Examining the Relationship between Crop Net Returns, Risk, and Conservation Practices

Abstract

This study aims to evaluate the effects of different tillage practices and cover crop options on crop net returns, downside risk, soil loss, and greenhouse gas (GHG) emissions in a corn-soybean rotation in central Illinois. The conceptual framework developed encompasses tradeoffs between net returns, downside risk, soil loss, and greenhouse gas emissions. The conservation system had the highest net return per acre. Crop net return differences were smaller between the conservation tillage and no-till systems than they were between the conservation tillage system with no cover crop and with a cover crop. The no-till and cover crop systems also exhibited more downside risk than the conservation system. However, utilizing the no-till system and the cover crop systems was an effective mechanism to reduce soil loss and greenhouse gas emissions.

1. Introduction

Conservation practices such as the utilization of a no-till crop system or cover crops can be used to improve soil health, reduce soil loss, and mitigate net greenhouse gas (GHG) emissions. No-till is the practice of refraining from tilling the soil from harvest of the previous crop to the harvest of the current crop. Cover cropping involves planting a crop for seasonal cover. For example, numerous U.S. farms plant annual or cereal ryegrass in the fall to provide cover during the winter months.

No-till and cover crop practices vary widely among farms. Using U.S. Department of Agriculture-Economic Research Service (USDA-ERS) survey estimates, 27 percent of corn in 2016, 40 percent of soybeans in 2012, and 45 percent of wheat in 2017 utilized no-till cropping systems [1]. Though cover cropping is not as common as no-till systems, its use has been growing. In 2017, 5.1 percent of U.S. acres utilized cover crops [2]. Moreover, with the recent interest in carbon farming, a carbon sequestering change made to some farm practices in exchange for receiving payments for carbon credits, the interest in no-till and cover crop practices has increased.

Given their obvious conservation benefits, why have management practices such as no-till and cover crops not been more widely adopted? As with any new system or technology, the benefits have to be weighed against the costs. Benefits may include an improvement in soil health, a reduction in soil loss, and mitigation of net greenhouse gas emissions. Costs may include extra costs associated with the practice (e.g., planting a cover crop), potential reductions in crop yields, and potential increase in net return risk (i.e., increased variability or downside risk of net returns resulting from the adoption of a conservation practice), because there are numerous benefits and costs, it is important to examine tradeoffs between key variables such as net returns, risk, soil health, and net greenhouse gas emissions. In other words, it is seldom possible to adopt a conservation practice that has higher net returns and less risk, and that improves soil health or reduces net greenhouse gas emissions.

The objective of this chapter is to examine the relationship between crop net returns, risk, and conservation practices. The conceptual framework developed can be used to explore crop net returns, risk, soil loss, and greenhouse gas emissions for different conservation practices.

2. Previous research

Given the importance of the no-till and cover crop rotations to the conceptual framework developed in this study, the literature review in this section will briefly discuss previous studies that have examined the impact of tillage practices on net returns, soil health, and net greenhouse gas emissions, and the costs and benefits of cover crops. These discussions will be followed by a brief discussion of carbon markets.

Wade et al. [3] summarized the adoption of conservation practices that could be used to reduce the environmental impact of crop production, improve soil health, and reduce net greenhouse gas emissions. Though practices varied widely among crops and regions, approximately 40 percent of the combined acreage of corn, soybean, wheat, and cotton utilized no-till or strip-till practices. Strip-till is a tillage system that utilizes tillage only in narrow strips where seed are planted. In another USDA-ERS study, Claassen et al. [1] noted that no-till and strip-till used in conjunction with conservation rotations and cover crops have a multitude of soil health benefits. The authors noted that practices varied widely among crops and locations. They noted in general, however, that 70 percent of soybean, 65 percent of corn, 67 percent of wheat, and 40 percent of cotton acres used conservation tillage practices, which included no-till, strip-till, and mulch-till. Mulch-till refers to a technique in which organic materials, such as crop residues or mulch, are left on the soil surface and incorporated into the top layer of soil through tillage. The purpose of mulch-till is to improve soil fertility, moisture retention, and weed suppression while reducing soil erosion.

Bergtold and Sailus [4] edited a book that discussed the production, profitability, and stewardship involving conservation tillage systems in the southeast U.S. One of the chapters in the book focused on conservation economics [5]. The authors of this chapter indicated that in order to achieve goals related to maximizing profit and environmental stewardship requires an understanding of tools such as partial budgeting and/or enterprise budgets.

Practices such as the adoption of a no-till crop rotation often involve a learning curve. This fact was confirmed by Cusser et al. [6] who compared the development and stability of a no-till crop rotation with a conventional till system over a 29-year period. The authors indicated that it took over a decade to ascertain the impacts of the no-till system, underscoring the importance of long-run studies.

Precision Conservation Management [7] summarized gross revenue, production costs, soil loss, and greenhouse gas (GHG) emissions for various tillage systems including no-till, strip-till, 1-pass light, 2-pass light, 2-pass moderate, and 2+ passes. The “light” passes utilized low disturbance tillage. Operator and land return were higher for the 1-pass light, 2-pass light, and 2-pass moderate systems than it was for no-till, strip-till, and 2+ passes. In particular, the return for the no-till system was from $19 to $30 lower than the return for the light and moderate pass systems. However, soil loss and GHG emissions were lower for the no-till system than they were for other tillage systems examined.

Next, we will turn our attention to previous research pertaining to cover crops. Plastina et al. [8] used partial budgets to assess the economic return to cover crop use on Midwest U.S. row crop farms. Essentially, the authors compared returns and costs for farms that utilized cover crops to those that did not utilize cover crops. The economic loss accruing to use of cover crops terminated with herbicides in a corn/soybean rotation was $12 per acre with the inclusion of cost-share payments and $43 per acre without the inclusion of these payments. Plastina et al. [9] used focus groups and a partial budgeting framework to compare the net returns of crop systems with and without the use of cover crops. The net change in profits associated with cover crop use was a negative $54 per acre.

Myers et al. [10] note that additional net returns generated from the adoption of cover crops is difficult to discern with one-year budget analysis. The authors noted that some farms have a very long-term positive experience associated with the use of cover crops. Cover crops were found to provide a faster payment when herbicide-resistant weeds are a problem, cover crops are grazed, soil compaction is an issue, cover crops are used to speed up and ease the transition to no-till, soil moisture is at a deficit, fertilizer costs are high, and incentive payments are available.

A recent USDA-ERS publication noted that the share of harvested cropland with cover crops increased from 3.4 percent in 2012 to 5.1 percent in 2017 [2]. This study noted that unlike no-till and conservation tillage, cover crops involve increased costs, particularly in the short term. A recent survey by the Conservation Tillage Information Center [11] indicated that cover crops are typically combined with a no-till system. Approximately 12 percent of those surveyed went from not using cover crops to using cover crops on some of their acres between 2015 and 2019. Over half of the respondents used cover crops on at least 40 percent of their crop acres.

Gross revenue, production costs, soil loss, and GHG emissions for a no cover crop system and two cover crop systems, overwintering and winter terminal, are summarized by Precision Conservation Management [7] and Sellars et al. [12]. Operator and land return for the overwintering and winter terminal cover crop systems used for corn production (soybean production) were $32 ($44) and $12 per acre ($21 per acre) lower than the return under the no cover crop system, respectively. As with the utilization of a no-till system, soil loss and GHG emissions were reduced by utilizing the cover crop systems.

The potential to sequester carbon in agricultural soils has increased public and private interest in markets that pay farmers to sequester carbon using various management practices. Two common management practices discussed are the adoption of a no-till system or the use of cover crops. In their review of the literature, Havens et al. [13] noted that the average implementation cost for no-till was $17 per acre and that the average implementation cost for cover crops was $31 per acre. On average, sequestration resulted from the adoption of a no-till system and cover crops would be 0.77 and 0.76 metric tons per acre. In addition to discussing the average sequestration and average cost per acre, the authors estimated that the social benefit of sequestration would be $51 per metric ton of CO₂, which would more than offset the expected cost of implementing no-till or cover crop systems.

Thompson et al. [14] reported recent survey results pertaining to farm adoption of carbon contracts. Of the survey respondents, 39 percent were aware of opportunities to receive payments for capturing carbon, 7.1 percent had actively engaged in discussions regarding receiving payments for capturing carbon, and 1.3 percent had signed a contract to capture carbon. In a follow-up question, reasons preventing producers from enrolling, in order of percentage responding affirmatively, were payment level offered that was not large enough, potential legal liability, skepticism of carbon sequestration viability, and previous use of eligible practices were not covered under the contract.

In a series of Ag Decision Maker articles, Plastina [15], Plastina and Jo [16], and Plastina and Wongpiyabovorn [17] discuss carbon markets; how data, payments, and methods are made in carbon programs; and describe a tool that can be used to examine the potential net returns for carbon farming. Net returns are dependent on farming practices, contract type, contract length, frequency of additional practice implementation, contract price for each practice, expected change in contract price, farm area enrolled, participation in cost share programs, expected changes in costs, and discount rate. Plastina [15] noted that programs typically require additionality to generate payments. Additionality means that farmers must do something different or adopt a new practice to receive carbon payments.

3. Methods

Experimental data that contain all of the variables that need to be explored when examining tradeoffs between key variables are lacking. However, it is possible to develop a conceptual framework and provide an illustration using available data sources pertaining to crop budgets, soil health parameters, and net greenhouse gas emissions.

Crop budgets for 2015–2021 were developed using several sources of information. Crop yield data were obtained from Precision Conservation Management [7], Schnitkey and Swanson [18, 19], and Sellars et al. [12]. Most of the tillage scenarios reported in Precision Conservation Management [7] could be considered conservation tillage systems, so the crop system used to compare with the no-till and cover cropping systems will be referred to as a conservation tillage system. Crop yield data for the conservation tillage system were obtained from Precision Conservation Management [7] and Schnitkey and Swanson [18, 19]. Yields for corn and soybeans produced after a cover crop were obtained from Sellars et al. [12]. Annual yield data were not available for the no-till practice from the sources noted above so additional assumptions were needed to estimate crop yields. For corn, the average difference between corn yields for a no-till and a 1-pass light (i.e., one pass with low disturbance) was used to estimate annual yields. For soybeans, the relationship between soybean crop yields generated under a no-till system and under miscellaneous tillage systems reported by the Center for Farm Financial Management [20] was used to estimate annual yields. Crop price, government payments, and crop insurance indemnity payments were obtained from Schnitkey and Swanson [18, 19].

Cost information for direct costs (fertilizers, pesticides, seed, cover crop seed, drying, storage, and crop insurance), power costs (tillage, fertilizer application, spraying, planting, harvesting, and grain hauling), and overhead costs (hired labor, building repairs and depreciation, insurance, and interest) was obtained from Precision Conservation Management [7] and Schnitkey and Swanson [18, 19]. To account for the use of soybean yields from the Center for Farm Financial Management [20] for the no-till system, the relationship between soybean costs using a no-till system and miscellaneous tillage systems was utilized to estimate soybean costs.

Net return was computed by subtracting direct costs, power costs, and overhead costs from gross revenue, which consisted of crop revenue (crop price × crop yield), government payments, and crop insurance indemnity payments. Net return excludes operator and land costs so it can be interpreted as a net return to operator and land.

For risk averse decision makers, the choice between conservation practices depends on not only the expected net return and soil health and net greenhouse gas emissions, but also the variability in net returns. For example, if a particular conservation practice reduces or increases crop yield variability, this fact will be important to decision makers. One of the ways to incorporate net return variability into the analysis is to compute the certainty equivalent of net returns for each conservation practice. The certainty equivalent of net returns represents a risk-adjusted net return. In other words, it incorporates both expected net return and risk. Certainty equivalents are computed using an expected utility function and specific levels of risk aversion [21]. The power utility function was used to compute certainty equivalents in this study. This utility function has been used extensively to model risk aversion in production agriculture [22]. Relative risk aversion levels of 0, 1, 3, and 5 were used in this study. A relative risk aversion level of 0 is applicable to a risk-neutral decision maker. Someone with these preferences would choose the conservation practice with the highest average net return. Risk aversion levels of 1, 3, and 5 represent slightly, moderately, and strongly risk averse preferences [21].

In addition to comparing the expected net return and certainty equivalents among the conservation practices, a conceptual framework was developed to examine the tradeoffs between net return, risk, soil loss, and GHG emissions. This conceptual framework is consistent with the notion that farms use a multidimensional framework when making decisions [23, 24]. The specific model used represents a modified version of the Target MOTAD model. The Target MOTAD model maximizes expected net return subject to a constraint on downside risk, which is measured as the total negative deviations below a specified target [25, 26]. A target income or net return to land and operator labor of $280 was used. This target income represents the average cash rent over the study period. Constraints related to soil loss and gas emissions were added to the Target MOTAD model so that tradeoffs could be examined. A similar approach was used by Stucky [27] and Stucky et al. [28] to examine the tradeoff between return to labor and management, risk, and water quality for crop rotations in Kansas.

Solutions to the modified Target MOTAD model are generated by relaxing the constraints on downside risk, soil loss, and net greenhouse gas emissions. Each solution contains information on the expected net return, downside risk or the total negative deviations below a specified target, soil loss, and net greenhouse gas emissions.

4. Results and discussion

Table 1 presents the annual net return, average net return, level of downside risk, soil loss, and greenhouse gas (GHG) emissions for each crop and conservation practice. The base case, as noted above, assumes the use of a conservation tillage system. Downside risk in Table 1 is represented using average annual negative deviations rather than total negative deviations below the target net return of $280. In general, soybeans were more profitable than corn during the study period.

	Base case		No-till		Cover crop
Item	Corn	Soybeans	Corn	Soybeans	Corn	Soybeans
2015	232	309	215	206	229	262
2016	233	349	215	316	206	301
2017	212	314	194	309	177	266
2018	297	448	278	455	242	401
2019	287	325	270	340	233	278
2020	425	395	404	377	373	345
2021	696	585	665	667	613	525
Avg NR ($/acre)	340	389	320	381	296	340
Downside risk ($/acre)	−23	0	−32	−11	−45	−5
Soil loss (tons/acre)	0.93	1.29	0.55	0.90	0.64	0.96
GHG emissions (mt C/acre)	0.30	−0.28	−0.32	−1.12	−0.72	−1.76

Table 1.

Crop net return, soil loss, and GHG emissions for alternative conservation practices.

Without considering soil health and net greenhouse gas emissions which will be addressed below, a risk neutral decision maker would choose the conservation practice with the highest net return. Assuming the adoption of a corn/soybean rotation, the net return for corn and soybeans is the highest for the base case. The average difference in net returns between the base case and the no-till system was $20 per acre for corn and $8 per acre for soybeans. The difference between net returns was larger for the comparison between the base case and the cover crop system. For corn, net return using cover crops was $44 per acre lower than the base case. The net return difference for soybeans was even greater at $49 per acre.

Soil loss and net greenhouse gas emissions can be reduced by adopting a no-till or cover crop system. The no-till system results in the largest drop in soil loss, while the cover crop system exhibits the largest reduction in net greenhouse gas emissions.

The certainty equivalent of net return (CE) for each crop and conservation practice is depicted in Table 2. The crop enterprise with the #1 label refers to the base case. The crop enterprise labels designated as #2 and #3 refer to the no-till system and the cover crop system, respectively. The differences in CEs among risk aversion levels for corn are similar to the difference in average net returns illustrated in Table 1. In contrast, the difference in CEs between soybean enterprises depends on the level of risk aversion. What explains these results? If there is not much difference in annual net returns between conservation practices, which is the case for corn, the CE results will not differ very much from the average net return results. For soybeans, the annual net returns across conservation practices differ more than it does for corn; thus, comparisons between soybean enterprises will depend more on the level of risk aversion. Too see this, let us focus on the comparison between soybean net returns for the base case and soybean net returns for the no-till system. The largest divergence in net returns was for 2015 and 2021. In 2015, soybean net returns were substantially lower for the no-till system. In contrast, for 2021, net returns were relatively lower for the base case.

	Relative risk aversion
Item	r = 1	r = 3	r = 5
C #1	312	278	261
S #1	380	365	355
C #2	292	259	242
S #2	360	324	295
C #3	271	242	227
S #3	330	314	314
C #1 minus C #2	20	20	19
C #1 minus C #3	41	36	34
S #1 minus S #2	20	41	59
S #1 minus S #3	50	51	41

Table 2.

Certainty equivalent of net returns for corn and soybean enterprises ($/acre).

In summary, results in Tables 1 and 2 indicate that net returns and risk-adjusted net returns were higher for the base case than they were for the no-till and cover crop systems. Assuming a corn/soybean rotation, the average difference in CEs between the base case and the no-till system was $26, and the average difference in CEs between the base case and the cover crop system was $43. These results did not account for differences in soil loss and GHG emissions. The modified Target MOTAD results discussed below will incorporate differences in these items.

Three sets of results for the modified Target MOTAD model are illustrated in Table 3. Scenario #1 represents the maximum expected net return solution. Because soil loss and GHG emissions were not constrained for the base case, the values for these two conservation dimensions are the highest for the base case scenario. Also, note that corn and soybeans produced under the base case are part of a conservation tillage system. The other two scenarios illustrate solutions for a GHG emission constraint of −0.50 and −1.00, respectively. As in Table 2, the crop enterprise with the #1 label refers to the base case, the crop enterprises with the #2 label refers to the no-till system, and the crop enterprise with the #3 label refers to cover cropping system.

Item	Scenario #1	Scenario #2	Scenario #3
C #1	0.500	0.151	0.000
S #1	0.500	0.151	0.000
C #2	0.000	0.349	0.231
S #2	0.000	0.349	0.231
C #3	0.000	0.000	0.269
S #3	0.000	0.000	0.269
Expected net return ($/acre)	364.79	355.00	333.09
Negative deviations ($/acre/year)	3.79	11.90	16.85
Soil loss (tons/acre)	1.11	0.84	0.77
GHG emissions (mt C/acre)	0.01	−0.50	−1.00

Table 3.

Expected net return, risk, soil loss, and GHG emissions for alternative scenarios.

As expected, the maximum net return solution produces corn and soybeans using the conservation tillage system, or the base case. Expected net return for the solution is $365 and average annual negative deviations below the $280 target net return is $4. Soil loss for this solution is 1.11 tons per acre and GHG emissions are 0.01 mt C per acre. With scenario #2, GHG emissions are reduced to −0.50 mt C per acre and soil loss is reduced approximately 24 percent. To achieve these reductions, net return per acre was reduced $10 per acre and downside risk increased from $4 per acre to $12 per acre. Under this scenario, approximately 30 percent of crops were produced using the conservation tillage rotation. The other 70 percent of crops were produced using the no-till system.

With scenario #3, GHG emissions are reduced to −1.00 mt C per acre and soil loss is reduced approximately 31 percent. These reductions were achieved by producing 46 percent of the crops under the no-till system and 54 percent of the crops under the cover cropping system. Not surprisingly, given the difficulty of reducing GHG emissions from 0.01 to −1.00, the reduction in expected net returns and increase in downside risk when comparing the shift from scenario #1 to #2 with the shift from scenario #1 to #3 were larger in this instance. Specifically, net return was reduced by $32 per acre and downside risk increased from $4 per acre to $17 per acre under scenario #3.

There are several extensions that could be made to the conceptual framework presented in this study. First, it would be helpful to include more years in the comparisons among crop systems. This would ensure that we are properly capturing the difference in crop yields and costs between the systems. Given the learning curves associated with adopting a no-till or cover crop rotation, this point is particularly salient [6, 10]. Second, it would be helpful if annual data pertaining to soil loss and GHG emissions were available. With these data, it would be possible to generate another set of constraints that would capture the risk associated with not achieving a target level of soil loss or GHG emissions. With annual data, years with higher soil loss or GHG emissions, due to whatever cause (e.g., weather fluctuations), than a target, which could be represented by the averages for a sample period, would be penalized. For example, using a similar conceptual framework, Stucky et al. [28] examined improvements in water quality one variable at a time. Solutions examining each water quality variable were constrained so that deviations below the target could not increase above those from the net return maximizing solution and by not allowing any of the water quality variables except for the variable of interest to exceed average levels.

5. Conclusions

This chapter examined the relationship between crop net returns and conservation practices. The conceptual framework developed can be used to compare crop net returns, risk, soil loss, and GHG emissions for different conservation practices. Using an example that compared net returns, downside risk, soil loss, and GHG emissions, it was possible to reduce both soil loss and GHG emissions. However, these reductions came at a cost. To achieve a reduction in GHG emissions of approximately −0.50 mt C per acre, it was necessary to produce part of the crops under a no-till system. For this case, expected net return was reduced approximately $10 per acre and downside risk increased approximately $8 per acre compared to the maximum expected net return solution, which involved producing corn and soybeans utilizing a conservation tillage rotation. A reduction in GHG emissions of −1.00 mt C per acre was achieved by utilizing a combination of the no-till and cover crop systems. The reduction in expected net return was approximately $32 per acre, and the increase in downside risk was approximately $13 per acre in this case.

Conflict of interest

The author declares no conflict of interest.