Can cover crops pay? Unraveling yield enhancement on a wide scale to provide incentive for increased adoption.

Progress report for LNC21-456

Project Type: Research and Education
Funds awarded in 2021: $249,942.00
Projected End Date: 02/28/2025
Grant Recipient: Stute Farms
Region: North Central
State: Wisconsin
Project Coordinator:
Dr. James Stute
Stute Farms
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Project Information


Can cover crops pay? Unraveling yield enhancement on a wide scale to provide incentive for increased adoption.

Cover crops (CC) have demonstrated ecosystem services which contribute to sustainability, yet uncertainty over financial benefits and fear of crop yield reduction continue to prevent adoption. Survey results and research data indicate CC use can have a positive effect on yield, yet knowledge of what specific practices increase crop yield and by how much is limited. Our objective is to identify which management practices contribute most to yield response and to what extent, using better data and resulting recommendations to build an argument for increased adoption. This project builds on two past SARE projects, ONC17-034 and LNC15-375.

On-farm trials will be conducted over an agriculturally diverse region of Wisconsin, generating 90 site-years of replicated comparisons of CC management variations against no cover to determine which practices contribute most to yield response, the magnitude and variability of the response and the overall yield response to CC. Cooperating farmers will design their individual trials to answer farm-specific production questions they have, for example “should I increase corn starter N rate when planting green?” In addition to crop yield response, we will collect CC conservation performance data to better credit CCs for their role in erosion and run-off reduction by SnapPlus, Wisconsin’s nutrient management planning software, also increasing incentive for adoption. We will also conduct partial budget analysis to calculate net returns and analyze this data for variability and risk to demonstrate financial incentive.

Our outreach plan relies equally on peer-to-peer information exchange within producer-led watershed protection groups and routine Extension programming, targeting farm advisors. Our state-wide outreach efforts will involve cooperating farmers to share their experiences and insights for events with largely farmer audiences. With increased knowledge of documented CC impacts on yield and net return as well as best management practices (BMPs) to maximize them, farmers will increase adoption. The increase in CC use will lead to improved farm profitability through crop revenue and improved water quality trade credits, improvements in soil health and water quality and a more bucolic landscape.


Project Objectives:

Learning outcomes: Increased knowledge of CC impacts on crop yield response, net return, and risk; increased knowledge of BMPs to maximize yield response and net return.

Action outcomes: Increased CC adoption, CCs managed for maximum return and ecosystem services, improved crediting of CC contribution to soil and P loss reductions in SnapPlus nutrient management plan estimates, use of data in agricultural lending decisions and crop insurance program revisions.

Systems changes: Improved farm profitability through crop revenue and improved water quality trade credits, improvements in soil health and water quality and a more bucolic landscape.


Cover crops (CC) are an integral part of sustainable systems with combined roles of maintaining productivity, protecting the resource base, and improving the environment. The ecosystem services of appropriately chosen and managed CCs are well documented (Blanco-Canqui et al., 2015), farmer interest in their use, especially as it relates to soil health continues to grow (Smith and Meyers, 2020) yet Midwestern adoption continues to be limited (USDA, NASS), limiting sustainability advances. Efforts to explain or address this disconnect have consistently found economic issues, real or perceived as the major barrier to adoption (Smith and Meyers, 2020; Bergtold et al., 2017; Arbuckle and Roesch-McNally, 2015; Carlson and Stockwell, 2013). Conversely, Bergtold et al. (2017) suggest economic impact is likely to be the strongest adoption driver, the case simply needs to be made in a convincing manner.

The most recent CTIC/SARE Cover Crop Use Survey (2019-2020) qualifies the barrier. Major reasons for non-adoption are no documented, direct economic benefits (i.e., return on investment) and the fear of potential yield reductions. Our SARE funded experience with conservation professionals in Wisconsin (ENC15-150) further validate these concerns. It also suggests current users intend to continue, citing direct financial benefits of crop yield response and reduced input costs as well as less quantifiable soil benefits. However, a full quarter of them plant on 20% or less of their acreage, leaving room for improvement and providing indirect evidence of financial barriers; if they profess buy-in, why not go full-in?

Recent midwestern work has addressed the economic barrier at the enterprise level through partial budget analysis, comparing CC systems with no cover for additional costs and returns based on response crop performance [Thompson et al., 2020; Plastina et al., 2018 (SARE Project LNC15-375)]. Using different data gathering approaches, both documented consistently reduced net returns for CC systems (negative relative to no cover) when cost-share or other financial assistance was excluded. They conclude that negative or modest crop yield responses are the major limiting factor for producing a positive return. Additionally, this work suggested CC cost containment strategies to increase potential for positive net return when yield response is positive. Our work in Wisconsin (SARE ONC17-03) drew similar conclusions. Even with a positive yield response in 71% of cases, neutral or positive net return was achieved in only 14% of cases under existing market conditions (as a stand-alone practice without cost-share incentive) using low-cost cover systems. This underscores the importance of yield response maximization.

Yield response results and conclusions from formal research are mixed but demonstrate potential for increased yield. In an updated meta-analysis of corn yield response to winter covers (WCC), Marcillo and Miguez (2017) found they didn’t reduce yield if properly managed. This analysis included 65 studies conducted in the U.S. and Canada, 28 studies (2004-2015) since the first analysis and noted a trend towards smaller yield responses with time as work has shifted from legumes (Southern) to grasses (Mid-Western). They identified region, species, N management, termination timing and tillage as significant factors contributing to yield response. The proper management statement is important because it implies experience with CC use and management. Plastina et al. (2018) reported declining yield reduction or even positive yield response with increasing user experience. In a review of temperate region ecosystem services, Blanco-Canqui et al. (2015) also examined yield effects and found neutral or positive impacts in 88% of cases, identifying the same contributing factors as well as site cover crop history, indicating a need to identify and separate first-year and cumulative effects. 

Subsequent Midwestern studies(1) exemplified by Dozier et al. (2017) and Patel et al. (2019) also report mixed results and suggest yield response could be improved with changes in CC management. Other authors argue for practice differentiation to identify BMP’s (Reed et al., 2019; Basche and Roesch-McNally, 2017; Delgato and Gantzer, 2015) but work is limited in the Midwest. We also observed differential yield responses in nearly identical systems and environments in project ONC17-034, begging the questions of what really causes yield response and more importantly, how can we enhance it? 

We focus on these studies because several authors suggest conclusions and recommendation should be made on a regional basis to capture the unique regional characteristics (soil types, growing season conditions including precipitation etc.) and constraints which impact CC performance and crop response (Plastina et al., 2020; Miner et al., 2018; Blanco-Canqui et al., 2015). These authors also note that the focus on increased yield does not come at the expense of ecosystem services.

Formation of producer-led watershed protection groups (PLWPG) is a recent phenomenon in Wisconsin. These groups voluntarily address watershed resource concerns as a socially minded objective but also to gain “license to farm”, improved public approval which facilitate positive local interactions. PLWPGs facilitate conservation practice implementation through outreach efforts, group learning and peer mentoring. As such, they augment efforts of conservation agencies and may accelerate conservation implementation due to peer trust factors. Most groups focus on soil health and offer cost-share programs for CC. Example groups, involved in this project include:

Watershed Protection of Racine County (WPCRC)

Jefferson County Soil Builders

Farmers on the Rock

Dodge County Farmers for Healthy Soil- Healthy Water (DCFHSHW)

Work with these groups is a key strategy to facilitate adoption. In addition to their overall enthusiasm for CCs, research shows farmers learn best from each other, individually and in small groups, and technology transfer is most effective locally-especially when information contains local data (Hoffman et al., 2007) and a high percentage of farmers participating in on-farm research will adopt a successful practice, driven by profit (Thompson et al., 2019). Farmers also engage with networks to resolve CC management issues (Roesch-McNally et al., 2017), drawing on local-practitioner expertise.


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  • Tom Novak - Technical Advisor
  • Tom Novak
  • Scott Fleming - Technical Advisor
  • Scott Fleming
  • Bill Stangel - Technical Advisor
  • Tony Peirick
  • Charlie Hammer
  • Mark Holl
  • Cyndi Pitzner
  • Nick Kau
  • Tyler Troiola
  • Dean Weichmann
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  • Rob Mawhinney



Crop yield response to cover crop will be affected by cover crop management through influences on soil moisture, biomass production, soil health and condition at planting etc. By measuring yield response over multiple management systems and environments, the factors which most influence it will become apparent.

Materials and methods:

This project works directly with PLWPGs, gathering data from a series of on-farm trials conducted by their member farmers in partnership with professional crop consultants. The consultants have existing relationships with some member farmers and either serve directly on the PLWPG Executive Committees or are of council, providing regular programming guidance. The Projects relationship with PLWPGs is key for our outreach efforts, more deeply expanding our outreach to the farming community, relying on farmers for peer-to-peer learning and capitalizing on their enthusiasm for conservation. Our relationship with the consultants is also important for information dissemination and advocacy because their client base is larger than the PLWPG’s they serve. Additionally, we are providing outreach through routine Extension programming and our collective service to several statewide boards and committees.

Our cooperating farmers range in CC experience level from little to intermediate, allowing us to investigate first year and cumulative effects. At the individual farm level, trials are investigating practices to address the farmers specific questions. For a beginner, it may be “can I plant at a lower rate and still get a benefit?”, comparison: low vs recommended rate. For the experienced practitioner, questions could be “is the benefit of planting green worth the extra trip and herbicide expense?” or “can I roll-crimp for termination after the crop has emerged?”, the comparison in both cases is: preplant vs. postemergence termination. In aggregate, data from these individual trials will allow us to determine the overall yield effect, separate first-year from cumulative effects, identify practices/ factors which contribute most to yield response and calculate net return.

We limit CC systems to those most common in the region and not allow a species comparison. Cropping systems include:

  1. Cover with/after soybean-corn
  2. Cover with/after corn-soybean
  3. Cover with/after corn silage-rotational crop
  4. Cover with/after wheat-corn.

Limiting systems to those most representative of the region allows us to focus resources for the greatest possible impact. Species comparisons are disallowed because that work may have been done (from a CC performance standpoint), the results won’t contribute to identification of management factors, and more importantly, non-adapted species will skew results.

Research objectives:

  1. Determine the impact of CC use on yield of the subsequent crop and the crop which follows;
  2. Separate first-year and cumulative yield effects to determine the immediate impact of CC use;
  3. Determine which practices maximize yield response to develop BMP recommendations;
  4. Calculate net return to CC using partial budget analysis and estimate variability of return, risk;
  5. Collect CC conservation performance data to refine soil/nutrient loss estimates in SnapPlus;

Yield Response Research

We are conducting 30 strip-trials annually (90 site-years of data total), using a simple treatment design of +/- CC with a management variable that is a variation on either CC culture or management within the response crop, creating two cover systems.

Treatment 1: No cover, control

Treatment 2: Cover 1, base cover crop system

Treatment 3: Cover 2, variation on base system.

Cover crop planting rate and termination timing (fall vs. spring) are examples of cultural variables. Traditional burn-down vs. green planting or differential starter N application rates within a green planting system are examples of response crop management variations.

Cooperators define their treatments based on considerations discussed above. Individual trials have a minimum of three replicates generating at least 270 paired comparisons of response data within a single comparison. Comparisons are multi-dimensional within an individual site and include: cover (in aggregate) vs. no cover; cover 1 vs. no cover; cover 2 vs. no cover and cover 1 vs. cover 2 giving us a minimum potential total of 1,080 individual paired comparisons.

Field length trials are randomized and blocked based on field characteristics (soil type, topography) to insure between plot uniformity to the extent possible while capturing field variability.  Plot width is dictated by width of planting equipment. Harvest width is one-half of plot width and yield measured from the plots center rows to eliminate border effects. This scheme fits most farms because harvest equipment size is normally one-half of planting width.  Where equipment widths match, plot width will be twice equipment width and the center harvested for yield determination.

From our on-farm experience, we anticipate the most cooperators use precision agriculture technology in some form, enabling them to overlay second- and third-year measurements on the initial trial, allowing the project to further separate first-year and cumulative effects. This will also allow the cooperator to self-investigate 2nd year effects using their yield monitor (methods discussed below).

Each experimental cycle is conducted on separate, independent fields. This will result in measurement of all first-year effects for non-users and all cumulative effects for current users. The ability of cooperators to measure 2nd year effects without assistance may facilitate continuation of the trials beyond the scope of this project. At a minimum, the project will collect 2 cycles of second-year effect data and will encourage cooperators to submit the third. This is not a stretch given the relationship of project consultants with the watershed groups. Documenting positive 1st and 2nd year effects is key for adoption on leased cropland.

Trials were initiated in fall 2021. Cooperators follow their routine cultural practices related to cover and response crops. In-season diagnostic tests (PSNT etc.) are conducted where variables include a nutrient component to enrich the dataset and provide possible explanations when treatment differences exist. Each site is sampled for routine soil fertility at CC establishment.

Yield is determined from grain weight (preferred) or by calibrated combine yield monitor, using methods of the UW Discovery Farms Program ( ). Accuracy of weighing equipment or yield monitor calibration is certified by the project consultant before harvest. Grain moisture and test weight are determined independent of monitoring equipment.

Cooperating farmers  maintain and submit the following records to the project:

Cover crop:

Planting date(s), planting rate(s), variety (if applicable), termination date(s), additional management operation date(s).

Response crop:

Planting date and rate, hybrid/variety (with relative maturity), N rate(s), N application (timing, material, method), starter fertilizer (rate and material), P/K application (materials, rate(s), date(s), method, seed treatments, and pesticides (product, rate, adjuvant(s), application date and method).

Input/output data:

Grain price (harvest date local spot or contracted), interest rate (operating), drying and hauling cost ($/bu.), CC seed cost ($/unit), CC field operation costs($/a).

Agronomic records are used in the analysis to help qualify and interpret results. Growing season (April 1-Oct. 31) precipitation data is collected using standardized CoCoRaHS gauges (Productive Alternatives, Fergus Falls, MN) where possible. Project consultants are responsible for scouting and collecting in-season data (emergence date(s), final stand, harvest population) as well as tissue and/or soil sampling where trials have a nutrient component.

Input records are bundled by case (individual on-farm trial) with agronomic and yield data and subjected to economic analysis.

Cover crop conservation performance

Above ground biomass and canopy development (as % ground cover at termination) data will be added to the Wisconsin database which the SnapPlus Development Team is using to calibrate its soil erosion estimations.

Three 0.5 m2 samples are taken per plot and air dried (60oC to constant weight) to determine DM yield. For trials with a nutrient component, samples will be analyzed for total C/N using dry combustion methods with a Flash EA 1112CN Automatic Elemental Analyzer (Thermo Finnigan). Data from trials with differential termination timing will be combined to estimate species specific growth curves and average daily DM accumulation. Percent canopy is estimated concurrently by fractional green canopy cover using Canopeo (Patrignani and Ochsner, 2015), 5 estimates per plot.

SnapPlus uses the Revised Universal Soil Loss Equation 2 (RUSLE2) to estimate erosion and as a component of phosphorus runoff loss estimates (WI P Index).  Data will be used to calibrate potential biomass production within RUSLE2 by planting date, CC type and termination timing.

Data analysis and use

Data is analyzed by site to provide farm-specific information to the cooperator, in aggregate to estimate the magnitude and variability of response and within CC system to determine which specific practice(s) promote the greatest response as well as response variability to determine risk. Data is transformed to response ratio (yield following cover/ yield following fallow) for the combined analysis to normalize soil yield potential differences where appropriate.

Individual farm trials are complete, balanced 3-year experiments with a randomized complete block design. Data is analyzed by ANOVA to determine significant main effects and interactions. Orthogonal contrasts are used to compare CC vs. no cover, and response expressed as a % of no cover. Individual site characteristics will inform conclusions from the data. This includes approximate site temperature data sourced from PRISM ( which is also used for precipitation data if not provided by the cooperating farmer or project fields are more than one-half mile from their gauge.

Combined data will be subject synthesis analysis, following methods similar to those of Mourtzinis et al. (2018) using a combination of ANCOVA and regression tree analysis. This hierarchical approach will allow separation and ranking of factors contributing to yield response including first-year and cumulative effects leading to BMP recommendations. 

Financial data

Agronomic data and input/output information will be used to conduct partial budget analysis by Case, accounting for cost and return differences between systems to calculate a net return for each CC system, compared to fallow on a per acre basis. The analysis will include additional costs for CC establishment, management, termination, and interest (constant costs) and costs associated with additional crop yield including drying, hauling, and nutrient removal (yield-dependent costs). Returns to CC include additional crop yield and the value of a N credit (if applicable). Any cost-share incentive payments will be excluded from the analysis. Actual market prices, tied to each response cycle will used in this analysis. Return on investment (ROI) will be calculated as is and on an annualized basis to compare each cover system to no cover and CC management systems to each other.

Data will be aggregated and analyzed by methods similar to yield response, identifying the most profitable CC systems and quantifying risk associated with each.


Our outreach plan has two primary audiences, farmers, and their advisors. It is designed to leverage our direct efforts (field days and routine Extension programming) through peer-to-peer learning using PLWP groups as the outreach mechanism and through consultation/ information sharing between agricultural advisors and farmers. Advisors are the primary audience for routine Extension programming.

Initial outreach activities will focus on PLWPG summer field-days (5 per year) and concentrate on creating awareness about the project and its forthcoming results as well as generating internal interest and discussion. Cooperating farmers will host the field-day in conjunction with their respective PLWPG and share their experiences and results to date. Project representatives will also share whole project results and insights including nitrogen use efficiency and P runoff findings from a companion UW Discovery Farms-WPCRC project (see collaboration, Team section).

Upon completion of the research component, emphasis will shift to sharing results and recommendations. At the PLWPG level, this will be done at formal winter meetings/ conferences with a combination of individual cooperators sharing their farm results/experience and the project sharing whole project information. We will use the same format at State-level events which have a primary farmer audience, with select farmer presenters. Specific events are listed in Table 1.

Results and recommendations will be incorporated into routine UW-Extension programming and delivered over winter 2024-25 (Table 1). We will produce outreach materials including a UW NPM publication to be distributed at these events.


Mourtzinis, S. et al. 2018. Soybean response to nitrogen application across the United States: A synthesis -analysis. Field Crops Research 215:74-82. doi:10.1016/j.fcr.2017.09.035

Patrignani A. and T.E. Ochsner. 2015 Canopeo: A powerful new tool for measuring fractional green canopy cover. Agron. J. 107:2312-2320. doi:10.2134/Agronj15.0150




Research results and discussion:


The first cycle of response work includes 29 trials conducted by 15 cooperators across 5 counties of Southeastern Wisconsin (Figure 1). Three additional trials were established in fall of 2021 but were abandoned due to cover crop failure in one case (poor stand, seed broadcast too late on soybean stubble) and in-season management errors in the others. Trial information is reported in Table 1.

All trials used cereal rye as the cover, 18 measured yield response in soybean, 12 in corn. The majority of trials were conducted in the context of a corn-soybean rotation with the cover established following harvest of the prior crop. Exceptions include sites JF02-03, RC02-03 where corn followed corn and sites RK01-02 where rye was aerially seeded into standing crops in advance of harvest. Covers were drilled in most cases, the exception being the aerial applications noted above and rye broadcast with an air-seeder after harvest (RC05-06).

Cover crop management variables included: seeding rate, 17 trials; termination timing, 8 trials; cover crop spatial arrangement (in-row vs between row), 2 trials; additional N on corn, 2 trials and a single factor +/- cover trial. The supplemental N trials (JF02-3) were established and managed as one trial but was split into two because the plot arrangement doesn’t conform to the experimental design. Early season conditions (discussed below) impacted planned termination timing for several of the trials not evaluating timing as a factor: delayed start of the field season forced “planting green” followed by preemergence termination in several situations where preplant termination was planned.

Growing season conditions

Growing season precipitation was variable between project regions and within-season (Table 2), impacting both rye and response crop growth, management and yield. In general, excess precipitation in April and early May delayed crop planting and in many situations forced green-planting and delayed termination where preplant termination was planned. Total early season precipitation was less in the northern region allowing earlier planting compared to other locations and season long precipitation was near normal which, coupled with heavier soil types, resulted in response crops never being exposed to moisture stress. In the southern locations, early season moisture surplus was followed by a prolonged period of moisture deficit and crop stress into initiation of reproductive growth, then abundant rainfall and crop recovery. Trials in the Palmyra area were probably most impacted by the combination of the greatest seasonal precipitation deficit and the lightest soil types. Seasonal growing degree day (GDD) accumulation was near normal (data not shown).

Yield response

Yield response data by individual trial are presented in Table 3. In aggregate (cover crop treatment means averaged), cereal rye reduced crop yield by 2.3%; -1.5% for corn and -2.8% for soybean. Impact on corn ranged from +1.6 to -3.8% with average yield reductions in 78% of cases. The greatest reduction (Site RK03, p= 0.001) was attributed to stand reductions which the cooperator attributed to slug feeding. Impact on soybean yield ranged from +5.3 to -16.5% with neutral or positive responses in 53% of cases. Soybean yield reductions were consistently greatest in cases where termination was delayed, either as a component of a termination timing comparison or as routine farm practice where another practice (e.g., seeding rate) was evaluated. Except for Site JF10, these reductions were from sites in the southern regions where mid-season moisture stress was prevalent (Table 2) enhancing yield reduction due to direct competition for soil moisture.

Distribution of individual treatment responses, expressed as response ratio (yield follow cover crop/ yield without cover) and categorized by response crop is presented in Figure 2.  In general, corn response was normally distributed while soybean was downwardly skewed by the large proportion and magnitude of yield reductions due to late termination. In 2022, soybean had a much larger range in yield response, indicating greater potential response to rye management practices, especially yield reduction. That said, 53% of cases were positive with a potential yield response of up to 10%.

Identification of practices which maximize yield response as well as practices to avoid is a major objective of this project and synthesis analysis to accomplish it will be performed when data collection is complete. Cursory examination of 2022 response data: comparison of practices which resulted in increases/decreases in the upper and lower quartiles indicate general trends (at least for 2022) as well as the efficiency of the paired treatment design in identifying important practices. In corn, greatest responses tended to involve early termination (preplant or preemergence) and lower seeding rates while later termination and/or greater seeding rates reduced yield. In soybean the same termination timing relationship existed but the influence of seeding rate is less clear. Here the termination timing issue is of great interest because of cooperator perception that soybean is more tolerant of later termination and therefore use of the practice on-farm with the intent of producing maximum rye biomass for ecosystem benefits. Results from 5 sites (JF03, RC01, RC03, WW01 and WW03) illustrate the importance of rye management and the thin margin between positive and negative responses, all having one treatment in the top 25% of response and the other in the bottom. Site WW03 which examined termination timing in corn is of particular interest because the two timings were separated by only 11 days yet resulted in a yield change of 5.25% between them.


The second cycle of response work included 25 trials conducted by 10 cooperators across 5 counties of Southeastern Wisconsin (Figure 3). One additional trial was established in fall of 2022 but abandoned due to in-season management errors. Trial information is reported in Table 4. Please note that Figure 3 illustrates cumulative trial sites to date.

Twenty-three trials used cereal rye as the cover, 16 measured yield response in soybean, 7 in corn. Most were conducted in the context of a corn-soybean rotation with the cover established following harvest of the prior crop. Exceptions include site JF19, where corn followed corn (C-C-Sb sequence) and sites RK05-06 where rye was aerially seeded into standing crops in advance of harvest. Covers were drilled in most cases, the exception being the aerial applications noted above and rye broadcast with an air-seeder after harvest (RC11-12).

Rye management variables included: seeding rate, 8 trials; termination timing, 12trials; cover crop spatial arrangement (in-row vs between row), 1 trial; and 2 single factor +/- cover trials. As in 2022, early season conditions (discussed below) impacted planned termination timing for several of the trials not evaluating timing as a factor: delayed start of the field season forced “planting green” followed by preemergence termination in several situations where preplant termination was planned.

Two trials (JF17-18) used proprietary multi-species mixes established after wheat and evaluated corn response to applied N at 2 rates, 100 and 140 lb. N/a to determine if the cover mixes provided a “N credit”. These two trials are the exception to the majority evaluating cereal rye in a C-Sb or C-C-Sb rotation so will be discussed separately and not included in the aggregate analysis.

Growing season conditions

Drought conditions dominated the 2023 growing season, affecting all areas and trials within the project region (Figure 3). Characterized as a “flash drought” (2 Drought Monitor category changes within a 4-week period (USDM, Svoboda et al., 2002)), significant precipitation ceased regionally in early May and this persisted into late July (Table 5), changing our regional Drought Monitor status from “normal” in early May to “D2, Severe Drought” by July 4. The result was a rapid drying of the upper soil profile, often to below crop rooting depth causing reduced crop growth and development rates. This was compounded by less-than-ideal soil conditions after planting. Late April rains delayed field operations and, in many cases, forced planting into wetter soils, resulting in hard or crusted conditions when soils dried out. Late April precipitation also changed many planned preplant termination applications to preemergence or later, resulting in moisture competition with the crop which is evident in the yield response data.

While monthly precipitation returned to near normal in most areas later in the growing season, it did not compensate for early season deficits and all regions except the SE remained in “D1, moderate drought” into October. Total season moisture deficits ranged from 5.77 to 9.72” (Table 5). Seasonal growing degree day (GDD) accumulation was 99.5% of normal (20 yr., 2001-2020), measured at the centrally located NOAA NWS Field Office at Sullivan, WI ( Midseason smoke from Canadian wildfires kept June temperatures below normal (data not shown) which was fortunate for already drought stressed crops.

Yield response

Yield response data by individual trial are presented in Table 6, sorted by the cover crop management comparison within response crop categories. Trials not using cereal rye as the cover crop (JF17,18) are included in the table but segregated for sake of analysis and discussion. As in 2022, discussion of results focuses on rye management impacts comparing trends between responses in the upper and lower quartiles of distribution in advance of synthesis analysis which will be performed when data collection is completed.

Cereal rye reduced corn yield in all trials regardless of management, -6.2% averaged over trial responses, Figure 4. The limited number of individual comparisons (n=9) makes it difficult to draw firm conclusions but sites which terminated before planting (JF19, WW07 Cover 1) minimized yield reduction, while later termination (WW07, WW08) resulted in the greatest reduction. Soils at these sites tend to be the drouthiest of project fields so we partially attribute this result to moisture use. On more poorly drained soils (RC11,12), rye management had no meaningful impact on yield reduction, so we attribute the effect totally to the use of the cover. Inclusion of the pending data (JF12, RK06), which compare seeding rates on well-drained soil types may help to clarify the nature of the response.

Use of cereal rye increased soybean yield 7.4% on average (Figure 4) and rye management had a major impact on the response. As in 2022, early termination (PP or PRE) was a common factor in the upper quartile yield responses while seeding rate appears less of a factor. Mean yield response in the upper quartile was 8.6%. Trials RC08,09 are of particular note because they had the greatest mean response to rye (10.7%) on a first-year site with no rye history. These trials exhibited differential response to management: delaying termination reduced yield 1.3 and 3.5 bu./a respectively, and the greater reduction was in the trail with the greater seeding rate (40 vs 80 lb./a); but the overall response clearly indicates first-year responses can be substantial, even under drought conditions. We have previously reported on significant first year responses in Project ONC17-034 on which this project is based.

Delayed termination (beyond PRE) and greater seeding rates contributed to yield reductions. The mean reduction of the lower quartile was 12.9%. In general, these trials were conducted on droughty soil types, had termination timings after soybean emergence and seeding rates greater than 50 lb./a, all factors which have an impact on soil moisture. Our overall response distribution was better in 2023 (w=0.976, p=0.773) than 2022 (Figure 2) due mostly to a lack of trials with extremely late termination, discussed above.

Non rye response trials

Two trials (JF17,18) evaluated corn N response following diverse, proprietary cover crop mixes established after wheat harvest. These mixes, marketed as “N fixing”, differed in species composition including proportion of legume and grass species. The comparisons included in-season N application at the cooperators normal 140 lb. N/a rate and a reduced (100 lb./a) to conservatively evaluate the N credit. Trial JF17 had an aggregate 14.0% yield response to cover (p=0.040) and no apparent “credit” as the normal rate yielded an additional 12.5 bu./a or 0.31 bu./ lb. applied N compared to the reduced rate. Trial JF18 had an aggregate 8.6% reduction in yield and no response to N (p=0.326). The results reinforce that an appropriately chosen legume mix can result in substantial yield response and in turn, may not produce a “N credit” because of increased N demand with greater yield potential following the legume.

Project status

Cycle 1, 2 agronomic data collection is complete and input/output data (individual site prices paid/ received) is being compiled for partial budget analysis. Cycle 3 response year fieldwork has been initiated, 34 trials across 6 counties with 5 new cooperators were established in fall 2023.






Participation Summary
15 Farmers participating in research

Project Activities

2022 National Strip-tillage Conference

Educational & Outreach Activities

2 Curricula, factsheets or educational tools
3 Tours
17 Webinars / talks / presentations

Participation Summary:

829 Farmers participated
293 Ag professionals participated
Education/outreach description:

Year One (2022-2023) outreach work focused on creating project awareness in anticipation of the release of preliminary results in early 2023. Outreach activities included both invited and volunteered presentations at a variety of events, most with farmers as the primary audience and several in the context of producer-led watershed group outreach efforts. Formal event evaluation was not possible due to the informal nature of most events. Events included:

Byron Seed Update Meetings: Loganville, WI (Feb. 16); Waupun, WI (Mar. 9), 142 participants

Walworth County Cover Crop Update Meeting, Elkhorn, WI (Mar. 16), 41 participants

Jefferson County Soil Builders Twilight Meeting, Palmyra, WI (June 2), 46 participants

Wisconsin Cover Crop Initiative (CCrop) Summer Meeting, Sauk Prairie, WI (June 15), 45 participants

Strategies for Land Stewardship Summit, Lake Geneva, WI (June 21), 64 participants

National Strip Tillage Conference, Iowa City, IA (July 28), 45 participants

Wisconsin Association of Professional Agricultural Consultants (WAPAC) winter seminar, Manitowoc, WI (Dec. 8), 28 participants

Waukesha County Green Team Winter Meeting, Oconomowoc, WI (Feb. 13, 2023), 32 participants


In addition, two project tours for staff of Lessiter Media (publishers of “Cover Crop Strategies”, “No-till Farmer” and “Strip-till Farmer” magazines, ) were conducted on June 17 and Oct 8. These tours of select research sites were designed to create awareness and discuss opportunities to disseminate project results when available.


Year Two (2023-24) outreach activities included continued project awareness creation in anticipation of results as well as initial results dissemination and lessons learned. Presentations included:

2023 National Cover Crop Summit, March 14, National Virtual Event

Sponsor: Lessiter Media, publishers of No-till Farmer, Cover Crop Solutions

Title: “Farmer to farmer panel: tips for making cover crops work with your tillage systems”

253 verified participants, reported as 253 farmers


2023 Fox River Summit, March 16, Burlington, WI

Sponsors: Fox River Commission, SE Wisconsin Regional Planning Commission

Title: “Overcoming barriers to cover crop adoption: carrots, sticks, and many little hammers”

124 Participants, 8 farmers, 60 professionals (agency/ NGO)


Walworth County Soil Health/ Cover Crop Interest Group meeting, March 22, Elkhorn, WI

Sponsor: Walworth County Land Conservation Dept.

Title: “Best practices when planting green”

32 participants, 28 farmers, 4 professionals


GROW Farmer Forum, March 29, National Virtual Event

Sponsor: GROW (Getting Rid of Weeds through integrated mgmt.)

Title: “Farmer Forum: cover crop termination”

85 verified participants, 65 farmers, 20 professionals (ratio estimated)


WiscWeeds Giant Ragweed Control Field Day, June 15, Janesville, WI

Sponsors: University of Wisconsin-Extension/ Rock County Land Conservation Dept.

Title: “Can cover crops pay?: best practices when planting green”

98 participants, 42 farmers, 16 professionals


Delevan Lake Association Field Day, June 27, Elkhorn, WI

Sponsor: Walworth County Land Conservation Dept, Delevan Lake Association

Title: “Cover crop economics: the quest for a stand-alone agronomic practice”

48 participants, 28 farmers, 15 professionals


Farming for Soil Health, December 19, Whitewater, WI

2023 Annual Conference for SE Wisconsin Producer-led Watershed Protection Groups (PLWPG)

Sponsor: Glacierland Resource Conservation and Development (RC&D)

Title: “Cover crop economics: best practices to maximize crop yield response”

78 participants, 52 farmers, 14 professionals


2023 Soil Health Expo, February 7, 2024, Juneau, WI

Sponsor: Dodge County Farmers for Healthy Soil, Healthy Water (a Wisconsin PLWPG)

Title: “Rye cover crop termination timing: weed suppression and yield impacts”

Presentation summarized 2023 results and recommendations from project ONC23-135 which led into a broader discussion and results sharing from this project. Our message: stay the course with covers even with bad experiences in 2023. The data shows positive yield responses following rye when terminated early, even in a drought.

122 participants, 75 farmers, 23 professionals


Awareness creation tour

Lessiter Media (publishers of No-till Farmer, Cover Crop Solutions), June 12, East Troy/ Palmyra, WI

with Michaela Paukner (Acting Editor) and intern (also reps of Michael Fields Institute (NGO), UW-Extension and Green Wisconsin (NGO)), tour discussed project and looked a project sites.

6 participants, 6 professionals


Project Outcomes

Key practices changed:
  • Planting green- earlier termination.

3 Grants applied for that built upon this project
3 Grants received that built upon this project
1 New working collaboration

Information Products

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.