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The role of biotechnology and biofuels in US Corn Belt cropping system changes

Published online by Cambridge University Press:  28 February 2022

Kenneth Annan ,
Evert Van der Sluis Open the ORCID record for Evert Van der Sluis [Opens in a new window] ,
Scott W. Fausti  and
Deepthi E. Kolady
Kenneth Annan
Affiliation:
Ness School of Management & Economics, South Dakota State University, Harding Hall 251, Box 2220, Brookings, SD 57007, USA
Evert Van der Sluis*
Affiliation:
Ness School of Management & Economics, South Dakota State University, Harding Hall 248, Box 2220, Brookings, SD 57007, USA
Scott W. Fausti
Affiliation:
California State University Monterey Bay (CSUMB), College of Business, 100 Campus Center, BIT 300, Seaside, CA 93955, USA
Deepthi E. Kolady
Affiliation:
Ness School of Management & Economics, South Dakota State University, Harding Hall 203, Box 2220, Brookings, SD 57007, USA
*
Author for correspondence: Evert Van der Sluis, E-mail: [email protected]
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Abstract

The effects of transgenic corn use and federal biofuel policies on state-level cropping patterns in the US Corn Belt region are investigated using state-level data from 2000 to 2019. During this time, producers moved away from diverse cropping patterns and toward simpler rotational practices. Empirical evidence indicates that the intensification of corn acres planted was positively impacted by the spread of genetically modified (GM) soybeans—used as a proxy for GM corn for biofuel usage—but the effects of biotech advancements on producer planting decisions vary across states. This suggests that future policy changes affecting corn production decisions at the farm level will also be heterogeneous across states.

Keywords

Biofuel policycorn productioncrop rotation patternsGM crop diffusionlongitudinal analysis

JEL classification

Q1: Agriculture Q4: Energy Q5: Environmental Economics
Type
Research Paper
Information
Renewable Agriculture and Food Systems , Volume 37 , Issue 4 , August 2022 , pp. 313 - 321
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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References

Aguilar, J, Gramig, GG, Hendrickson, JR, Archer, DW, Forcella, F and Liebig, MA (2015) Crop species diversity changes in the United States: 1978–2012. PLoS ONE 10, e0136580.CrossRefGoogle ScholarPubMed
Amundson, R, Berhe, AA, Hopmans, JW, Olson, C, Sztein, AE and Sparks, DL (2015) Soil science. Soil and human security in the 21st century. Science (New York, N.Y.) 348, 1261071.CrossRefGoogle ScholarPubMed
Benbrook, CM (2012) Impacts of genetically engineered crops on pesticide use in the U.S. – the first sixteen years. Environmental Sciences Europe 24, 1–13. doi: https://doi.org/10.1186/2190-4715-24-24.CrossRefGoogle Scholar
Bowles, TM, Mooshammer, M, Socolar, Y, Calderón, F, Cavigelli, MA, Culman, SW, Deen, W, Drury, CF, Garcia, AG-y, Gaudin, ACM, Harkcom, WS, Lehman, RM, Osborne, SL, Robertson, GP, Salerno, J, Schmer, MR, Strock, J and Grandy, AS (2020) Long-term evidence shows that crop-rotation diversification increases agricultural resilience to adverse growing conditions in North America. One Earth 2, 284–293.CrossRefGoogle Scholar
Bracmort, K (2020) The Renewable Fuel Standard (RFS): Waiver Authority and Modification of Volumes. Congressional Research Service, R44045, Washington, DC. August 3. Available at https://crsreports.congress.gov/product/details?prodcode=R44045.Google Scholar
Brester, GW, Atwood, J, Watts, MJ and Kawalski, A (2019) The influence of genetic modification technologies on U.S. and EU crop yields. Journal of Agricultural and Resource Economics 44, 16–31.Google Scholar
Brookes, G and Barfoot, P (2018) Farm income and production impacts of using GM crop technology 1996–2016. GM Crops & Food 9, 59–89.CrossRefGoogle ScholarPubMed
Cai, X and Stiegert, KW (2014) Market analysis of ethanol capacity. International Food and Agribusiness Management Review 17, 83–93.Google Scholar
Cap, E and Malach, V (2012) The changing patterns in land allocation to soybeans and maize in Argentina and the Americas and the role of GM varieties. A comparative analysis. International Association of Agricultural Economists, August 18–24, Foz do Iguacu, Brazil 126376.Google Scholar
Catacora-Vargas, G, Binimelis, R, Myhr, AI and Wynne, B (2018) Socio-economic research on genetically modified crops: a study of the literature. Agriculture and Human Values 35, 489–513.CrossRefGoogle Scholar
Cattaneo, MG, Yafuso, C, Schmidt, C, Huang, CY, Rahman, M, Olson, C, Ellers-Kirk, C, Orr, BJ, Marsh, SE, Antilla, L, Dutilleul, P and Carrière, Y (2006) Farm-scale evaluation of the impacts of transgenic cotton on biodiversity, pesticide use, and yield. Proceedings of the National Academy of Sciences of the USA 103, 7571–7576.CrossRefGoogle ScholarPubMed
Claassen, R, Carriazo, F and Ueda, K (2010) Grassland Conversion for Crop Production in the United States: Defining Indicators for Policy Analysis. OECD Agri-environmental Indicators: Lessons Learned and Future Directions. Washington, DC: Economic Research Service, U.S. Department of Agriculture. Available at https://www.oecd.org/greengrowth/sustainable-agriculture/44807867.pdf.Google Scholar
Davis, AS, Hill, JD, Chase, CA, Johanns, AM and Liebman, M (2012) Increasing cropping system diversity balances productivity, profitability, and environmental health. PLoS ONE 7, e47149.CrossRefGoogle ScholarPubMed
Diggle, P, Liang, K-Y and Zeger, SL (1994) Analysis of Longitudinal Data. New York: Oxford University Press.Google Scholar
Economic Research Service (2019) Genetically engineered (GE) corn varieties by State and the United States, 2000-19. Data from USDA, National Agricultural Statistics Service, June Agricultural Survey as published in the NASS report Acreage (various years). Available at https://www.ers.usda.gov/data-products/adoption-of-genetically-engineered-crops-in-the-us.aspx (Accessed 22 May 2020).Google Scholar
Economic Research Service (2021 a) U.S. Bioenergy Statistics. Available at https://ers.usda.gov/data-products/us-bioenergy-statistics.aspx (Accessed 21 February 2021).Google Scholar
Economic Research Service (2021 b) Adoption of genetically engineered crops in the U.S. Available at https://www.ers.usda.gov/data-products/adoption-of-genetically-engineered-crops-in-the-us/ (Accessed 21 February 2021).Google Scholar
Energy Information Administration (2019) U.S. ethanol plant count, capacity, and production. Available at https://afdc.energy.gov/data/10342 (Accessed 21 February 2021).Google Scholar
Fausti, SW (2015) The causes and unintended consequences of a paradigm shift in corn production practices. Environmental Science & Policy 52, 41–50.CrossRefGoogle Scholar
Fausti, SW, McDonald, TM, Lundgren, JG, Li, J, Keating, AR and Catangui, M (2012) Insecticide use and crop selection in regions with high GM adoption rates. Renewable Agriculture and Food Systems 27, 295–304.CrossRefGoogle Scholar
Fausti, SW, Van der Sluis, E, Qasmi, BA and Lundgren, J (2014) The effect of biotechnology and biofuels on U.S. Corn Belt cropping systems: updated version. SDSU, Economics Staff Paper No. 2014-1. Available at http://ageconsearch.umn.edu/handle/168202.Google Scholar
Fausti, SW, Kolady, DE, Van der Sluis, E, Lundgren, J and Qasmi, BA (2018) Extensive usage of insecticide and changing crop rotation patterns: a South Dakota case study. PLoS ONE 13, e0208222.CrossRefGoogle ScholarPubMed
Fernandez-Cornejo, J and McBride, WD (2002) Adoption of bioengineered crops (Agricultural economic report no. 810). Retrieved December 5, 2006, from USDA Economic Research Service web site http://hdl.handle.net/1805/767.Google Scholar
Fernandez-Cornejo, J, Wechsler, S, Livingston, M and Mitchell, L (2014). Genetically Engineered Crops in the United States. ERR-162. U.S. Department of Agriculture, Economic Research Service.CrossRefGoogle Scholar
Gassmann, AJ, Petzold-Maxwell, JL, Keweshan, RS and Dunbar, MW (2011) Field-evolved resistance to Bt maize by western corn rootworm. PLoS ONE 6, e22629.CrossRefGoogle ScholarPubMed
Gujarati, DN and Porter, DC (2009) Basic Econometrics, 5th Edn. New York: McGraw Hill Inc.Google Scholar
Heinemann, JA, Massaro, M, Coray, DS, Agapito-Tenfen, SZ and Wen, JD (2014) Sustainability and innovation in staple crop production in the US Midwest. International Journal of Agricultural Sustainability 12, 71–88.CrossRefGoogle Scholar
Hunt, ND, Hill, JD and Liebman, M (2017) Reducing freshwater toxicity while maintaining weed control, profits, and productivity: effects of increased crop rotation diversity and reduced herbicide usage. Environmental Science & Technology 51, 1707–1717.CrossRefGoogle ScholarPubMed
Hunt, ND, Liebman, M, Thakrar, SK and Hill, JD (2020) Fossil energy use, climate change impacts, and air quality-related human health damages of conventional and diversified cropping systems in Iowa, USA. Environmental Science & Technology 54, 11002–11014.CrossRefGoogle ScholarPubMed
Hutchison, WD, Burkness, EC, Mitchell, PD, Moon, RD, Leslie, TW, Fleischer, SJ, Abrahamson, M, Hamilton, KL, Steffey, KL, Gray, ME, Hellmich, RL, Kaster, LV, Hunt, TE, Wright, RJ, Pecinovsky, K, Rabaey, TL, Flood, BR and Raun, ES (2010) Areawide suppression of European corn borer with Bt maize reaps savings to non-Bt maize growers. Science (New York, N.Y.) 330, 222–225.CrossRefGoogle ScholarPubMed
Johnston, CA (2014) Agricultural expansion: land use shell game in the US Northern Plains. Landscape Ecology 29, 81–95.CrossRefGoogle Scholar
Landis, DA, Gardiner, MM, van der Werf, W and Swinton, SM (2008) Increasing corn for biofuel production reduces biocontrol services in agricultural landscapes. Proceedings of the National Academy of Sciences 105, 20552–20557.CrossRefGoogle ScholarPubMed
Lundgren, JG and Fausti, SW (2015) Trading biodiversity for pest problems. Science Advances 1, e1500558.CrossRefGoogle ScholarPubMed
Mercier, S (2011) Review of U.S. Food and Agricultural Policy. Policy background paper commissioned by the AGree initiative. Available at http://www.fairfoodnetwork.org/sites/default/files/Review%20of%20US%20Farm%20Programs-_110611.pdf.Google Scholar
National Academies of Sciences, Engineering, and Medicine (2016) Genetically Engineered Crops: Experiences and Prospects. Washington, DC: The National Academies Press.Google Scholar
National Agricultural Statistics Service (2019) Web Page: https://quickstats.nass.usda.gov/ (Accessed 22 May 2020).Google Scholar
National Research Council (2015) A Framework for Assessing Effects of the Food System. Washington, DC: The National Academies Press.Google Scholar
Pindyck, RS and Rubinfeld, DL (1998) Econometric Models and Economic Forecasts, 4th Edn. New York: McGraw Hill Inc.Google Scholar
Plourde, JD, Pijanowski, BC and Pekin, BK (2013) Evidence for increased monoculture cropping in the Central United States. Agriculture, Ecosystems & Environment 165, 50–59.CrossRefGoogle Scholar
Renewable Fuels Association (2021) Maps and data – U.S. ethanol plant count, capacity, and production. Available at https://afdc.energy.gov/data/10342 (Accessed 10 February 2021).Google Scholar
SAS Institute (1999) SAS/STAT® User's Guide: Chapter 41, Version 8. Cary, NC: SAS Institute Inc.Google Scholar
SAS Institute (2011) SAS/STAT® User's Guide: Chapter 6, Version 9.3. Cary, NC: SAS Institute Inc. Available at http://support.sas.com/documentation/cdl/en/statug/63962/HTML/default/viewer.htm#statug_mixed_sect003.htm (Accessed 21 February 2021).Google Scholar
Scandizzo, PL and Savastano, S (2010) The adoption and diffusion of GM crops in the United States: a real option approach. Ag Bio Forum 13, 142–157.Google Scholar
Seifert, CA, Roberts, MJ and Lobell, DB (2017) Continuous corn and soybean yield penalties across hundreds of thousands of fields. Agronomy Journal 109, 541–548.CrossRefGoogle Scholar
Sindelar, AJ, Schmer, MR, Jin, VL, Wienhold, BJ and Varvel, GE (2016) Crop rotation affects corn, grain sorghum, and soybean yields and nitrogen recovery. Agronomy Journal 108, 1592–1602.CrossRefGoogle Scholar
Stigler, M (2019) Measuring rotation effects in the US Corn Belt. Working paper. Available at https://matthieustigler.github.io/docs/rotation_effects_Stigler_standalone.pdf (Accessed 21 March 2021).Google Scholar
Turner, RE and Rabalais, NN (2003) Linking landscape and water quality in the Mississippi River Basin for 200 years. Bioscience 53, 563–572.CrossRefGoogle Scholar
Vincelli, P (2016) Genetic engineering and sustainable crop disease management: opportunities for case-by-case decision-making. Sustainability 8, 495.CrossRefGoogle Scholar
Wallander, S, Claassen, R and Nickerson, C (2011) The ethanol decade: an expansion of US corn production, 2000-09. U.S. Department of Agriculture, Economic Research Service, Economic Information Bulletin No. EIB-79. Available at https://www.ers.usda.gov/publications/pub-details/?pubid=44566.CrossRefGoogle Scholar
Wooldridge, JM (2019) Introductory Econometrics: A Modern Approach, 7th Edn. Mason, OH: South-Western Cengage Learning.Google Scholar
Wright, CK and Wimberly, MC (2013) Recent land-use change in the Western Corn Belt threatens grasslands and wetlands. PNAS 110, 4134–4139.CrossRefGoogle ScholarPubMed