IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i2p273-d746778.html
   My bibliography  Save this article

Characterizing Dominant Field-Scale Cropping Sequences for a Potato and Vegetable Growing Region in Central Wisconsin

Author

Listed:
  • Emily Marrs Heineman

    (Nelson Institute for Environmental Studies, University of Wisconsin-Madison, Madison, WI 53706, USA)

  • Christopher J. Kucharik

    (Nelson Institute for Environmental Studies, University of Wisconsin-Madison, Madison, WI 53706, USA
    Department of Agronomy, University of Wisconsin-Madison, Madison, WI 53706, USA)

Abstract

Crop rotations are known to improve soil health by replenishing lost nutrients, increasing organic matter, improving microbial activity, and reducing disease risk and weed pressure. We characterized the spatial distribution of crops and dominant field-scale cropping sequences from 2008 to 2019 for the Wisconsin Central Sands (WCS) region, a major producer of potato and vegetables in the U.S. The dominant two- and three-year rotations were determined, with an additional focus on assessing regional potato rotation management. Our results suggest corn and soybean are the two most widely planted crops, occurring on 67% and 36% of all agricultural land at least once during the study period. The most frequent two- and three-year crop rotations include corn, soybean, alfalfa, sweet corn, potato, and beans, with continuous corn being the most dominant two- and three-year rotations (13.2% and 8.5% of agricultural land, respectively). While four- and five-year rotations for potato are recommended to combat pest and disease pressure, 23.2% and 65.9% of potato fields returned to that crop in rotation after two and three years, respectively. Furthermore, 5.6% of potato fields were planted continuously with that crop. Given potato’s high nitrogen (N) fertilizer requirements, the prevalence of sandy soils, and ongoing water quality issues, adopting more widespread use of four- or five-year rotations of potato with crops that require zero or less N fertilizer could reduce groundwater nitrate concentrations and improve water quality.

Suggested Citation

  • Emily Marrs Heineman & Christopher J. Kucharik, 2022. "Characterizing Dominant Field-Scale Cropping Sequences for a Potato and Vegetable Growing Region in Central Wisconsin," Land, MDPI, vol. 11(2), pages 1-16, February.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:2:p:273-:d:746778
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/2/273/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/11/2/273/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David A. Hennessy, 2006. "On Monoculture and the Structure of Crop Rotations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(4), pages 900-914.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wade, Tara & Kurkalova, Lyubov & Secchi, Silvia, 2016. "Modeling Field-Level Conservation Tillage Adoption with Aggregate Choice Data," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(2), May.
    2. Liu, Xing & Lehtonen, Heikki & Purola, Tuomo & Pavlova, Yulia & Rötter, Reimund & Palosuo, Taru, 2016. "Dynamic economic modelling of crop rotations with farm management practices under future pest pressure," Agricultural Systems, Elsevier, vol. 144(C), pages 65-76.
    3. Hongli Feng & Bruce A. Babcock, 2010. "Impacts of Ethanol on Planted Acreage in Market Equilibrium," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(3), pages 789-802.
    4. Mauro Vigani & Manuel Gomez-Barbero & Emilio Rodríguez-Cerezo, 2015. "The determinants of wheat yields: the role of sustainable innovation, policies and risks in France and Hungary," JRC Research Reports JRC95950, Joint Research Centre.
    5. Thomas, Alban & Chakir, Raja, 2020. "Unintended consequences of environmental policies: the case of set-aside and agricultural intensification," TSE Working Papers 20-1066, Toulouse School of Economics (TSE).
    6. Ji, Yongjie & Rabotyagov, Sergey & Kling, Catherine L., 2014. "Crop Choice and Rotational Effects: A Dynamic Model of Land Use in Iowa in Recent Years," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170366, Agricultural and Applied Economics Association.
    7. Ji, Yongjie & Rabotyagov, sergey & Valcu-Lisman, Adriana, 2015. "Estimating Adoption of Cover Crops Using Preferences Revealed by a Dynamic Crop Choice Model," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205799, Agricultural and Applied Economics Association.
    8. Bohan, David & Schmucki, Reto & Abay, Abrha & Termansen, Mette & Bane, Miranda & Charalabiis, Alice & Cong, Rong-Gang & Derocles, Stephane & Dorner, Zita & Forster, Matthieu & Gibert, Caroline & Harro, 2020. "Designing farmer-acceptable rotations that assure ecosystem service provision inthe face of climate change," MPRA Paper 112313, University Library of Munich, Germany.
    9. Kurkalova, Lyubov A. & Randall, Stephen M., 2015. "Elasticities of demand for energy inputs in crop production: impact of rotation," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205298, Agricultural and Applied Economics Association.
    10. Federico Ciliberto & GianCarlo Moschini & Edward D. Perry, 2019. "Valuing product innovation: genetically engineered varieties in US corn and soybeans," RAND Journal of Economics, RAND Corporation, vol. 50(3), pages 615-644, September.
    11. Ibirénoyé Romaric Sodjahin & Fabienne Femenia & Obafemi Philippe Koutchade & A. Carpentier, 2022. "On the economic value of the agronomic effects of crop diversification for farmers: estimation based on farm cost accounting data [Valeur économique des effets agronomiques de la diversification de," Working Papers hal-03639951, HAL.
    12. Ridier, Aude & Chaib, Karim & Roussy, Caroline, 2012. "The adoption of innovative cropping systems under price and production risks: a dynamic model of crop rotation choice," Working Papers 207985, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    13. Renwick, Alan W. & Revoredo-Giha, Cesar & Topp, Kairsty, 2007. "Modelling the Adoption of Crop Rotation Practices in Organic Mixed Farms," Working Papers 109390, Scotland's Rural College (formerly Scottish Agricultural College), Land Economy & Environment Research Group.
    14. Hongli Feng & Ofir D. Rubin & Bruce A. Babcock, 2008. "Greenhouse Gas Impacts of Ethanol from Iowa Corn: Life Cycle Analysis versus System-wide Accounting," Center for Agricultural and Rural Development (CARD) Publications 08-wp461, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    15. Kaninda Tshikala, Sam & Fonsah, Esendugue Greg & Boyhan, George & Little, Elizabeth & Gaskin, Julia, 2018. "Crop Rotation Systems for High-Value, Cool-Season Vegetables in the Southern United States," Journal of Food Distribution Research, Food Distribution Research Society, vol. 49(1), March.
    16. Xiaodong Du & David A. Hennessy & Cindy L. Yu, 2012. "Testing Day's Conjecture that More Nitrogen Decreases Crop Yield Skewness," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(1), pages 225-237.
    17. Sanna Lötjönen & Markku Ollikainen, 2017. "Does crop rotation with legumes provide an efficient means to reduce nutrient loads and GHG emissions?," Review of Agricultural, Food and Environmental Studies, Springer, vol. 98(4), pages 283-312, December.
    18. François Bareille & Pierre Dupraz, 2017. "Biodiversity Productive Capacity in Mixed Farms of North-West of France: a Multi-output Primal System," Working Papers SMART 17-03, INRAE UMR SMART.
    19. Deininger,Klaus W. & Ali,Daniel Ayalew & Kussul,Nataliia & Lavreniuk,Mykola & Nivievskyi,Oleg, 2020. "Using Machine Learning to Assess Yield Impacts of Crop Rotation : Combining Satellite and Statistical Data for Ukraine," Policy Research Working Paper Series 9306, The World Bank.
    20. Alain Carpentier & Elodie Letort, 2010. "Simple econometric models for short term production choices in cropping systems," Working Papers SMART 10-11, INRAE UMR SMART.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:11:y:2022:i:2:p:273-:d:746778. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.