Introduction
Cover crops provide a myriad of environmental and agronomic benefits (Hillel, Reference Hillel2005), leading to more sustainable agricultural production. They can reduce soil erosion, add organic matter, reduce nutrient losses, reduce pest populations, reduce compaction, improve soil structure, aid in water management, and provide emergency forages for livestock consumption (Snapp et al., Reference Snapp, Swinton, Labarta, Mutch, Black, Leep, Nyiraneza and O'Neil2005; Blanco-Canqui et al., Reference Blanco-Canqui, Shaver, Lindquist, Shapiro, Elmore, Francis and Hergert2015). Cover crops can also provide broader ecosystem services such as enhancing biological diversity and water quality (Van Alfen, Reference Van Alfen2014; Van Eerd et al., Reference Van Eerd, Chahal, Peng and Awrey2023). Agronomic benefits from cover crops include increases in crop yield (Lenzi et al., Reference Lenzi, Antichi, Bigongiali, Mazzoncini, Migliorini and Tesi2009; Li et al., Reference Li, Peterson, Tautges, Scow and Gaudin2019; Sainju, Singh and Whitehead, Reference Sainju, Singh and Whitehead2001), weed suppression (Price et al., Reference Price, Duzy, Balkcom, Kelton, Kornecki and Sarunaite2016), and lowered N input requirements (Frye, Smith and Williams, Reference Frye, Smith and Williams1985). Thus, cover crops contribute to agroecosystem sustainability and food security.
Despite the environmental and agronomic benefits of cover crops, the economic and financial consequences are less clear. While researchers tend to find that cover crops influence the yield (and revenue) of the subsequent cash crops, the direction and magnitude of this yield effect changes with species of cover crop and timeframe (Muchanga, et al., Reference Muchanga, Hirata, Uchida, Hatano and Araki2020; Bourgeois et al., Reference Bourgeois, Charles, Van Eerd, Tremblay, Lynch, Bourgeois, Bastien, Belanger, Landry and Vanasse2022). For example, short-term yield losses leading to long-term gains are possible, depending on soil characteristics (Creamer et al., Reference Creamer, Bennett, Stinner and Cardina1996; Nunes et al., Reference Nunes, Van Es, Schindelbeck, Ristow and Ryan2018). However, there is mixed evidence regarding whether the added costs of establishment and termination are greater or less than the additional returns expected from yield increases (Cai et al., Reference Cai, Udawatta, Gantzer, Jose, Godsey and Cartwright2019; Chahal et al., Reference Chahal, Vyn, Mayers and Van Eerd2020; Yanni et al., Reference Yanni, De Laporte, Rajsic, Wagner-Riddle and Weersink2021).
Previous financial and economic assessments of cover crops have been conducted on field crops (Frye, Smith and Williams, Reference Frye, Smith and Williams1985; Gabriel, Garrido and Quemada, Reference Gabriel, Garrido and Quemada2013), such as cotton (Boyer et al., Reference Boyer, Lambert, Larson and Tyler2018; Morton, Bergtold and Price, Reference Morton, Bergtold and Price2006), corn, soybean, and wheat (Champagne et al., Reference Champagne, Wallace, Curran and Baraibar2021; Janovicek et al., Reference Janovicek, Hooker, Weersink, Vyn and Deen2021). Some research has employed cost–benefit analysis and financial accounting to assess cover crop viability (Bounaffaa, Reference Bounaffaa2015; DeVincentis et al., Reference DeVincentis, Solis, Bruno, Leavitt, Gomes, Rice and Zaccaria2020; Pratt et al., Reference Pratt, Tyner, Muth and Kladivko2014; Snapp et al., Reference Snapp, Swinton, Labarta, Mutch, Black, Leep, Nyiraneza and O'Neil2005). The financial feasibility of cover crops within a vegetable crop farming system, particularly with field processing tomatoes, have been investigated in the United States (DiGiacomo et al., Reference DiGiacomo, Gieske, Grossman, Jacobsen, Peterson and Rivard2023; Price et al., Reference Price, Duzy, Balkcom, Kelton, Kornecki and Sarunaite2016), and in Canada (Belfry et al., Reference Belfry, Trueman, Vyn, Loewen and Van Eerd2017; Chahal et al., Reference Chahal, Vyn, Mayers and Van Eerd2020), but only for limited timeframes.
The production of processing tomatoes in Ontario, Canada is centered in Chatham-Kent and Essex counties in the extreme southwest of the province due to unique climate factors, including a long growing season, neutral (pH of 6.2–6.8), well-drained soil, and proximity to processing facilities. Total area of processing tomato production in Ontario since 2010 has averaged approximately 4900 ha. Yield per hectare has been increasing over time, while there have been fluctuations in gross farm value (Statistics Canada, 2021). Therefore, valuation of management practices that affect sustainability, like cover cropping, N application, and residue management, is critical for assessing the viability of tomato-based food production.
The purpose of this study is to investigate the effects of several cover crop options, along with nitrogen (N) application and winter wheat residue management, on processing tomato yield and profitability in Ontario's temperate humid climate, using farm-level financial analysis. The specific objectives of this research are to:
1) evaluate the effects of four different cover crop treatments, N application, and preceding crop residue management on the yield of processing tomatoes, over six growing seasons; and
2) determine the financial impact of the four cover crop treatments, N application, and residue management for processed tomatoes.
Better understanding of the financial implications of sustainable management practices (i.e., cover crops, fertilizer N and crop residue management) provides growers key information to assist in making management decisions that buttress sustainable adaptation efforts.
Methods and data
Experimental design and plot description
An ongoing research experiment was initiated in 2007 (Site A) and repeated a few meters adjacent in 2008 (Site B) at the Ontario Crops Research Centre, Ridgetown, ON, Canada (42.46 N, 81.89 W) using a split-split plot design with cover crop treatments arranged in a randomized complete block design with four replications (Belfry et al., Reference Belfry, Trueman, Vyn, Loewen and Van Eerd2017; Chahal and Van Eerd, Reference Chahal and Van Eerd2021; Trueman et al., Reference Trueman, Awrey, Delaporte, Kerr, Weersink and Van Eerd2023). Soil texture was a sandy loam (Orthic Humic Gleysol), and the field was tile drained. This site had a temperate humid climate with a 30-year mean annual air temperature of 9.6°C and 30-year mean annual total precipitation of 900 mm. This experiment assessed the interaction of cover crop, fertilizer N, and crop residue management treatments applied in selected main crops within a nine-year vegetable and field crop rotation at both sites with Site B lagged one year from Site A. The rotation crop order was: (1) processing peas-CC, (2) sweet corn-CC, (3) spring (or winter) wheat-CC, (4) processing tomato-CC, (5), grain corn, (6) squash-CC, (7) soybeans, (8) winter wheat-CC, and (9) processing tomato-CC, where CC indicates that a cover crop was planted after main crop harvest. Depending on the main crop harvest date, cover crops were either planted in late July, August, or early September, accumulating at least 1 Mg ha−1 of dry biomass, and remained in place until the following spring (Belfry et al., Reference Belfry, Trueman, Vyn, Loewen and Van Eerd2017; Chahal et al., Reference Chahal, Vyn, Mayers and Van Eerd2020).
This study isolated the processing tomato data obtained in years four and nine of the rotation. It measured the yield and financial consequences of cover crops planted after wheat the previous season, preplant fertilizer N application and preceding wheat residue management. We analyze the subset of data (Table 1) from 2010 to 2020 of six years with tomatoes (2010, 2015, and 2019 at Site A and 2011, 2016, and 2020 at Site B). The main plot factor (6 m by 16 m) was autumn cover crop treatment (i.e., planted after wheat and before tomatoes). The split plot factor (6 m by 8 m) implemented in the years preceding tomato production (2014 and 2018 at Site A; 2015 and 2019 at Site B) was wheat crop residue management (removal versus retention). In 2010, 2019 (Site A), 2011, and 2020 (Site B), there was also a split-split plot factor (6 m by 4 m) of N fertilizer applied to the tomato crop (140 kg N ha−1 versus zero).
Table 1. Site location (side-by-side in Ridgetown, ON), main plot, split plot and split-split plot factor for each year of tomato data considered in this study
a Results not presented in this study due to only being considered in the first two years.
Cropping practices
The cropping practices for this study were detailed in Belfry et al. (Reference Belfry, Trueman, Vyn, Loewen and Van Eerd2017) for 2010 and 2011, in Chahal and Van Eerd (Reference Chahal and Van Eerd2018; Reference Chahal and Van Eerd2021) for 2015 and 2016, and in Trueman et al. (Reference Trueman, Awrey, Delaporte, Kerr, Weersink and Van Eerd2023) for 2019 and 2020. The year before tomato production, after wheat mechanical grain harvest, crop residue was either retained (evenly distributed with rake by hand) or removed (raked, collected, and removed by hand) to implement the residue management split-plot factor treatments. Cover crops were direct seeded after wheat harvest in late July or early August. There were five annual cover crop main-plot treatments: (1) no cover crop control; (2) oat (Avena sativa L.); (3) radish (Raphanus sativus L.); (4) winter cereal rye (rye; Secale cereale L.); and (5) a mixture of rye and radish (radish-rye) planted at 81, 16, 67, and 34 plus 9 kg ha−1, respectively. No specific cultivars were used for cover crop species.
About 3 weeks after planting the four cover crops, glyphosate was applied at 540 g a.e. ha−1 to the no cover crop plots to control fall weeds (Chahal and Van Eerd, Reference Chahal and Van Eerd2021). Radish (in mono- and bi-culture) and oat were frost terminated (typically in November), but rye (in mono- and bi-culture) overwintered. In the following spring (early May), the entire trial was sprayed with glyphosate at 810 g a.e. ha−1 to control rye and weeds.
Prior to tomato transplanting (late May), split-split-plot treatments of with or without N fertilizer were established by hand-broadcasting (or not in the zero-N control split plots) calcium ammonium nitrate 27:0:0 at 140 kg N ha−1 and the entire experimental area was disced and cultivated to incorporate cover crop residues and fertilizers. Some of the fertilizer (15 kg N ha−1) was applied with water at transplanting (Belfry et al., Reference Belfry, Trueman, Vyn, Loewen and Van Eerd2017; Chahal and Van Eerd, Reference Chahal and Van Eerd2021) in the first four tomato years but this was not done in 2019 and 2020 (Trueman et al., Reference Trueman, Awrey, Delaporte, Kerr, Weersink and Van Eerd2023). Tomato seedlings for all six years of the experiment were transplanted in late May when the major risk of frost was past. All other management practices (e.g., fertilizer, pest, and weed control) were in accordance with Ontario processing tomato production guide as part of a typical production program (OMAFRA, 2020), except a ripening agent was not applied prior to harvest to allow for assessments of maturity. Each subplot, 2 m from the center two rows, was hand harvested when visual observation of the experimental area estimated that 80% of fruit was red.
Marketable fruit yield
Based on industry standards, tomato fruit was graded into five categories. The marketable categories consisted of red (exterior yellow color is <5%), green (external surface >50% yellow), and breakers (>90% blush of red, orange, or pink color). The unmarketable categories consisted of grass green (external surface being totally green or greenish-white and/or <50% yellow) and rots (OPVG, 2006). Using the marketable (red, green, and breakers) fruit weight and harvest area, marketable yield was calculated and expressed as fresh weight per hectare (Mg ha−1). For the first four years, this measure was used directly (Belfry et al., Reference Belfry, Trueman, Vyn, Loewen and Van Eerd2017; Van Eerd, Loewen and Vyn, Reference Van Eerd, Loewen and Vyn2015) and for the 2019 and 2020 seasons, these values were corrected for anthracnose lesions as these assessments were available (Trueman et al., Reference Trueman, Awrey, Delaporte, Kerr, Weersink and Van Eerd2023).
Determining yield effects from cover cropping, N application, and crop residue management on tomatoes
Analysis of variance (ANOVA) (IBM SPSS Statistics) was used to determine if marketable yields of the treatments were statistically different, and Tukey's HSD at an alpha value of 0.05 was used to determine which specific treatment means were different from one another. In this study, fixed effects were cover crop (2010, 2011, 2015, 2016, 2019, 2020), N application rate (2010, 2011, 2019, 2020) and crop residue management (2015, 2016, 2019, 2020), and the random effects were year, replicate and replicate by cover crop to account for the split-plot factor. There was a total of 80 observations in each cover crop group. This analysis was done first by year and then considering the combined six-year dataset.
Financial effects of cover cropping, N application, and crop residue management on tomatoes
This study employed partial budgeting techniques for financial analysis (DiGiacomo et al., Reference DiGiacomo, Gieske, Grossman, Jacobsen, Peterson and Rivard2023). The potential partial benefits of the cover crop, N application and preceding residue management changes detailed above included increases in revenue from higher tomato yields, and the sale of crop residue (straw). Costs from the treatments included potential decreases in tomato yields and resulting revenues, along with expenses incurred from cover crop, fertilizer N application, and wheat residue harvest.
In this study, tomato revenue changed due to marketable yield only. Quality was not assumed to change with alternative management systems. The 2022 contract price for processing tomatoes was $109.76 Mg−1 (OPVG, 2022). We employed a more conservative tomato price, fixed at $105 Mg−1, the estimated average price paid to producers between 2013 and 2022.
Cover crop costs included establishment, based on seeding rates and seed prices, and termination (Table 2). The costs of seeding, glyphosate burndown, and application were based on OMAFRA Publication 60 for switchgrass (Molenhuis, Reference Molenhuis2021) and custom rate surveys (OMAFRA, 2022). Since glyphosate was applied to the entire experimental area for ease of management (i.e., tractor and large sprayer as opposed to a back-pack sprayer) (see section ‘Cropping practices’), rather than necessity, for the financial analysis, these costs were not included for oat and radish alone treatments because they were winterkilled.
Table 2. Direct expenses of cover crop establishment (adapted from Chahal et al., Reference Chahal, Vyn, Mayers and Van Eerd2020)
a OMAFRA (2022) Table 8. Survey of Custom Farmwork Rates Charged in 2018.
b Calculated from Molenhuis (Reference Molenhuis2021) using burndown line item for switchgrass.
The price for N fertilizer assumed in this study was $1.10 kg−1 (Molenhuis, Reference Molenhuis2021). Custom N application was $24.71 ha−1 (OMAFRA, 2022).
The crop residue management revenue and cost analyses were based on straw yield and N, P, and K removed from the field. Straw bale dimensions were assumed to be 0.91 m by 0.91 m by 2.44 m. This created a 375 kg bale (Steer Planet.com, 2020). This analysis assumed that the cost of producing a large square bale was $4.72 m−1, or $11.52 bale−1 (OMAFRA, 2022). Straw yield was assumed to be 5955 kg ha−1 (Molenhuis, Reference Molenhuis2021) and consistent with 4-year sub-sampling estimates in this experiment. The amount of N removed with the straw residue was estimated to be 0.77% of bale weight, equivalent to 45.9 kg N ha−1 (Budynski, Reference Budynski2020). Given the price listed previously, N replacement costs were $50.44 ha−1. Replacement costs for P were $9.39 ha−1 (at $0.92 kg−1) and for K were $59.18 ha−1 (at $0.82 kg−1) (Molenhuis, Reference Molenhuis2021). Total residue removal costs were estimated at $301.95 ha−1. Straw prices were assumed to be $0.0662 kg−1 (RealAgriculture.com, 2021). At 5955 kg ha−1, the total revenue from the sale of wheat straw residue was $394.23 ha−1.
The breakeven yield for each treatment was determined through partial budgeting. This analysis determined the increase in tomato yield required to offset the costs of implementing the alternative management being considered. The breakeven equation for each treatment was calculated as the net cost of the treatment, independent of changes in tomato revenue, divided by the 10-year average tomato price.
Results
Yield effects
The difference in marketable yields between the treatments was first assessed by year (Table 3) and then the annual values were combined into a total dataset and analyzed over the relevant 4- to 6-year timeframes (Table 4). Tomato yields with radish cover crop were greater than without in two of the three years (i.e., in 2010 and 2016 but not 2019) when the cover crop effect was significant (Table 3; Fig. 1). However, yields under no cover crop were never significantly higher than with cover crops. Across the combined six-year dataset, the tomato yield with no cover crops was 87 Mg ha−1 (Table 4). This was statistically significantly lower than tomato yields after both radish (99.6 Mg ha−1) and radish-rye mix (95.2 Mg ha−1) cover crops based on significance groupings. Tomato yields with oat and rye only cover crops were not statistically significantly different than no cover crop nor the radish-rye mix.
Table 3. Impact of cover crop, nitrogen, and crop residue management on marketable tomato yield (Mg ha−1) in six years using ANOVA with Tukey HSD0.05 with significance groups identified by letters
Table 4. Impact of cover crop, N application and residue removal on tomato yield (Mg ha−1) in the total six-year dataset using ANOVA with Tukey HSD0.05 with significance groups identified by letters
Figure 1. Processing tomato yields by cover crop treatment by year. Statistically significant groupings with Tukey HSD0.05 in 2011, 2016, and 2019. Standard errors by year: 2010—4.474; 2011—3.117; 2015—3.904; 2016—5.601; 2019—3.149; 2020—3.711).
Applying 140 kg N ha−1 increased tomato yield in all four applicable years but this increase was only statistically significant in 2011 and 2020 (Table 3). In the combined six-year dataset, the tomato yield significantly increased by 10.1 Mg ha−1 with fertilizer N application (Table 4).
Wheat crop residue removal before tomatoes had no statistically significant impact on tomato yield in any of the four years (Table 3) or in the combined dataset (Table 4).
The interaction effects between factors were generally insignificant. For example, harvesting crop residue did not influence tomato yield regardless of fertilizer N application in any year or overall. The only year where an interaction term was statistically significant was 2011, when tomato yield was influenced by the interaction of cover crop choice and N rate (Table 3). In the six-year dataset, cover crop was the only statistically significant effect (Table 4).
Crop management and uncontrolled growing season effects, captured in the ‘year’ variable, appeared to affect tomato yields statistically significantly (Table 4). In general, based on significance groupings, 2011 and 2016 were the highest yielding years, 2010 and 2020 were in the middle, followed by 2015, while 2019 was the lowest yielding year.
The changes in tomato yield due to each of the cover crops, N application, and crop residue management treatments for financial analysis were summarized in Table 5. The base cropping system assumed was no cover crops, with no N applied, and residue retained on the field. The remaining 19 cropping options were compared to this base to establish the results, which showed that any combination of cover crops, residue removal and N application resulted in positive total yield increases in the combined dataset. However, based on 95% confidence yield intervals, only rye, radish, and the rye-radish mix, with N application, independent of residue management, were significantly different from the base. The other results were not significantly different.
Table 5. Tomato yield change by alternative cropping system compared to base [66 Mg ha−1] (No cover crop, N= 0, and wheat residue retained)
a Bold indicates that 95% confidence yield intervals do not overlap with the base.
Financial analysis
Using the average price of tomatoes for the last 10 years of $105 Mg−1 multiplied by the change in yield due to the associated treatment in Table 4 and subtracting the cost of cover crop management (Table 2), N application, and residue management, provided the average change in net returns from engaging in the practice (Table 6). The results presented assume a single period financial analysis and average overall changes in yield. The practices here were treated in isolation as independent decisions.
Table 6. Independent net financial impact of cover crops, N application and residue removal treatments using partial budgets ($ ha−1) along with the break-even yield required to offset treatment costs (Mg ha−1)
a Bold indicates statistically significant yield differences in the six-year dataset.
Examining the practices in isolation showed that all four cover crop options as well as N application and residue management resulted in positive net returns, but the oat and rye results were not significant (Table 6). Changes in yield from residue management were not significantly different from zero, but residue removal had a positive net return without any change in tomato yield ($92 ha−1), based on a straw revenue of $394 ha−1 minus the cost of removal of $302 ha−1.
The break-even yield analysis (Table 6) showed that increases in one to two Mg of tomatoes per hectare can cover the costs of all the management practices, with insignificantly small yield losses being covered by straw revenue in the case of residue removal. Similarly, the cover crops resulting in a statistically significant yield increase, radish, and radish-rye (Table 4), and N application, had lower break-even tomato prices.
The joint financial impacts of cover crop, N and crop residue management are shown in Table 7. This result was derived from Table 5, combined with changes in revenue and cost. This analysis showed that any cover crop had a net return that was higher than the base case (i.e., no cover crop control, with zero N application, and residue retention), regardless of N application and residue management. It also showed that N application increased net returns. However, depending on the cover crop and N rate, residue removal had an ambiguous effect on net returns compared to retention. Specifically, oat without N application, and radish-rye with N application, have lower net returns from crop residue removal. However, only the rye, radish, and radish-rye mix with N application, regardless of straw residue management, had changes in revenues, costs and net returns that were statistically significant from the base, based on yield intervals from Table 5.
Table 7. Change in net returns for alternative cover cropping systems ($ ha−1) from no cover crop, N application, and residue retention
a Bold indicates that 95% confidence yield intervals do not overlap with the base.
Discussion and conclusions
Financial considerations are important determinants in the uptake of sustainable innovative technologies (Barnes et al., Reference Barnes, Soto, Eory, Beck, Balafoutis, Sanchez, Vangeyte, Fountas, van der Wal and Gomez-Barbero2019; Gao and Arbuckle, Reference Gao and Arbuckle2021), including sustainable management practices like cover cropping (Lu et al., Reference Lu, Ranjan, Flores, Arbuckle, Church, Eanes, Gao, Gramig, Singh and Prokopy2022; Van Eerd et al., Reference Van Eerd, Chahal, Peng and Awrey2023). Previous studies have found mixed evidence that cover crops increase farm financial performance, in perception (Morrison and Lawley, Reference Morrison and Lawley2021), in the short run (Basche et al., Reference Basche, Archontoulis, Kaspar, Jaynes, Parkin and Miguez2016), and over longer periods (Chahal et al., Reference Chahal, Vyn, Mayers and Van Eerd2020). For tomatoes, cover crops have been shown to increase farm returns in single years (Belfry et al., Reference Belfry, Trueman, Vyn, Loewen and Van Eerd2017; Trueman et al., Reference Trueman, Awrey, Delaporte, Kerr, Weersink and Van Eerd2023), but they have also been shown to result in negative financial outcomes (DiGiacomo et al., Reference DiGiacomo, Gieske, Grossman, Jacobsen, Peterson and Rivard2023). The results of this study indicate that financial gains can be realized from careful selection of cover crop types in various annual conditions, but there is potential for loss.
Much of the financial benefit stems from yield increases with cover crops, particularly radish and a radish-rye mixture, which may be crucial to sustainable food production systems (Kopittke et al., Reference Kopittke, Menzies, Wang, McKenna and Lombi2019; Schoolman and Arbuckle, Reference Schoolman and Arbuckle2022; Van Eerd et al., Reference Van Eerd, Chahal, Peng and Awrey2023). While all four cover crops increased average actual tomato yields in the trial years (Table 5), based on 95% confidence intervals, only tomato yields influenced by rye, radish and radish-rye with N application were significantly different from the base. However, radish and radish-rye also significantly increased tomato yields in isolation (Table 4). Possible mechanisms of this difference in yield effect could be related to greater disease suppression (Trueman et al., Reference Trueman, Awrey, Delaporte, Kerr, Weersink and Van Eerd2023) and greater available N (Chahal and Van Eerd, Reference Chahal and Van Eerd2021). Coupled with reasonable costs that do not appear to exceed the benefits, carefully selected cover crops appear to increase the financial sustainability of crop production. This concept is reinforced by the break-even tomato price analysis (Table 6), where radish and radish-rye cover crops lower the tomato price required to make a profit from $105 to $93.76 and $98.66 Mg−1, respectively.
In this study, cover crops were selected based on grower experience and regional seed availability when the experiment began in 2007. As horticultural crop yield and quality can be negatively influenced by excess N fertility (Chahal et al., Reference Chahal, Baral, Congreves, Van Eerd and Wagner-Riddle2021), legume cover crops, such as red clover, were not evaluated. More than ten years later, there are many additional available cover crops and cover crop mixtures in the area, and each could have different effects, as inferred from the results of this study. This reinforces a need for additional research using different cover crops and mixtures and emphasizes careful selection of cover crop approaches.
Fertilizer N application at 140 kg ha−1 increased tomato yield by a statistically significant amount (Table 4). While N application is industry standard, the zero N rate treatment was included to examine the extent to which cover crops impact N availability to the following crop. Radish cover crop and N application as separate practices appear to have similar effects, overall (Table 6), with N application having a lower break-even yield, but higher break-even tomato price. This could make transitioning to organic production more attractive and lead to increases in cover crop adoption as suggested by Schoolman and Arbuckle (Reference Schoolman and Arbuckle2022). Alternatively, this may limit the attractiveness of cover crop use as the standard N application practice has a similar effect. Furthermore, O'Reilly et al. (Reference O'Reilly, Lauzon, Vyn and Van Eerd2012) suggested that many growers were unwilling to modify their N application behaviors due to the relatively high value of field processing vegetable crops and the lack of information surrounding cover crops on N availability for the subsequent crop. Regardless, the highest net return value in Table 7 was radish cover crop with N application. This implies that the recommended practice, with the highest net return, was radish and N application, followed by radish-rye with N application.
Removing crop residue from the winter wheat crop planted prior to tomatoes did not statistically significantly affect yields, in any year (Table 3), or in the combined six-year dataset (Table 4), compared to keeping residue in the field. Therefore, the result in Table 6 for residue removal, while showing a positive net return, has some uncertainty. There is some financial gain without a change in tomato yield ($92 ha−1) because the revenues from straw are generally higher than the costs of removal. However, there is one statistically significant scenario where residue removal is not advised (Table 7). Specifically, the rye-radish mixture with N application has higher net returns from straw retention. In this case, although there may be additional revenue from residue removal, the high value of the tomato crop means that any relative yield reduction can be detrimental. Care needs to be taken with residue removal, from a financial standpoint, and needs to be especially well considered from an environmental sustainability perspective.
The ‘Year’ variable, which implicitly captures, for example, differences in weather variables, including temperature and rainfall, and pest pressures (weeds, insects, diseases), along with minor differences in planting and harvest timing dictated mainly by weather and soil conditions, significantly impacted annual yields. All cash cropping operations are unique, in terms of inputs required, land or soil characteristics, and management type. When considering cover crops as part of an overall farm management strategy, it is important to understand that short-term changes in crop yield or soil health may not be noticeable and initial financial impacts may be negative. However, an extended outlook for yield increases and positive economic returns is necessary to successfully and fully integrate cover crops into an existing cash crop operation.
Stand-alone analysis showed that all cover crop, N application, and residue management treatments resulted in average actual positive tomato yields (Table 4) and net returns (Table 6), with increases due to N application, and radish and radish-rye mix cover crops being statistically significant. In combination, all 16 treatments provided positive processing tomato yields compared to the base (Table 5) and resulted in higher net returns (Table 7) that were significant for rye, radish, and radish-rye mix cover crops with fertilizer N applied, regardless of residue management. Therefore, rye, radish, and radish-rye cover crop adoption can be generally recommended as a beneficial management practice for tomato producers in Ontario. Building on previous literature analyzing cover crop influences on main cash crop yield and profitability, this research provides valuable information to tomato producers in southwestern Ontario, particularly that carefully selected cover crops may increase financial performance.
Competing interests
None.
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