Ignacio San JCP Ayacucho JPR

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35

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1/03/2015

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Dry Matter (%)

ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

APPENDIX 2.3. GRAPHS FOR EFFECT OF PERUVIAN AVOCADO FRUIT SIZE ON DRY MATTER (TRIAL 5.2) Trial 5.2; Section 2.4. For small and large (“big”) fruit, changes in dry matter (DM; coded “A”) and fruit weight (coded “B”) during the 2015 season for seven Peruvian avocado companies. The twoor three-letter code designates the company code; see Table 2.1 for orchard details, and Figure 2.1 for location of orchards on map of Peru. Mean DM data ± Standard error of the mean (SEM), N=3.

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1â&#x20AC;&#x201C;3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

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1/10/2015

1/09/2015

1/08/2015

1/07/2015

1/06/2015

1/05/2015

1/04/2015

1/03/2015

1/02/2015

1/01/2015

1/12/2014

1/01/2015

50

10

400

big Reposo JPR-big JPP-big big Patipampa JAC-big big Ayacucho JPR-small small Reposo JPP-small small Patipampa JAC-small Ayacucho small

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JJC 3A: JCC

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Average fruit weight (g per fruit)

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big Reposo JPR-big Patipampa JPP-big big Ayacucho JAC-bigbig small Reposo JPR-small small Patipampa JPP-small small Ayacucho JAC-small

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ProHass Avocado Multi-Year Fruit Quality Research. Years 1–3 Results. March 2016. PFR SPTS No. 12759. This report is confidential to ProHass.

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11 big 12 big 16 big 11 small 12 small 16 small

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Plant and Food Research