Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-19T10:35:29.142Z Has data issue: false hasContentIssue false
  • English
  • Français

Agronomic and economic tradeoffs between alternative cover crop and organic soybean sequences

Published online by Cambridge University Press:  02 December 2019

Rebecca J Champagne Open the ORCID record for Rebecca J Champagne [Opens in a new window] ,
John M Wallace ,
William S Curran  and
Barbara Baraibar
Rebecca J Champagne*
Affiliation:
The Pennsylvania State University, University Park, Pennsylvania, United States The University of Maine, Orono, Maine, United States
John M Wallace
Affiliation:
The Pennsylvania State University, University Park, Pennsylvania, United States
William S Curran
Affiliation:
The Pennsylvania State University, University Park, Pennsylvania, United States
Barbara Baraibar
Affiliation:
The Pennsylvania State University, University Park, Pennsylvania, United States
*
Author for correspondence: Rebecca J Champagne, E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Organic grain producers are interested in reducing tillage to conserve soil and decrease labor and fuel costs. We examined agronomic and economic tradeoffs associated with alternative strategies for reducing tillage frequency and intensity in a cover crop–soybean (Glycine max L. Merr.) sequence within a corn (Zea mays L.)–soybean–spelt (Triticum spelta L.) organic cropping system experiment in Pennsylvania. Tillage-based soybean production preceded by a cover crop mixture of annual ryegrass (Lolium perenne L. ssp. multiflorum), orchardgrass (Dactylis glomerata L.) and forage radish (Raphanus sativus L.) interseeded into corn grain (Z. mays L.) was compared with reduced-tillage soybean production preceded by roller-crimped cereal rye (Secale cereale L.) that was sown after corn silage. Total aboveground weed biomass did not differ between soybean production strategies. Each strategy, however, was characterized by high inter-annual variability in weed abundance. Tillage-based soybean production marginally increased grain yield by 0.28 Mg ha−1 compared with reduced-tillage soybean. A path model of soybean yield indicated that soybean stand establishment and weed biomass were primary drivers of yield, but soybean production strategy had a measurable effect on yields due to factors other than within-season weed–crop competition. Cumulative tillage frequency and intensity were quantified for each cover crop—sequence using the Soil Tillage Intensity Rating (STIR) index. The reduced-tillage soybean sequence resulted in 50% less soil disturbance compared to tillage-based soybean sequence across study years. Finally, enterprise budget comparisons showed that the reduced-tillage soybean sequence resulted in lower input costs than the tillage-based soybean sequence but was approximately $114 ha−1 less profitable because of lower average yields.

Keywords

Croppingsustainabilityorganicsoybeancover cropreduced-tillageno-till
Type
Research Paper
Information
Renewable Agriculture and Food Systems , Volume 36 , Issue 1 , February 2021 , pp. 17 - 25
Check for updates
Copyright
Copyright © Cambridge University Press 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Brooker, RW, Bennett, AE, Cong, WF, Daniell, TJ, George, TS, Hallett, PD, Hawes, C, Iannetta, PM, Jones, HG, Karley, AJ, Li, L, McKenzie, BM, Pakeman, RJ, Paterson, E, Schob, C, Shen, J, Squire, G, Watson, CA, Zhang, C, Zhang, F, Zhang, J and White, PJ (2014) Improving intercropping: a synthesis of research in agronomy, plant physiology and ecology. New Phytologist 206, 107–117.CrossRefGoogle ScholarPubMed
Carr, PM (2017) Guest editorial: conservation tillage for organic farming. Agriculture 7, 19.CrossRefGoogle Scholar
Caswell, K, Wallace, JM, Curran, WS, Mirsky, SB and Ryan, MR (2019) Cover crop species and cultivars for drill-interseeding in Mid-Atlantic corn and soybean. Agronomy Journal 111, 1–8.CrossRefGoogle Scholar
Clark, A (2007) Managing Cover Crops Profitably, 3rd Edn. USDA Sustainable Agriculture Research and Education. Handbook Series Book 9. College Park: University of Maryland.Google Scholar
Cooper, J, Baranski, M, Stewart, G, Nobel-de Lange, M, Barberi, P, Fliesbach, A, Peigne, J, Berner, A, Brock, C, Casagrande, M, Crowley, O, David, C, De Vliegher, A, Doring, TF, Dupont, A, Entz, M, Grosse, M, Haase, T, Halde, C, Hammerl, V, Huiting, H, Leithold, G, Messmer, M, Schloter, M, Sukkel, W, van der Heijden, MGA, Willekens, K, Wittwer, R and Mader, P (2016) Shallow non-inversion tillage in organic farming maintains crop yields and increases soil C stocks: a meta-analysis. Agronomy for Sustainable Development 36, 22.CrossRefGoogle Scholar
Crowley, KA, Van Es, HM, Gómez, MI and Ryan, MR (2018) Trade-offs in cereal rye management strategies prior to organically managed soybean. Agronomy Journal 110, 1492–1504.CrossRefGoogle Scholar
Curran, W, Lingenfelter, D, Ryan, M, Sandy, D, Dempsey, M and Crockett, B (2014) Weed management. In Penn State Organic Crop Production Guide, 1st Edn. College of Agricultural Sciences, Penn State University, University Park, Pennsylvania, pp. 121–150.Google Scholar
Curran, WS, Hoover, RJ, Mirsky, SB, Roth, GW, Ryan, MR, Ackroyd, VJ, Wallace, JM, Dempsey, MA and Pelzer, CJ (2018) Evaluation of cover crops interseeded into corn (Zea mays L.) across the Mid-Atlantic region. Agronomy Journal 110, 435–443.CrossRefGoogle Scholar
Finney, DM, White, CM and Kaye, JP (2016) Biomass production and carbon/nitrogen ratio influence ecosystem services from cover crop mixtures. Agronomy Journal 108, 39–52.CrossRefGoogle Scholar
Grace, JB and Bollen, KA (2005) Interpreting the results from multiple regression and structural equation models. Ecological Society of America 86, 283–295.CrossRefGoogle Scholar
Jaeger, BC (2016) r2glmm: R squared for mixed (multilevel) models. R package version 0.1.2. Available at https://cran.r-project.org/web/packages/r2glmm (Accessed 15 November 2018).Google Scholar
Keene, CL and Curran, WS (2016) Optimizing high-residue cultivation timing and frequency in reduced-tillage soybean and corn. Agronomy Journal 108, 1897–1906.CrossRefGoogle Scholar
Keene, CL, Curran, WS, Wallace, JM, Ryan, MR, Mirsky, SB, VanGessel, MJ and Barbercheck, ME (2017) Cover crop termination timing is critical in organic rotational no-till systems. Agronomy Journal 109, 272–282.CrossRefGoogle Scholar
Kornecki, TS, Price, AJ and Raper, RL (2006) Performance of different roller designs in terminating rye cover crop and reducing vibration. American Society of Agricultural and Biological Engineers 22, 633–641.Google Scholar
Laughlin, D and Spurlock, S (2008) Mississippi State Budget Generator v 6.0. Software User's Manual. Available at http://www.agecon.msstate.edu/whatwedo/budgets/generator/index.asp (Accessed 7 November 2017).Google Scholar
Lefcheck, JS (2016) piecewiseSEM: Piecewise structural equation modelling in r for ecology, evolution, and systematics. R package version 2.0.2. Available at https://cran.r-project.org/web/packages/piecewiseSEM (Accessed 15 November 2018).Google Scholar
Liebert, JA and Ryan, MR (2017) High planting rates improve weed suppression, yield, and profitability in organically-managed, no-till planted soybean. Weed Technology 31, 536–549.CrossRefGoogle Scholar
Liebert, JA, DiTomasso, A and Ryan, MR (2017) Rolled mixtures of barley and cereal rye for weed suppression in cover crop-based organic no-till planted soybean. Weed Science 65, 426–439.CrossRefGoogle Scholar
Mirsky, SB, Curran, WS, Mortensen, DA, Ryan, MR and Shumway, DL (2009) Control of cereal rye with a roller/crimper as influenced by cover crop phenology. Agronomy Journal 101, 1589–1596.CrossRefGoogle Scholar
Mirsky, SB, Ryan, MR, Curran, WS, Teasdale, JR, Maul, J, Spargo, JT, Moyer, J, Grantham, AM, Weber, D, Way, T and Camargo, GG (2012) Conservation tillage issues: cover crop-based organic rotational no-till grain production in the mid-Atlantic, USA. Renewable Agriculture and Food Systems 27, 31–40.CrossRefGoogle Scholar
Mirsky, SB, Ryan, MR, Teasdale, JR, Curran, WS, Reberg-Horton, CS, Spargo, JT, Wells, MS, Keene, CL and Moyer, JW (2013) Overcoming weed management challenges in cover crop-based organic rotational no-till soybean production in the eastern United States. Weed Technology 27, 193–203.CrossRefGoogle Scholar
Mohler, CL and Teasdale, JR (1993) Response of weed emergence to rate of Vicia villosa Roth and Secale cereale L. residue. Weed Research 33, 487–499.CrossRefGoogle Scholar
Nakagawa, S and Schielzeth, H (2013) A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods in Ecology and Evolution 4, 133–142.CrossRefGoogle Scholar
Noland, RL, Wells, MS, Sheaffer, CC, Baker, JM, Martinson, KL and Coulter, JA (2018) Establishment and function of cover crops interseeded into corn. Crop Science 58, 863–873.CrossRefGoogle Scholar
Nord, EA, Curran, WS, Mortensen, DA, Mirsky, SB and Jones, BP (2011) Integrating multiple tactics for managing weeds in high residue no-till soybean. Agronomy Journal 103, 1542–1551.CrossRefGoogle Scholar
Nord, EA, Ryan, MR, Curran, WS, Mortensen, DA and Mirsky, SB (2012) Effects of management type and timing on weed suppression in soybean no-till planted into roll-crimped cereal rye. Weed Science 60, 624–633.CrossRefGoogle Scholar
Peigné, J, Ball, BC, Roger-Estrade, J and David, C (2007) Is conservation tillage suitable for organic farming? A review. Soil Use Management 23, 129–144.CrossRefGoogle Scholar
Peigné, J, Vian, JF, Payet, V and Saby, NP (2018) Soil fertility after 10 years of conservation tillage in organic farming. Soil and Tillage Research 175, 194–204.CrossRefGoogle Scholar
Pinheiro, J, Bates, D, DebRoy, S, Sarkar, D and R Core Team (2017) nlme: Linear and nonlinear mixed effects models. R package version 3.1-130. Available at https://CRAN.R-project.org/package=nlme (Accessed 15 November 2018).Google Scholar
R Core Team (2018) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available at https://www.R-project.org/ (Accessed 15 November 2018).Google Scholar
Reberg-Horton, SC, Grossman, JM, Kornecki, TS, Meijer, AD, Price, AJ, Place, GT and Webster, TM (2012) Utilizing cover crop mulches to reduce tillage in organic systems in the southeastern USA. Renewable Agriculture and Food Systems 27, 41–48.CrossRefGoogle Scholar
Ryan, MR, Mirsky, SB, Mortensen, DA, Teasdale, JR and Curran, WS (2011) Potential synergistic effects of cereal rye biomass and soybean planting density on weed suppression. Weed Science 59, 238–246.CrossRefGoogle Scholar
Snyder, EM, Curran, WS, Karsten, HD, Malcolm, GM, Duiker, SW and Hyde, JA (2016) Assessment of an integrated weed management system in no-till soybean and corn. Weed Science 64, 712–726.CrossRefGoogle Scholar
Teasdale, JR and Cavigelli, MA (2017) Meteorological fluctuations define long-term crop yield patterns in conventional and organic production systems. Nature 7, 688.Google ScholarPubMed
Teasdale, JR, Mirsky, SB and Cavigelli, MA (2018) Meteorological and management factors influencing weed abundance during 18 years of organic crop rotations. Weed Science 66, 477–484.CrossRefGoogle Scholar
USDA ARS (2016) RUSLE2. Available at https://www.ars.usda.gov/southeast-area/oxford-ms/national-sedimentation-laboratory/watershed-physical-processes-research/research/rusle2/revised-universal-soil-loss-equation-2-overview-of-rusle2/ (Accessed 7 November 2018).Google Scholar
Wallace, JM, Keene, CL, Curran, WS, Mirsky, SB, Ryan, MR and VanGessel, MJ (2017) Integrated weed management strategies in cover crop-based, organic rotational no-till corn and soybean in the mid-Atlantic region. Weed Science 66, 96–108.Google Scholar
Youngerman, CZ, DiTommaso, A, Curran, WS, Mirsky, SB and Ryan, MR (2018) Corn density effect on interseeded cover crops, weeds, and grain yield. Agronomy Journal 110, 2478–2487.CrossRefGoogle Scholar