Final report for LNC21-456
Project Information
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 overarching objective was to identify management practices which contribute most to positive yield response, and measure net return generated by using those practices. Our goal was to generate data and make recommendations to build an economic argument for increased adoption. This project was built on two past SARE projects, ONC17-034 and LNC15-375.
We conducted on-farm strip trials over the agriculturally diverse region of SE Wisconsin, generating 74 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 designed their individual trials to answer farm-specific production questions about CC management. All trials were conducted in no-till systems and the majority used cereal rye, focusing our project on this system. Yield response data was converted to response ratio (crop yield following rye/ no rye) and in aggregate, was analyzed using regression to determine effect of rye management on yield response of corn and soybean. Net margin ($/acre) for each paired comparison was calculated using partial budgeting from price data submitted by cooperators. These results underwent identical analysis to identify impact of rye management on net margin. We separated and re-analyzed the upper quartile of response data to represent outcomes when rye best management practices are followed, both average as well as range.
Use of a rye cover crop resulted in positive yield responses in 34.2% of corn comparisons, 55.8% of soybean but reduced mean crop yield by 1.8%; corn by 2.3%, soybean by 1.3%. This resulted in a mean financial loss of $49.70/acre; $-55.92/acre for corn, $-43.47/acre for soybean, with annual variation, ranging from $-81.10 to -41.84/ acre for corn, $-53.27 to -35.18 for soybean depending on annual yield response and price structures. Later termination timings (beyond pre-emergence) and increased seeding rate were the management factors most responsible for negative yield responses while rye planting date had no effect. Years with normal or above precipitation favored yield response but soybean exhibited less sensitivity to precipitation than corn.
The upper quartile of yield response data had a mean positive response of 4.7%, 3.3% for corn, 6.1% for soybean. Under the market conditions of this study, this resulted in a mean $10.07/ acre loss in corn and basically no difference in soybean. These sites terminated rye early, favoring preplant termination timing and used seeding rates less than 50 lb./ acre. Importantly, a large number of these sites: 50% corn, 45% of soybean were first year, having no cover crop history, demonstrating an immediate impact, and dispelling a widespread belief that benefits of cover crops are a long-term proposition. This important finding shows cover crop use is appropriate on cropland under short-term lease. Evaluating the range of net returns in the context of using cost-share assistance as a risk management strategy to offset potential income reductions, minimum levels of assistance needed were $22.54/acre for corn, $11.90 for soybean, well below those offered in Wisconsin. Under the market conditions of this study, greater cost-share rates would have guaranteed a positive net return, leading us to believe rye covers can be used confidently on leased cropland if best practices are used, supported by cost-share assistance.
With increased knowledge of documented CC impacts on yield and net return as well as best management practices (BMPs) to maximize them, farmers will change management and increase adoption. Our outreach plan relied heavily on peer-to-peer information exchange within producer-led watershed protection groups (PLWPGs) and more routine Extension type programming, targeting farm advisors. This approach leveraged project efforts. Sharing data and insights with PLWPGs at their learning events resulted in immediate information transfer and farmer experience sharing. More importantly, it led to subsequent, independent discussions as group members share their own experiences during routine, season end recap meetings. Concurrently, crop advisors incorporated project recommendations into their work with clients, writing crop management plans with best practices.
Practice changes, earlier termination and reduced seeding rates were implemented rapidly, after release of first year results. This is evident in project summary data: in subsequent years cooperators shifted to earlier termination timings, ceased terminating at anthesis, and became interested in comparing reduced seeding rates as compared to increased rates. It is also evident in farmer reporting at season wrap-up, evaluation meetings where satisfaction following best practice recommendations and intent to continue is expressed. Interestingly, farmers who produce rye for local seed sales are recommending reduced seeding rates, to the apparent detriment of their enterprise.
Adoption increases are more difficult to measure and will take time. Anecdotally, PLWPGs experienced increased demand for their CC cost-share programs from new applicants, indicating increased interest and planned changes in farm management.
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) https://www.wpcracinecounty.org/
Jefferson County Soil Builders https://www.facebook.com/jeffersoncountysoilbuilders/
Farmers on the Rock https://www.farmersontherock.com/
Dodge County Farmers for Healthy Soil- Healthy Water (DCFHSHW) https://dodgecountyfarmers.com/
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.
Cooperators
- - Technical Advisor
- - Technical Advisor
- - Technical Advisor
Research
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.
This project worked directly with PLWPGs, gathering data from a series of on-farm trials conducted by their member farmers in partnership with professional crop consultants. These 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 was 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 was also important for information dissemination and advocacy because their client base is larger than the PLWPG’s they serve and project results and recommendations inform their management recommendations. Additionally, we provided outreach through routine Extension programming and our collective service to several statewide boards and committees. The distribution of trial sites is shown in Figure 1 and reflects concentration in counties with active PLWPGs.
Cooperating farmers ranged in CC experience level from some to advanced, allowing us to investigate some first year as well as cumulative effects as newer users had yet to implement practices in all fields while experienced users have implemented them over most or all their operations cropland. Anecdotal evidence suggest greater usage following corn than soybean, explaining the greater proportion of soybean response trials in this project. At the individual farm level, trials investigated practices addressing the farmers specific questions and or management concerns. 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?” comparing: preplant vs. postemergence termination. In aggregate, data from these individual trials allowed us to determine the overall yield effect, somewhat separate first year from cumulative effects, identify practices/ factors which contribute most to yield response and calculate net return to cover. All cooperating farmers practice almost exclusive no-tillage (NT) production, most for more than 5 years. All trials reported here were conducted in NT systems.
We intended to limit CC systems to those most common in the region and not allow a species comparison. Common regional cropping systems include:
- Cover with/after soybean->corn
- Cover with/after corn->soybean
- Cover with/after corn silage->rotational crop
- Cover with/after wheat->corn.
In practice, most cooperators use cereal rye (hereafter rye) after harvest of both corn and soybean, rotating annually to the opposite crop so trials focused on this system with emphasis on soybean following rye. In some cases, annual rotation was prevented so the response crop followed itself with rye grown in-between. One cooperator routinely grows wheat followed by corn so investigated use of multi-species cover crop mixes and potential N crediting in the following corn crop. The sheer number of rye trials (94.6%) shifted our focus: data analysis, presentation, and discussion examine rye use with a separate discussion of the other, non-rye system. This should increase project relevance as rye systems are the dominant cover crop system in the upper Mid-west (Heiniger, 2023).
Individual trial details including the cover crop management comparison are reported in Table 1, a summary of comparisons can be found in Table 2.
Research objectives:
- Determine the impact of CC use on yield of the subsequent crop;
- Separate first-year and cumulative yield effects to determine the immediate impact of CC use;
- Determine which practices maximize yield response to develop BMP recommendations;
- Calculate net return to CC using partial budget analysis and estimate variability of return, risk;
- Collect CC conservation performance data to refine soil/nutrient loss estimates in SnapPlus;
Field Trials
We conducted 74 on-farm strip-trials, using a simple treatment design of with and without (+/-) cover, using the farm’s standard cover practice as the base CC treatment. We added a second CC 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.
Cooperators defined their treatments based on considerations discussed above to answer their own farm specific questions.
Field length trials were randomized and blocked based on field characteristics (soil type, topography) to ensure between-plot uniformity to the extent possible while capturing field variability (Photo 1). Plot width was dictated by width of planting equipment. Cooperators followed their routine cultural practices related to cover and response crops. In-season diagnostic tests (PSNT etc.) were conducted where variables include a nutrient component to enrich the dataset and provide explanations when treatment differences exist.
Yield was measured from plot center rows to eliminate border effects, determined from plot weight (in most cases) or by calibrated combine yield monitor, using methods of the UW Discovery Farms Program (https://uwdiscoveryfarms.org/resource-library/ ) (Photo 2). Accuracy of weighing equipment or yield monitor calibration was certified by the project consultant before harvest (Photo 3). Grain moisture and test weight were determined from samples submitted to the project, independent of yield monitoring equipment (Photo 4).
Cooperating farmer/ consultant pairs maintained site-specific records for 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 (I/O) data:
Grain price (harvest date local spot or contracted), interest rate (operating), drying and hauling cost ($/bu.), CC seed cost ($/lb.), herbicide ($/gal.), fertilizer ($/ton), and CC field operation costs($/a).
Agronomic records were used in the analysis to help qualify and interpret results. Growing season (April 1- Sept. 30) precipitation and growing degree day (GDD) data was collected from the nearest National Weather Service reporting station. Project consultants were 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 were combined by case (individual on-farm trial) with agronomic and yield data and subjected to economic analysis described below.
Cover crop conservation performance
Cover crop aboveground biomass was sampled at termination and air dried (60oC to constant weight) to determine DM yield. For trials with a nutrient component, samples were analyzed for total C/N using dry combustion methods. Percent canopy was estimated concurrently by fractional green canopy cover using Canopeo (Patrignani and Ochsner, 2015), 5 estimates per plot, along with height measurement.
Above ground biomass and canopy development (as % ground cover at termination) data was added to the University of Wisconsin cover crop database which the UW SnapPlus Development Team uses to calibrate its soil erosion estimations. SnapPlus is Wisconsin’s official nutrient management planning software and 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 CC type, planting date and method, and termination timing.
Data analysis and use
Data was initially analyzed by site-trial 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 was transformed to response ratio (yield following cover/ yield following fallow) for the combined analysis to normalize soil yield potential differences where appropriate. For discussion purposes, a positive yield response to cover is a RR > 1.0, a yield increase is an increase in RR and vice versa.
Individual farm trials are complete, balanced experiments with a randomized complete block design. Data was analyzed by ANOVA to determine the significance of response differences which were reported to cooperators as actual yield and expressed as a % of no cover. Treatment means were used to calculate trial response ratios; most trials had the full treatment array (7 sites had the single cover vs. no cover comparison only) generating two response ratios per site-year. Individual trial results are reported in Table 4.
Response ratio data from trials using rye were combined by response crop and subject to linear regression using both rye management (planting date, seeding rate, termination date, termination timing) and environment (soil factors such as yield potential, drainage class, soil test results, previous crop and precipitation) as the independent variables to determine their impact on yield response. The upper quartile of RR data were segregated and reanalyzed independently to confirm that the “Top 25%” of results used the practices identified as important for maximizing yield response.
Financial data
Agronomic data was combined with input/output (I/O) price information to conduct partial budget analysis by case (RR). The analysis accounted for cost and return differences between cover and no-cover systems to calculate a net return for each CC system, compared to fallow on a per acre basis. The analysis included 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). Return to cover is expressed as net margin ($/a):
Gross Margin (yield difference x price) – Yield Dependent Costs (additional bu.: hauling, drying, P/K removal) – Constant Costs (cover crop seed, establishment, termination, interest, other management costs)
Cooperators’ actual market prices, tied to each response cycle, were used in the analysis. We calculated and used a price average for each I/O price to better reflect the market average by removing marketing bias (higher or lower prices due to differential marketing skill, seasonal input purchasing practices which include price differentials and input purchasing efficiency based on farm scale). Average prices are reported in Table 2. Interest charges were applied to inputs and field operations from the time of application to harvest. Cost-share incentive payments were excluded from the analysis but are an important consideration and discussed below.
Crop prices received by cooperating farmers declined approximately 21% over the study period (Table 2). To evaluate the potential impact on project results and their interpretation, we examined the ratio between prices received and input costs using an index of input prices for inputs used in the study including rye seed, fertilizer, grain handling charges, and interest. The data suggests a linear decline in the ratio (Figure A1) indicating a reduction of potential net margin as the spread between crop price and input price decreases. The 2023 margin was least and shows a departure from the trendline due to the greatest year over year decline in commodity prices and increases in P/K fertilizer prices and interest charges. The functional implication of this trend is that greater yield responses were required to maintain the same net margin potential. In other words, it is more difficult to achieve a positive net margin in 2023 and ’24 compared to 2022.
The exclusive use of NT by cooperating farmers revealed an important efficiency which impacted total cover crop cost and our financial analysis. All cooperators use glyphosate to terminate their rye, applied at the same rate (~32 oz/a, > 0.75 lb. acid equivalent (AE)/ acre depending on product) as used for “burndown” on non-cover treatments (and in their non-cover production fields). These applications typically also contain additional modes of action to control emerged, potentially herbicide resistant (specifically glyphosate) weeds, based on their assumption that the high glyphosate rate in combination with additional AIs will help prevent development of additional resistant weed species. The financial result is that termination of living covers in NT represents no additional input costs, only application costs if applied independently of the residual herbicide application (e.g., post emergence termination following earlier residual herbicide application).
Return on investment (ROI, $/$) was calculated by dividing net margin by total cover crop cost. Data was aggregated and analyzed by methods identical to yield response, identifying practices which have the greatest impact on net margin.
Apparent outliers, indicated in the figures were intentionally not removed from the analysis. Each data point represents a calculation comparing trial means (converting treatment yield means to RR) involving either 6 or 8 observations depending on replication level in the individual trial.
Finally, the upper quartile of response data was isolated and reanalyzed separately. This allows for comparison of practices used by the “Top 25%” against the entire dataset, representing “everyone” in the farming community. This format and framing was extremely helpful in outreach work with farmers because no one likes to be average.
Growing seasons
This evaluation was conducted over three contrasting growing seasons, differing widely in rainfall amounts, regional and seasonal distribution. Precipitation data is reported for each study region in Table 3 and includes monthly totals as well as accumulated departure from the 20-year mean for early (Apr.-May), mid (Jun.-Jul.), and late (Aug.-Sept.) growing season periods. Each of these periods relates directly to specific aspects of crop growth and development, and especially how soil moisture is impacted by growing cover crops before planting or in direct competition with the response crops as in the case of planting green. Expected regional variability is evident, especially in 2022.
2022
Growing season precipitation was variable between project regions and within-season, 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 not 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, followed by abundant rainfall and crop recovery. Trials in the Palmyra area were 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).
2023
Drought conditions dominated the 2023 growing season, affecting all areas and trials within the project region. Characterized as a “flash drought” [Two US Drought Monitor (https://droughtmonitor.unl.edu/)
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, 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 rain delayed field operations and, in many cases, forced planting into wetter soil, resulting in hard or crusted conditions when it dried out. Late April precipitation also changed many planned preplant termination applications to pre-emergence 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.” 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 (https://www.weather.gov/mkx/). Midseason smoke from Canadian wildfires kept June temperatures below normal (data not shown) which was fortunate for already drought stressed crops.
2024
The 2024 growing season was the opposite extreme of 2023, most influenced by a five-month period of consecutive above normal monthly precipitation beginning in March which heavily influenced the rye/ crop relationship. Frequent rainfall again disrupted spring field operations and delayed planting, up to 4-weeks in some areas but ultimately resulted in near ideal growing conditions into August and no observed crop moisture stress related to cover crop soil moisture use. As in 2022-23, overwinter precipitation was below normal through February which contributed to continuing drought conditions but March-April rains (>11” total) recharged the soil profile. On the other end of the growing season, precipitation became severely limited during August and most regions developed “flash drought” conditions by early September. General trial effects included forced maturity (early soybean death with leaf retention) and overall yield and test weight reduction despite the potential for an exceptional growing season and high yields that could be expected from a growing season with near normal to a 9.30” rainfall surplus. Growing degree day accumulation was 104% of normal.
All three seasons shared a common trend: a wet period at or near planting, impacting not only crop planting date (May 1 is the optimum for both corn and soybean in SE. Wisconsin, most planting delayed beyond then) but also interfering with many planned rye management activities including preplant (PP) termination. This important management consideration will be discussed at length in the rye management section.
Yield response
Use of a rye cover crop resulted in positive yield responses in 34.2% of corn comparisons, 55.8% of soybean but reduced mean crop yield by 1.8%; corn by 2.3%, soybean by 1.3% (Table 5). Annual variation in this yield reduction is evident, more so in corn (0.5 to 6.2%) vs. soybean (0.3 to 2.0). This variation is expected with widely varying growing season precipitation totals and distribution. This appears to have had a greater impact on corn than soybean and, in particular under drought conditions in 2023 which reduced yield response 6.2%. Soybeans fared well in this drought year but experienced their greatest yield reduction in 2022 (2.0%), the growing season considered most typical of our region. We attribute this reduction to a greater percentage of trials using extremely late rye termination (at anthesis) compared to subsequent years, resulting in greater crop competition and yield reduction (discussed later).
In general, soybean had greater yield response variability than corn, both mean and by year (Table 5, Figure 2, Figure 3). In addition to a wider range of yield responses, soybean exhibited a greater number of substantial yield reductions, effectively reducing mean response despite 55.8% of trial responses being positive, most evident in Figure 2. This variability in soybean response and yield drag by poor performing sites is also consistent across years, best observed in Figure 3. The wide range in response is best characterized by a downward pull of low response practices (mean < median) and upside potential of positively responding practices (same relational observation). We will relate this to management practices in a following section.
Net margin
Use of rye as a cover crop resulted in a mean financial loss of $49.70/acre; $-55.92/acre for corn, $-43.47/acre for soybean, Table 5. As with yield response, returns had annual variation, ranging from $-81.10 to -41.84/ acre for corn, $-53.27 to -35.18 for soybean. These annual values appear directly related to yield response (maximum annual reductions: 2023 for corn; 2022 for soybean) but may also be somewhat influenced by the crop: input price ratio in the case of corn in 2023. This year had both the lowest mean yield response (-6.2%) and the lowest crop; input price ratio (1.94, Figure 1A), in other words, the year with the least price forgiveness also experienced the greatest mean yield reduction due to drought. In soybean, the greatest annual loss occurred in 2022, related mostly to yield reductions as it had the widest and hence most forgiving crop: input price ratio (Figure A1), creating the greatest potential for positive return from a price standpoint.
The relationship between yield response and net margin for both crops is presented in Figure 6. This data and analysis suggests a strong relationship for both corn (R2= 0.91, p<0.001) and soybean (R2= 0.92, p<0.001) despite including the differential crop: input price ratios over the 3-year period. We suggest that differing annual ratios are normal in production agriculture, can only be partially (minimally) managed by farmers through grain marketing and purchasing, and probably should be a minor consideration when evaluating cover crop management other than cost minimization. Because of the strong relationship with yield response, cover crop management to maximize response is important for financial success with this practice, or conversely to minimize the potential for losses.
The return on cover crop investment, expressed as $ return to $ invested (Table 5) follows trends similar to net margin.
Factors influencing yield response and net margin
Rye management, both fall and spring, and precipitation impacted yield response while the soil factors inherent at each site did not. Results from linear regression evaluation are presented in Table 6. In general, the analysis resulted in models with low predictive ability which we attribute to the variability in the data, generated from trials conducted over a broad geographic area (and other factors inherent in on-farm research). We present the rye management factor data graphically because it illustrates the yield response trends we observed, especially on the extremes of the data distribution.
Precipitation impacts on yield response were broadly discussed in the growing season characterizations which have a few important trends. First, the data includes responses from a year with near normal precipitation (2022), a drought year (2023), and a year with above normal precipitation (2024) which had ample rainfall to support crop growth for most of the season until the onset of flash drought as crops neared maturity. Secondly, all years experienced a wet period just before planting, impacting both spring rye management and response crop establishment. Finally, regional variability in precipitation was expected and observed (Table 2), and was more pronounced in years with normal or above total precipitation while the drought year was uniformly dry through the early and mid-season periods then more variable late.
Years with greater precipitation more favored the cover crop systems in both corn and soybean, evidenced by greater RR values (Table 5). Evaluation of the relationship between season total precipitation (both actual and expressed as departure from long-term mean, Table 6) confirms yield response increases (increasing ratios) with increasing precipitation totals. Moreover, the growing season period when precipitation occurred impacted yield response and response crops showed differential responses. Increasing early season (Apr.–May) precipitation increased corn yield response while soybean was unaffected. Increasing mid-season (Jun.–Jul.) precipitation increased yield response of both while decreasing late season (Aug.-Sept.) reduced yield response. In corn, the response was greatest early season compared to mid-season (slopes of 0.008 vs. 0.004 respectively) and also greater than soybean in mid-season (0.004 vs 0.003, respectively. We attribute this to greater moisture use by corn’s more rapid growth and development and more precipitation moisture needed to replenish soil moisture used by rye. The negative response of both crops to increasing late season precipitation, corn more so than soybean (slopes: -0.003 vs. -0.002) is interesting and suggests positive yield response by the crop not following rye as both crops (+/- rye) would be expected to respond positively to increasing precipitation. Moisture conservation (reduced evaporation) from rye residue earlier in the season is a possible explanation of this effect, meaning residue conserved soil moisture, making crops less reliant on current precipitation. It is apparent that early to mid-season precipitation is important for both crops, corn more so than soybean and rye use has a yield benefit with later-season dryness.
Time of fall rye seeding had no effect on yield response (Figure 4, Table 6) nor net margin for either crop (Figure 5). This is an important consideration for overall farm management as weather related harvest delays often result in later rye planting when established post-harvest. That said, planting date does affect biomass production after both crops at time of termination and should not be discounted for conservation purposes.
Rye seeding rate affects both crops: increasing rates reduced the yield response (Figure 4) and corn appears to be more sensitive based on slope and p value (Table 6). The same relationship exists for net margin (Figure 5). With net margin, the rate of decline is much greater because of a compounding effect: not only does increasing rate reduce yield, but it also adds proportionately more expense. Seeding rate selection is an important consideration based on this relationship and should balance conservation and weed suppression goals against financial reality.
Termination timing had the greatest impact on both yield response and net margin. In our analysis, categorical grouping of termination dates into defined timings, related to response crop culture and development, were the best predictor of yield response and net margin and are more helpful in making management recommendations than Julian date. Delaying termination reduces both yield response (Figure 4) and net margin (Figure 5) and again more so for corn than soybean, based on slopes for both variables (Table 6). The reduction in net margin relative to delayed termination timing also has a compounding effect: termination timings beyond PRE mostly involve an additional application operation which adds expense. There are exceptions to this, site DG10 for example where residual herbicide was co-applied at early post emergence, but residual herbicide was largely applied to both crops along with “burndown” for the non-rye control within a few days of planting, requiring the extra termination application.
The Top 25%: results and practices which maximized responses
The upper quartile of response data represents top management and illustrates the achievable results if management recommendations are followed.
Mean response data for all cases paints a less than attractive picture of rye cover crop use: slight yield reduction, negative net margins which exceed most practice cost-share incentives and a negative return on investment, ignoring the value of conservation and other soil benefits. Within the range of response data, however, we see positive yield responses, up to 16.7% (Table 5) resulting in positive net margin and return on cover crop investment.
The upper quartile of yield response data has a mean positive response of 4.7%, 3.3% for corn, 6.1% for soybean (Table 5). Under the market conditions of this study, this resulted in a $10.07/ acre loss in corn and basically no difference in soybean. The spread in corn indicates a positive potential, but mostly losses which are easily within the range of cost-share incentives which, if used, would result in a positive return in addition to soil benefits. The spread in soybean is greater, and skewed upward from the mean, indicating greater upside potential for return.
Distributions of the upper quartile data are shown in Figure 7. From a management standpoint, it illustrates mostly an investment (the negative returns are considered the actual cost of cover cropping) in soil protection for corn with some profit potential. In soybean, the distribution shows a lessor investment in soil protection (reduced net losses in the distribution) with greater profit potential if best practices are followed. This analysis also ignores the tremendous potential for management of glyphosate resistant weeds with rye, documented in our other SARE funded work (Projects ONC21-094, ONC23-135). In our predecessor SARE funded project entitled “Do cover crops pay?” (ONC17-034), we reported marginal losses in 86% of cases. In response to the results, the cooperators rationalized them as “we reduced our cover crop costs by 50%”. Inherent in that statement is that they would practice cover cropping regardless of financial outcome, choosing to farm “the way we want to,” opting for soil protection and weed suppression. In this current work, we had hoped to generate positive financial data to provide a business management decision driver in the absence of cost-share incentives, in other words: a stand-alone financial practice. That is unlikely under the market conditions of this study, given the downside risk which is evident in data distribution. However, the minimum values for net margin shown in Figure 7 could (and should) be viewed as a floor for deciding on cost share assistance. If the per acre assistance offsets the minimum value (maximum loss), positive return should be expected. In other words, the cost share amount would shift the entire distribution upward, resulting in a positive return.
The production practices used to achieve upper quartile responses compared to all data are summarized in Table 7. The data is sorted by response (agronomic, RR; Economic, NM) and also includes a “common” category for sites which fall into both categories. This data confirms the conclusions of the regression analysis with some exceptions but most importantly, demonstrates that positive outcomes can be achieved when using rye for the first time. At least 50% of corn sites and 37.5% of soybean sites were first-year, producing upper quartile results. The dataset for all sites is incomplete so that data is not reported: most cooperators could not provide accurate cover cropping history so we cannot make an accurate comparison. An argument could be made that it doesn’t matter, this project is about the upper quartile and this finding is really important for dispelling the perception that covers don’t produce short term benefits (conversely that they are a long-term proposition) and are therefore not appropriate for short-term rental contracts on cropland.
Mean seeding rates for the common sites: 49.4 and 53.4 lb./acre for corn and soybean respectively fit the analysis trend, 8.0 and 2.8 lb./acre less than all trial means but this data is confounded by first year effects at several sites which included a higher, 80 lb./acre rate, which is near the trial maximum tested and serves to inflate the mean. In corn, this included site RC03; in soybean, sites RC09, JF05, and RC04. Interestingly, the later two trials investigated seeding rate, 40 vs 80 lb./ acre and in both cases, the upper rate produced greater RR and NM responses. From this limited data, it may be possible that seeding rate is not as critical in first year fields, especially soybean, and in fact, first year cropland may respond favorably to increased rates.
Termination timing practices of upper quartile sites mirror the regression analysis, in corn PRE or earlier, favoring preplant. In soybean, most sites also terminated before emergence with a greater proportion preplant. The important recommendation drawn here is to terminate early.
Non rye trials
Four trials (JF17, JF18, JF25, JF26) evaluated diverse, multi-species mixes planted after wheat for their yield and nitrogen effects on corn. The proprietary mixes: Byron Seeds “Maize Pro” and “Nitro-green” contain differing ratios of legumes and nonlegume and were planted with the intent of providing a nitrogen “credit” which was evaluated by reducing the applied sidedress N rate by 40 lb. N/acre (as UAN) from one cover treatment of the pair compared to the other and the no-cover control. In general, these are higher cost systems due to greater seed expense (~ $47.00/ acre) and greater interest charges because of August planting. They also offer potential benefits of increased biomass production, rotational benefits from non-grass species and a “N credit” from the legume component.
Trials produced conflicting results based on previous mix but were consistent with a lack of “apparent N credit” and yield response at the full N rate: RR=1.181, NM= $23.23/acre in 2023; RR= 1.184, NM= $55.83/ acre in 2024. Unfortunately, these results are from different mixes, Maize Pro in 2023, Nitro-green in 2024. Within each year, the alternating mix reduced yield but produced its greatest yield at the reduced N rate: RR= 0.936, NM= $-61.48/ acre in 2023; RR=0.998, NM= $-51.56 in 2024.
The positive results demonstrate the value of crop diversity in rotation which produced yield responses far greater than rye {maximums: 2023, 0.977; 2024, 1.066 (trial maximum)]. Unfortunately, the differential response to the individual mixes, which may be linked to the nature of the unique growing seasons (drought vs. ample precipitation) and the downside financial potential of making the wrong choice of cover mix make this option risky and warrants further investigation.
Can cover crops pay? Yes, under certain circumstances, using best practices. For cereal rye in NT systems, using best practices for rye management includes lower seeding rates, early termination and co-applying termination herbicide with residual products to reduce application costs.
Soybean has a greater probability of a positive return than corn. Soybean systems also showed less susceptibility to drought conditions than corn. Under upper midwestern conditions, seeding rates should not exceed 55 lb./acre [this was the Wisconsin NRCS required rate for cost-share (EQIP, CSP) during this project] unless other benefits such as weed suppression are desired, but the increased rates increase risk of reduced yield and return. Rye should also be terminated early, at or before soybean emergence. Given our experience with rainfall interfering with planned early-season management activities, prioritization should be given to termination so that opportunities are not missed during the spring rush.
In corn, seeding rates of 50 lb./acre or less should be used. This was not previously discussed, but a 28 lb./acre seeding rate (one-half of the NRCS cost-share requirement) produced the greatest yield response (RR 1.064) of all corn response trials following rye, further indicating corn sensitivity to seeding rate. Corn is also more sensitive to termination timing, which should occur before emergence. In the Top 25% analysis, the data showed a definite skew towards preplant termination but PRE co-application with residual does offer an attractive, agronomic efficiency as well as cost savings.
Rye planting date has no impact on yield response, but earlier planting should be prioritized because it affects biomass production, directly impacting conservation performance potential and one of the reasons we plant covers.
Using best practices still resulted in negative mean net margins under our market conditions. However, use of best practices reduced the losses to a level that could be overcome by cost-share assistance. Based on our results, minimum levels of assistance to offset the deficit were $22.54/acre for corn, $11.90 for soybean. These are the values needed to offset the greatest losses; greater cost-share rates would have guaranteed a positive net return.
Finally, and possibly most important, positive yield response and net return are possible in the first year of rye cover use. We found that 50% of trial sites in the upper quartile of data were first-year sites. For farmers operating rental cropland, this “perception barrier” should be discounted if not ignored, especially if best practice recommendations are followed and cost-share assistance is used as a guarantee. This is especially the case with soybean which appears more accommodating of the rye cover crop.
Education
Our outreach plan had two primary audiences, farmers, and their advisors. It was 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 focused on PLWPG summer field-days and winter workshops, concentrating on creating awareness about the project and its forthcoming results as well as generating internal interest and discussion. Cooperating farmers hosted some field days in conjunction with their respective PLWPG and shared their experiences and results to date. Project representatives also shared whole project results and recommendations.
Upon completion of the research component, emphasis shifted to sharing results and recommendations. At the PLWPG level, this was done at formal winter meetings/ conferences with a combination of individual cooperators sharing their farm results/experience and the project sharing whole project information.
Results and recommendations will be incorporated into routine conference programming and delivered over winter 2025-26. We will also produce outreach materials (a project summary) to be distributed at these events.
Project Activities
Educational & Outreach Activities
Participation Summary:
Year 1, 2022-23
Year One 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, www.lessitermedia.com ) 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 2, 2023-24
Year two 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.) https://growiwm.org/
Title: “Farmer Forum: cover crop termination”
https://growiwm.org/farmer-forum-recap-cover-crop-termination/
85 verified participants, 65 farmers, 20 professionals (ratio estimated)
Fertilizer Value of Cover Crops Field Day, June 1, 2023, Milford, WI
Sponsor: Jefferson County Soil Builders
Title: “Evaluating the fertilizer benefits of cover crops”
37 participants, 32 farmers, 5 professionals
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
2024 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 to 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
Year 3, 2024-25
2024 Fox River Summit, March 16, 2024, Burlington, WI
Sponsors: Fox River Commission, SE Wisconsin Regional Planning Commission
Title: “Peaking under the covers”
120 Participants, 12 farmers, 68 professionals (agency/ NGO)
Weatherproofing Your Farm Field Day, June 13, 2024, East Troy, WI
Sponsor: Michael Fields Agricultural Institute
Title: “Lessons from on-farm research”
42 participants, 22 farmers, 12 professionals
Regional Nitrogen Optimization Pilot Program meeting, February 19, 2025, Eau Claire, WI
Sponsor: University of Wisconsin-Madison, Division of Wisconsin
Title: “Does a cereal rye cover crop change the optimum N rate in corn following soybean?”
31 participants, 14 farmers, 17 professionals
Walworth County Soil Health/ Cover Crop Interest Group meeting, March 30, 2025, Elkhorn, WI
Sponsor: Walworth County Land Conservation Dept.
Title: “2024 Research Update: cereal rye management”
27 participants, 25 farmers, 3 professionals
Spring Cover Crop Management Field Day, June 5, 2025, Palmyra, WI
Sponsor: Jefferson County Soil Builders
Title: “Cereal rye management in corn”
45 participants, 38 farmers, 5 professionals
NACD Summer Conservation Forum and Tour, July 29, 2025, Rochester, WI
Sponsor: National Association of Conservation Districts
Tour theme: Wisconsin’s collaborative conservation delivery model
Tour stop featured a different project but results from current project (SARE acknowledged) were shared and used to reinforce key points about rye cover crop use and management.
97 participants, 6 farmers (local), 91 professionals (this mostly included farmers serving their Soil and Water Conservation Districts in addition to agency personnel)
Uplands Summer Meeting, August 8, 2025, Spring Green
Sponsor: The Uplands Watershed Protection Group
Title: “Cereal rye management: crop yield responses and returns”
Print project summary provided, results presented in absentia.
Attendance figures unavailable
Outreach, advance work conducted:
National No-till Conference, Jan 8, 2026
Title: “Do cover crops pay? Here’s what the numbers say…”
The entirety of project results will be presented. This presentation was invited and advance promotional work was completed during the grant period. Based on experience, content will be summarized and published as a print article in No-till farmer or Cover Crop Solutions, summer 2026.
Learning Outcomes
- Rye cover crop management: impact on yield response.
- Planting green: trade-off between soil benefits and yield impacts.
- Economics of rye use: yield response and net margin ($/ acre).
- Farmer conservation efforts: measuring cereal rye conservation potential. Several of our presentations were made to non farming conservation groups made up of agency and NGO representatives. Presentations focused on efforts farmers make to improve conservation and reduce nonpoint pollution such as cover cropping, how this project is working to increase adoption and methods we use to measure cover crop conservation potential.
Project Outcomes
Planting green- earlier termination, preemergence or before.
Planting green- eliminated termination at anthesis.
Cereal rye seeding rates: reduced to a maximum of 55 lb./a, the Wisconsin NRCS recommended (and required rate for cost-share) during the project. This rate was reduced in 2025 and anecdotally, we suggest that project results contributed to this reduction.
The Watershed Protection Committee of Racine County: Group learning, group action
The WPCRC is a producer-led watershed protection group in SE Wisconsin with membership representing five counties. Chartered in 2018, its mission is promoting conservation agriculture which it supports through formal outreach activities, group and peer to peer learning, and offering a simplified conservation practice cost-share program, enabling recipients to try new practices without risk or formal commitments. Farmer members also model conservation agriculture on their own farms. Most members are long-term no-tillers but more recent cover crop practitioners, most with 3 to 5 years’ experience.
The group formed during the early wave of PLWPG formation in Wisconsin. Lacking local expertise in managing the complexity of conservation systems using multiple practices successfully, it followed a common outreach strategy used by other producer-led groups: invite guest speakers from outside our region to share their experiences and recommendations. While successful in generating enthusiasm for conservation in general and soil health in particular, the pitfall of this strategy is that practices which work elsewhere may not be appropriate under our unique conditions, mostly a shorter growing season. Concurrently, our outreach evaluation results clearly indicated our audience wanted local data and experience before they would make changes, especially practice adoption.
The WPCRC turned Project LNC21-456 into a group exercise, contributing 13 site years of data from their own farms and our Case-Eagle Park regenerative agriculture research and outreach center, a county-owned facility operated in partnership to promote conservation. We reviewed data (Exhibit 1, a typical trial summary report) and shared experiences annually at our December, season wrap-up “shop meeting”. After three project cycles of results and experiences, our approaches and management have changed. As a promotional group, we have and will continue to incorporate results into our outreach efforts including a presentation of the full project results at our 2026 Winter Workshop in February. As farmers, we have universally changed our rye management, terminating earlier and reducing seeding rates. Anthesis termination was common at the beginning of the project, following the advice of the out of region regenerative agriculture gurus. We were excited by the initial results of anthesis termination: huge biomass and soil health impacts but were grounded by the reality demonstrated by no rye comparison strips: unacceptable yield and financial losses. Anecdotally, we can suggest that our outreach audience also got that message because heading and “smoking” rye (pollen shed) have all but disappeared from the landscape. The adoption of reduced seeding rates was driven as much by experiential learning as it was by yield and financial data. Cooperators learned that the conservation systems are easier to manage at reduced rates, especially planting, a phenonium not evident in the data and wisdom which would have been lost without cooperator involvement in project evaluation. Reducing rates is so critical that our primary, regional seed grower and supplier recommends it to his clients, to the detriment of his on-farm profit center.