Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-23T16:06:41.499Z Has data issue: false hasContentIssue false
  • English
  • Français

Changes in Producers' Perceptions of Within-Field Yield Variability after Adoption of Cotton Yield Monitors

Published online by Cambridge University Press:  26 January 2015

Roderick M. Rejesus ,
Michele C. Marra ,
Roland K. Roberts ,
Burton C. English ,
James A. Larson  and
Kenneth W. Paxton
Roderick M. Rejesus
Affiliation:
Department of Agricultural and Resource Economics, North Carolina State University, Raleigh, North Carolina
Michele C. Marra
Affiliation:
Department of Agricultural and Resource Economics, North Carolina State University, Raleigh, North Carolina
Roland K. Roberts
Affiliation:
Department of Agricultural Economics, University of Tennessee, Knoxville, Tennessee
Burton C. English
Affiliation:
Department of Agricultural Economics, University of Tennessee, Knoxville, Tennessee
James A. Larson
Affiliation:
Department of Agricultural Economics, University of Tennessee, Knoxville, Tennessee
Kenneth W. Paxton
Affiliation:
Department of Agricultural Economics and Agribusiness, Louisiana State University, Baton Rouge, Louisiana
Get access Rights & Permissions [Opens in a new window]

Extract

This article investigates how information from cotton yield monitors influences the perceptions of within-field yield variability of cotton producers. Using yield distribution modeling techniques and survey data from cotton producers in 11 southeastern states, we find that cotton farmers who responded to the survey tend to underestimate within-field yield variability (by approximately 5-18%) when not using site-specific yield monitor information. Results further indicate that surveyed cotton farmers who responded to a specific question about yield monitors place a value of approximately $20/acre/year (on average) on the additional information about within-field yield variability that the yield monitor technology provides.

Keywords

precision farmingriskspatial yield distributionswithin-field variability yield monitoryield perceptionsyield variabilityQ12Q16
Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 45 , Issue 2 , May 2013 , pp. 295 - 312
Copyright
Copyright © Southern Agricultural Economics Association 2013

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

Babcock, B.A., Hart, CE., and Hayes, D.J.. “Actuarial Fairness of Crop Insurance Rates with Constant Rate Relativities.” American Journal of Agricultural Economics 86,3(2004):563–75.CrossRefGoogle Scholar
Bessler, D.A. “Aggregated Personalistic Beliefs on Yields of Selected Crops Estimated Using ARIMA Processes.” American Journal of Agricultural Economics 62,4(1980):666–74.CrossRefGoogle Scholar
Bullock, D.S., Ruffo, M.L., Bullock, D.G., and Bollero, G.A.. “The Value of Variable Rate Technology: An hrformation-Theoretic Approach.” American Journal of Agricultural Economics 91,1(2009):209–23.CrossRefGoogle Scholar
Chen, S.L., and Miranda, M.J.. “Modeling Texas Dryland Cotton Yields, with Application to Crop Insurance Actuarial Rating.” Journal of Agricultural and Applied Economics 40, 1(2008):239–52.CrossRefGoogle Scholar
Claasen, R., and Just, R.E.. “Heterogeneity and Distributional Form of Farm-Level Yields.” American Journal of Agricultural Economics 93,1(2011):144–60.CrossRefGoogle Scholar
Clop-Gallart, M.M., and Juarez-Rubio, F.. “Elici-tation of Subjective Crop Yield PDF.” Spanish Journal of Agricultural Research 5,1(2007):16–24.CrossRefGoogle Scholar
Cochran, R.L., Roberts, R.K., English, B.C., Larson, J.A., Goodman, W.R., Larkin, S.R., Marra, M.CMartin, S.W.Paxton, K.W.Shurley, W.D., and Reeves, J.M.. Precision Farming by Cotton Producers in Eleven States: Results from the 2005 Southern Precision Farming Survey. Research Series No. 01-06, University of Tennessee Agr. Exp. Sta., Dept. of Agr.Econ., Knoxville, TN, 2006.Google Scholar
Daberkow, S.G., Fernandez-Cornejo, J., and Padgitt, M.. 2002. “Precision Agriculture Technology Diffusion: Current Status and Future Prospects.” Proceedings of the 6th International Conference on Precision Agriculture, 2002, pp. 1668–81.Google Scholar
Delavande, A., Gine, X., and McKenzie, D.. “Measuring Subjective Expectations in Developing Countries: A Critical Review and New Evidence.” Policy Research Working Paper, Development Economics Research Group, The World Bank, Washington, DC, 2009.CrossRefGoogle Scholar
Durrence, J.S., Thomas, D.L., Perry, CD., and Vellidis, G.. “Preliminary Evaluation of Commercial Cotton Yield Monitors: The 1998 Season in South Georgia,” Proceedings of the Beltwide Cotton Conference, 1999, pp. 366–72.Google Scholar
Egelkraut, T.M., Sherrick, B.J., Garcia, P., and Pennings, J.M.E.. “Farmers' Subjective Perceptions of Yield and Yield Risk.” Selected Paper presented at the 2006 NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management, St. Louis, MO, April 17-18, 2006a.Google Scholar
Egelkraut, T.M., Garcia, P.Pennings, J.M.E., and Sherrick, B.J.. “Producers' Yield and Yield Risk: Perceptions versus Reality and Crop Insurance Use.” Selected Paper presented at the AAEA Meetings, Long Beach, CA, July 23-26, 2006b.Google Scholar
English, B.C., Mahajanashetti, S.B., and Roberts, R.K.. “Assessing Spatial Break-Even Variability in Fields with Two or More Management Zones.” Journal of Agricultural and Applied Economics 33,3(2001):551–65.CrossRefGoogle Scholar
Field, J.E., Misra, S.K., and Ramirez, O.A.. “Evaluating Crop and Revenue Insurance Products as Risk Management Tools for Texas Cotton Producers.” Journal of Agricultural and Applied Economics 35,1(2003):39–52.CrossRefGoogle Scholar
Goodwin, B.K. “Payment Limitations and Acreage Decisions under Risk Aversion: A Simulation Approach.” American Journal of Agricultural Economics 91,1(2009):191.CrossRefGoogle Scholar
Griffin, T.W., Lowenberg-DeBoer, J.M.Lambert, D.M.Peone, J.Payne, T., and Draberkow, S.J.. “Precision Farming: Adoption, Profitability, and Making Better Use of Data.” Paper presented at the Triennial North Central Farm Management Conference, Lexington, KY, July 14-16, 2004a.Google Scholar
Griffin, T.W., Lambert, D.M., Lowenberg-DeBoer, J.M., and Erickson, B.J.. “Using Cotton Yield Monitor Data for Farm-level Decision Making.” Site-specific Management Center (SSMC) Newsletter. West Lafayette, IN: Purdue University, October 2004b.Google Scholar
Grissley, W., and Kellogg, E.D.. “Farmers' Subjective Probabilities in Northern Thailand: An Elicitation Analysis.” American Journal of Agricultural Economics 65,1(1983):74–82.CrossRefGoogle Scholar
Harri, A., Erdem, C., Coble, K.H., and Knight, T.O.. “Crop Yield Distributions: A Reconciliation of Previous Research and Statistical Tests for Normality.” Rev. of Ag. Econ 31,1(2009):163–82.CrossRefGoogle Scholar
Johnson, D. “The Triangular Distribution as a Proxy for the Beta Distribution in Risk Analysis.” The Statistician 46,3(1997):387–98.CrossRefGoogle Scholar
Just, R.E., and Weninger, Q.. “Are Crop Yields Normally Distributed?” American Journal of Agricultural Economics 81,2(1999):287–304.CrossRefGoogle Scholar
Larson, J.A., and Roberts, R.K.. “Farmers' Perceptions of Spatial Yield Variability as Influenced by Precision Farming Information Gathering Technologies.” Selected Paper presented at the SAEA Annual Meetings, Tulsa, OK, February 14-18, 2004.Google Scholar
Lechner, W., and Baumann, S.. “Global Navigation Satellite Systems.” Computers and Electronics in Agriculture 25,1-2(January 2000):67–85.CrossRefGoogle Scholar
Malcolm, D.G., Rosenboom, J.H., Clark, CE., and Fazer, W.. “Application of a Technique for Research and Development Program Evaluation.” Operations Research 7,5(1959):646–69.CrossRefGoogle Scholar
Manski, CF. “Measuring Expectations.” Econometrica: Journal of the Econometric Society 72,5(2004):1329–76.CrossRefGoogle Scholar
Mooney, D.F., Roberts, R.K., English, B.C., Lambert, D.M., Larson, J.A., Velandia, M., Larkin, S.L., Marra, M.C., Martin, S.W., Mishra, A., Paxton, K.W., Rejesus, R., Segarra, E., Wang, C., and Reeves, J.M.. Precision Farming by Cotton Producers in Twelve Southern States: Results from the 2009 Southern Cotton Precision Farming Survey. Research Series 10-02. Knoxville, TN: Department of Agricultural and Resource Economics, University of Tennessee, 2010.Google Scholar
Moskowitz, H., and Bullers, W.I.. “Modified PERT versus Fractile Assessment of Subjective Probability Distributions.” Organizational Behavior and Human Performance 24,2(1979):167–94.CrossRefGoogle Scholar
Pease, J.W. “A Comparison of Subjective and Historical Crop Yield Probability Distributions.” Southern Journal of Agricultural Economics 24,2(1992):23–32.Google Scholar
Perry, CD., Vellidis, G., Wells, N., and Kvien, C.. 2001. “Simultaneous Evaluation of Multiple Commercial Yield Monitors in Georgia,” Proceedings of the Beltwide Cotton Conference, 2001, pp. 328–39.Google Scholar
Ramirez, O.A., Misra, S.K., and Field, J.E.. “Crop-Yield Distributions Revisited.” American Journal of Agricultural Economics 85,1(2003):108–20.CrossRefGoogle Scholar
Roades, J.P., Beck, A.D., and Searcy, S.W.. “Cotton Yield Mapping: Texas Experiences in 1999,” Proceedings of the Beltwide Cotton Conference, 2000, pp. 404–407.Google Scholar
Sassenrath-Cole, G.F., Thomson, S.J., Williford, J.R., Hood, K.B., Thomasson, J.A., Willams, J., and Woodard, D.. “Field Testing of Cotton Yield Monitors,” Proceedings of the Beltwide Cotton Conference, 1998, pp. 364–66.Google Scholar
Searcy, S.W., and Roades, J.P.. “Evaluation of Cotton Yield Mapping,” Proceedings of the Beltwide Cotton Conference, 1998, pp. 33–35.Google Scholar
Schimmelpfennig, D., and Ebel, R.. On the Doorstep of the Information Age: Recent Adoption of Precision Agriculture. EIB-80, US Dept. of Agriculture, Economics Research Service, Washington, DC, August 2011.Google Scholar
Smith, J., and Mandac, A.M.. “Subjective versus Objective Yield Distributions as Measures of Productive Risk.” American Journal of Agricultural Economics 77,1(1995):152–61.CrossRefGoogle Scholar
Tversky, A., and Kahneman, D.. Judgement under Uncertainty: Heuristics and Biases. Kahneman, D., Slovic, P., and Tversky, A., eds. Cambridge, MA: Cambridge University Press, 1974.Google ScholarPubMed
Valco, T.D., Nichols, R.L., and Lalor, W.F.. “Adopting Precision Farming Technology for Cotton Nutrition,” Proceedings of the Beltwide Cotton Conference, 1998, pp. 627–29.Google Scholar
Wolak, F.J., Khalilian, A., Dodd, R.B., Han, Y.J., Keshkin, M., Lippert, R.M., and Hair, W.. “Cotton Yield Monitor Evaluation, South Carolina-Year 2,” Proceedings of the Beltwide Cotton Conference, 1999, pp. 361–64.Google Scholar