2024 eBarns Report

2024 eBarns Report

COLLEGE OF FOOD, AGRICULTURAL, AND ENVIRONMENTAL SCIENCES COLLEGE OF VETERINARY MEDICINE

2024 eBarns Report

eBarns

“connecting science to farmers” eBarns is a program at The Ohio State University dedicated to advancing production agriculture through the use of field-scale and applied research. The 2024 eBarns Report is a combination of the research conducted on partner farms and Ohio State agricultural research stations throughout Ohio. Current research is focused on enhancing animal production, growing high-quality forages, precision nutrient management and to develop analytical tools for digital agriculture.

In the third edition of eBarns we have included research studies not only from the past year, but studies from previous years that have yet to be summarized in a producer friendly manner. It is our goal to continue to share results from applied livestock, forage, and manure nutrient management in this publication for years to come.

2024 Research Recap 29 Total Studies

• 9 Forages • 1 Manure Nutrients • 5 Cattle • 1 Cattle (Combined Beef & Dairy) • 1 Beef • 3 Dairy • 6 Small Ruminant • 3 Equine • 4 Swine • 1 Poultry

15 Counties 31 Research Sites 4 Statewide Projects

Disclaimer Notice: The information provided in this document is intended for educational purposes only. Mention or use of specific products or services, along with illustrations, does not constitute Endorsement by The Ohio State University. The Ohio State University assumes no responsibility for any damages that may occur through adoption of the programs/techniques described in this document.

2 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

Editorial Welcome to the 2024 Ohio State eBarns report.

This is the third edition of the eBarns report, where we share and highlight livestock, equine, and foragebased research that is conducted across Ohio on farms and university research facilities. We appreciate the faculty, staff, and students that contributed to this year’s report, without their cooperation none of this would be possible.

The past year has been an interesting one in the livestock industry. We came out of a nearly ideal 2023 growing season for feedstuffs and forage. Now we are well into a 2024 growing season where drought and poor pasture conditions are prominent especially in southern and eastern Ohio.

We entered 2024 with the smallest beef cow herd in the U.S. since 1960. Livestock prices have been all over the board from setting record highs in beef, while hog and dairy prices have remained relatively low. Small ruminants continue to remain a topic of discussion with small farm clientele and have now drawn the attention of those looking to control vegetation in the many solar energy fields across the state.

In the past year we had a further infestation of the Longhorned Tick into the state and have dealt with Highly Pathogenic Avian Influenza (HPAI) in poultry and dairy. Ohio livestock producers are resilient as they come and hopefully rain will fall in the drought impacted areas of the state soon.

For the 2024 report the eBarns team conducted 29 studies in 15 counties, with 4 of the studies being statewide efforts. We hope that some of the data presented in this year’s report will provide value to Ohio’s livestock and equine industries at the local level. If you have an interest in conducting on-farm research for next year’s report, contact your county OSU Extension office or go to digitalag.osu.edu/ebarns to get started.

Sincerely, The 2024 eBarns Team

The eBarns Report is published on an annual basis. To view past reports, visit our website at go.osu.edu/ebarnsreports.

2024 eBarns Report | 3

Table of Contents Ohio State Digital Ag Program................................................................................................................. 6 Report Guide............................................................................................................................................ 8 eBarns Contributors............................................................................................................................... 10 2023/2024 Growing Season Weather.................................................................................................... 16 Ohio Farm Custom Rates....................................................................................................................... 18 Ohio State Forages Research................................................................................................................ 20 Autumn Olive Control........................................................................................................................... 22 Corn DON Resistance Screening........................................................................................................ 24 Mechanical Control of Pasture Weeds................................................................................................ 26 Oats Nitrogen Rate August Planting ....................................................................................................28 Oats Nitrogen Rate July Planting ........................................................................................................ 30 N Rate on Organic Summer Annual Species ...................................................................................... 32 No-Till Organic Summer Annuals ........................................................................................................ 34 N Rate on Summer Annual Species.................................................................................................... 36 Winter Annual Rye Nitrogen Rates...................................................................................................... 38 Ohio State Manure Nutrients Research Manure Sidedress................................................................................................................................ 40 Ohio State Cattle Research 2024 Tick Update................................................................................................................................. 42 Ohio State Beef Research Beef Breeding Program Impact Survey ...............................................................................................44 Ohio State Dairy Research Mastitis’ Effects on Milk Composition ...................................................................................................46 Dairy Cattle Behavior During Solar Eclipse .........................................................................................48 Circadian Temperature or Activity Detection ........................................................................................50 Ohio State Small Ruminant Research Effect of Dietary Fiber Management.................................................................................................... 52 Effect of Overprocessing Distiller Grains............................................................................................. 54 Feeding Different Distiller Concentrations .......................................................................................... 56 Pumpkin Seed Impact on Parasites in Sheep..................................................................................... 58 Sheep LAI Summary............................................................................................................................ 60 Small Ruminant Record Keeping Survey............................................................................................ 62 Ohio State Equine Research Cool-Season Grass Hay Preferences.................................................................................................. 64 Meal Frequency Effects on Heart Rate................................................................................................ 66 Meal Frequency Effects on Plasma Amino Acids................................................................................ 68 Ohio State Swine Research Intestinal Parasite Surveillance.............................................................................................................70 Noise on the Swine Farm.................................................................................................................... 72 pH and Temperature of Different Pork Muscles .................................................................................. 74 Quality of the Pork Tenderloin ............................................................................................................. 76 Ohio State Poultry Research Highly Pathogenic Avian Influenza...................................................................................................... 78 Acknowledgments.................................................................................................................................. 80 Glossary................................................................................................................................................. 82

4 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

Ohio State University Department of Animal Science Advancing knowledge of animal sciences for the betterment of animals and humans…

Our areas of research and teaching includes: •

Growth, development, and meat science

•

Breeding, genetics, and reproduction

•

Mammary biology and milk quality

•

Animal welfare and behavior

•

Nutrition and microbiology

•

Waste management and bio-fuels

•

Human-animal interactions

Our Purpose

Visit us at ansci.osu.edu.

2024 eBarns Report | 5

Ohio State Digital Ag Program

DigitalAg OHIO STATE

ABOUT US The Digital Agriculture Program at The Ohio State University embodies the best of the land grant mission – creation, validation, and dissemination of cutting-edge agricultural production technologies. The central focus of this program is the interaction of automation, sensing, and data analytics to optimize crop production in order to address environmental quality, sustainability, and profitability. Research is focused on execution of site-specific nutrient management practices, development of handheld devices for in-field data capture, autonomous functionality of machinery, remote sensing solutions, and data analytics to enhance timing, placement and efficacy of inputs within cropping systems.

VISION The Digital Agriculture Program at The Ohio State University strives to be the premier source of research-based information in the age of digital agriculture.

MISSION • • •

Uniting the private and public sectors to drive innovation for the benefit of farmers.

Partnering with farmers to translate innovation into long-term profitability for production agriculture.

Delivering timely and relevant information for the advancement of digital agriculture technologies.

WHAT IS DIGITAL AGRICULTURE? The premise of digital agriculture includes the advancement of farm operations through implementation of precision agriculture strategies, prescriptive agriculture and data-based decision making. Digital agriculture is a holistic picture of the data space in agriculture, trends related to services directing input management and the value of data usage for improving productivity and profitability of farm operations.

“Digital Agriculture” combines multiple data sources with advanced crop and environmental analyses to provide support for on-farm decision making.

6 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

Ohio State Livestock Production Resources Forages Pasture comprises 7.5% of Ohio's farm land.

For more information visit the Integrated Forage Management Team at forages.osu.edu Manure Nutrients Right source, right rate, right time, right place, right technology.

For more information visit the Ohio Composting and Manure Management at ocamm.osu.edu Beef Cattle Since 2018, Ohio ranks in the top five for Beef Quality Assurance certifications.

For more information on beef production visit the OSU Extension Beef Team at beef.osu.edu Dairy Cattle Ohio is the number one Swiss cheese producing state.

For more information on dairy production visit the Ohio Dairy Resource Center at dairy.osu.edu Small Ruminants Ohio is the largest sheep producing state East of the Mississippi River.

For more information on small ruminant production visit the OSU Extension Sheep Team at sheep.osu.edu Equine Ohio has the 6th largest horse population in the country.

For more information visit the Ohio Equine Resource Center at equine.osu.edu

Swine See Ohio State's new Ohio Pork Information Center: porkinfo.osu.edu

Poultry Ohio is ranked number two in the nation for egg production.

For more information visit the OSU Poultry Team at u.osu.edu/poultry

2024 eBarns Report | 7

Report Guide OBJECTIVE

Location Box

Find study information, objectives, study design, graphs, and summary on the left page. Find results, summaries, project contact, and statistical summary on the right page.

Look to see the county where the study was conducted.

STUDY INFORMATION

STUDY INFORMATION

Planting Date 05/03/2023

Start Date 10/15/2023

Harvest Date 10/20/2023

End Date 08/01/2024 Species Swine

Variety Becks 6076V2P

Start Point 50 lb. (DOF, DOA, DIM)

Population 34,000 sds/ac

End Point 300 lb (DOF, DOA, DIM)

Acres 70 Treatments 5

Treatments 5

Reps 7

Reps 4 Experimental Pen Unit

Treatment Width 40 ft.

Tillage Conventional Management Fertilizer, Herbicide, Insecticide

Breed, Genetics Commercial Line, Yorkshire Cross x Duroc

Previous Crop Soybeans Row Spacing 30 in.

Soil Type Crosby silt loam, 52% Celina silt loam, 48%

Sex Equal Barrow:Gilt Health Protection As needed

Feeding System Self Feeder, Ad libitum IACUC #

RESULTS STUDY DESIGN The study design provides a background on the study. This could include a brief history of research, observations that led to the implementation of this study, explanation of the study design, etc.

Response Variable

Treatment

Treatment

Within a row, means without a common superscript letter differ, P-value <0.05.

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Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

OBSERVATIONS

SUMMARY

The observations section of the report allows us to provide any relevant information that the researchers noticed throughout the duration of the project.

Observations allow for a deeper understanding of the study results.

•

The summary section proves results and findings from the study.

•

Thank you for taking the time to explore our eBarns Report!

RESULTS Treatments (XXX)

Avg. Emergence (plants/ac)

Moisture (%)

Yield (bu/ac)

Treatment Means with the same letter are not significantly different according to Fisher’s Protected Least Significant Differences (LSD) test at alpha = 0.1.

TOOLS OF THE TRADE This section allows us to display the tools and technology used to make each study possible.

LSD: CV:

PROJECT CONTACT The Project Contact section provides the name of the researcher along with their email address. We encourage you to contact them if you have questions about an individual study.

2024 eBarns Report | 9

eBarns Contributors

Tim Barnes

Dara Barclay

Amanda Bennett

OSU Extension

OSU Extension

OSU Extension

Extension Educator Marion County

Ben Bohrer

Assistant Professor

Department of Animal Sciences

Nick Eckel

Extension Educator Wood County OSU Extension

Program Manager, eFields & eBarns

Alora V. Brown Undergraduate Researcher

Extension Educator Miami County

Brady Campbell

Assistant Professor

Karen BennettWimbush

Associate Professor OSU ATI

Chris Clark

Department of Animal Sciences

Eastern Agricultural Research Station Manager

Amber Emmons

Ben Enger

Kellie Enger

OSU Extension

Department of Animal Sciences

Department of Animal Sciences

Department of Animal Sciences

Water Quality Extension Associate

10 | Ohio State Digital Ag Program

Associate Professor

Research Associate

Forages

Manure Nutrients

Alyssa Essman

Assistant Professor

Department of Horticulture and Crop Science

Cattle

Small Ruminant

Kara Flaherty

Education Program Specialist

Department of Animal Sciences

Equine

Gregg Fogle

Small Ruminant Research Center Manager

Swine

Poultry

John Fulton Professor

Department of Food, Agricultural and Biological Engineering

Allen Gahler

Cori Gammariello

Christine Gelley

Yang Geng

OSU Extension

Department of Animal Sciences

OSU Extension

Department of Food Agricultural and Biological Engineering

Jason Hartschuh

Elizabeth Hawkins

Kate Hornyak

OSU Extension

OSU Extension

OSU Extension

Extension Educator Sandusky County

Ryan Haden

Associate Professor OSU ATI

Graduate Research Associate

Assistant Professor, Field Specialist

Extension Educator Noble County

Associate Professor, Field Specialist

Post Doctoral Scholar

Program Coordinator Delaware County

2024 eBarns Report | 11

eBarns Contributors

Dee Jepsen

Dean Kreager

Rob Leeds

Department of Food, Agricultural and Biological Engineering

OSU Extension

OSU Extension

Associate Professor, Extension Educator Guernsey County

Sara Mastellar

Tim McDermott

Professor

Dr. Mark Loux Emeritus Faculty

Department of Horticulture and Crop Science

Alejandro Relling Associate Professor Department of Animal Sciences

Extension Educator Licking County

Clifton Martin

Extension Educator Muskingum County OSU Extension

Talita Resende

Assistant Professor, Swine Health Extension Specialist Department of Animal Sciences

12 | Ohio State Digital Ag Program

Extension Educator Delaware County

Associate Professor

Clif Little

OSU Extension

OSU ATI

Extension Educator Franklin County

Eric Richer

Garth Ruff

Associate Professor, Field Specialist OSU Extension

OSU Extension

Field Specialist OSU Extension

Forages

Manure Nutrients

Clint Schroeder

Program Manager, Ohio Farm Business Analysis Program

Cattle

Small Ruminant

Equine

Swine

Poultry

Elizabeth Share

Jacci Smith

Kendra Stahl

Department of Animal Sciences

OSU Extension

OSU Extension

Program Specialist

Extension Educator Delaware County

Extension Educator Crawford County

OSU Extension

Melva Tacuri Vera

Brayden Thompson

Catelyn Turner

Yifei Wang

Department of Animal Sciences

Department of Animal Sciences

OSU Extension

Department of Animal Sciences

Undergraduate Researcher

Summer Research Intern

Extension Educator Monroe County

Graduate Researcher

Barry Ward

Benjamin Wenner

Aaron Wilson

Ted Wiseman

OSU Extension

Department of Animal Sciences

OSU Extension

OSU Extension

Leader, Production Business Management

Former Associate Professor

Assistant Professor, Field Specialist

Extension Educator Perry County

2024 eBarns Report | 13

John Yost

Chris Zoller

OSU Extension

OSU Extension

Extension Educator Wayne County

Extension Educator Tuscarawas County

14 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

Find eBarns on digitalag.osu.edu/ebarns

Examine the world of agricultural production in more detail than ever before with the eBarns Hub. Access on-farm research from Ohio producers and Extension through the searchable database.

Report Database

Discover a wealth of knowledge available in the yearly eBarns Report now online. Easily find and print specific research reports from every report edition at once.

Filter your search by year, county, report author, research area, and topics.

To Print a Report or Save as a PDF: Select the reports, check the download box in the far-right column, and click Download at the top of the column.

Interested in participating in on-farm research?

Contact the eBarns team to get started!

2024 eBarns Report | 15

2023/2024 Growing Season Weather June 2023 – May 2024 Weather From a smoky yet comfortably cool summer in 2023 to a very active severe weather season to start 2024, the past year has offered plenty to talk about when it comes to weather. Parts of Ohio ebbed in and out of drought, while numerous extreme precipitation events were felt across the state as well. Overall, 2023 (calendar year) was Ohio’s 4th warmest and 49th driest year on record (1895-2023) and over the 12-month period (June 2023-May 2024), it was Ohio’s 3rd warmest 12-month (June to May) on record according the National Centers for Environmental Information. Figure 1 shows temperature and precipitation rankings for individual counties in Ohio for June 2023 – May 2024. For more inseason climate analysis, please visit the State Climate Office of Ohio at climate.osu.edu.

Figure 1. County rankings for average temperature (left) and total precipitation (right) for the 12-month period June 2023May 2024 compared to the long-term mean (1895-2023). Figure courtesy of NOAA Climate at a Glance.

Summer 2023 (June – August): Cooler than average conditions prevailed in June as the state experienced its 25th coldest June on record (1895-present). July and August only featured a few days of extreme heat as well, with near to below average temperatures recorded for the season (Fig. 2. Temperature differences (°Fahrenheit) from the long-term (1991-2020) average conditions for June – August 2023). The cool conditions were the result of frequent episodes of northerly flow that brought cooler and drier air south from Canada.

This pattern also brought periods of persistent wildfire smoke to the region, including three major episodes on June 6-7, June 27-29, and July 16-17. Overall, June was drier than normal, though rain finally started falling around the state on June 10, with heavy rainfall observed across the northern Miami Valley to the Cleveland area. An active pattern followed, with both July and August depicted as wetter than normal. Riding along the edge of a heat dome that brought temperatures up close to 100°F in late August in southwest Ohio, a complex area of showers and storms dropped upwards of 10 inches of rain in 6 hours across north central Ohio. Summer 2023 ranks as the 39th coldest and 32nd wettest summer on record.

Fall 2023 (September – November): Conditions turned dry once again in September, as rainfall was 3-4 inches below average across most of Ohio, and September 2023 ranks as the 5th driest on record.

The U.S. Drought Monitor showed expanding abnormally dry and moderate drought conditions across the state that reached a peak on October 10, 2023 (Fig. 3). There were multiple reports of combine and field fires as a result of the dry conditions. More frequent rainfall events returned later in October and November, though amounts generally stayed below average throughout the fall.

16 | Ohio State Digital Ag Program

Figure 2.

Courtesy of the Midwestern Regional Climate Center.

Figure 3.

U.S. Drought Monitor for Ohio as of 10/10/2023.

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

Fall 2023 (September – November), continued: Temperatures were fairly mild throughout the season, a bit above average for October but close to long-term normals for September and November. The lingering warmth and dry conditions may have helped slightly offset the slow drydown of corn due to the slow growing degree day accumulation throughout the growing season. The first hard freeze conditions (28°F or colder) came to the northwest half of Ohio the last week of October and to southeast Ohio during the first week of November. Fall 2023 ranks as the 24th warmest and 13th driest fall on record.

Winter 2023-2024 (December - February): Typical of El Niño patterns, dry weather persisted into the first part of winter and returned in February, with wetter than normal conditions recorded in January 2024. Temperatures remained above to much above normal for most of the winter, exceeding 8°F above average in some counties. The warm conditions led to a lack of frozen ground and off and on muddy conditions in fields and pastures throughout the winter, though cold stress on livestock was minimal.

The Accumulated Winter Season Severity Index (AWSSI), which uses a mixture of maximum and minimum temperatures along with snow depth and snow duration to quantify the severity of a winter season, shows mild to "record" mild conditions prevailed for much of the region during the 2023-2024 winter season (Fig. 4).

Figure 4. The Accumulated Winter Season Severity Index While snowfall fell behind normal values, one mid-February event for the 2023-2024 winter season. Figure courtesy of the brought upwards of 8” to portions of central Ohio, which was more Midwestern Regional Climate Center. than half of the season’s total.

By the end of February though, warm, moist conditions from the Gulf of Mexico led to an outbreak of severe weather during the early morning hours of February 28th. Several hail and damaging wind reports were reported along with nine tornadoes. One of these included an EF2 tornado (winds ~135 mph) that moved across eastern Clark County into Madison County, and brought damage to the Molly Caren Agricultural Center, home of the Farm Science Review. In summary, the Winter 2023-2024 ranks as the 2nd warmest and 57th wettest winter on record.

Spring 2024 (March - May): Frequent severe weather outbreaks and warmer than average temperatures headlined the weather stories for spring 2024. Numerous tornado and severe weather events occurred across the state, as Ohio approached the tornado record with 58 by the end of the month (eventually eclipsed its record number of tornadoes for a year and currently at 65 as of August 1, 2024). Destructive and deadly tornadoes hit rural areas hard, with major destruction in places like Mercer, Darke, Auglaize, and Logan Counties. Ohio experienced its third largest tornado outbreak on record on May 7th with 19 tornadoes officially reported.

All three months had above average and top ten warmest temperature rankings, and the last hard freeze conditions (28°F or colder) occcured before April 10th for most of Ohio. Precipitation extremes were also prevalent, as northwest Ohio seemed to catch the bulk of the rainfall during the planting season (Fig. 5. Precipitation differences (percent of normal) from the long-term (1991-2020) average conditions for March – May 2024).

Mercer to Marion Counties northward to Defiance and Lucas Counties all experienced much above normal precipitation for the spring season which hampered planting efforts. Wet conditions were also noteworthy in parts of eastern and southeastern Ohio where high river levels were recorded on the Ohio River and flooding fatalities were reported near Marietta. Across the south however, wet conditions in March turned a bit drier by April and May and precipitation was timely for planting and pasture growth throughout the region. However, these drier conditions would initiate more drought like conditions that set in during the summer. Overall, Spring 2024 ranks as the 2nd warmest and 28th wettest spring on record.

Figure 5.

Figure courtesy of the Midwestern Regional Climate Center.

PROJECT CONTACT Dr. Aaron B. Wilson, Extension Field Specialist Ag Weather & Climate (wilson.1010@osu.edu).

2024 eBarns Report | 17

Ohio Farm Custom Rates, 2024 Farming is a complex business, and many Ohio farmers utilize outside assistance for specific farm-related work. This option is appealing for tasks requiring specialized equipment or technical expertise. Often, having someone else with specialized tools perform tasks is more cost effective and saves time. Farm work completed by others is often referred to as “custom farm work” or more simply, “custom work”. A “custom rate” is the amount agreed upon by both parties to be paid by the custom work customer to the custom work provider.

The 2024 publication, released on July 1, 2024, reports custom rates based on a statewide survey. Surveys were mailed/ emailed to past respondents and distributed at various Extension programs through the winter of 2024 (beginning of 2024). The summary information included in the publication is based on the responses of 333 farmers, custom operators, farm managers, and landowners. These rates, except where noted, include the implement and tractor if required, all variable machinery costs such as fuel, oil, lube, twine, etc., and labor for the operation.

Some custom rates published in this study vary widely, possibly influenced by type or size of equipment used (e.g.

20-shank chisel plow versus a 9-shank), size and shape of fields, condition of the crop (for harvesting operations), skill level of labor, amount of labor needed in relation to the equipment capabilities, cost margin differences for full-time custom operators compared to farmers supplementing current income, and region of Ohio with different custom services supply and demand characteristics.

Some custom rates reflect discounted rates as the parties involved have family or community relationships. Discounted rates may also occur when the custom work provider is attempting to strengthen a relationship to help secure the custom farmed land in a future purchase, cash rental or other rental agreement. Some providers charge differently because they are simply attempting to spread their fixed costs over more acreage to decrease fixed costs per acre and are willing to forgo complete cost recovery. Charges may be added if the custom provider considers a job abnormal such as distance from the operator’s base location, difficulty of terrain, amount of product or labor involved with the operation, or other special requirements of the custom work customer.

As a custom provider, the average rates reported in this publication may not cover your total costs for performing the custom service. As a customer, you may not be able to hire a custom service for the average rate published in this factsheet.

It is recommended that you calculate your own costs carefully before determining the rate to charge or pay.

18 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

Note for Tables included here: The measures shown are the summary of the survey respondents. The measures are the Average (Mean), Responses, Maximum, Minimum, Median, Standard Deviation, and Statistical Range. The Average reported in this publication is a simple average of all the survey responses for each operation. Responses indicates the number of survey responses for each given operation. The Maximum and Minimum reported in the table are the maximum and minimum amounts reported from the survey data for a given custom operation. The median represents the middle value of the survey responses. Standard Deviation is a measure of variability. Statistical Range identified in the tables consists of two numbers. The first is the average plus the standard deviation. The second number of the range is the average minus the standard deviation. In cases where there were too few responses to statistically analyze, statistics are not presented due to the low response rate. The data from this survey are intended to show a representative farming industry cost for specified machines and operations in Ohio.

To review the full publication, visit the Custom Rates and Machinery Costs on the OSU Extension, Farm Office website:

go.osu.edu/FarmCustomRates2024

PROJECT CONTACT Barry Ward

Clint Schroeder

Leader, Production Business Management ward.8@osu.edu

Program Manager, Farm Business Analysis schroeder.307@osu.edu

Eric Richer

Amanda Bennett

Field Specialist, Farm Management richer.5@osu.edu

Extension Educator, Agriculture and Natural Resources bennett.709@osu.edu

2024 eBarns Report | 19

Ohio State Forages Research For 2024, eBarns forage research was focused on increasing forage production, forage quality, and pasture management in Ohio. The forage research presented in here covers precision nutrient management, species selection, and looking critically at effective management strategies. Below are highlights of the 2024 eBarns Forage research: 22 acres of forage

9 forage studies

For more forage research and feeding management from Ohio State University Extension, explore the following resources: Agronomic Crops Team Forages Research The Agronomic Crops Team performs interesting research studies on a yearly basis.

Resources, fact sheets, and articles on alfalfa, winter annuals, and summer annuals can be found here Agronomic Crops Team Forage Research on the Agronomic Crops go.osu.edu/CropTeamForages Team website.

Ohio Forage Performance Tests The purpose of the Ohio Forage Performance Test is to evaluate forage varieties of alfalfa, annual rye grass, and cover crops for yield and other agronomic characteristics.

This evaluation gives forage producers comparative information for selecting the best varieties for their unique production systems.

20 | Ohio State Digital Ag Program

Forage Team forages.osu.edu

Beef Team u.osu.edu/beefteam

Ohio Forage Performance Tests go.osu.edu/OhioForages Dairy Team dairy.osu.edu

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

Species for Planting by Mid-July Corn Plant Silage

Highest single cut forage yield potential of all choices.

Silage quality will be lower than with normal planting dates.

Risk will be getting it harvested at right moisture for good fermentation.

Forage Sorghum Sorghum Sudangrass Sudangrass

Best harvested as silage.

Brown midrib (BMR) varieties are best for lactating cows. Conventional varieties are okay if BMR seed is not available.

Can produce 3-4 tons of dry matter/acre.

Risk of prussic acid (hydrogen cyanide gas) if frosted.

Soybean Silage

Reasonable alternative to replace alfalfa forage.

Check seed treatment and herbicide labels, many restrict forage use.

Teff Grass

Best suited to beef and sheep; lower yield than sorghum grasses.

Can harvest as hay or silage.

Millets

Best suited to beef and sheep; many produce a single harvest.

Best harvested as silage.

Pearl millet does not produce prussic acid after frost damage.

Mixtures of annual grasses with soybean

Best harvested as silage.

Mixtures of sorghum grasses or millets or even oats and spring triticale with soybean are feasible and can improve forage quality characteristics.

Species for Planting Late-July to Mid-September Oat or Spring Triticale

Can be mowed and wilted to correct harvest moisture.

Harvesting as hay can be challenging.

Earlier planting dates provide more autumn yield.

Oat or Spring Triticale Plus Winter Cereals

Winter cereals (Winter rye, Winter wheat, Winter triticale) can be added to oat or spring triticale to add a forage harvest early next spring. Winter rye can also contribute a little extra autumn yield to the mixture.

Oat or Spring Triticale Plus Field Peas

Field peas can improve forage quality (especially crude protein content) but will increase seed cost.

Italian Ryegrass

Earlier planting dates provide more autumn yield.

Excellent forage quality in the fall.

Potential for three harvests next year starting in late April.

2024 eBarns Report | 21

Autumn Olive Control OBJECTIVE

Autumn Olive is a non-native and invasive shrub/tree that can be found in Ohio woodlands, pastures, and abandoned fields. The objective of this study was to evaluate dormant, winterapplied treatments for the management of Autumn Olive in pasture systems.

Eastern Ag Research Station CFAES and OSU Extension Noble County

STUDY INFORMATION Application Date 02/07/2024

Evaluation Date 05/21/2024 Species Autumn Olive System Pasture Location Caldwell, OH Treatments 6 Reps 5 Application Cut Stump, Basal Bark, or Dormant Stem Location EARS

STUDY DESIGN

Figure 1. Autumn Olive dormant management trial at the Eastern Agricultural Research Station in Caldwell, OH.

This study was conducted in 2023 and repeated in 2024 at one location evaluating six Autumn Olive treatments. The experimental design was a completely randomized design (CRD). The study was conducted at the Eastern Agricultural Research Station (EARS) in Caldwell, OH. Applications were made in late-winter (February) and treatments were evaluated approximately three months later (May). View the 2023 data in the 2023 eBarns Report on pages 20-21.

Figures 2, 3, and 4. Treated Autumn Olive plants in May following applications in late-February.

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Forages

Manure Nutrients

Cattle

Small Ruminant

OBSERVATIONS

Equine

Swine

Poultry

SUMMARY

In the two years conducting this trial, all treatments except treatments 2 and 4 provided adequate control of Autumn Olive with little to no regrowth.

Plant size and environmental conditions may influence efficacy.

RESULTS

•

Several options exist for control of Autumn Olive in pasture systems.

•

With appropriate product, carrier, and rate selection, applications can be made in late-winter to cut stumps, basal bark, or dormant stems.

Figure 5. Results of the 2024 trial evaluating different treatments for the control of Autumn Olive.

Treatment means with the same letter are not significantly different at a = 0.05.

Rating structure, based on regrowth following applications: 1: none 2: slight regrowth 3: moderate regrowth 4: extensive regrowth

Treatment

Application Type

Herbicides and Rates

1 2 3

Cut Stump

Pathfinder RTU

Basal Bark

20% Garlon 4, 80% Bark Oil

Basal Bark

20% Garlon 4, 1% Milestone, 79% Bark Oil

4

Dormant Stem

5% Garlon 4, 2% Dyne-Amic, 93% Water

5

Cut Stump

50% Glyphosate

6

Basal Bark

20% Garlon 4, 80% Diesel Fuel

PROJECT CONTACTS TOOLS OF THE TRADE Find more information on the identification and control of problematic weed species by visting: u.osu.edu/osuweeds/ (or use the QR code to the right)

•

Ted Wiseman • (wiseman.15@osu.edu)

Dr. Alyssa Essman (essman.42@osu.edu)

•

Dean Kreager (kreager.5@osu.edu)

•

Chris Zoller (zoller.1@osu.edu)

•

Clifton Martin (martin.2422@osu.edu)

•

Clif Little (little.16@osu.edu)

•

Christine Gelley (gelley.2@osu.edu)

•

Dr. Mark Loux

2024 eBarns Report | 23

Corn DON Resistance Screening OBJECTIVE

eBarns Collaborating Farms

Assessing the difference between hybrids in resistance to DON mycotoxin production from Gibberella Ear Rot

STUDY INFORMATION

OSU Extension Statewide

Bucyrus

Planting: 05/19/2023

Temperature (⁰F)

Departure from Avg.

GDD

10 30 High Low Mean year year

Population 34000 sds/ac

Harvest: 11/16/2023

Relative Humidity Average (%)

Rain Fall

Departure from Avg.

(inches)

10 30 year year

Total Acres 5

July 90.2

50.8

71.2

-1.7

-1.5

657

81.5

5.38

0.68 1.33

Treatments 80

August 89.2

44.2

67.6

-3.5

-3.4

550

83.3

7.11

3.82 3.72

April-Sept. 88.5

38.3

63.6

-1.7

-1

2681

72.6

22

-2.7

-1.9

April- Oct. 88.4

35.7

62.1

-1.8

-0.9

2864

73.4

25.3

-3.3

-2

Reps 4 Treatment 10 ft.

Width Row Spacing 30 in.

Figure 1. Weather condition data in Bucyrus, OH. GDD = Growing Degree Days

Apple Creek

STUDY DESIGN This study was conducted in South Charleston, Apple Creek, and Bucyrus in a randomized complete block design.

The Bucyrus and Apple Creek locations had natural DON infection and was inoculated at green silk by spraying Fusarium Graminearum spores on the silks.

Temperature

Dep. from Avg.

GDD

Harvest: 12/13/2023

Rel. Hum. Avg.

Rain Fall

Dep. from Avg.

10 yr.

30 yr.

High

Low

Mean

10 yr.

30 yr.

July 89.6

53

71.7

-0.5

-0.1

673

76

3.92

-1.05

-0.63

August 85.4

48.6

67.7

-2.9

-2.7

548

81

8.11

4.87

4.39

April-Sept. 86.5

41.4

63.1

-1.5

-0.8

2595

72.1

20.8

-4.8

-4.5

April-Oct. 86.2

38.9

61.8

-1.3

-0.4

2792

72.8

24

-5.2

-4.8

Figure 2. Weather condition data in Apple Creek, OH.

South Charleston

The South Charleston location was not inoculated due to stalk lodging at tassel and only had natural infection.

Grain samples were collected at harvest from each plot and finely ground for DON analysis which was conducted using Liquid chromatography-mass spectrometry.

Planting: 05/26/2023

Temperature

Planting: 05/23/2023 Dep. from Avg.

GDD

Harvest: 11/20/2023

Rel. Hum. Avg.

Rain Fall

Dep. from Avg.

10 yr.

30 yr.

High

Low

Mean

10 yr.

30 yr.

July 89.6

53.5

72.6

-0.9

-0.5

698

81

5.62

0.21

0.71

August 90.5

48.5

69.8

-2.1

-2

613

81

4.3

0.93

1.05

April-Sept. 87.9

41

64.6

-1.8

-0.9

2837

74.2

20.5

-5.7

-4.8

April-Oct.

38.6

63.1

-1.7

-0.7

3058

74.6

23.2

-6.3

-5

88

Figure 3. Weather condition data in South Charleston, OH.

24 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Small Ruminant

Cattle

OBSERVATIONS

Equine

Swine

Poultry

SUMMARY

•

At all locations, tassel window was compressed with all hybrids in green silk during a 2-week window.

•

Weather conditions during tassel were most favorable in Bucyrus, then Apple Creek, with the least favorable conditions in South Charleston.

RESULTS

•

A total of 13 hybrids had an average DON below 1 ppm (range 0 to 2.4) and 28 hybrids had an average DON below 2 ppm (range 0 to 4.1) at all locations.

•

A total of 43 hybrids had average DON below 3 ppm at all 3 locations, but the range of DON for these hybrids was 0-6.5 ppm across all plots at these locations.

•

With one year of data we can not guarantee a hybrids resistance, but hybrids with high DON levels are susceptible.

Numbers are DON in ppm Hybrid

RM

Bucyrus

South Charleston

Apple Creek

All Location Average

High

116

30.85

7

22.85

19.7

•

Dekalb

Low

97

0

0

0.1275

0.131

•

Golden Harvest •

Pioneer

Mean

3.03

1.19

4.24

3.1499

•

LG Seeds

•

Revere

LSD 0.1

4.62

2.67

2.849

2.315718

•

NK

•

•

Minyo Check

Seed Genetics Direct

CV

130.6

134.68

57.488

99.75

PARTICIPATING BRANDS •

PC SEED

Figure 4. Summary of Results. RM = Relative Maturity

See the C.O.R.N. Newsletter article for a full list of data (detailed by hybrid), and more weather details (by location): go.osu.edu/don2023 Figures 5 and 6. Images of corn ears during this study Thank you to the Ohio Corn Board for funding this research project.

TOOLS OF THE TRADE Almaco Small Plot Combine with Air Cyclone Grain Sampler

PROJECT CONTACT Jason Hartschuh (hartschuh.11@osu.edu)

This tool collects a uniform grain sample from the entire plot.

2024 eBarns Report | 25

Mechanical Control of Pasture Weeds OBJECTIVE

Determining if weed populations in pastured forages could be changed or reduced by varying the timing of mowing throughout the late spring and summer growing period without the use of herbicides.

STUDY INFORMATION STUDY INFORMATION

Eastern Ag Research Station OSU Extension Noble County

WEATHER INFORMATION

Planting Date Established Pasture Harvest Date Treatment Dependent Variety Pasture Forages Acres 1 Treatments 8 Reps 4 Plot Size 15 ft. wide x 20 ft. long, 1 ft. border outside Management No additional fertilizer

STUDY DESIGN A randomized complete block design with 8 treatments (including a control) and 4 replications of each treatment in this multiyear experiment (2020 - 2022). Forage samples (61cm x 61cm, hand harvested) taken near the beginning of June, July, August and September each year. Broadleaf weed species were separated out. Fresh weights were recorded and a sub-sample was dried in a forage dryer at 46 degrees Celsius (114.8 degrees Fahrenheit).

Figure 1. The toal rainfall for each year of the study, from the month of May - September.

After harvesting samples, cow/calf pairs grazed the plots paddock until the farm manager determined cattle should be moved.

After each grazing, treatment plots were cut with a rotary mower according to treatment (1 pass over the plot, cutting to height of approximately 4 inches above the soil surface).

Figure 2. Image of pasture used in study with weeds present. Site is a predominately tall fescue and mixed grass pasture field.

26 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

OBSERVATIONS

Small Ruminant

•

Data showed that mowing monthly significantly reduced the number of weeds compared to no mowing or mowing in June (Figure 4).

•

•

Mowing in only June had higher weed yields than did the control (no mowing). The increased • weeds present in the June treatment may be the result of opening up the canopy too early in the growing season exposing weeds to increased sunlight.

Equine

Swine

Poultry

SUMMARY

With cocklebur being a summer annual, early mowing may have contributed to it being so prevalent.

•

Mowing in just July maximized forages and minimized weeds at this location.

Cocklebur was also able to produce seed under the mowing height in all treatments.

•

Some weeds, such as Cocklebur, will require a herbicide treatment for optimum control.

RESULTS Forages DM lbs/ac

Forage Totals

Figure 3.

Treatment

Mowing Treatment

Weeds DM lbs/ac

Weed Totals

Mowing Treatment

Figure 4.

TOOLS OF THE TRADE 2’ x 2’ Grid The grid is placed in a different quadrant of the plot, samples were collected by hand. Weeds can be separated from the forages and dried. Samples were collected at the beginning of every month during this study.

Description

1

Control, No Mowing

2

Mowing in June

3

Mowing in July

4

Mowing in August

5

Mowing in September

6

Mowing in June and August

7

Mowing in July and September

8

Mowing in June, July, August, and September

Figures 3 and 4: Letters indicate significant difference of p> 0.10 between treatments for all three years.

PROJECT CONTACT Ted Wiseman (wiseman.15@osu.edu) Christine Gelley (gelley.2@osu.edu) Catelyn Turner (turner.1630@osu.edu)

2024 eBarns Report | 27

Oats Nitrogen Rate August Planting OBJECTIVE

NC Ag Research Station

Assess the effects of nitrogen rate on mid-August planted oats.

OARDC Sandusky County

Planting Date 08/31/2023 Harvest Date 11/09/2023 Variety FSM Oats Population 100 lbs/ac Acres 2 Treatments 5

WEATHER INFORMATION MAX. AND MIN. TEMPERATURE (°F)

STUDY INFORMATION

Management Fertilizer Previous Crop Wheat Row Spacing 7.5 in.

Soil Type Hoytville Clay Loam, 90% Rimer Loamy Fine Sand, 10%

DAILY PRECIPITATION (IN)

Tillage No-Till

Harvest Date

90 80 70 60 50 40 30 20 10 0

Reps 4 Treatment Width 10 ft.

Planting Date

100

3

2

1

0

Growing Season Weather Summary APR

MAY

JUN

JUL

AUG

SEP

Total

Precip (in.)

2.72

0.92

2.71

6.61

4.64

2.22

19.82

Cumulative GDDs

186

501

1012

1725

2344

2831

2831

STUDY DESIGN This study was designed as a randomized complete block design with nitrogen rates of 0, 23, 46, 69, and 92 lbs/ac of nitrogen as urea applied at planting. Plots were no-till planted with a Great Plains grain drill at 100 pounds of oats per acre. A fungicide was applied 3 weeks after planting for crown rust control. Plots were harvested once they began to head using an RCI plot harvester which harvested the center 3 feet of the plot by 30 feet long. Sub-samples for the forage were collected and dried for lab analysis of forage quality.

28 | Ohio State Digital Ag Program

Figure 1. Planted oats - planted at 100 pounds per acre.

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

OBSERVATIONS

SUMMARY

Plots were slower growing than normal and never reached head emergence. Harvest was done after the first frost that appeared to stunt plant growth. Plots were moisture stressed with too much rainfall. While the field is well tiled, harvest was further complicated by muddy field conditions.

•

Nitrogen rate had a significant effect on oats yield and quality factors.

•

The zero nitrogen treatment contained about 50% wheat stubble in the samples.

•

Yields were below our trend line oats yield for late August plantings by about half a ton.

•

Nitrogen had a significant effect of increasing Crude Protein and Total Digestible Nutrients (TDN).

•

Even though yields and Crude Protein were lower than our historic trend, the 69 lbs/ac rate of nitrogen was the most economical for both yield and quality.

RESULTS Treatments (lbs/ac N)

Yield lbs/ac Crude Protein 15% moisture %

NDF

TDN

0

212 c

7.7 c

60.9 a

53.8 b

23

409 b

8.5 bc

48.5 a

63.4 a

46

557 b

9.2 b

45.5 a

65.7 a

69

989 a

12.4 a

45.0 a

67.5 a

92

1,086 a

13.2 a

44.9 a

66.1 a

LSD: 180

LSD: 2

LSD: 7

LSD: 6

CV: 22.6%

CV: 11.7%

CV: 12.2%

CV: 7.5%

Treatment Means with the same letter are not significantly different according to Fisher’s Protected Least Significant Differences (LSD) test at alpha = 0.1.

PROJECT CONTACT Jason Hartschuh (hartschuh.11@osu.edu) Allen Gahler (gahler.2@osu.edu)

2024 eBarns Report | 29

Oats Nitrogen Rate July Planting OBJECTIVE

NC Ag Research Station

Evaluate July planted oats after wheat harvest response to nitrogen fertilizer rate.

Planting Date 07/30/2023 Harvest Date 09/26/2023 Variety FSM Oats Population 100 lbs/ac Acres 1 Treatments 5

Sandusky County

WEATHER INFORMATION MAX. AND MIN. TEMPERATURE (°F)

STUDY INFORMATION

OARDC

Management Fungicide, Insecticide Previous Crop Wheat Row Spacing 7.5 in.

Soil Type Hoytville Clay Loam, 90% Rimer Loamy Fine Sand, 10%

DAILY PRECIPITATION (IN)

Tillage No-Till

Harvest Date

90 80 70 60 50 40 30 20 10 0

Reps 4 Treatment Width 10 ft.

Planting Date

100

3

2

1

0

Growing Season Weather Summary APR

MAY

JUN

JUL

AUG

SEP

Total

Precip (in.)

2.72

0.92

2.71

6.61

4.64

2.22

19.82

Cumulative GDDs

186

501

1012

1725

2344

2831

2831

STUDY DESIGN This study was designed as a randomized complete block design with nitrogen rates of 0, 23, 46, 69, and 92 lbs/ac of nitrogen as urea applied at planting. Plots were no-till planted with a Great Plains grain drill at 100 pounds of oats per acre. A fungicide was applied 3 weeks after planting for crown rust control. Plots were harvested once they began to head using an RCI plot harvester which harvested the center 3 feet of the plot by 30 feet long. Sub-samples for the forage were collected and dried for lab analysis of forage quality.

Figure 1. Planted oats - yield was not significanly impacted by the change in nitrogen rate.

30 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

OBSERVATIONS

SUMMARY

Oats growth was very slow this year due to suffering from both too wet and too dry of conditions. Wet conditions delayed planting after wheat harvest for 2 weeks. After planting another large rain fall event may have tied up nitrogen or caused leaching.

•

July planted oat yields were much lower than normal, with our highest yielding treatments being less than half a ton per acre on average. This led to nitrogen not having a significant impact on yield but higher nitrogen rates did trend towards a higher yield.

•

With these low yields, about 200 pounds per acre or half of the forage yield in some of the treatments was wheat stubble.

•

Nitrogen didn’t have a significant effect on Crude Protein.

•

The 46 lbs/ac of nitrogen treatment had the highest digestibility and energy which was significantly different from the untreated control.

•

Results followed trends seen in previous years but yields and protein levels were below average.

RESULTS Treatments (lbs/ac N)

Yield lbs/ac Crude Protein 15% moisture %

NDF

TDN

0

533 a

8.3 a

67.7 a

51.7 b

23

476 a

7.9 a

59.9 ab

57.2 ab

46

554 a

8.6 a

58.3 b

59.8 a

69

587 a

8.6 a

59.2 ab

58.9 ab

92

895 a

7.8 a

64.4 ab

56.8 ab

LSD: 426

LSD: 1

LSD: 9

LSD: 7

CV: 56.9%

CV: 12.4%

CV: 11.2%

CV: 10.3%

Treatment Means with the same letter are not significantly different according to Fisher’s Protected Least Significant Differences (LSD) test at alpha = 0.1.

PROJECT CONTACT Jason Hartschuh (hartschuh.11@osu.edu) Allen Gahler (gahler.2@osu.edu).

2024 eBarns Report | 31

N Rate on Organic Summer Annual Species OBJECTIVE

eFields Collaborating Farm

Evaluate the effect of nitrogen rate across four summer annual organic forage species planted into Red Clover after wheat.

Planting Date 08/10/2023 Harvest Date 10/09/2023 Variety See Treatments Population See Treatments Acres 5 Treatments 16

Ottawa County

WEATHER INFORMATION MAX. AND MIN. TEMPERATURE (°F)

STUDY INFORMATION

OSU Extension

Management None Previous Crop Wheat Row Spacing 7.5 in.

Soil Type Colwood Loam, 80% Kibbie Fine Sandy Loam, 20%

DAILY PRECIPITATION (IN)

Tillage Light Tillage

90 80 70 60 50 40 30 20 10

3

2

1

0

Growing Season Weather Summary APR

MAY

JUN

JUL

AUG

SEP

Total

Precip (in.)

2.02

0.99

2.15

7.63

4.34

1.58

18.71

Cumulative GDDs

200

549

1101

1848

2480

2973

2973

STUDY DESIGN This study was laid out in a randomized complete block split block design. With the treatments of species (oats, BMR Sorghum, Sorghum Sudan, and Red Clover) and nitrogen rates of (0, 50, 100, and 150 pounds per acre) from pelletized chicken litter. All species were planted and harvested on the same day. Plots were planted after wheat harvest and frost seeded into Red Clover. The field was lightly disc to slow down clover growth and allow for grass crop establishment.

Figure 1. Organic Sudan Oats.

32 | Ohio State Digital Ag Program

Harvest Date

0

Reps 4 Treatment Width 15 ft.

Planting Date

100

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

OBSERVATIONS

SUMMARY

In this trial, we lightly disced the red clover that was already established to slow its growth, so that the grass crops could establish. In all plots, the red clover survived the discing and grew with the grass crop. The visual amount of clover was inversely related to nitrogen rates, ie, more nitrogen less clover, but more grass crops. Plots were harvested before grass crop heading, possibly reducing yield.

•

Compared to other species trials, there was less yield increase from nitrogen application showing that the grass crop was able to find soil nitrogen from the clover that was present.

•

However, nitrogen applications did significantly increase crop yields in all plots but the Red Clover only plots. Both species and nitrogen had a significant effect on Crude Protein (CP). While in some species CP decreased with increased nitrogen applications, this was caused by the change in species mix with less clover at higher nitrogen application rates and more grass crop.

•

Neither species nor nitrogen rate affects energy.

Planting other summer annual forages into frost seeded red clover can increase yield and may decrease CP so that the forage is closer to livestock’s nutritional needs.

PROJECT CONTACT Jason Hartschuh (hartschuh.11@osu.edu) Nick Eckel (eckel.21@osu.edu) Allen Gahler (gahler.2@osu.edu)

RESULTS Treatments

Yield lbs/ac 15% moisture

Crude Protein %

NDF

TDN

Oats 0 lb/ac Nitrogen

1.6 cdef

18.4 a

49.3 ef

56.5 a

Oats 50 lbs/ac Nitrogen

1.9 bcd

15.7 abc

52.3 cdef

56.9 a

Oats 100 lbs/ac Nitrogen

1.9 bc

16.9 ab

51.3 cdef

57.6 a

Oats 150 lbs/ac Nitrogen

2.0 ab

14.9 bc

53.2 bcde

58.1 a

BMR Sorghum 0 lb/ac Nitrogen

1.5 defgh

14.5 bc

56.1 abcd

55.9 a

BMR Sorghum 50 lbs/ac Nitrogen

2.0 abc

15.7 abc

54.3 abcde

55.4 a

BMR Sorghum 100 lbs/ac Nitrogen

1.8 bcde

14.0 bc

58.6 ab

56.4 a

BMR Sorghum 150 lbs/ac Nitrogen

1.8 bcde

14.2 bc

56.7 abc

56.7 a

Sorghum Sudan 0 lb/ac Nitrogen

1.5 efgh

14.5 bc

55.9 abcd

56.7 a

Sorghum Sudan 50 lbs/ac Nitrogen

1.6 cdefg

12.9 c

59.5 a

55.5 a

Sorghum Sudan 100 lbs/ac Nitrogen

1.8 bcde

13.1 c

56.7 abc

57.6 a

Sorghum Sudan 150 lbs/ac Nitrogen

2.3 a

14.0 bc

54.2 abcde

56.0 a

Red Clover 0 lb/ac

1.2 gh

16.8 ab

50.1 ef

55.4 a

Red Clover 50 lbs/ac

1.3 fgh

16.2 ab

50.8 def

56.6 a

Red Clover 100 lbs/ac

1.1 h

17.0 ab

51.9 cdef

57.2 a

Red Clover 150 lbs/ac

1.2 h

18.4 a

47.1 f

56.4 a

LSD: 0.3

LSD: 3.0

LSD: 5.5

LSD: 2.9

CV: 20.5%

CV: 16.5%

CV: 8.7%

CV: 4.3%

Treatment Means with the same letter are not significantly different according to Fisher’s Protected Least Significant Differences (LSD) test at alpha = 0.1.

2024 eBarns Report | 33

No-Till Organic Summer Annuals OBJECTIVE

NC Ag Research Station

Asses yield differences between summer annual forage species and nitrogen rate in a no-till organic system, with frost seeded Red Clover.

Planting Date 08/10/2023 Harvest Date 10/09/2023 Variety See Treatments Population See Treatments Acres 5 Treatments 16

Sandusky County

WEATHER INFORMATION MAX. AND MIN. TEMPERATURE (°F)

STUDY INFORMATION

OARDC

Previous Crop Wheat Row Spacing 7.5 in.

Soil Type Hoytville Clay Loam, 90% Rimer Loamy Fine Sand, 10%

STUDY DESIGN This study was conducted on an organic farm after wheat harvest. Red clover was frost interseeded into the wheat in March. After wheat harvest Red Clover was mowed to slow the clover. A randomized complete block split-plot design was used with nitrogen rate as organic poultry litter pellets as the main effect and forage species as the secondary effect.

Nitrogen was applied using a calibrated horn spreader, and then forages were planted with a John Deere no-till drill. Seeding rates were 100 lbs/ac of oats, 35 lbs/ac BMR Sorghum, 30 lbs/ac Sorghum Sudan, and 15 lbs/ac Red Clover with no additional forage.

34 | Ohio State Digital Ag Program

DAILY PRECIPITATION (IN)

Tillage No-Till

Harvest Date

90 80 70 60 50 40 30 20 10 0

Reps 4 Treatment Width 15 ft.

Planting Date

100

3

2

1

0

Growing Season Weather Summary APR

MAY

JUN

JUL

AUG

SEP

Total

Precip (in.)

2.72

0.92

2.71

6.61

4.64

2.22

19.82

Cumulative GDDs

186

501

1012

1725

2344

2831

2831

Forages

Manure Nutrients

Cattle

OBSERVATIONS •

Cooler temperatures after planting favored clover and oats growth over the summer annuals BMR Sorghum and Sorghum Sudan.

•

The cooler conditions also slowed summer annual plant growth with plant height being only half of normal at 60 days.

•

The weed plant count was lower in the plots with at least 50 pounds of nitrogen and a grass species than in the clover-only plot.

Small Ruminant

Equine

Swine

Poultry

SUMMARY In this trial, the Red Clover dominated the plots reducing the growth of the grass species. With the clover alone plots having the highest yields. However, the higher rates of nitrogen did assist the oats in competing with the clover. As a blend, the higher nitrogen rates increased the growth of the grass species, decreasing the total forage protein. As the amount of grass species present increased so did the Neutral Detergent Fiber (NDF) and the Total Digestible Nutrients (TDN) of the forage. While the grasses competed with the clover when higher nitrogen rates were applied, a better method of stunting the clover than mowing is needed to maximize forage yields from the grass species.

PROJECT CONTACT Jason Hartschuh (hartschuh.11@osu.edu) Allen Gahler (gahler.2@osu.edu)

RESULTS Treatments

Yield lbs/ac 15% moisture

Crude Protein %

TDN

NDF

Oats 0 lb/ac N

1.57 cdef

18.43a

56.5a

49.33ef

Oats 50 lbs/ac N

1.85 bcd

15.73abc

56.85a

52.25cdef

Oats 100 lbs/ac N

1.85 bc

16.93ab

57.55a

51.33cdef

Oats 150 lbs/ac N

2.02 ab

14.85bc

58.05a

53.23bcde

BMR Sorghum 0 lb/ac N

1.45 defgh

14.45bc

55.93a

56.08abcd

BMR Sorghum 50 lbs/ac N

1.99 abc

15.7abc

55.38a

54.25abcde

BMR Sorghum 100 lbs/ac N

1.83 bcde

14.03bc

56.43a

58.55ab

BMR Soghum 150 lbs/ac N

1.84 bcde

14.2bc

56.68a

56.7abc

Sorghum Sudan 0 lb/ac N

1.45 efgh

14.5bc

56.73a

55.88abcd

Sorghum Sudan 50 lbs/ac N

1.56 cdefg

12.93c

55.53a

59.53a

Sorghum Sudan 100 lbs/ac N

1.81 bcde

13.05c

57.63a

56.65abc

Sorghum Sudan 150 lbs/ac N

2.32 a

14.03bc

56.03a

54.15abcde

Red Clover 0 lb/ac N

1.16 gh

16.75ab

55.38a

50.05ef

Red Clover 50 lbs/ac N

1.26 fgh

16.2ab

56.6a

50.75def

Red Clover 100 lbs/ac N

1.14 h

17.03ab

57.18a

51.93cdef

Red Clover 150 lbs/ac N

1.15 h

18.4a

56.43a

47.05f

LSD: x

LSD: 3.0

LSD: 2.9

LSD: 5.5

CV: 20.5%

CV: 16.5%

CV: 4.3%

CV: 8.7%

Treatment Means with the same letter are not significantly different according to Fisher’s Protected Least Significant Differences (LSD) test at alpha = 0.1.

2024 eBarns Report | 35

N Rate on Summer Annual Species OBJECTIVE

NC Ag Research Station

Evaluate the effect of nitrogen rate across four summer annual forage species.

Planting Date 08/04/2023 Harvest Date 10/19/2023 Variety See Treatments Population See Treatments Acres 2 Treatments 16

Sandusky County

WEATHER INFORMATION MAX. AND MIN. TEMPERATURE (°F)

STUDY INFORMATION

OARDC

Management None Previous Crop Wheat Row Spacing 7.5 in.

Soil Type Hoytville Clay Loam, 89% Rimer Loamy Fine Sand, 11%

DAILY PRECIPITATION (IN)

Tillage No-Till

Harvest Date

90 80 70 60 50 40 30 20 10 0

Reps 4 Treatment Width 10 ft.

Planting Date

100

3

2

1

0

Growing Season Weather Summary APR

MAY

JUN

JUL

AUG

SEP

Total

Precip (in.)

2.72

0.92

2.71

6.61

4.64

2.22

19.82

Cumulative GDDs

186

501

1012

1725

2344

2831

2831

STUDY DESIGN This study was laid out in a randomized complete block split block design. With the treatments of species (oats, BMR Sorghum, Sorghum Sudan, and red clover) and nitrogen rates of (0, 50, 100, and 150 pounds per acre).

All species were planted and harvested on the same day. Harvest was planned for 60 days after planting but was delayed due to slower than normal growing conditions with all plots harvested once the oats reached the heading stage. Plots were harvested with a small plot forage harvester with sub-samples pulled to dry and submit to the lab for forage quality analysis.

36 | Ohio State Digital Ag Program

Figure 1. Summer annual species were harvested on a plot harvester.

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

SUMMARY

OBSERVATIONS This trial suffered from wet soil conditions through much of the growing season along with below average growing degree days (GDD). All nitrogen rates on BMR Sorghum and Sorghum Sudan had a light green color throughout the growing season instead of the normal dark green color. Plots were harvested just before a frost in muddy conditions which slightly increased ash content in some plots.

PROJECT CONTACT Jason Hartschuh (hartschuh.11@osu.edu) Allen Gahler (gahler.2@osu.edu)

RESULTS

•

Both species and nitrogen rate had a significant effect on yield and forage quality.

•

On all species but Red Clover, as nitrogen rates increased so did forage yield, but in all the grass species there was no statistical significance between the 100 and 150 lbs/ac nitrogen rates.

•

All grass species had significantly greater Crude Protein and Total Digestible Nutrients (TDN) when 150 pounds of nitrogen was applied.

•

Under more normal growing conditions we would have expected the BMR Sorghum and the Sorghum Sudan to have out yielded the oats.

•

Each year is different and producers must decide which species will best fit there operations needs.

Treatments

Yield lbs/ac 15% moisture

Crude Protein %

NDF

TDN

Oats 0 lb/ac Nitrogen

0.4 ef

7.9 fg

55.7 f

56.4 cd

Oats 50 lbs/ac Nitrogen

0.7 cde

6.8 g

57.2 f

59.7 bc

Oats 100 lbs/ac Nitrogen

1.2 ab

8.7 efg

56.2 f

59.8 b

Oats 150 lbs/ac Nitrogen

1.3 a

14.6 b

57.2 f

61.6 ab

BMR Sorghum 0 lb/ac Nitrogen

0.3 f

10.6 cde

73.6 a

41.6 hi

BMR Sorghum 50 lbs/ac Nitrogen

0.4 ef

10.2 cde

70.8 ab

44.6 gh

BMR Sorghum 100 lbs/ac Nitrogen

0.5 def

12.0 c

66.2 cd

48.1 ef

BMR Sorghum 150 lbs/ac Nitrogen

0.7 de

15.1 b

62.0 e

53.8 d

Sorghum Sudan 0 lb/ac Nitrogen

0.3 ef

9.2 def

73.4 a

39.8 i

Sorghum Sudan 50 lbs/ac Nitrogen

0.4 ef

9.9 cdef

68.9 bc

46.5 fg

Sorghum Sudan 100 lbs/ac Nitrogen

0.8 bcd

8.3 efg

68.4 bc

50.0 e

Sorghum Sudan 150 lbs/ac Nitrogen

1.1 abc

11.1 cd

64.4 de

53.4 d

Red Clover 0 lb/ac

0.3 ef

25.0 a

36.3 g

63.4 a

Red Clover 50 lbs/ac

0.3 ef

25.4 a

37.6 g

63.4 a

Red Clover 100 lbs/ac

0.3 ef

24.1 a

38.1 g

63.3 a

Red Clover 150 lbs/ac

0.4 ef

23.8 a

38.7 g

63.1 a

LSD: 0.4

LSD: 2.5

LSD: 3.9

LSD: 3.2

CV: 55.5%

CV: 13.9%

CV: 5.0%

CV: 5.0%

Treatment Means with the same letter are not significantly different according to Fisher’s Protected Least Significant Differences (LSD) test at alpha = 0.1.

2024 eBarns Report | 37

Winter Annual Rye Nitrogen Rates OBJECTIVE

NC Ag Research Station

Use spring NDVI readings to assist making spring nitrogen application management decisions and determine if fall applied nitrogen increases density and protein in cereal rye.

STUDY INFORMATION

OARDC Sandusky County

WEATHER INFORMATION

Planting Date 10/06/2023 Harvest Date 05/02/2024 Variety Cereal Rye VNS Population 2 bushels per acre Acres 1 Treatments 16 Reps 4 Treatment Width 10 ft.

Tillage Minimum Till Management No herbicides, insecticides, or fungicides applied Previous Crop Soybean Row Spacing 7.5 in.

STUDY DESIGN

Growing Season Weather Summary OCT

NOV-FEB

MAR

APR

MAY

Total

Precip (in.)

3.74

6.39

2.15

4.79

4.01

21.08

Cumulative GDDs

205.1

247.2

291.8 450.6 943.1 943.1

This trial was a randomized complete block split-plot design with four nitrogen rates in the fall (0, 30, 60, and 90 lbs/ac) and four nitrogen rates in the spring (25, 50, 75, and 100 lbs/ac) over the fall rates in cereal rye.

Rye was planted in October and harvested in May. NDVI and Canopeo readings were taken in late November before fall dormancy and in the spring after greenup to determine the greenness and density of green matter.

OBSERVATIONS •

The 0 nitrogen fall treatment was thin and yellow compared to the other treatments in the spring.

•

90 pounds of spring nitrogen improved the 0-fall nitrogen color, but plots were still thin.

•

The highest nitrogen plots had wider leaves than the low nitrogen plots.

38 | Ohio State Digital Ag Program

Figure 1. View of plot layout.

Forages

Manure Nutrients

Cattle

RESULTS

View the treatments to the right.

SUMMARY

Small Ruminant

Equine

Swine

Poultry

Treatments (lbs/ac N)

Yield (tons/ac)

Crude Protein %

NDF

TDN

Fall 0, Spring 25

5.07 g

8.48 e

66.3 a

64.79 ab

Fall 0, Spring 50

6.15 efg

10.32 de

63.0 abc

63.57 abc

Fall 0, Spring 75

8.72 abc

12.56 abc

64.5 abc

64.98 ab

•

At least 30 pounds of fall nitrogen was needed to maximize the yield.

•

Spring nitrogen is the primary driver of Crude Protein (CP).

CP was significantly affected by each 25 pound increase in spring nitrogen regardless of fall nitrogen rate.

Fall 0, Spring 100

7.43 cdef

12.43 abc

65.0 ab

62.01 abc

Fall 30, Spring 25

7.02 def

9.48 e

61.2 bc

64.44 ab

Fall 30, Spring 50

7.88 cd

10.01 de

64.4 abc

65.67 a

Total Digestible Nutrients (TDN) of cereal rye was negatively affected by increased nitrogen rates and was not affected at all by fall nitrogen treatments.

Fall 30, Spring 75

8.64 abc

12.83 ab

62.4 abc

64.83 ab

Fall 30, Spring 100

9.54 a

12.90 ab

60.8 c

59.48 c

Fall 60, Spring 25

7.51 cde

10.01 de

62.0 bc

63.86 ab

Fall 60, Spring 50

8.10 bcd

10.56 de

63.1 abc

63.44 abc

Fall 60, Spring 75

9.41 a

12.00 bcd

62.2 bc

62.37 abc

Fall 60, Spring 100

9.42 a

13.54 a

62.4 abc

62.12 abc

Fall 90, Spring 25

9.28 ab

11.10 cd

60.8 c

63.82 ab

Fall 90, Spring 50

9.38 a

13.51 ab

60.3 c

62.42 abc

Fall 90, Spring 75

9.48 a

12.28 abcd

60.2 c

60.69 abc

Fall 90, Spring 100

9.68 a

13.56 a

62.1 bc

60.44 bc

LSD: 1.1

LSD: 1.4

LSD: 3.7

LSD: 3.7

CV: 11.2%

CV: 10.4%

CV: 5%

CV: 5%

•

•

NDVI had a correlation with all the spring applied nitrogen treatments - Canopeo did not. NDVI is a better tool for measuring ground cover and potential nitrogen available in spring for the crop, compared to Canopeo.

Figure 2. Plot harvester in action.

Treatment Means with the same letter are not significantly different according to Fisher’s Protected Least Significant Differences (LSD) test at alpha = 0.1.

TOOLS OF THE TRADE

Normalized Difference Vegetation Index (NDVI) A handheld sensor that is walked across each plot to estimate the percent of live green vegetation in an area. The NDVI scale is between 0 and 1, with values closer to 1 indicating a higher percent of green vegetation.

PROJECT CONTACT Jason Hartschuh (hartschuh.11@osu.edu) Kendra Stahl (stahl.221@osu.edu)

2024 eBarns Report | 39

Manure Sidedress OBJECTIVE

eFields Collaborating Farm

Evaluate the potential yield difference between swine manure and commercial fertilizer applied at sidedress.

Planting Date 05/18/2023 Harvest Date 11/02/2023 Variety Becks 5413Q Population 31,100 sds/ac Acres 36 Treatments 2

Williams County

WEATHER INFORMATION MAX. AND MIN. TEMPERATURE (°F)

STUDY INFORMATION

OSU Extension

Treatment Width 30 ft.

Tillage No-Till Management Fertilizer Previous Crop Soybeans Row Spacing 30 in.

Soil Type Del Rey silty clay loam, 13% Fulton silty clay loam, 37% Latty silty clay loam, 50%

DAILY PRECIPITATION (IN)

Reps 3

100 90 80 70 60 50 40 30 20 10 0

3

2

1

0

Growing Season Weather Summary APR

MAY

JUN

JUL

AUG

SEP

Total

Precip (in.)

2.14

1.04

1.74

4.83

2.48

1.12

13.35

Cumulative GDDs

182

551

1104

1819

2429

2902

2902

STUDY DESIGN The study was a randomized complete block design. There were two treatments, swine manure and commercial fertilizer (28%). This study had 3 replications.

Figure 1. Swine manure was applied to the field on 6/9/2023.

40 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

OBSERVATIONS

SUMMARY

This field had a dry period in May, June and July during the vegetative growth of the corn. Harvest was later than usual as fall dry-down was slower than usual.

Disease pressure and insect pressure were minor.

•

As with the previous year, corn sidedressed with manure had a significantly greater yield than corn sidedressed with commercial fertilizer.

•

There was a significant difference in yield.

There was a 48 bu/ac advantage in the manure treatment.

RESULTS Treatments

Yield (bu/ac)

Manure

243 a

Control

195 b

Treatment Means with the same letter are not significantly different according to Fisher’s Protected Least Significant Differences (LSD) test at alpha = 0.1.

LSD: 7 CV: 1.9%

PROJECT CONTACT Amber Emmons (emmons.118@osu.edu)

2024 eBarns Report | 41

2024 Tick Update Introduction Ticks and the diseases that they vector to livestock, companion animals, and humans have become an increasingly larger public health risk and a huge impact on our cattle industry.

Top 3 Ticks for Medical Concerns in Humans American Dog Ticks prefer a more open habitat including pasture, meadows, and lawns. This tick is a prominent vector of Rocky Mountain Spotted Fever and Tularemia.

Black Legged or Deer Ticks prefer to live in a wooded habitat.

This tick is the primary vector for Lyme disease, plus it can also vector Babesia and Anaplasmosis.

Lone Star Ticks are aggressive feeders and prefer a wooded habitat.

This tick is the reported causative agent for the Alpha-gal (Mammalian Muscle Allergy reaction) where the person who is bitten can become allergic to meat including beef, pork, and venison.

American Dog Tick (Dermacentor variabilis)

Black Legged or Deer Tick (Ixodes scapularis)

Lone Star Tick (Amblyomma americanum)

Top Tick for Medical Concerns in Livestock

Longhorned Ticks are an invasive tick that was identified in Ohio in 2020.

This tick is unique in that it reproduces via parthenogenesis, meaning the female does not need a male to breed, allowing it to produce extreme numbers of ticks on its host or in a pasture.

Longhorned Tick (Haemaphysalis longicornis)

42 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

Tips for Managing Longhorned Ticks in Pastures and on Cattle •

Frequently scout your animals as this tick can reproduce in large numbers.

•

While we have had detection as early as April, this tick is known to prefer heat and tall grass. The largest numbers of ticks on cattle in Ohio have been detected in July.

•

This tick has been known to vector Theileria (protozoal blood parasite) to cattle that can cause fever, inappetence, open cows, jaundice, and mortality.

•

Work with your veterinarian if you think you have longhorned ticks on your animals. Guidance for extra-label application of tick control needs to come from a veterinarian.

•

Intensive grazing management with rotation through paddocks to let animals maintain the pasture will be an important integrated pest management strategy.

•

Products labelled for pasture application to control ticks have shown to be effective, but they need to contact the tick to work. Application on top of tall grass or residue may not contact the tick directly and therefore may not be effective for control.

Longhorned Ticks in Ohio Fact Sheet https://ohioline.osu.edu/factsheet/vme-1035

PROJECT CONTACT Timothy S. McDermott, DVM Extension Educator, Franklin County mcdermott.15@osu.edu (614)-292-7916 *Map reflects confirmed data prior to June 1, 2024.

Some suspected LH Ticks and theileria locations are pending confirmation.

Future updates will contain an updated map.

Note: This tick outreach is supported by a grant from USDA NIFA 20217000635562

2024 eBarns Report | 43

Beef Breeding Program Impact Survey OBJECTIVE

eBarns Collaborating Farms

Gaining a greater understanding of how producers manage beef cattle operations through a survey regarding reproductive data management.

STUDY INFORMATION Time Surveyed Spring / Summer 2024 Species Beef Topic Surveyed Reproduction County Distributing Delaware County Survey Type of Farmers/Herdsman Respondents

OSU Extension Statewide

STUDY DESIGN A survey was distributed that contained questions designed to provide insights into the current practices of beef cattle reproductive data management. This survey aims to understand how producers manage their beef cattle operations, particularly focusing on the types of reproductive records kept and the methods used for record keeping. The goal is to gather valuable information that will aid in maintaining high-quality livestock through effective breeding program management.

States Surveyed Ohio 57 (83%) Indiana 3 Kentucky 2 States with 1 Arkansas, Response each Oklahoma, Pennsylvania, Tennessee, West Virginia, Wisconsin

50% of the survey participants have a commercial production enterprise

Figure 1. Responses to: Which best describes your cow-calf enterprise?

Total 68

Breeding Age Cattle Surveyed Mature Cows 3,068 Replacement 617 Heifers Bulls 147 Total Animals 3,832 Represented

44 | Ohio State Digital Ag Program

SUMMARY Results emphasize the diversity in record-keeping and breeding techniques used to maintain highquality livestock.

This survey aims to aid producers in refining breeding strategies for enhanced operational effectiveness.

See more about Delaware County's eBarns studies at go.osu.edu/24ebarnsvideos

Forages

Manure Nutrients

Beef

Small Ruminant

RESULTS What is the biggest benefit of your preferred breeding method?

17.65% Genetics and Genetic Improvement 14.71% Time and Labor Savings

10.29% Variety and Flexibility in Sire Selection

Equine

Swine

Poultry

Sire Selection: Ranking the most importanct traits considered when making sire selection decisions: Ranked as #1 Importance Birth Weight (25.42%) Reproductive Performance / Fertility (25.42%) Conformation/Structural Soundness (23.72%) Ranked as #2 Importance Reproductive performance / Fertility (32.20%) Conformation/Structural Soundness (22.03%) Growth Rate (11.86%) Ranked as #3 Importance Maternal Ability (23.73%) Conformation/Structural Soundness (15.25%)

Figure 2. Responses to: What is your preferred breeding methods?

•

46.15% of those who preferred NS answered that they mated 100% using this method.

•

Of those who preferred AI, 36.12% answered that they mated 80-100% using this method. (13.89% said 80%, 8.34% said 90%, 13.89% said 100%).

•

23.08% of those who preferred ET answered that they only mated 20% using this method, A smaller percentage of 15.38% answered that they mated 70% using this method.

Perceived barriers for not using AI:

#1 = Time (15%) #2 = Facilities (7%) #3 = Cost (2%)

TOOLS OF THE TRADE Social Media Distribution of this survey went through digital newsletters and on social media.

Beef Team: u.osu.edu/beefteam facebook.com/delawarecountyag

Figure 3. Responses to: Who breeds your cows?

Answers for "Other" • 60% - Bull • 30% - Family • 20% - Natural Service

Answers for "Service" • 37.5% said ABS • 25% listed individuals • 6.25% listed Specific Companies

PROJECT CONTACT Kate Hornyak (hornyak.26@osu.edu) Jacci Smith (smith.11005@osu.edu) Rob Leeds (leeds.2@osu.edu)

2024 eBarns Report | 45

Mastitis’ Effects on Milk Composition OBJECTIVE

CFAES Wooster

Evaluating biochemical changes in blood and milk to determine how subclinical mastitis affects local mammary tissue function and metabolism.

OARDC Wayne County

STUDY INFORMATION Start Date 05/01/2022 End Date 03/01/2023 Species Dairy Cattle Start Point Primiparous End Point Primiparous Treatments 2 Reps 4

Figure 1. Study timeline. Red lines denote milking time points (every 8 hours).

Asterisk denotes blood sampling time point (every 2 h. 40 min., beginning 1 h. 20 min. after milking and intramammary infusions.

Experimental Head Unit Breed, Genetics Holstein Reproduction Heifers Stage Feed Access Hand Fed Diet Standard Krauss Dairy Diet (OSU Location) IACUC # 2022A00000020

STUDY DESIGN

Figure 2. Graphic of study design

Part 1 of Study: Four primiparous cows (in first transition period, both pre and postpartum) were milked 3 times a day. Each cow had both quarters of either the right or left side of her udder infused with oyster glycogen (an inducer of neutrophil recruitment), and the opposite quarters were infused with saline (a control). Milk yields were recorded for each udder half. Milk samples were taken at each milking and evaluated by the Dairy Herd Improvement Association (DHIA) for somatic cell count (SCC), protein, lactose, and fat for 3 days after infusions.

Part 2 of Study: Part 1 did not result in a milk yield response, so in Part 2 the experimental design was changed to try to elicit subclinical mastitis that would also result in a decrease in milk yield. Part 2 utilized 4 mid-lactation primiparous Holstein cows. One udder half of each cow was challenged with killed, non-viable, Staphylococcus aureus, and the opposite quarters were infused with saline. Milk and blood measures were taken for 2 days postinfusions.

46 | Ohio State Digital Ag Program

Figure 3. Collection of mammary tissue for further examination.

Forages

Manure Nutrients

Dairy

Small Ruminant

Equine

Swine

OBSERVATIONS (PART 1)

OBSERVATIONS (PART 2)

• Differences in milk components: large increase in milk somatic cell count, marginal alterations in lactose and protein percentages.

• Significant increase in SCC.

• No significant milk yield response.

Poultry

• No significant milk yield response.

• Pronounced changes in milk composition.

• Milk protein concentrations increased in Staph. aureus challenged udder halves while lactose concentrations reduced.

RESULTS

SUMMARY The fact that a large increase in SCC did not result in a decrease in milk yield was a surprising result. A change in tissue metabolism may be due to utilization of nutrients by the immune cells recruited to the mammary gland during mastitis.

In Part 2 of the study there was a notable increased concentration of milk lactate, which is a byproduct of anaerobic metabolism. This indicates that mammary tissue metabolism and milk synthesis pathways are altered during disease. Future research is needed to further elucidate what is happening during subclinical mastitis.

Figure 4. Data point visual: Saline (SAL, solid blue line, n = 4), formalin-fixed Staphylococcus aureus (FX-STAPH, dashed red line, n = 4).

Mean SCS (A), Energy corrected milk yields (ECMY) (F) Lactose Content (B), of whole milk from udder halves receiving designated intramammary infusions of Fat Content (C), Protein Content (D), SAL or FX-STAPH at time point 0.

Milk Yields (E), Error bars denotes SEM, asterik = P ≤ 0.05, † = P = 0.10 for SAL vs. FX-STAPH comparisons within time point.

PROJECT CONTACT

Dr. Ben Enger, Associate Professor (enger.5@osu.edu) Kellie Enger, Research Associate (enger.6@osu.edu) Cori Gammariello

2024 eBarns Report | 47

Dairy Cattle Behavior During Solar Eclipse OBJECTIVE

CFAES Wooster

Evaluating behavior and milk production of dairy cattle during the solar eclipse on April 8, 2024.

STUDY INFORMATION Start Date 04/05/2024 End Date 04/11/2024 Species Dairy Cattle Experimental Unit Head Total Units 165

OSU Extension Wayne County

BACKGROUND It is understood that animals do not have the ability to think, but they are able to learn. Dairy cattle quickly habituate to a daily routine of feed delivery and milking timing. The processes by which animals learn is still not understood, but is affected by their interactions with humans and the environment. On April 8, 2024 a rare solar eclipse occurred, with Wooster, OH in the path of the darkness totality at approximately 3:14pm.

Breed, Genetics Holstein

STUDY DESIGN All production cattle at The Ohio State University CFAES Krauss Dairy are fitted with a SRS collar.

The collar system at Krauss Dairy records in 2-hour increments, on each even hour (2:00am, 4:00am, 6:00am, etc.), 24 hours/day. It also records milk production totals (milking twice daily at 4:00am and 4:00pm).

A report was generated for all cattle at the dairy to include activity and milk yield from April 4, 2024 to April 11, 2024. All cattle with complete records from April 5 - 11 (N=165) were used in the analysis. Data for total daily activity (minutes/day), total activity between 2:00pm and 4:00pm, and second shift milk yields (4:00pm) were used to create time blocks: • • •

Pre-Eclipse average (April 5 - 7) Day of Eclipse (April 8) Post-Eclipse average (April 9 - 11)

A paired sample t-test analysis (JMP Pro) was used to determine if there was a difference in activity level and production between these timing blocks.

48 | Ohio State Digital Ag Program

Figure 1. Dairy cattle feeding at CFAES Wooster.

OBSERVATIONS •

Slight variations in herd averages for: total daily activity, activity between 2 - 4pm, and second shift milk yield.

•

No significant activity differences were found when comparing (Pre-Eclipse and Post-Eclipse activity levels to the activity level on April 8th (Figure 3).

•

There was a significant difference in the second shift (4:00pm) milk yield for all comparisons as the averages gradually increased over the total days observed (Figure 2).

Forages

Manure Nutrients

Dairy

Small Ruminant

Equine

Swine

Poultry

RESULTS SUMMARY •

•

•

The dairy’s average per cow production increased each day from April 7 - 10. This increase can not be directly attributed to any environmental impact related to the decrease in sunlight associated with the April 8th solar eclipse.

The short period of decreased sunlight from the April 8th, 2024 had no observable impact on the activity level or milk production of dairy cattle at the OSU CFAES Krauss Dairy.

The findings of this observation agree with another published study (on grazing dairy cattle) that a solar eclipse does not significantly alter dairy cattle behavior.

Date

Total Daily Activity (minutes/day)

Activity from 2 - 4pm (minutes/day)

Milk Yield, second shift at 4:00pm (lbs.)

April 5

477.79

47.67

44.0

April 6

486.40

48.79

42.9

April 7

482.08

48.87

42.5

April 8

485.99

49.48

44.1

April 9

488.98

51.37

44.5

April 10

472.50

45.88

45.9

April 11

476.89

50.96

44.9

Pre-Eclipse Avg. (April 5 - 7)

482.09

48.44

43.1

Post-Eclipse Avg. (April 9 - 11)

479.46

49.41

45.2

Figure 2. Table displaying data collected on Total Activity, Activity between 2:00pm and 4:00pm, and the second shift milk yield.

Time Block

Total Activity

Activity from 2 - 4pm

Milk Yield

Pre-Eclipse VS. Day of Eclipse

0.1863

0.0780

0.0026*

Post-Eclipse VS. Day of Eclipse

0.0810

0.9135

0.0206*

Pre-Eclipse VS. Post-Eclipse

0.4876

0.1010

0.0001*

Figure 3. Probabilities from paired t-test comparisons of total daily activity, 2:00pm - 4:00pm activity, and milk yield by time block.

Asterik (*) signifies a statistical difference between averages. Alpha (∞) = 0.05

TOOLS OF THE TRADE SRS Collar System The collars record an individual animal’s activity in 2-hour increments (total minutes active in that time).

PROJECT CONTACT John Yost Extension Educator, Wayne County yost.77@osu.edu 330-264-8722

2024 eBarns Report | 49

Circadian Temperature or Activity Detection OBJECTIVE Evaluating if a significant circadian temperature or activity rhythm can be detected with indwelling rumen boluses in dairy calves and if that rhythm changes by season.

eBarns Collaborating Farm OSU Extension Crawford County

STUDY INFORMATION Start Date 10/01/2021 End Date 10/31/2023 Species Dairy Start Point 3 weeks of age End Point 13 weeks of age Treatments 9 Reps 189 Experimental Head Unit Breed, Genetics Holstein Sex Females Feeding System Ad Libitum, Self Feeder IACUC # 2020A00000111

Figure 1. Holstein calf lying down.

STUDY DESIGN For this study, each calf was treated as an individual study unit. The rhythm was analyzed for calves that were 3, 6, and 12 weeks of age to determine if rhythms change as the calf ages.

Season was also analyzed as a factor to determine if winter and summer have different rhythm patterns since during these seasons calves experience either heat stress or cold stress.

Figure 2. Average temperature (blue line) and activity (orange line) of calves at 3 weeks of age, over a weeks time.

50 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Small Ruminant

Dairy

Equine

Swine

Poultry

OBSERVATIONS

SUMMARY

•

Calves are most active at the time of day when they are fed.

•

Sick calves were visually slower and less active than healthy calves.

Season had a significant affect on both calf temperature and activity rhythms. Spring and fall had similar rhythm, but summer and winter showed increased variation with less calf activity between meals.

•

Calf temperature decreased any time the calf's activity increased.

Age of the calf was also significant. The 12 week old calves activity had increased variation between calves.

The drop in calf temperature during times of increased activity could lead to low grade fevers being missed by manual rectal temperature monitoring.

RESULTS Timing

8-Hour (Temp)

12-Hour (Temp)

Winter, 3 weeks

24-Hour (Temp)

Timing

8-Hour (Activity)

12-Hour (Activity)

24-Hour (Activity)

0.64

Winter, 3 weeks

0.19

0.12

0.32

0.21

0.51

Winter, 6 weeks

0.19

0.25

0.26

0.13

0.32

Winter, 12 weeks

0.61

0.27

Summer, 3 weeks

Summer, 6 weeks

0.59

Summer, 6 weeks

Summer, 12 weeks

0.28

Summer, 12 weeks

Spring / Fall, 3 weeks

0.57

Spring / Fall, 3 weeks

0.14

0.4

0.23

Spring / Fall, 6 weeks

0.78

Spring / Fall, 6 weeks

0.13

0.4

0.22

0.37

Spring / Fall, 12 weeks

0.18

0.21

0.29

Winter, 6 weeks Winter, 12 weeks

0.17

Summer, 3 weeks

Spring / Fall, 12 weeks

0.16

0.20

Only Significant rhythm powers are shown Figure 3. Results table for temperature rhythm power

0.18 0.1

0.39

0.14

0.4

0.31 0.18

Only significant rhythm powers are shown Figure 4. Results table for activity rhythm power

PROJECT CONTACT

TOOLS OF THE TRADE ST Farmfit Rumen Bolus (Fig 5.) and Management app (Fig. 6)

Jason Hartschuh (hartschuh.11@osu.edu)

Used to monitor dairy calf temperature and activity for illness detection.

Figure 5.

Figure 6.

2024 eBarns Report | 51

Effect of Dietary Fiber Management OBJECTIVE Evaluate the effects of feeding different types and amount of fiber during gestation on both ewes and lambs.

Small Ruminant Research Center CFAES Wooster Wayne County

STUDY INFORMATION Start Date January 2020 End Date March 2020 Species Sheep Start Point Multiparous End Point Multiparous Treatments 3 Reps 3 Experimental Pen Unit Breed, Genetics Dorset x Hampshire Crossbred Sheep Sex 87 Mature Ewes Feeding System Self Feeder IACUC # 2019A00000001

Figure 1. View of ewes using a fence line feeder during this study.

STUDY DESIGN

Two separate groups of non-pregnant ewes (91) were put on a fescue-based pasture with rams for breeding. Ewes were exposed to rams for 2 complete estrus cycles (34 days). When environmenatal conditions no longer allowed for grazing, ewes were moved to indoor housing and fed a diet containing concentrate and soybean hulls (1:3 ratio). Ewes were then blocked by body weight into 3 blocks and randomly allotted to a pen (10 ewes/pen). Diet fiber treatments were as follows: soybean hulls (SH), limit fed hay (LH), and ad libitum hay access (CONT). Diets were offered to 9 pens (3 pens/treatment, 9-10 ewes/pen). On day 20 of the feeding period, ewes were pregnancy checked. Four ewes were not confirmed pregnant and were removed from the experiment. Dietary treatments for hay were chosen to reflect winterfeeding systems commonly used in the midwestern United States. For lambing, ewes moved to lambing pens for 48 hours, then to maternity pens following birth. During lambing, and until ewes were moved back to pasture (day 112), ewes were fed the same diet and amount as when they were in the group pen setting.

Data Collected: • • • • •

Daily: Concentrate/roughage offerings and refusals (measuring dry matter intake (DMI)), Total pen feed refusal for SH and LH fed ewes Weekly: Hay refusal for CONT fed ewes Every 2 weeks: feed samples (for dry matter (DM) content and nutrient composition) Ewe body weight (BW): at the beginining of the experiment (d -28), mid-gestation (d 34), late-gestation (d 76), and 2 days after lambing.

Lamb BW: at lambing and at weaning (60 days of age)

52 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

OBSERVATIONS

SUMMARY

•

Ewes consuming SH had to be limited in their intake of SH as these ewes demonstrated an eating behavior that drove them to eat more of what was really needed, thus pushing them to gain more body weight gain.

•

The SH wes over ate on the SH offered which led to additional complications including excessive hoof growth, leading to foundering.

•

The average day of lambing was day 103 ± 5 with respect to the initiation of the experiment on d -51 (starting/finishing dates of the experiment were set by the ability to return the sheep back to pasture).

Under the conditions of this experiment, SH ewes demonstrated an increase in body weight, and lambs of SH ewes were born heavier, but had a slower growth until weaning. Management of the hay (ad libitum or restricted) did not affect the amount of hay consumed by the ewe.

RESULTS

Ewe Data Collected

Ewe Data Results: (Figure 2, right)

DMI (kg), day 28

2.5

DMI (kg), day 42

Effect of feeding unrestricted access to hay (CONT) and a fixed amount of SH or LH during gestation on ewe body weight before and during gestation as well as at lambing.

Lamb Data Results: (Figure 3, right)

CONT Ewes LH Ewes

SH Ewes

SEM

P-value

2.2

2.6

0.19

0.13

2.1

2.2

3

0.23

0.07

DMI (kg), day 62

2.1a

2.1a

3.0b

0.21

0.02

Initial BW (kg)

83.6

84.2

83.9

4.44

0.91

Mid-gestation BW1 (kg)

102.3ab

97.0a

105.8b

4.4

< 0.01

Late-gestation BW1 (kg)

97.5a

102.2b

101.8b

2

0.01

Lambing BW2 (kg)

88.3

88.9

91.9

1.54

0.21

SH Ewes

SEM

P-value

Lamb Data Collected CONT Ewes LH Ewes

Effect of feeding CONT Birth BW3 (kg) and a fixed amount of SH or LH on lamb Weaning BW3 (kg) body weight at birth and weaning.

4.9a

5.1ab

5.5b

0.24

0.02

31.9b

30.2b

27.5a

0.77

< 0.01

*Treatment Means with the same letter are not significantly different according to Fisher’s Protected Least Significant Differences (LSD) test at alpha = 0.1. SEM = Standard Error of the Mean.

TOOLS OF THE TRADE Soybean Hulls A by-product of soy or vegatable oil production.

Once processed, soybeans can produce oil, meal, fiberous hulls. The hulls (outer coating of the seed) mainly consists of fiber that has no current use in human consumption or fuel production.

However, this fiber source can be useful in ruminant production systems.

PROJECT CONTACT Dr. Braden J. Campbell Assistant Professor, State Small Ruminant Extension Specialist (campbell.1279@osu.edu) Dr. Ale Relling, Associate Professor (relling.1@osu.edu)

2024 eBarns Report | 53

Effect of Overprocessing Distiller Grains OBJECTIVE

Small Ruminant Research Center

Investigate how different heat processing methods of Dried Distillers Grain (DDG) affects the growth of finishing lambs.

CFAES Wooster Wayne County

STUDY INFORMATION Start Date 06/16/2023 End Date 07/28/2023 Species Sheep Start Point ~ 100 days of age End Point ~ 150 days of age Treatments 2 Reps 6 Experimental Pen Unit Total Units 34 Breed, Genetics Hampshire × Dorset × Ile de France × South African Meat Merino (SAMM) crossbred lambs

Parameter

Diet A

Diet B

Neutral Detergent Fiber (NDF)

27.17

27.38

Acid Detergent Fiber (ADF)

16.59

15.39

Crude Protein (CP)

14.19

14.68

Ether Extract (EE)

2.27

2.35

Ash

5.10

5.34

Figure 1. Nutrient composition of commercial (Diet A) and heat processed* (Diet B) dried distillers grain (DDG) fed to finishing lambs, reported as a percent (%) on a dry matter basis.

Sex 18 Wethers, 16 Ewes Feeding System Self Feeder Space 66 ft² IACUC # 2023A00000070

STUDY DESIGN

Thirty-four cross-bred lambs were weighed and blocked by body weight and sex, then assigned to 1 Figure 2. Visual comparison of DDG sample. of 12 pens. Then, each pen was randomly assigned Diet A (left) is a commercial DDG source 1 of 2 treatments (Diet A or Diet B). Lambs were received from the mill (no additional heat offered water ad libitum and offered feed daily using processing). Diet B (right) is the same slick bunk management. The bunk feeder was commercial DDG, but was further processed considered slick when there was no feed remaining in using heat*. the bunk 24 hours post feeding. When this occurred for 2 consecutive days, the amount of feed offered increased by 0.75 lbs./pen. If a pen left feed for 2 consecutive days, the amount of feed offered was decreased by 0.5 lbs./pen. Prior to beginning the experiment, all lambs were fed diet A (CON) for 10 days during an adaptation period. Lamb body weight (BW) was measured at the start of the experiment (day 1), and every 14 days throughout the duration of the experiment (42 days). Dry matter intake (DMI) was recorded daily for each pen prior to feeding by weighing the previous day’s feed refusals.

54 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Small Ruminant

Cattle

OBSERVATIONS •

There were no differences observed in lamb body weight or Average Daily Gain (ADG).

•

There was no difference in diet nutritional composition (NDF, ADF, CP, EE, or Ash).

SUMMARY Completion of this experiment revealed that processing DDG at 302°F for 70 minutes does not affect lamb growth, ADG, DMI, or Gain to Feed Ratio (G:F).

Further research should be conducted to focus on processing DDG at greater temperatures for longer periods of time.

Equine

Swine

Poultry

Feed Ingredient

Percent Inclusion Rate in the Diet

Ground Corn

48.44

Soybean Hulls

28.00

Dried Distillers Grain

20.00

Minerals/salt**

2.06

Animal - vegetable fat blend

1.50

Figure 3. Diet composition and ingredient inclusion rates for both Diet A and heat processed* Diet B. **48.50% limestone, 24.30% salt, 19.40% ammonium chloride, 4.40% Vitavet selenium, 2.40% Vitamin E, 0.49% Vitamin A and D

RESULTS Parameters

Control

Processed*

SEM

P-value¹

Body Weight (BW) (kg)

51.3

49.8

0.68

0.14

Average Daily Gain (ADG) (kg)

0.35

0.32

0.016

0.13

Dry Matter Intake (DMI) (kg)

1.81

1.82

0.042

0.84

Grain to Feed Ratio (G:F)

0.2

0.2

0

0.15

Figure 4. Data collected and calculated on finishing lambs consuming a diet with 20% DDG that differ through heat processing*. SEM = Standard Error of the Mean. ¹All variables were analyzed as repeated measurements considering the fixed effects of treatment, day, and their interaction. Because of the lack of observed differences in the time by treatment interaction (P ≥ 0.36) only the main effect of treatment are presented. * Dried Distillers Grain (DDG) heat processing: 40% moisture was added to the DDG and heated at 150°C for 70 minutes. Then, Diet B was placed in a second oven at 56°C for 2 days to allow for humidity evaporation.

PROJECT CONTACT TOOLS OF THE TRADE Drying Oven A commerical drying oven was used to heat process the DDG further to elicit the Milard reaction. The Milard reaction is noted by the color change in the two examples of DDG here.

The darker sample (Diet B) was heat processed.

(See Fig. 2 for an example of this color change)

Dr. Braden J. Campbell Assistant Professor, State Small Ruminant Extension Specialist (campbell.1279@osu.edu) Dr. Ale Relling, Associate Professor (relling.1@osu.edu) Brayden Thompson, Animal Sciences Undergraduate, Summer Research Intern

2024 eBarns Report | 55

Feeding Different Distiller Concentrations OBJECTIVE

Eastern Ag Research Station

Investigating the effect of feeding increasing concentrations of Dried Distillers Grains (DDG) on finishing lambs.

OSU Extension Noble County

STUDY INFORMATION Start Date June 2023 End Date July 2023 Species Sheep Start Point ~ 120 days of age End Point ~ 180 days of age Treatments 3 Reps 5 Experimental Pen Unit Breed, Genetics Dorset Sex 75 Wethers Feeding System Self Feeder Space 118 ft² IACUC # 2023A00000070

Figure 1. Feedlot lambs at the Eastern Ag Research Station in Caldwell, OH.

STUDY DESIGN

During the summer of 2023, 75 wethers were identified for this experiment, with each lamb having intial body weights of 95 lbs. and at approximately 120 days of age. They were weighed and blocked by body weight (BW), then were assigned to 1 of 15 pens. Each pen was randomly assigned 1 of 3 treatments (diets containing different concentrations of Dried Distillers Grains (DDG) at 10, 20, or 30%).

Soybean meal and soybean hulls were used to replace the difference of the DDGs to ensure diets were isonitrogenous and isocaloric. Lambs were weighed every 28 days for a feeding period of 56 days. Feed samples were collected every other week and sent for nutrient analysis. The following was calculated at the conclusion of the experiment: Average Daily Gain (ADG), Dry Matter Intake (DMI), and Gain to Feed Ratio (G:F).

56 | Ohio State Digital Ag Program

Treatment

Details

10%

Diet consisted of 10% DDG

20%

Diet consisted of 20% DDG

30%

Diet consisted of 30% DDG

Figure 2. Treatment table for the different DDG concentrations.

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

OBSERVATIONS •

No differences in lamb performance were observed when evaluating lamb final BW, ADG, and G:F.

•

A decrease in lamb DMI was noted when inclusion rates of DDG increased in the diet.

SUMMARY Increasing the concentration of DDG in lamb finishing diets from 10% to 30% does not affect lamb growth, but linearly decreases feed intake. These results should be interpreted with caution as different sources of DDG may present differing results.

Further research is required to determine the impacts of this feeding strategy.

Figure 3. Feedlot lambs eating research diets from the feed bunk.

RESULTS Calculation

On a 10% Diet

On A 20% Diet

On a 30% Diet

SEM

Body Weight

116

113

114

3.8

Avgerage Daily Gain

0.372

0.344

0.332

0.028

Dry Matter Intake

3.70 a

3.22b

3.10 c

0.085

Grain to Feed Ratio

0.1

0.105

0.107

0.01

Figure 4. The effect of increasing the concentration of dried distillers grains (DDG) in the finishing diet of feedlot lambs on lamb body weight gain, average daily gain, dry matter intake, and gain to feed ratio.

SEM = Standard Error of the Mean.

TOOLS OF THE TRADE Dried Distillers Grain (DDG) Dried Distillers Grain is a popular by-product from ethanol production used in the livestock feed industry as it is a cost-effective feedstuff that is rich in crude protein and minerals.

PROJECT CONTACT Dr. Braden J. Campbell Assistant Professor, State Small Ruminant Extension Specialist (campbell.1279@osu.edu) Dr. Ale Relling, Associate Professor (relling.1@osu.edu)

2024 eBarns Report | 57

Pumpkin Seed Impact on Parasites in Sheep OBJECTIVE Evaluating the effect of pumpkin seeds as a supplement for sheep and as a natural anthelmintic (de-worming treatment), while reducing chemical anthelmintic use and fall pumpkin waste.

Small Ruminant Research Center CFAES Wooster Wayne County

STUDY INFORMATION Start Date 11/06/2023 End Date 12/11/2023 Species Sheep Start Point 8 months of age End Point 9 months of age Treatments 2 Reps 5 Experimental Unit Pen

Figure 1. Lamb eating pumpkin seeds

Genetics Commercial Breed Dorset, Suffolk, Hampshire, South African Meat Merino (SAMM), and Ile de France Crossbred lambs Sex 20 ewe lambs Space 66 ft² Feeding System Self Feeder IACUC # 2023A00000082

STUDY DESIGN

Figure 2. Data comparing “as Fed Intake“ for the 2 treatment groups

Pumpkin seeds (PS) were sourced from pumpkins grown at the Western Agricultural Research Center and Waterman Student Farm at The Ohio State University. Pumpkin seeds were collected and stored in 1 lb. increments and frozen for future use. Samples of PS were sent to a commerical laboratory for nutrient composition analysis.

Initially, 32 ewe lambs (grazing on pasture) were identified based upon parasite load using fecal egg counts (FEC). The top 20 greatest FEC sheep were used and sorted for this experiment. Lambs were randomized and allocated to 1 of 10 pens (5 pens/treatment; 2 lambs/pen). All lambs were fed a common diet, but differed in supplement or top dressing offered. Lambs in PS group received 1 lb. of PS/head(hd)/day whereas control lambs (CON) recieved 0.5 lbs. of whole shelled corn (WSC)/hd/day to ensure both groups of lambs were offered isoenergetic diets. Lambs were fed for 28 days.

Data collected every 7 days: lamb live body weight, fecal samples for FEC evalution to quantify parastic burden, blood samples for Packed Cell Volume (PCV) observation, and FAMACHA eye scores (FAM) Data collected daily (prior to feeding): feed refusals (amount of feed not eaten from the previous days feed offering)

58 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

OBSERVATIONS

Small Ruminant

Equine

Swine

Poultry

RESULTS

•

There was no difference in lamb FAM or FEC. However, lambs in the PS group had a greater PCV (38%) when compared to the CON lambs (36%) (see Figure 5).

•

There was also a decrease in lamb body weight for lambs offered PS when compared with lambs in the CON group (see Figure 4).

•

Although not quantified, it was observed that lambs in the PS treatment group excreated tapeworm segments (proglotids) whereas CON lambs did not.

SUMMARY

•

Although there was no change observed in Figure 4. Data representing the recorded average body weights lamb FEC or FAM, lamb PCV increased in every week of the study. the PS feeding group.

•

Lamb body weight decreased in the PS group, which was associated with the decrease in feed intake or refusal of PS in the PS lambs. The decrease in PS consumption may have negatively impacted the effectiveness of PS as a natural parasite control method.

•

The PS fed lambs were the only group that was observed to have shed tapeworm proglotids. Although not measured, this unique observation indicates the potential for some type of anthelmintic effect which warrents additional research.

Figure 5. Data representing the recorder average PCV from blood samples every week of the study.

Figure 3. Lamb with pumpkin on their nose

TOOLS OF THE TRADE McMaster Slide The McMaster’s Technique uses a special slide (McMaster Slide) with 2 chambers (6 columns/chamber). This slide is used to quantify the parasitic burden using a fecal sample that is collected directly from an animal.

PROJECT CONTACT Dr. Braden J. Campbell Assistant Professor, State Small Ruminant Extension Specialist (campbell.1279@osu.edu) Dr. Benjamin Wenner Melva Tacuri Vera Animal Sciences Undergraduate Honors Thesis Project

2024 eBarns Report | 59

Sheep LAI Summary OBJECTIVE Measuring the lambing rate in Ohio Seedstock Sheep Flocks with an extended history of using frozen semen for Laparoscopic Artificial Insemination.

eBarns Collaborating Farm OSU Extension Marion County

STUDY INFORMATION Start Date 09/01/2016 End Date 12/01/2023 Species Sheep Start Point Various End Point Various Estrous Yes Synchronization Breeding Method Artificial Insemination (AI) Experimental Unit Head Breed, Genetics Shropshire, Tunis, Hampshire Sex Ewes

Figure 1.Technician using a cradle device during a LAI.

Feeding System Self Feeder, Ad Libitum

STUDY DESIGN Laparoscopic artificial insemination (LAI) is an intrauterine method of insemination to bypass the unique anatomically tortuous cervix in sheep. Success of LAI programs depends on proper implementation of the estrus synchonization program, animal selection, and knowledge of the LAI process.

Data was collected through a questionnaire from seedstock flocks using LAI standarized protocol administered by experienced technicians. Source flock selection was based on multiple years of LAI experience.

60 | Ohio State Digital Ag Program

Figure 2. An up-close view of LAI by a technician.

Forages

Manure Nutrients

Cattle

OBSERVATIONS •

•

Our study participants felt a better understanding of how sperm traits alter fertility in the ewe after insemination are warrented.

Rams need to be screened for semen factors (concentration during storage, motility at insemination, number of sperm inseminated, morphology of sperm inseminated, viability of sperm inseminated, and acrosome intergrity) that are known to influence the success of LAI.

SUMMARY

Small Ruminant

Equine

Swine

Poultry

RESULTS Year

Bred

Lambed

Birth Rate

2017

33

23

0.70

2018

42

27

0.64

2019

42

27

0.64

2020

44

21

0.48

2021

153

91

0.59

2022

55

36

0.65

2023

154

75

0.49

2024

98

45

0.46

Figure 3. Results Table showing a summary of the calculated birth rate for each year of this multi-year study.

Extensive efforts have been focused to understand the causes of such variability in lambing rates. The degree to which various factors interact and influence LAI remain unknown. The standardized process for LAI with frozen semen has not changed significantly since it was first introduced in 1980.

Today, the following variables remain at the core for lambing rate success: •

• •

Preparation of the ewe (age, body condition, plane of nutrition, body weight, synchronistion of estrus, and use of teaser) Quality of semen Enviromental condition (before, during, and after the program).

TOOLS OF THE TRADE Laparoscope Used with veterinarian accepted procedures and timings for Laparoscopic Artificial Insemination in Ohio seeddtock ewes.

Figure 4. Birth Rate Visual, based on Figure 3.

PROJECT CONTACT Tim Barnes (barnes.821@osu.edu)

2024 eBarns Report | 61

Small Ruminant Record Keeping Survey OBJECTIVE Assess common methods of records being kept and types of records being kept by small ruminant producers.

STUDY INFORMATION Time Surveyed Spring / Summer 2024 Species Small Ruminant

eBarns Collaborating Farms OSU Extension Statewide

STUDY DESIGN A survey was distributed digitally and contained questions designed to give insight on current small ruminant record keeping practices, how producers keep records, and what records they keep.

Topic Surveyed Farm Management County Distributing Delaware County Survey Locations Surveyed USA, Canada, United Kingdom Type of Respondents Farmers/Herdsman Total Number of 192 Survey Responses

What type of livestock do you raise?

Figure 2. Chart showing that over 96% of the respondents keep some type of records.

What benefits do you see from keeping livestock management records?

Figure 1. Bar chart showing the breakdown of what types of producers responded.

Mainly sheep vs. goat producers.

Animals Represented in Survey Sheep 14,551 Goats 3,735 Other 846 Figure 3. Word cloud generated from answers provided, with the larger words being the most frequently mentioned.

62 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

OBSERVATIONS • •

• • • •

The top 4 types of records that small ruminant managers keep are birthing, breeding, health, and genetics (Fig. 4).

The top uses for management records are Breeding and selection/ genetic progress, Health and death loss tracking, Performance/ Show results, Financial, Reference guide, Birthing rates, Feed and nutrition, and Compliance and regulation.

Most respondents (64.81%) use ear tags as their identification method.

Method of keeping records are split close to even for paper versus electronic.

Electronic record keepers tend to use spreadsheets.

The most prevalent pre-made record system represented in our survey was the “HerdBoss” app.

Small Ruminant

Equine

Swine

Poultry

RESULTS

Figure 4. Chart showing most commonly recorded livestock operation data.

SUMMARY The 192 respondents of the survey manage 18,286 head of small ruminants, made up of over 14,500 head of sheep and over 3,700 head of goats. Over 96% of the respondents keep some type of livestock management records, however it’s worth noting that over 3% of respondents do not keep any type of records (Fig. 2).

Survey answers reflected that producers see records as a benefit to their livestock management; however, they are not always updating them right after a handling event (Fig. 5).

In conclusion, this survey showed that most sheep and goat producers keep dedicated livestock records and see benefits to their livestock business.

Figure 5. Pie chart showing that these producers update their permanent records most often after each handling of an animal (67.86%).

TOOLS OF THE TRADE

PROJECT CONTACT

Social Media

Jacci Smith (smith.11005@osu.edu)

Distribution of this survey went through digital newsletters and on social media.

Sheep Team: u.osu.edu/sheep facebook.com/delawarecountyag

See more about Delaware County's eBarns studies at go.osu.edu/24ebarnsvideos

Kate Hornyak (hornyak.26@osu.edu) Rob Leeds (leeds.2@osu.edu)

2024 eBarns Report | 63

Cool-Season Grass Hay Preferences OBJECTIVE

ATI Equine Facility

Measure yield, macronutrient content, and ergovaline presence within monocultured coolseason grass hays. Then, evaluate relative horse preference focusing on Fescue and Ryegrass families.

CFAES Wooster Wayne County

STUDY INFORMATION Start Date

05/01/2019

End Date 12/31/2020 Species Equine Start Point Mature End Point Mature Treatments 8 Reps 2 Unit per Rep 4 Experimental Head Unit Breed, Stock type Genetics

Figure 1. 2019 Yield of the seven cool season cultivars grouped by horse preference.

Sex M:F 2 mares : 2 geldings IACUC # 2019A00000070

STUDY DESIGN

First cutting chopped hay (7 cultivars) was created in 2019 and analyzed for nutrients and ergovaline concentrations. Taste preferences were evaluated during summer 2019 and winter 2020 using a randomized complete block design with cultivar and bucket location as variables.

Stalls had 8 buckets along a wall and visible to pre-installed foaling cameras for recording. The same 4 mature horses at maintenance were used for the preference testing both years. Horses were fasted 30 minutes before entering the testing stalls and had access to the cultivars for 30 minutes. Weight consumed was recorded. Equine preference data for cultivar and bucket location were analyzed in JMP Pro 15.

Figure 2. Example camera view of preference test set up, using a foaling camera.

ACKNOWLEDGMENTS: We would like to thank Ben Traver, Ben Lowe, and Ben Wasson for their assistance in harvesting, chopping, and weighing the 2019 hay. The study was supported by an Ohio State ATI Research, Creative, and Other Scholarly Activities (RCOSA) grant. This data was originally presented/published as an abstract at the virtual 2021 Equine Science Society Symposium: Bennet-Wimbush, K., B. Lowe, V. R. Haden, and S. L. Mastellar.

2021. 44 Relative preferences for cool season grass hay cultivars in adult horses. Journal of Equine Veterinary Science 100:103507. doi: 10.1016/j.jevs.2021.103507.

64 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

OBSERVATIONS

SUMMARY

•

In 2019 Meadow Fescue, Festulolium and the three Tall Fescue cultivars all had significantly greater first cutting yields than the Perennial Ryegrass and Orchardgrass cultivars (P < 0.05; Figure 1).

In this study, horses preferred Perennial Ryegrass and Orchardgrass hay which were also the lowest yielding cool season cultivars.

•

Consumption varied by cultivar (P < 0.05; Figure 3).

Cultivar ranks by amount consumed by the horses were similar across years.

•

Ergovaline was below detectable limits in all 2019 samples, so 2020 fescue hay was analyzed for endophyte presence (via tiller staining) confirming very low levels of infection: Bronson (3%), Texoma Max Q (17%), and KY 31 (0%).

Poultry

Horses demonstrated a consistent preference for some species of cool season grasses in both 2019 and 2020. However, the preference does not appear to be due to endophyte presence or macronutrient content.

For hay producers looking to strike a balance between moderately high yield and feeding preference by horses, Festulolium is likely to be a promising option.

RESULTS

Figure 3. Preference of mature horses for monocultured cultivars first cutting hay during two years. Total consumed is across all preference tests within year. Means within columns with different superscripts are statistically different (P<0.05).

TOOLS OF THE TRADE Foaling Cameras Cameras mounted above the stalls allowed researchers to record and quantify horse behavior.

PROJECT CONTACT Dr. Sara Mastellar (mastellar.1@osu.edu) Dr. Karen Bennett-Wimbush (wimbush.4@osu.edu) Dr. Ryan Haden (haden.9@osu.edu)

2024 eBarns Report | 65

Meal Frequency Effects on Heart Rate OBJECTIVE

ATI Equine Facility

Evaluate equine heart rate in response to feeding frequency.

CFAES Wooster Wayne County

STUDY INFORMATION Start Date 05/27/2022 End Date 06/30/2022 Species Equine Start Point Mature End Point Mature Treatments 3 Reps 2 Unit per Rep 6 Experimental Head Unit Breed, Light horses used for riding Genetics Sex M:F 6 mares : 6 geldings

Figure 1. Horse with the Polar heart rate monitor during sampling.

Wet sponges (pink and blue) were placed under the electrodes.

Sweat ensured subsequent conductivity. Inset image on bottom right: Tablets connected via Bluetooth to each heart rate monitor collecting data every second.

Feeding Pellets in corner feeders and hay in System slow feeder nets with 5 cm x 5 cm holes.

Diet Fed At a 2% body weight (BW) on a dry matter (DM) basis with 1.55% BW DM basis in grass hay (slow feed hay net). Concentrate provided at 0.45% BW on a DM basis.

IACUC # 2019A00000081-R1

Figure 2. Image of heart rate recording (split across both pages).

Heart rates of 12 horses fed 1x, 2x, or 3x/day over 12 hour period.

STUDY DESIGN

Two groups of 6 horses each received a meal frequency of 1x, 2x, or 3x for one week each in a randomly generated order. Diets were the same for all treatments. On day 6 of each week, using Polar H10 heart rate monitors connected to iPad tablets, data was collected (heart rate each second) for 12 hours while the horses were stalled. Data was imported into Excel. Outliers (>2.5 x mode) were removed from the original data set (1,514,799 data points) relative to the individual horses’ resting heart rate. Mode was used to represent the horses’ resting heart rate. After outliers were removed, the number of values above, at, and below the mode were quantified. Chi Square tests were used to evaluate statistical significance.

66 | Ohio State Digital Ag Program

Treatment

Description

1x

Horses received daily allotment of feed at 8 am

2x

Horses received daily allotment of feed split across two feedings (8 am & 6 pm)

3x

Horses received daily allotment of feed split across three feedings (8 am, 1 pm, & 6 pm)

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

OBSERVATIONS SUMMARY •

Of the 12 horses, 9 did have a significant difference in the proportion of heart rate readings above or below mode based on meal frequency (P<0.05).

RESULTS

With this information it does appear that one meal daily was the most stressful for the horses within this study despite the use of slow feeder hay nets. For these reasons it may be beneficial for the horse’s well-being if managers and owners can feed horses more often.

However, it is important to note that, ideally, stress is evaluated using multiple measures.

For the final analysis of the heart rate data, 1,479,854 of the original data points were used.

Outliers (>2.5 x mode) accounted for 2.3% of the data.

This data was part of a larger study evaluating additional effects of meal feeding frequency in horses of varying body condition scores.

Figure 3. Each horse with their mode, and the percentages of their heart rate data that was above, at, or below mode.

Figure 2. continued ACKNOWLEDGMENTS: We would like to thank Oriana Tillery-Sucre for assistance with horse care and sampling. We would also like to thank Ohio State ATI’s equine facility and staff for providing the horses. The project was funded by an Ohio State ATI’s Research, Creative & Other Scholarly Activities (RCOSA) grant and Buckeye Nutrition. This research was previously presented/ published as a poster: Brown, A. V., E. R. Share, N. Liburt, J. K. Bedore, P. Harris, and S. L. Mastellar. 2024. Effects of Meal Frequency on Heart Rate in Horses American Society of Animal Science Midwest No. PSIV-A-8, Madison, WI.

TOOLS OF THE TRADE

PROJECT CONTACT

Polar H10 Heart Rate Monitors

Dr. Sara Mastellar (mastellar.1@osu.edu)

Used to track heart rates. Data can be collected by connecting the monitors to portable devices, like iPad tablets, for data analysis.

Elizabeth E. Share (share.8@osu.edu) Alora V. Brown

2024 eBarns Report | 67

Meal Frequency Effects on Plasma Amino Acids OBJECTIVE

ATI Equine Facility

Evaluate the effect of feeding frequency on plasma amino acid responses in metabolically healthy horses of various stable body conditions.

CFAES Wooster Wayne County

STUDY INFORMATION Start Date 05/27/2022 End Date 06/30/2022 Species Equine Start Point Mature End Point Mature Treatments 3 Reps 2 Unit per Rep 6 Experimental Head Unit Breed, Light horses used for riding Genetics Sex M:F 6 mares : 6 geldings

Figure 1. Body composition has been known to affect basal metabolism, circulation of metabolites, and response to meals in other species. Visual was adapted from: buckeyenutrition.com/tools/body-condition-score.aspx

Feeding Pellets in corner feeders and hay in System slow feeder nets with 5 cm x 5 cm holes.

Diet Fed At a 2% body weight (BW) on a dry matter (DM) basis with 1.55% BW DM basis in grass hay (slow feed hay net). Concentrate provided at 0.45% BW on a DM basis.

IACUC # 2019A00000081-R1

STUDY DESIGN

Horses were fed to maintain condition with a complimentary feed (16% Cruide Protein (CP)) and hay (11% CP). Diet and feeding system is listed above, and treatments are listed in the Table to the right. After a 14 day adaptation, 2 groups (6 horses each) were randomly allocated to meal frequency regimens (lasting 7 days each) in a crossover design.

Treatment

Description

1x

Horses received daily allotment of feed at 8 am

2x

Horses received daily allotment of feed split across two feedings (8 am & 6 pm)

3x

Horses received daily allotment of feed split across three feedings (8 am, 1 pm, & 6 pm)

Jugular vein catheters were placed on day 7 of each regimen. Blood samples were taken relative to the morning feeding at −30, 0, 30, 60, 90, 120, 180 minutes. A mixed model with repeated measures in SAS was used to determine the effects of meal frequency, time point, and body condition score on plasma amino acid concentrations.

ACKNOWLEDGMENTS: We would like to thank Oriana Tillery-Sucre for assistance with horse care and sampling and Dr. Shaun Wellert for assistance with placing catheters. We would also like to thank Ohio State ATI’s equine facility and staff for providing the horses. The project was funded by an Ohio State ATI’s Research, Creative & Other Scholarly Activities (RCOSA) grant and Buckeye Nutrition. This research was previously presented/published at a scientific conference: Mastellar, S. L., E. R. Share, J. K. Suagee-Bedore, K. Bennett-Wimbush, N. R. Liburt, A. Krotky, B. Cassill, K. L. Urschel, and P. A. Harris. 2023. 74 Effects of meal frequency on plasma amino acid concentrations in horses of various body condition scores. Journal of Equine Veterinary Science 124:104376. doi: https://doi. org/10.1016/j.jevs.2023.104376

68 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

OBSERVATIONS •

With the exception of glutamate, all plasma amino acid concentrations increased after meal consumption (P < 0.01).

•

While meal feeding frequency did affect plasma amino acid concentrations for most amino acids (P < 0.01), there was no interaction between meal frequency and time point for any amino acid (P > 0.7).

•

Indispensable postprandial plasma amino acid concentration increases over baseline at 60 min (average± SE) were 56 ± 7%, 56± 8%, and 59 ± 7% for the 1x, 2x, and 3x meal feeding regimens, respectively.

Body condition score affected plasma concentrations of alanine, arginine, aspartate, and tyrosine (P < 0.01).

Small Ruminant

Equine

Swine

Poultry

RESULTS

Figure 2. Plasma amino acid responses to the 8 am meal were similar across treatments (1x, 2x, & 3x), despite the difference in meal size.

SUMMARY The findings demonstrate that even one third of the dietary allotment was able to create increases in plasma amino acid concentrations similar to the 1x feeding regimen.

Feeding smaller, more frequent meals could be a simple way to improve protein and amino acid bioavailability in equine diets.

More research is needed to investigate plasma amino acid profiles related to disease states and body composition.

Figure 3. Plasma amino acid responses to the 8 am meal varied with body condition.

TOOLS OF THE TRADE

PROJECT CONTACT

Henneke body condition scoring system

Dr. Sara Mastellar (mastellar.1@osu.edu)

To learn more and find scoring sheets:

Dr. Karen Bennett-Wimbush (wimbush.4@osu.edu)

ohioline.osu.edu/factsheet/as-1024

Elizabeth E. Share (share.8@osu.edu)

2024 eBarns Report | 69

Intestinal Parasite Surveillance OBJECTIVE Characterizing the occurrence of intestinal parasites of pigs raised on free-range systems located in Ohio and surrounding states.

STUDY INFORMATION Start Date Summer 2024 End Date On-going, Expected Spring 2025 Species Swine Breed Various

eBarns Collaborating Farms CFAES Animal Sciences and Center for Food Animal Health Statewide

STUDY INTRODUCTION Intestinal Parasite Surveillance in Free-Range Pig Farming: Farms are being recruited and enrolled continuously throughout the project period based on the OSU CFAES Extension network and on direct contact with farmers listed on pastured pig farms and pork products directories available on the internet. The criterium for farm inclusion is: “pigs have access to out-door, non-concreted areas.”

Sex Males and Females

STUDY DESIGN Fecal samples are collected directly from the rectal ampulla of pigs, or, if this method is not successful, freshly dropped feces are carefully collected to avoid contact with soil. Each sample receives a unique identification and is stored under refrigeration until submission to the Veterinary Parasitology Laboratory at the OSU-College of Veterinary Medicine for parasitology tests. Laboratory test results are emailed to the producers along with a summary about the parasites observed in the samples.

A survey is conducted at each farm to gather characteristics related to the farm management and health status of pigs. Information from surveys is compiled and analyzed using descriptive summary statistics.

Learn more about the project and other swine topics: Figure 1. Our research/Extension team visiting a farm to collect pig fecal samples and to interact with producers in person.

porkinfo.osu.edu

70 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

OBSERVATIONS

SUMMARY

•

At least 1 pig of each farm was positive for at least 1 intestinal parasite.

•

Five farms have been included in the project up to now, with 57 samples collected (as of July 2024).

•

Only 8 pigs (14.03%) were negative for intestinal parasites.

•

All 5 farms included up to this point are raising their pigs in a near-organic condition.

•

Coccidia and Ascasis suum were the most prevalent parasites observed, with 80.7% and 54.3% positive samples, respectively. Strongyloides sp. was present in 31.58% of the samples and Trichuris sp. in 14.04%. Giardia and Cryptosporidium were detected punctually.

•

Current age of sampled pigs range from 8 weeks to 12 years old.

•

None of the intestinal parasites detected can be transmitted to humans through consumption of pork.

PRELIMINARY RESULTS

Figure 2. Chart with data as of Summer 2024.

Acknowledgements for project: Dr. Antoinette Marsh, Dr. Arruda, and Abby Waldrop

PROJECT CONTACT Are you curious to know if your pasture pigs have intestinal parasites?

Contact us and enroll in the project! All costs related to sampling and parasitology tests are covered by the project team.

Dr. Talita Resende, DVM Assistant Professor and Swine Health Extension Specialist (resende.2@osu.edu) Kara Flaherty BS Animal Sciences Education Program Specialist (flaherty.177@osu.edu)

2024 eBarns Report | 71

Noise on the Swine Farm How much noise are Ohio farmers exposed to during their daily livestock routines?

The answer is more than expected. Sounds that register 90 decibels for an 8-hour shift are considered hazardous for workers. In fact, the noise-contributing sources at swine facilities are cumulative over one’s lifetime. Common high-noise sources include squealing pigs when receiving health care, feeding times in the breeding and finishing barns, and pressure washing the pens. Additional noise from tractors, machinery and grain augers contribute to a farmer’s daily noise dose. Debilitating hearing loss is a common hazard outcome of farm work.

How to measure sound on the farm: Sound is measured in units called decibels (dB). Knowing the decibel level of a workplace makes it easy to determine if and where protection practices should be put in place.

To know if noise levels exceed the 90dB threshold, take a sound pressure reading. Handheld sound pressure meters record on the spot. Local feed elevators may have these units available to monitor a workspace – or at least discuss noise exposure hazards at their facility. If a farm is covered under the Ohio Bureau of Workers’ Compensation (BWC) Program, BWC field specialists can provide a workplace noise reading upon request.

Figure 1. A sound pressure meter (left) or a smart phone with a sound APP (right) provides quick measurement of the decibel level in the work environment.

Another tool to use for sound measurements is a smart phone with a sound APP. These APPS have similar capacity to sound meters and provide a convenient and economical way to get instantaneous results. Search the APP store for “sound level meter” to find a variety of free options.

Personal Noise Exposure Level Recorded in an 8-Hr Day

In this noise exposure sample a worker wore a personal noise dosimeter inside a swine animal facility for 470 minutes (from 7:40 to 15:30 on the 24-hour clock). From 7:40 to 12:00 (Period 1) the worker fed pigs and cleaned pens, except for a break at 10:10am where the worker stepped outside the building (shown as Period 2). After lunch (from 12:00 – 12:45), the worker resumed pen cleaning (Period 3). Excluding the outlier noise at 15:10, the highest recorded point was 109.6dB. To read the graph: x axis = time of day, y axis = noise sound level in (dB), red line marks 90dB (the OSHA standard for permissible sound level). Anything over the red line requires hearing protection, however it is recommended to start wearing hearing protection at 85dB. In this example, the worker spent a majority of their workday in a high noise environment that required hearing protection.

Figure 2. A graph of the data collected during the noise exposure sampling

72 | Ohio State Digital Ag Program

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Cattle

Small Ruminant

Prevention tips for the workers

Equine

Swine

Poultry

Control the noise at the source

1. Limit daily exposure to high noise areas. Prominently 1. Select equipment and ventilations systems with lower post “High Noise Area” signs in work areas where sound levels. Often times, newer equipment has housing the sound level exceeds 85dB. and insulation that reduces noise output.

2. Wear hearing personal protective equipment (PPE) in workplaces that exceed 90dB. Farm chores measuring 90dB and higher require protection while doing that task, but these activities may not take an entire workday. It’s a good practice to start wearing hearing protection at 85dB as a preventative measure.

3. There are many types of PPE ranging from ear plugs to muffs. All are acceptable if they are worn correctly. Ear plugs need to be inserted into the ear canal, while earmuffs cover the entire outer ear.

2. Perform routine maintenance on equipment and fans.

Replace worn, loose or unbalanced parts to reduce the noise generated by vibration and friction. Well-lubricated equipment can reduce vibration and friction. Also ensure engines have properly installed mufflers and are in good condition.

3. Isolate the noise source from the worker. Insulating walls in the barns and farm shop will reduce the transfer of noise to other work or office spaces. Also, cab tractors are good options for muffling engine noises and protect workers while performing other farm tasks.

4. Choose PPE with a Noise Reduction Rating (NRR) 4. While it is difficult to contain noises created by the livestock of 20 or higher. The NRR is included on the package and pressure washers, workers can protect themselves of each product. This number indicates the decibels by wearing hearing protection and rotate their work so that are reduced by wearing the hearing protection. that they limit the amount of time exposed to high noise The higher the rating, the better the product. As an activities. example, if the workplace measures 100dB, wearing 5. If the farm hires more than 10 non-family members, hearing protection with an NRR rating of 22, makes employers should follow the recommended practice in the the worker’s exposure 78dB. OSHA 1910.95 standard for Occupational Noise Exposure.

SUMMARY

Don’t wait to put a noise protection practice in place.

Hearing loss is permanent! Unlike wearing corrective eyeglasses, hearing aids cannot restore a person’s hearing; these devices can only amplify the sounds detected by the auditory nerves.

TOOLS OF THE TRADE Sound Level Meter A sound level meter takes instantaneous measurements of the environmental noise conditions at their source.

To learn more about noises on the farm, watch a video produced by the OSU Ag Safety and Health program in partnership with Ohio Bureau of Workers’ Compensation. This video explains the common ways hearing loss can occur in agricultural environments, how audiograms are used to detect hearing impairment, https://youtu.be/YxH10xQVTok and the steps to take to prevent damage.

PROJECT CONTACT

Agricultural Safety and Health Program For inquiries about this article, contact Dee Jepsen (jepsen.4@osu.edu) or Yang Geng (geng.83@osu.edu)

2024 eBarns Report | 73

pH and Temperature of Different Pork Muscles OBJECTIVE

OSU Meat Lab

Characterize the relationship between pH and temperature decline with color and water-holding capacity of five different pork muscles.

CFAES Animal Sciences Franklin County

STUDY INFORMATION Start Date 02/20/2024 End Date 05/24/2024 Species Swine Treatments 5 Reps 15 Experimental Unit Head

STUDY DESIGN Fifteen pigs (hot carcass weight = 93 ± 3 kg) were slaughtered at the Ohio State University The pH and temperature of 5 muscles were measured at 1-, 3-, 6-, 9-, 12-, and 24-hours(h) postmortem (during the conventional chilling process): • • • • •

longissimus dorsi (LD) psoas major (PM) semitendinosus (ST) triceps brachii (TB) gluteus medius (GM)

Data Collection and Evaluation: Instrumental CIE (L*, a*, b*) Color Values: using a Minolta CM600d on the cut surface of each muscle following carcass fabrication at 24-h postmortem.

Drip Loss of Pork (loss of fluid from fresh, non-cooked pork as muscle transitions to meat): assessed using 25-mm diameter cores with the EZ cup method over a 48-hour period.

Muscles were randomly allocated to 1 of the 3 postmortem aging time points (1, 3, and 10 day(s)), and 1 of the 2 endpoint cooking temperatures (145°F (63°C) or 160°F (71°C)) using sous-vide technique before Warner-Bratzler shear force analysis. The rate and the extent of pH and temperature decline, color, and drip loss were analyzed using a randomized complete block design in PROC GLIMMIX of SAS v9.4, with muscle as the fixed effect, and pork carcass nested within slaughter event as a random effect. Stepwise regression analysis was performed with PROC REG of SAS to develop prediction equations for the parameters of interest while including slaughter event as dichotomous variables in the model.

74 | Ohio State Digital Ag Program

Figure 1. Swine carcass graphic.

Meat Lab.

SUMMARY This study characterized the relationship between pH and temperature decline with color and waterholding capacity of 5 different pork muscles. The results indicated that the rate and extent of pH and temperature decline, color, and drip loss appear to be muscle-specific. The relationship between pH and temperature decline with color and drip loss also appears to be muscle-specific.

While both pH at 1h and 24h postmortem played critical roles in color and drip loss, pH at 1h postmortem is the best predictor for the quality of the LD muscle, but not for other muscles.

Figure 2. Yifei Wang with pigs prior to project.

Forages

Manure Nutrients

Small Ruminant

Cattle

Equine

Swine

Poultry

OBSERVATIONS •

The main effect of muscle was significant for both pH and temperature at each time point, as well as for color and drip loss.

•

Pork LD, ST, and GM demonstrated greater "lightness" in color than PM and TB. PM demonstrated the greatest "redness" among the 5 muscles.

•

The LD, ST, and GM muscles exhibited greater pH than • TB and PM at 1h postmortem. Then the PM, ST, and TB muscles demonstrated greater pH than LD and GM at 24h postmortem.

•

The LD muscle demonstrated the greatest rate of pH decline from 1h to 3h postmortem, while no differences in the rate of pH decline at other time points were observed between muscles. LD also had the greatest drip loss among the five muscles.

For ST, pH at 1h postmortem explained greater variation in drip loss (50%) than pH at other time points. However, for the PM, TB, and GM, pH and temperature (when measured at each of the timepoints used in this study) explained less than 33% of the variation in color and drip loss.

•

•

PM and ST had the lowest temperature at 1h postmortem, while LD and PM had the lowest temperature at 24h postmortem.

RESULTS

Figure 3. Carcass data collection in the OSU Meat Lab

Response Variable

Cooking Temperatures: GM had the greatest WBSF compared to other muscle cuts when cooked to both temperatues used; PM demonstrated the lowest WBSF when cooked to 145°F (63°C); and LD, PM, ST, and TB exhibited similar WBSF when cooked to 160°F (71°C).

LD

PM

ST

TB

GM

Significant?

pH-1h

6.13ab

5.73c

6.29ab

6.06b

6.35a

Yes P ≤ 0.05

pH-3h

5.53c

5.68bc

5.99a

5.84ab

5.94a

Yes P ≤ 0.05

pH-6h

5.48b

5.76a

5.80a

5.80a

5.78a

Yes P ≤ 0.05

pH-9h

5.49b

5.71a

5.80a

5.80a

5.67a

Yes P ≤ 0.05

pH-12h

5.49b

5.71a

5.75a

5.75a

5.66a

Yes P ≤ 0.05

pH-24h

5.47b

5.67a

5.68a

5.69a

5.56b

Yes P ≤ 0.05

Lightness L*

55.88a

48.66b

54.42a

45.57b

52.70a

Yes P ≤ 0.05

Redness a*

5.56c

14.84a

10.42b

10.97b

6.96c

Yes P ≤ 0.05

b*

15.30b

17.23a

16.94a

13.80c

15.15bc

Yes P ≤ 0.05

Drip loss (%)

6.70a

0.93c

1.47c

1.16c

3.81b

Yes P ≤ 0.05

Figure 4. Quality results for the Longissimus Dorsi (LD), Psoas Major (PM), Semitendinosus (ST), Triceps Brachii (TB), and Gluteus Medius (GM) muscles. a-c Means with different letters in each row and different muscles are significantly different (P < 0.05)

TOOLS OF THE TRADE

PROJECT CONTACT

Portable MPI pH Meter (Meat Probes Inc., Topeka, KS)

Dr. Ben Bohrer, Assistant Professor Department of Animal Sciences (bohrer.13@osu.edu) Yifei Wang, Graduate Research, Ph.D Department of Animal Sciences (wang.10408@osu.edu)

2024 eBarns Report | 75

Quality of the Pork Tenderloin OBJECTIVE

OSU Meat Lab

Determine the associations between meat quality and sensory traits for the pork tenderloin (psoas major).

CFAES Animal Sciences Franklin County

STUDY INFORMATION Start Date 07/27/2023 End Date 05/24/2024 Species Swine Treatments 6 Reps 103 Experimental Unit Meat Pieces Figure 1. Preparing samples for analysis.

STUDY DESIGN A total of 103 pork tenderloins (IMPS# 415; psoas major muscle) were utilized on the same day of production. Each sample was cut into 2 sections: One 10cm section for quality analysis and one 5cm section for sensory analysis.

Quality Analysis consisted of instrumental color, pH, cooking loss when vacuum-packaged samples were cooked in a water bath to an endpoint cooking temperature of 160°F (71°C), and WarnerBratzler shear force. Desmin degradation was analyzed using western blot.

Sensory Analysis consisted of juiciness, tenderness, flavor, and overall acceptability assessments using a trained sensory panel that utilized a 15cm line scale (0 = extremely dry, extremely tough, no flavor, or very unacceptable, and 15 = extremely juicy, extremely tender, very flavorful, or very acceptable).

SUMMARY This study characterized the associations between meat quality and sensory traits for the pork tenderloin. Data from this study suggests that changes in important meat quality traits such as pH and shear force are influential to sensory attributes for pork tenderloins. Future research efforts to quantify the underlying biological mechanisms of such quality traits will be beneficial for the pork industry.

Data Categorization: • 3 groups based on pH values of low, average, or high pH (< 5.60, 5.60-5.80, or > 5.80) • 3 groups based on Warner-Bratzler shear force values of tender, intermediate, or tough (< 2.5kg, 2.5-3.0kg, or > 3.0) Data were analyzed using PROC CORR of SAS (SAS Inst. Inc., Cary, NC) to generate Pearson correlation coefficients.

Data was analyzed with PROC GLIMMIX of SAS with fixed effects of pH value group or Warner-Bratzler shear force group.

76 | Ohio State Digital Ag Program

Figure 2. Image of a cooked pork tenderloin.

Photo credit: Food Network

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

OBSERVATIONS

Data initially suggested weak and moderate associations between the quality parameters and sensory characteristics.

However, when samples were categorized into groups (based on data categories), interesting trends began to emerge.

•

•

Low pH tenderloins: lighter in color; greater levels of cooking loss; tended to be perceived as less juicy and tougher (by the sensory panel); had lower levels of sensory acceptability compared with high pH tenderloins.

Average pH tenderloins: intermediate tenderness (compared with low and high pH tenderloins) with a linear effect for instrumental lightness, cooking loss, sensory juiciness, sensory tenderness, and sensory acceptability.

RESULTS

•

Tender category: perceived as more tender, with greater levels of acceptability (compared to tough tenderloins).

•

Intermediate category: tenderloins were an intermediate tenderness (compared to tender and tough tenderloins).with a linear effect for both sensory tenderness and sensory acceptability.

•

Low pH tenderloins and tough tenderloins had greater abundance of degraded desmin (last row in Fig. 3), which is an indicator of the extent of protein degradation in meat - believed to contribute to meat tenderization.

Response Variable

Tender

Intermediate

Tough

P-value

Low pH

pH

5.72

5.69

5.67

0.36

5.53c

5.69b

5.90a

< 0.01

Lightness, L*

48.82

48.99

49.42

0.76

51.80a

48.98b

46.67c

< 0.01

Cook loss, %

19.02

19.65

19.97

0.25

20.83a

19.68a

17.86b

< 0.01

WBSF, kg

2.32c

2.77b

3.25a

< 0.01

2.94

2.85

2.70

0.14

Sensory juiciness

7.54

7.19

6.67

0.16

6.88

6.93

7.90

0.07

Sensory tenderness

9.59a

8.59b

8.01b

< 0.01

8.19b

8.44b

9.95a

< 0.01

Sensory flavor

7.82

7.39

7.35

0.13

7.29

7.46

7.74

0.36

Sensory acceptance

8.21a

7.63ab

7.16b

0.01

7.19b

7.54b

8.39a

0.02

"Desmin intact (55 kDa)"

0.31

0.38

0.47

0.70

0.27

0.39

0.56

0.47

Degraded desmin (42 kDa)

0.22b

0.33ab

0.42a

0.01

0.56a

0.30b

0.26b

0.0003

Average pH High pH

P-value

Figure 3. Quality and sensory results for pork tenderloin samples. n = 103 pork tenderloin muscles; superscripts within each row with different letters indicate significant differences (P < 0.05).

TOOLS OF THE TRADE

PROJECT CONTACT

TA-XT Plus Texture Analyzer (Texture Technologies Corp., MA)

Dr. Ben Bohrer, Assistant Professor Department of Animal Sciences (bohrer.13@osu.edu)

Measures shear force values to determine: tender, intermediate, or tough categorization.

Yifei Wang, Graduate Research, Ph.D Department of Animal Sciences (wang.10408@osu.edu)

2024 eBarns Report | 77

Highly Pathogenic Avian Influenza An Update on 2022-2024 HPAI Detections in Ohio The Highly Pathogenic Avian Influenza (HPAI) outbreak of 2022-2024 affected 96,809,026 birds, making it even more devastating than the 2014-2015 outbreak. This has included 495 commercial flocks and 653 backyard flocks in 48 states (as of June 5, 2024). The first confirmed case of Highly Pathogenic Avian Influenza detected in Ohio was confirmed on March 30, 2022, in a Franklin County non-commercial backyard flock.

Ohio Numbers 7 affected commercial flocks 10 affected backyard flocks 9,646,496 total birds affected

Most recent detection: February 27, 2024 Avian influenza is a viral disease that can affect multiple species of birds. It can exist in a low pathogenic form that causes mild symptoms of disease and can also mutate into a highly pathogenic form that can cause high mortality in multiple avian species including domestic poultry such as chickens and turkeys, shore birds, and raptors including hawks, owls, and eagles. Highly pathogenic avian influenza (HPAI) is devastating in that it is highly contagious with no treatment available. It can be spread widely in migratory waterfowl, in which it can exist in an asymptomatic carrier state. Two of the four major migratory pathways pass through Ohio which increases our risk of outbreaks.

Confirmed Detections in the United States for HPAI 2022-2024. Source: USDA APHIS

go.osu.edu/APHIS-HPAI-Data

78 | Ohio State Digital Ag Program

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Equine

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Poultry

Prevention The key to preventing outbreaks in both backyard poultry and the poultry industry is biosecurity.

Biosecurity is the strategy of prioritizing the health by preventing disease from entering the flock or herd. It comes in 2 main forms: direct biosecurity and indirect biosecurity.

Direct poultry biosecurity

Indirect poultry biosecurity

Preventing disease transmission from bird to bird. Make sure that your flock cannot encounter wild birds by fencing, bird netting or other exclusion.

Make sure to limit or exclude visitors to your flock whenever possible. Make sure to use proper sanitation procedures as well as include the use of personal protective equipment.

HPAI in Dairy Cattle In the United States over 99% of the commercial milk supply produced by U.S. dairy farmers participates in the Grade “A” milk program that follows the Pasteurized Milk Ordinance, which includes controls that help ensure the safety of dairy production. These dairy products are first pasteurized or processed in a fashion that kills pathogens similar to the cooking of meat. When H5N1 (subtype that causes avian influenza) was first detected in dairy cattle in early 2024 it was also detected in raw milk. To be sure that pasteurization killed the H5N1 virus the USDA conducted a study testing 297 retail dairy products in 17 states, including Ohio.

Results for Ohio are summarized below. A total of 8 products were tested in Ohio. None of the products tested in Ohio, or anywhere in the country, contained a live virus that could be grown and cause viral infection.

However, in 3 of the 8 products the virus that was inactivated by the pasteurization process could be found. This confirmed that pasteurization is an effective way to kill the H5N1 virus that may be in milk.

Detection of Live Virus in Retail Product(s)

Number of Retail Product Samples Tested

Retail Product Samples Negative for Viral RNA (qRTPCR Screening -)

Retail Product Samples Positive for Viral RNA (qRTPCR Screening +)

Retail Product Sample Results for Live Virus (Viability Testing by Egg Inoculation)

8

5

3

0

No

An additional study investigated the different types of pasteurization to be sure all processes were effective, and it is estimated that pasteurization can eliminate about 1 trillion virus particles per milliliter. This study found that all pasteurization techniques approved by the Pasteurized Milk Ordinance were effective.

For updates on HPAI from the FDA, use this QR code or the link below.

go.osu.edu/FDA-HPAI-updates

PROJECT CONTACT

For inquiries about this project:

For inquiries about HPAI in Dairy:

Timothy S. McDermott, DVM Extension Educator, Franklin County mcdermott.15@osu.edu (614)-292-7916

Jason Hartschuh, Extension Field Specialist,

Dairy Management & Precision Livestock

hartschuh.11@osu.edu

2024 eBarns Report | 79

Acknowledgments Research Collaborators and Supporters Eastern Agricultural Research Station and Staff: Chris Clark Dalton Huhn Edwin Pickenpaugh Kevin Stottsberry Jim Jasinski, OSU Extension Ben Lowe Dewey Mann, Director of Waterman Ohio Corn Board Ohio Sheep and Wool Program OSU ATI’s Equine Facility and Staff OSU Beef Team OSU Sheep Team OSU Small Ruminant Research Center in Wooster: Gregg Fogle Roger Shearer Erin Weisgarber ST Farmfit Dr. Mark Sulc Oriana Tillery-Sucre Ben Traver Ben Wasson Dr. Shaun Wellert Will C. Hauk Endowment

80 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

Future Dates September 16-18, 2025

September 22-24, 2026 2024 eBarns Report | 81

Glossary 95% CI – Confidence Interval, range of values that can be certain to contain the true mean of a population Ad Libitium – A feeding management in which animals are fed without any restrictions ADF – Acid Detergent Fiber, least digestible plant compounds, including lignin and cellulose ADFI – Average Daily Feed Intake, amount of feed (As Fed) consumed per animal, per day ADG – Average Daily Gain, weight gained per animal, per day Bob Veal – Veal calves marketed up to three weeks of age BW – Body Weight CP – Crude Protein, measures nitrogen content of feedstuffs, including true protein and nonprotein nitrogen DCAD – Dietary Cation Anion Difference, measurement used when formulating diets for dry or lactating cows using positively and negatively charged minerals on animal performance DDG – Dried Distillers’ Grain with Soluble, co-product of ethanol production and often used as a protein source in a diet DIM – Days In Milk, number of days a dairy cow has been lactating DM – Dry Matter, fiber and nutrients remaining once water is removed from a feedstuff or diet DMI – Dry Matter Intake, amount of dry matter consumed per animal, per day DON – Deoxynivalenol, Vomitoxin, a common mycotoxin found in grain Dressing Percent – (Hot Carcass Weight divided by Live Weight) x 100 GDD – Growing Degree Days, heat units used to estimate growth and development of crop and pests during the growing season FAMACHA © – Selective treatment method for controlling the level of parasitic barber’s pole worm in small ruminants FEC – Fecal Egg Count, quantitative assessment of how many parasite eggs an animal is shedding at a particular time Feekes Growth Stages 10.0 – Grass Forage at Boot Stage 10.5 – Grass Forage at Heading FTPI – Failed Transfer of Passive Immunity, when a calf fails to absorb adequate immunoglobulins via colostrum 82 | Ohio State Digital Ag Program

Forages

Manure Nutrients

Cattle

Small Ruminant

Equine

Swine

Poultry

Gain : Feed – Measure of Feed Efficiency, ratio of total pounds gained to total pounds of feed fed Hot Carcass Weight – Carcass Weight prior to chilling Hypoglycemic – Low Blood Sugar K2O – Potassium fertilizer form, Potash Laparoscopic Artificial Insemination – Intrauterine method of insemination used in small ruminants Mycotoxin – Toxin produced by certain molds or fungi in grains N – Nitrogen NDF – Neutral Detergent Fiber, structural components of plants, specifically the cell wall and predicts voluntary intake because it provides bulk or fill NEL – Net Energy Lactation, amount of energy in a feedstuff that is available for milk production and body maintenance NIR – Near Infrared Reflectance, measures light energy reflected by the feed sample to determine the chemical composition of forages OC% – Percent of Organic Carbon OM% – Percent Organic Matter P205 – Phosphorus fertilizer form Passive Immunity – Immunity acquired via colostrum intake shortly after birth PCV – Packed Cell Volume, a measurement of the proportion of blood that is made up of cells RFID – Radio Frequency Identification, method used to track livestock SEM – Standard Error of the Mean, indicates how different the population mean is likely to be from a sample mean TDN – Total Digestible Nutrients, sum of digestible proteins, fiber, lipids, and carbohydrates in feedstuff TKN – Total Kjeldahl Nitrogen, total concentration of nitrogen and ammonia TMR – Total Mixed Ration, method of feeding that combines feeds to a specific nutrient content Wet Chemistry – Chemistry based analytical methods used to measure chemical compounds in plant material 2024 eBarns Report | 83

eBarns

“connecting science to farmers” eBarns is a The Ohio State University program dedicated to advancing production agriculture through the use of field-scale research. eBarns utilizes modern technologies and information to conduct on-farm studies with an educational and demonstration component used to help farmers and their advisors understand how new practices and techniques can improve farm efficiency and profitability. The program is dedicated to delivering timely and relevant, data-driven, actionable information to farmers throughout Ohio.

Disclaimer Notice: The information provided in this document is intended for educational purposes only. Mention or use of specific products or services, along with illustrations, does not constitute Endorsement by The Ohio State University. The Ohio State University assumes no responsibility for any damages that may occur through adoption of the programs/techniques described in this document.