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Evaluation of the profitability of a new precision fungicide application system for strawberry production

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  • Vorotnikova, Ekaterina
  • Borisova, Tatiana
  • VanSickle, John J.

Abstract

This study evaluates farm-level risk and profitability of a new web-based expert system developed for precision fungicide management for strawberry production in a humid and warm climate. The Strawberry Advisory System (SAS) examined in this study allows for a temporally-variable, weather-dependent fungicide application to manage anthracnose and Botrytis fruit rot diseases in strawberry production in the southern United States (U.S.) and specifically Florida. Using results from six-year production trials combined with historical state-level data, we simulate the distribution of the ten-year net present value (NPV) of profits for SAS-based and traditional Calendar-based strawberry fungicide management. The joint probability distributions of yields and sale prices driven by weather variability are modeled with Monte Carlo stochastic simulation. The new expert system is estimated to significantly reduce crop losses (23.7% on average for anthracnose and 20% for Botrytis) and decrease fungicide use (47% on average for anthracnose and 49% for Botrytis), while increasing profit 41.6% on average in the case of anthracnose and 16.8% for Botrytis. Although the use of the new expert system increases the variability of yield and profit, SAS significantly increases both yield and profit compared to those of Calendar-based method. Based on the risk-adjusted profitability analysis, SAS is a preferred method of fungicide application. Assuming a representative Florida strawberry farm of 10.5 hectares (26 acres), the value of SAS is estimated on average to be $1.76 million for anthracnose and $0.89 million for Botrytis, over a ten-year horizon of use. SAS fungi management is a viable and practical decision-support system for fungicide application that can increase profit, and potentially reduce the environmental footprint from strawberry production. It can add significant economic value to the strawberry producer in the United States and in other countries.

Suggested Citation

  • Vorotnikova, Ekaterina & Borisova, Tatiana & VanSickle, John J., 2014. "Evaluation of the profitability of a new precision fungicide application system for strawberry production," Agricultural Systems, Elsevier, vol. 130(C), pages 77-88.
    • Handle: RePEc:eee:agisys:v:130:y:2014:i:c:p:77-88
    DOI: 10.1016/j.agsy.2014.06.006
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    1. Richardson, James W. & Herbst, Brian K. & Outlaw, Joe L. & Gill, Robert Chope, II, 2007. "Including Risk in Economic Feasibility Analyses: The Case of Ethanol Production in Texas," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 25(2), pages 1-18.
    2. Hezron O. Nyangito & James W. Richardson & Darrell S. Mundy & Adrian W. Mukhebi & Peter Zimmel & Jerry Namken, 1996. "Economic impacts of East Coast Fever immunization on smallholder farms, Kenya: a simulation analysis," Agricultural Economics, International Association of Agricultural Economists, vol. 13(3), pages 163-177, February.
    3. Richardson, James W. & Klose, Steven L. & Gray, Allan W., 2000. "An Applied Procedure For Estimating And Simulating Multivariate Empirical (Mve) Probability Distributions In Farm-Level Risk Assessment And Policy Analysis," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 32(2), pages 1-17, August.
    4. Lowenberg-DeBoer, J., 1999. "Risk Management Potential of Precision Farming Technologies," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 31(2), pages 275-285, August.
    5. Asche, Frank & Guttormsen, Atle G. & Roll, Kristin H., 2006. "Modelling Production Risk in Small Scale Subsistence Agriculture," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25574, International Association of Agricultural Economists.
    6. Richardson, James W. & Lemmer, Wessel J. & Outlaw, Joe L., 2007. "Bio-ethanol Production from Wheat in the Winter Rainfall Region of South Africa: A Quantitative Risk Analysis," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 10(2), pages 1-24.
    7. Nyangito, Hezron O. & Richardson, James W. & Mundy, Darrell S. & Mukhebi, Adrian W. & Zimmel, Peter & Namken, Jerry, 1996. "Economic impacts of East Coast Fever immunization on smallholder farms, Kenya: a simulation analysis," Agricultural Economics, Blackwell, vol. 13(3), pages 163-177, February.
    8. Maiorano, Andrea & Reyneri, Amedeo & Magni, Aronne & Ramponi, Cesare, 2009. "A decision tool for evaluating the agronomic risk of exposure to fumonisins of different maize crop management systems in Italy," Agricultural Systems, Elsevier, vol. 102(1-3), pages 17-23, October.
    9. Barham, E. Hart Bise & Robinson, John R.C. & Richardson, James W. & Rister, M. Edward, 2011. "Mitigating Cotton Revenue Risk Through Irrigation, Insurance, and Hedging," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 43(4), pages 1-12, November.
    10. Sells, J. E., 1995. "Optimising weed management using stochastic dynamic programming to take account of uncertain herbicide performance," Agricultural Systems, Elsevier, vol. 48(3), pages 271-296.
    11. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    12. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-1294, September.
    13. Lundy, M.E. & Hill, J.E. & van Kessel, C. & Owen, D.A. & Pedroso, R.M. & Boddy, L.G. & Fischer, A.J. & Linquist, B.A., 2014. "Site-specific, real-time temperatures improve the accuracy of weed emergence predictions in direct-seeded rice systems," Agricultural Systems, Elsevier, vol. 123(C), pages 12-21.
    14. Nyangito, Hezron O. & Richardson, James W. & Mukhebi, Adrian W. & Zimmel, Peter & Namken, Jerry & Berry, Brian P., 1996. "Whole farm simulation analysis of economic impacts of East Coast Fever immunication strategies on mixed crop-livestock farms in Kenya," Agricultural Systems, Elsevier, vol. 51(1), pages 1-27.
    15. Lowenberg-DeBoer, James, 1999. "Risk Management Potential Of Precision Farming Technologies," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 31(2), pages 1-11, August.
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    1. Yangxuan Liu & Michael R. Langemeier & Ian M. Small & Laura Joseph & William E. Fry & Jean B. Ristaino & Amanda Saville & Benjamin M. Gramig & Paul V. Preckel, 2018. "A Risk Analysis of Precision Agriculture Technology to Manage Tomato Late Blight," Sustainability, MDPI, vol. 10(9), pages 1-19, August.
    2. Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Gomez y Paloma, Sergio, 2015. "Farm-level economic impacts of EU-CAP greening measures," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205309, Agricultural and Applied Economics Association.
    3. Andrew, Rogers & Makindara, Jeremia & Mbaga, Said H. & Alphonce, Roselyne, 2019. "Economic viability of newly introduced chicken strains at village level in Tanzania: FARMSIM model simulation approach," Agricultural Systems, Elsevier, vol. 176(C).
    4. Vorotnikova, Ekaterina & Borisova, Tatiana & VanSickle, John, 2015. "Is Strawberry Advisory System (SAS) Feasible for Farmers of All Risk Preference Profiles?," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196846, Southern Agricultural Economics Association.
    5. Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Gomez y Paloma, Sergio, 2015. "EU-wide individual Farm Model for CAP Analysis (IFM-CAP): Application to Crop Diversification Policy," 2015 Conference, August 9-14, 2015, Milan, Italy 212155, International Association of Agricultural Economists.

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