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Spatial Regression Models For Yield Monitor Data: A Case Study From Argentina

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  • Lambert, Dayton M.
  • Lowenberg-DeBoer, James
  • Bongiovanni, Rodolfo

Abstract

Precision agricultural technology promises to move crop production closer to a manufacturing paradigm, but analysis of yield monitor, sensor and other spatial data has proven difficult because correlation among neighboring observations often violates the assumptions of classical statistical analysis. When spatial structure is ignored variance estimates tend to be inflated and significance levels of test statistics are reduced. The gap between data analysis and site-specific recommendations has been identified as one of the key constraints on widespread adoption of precision agriculture technology. This paper compares four approaches that explicitly incorporate spatial correlation into regression models: (1) a spatial econometric approach; (2) a polynomial trend regression approach; (3) a classical nearest neighbor analysis; and (4) and a geostatistic approach. In the Argentine data studied, the spatial econometric, geostatistical approach and spatial trend analysis offered stronger statistical evidence of spatial heterogeniety of nitrogen response than the ordinary least squares or nearest neighbor analysis. All the spatial models led to the same economic conclusion, which is that variable rate nitrogen is potentially profitable. The spatial econometric analysis can be implemented on relatively small data sets that do not have enough observations for estimation of the semivariogram required by geostatistics. The spatial trend analysis can be implemented with ordinary least squares functions that are already available in some GIS software. In this study, the main benefit of using spatial regression analysis is increased confidence in the corn yield response estimates by management zone, and conclusions about the profitability of precision agriculture technologies.

Suggested Citation

  • Lambert, Dayton M. & Lowenberg-DeBoer, James & Bongiovanni, Rodolfo, 2003. "Spatial Regression Models For Yield Monitor Data: A Case Study From Argentina," 2003 Annual meeting, July 27-30, Montreal, Canada 22022, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea03:22022
    DOI: 10.22004/ag.econ.22022
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    1. Bongiovanni, Rodolfo & Lowenberg-DeBoer, James, 2001. "Precision Agriculture: Economics Of Nitrogen Management In Corn Using Site-Specific Crop Response Estimates From A Spatial Regression Model," 2001 Annual meeting, August 5-8, Chicago, IL 20650, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Hurley, Terrance M. & Kilian, Bernard & Malzer, Gary L. & Dikici, Huseyin, 2001. "The Value Of Information For Variable Rate Nitrogen Applications: A Comparison Of Soil Test, Topographical, And Remote Sensing Information," 2001 Annual meeting, August 5-8, Chicago, IL 20726, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
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    1. Velandia, Margarita M. & Rejesus, Roderick M. & Segarra, Eduardo & Bronson, Kevin, 2006. "Economics of Management Zone Delineation in Cotton Precision Agriculture," 2006 Annual Meeting, February 5-8, 2006, Orlando, Florida 35387, Southern Agricultural Economics Association.
    2. Mkondiwa, Maxwell Gibson, 2015. "Whither Broad or Spatially Specific Fertilizer Recommendations?," Master's Theses and Plan B Papers 237344, University of Minnesota, Department of Applied Economics.
    3. Papa Ousmane Cissé & Abdou Kâ Diongue & Dominique Guegan, 2016. "Note on a new Seasonal Fractionally Integrated Separable Spatial Autoregressive Model," Documents de travail du Centre d'Economie de la Sorbonne 16013, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    4. Osei, Edward & Jafri, Syed H., 2015. "In-field Spatial Variability and Profitability of Precision Nitrogen Application On Corn in Buchanan County, Iowa," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205845, Agricultural and Applied Economics Association.
    5. Garth Holloway & Donald Lacombe & James P. LeSage, 2007. "Spatial Econometric Issues for Bio‐Economic and Land‐Use Modelling," Journal of Agricultural Economics, Wiley Blackwell, vol. 58(3), pages 549-588, September.
    6. Cheung, Tommy King-Yin & Wong, Wai-hung & Zhang, Anming & Wu, Yangming, 2020. "Spatial panel model for examining airport relationships within multi-airport regions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 148-163.
    7. Velandia Margarita & Roderick M. Rejesus & Eduardo Segarra & Kevin Bronson, 2004. "Un análisis económico de la aproximación estadística para el establecimiento de zonas de manejo en agricultura de precisión: caso de algodón en Texas," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, September.
    8. Tommy K. Y. Cheung & Simon K. C. Cheung, 2020. "Spatial dependence model with feature difference," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 615-627, July.
    9. Papa Ousmane Cissé & Dominique Guegan & Abdou Kâ Diongue, 2018. "On the parameters estimation of the Seasonal FISSAR Model," Post-Print halshs-01832115, HAL.
    10. Griffin, Terry W. & Florax, Raymond J.G.M. & Lowenberg-DeBoer, James, 2006. "Field-Scale Experimental Designs and Spatial Econometric Methods for Precision Farming: Strip-Trial Designs for Rice Production Decision Making," 2006 Annual Meeting, February 5-8, 2006, Orlando, Florida 35367, Southern Agricultural Economics Association.
    11. Osei, Edward & Li, Huijun, 2016. "Value of information: costs and returns of precision corn production in Livingston County, Illinois," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236184, Agricultural and Applied Economics Association.
    12. Hough, Ella Christina & Nell, Wilhelm T. & Maine, Ntsikane & Groenewald, Jan A. & van der Rijst, M., 2010. "Best fit model selection for spatial differences (regression) in the profitability analysis of precision phosphate (P) application to winter cereals in Precision Agriculture (PA)," 2010 AAAE Third Conference/AEASA 48th Conference, September 19-23, 2010, Cape Town, South Africa 96642, African Association of Agricultural Economists (AAAE).

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