OSU Extension to Host 7th Annual East Ohio Women in Agriculture Conference

Ohio State University (OSU) Extension, the outreach arm of the College of Food, Agricultural and Environmental Sciences (CFAES) will host the 7th Annual East Ohio Women in Agriculture Conference.  This year’s conference convenes on Thursday, March 19 from 9:00 a.m. – 3:30 p.m. at the RG Drage Career Technical Center, 2800 Richville Drive SE in Massillon.  All women and young women (high school age) who are interested in, involved in, or want to become involved with food, agricultural, or natural resources production or small business are encouraged and welcomed to attend.

The conference program features an agency/vendor fair and eighteen educational breakout sessions presented by OSU Extension educators, producers and partner agencies.  Sessions focus around five themes: Business & Finance, Plants & Animals, Communication, Home & Family and Special Interest (areas of specific interest to attendees).  Farm and Dairy Editor, Rebecca Miller is the conference featured keynote speaker. Her presentation will engage and enlighten participants on “Clinging to context in a noisy world: don’t lose sight of your “why”.

Interested individuals can register for the conference on-line at go.osu.edu/eowia2020.  Cost of the conference is $55 for adult participants and $30 for students.  Conference fee includes conference participation, continental breakfast, lunch and conference handouts.   Deadline for registration is Thursday, March 12.

Registered participants, community organizations or businesses interested in sponsorships and/or securing an informational or vendor table can do so from the registration page or contact 1-740-264-2212 to obtain more information.  A list of sponsorship opportunities is also available from the registration page.

Stay connected with the Ohio Women in Agriculture Learning Network on Facebook @OHwomeninag or subscribe to the Ohio Women in Agriculture blogsite at http://u.osu.edu/ohwomeninag/

2020 Central Ohio Agronomy School

by: John Barker, OSU Extension Educator

“The Nuts & Bolts About Corn & Soybean Production”

The 2020 Central Ohio Agronomy School will be held on Monday evenings, beginning on Monday,  February 10 through Monday March 9, from 6:30 –9:00 p.m. in the conference room of the Ag Services Building, 1025 Harcourt Rd. Mt. Vernon, Ohio 43050.   This five-week program will provide the attendees with the most comprehensive, up-to-date crop production and agricultural technology information available today.  This school is designed with everyone in mind; part-time or full-time producer, beginner or CCA agronomist.  Within each subject area we will teach the basic concepts and progress to the most advanced agronomic principles.

Topics include:

February 10   – Bruce Ackley, OSU Weed Science.

Weed Identification with Live Plants at Various Growth Stages.

Palmer, Waterhemp, Pigweed, Marestail, Various Grasses and more!

Dr. Mark Loux, OSU Weed Science

Developing a Multi-Year Herbicide Program for Tough to Control Weeds

Weed control update for 2020

February 17   – Dr. Scott Shearer, OSU Chair, Food, Agriculture and Biological Engineering

                                    Field Compaction Research

  – Dr. Elizabeth Hawkins, Field Specialist, OSU Extension

              2019 On-farm Research Results

February 24   – Ben Brown, OSU College of Food, Agriculture, & Environmental Sciences

                                    Farming & Marketing in an Uncertain World

Peggy Hall OSU Agricultural & Resource Law Program

“Hot” Agricultural Law Topics

March 2         – Glen Arnold, Field Specialist, OSU Extension

                                     Is Manure Right for You?

– Dr. Jeff Stachler, OSU Extension – Auglaize County

                                    Weed Seeds in Manure. 

 March 9         – Marne Tichenell, Wildlife Specialist, OSU Extension

Wildlife Damage in Field Crops

Aaron Wilson, Byrd Polar and Climate Research Center

                                    How Weather is Affecting our Farming Operations

2018 Weather Outlook

This school will provide:

14 continuing education credits (CEU’s) for Certified Crop Advisors,

C.M. 2, I.P.M. 6.5, N.M 2, P.D. 1.5,  S&W 2.0.

8 hours of Commercial Pesticide Credits

Core – 2 hrs., 2a – .5 hrs., 2c – 2 hrs., 2d –.5 hrs., 9 – .5 hrs., 10c – .5 hrs., 15 – 2 hrs.

8 hours of Private Pesticide Recertification Credits

Core – 2 hrs.,  Cat 1- 2.5 hrs., Cat 2 – .5 hrs., Cat 6 – .5hrs., Cat 7 – .5 hrs., Cat 15 – 2 hrs.

Registration costs vary due to CUE credits and pesticide applicator credits.

This program is sponsored by The Ohio State University Extension, Advantage Ag & Equipment, B&B Farm Service, Central Ohio Farmers CO-OP, Channel, Clark Seeds, Cubbage Electric, Farmcredit, First-Knox National Bank, and Seed Consultants.

For more information contact the OSU Extension Office in Knox County (740-397-0401).  The following links will provide more information for this program.  http://u.osu.edu/knoxcountyag/ or https://knox.osu.edu/


OSU Extension to Offer Lunch and Learn Webinars

By: Chris Bruynis, Extension Educator

In the age of multi-tasking and convenience, OSU Extension is offering a lunch and learn webinar series for farmers. We have arranged for eight topic and speakers to provide a webinar every Wednesday starting on Wednesday, February 5, 2020 and concluding March 25, 2020. Join us for eight consecutive Wednesdays for this educational series starting at 11:45 am and lasting 1.5 hours. Learn important risk management information during this lunch and learn series from top industry, private sector, and university experts important to the success of farm businesses in 2020 and beyond.

The topics that will be covered include:

February 5:         Using Financial Statements/Ratios to Make Informed Financial Decisions

February 12:      Farm Law 101: Leasing and Financing Agreements

February 19:      Grain Contracts and Markets: What to Use When

February 26:      Where to Start with Workers Compensation Benefits

March 4:             Meeting with a Lender: What Numbers are Important

March 11:           Estate Planning: What are the Tools and Options

March 18:           Grain Marketing Strategies for 2020

March 25:           Tips for Recruiting, Hiring, and Retaining Farm Business Employees

Farmers interested in participating should register at http://go.osu.edu/fm2020 by January 31, 2020.  At this website you can access detailed information on the speakers and the learning objectives for each session. There is also a registration link for the webinar at this site. The cost for all eight topics is $25 per registration and must be paid with credit card at time of registration.

Any question can be directed to Chris Bruynis or Marianne Guthrie at 740-702-3200 or email bruynis.1@osu.edu. We hope this program series will be beneficial to your farm business, whether you attend all the topic presentations or just some of them.

Precision University: Combating Compaction

by: Amanda Douridas, Extension Educator

The fall of 2018 and spring of 2019 created some less than ideal conditions for field work leaving many farmers concerned with field compaction. This concern is justified as compaction can significantly reduce yields. Compaction has been a concern for many years as equipment size grows, increasing axle weight.

Researchers have been conducting on-farm trials comparing farming practices to uncover ways farmers can reduce compaction. Comparisons include tires and tracks, equipment size and tillage practices. At the 2020 Precision University, OSU Extension has invited in some of the leading experts from across North America on compaction research and management.

Featured Speakers include:
Dr. Scott Shearer -The Ohio State University
Dr. Ian McDonald -Ontario Ministry of Agriculture
Dr. Mark Hanna -Iowa State University
Dr. Jason Warren -Oklahoma State University

We have also moved the event to the Champion Center at the Clark County Fairgrounds outside Springfield. This facility allows us to feature equipment demonstrations in a heated environment and enables exhibitors to display the latest in technology from their companies. We’re excited to get our hands dirty with some compaction demonstrations involving different types of equipment!

Details including online registration and hotel information can be found at go.osu.edu/precisionu. The registration deadline is January 3 and the cost to attend is $50. This includes breakfast, lunch and giveaways.

Sponsors and exhibitors include Camso, Soucy, Green Field Ag, Capstan Ag, Apple Farm Service, Precision Ag Reviews, Ag Info Tech, Mosaic, and Agro Chem.

Change Your Employee Recruitment and Interview Mindset

by: Rory Lewandowski, Extension Educator Wayne County

Originally written for Dairy Excel column for the 10-31-19 Farm and Dairy

Labor is an important component of any farm operation.  Beyond just checking the box that a certain task has been completed, farm profitability often turns on how well a task was completed, the attention to detail and protocol.  Improving employee recruiting and interviewing skills increases the chance of hiring the right employee for your farm situation.  For many farms, employee recruitment, interviewing and hiring requires a mindset adjustment.

How do you attract dependable farm employees? What is your goal and objective when you hire a farm employee?  I once heard Bernie Erven, professor emeritus of The Ohio State University, and human resource management specialist, say that too many farms do not manage the employee recruitment and interview process.  Desperate for labor, the only job requirement seemed to be that the person could walk and breathe.  Interview questions consisted of “Have you worked on a farm before? and Do you want the job?”  A management mindset involves developing a recruitment strategy and a process to find employees that are the right fit for your farm.  Donald Cooper, an international management consultant, says that businesses become what they hire.  If your goal is high performance and excellence, you need to recruit and hire above average, high quality persons.

Employee recruitment starts before there is a job vacancy.  Effective recruitment has both an outward and an inward focus.  An outward focus is about developing relationships with persons, organizations and institutions that could provide a contact or recommend a potential employee to the farm.  Some examples include FFA chapters/advisors, career centers, and farm service persons such as veterinarians, feed and equipment dealers, technicians and ag lenders.  In Wayne and surrounding counties, OSU-ATI is an obvious source of potential farm employees.  If you run into someone with the potential to be a good employee, even if you currently don’t have a vacancy, at least collect contact information.  Some farms may even create a temporary position for the person.  Inward recruitment focus is about building a reputation as a great place to work.  If someone were to drive around the county and ask the question, who is the best farm to work for, would the questioner hear the name of you or your farm?

The next important piece in recruitment and interviewing is the job description. Job descriptions guide the interviewing and hiring process.  Specific information included in a job description includes a job title, a short summary of the major job responsibilities, the qualifications for the job including knowledge, education and/or experience necessary, the specific job duties/tasks along with the frequency with which each needs to be performed, who supervises the job and/or supervisory requirements of the job and finally, something about the expectations for hours and weekly or monthly work schedule.

The job description, when well written, helps to provide a prepared list of questions for the employee candidate interview.  Questions should provide the candidate with the opportunity to talk about their skills, knowledge, experience, and personal attributes that match the job description.  According to Bob Milligan of Dairy Strategies, the interview should be designed to determine the qualifications of the candidate, their fit for not only the job requirements but also their fit within the culture of your farm.  The interview should be structured so that the farm owner or manager is promoting the farm and the position in a positive light so that the candidate is likely to accept the job if it is offered to them.

Ask questions that provide you with information about the candidate’s knowledge, ability and attitudes.  Examples of these type of questions are; what are two practices in the milking parlor that can improve milk quality?  Describe an equipment related problem you have solved in the past year.  How did you go about solving it?  I read an article by the founder of a company called Ag Hires entitled “Top 3 Interview Questions Every Farm Should Ask”.  They are: 1. In your past jobs, of the various tasks, roles and projects, what have you enjoyed doing the most and what have you enjoyed the least?  2. What is your superpower; what is it that you are naturally good at and bring to the table wherever you work?  3. If we spoke to your co-workers and managers and asked them what’s it like to work with you, how would they describe you?

These questions are designed to learn what the candidate is passionate about, what they enjoy, what they have a natural tendency toward, and how they interact with others.  Quoting that article, “farm managers have a tendency to place too much emphasis on someone’s work history and not enough emphasis on whether the person is the right fit for the farm.  Smart people with the right attitude, motivation and natural tendencies that align with the farm culture will get up to speed quickly.”

Every farm hire is an important hire.  Farm managers with employee recruitment and interviewing skills increase the rate of successful hires.

Farm Tax Update to be held in Coshocton County

OSU Extension in Coshocton County is pleased to be offering a Farm Tax Update on Monday, December 2 2019 from 7:00 to 8:37 p.m. at the Coshocton County Services Building – Room 145 located at 724 South 7th Street in Coshocton, Ohio.

OSU Extension Educator David Marrison will provide a Farm Tax Update. We will examine year farm tax strategies and learn more about the new Section 199A deduction for Qualified Business Income.  It is not business as usual in the world of farm taxes. Wrap up the year learning how to better manage your farm taxes.

This program is free & open to the public!  However, courtesy reservations are requested so program materials can be prepared. Call 740-622-2265 to RSVP or for more information.

Farm Bill Meetings to be held across Ohio

Click here for complete article with locations of meetings

Ohio State University Extension and the USDA Farm Service Agency in Ohio are partnering to provide a series of educational Farm Bill meetings this winter to help producers make informed decisions related to enrollment in commodity programs.

The 2018 Farm Bill reauthorized the Agriculture Risk Coverage (ARC) and Price Loss Coverage (PLC) safety net programs that were in the 2014 Farm Bill. While the ARC and PLC programs under the new farm bill remain very similar to the previous farm bill, there are some changes that producers should be aware of.

Farm Bill meetings will review changes to the ARC/PLC programs as well as important dates and deadlines. Additionally, attendees will learn about decision tools and calculators available to help, which program best fits the needs of their farms under current market conditions and outlook.

Enrollment for 2019 is currently open with the deadline set as March 15, 2020. Enrollment for the 2020 crop year closes June 30, 2020. Producers can enroll for both 2019 and 2020 during the same visit to an FSA county office. Producers have the opportunity to elect to either ARC or PLC for the 2019 to 2023 crop years, with the option to change their program election in 2021, 2022, and 2023.

To find out about upcoming meetings, and get information about the Farm Bill, visit go.osu.edu/farmbill2019

Corn, Soybean, and Wheat Yield Trends by Ohio County, 1972-2018

by: Carl Zulauf, Robert Dinterman, and Ben Brown, Ohio State University, November 2019

Click here to access full report complete with figures

Yield growth is the primary source of increased production of crops in Ohio and most of the US.  Most land that can be cropped is being cropped.  Understanding historic yield trends is thus important to an informed understanding of Ohio agriculture.  This article examines trends in corn, soybean, and wheat yields since 1972 at the Ohio state level and across Ohio counties.  These three crops composed 87% of Ohio harvested crop acres in the 2017 Census of US Agriculture.  Trend yield is higher for corn than soybean and wheat, both in terms of bushel / acre and percent of yield.  Trend yields vary across Ohio counties, particularly for corn.  Implications are drawn for Ohio crop agriculture, with a particular point of interest being the implication for the CAUV (Current Agricultural Use Value) program that taxes farm land at its agricultural use value rather than its appraised value.

Analysis:  Yield per harvested acre is analyzed.  Source for the data is USDA, NASS (US Department of Agriculture, National Agricultural Statistics Service).  The analysis starts with the 1972 crop and ends with the 2018 crop.  It spans 47 years that include periods of prosperity, financial stress, and tight profit margins.  Not all counties have 47 years of observations for each crop.  It was decided a county should have at least half or 24 years of observations to be included in the analysis.  This decision reflects (1) consideration of the power of statistical tests, (2) that 24 years is a “natural break” in the distribution of number of county yield observations, and (3) a feeling that it seems reasonable to require yields for at least half of all years in order to have confidence in a county’s estimated trend yield.  Counties with 24 years of harvested yields total 86, 78, and 69 for corn, soybeans, and wheat, respectively.  The county yield trends were tested for statistical difference from the yield trend for Ohio.  For additional discussion of the analytical procedures, see the Data Note.

Corn Yield Trend:  Ohio linear corn yield trend is +1.76 bushel / year over 1972- 2018 (see Figure 1).  In comparison, average of the 86 county yield trends estimated for corn is +1.62 bushel / year.  Since the state yield is the average of county yield weighted by the amount of production in the county, the higher state trend yield suggests counties with more corn production had a higher yield trend.

County corn yield trend ranged from +0.66 (Carroll County) to +2.14 (Clinton County) (see Figures 1 and 2).  When examining the range of values, it is useful to assess if the extreme values are outliers.  Examination of the county corn yield trends suggests that both Carroll and the county with the next lowest trend (Belmont – +0.71) are outliers as the next lowest yield trend is +1.09 for Monroe County.

Individual county yield trends were tested for statistically significant deviation from Ohio’s yield trend (see Date Note).  Thirty-five (41%) of county corn yield trends deviated from the state yield trend with the commonly-used 95% level of statistical confidence (see Figure 2).  Corn yield trend was above (below) the state corn yield trend in 9 (26) counties.  It was thus almost three times more likely for statistically significant county yield trends to be below than above the Ohio trend yield. Counties with a statistically significant lower trend have a tendency to be in eastern Ohio (see Figure 2).  Statistically significant higher corn yield trends have a tendency to be in southwestern and central Ohio.

Soybean Yield Trend:  Ohio linear soybean trend yield is +0.48 bushel per year over 1972-2018, the same as the average of the 78 county trend yields estimated for soybeans (see Figure 3).  Unlike corn, this comparison does not suggest county soybean yield trend varied with amount of county production.

County soybean yield trend ranged from +0.23 (Lawrence County) to +0.59 (Fairfield County) (see Figures 3 and 4).  Lawrence County may be an outlier as the next lowest soybean yield trend was Summit County at +0.30 bushel per year.

Statistically significant deviation from the state yield trend was far less common for soybeans than corn.  Only 10 (13%) of county soybean yield trends deviated from the state yield trend with 95% statistical confidence (see Figure 4).  Five were below and 5 were above the state trend.  The small number of counties with statistically significant deviations from the state yield trend calls for caution in making regional categorization of these deviations.  Given this caveat, the 5 counties with trend yield above the Ohio trend yield are in central Ohio.

Wheat Yield Trend:  Ohio’s linear wheat yield trend is +0.76 bushel per year over 1972-2018, nearly identical to the average of the 69 county yield trends estimated for wheat (see Figure 5).  Similar to soybeans and unlike corn, this comparison does not suggest wheat county yield trend varied with amount of county production.

County wheat yield trend ranged from +0.38 (Carroll County) to +0.98 Pickaway County) (see Figures 5 and 6).  There did not appear to be any obvious outlier county wheat yields.

Twenty (29%) of the county wheat yield trends deviated from Ohio’s wheat yield trend with 95% statistical confidence (see Figure 6).  As with corn, it was more common for a county yield trend that differed from the Ohio yield trend with statistical significance to be above than below Ohio’s trend (13 vs. 7).  No clear regional category of deviations from the state wheat trend yield is apparent.  Counties with significant deviations from the state trend are dispersed across Ohio (see Figure 6).

Comparing Yield Trend across Crops:  Comparing yield trend across corn, soybeans, and wheat is complicated by their different yield levels.  Given the use of regression analysis, one useful measure of yield level is the estimated intercept value for 1972.  These intercepts for Ohio corn, soybeans, and wheat are 87, 29, and 40 bushels/acre, respectively.  Taking the ratio of Ohio trend yield to the Ohio intercept finds that yield grew fastest for corn (2.0%) and slowest for soybeans (1.7%) (see Figure 7).  The difference may seem small, but it is an annual difference that has extended over 47 years.

Another useful comparison is to examine the relative variation in county yield trends by crop.  One such measure is the ratio of the standard deviation of county yield trends to the average county yield trend.  Using the values in Figures 1, 3, and 5, the so-called coefficient of variation ratio is 18% for corn, 12% for soybeans, and 16% for wheat.  Eliminating the two outlier county yield trends for corn reduces its coefficient of variation to 15%.  The coefficient of variation thus suggests that soybean yield trends varied less across Ohio counties than did corn and wheat yield trends.

Summary Observations:

►   Linear yield trend is higher for Ohio corn than soybeans, with wheat in between.

►   Among the three crops, soybean yield trends differ the least across Ohio’s counties.

►   County yield trends are more likely to deviate from Ohio’s yield trend with statistical significance for corn than for soybeans.

►   Only readily-apparent regional patterns in yield growth are a higher probability of slower yield growth for corn in eastern Ohio and faster yield growth for corn in central and southwestern Ohio.

►   Corn’s differential yield trends have likely differentially impacted profitability of crop agriculture across Ohio’s counties.

►   Statistically significant differences in county yield growth from state yield growth pose a potential policy issue for Ohio’s CAUV (Current Agricultural Use-Value) Program.  CAUV determines assessed value for a majority of agricultural land in Ohio.  It uses a net-income approach partially based on a soil type’s yield potential for corn, soybeans, and wheat.  Potential yield for a soil type partially comes from the state’s most recent comprehensive soil survey (Zobeck, Gerken, and Powell, 1983). This yield value, from the early 1980s, is then adjusted based on the state-wide trend in harvested yield for each of the three crops.  The significant differences between county and state-wide yield trends raises the potential issues of whether or not the use of state-wide yield trends to adjust a soil productivity index dating to the early 1980s continues to be appropriate policy and thus if an update of the soil productivity index may be an appropriate policy option.

Data Note:  The statistical method used for this analysis is multiple linear regression.  Unit of observation is a county-year in Ohio from 1972 to 2018.  Statewide yield is included as well.  Dependent variable is county yield (for corn, soybeans, or wheat) for a given year.  It is regressed on time, measured as a count of years starting with 1972 equal to zero.  A county specific intercept and a county specific annual trend are estimated.  The statistical test of interest is if a county specific annual yield trend is statistically different from the statewide annual yield trend for a given crop.  Since the county specific annual trend and statewide annual trend are both estimated coefficients, an F-Test is constructed with the null hypothesis that the two trend coefficients are equal to each other.  An F-test rejection of a null hypothesis is a function of both the difference between the two estimated coefficients and the estimated standard error of the coefficients.

References and Data Source:

US Department of Agriculture, National Agricultural Statistics Service.  (April 2019).  2017 Census of Agriculture:  United States  Summary and State Data. Volume 1, Geographic Area Series, Part 51.  AC-17-A-51   www.agcensus.usda.gov

Zobeck, TM, JC Gerken, and KL Powell. 1983. “Ohio Soils with Yield Data and Productivity Index.” Ohio State Univeristy Cooperative Extension Service.  Bulletin 685.

The Case for Looking at the ARC-IC (ARC-Individual) Program Option

by: Carl Zulauf and Ben Brown, Ohio State University, and Gary Schnitkey, Krista Swanson, Jonathan Coppess, and Nick Paulson, University of Illinois at Urbana-Champaign, October 2019

Click here for the complete article as PDF

ARC-IC (Agriculture Risk Coverage – Individual) has received less attention than ARC-CO (ARC – County) and PLC (Price Loss Coverage).  ARC-IC is operationally more complex, thus harder to explain and understand.  It pays on only 65% of program base acres while ARC-CO and PLC pay on 85% of base acres.  Nevertheless, ARC-IC is worth considering if an FSA farm has one or more of the appropriate production attributes.  These attributes include (1) 100% prevent plant acres on a FSA farm, (2) high year-to-year production variability, (3) much higher farm than ARC-CO and PLC yields, and/or (4) acres planted to fruits and vegetables.  The prevent plant attribute is more relevant than normal in 2019.

ARC-IC Overview

►   ARC-IC is a whole farm program option based on the average experience of all covered program commodities planted on the ARC-IC farm.

►   ARC-IC applies to all base acres of all covered commodities on an ARC-IC farm.  It is not elected on a commodity-by-commodity basis.

►   An ARC-IC farm is the sum of a producer’s share in all FSA farms he/she enrolls in ARC-IC in a state.

►   All payment entities on an FSA farm must elect to enroll in ARC-IC.

►   ARC-IC makes a payment if average actual revenue/acre of all covered commodities planted on the ARC-IC farm is less than 86% of the ARC-IC farm’s average benchmark revenue/acre.

►   Revenue/acre for a covered commodity and year is (ARC-IC farm yield times US market year price).

►   ARC-IC farm benchmark revenue/acre equals the sum of the 5-year Olympic average revenue/acre for each covered commodity weighted by current year acres planted to a covered commodity.

►   ARC-IC actual revenue/acre equals the sum of actual revenue/acre for each covered commodity that was planted weighted by current year acres planted to a covered commodity.

►   Payment is made on 65% of total base acres on an ARC-IC farm times ARC-IC payment/acre.

►   Payment/acre is capped at 10% of the ARC-IC farm benchmark revenue/acre.

►   NOTE: Payment depends on program commodities that are planted.

►   NOTE: Prevent plant acres are included in ARC-IC revenue calculations ONLY IF 100% of an ARC-IC farm’s initially reported covered commodities are approved as prevent plant.

►   NOTE: Only initially planted covered commodity and approved double crop acres are included in the revenue calculations.  Any subsequently planted crops are not included in the calculations.

When ARC-IC should be considered:  A farm production attribute must compensate for ARC-IC’s fewer payment acres (65% vs. 85% of base acres for ARC-CO and PLC).  Such attributes include:

(1)  All of an ARC-IC farm’s initially planted covered commodities are approved as prevent plant.  Current year revenue is zero since production is zero, resulting in a payment/acre equal to the payment cap of 10% of ARC-IC benchmark revenue/acre.  In contrast, if any acre is planted to any covered commodity, payment is based on revenue/acre for the planted acre(s).  Given the prevalence of prevent plant acres in 2019, examples are provided below.  To underscore the key point, payment in this situation requires the ARC-IC farm has prevent plant for all covered program commodities on all base acres.

(2)  Production is highly variable from year to year on the ARC-IC farm.  High variability increases the likelihood of ARC-IC payment.  High variability is most likely when1 crop is grown and 1 FSA farm makes up the ARC-IC farm.  ARC-IC averages across crops and FSA farms.  Variability declines as more than 1 crop is grown and/or more than 1 FSA farm makes up the ARC-IC farm.

(3)  ARC-IC benchmark yield is (much) higher than ARC-CO benchmark yield and PLC farm payment yield.  Assuming 1 covered commodity and same percent payment rate for both ARC programs, ARC-IC benchmark yield needs to be more than 30% higher than the county benchmark yield for ARC-IC to pay more than ARC-CO.  Other situations result in different breakeven yields.

(4)  Fruits and vegetables (other than mung beans and pulse crops) or wild rice are planted on a FSA farm.  Payment base acres are 65% for ARC-IC vs. 85% for ARC-CO and PLC.  Non-payment acres are the remaining base acres:  35% for ARC-IC vs. 15% for ARC-CO and PLC.  Payment is reduced if fruits and vegetables (other than mung beans and pulse crops) or wild rice are planted on more than the non-payment acres.  ARC-IC has more acres that can be planted to fruits and vegetables (other than mung beans and pulse crops) or wild rice without losing program payments.  Note, base acres on the FSA farm are not altered in this situation.

ARC-IC Examples – role of prevent plant – Overview:  An ARC-IC farm with all yield information needed to calculate the ARC-IC benchmark revenue is assumed.  This information plus the US market year average price for crop years 2013-2017 and 2019 are in the top half of each table of values for each example.  The farm has 100 acres of cropland and program base, both composed of 60 acres of corn and 40 acres of soybeans.

Calculation of the ARC-IC benchmark revenue is a 3-step process.  In step 1, per acre revenue is calculated for each covered commodity (corn and soybeans in this case) for each of the 5 years in the benchmark calculation window.  In step 2, the Olympic average revenue per acre is calculated.  An Olympic average removes the high and low value before calculating the average of the remaining values.  For the example ARC-IC farm, the Olympic average revenue is $605 for corn and $475 for soybeans.  In step 3, the Olympic average revenues are weighted by the acres planted in the current year (2019 in this case) to covered commodities to determine an ARC-IC farm average revenue per acre.  This calculation for the example ARC-IC farm is:  (($605*60) + ($475*40)) / (60+40), or an ARC-IC benchmark revenue of $553 / acre.

ARC-IC Example 1 – no prevent plant acres:  Actual revenue / acre is $631 (166 bushels / acre times $3.80 / bushel) for corn and $423 (47 bushels / acre times $9.00 / bushel) for soybeans (see Table 1).  These individual crop values are weighted by acres planted to each covered commodity, resulting in an actual revenue / acre for the ARC-IC farm of $548 (($631*60) + ($423*40)) / (60+40).  Since actual revenue of $548 / acre exceeds the ARC-IC coverage revenue of $476 / acre (86% ARC-IC coverage level times benchmark revenue of $553 / acre), ARC-IC makes no payment.

ARC-IC Example 2 – some prevent plant acres: This example has 20 acres of corn prevent plant acres and lower 2019 yields (see Table 2).  Actual revenue / acre is $570 (150 bushels / acre times $3.80 / bushel) for corn and $378 (42 bushels / acre times $9.00 / bushel) for soybeans.  These individual crop values are weighted by acres planted to each program commodity, resulting in an actual revenue / acre for the ARC-IC farm of $522 (($570*60) + ($378*20)) / (60+20).  Only 80 acres is used in calculating actual ARC-IC revenue.  The 20 prevent plant acres are not included in calculating ARC-IC actual revenue.  Since actual revenue of $522 / acre exceeds ARC-IC coverage revenue of $493 / acre (86% ARC-IC coverage level times benchmark revenue of $573 / acre), ARC-IC makes no payment.  ARC-IC benchmark revenue and coverage revenue is higher in Example 2 than Example 1.  The reason is the combined impact on the weighted averages of (a) higher revenue per acre for corn than soybeans and (b) fewer acres planted to soybeans (20, not 40).

ARC-IC Example 3 – all prevent plant acres:  This example has no planted acres, with all initial planted covered commodity acres approved for prevent plant (see Table 3).  Actual revenue / acre is $0 since no initial covered commodity is planted.  Because no acres are planted to covered program commodities and all acres of initial planted covered commodities are approved as prevent plant, a benchmark revenue exists.  It equals the benchmark revenue in example 1 ($553 / acre).  ARC-IC makes a payment since actual revenue of $0 / acre is less than the ARC-IC coverage revenue of $476 / acre (86% ARC-IC coverage level times benchmark revenue of $553 / acre).  Payment is however capped at 10% of the benchmark revenue, or $55 per base acre ($553 times 10%).  Total ARC-IC payment is $5,500 ($55 per base acre times 100 base acres).

Summary Observations: 

►   Crop program choice rests on the production attributes of an FSA farm.

►   ARC-IC may be worth considering more often than commonly thought.

►   Farm production attributes which make ARC-IC potentially attractive include:

  • 100% of program base acres on a FSA farm are prevent plant acres,
  • high production variability from year to year on a FSA farm,
  • much higher farm than county or PLC yields on a FSA farm, and
  • fruits and vegetables are planted on a FSA farm.

►   If prevent plant is the production attribute of interest, all covered commodity acres on the ARC-IC farm must be prevent plant for ARC-IC to make a payment.

►   If high production variability is the production attribute of interest, ARC-IC is more attractive if only 1 FSA farm in a state with only 1 program commodity is elected into ARC-IC.  ARC-IC pays on the average experience across all program crops on all FSA farms in the ARC-IC farm.  Averaging across multiple crops and FSA farms usually reduces variability and thus payment probability.

►   Program sign up is for 2019 and 2020.  Expected payments in both years need to be considered for ARC-IC, ARC-CO, and PLC.  It is highly possible that the program with the highest expected payment will differ for 2019 and 2020, especially if ARC-IC has the highest expected payment for one year.

►   This article is not an argument for electing ARC-IC.  It is an argument for not dismissing ARC-IC without thinking about the individual FSA farm production attributes.


Table 1.  ARC-IC Example 1 – no prevent plant acres
  corn corn corn beans beans beans corn beans corn beans ARC-IC
yield MYA ARC-IC yield MYA ARC-IC plant plant prevent prevent farm
price revenue price revenue acres acres plant plant per
year / calculation acres acres acre
2013 155 $4.46 $691 43 $13.00 $559 60 40 0 0  
2014 169 $3.70 $625 47 $10.10 $475 60 40 0 0
2015 166 $3.61 $599 48 $8.95 $430 60 40 0 0
2016 172 $3.36 $578 52 $9.47 $492 60 40 0 0
2017 174 $3.40 $592 49 $9.33 $457 60 40 0 0
2019 166 $3.80 $631 47 $9.00 $423 60 40 0 0
Olympic average (’13-’17) $605 $475
benchmark revenue $553
revenue coverage (86%) $476
actual revenue $548
revenue loss $0
payment $0
total ARC-IC payment                     $0






Table 2.  ARC-IC Example 2 – some prevent plant acres
  corn corn corn beans beans beans corn beans corn beans ARC-IC
yield MYA ARC-IC yield MYA ARC-IC plant plant prevent prevent farm
price revenue price revenue acres acres plant plant per
year / calculation acres acres acre
2013 155 $4.46 $691 43 $13.00 $559          
2014 169 $3.70 $625 47 $10.10 $475
2015 166 $3.61 $599 48 $8.95 $430
2016 172 $3.36 $578 52 $9.47 $492
2017 174 $3.40 $592 49 $9.33 $457
2019 150 $3.80 $570 42 $9.00 $378 60 20 20 0
Olympic average (’13-’17) $605 $475
benchmark revenue $573
revenue coverage (86%) $493
actual revenue $522
revenue loss $0
payment $0
total ARC-IC payment                     $0


Table 3.  ARC-IC Example 3 – 100% prevent plant acres
  corn corn corn beans beans beans corn beans corn beans ARC-IC
yield MYA ARC-IC yield MYA ARC-IC plant plant prevent prevent farm
price revenue price revenue acres acres plant plant per
year / calculation acres acres acre
2013 155 $4.46 $691 43 $13.00 $559          
2014 169 $3.70 $625 47 $10.10 $475
2015 166 $3.61 $599 48 $8.95 $430
2016 172 $3.36 $578 52 $9.47 $492
2017 174 $3.40 $592 49 $9.33 $457
2019 0 $3.80 $0 0 $9.00 $0 0 0 60 40
Olympic average (’13-’17) $605 $475
benchmark revenue $553
revenue coverage (86%) $476
actual revenue $0
revenue loss $476
payment $55
total ARC-IC payment                     $5,500


Ohio CAUV Values Projected to Decline Through 2020

The Current Agricultural Use Valuation (CAUV) program allows farmland devoted exclusively to commercial agriculture to be taxed based on their value in agriculture, rather than the full market value, resulting in a substantially lower tax bill for the farmer.

The formula for CAUV values incorporates agricultural factors (soil types, yields, prices, and non-land costs for corn, soybeans, and wheat) to calculate the capitalized net returns to farming land based on the previous 5 to 10 years. CAUV underwent large-scale changes to its calculation in 2017 that was targeted to reduce the property tax burden of farmland.

A new report, Ohio CAUV Values Projected to Decline Through 2020, shows the projection of CAUV values though 2020. According to the study authors, OSU agricultural economists Robert Dinterman and Ani Katchova forecast a decrease in the assessed value of agricultural land to an average CAUV value of approximately $600 in 2020.

Access this report at: