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Toward a reliable evaluation of forecasting systems for plant diseases : a case study using fusarium head blight of wheat

Sofie Landschoot (UGent) , Willem Waegeman (UGent) , Kris Audenaert (UGent) , J. Vandepitte, Geert Haesaert (UGent) and Bernard De Baets (UGent)
(2012) PLANT DISEASE. 96(6). p.889-896
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Abstract
Despite great efforts to forecast plant diseases, many of the existing systems often fall short in providing farmers with accurate predictions. One of the main problems arises from the existence of year and location effects, so that more advanced procedures are required for evaluating existing systems in an unbiased manner. This paper illustrates the case of Fusarium head blight of winter wheat in Belgium. We present a new cross-validation strategy that enables the evaluation of the predictive performance of a forecasting system for years and locations that are different from the years and locations on which the forecast was developed. Four different cross-validation strategies and five regression techniques are used. The results demonstrated that traditional evaluation strategies are too optimistic in their predictions, whereas the cross-year cross-location validation strategy yielded more realistic outcomes. Using this procedure, the mean squared error increased and the coefficient of determination decreased in predicting disease severity and deoxynivalenol content, suggesting that existing evaluation strategies may generate a substantial optimistic bias. The strongest discrepancies between the cross-validation strategies were observed for multiple linear regression models.
Keywords
WINTER-WHEAT, DEOXYNIVALENOL CONTENT, CROSS-VALIDATION, MODEL, REGRESSION, PREDICTION, CROPS, CLASSIFICATION, POPULATION, EPIDEMICS

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MLA
Landschoot, Sofie, et al. “Toward a Reliable Evaluation of Forecasting Systems for Plant Diseases : A Case Study Using Fusarium Head Blight of Wheat.” PLANT DISEASE, vol. 96, no. 6, 2012, pp. 889–96, doi:10.1094/PDIS-08-11-0665.
APA
Landschoot, S., Waegeman, W., Audenaert, K., Vandepitte, J., Haesaert, G., & De Baets, B. (2012). Toward a reliable evaluation of forecasting systems for plant diseases : a case study using fusarium head blight of wheat. PLANT DISEASE, 96(6), 889–896. https://doi.org/10.1094/PDIS-08-11-0665
Chicago author-date
Landschoot, Sofie, Willem Waegeman, Kris Audenaert, J. Vandepitte, Geert Haesaert, and Bernard De Baets. 2012. “Toward a Reliable Evaluation of Forecasting Systems for Plant Diseases : A Case Study Using Fusarium Head Blight of Wheat.” PLANT DISEASE 96 (6): 889–96. https://doi.org/10.1094/PDIS-08-11-0665.
Chicago author-date (all authors)
Landschoot, Sofie, Willem Waegeman, Kris Audenaert, J. Vandepitte, Geert Haesaert, and Bernard De Baets. 2012. “Toward a Reliable Evaluation of Forecasting Systems for Plant Diseases : A Case Study Using Fusarium Head Blight of Wheat.” PLANT DISEASE 96 (6): 889–896. doi:10.1094/PDIS-08-11-0665.
Vancouver
1.
Landschoot S, Waegeman W, Audenaert K, Vandepitte J, Haesaert G, De Baets B. Toward a reliable evaluation of forecasting systems for plant diseases : a case study using fusarium head blight of wheat. PLANT DISEASE. 2012;96(6):889–96.
IEEE
[1]
S. Landschoot, W. Waegeman, K. Audenaert, J. Vandepitte, G. Haesaert, and B. De Baets, “Toward a reliable evaluation of forecasting systems for plant diseases : a case study using fusarium head blight of wheat,” PLANT DISEASE, vol. 96, no. 6, pp. 889–896, 2012.
@article{2136140,
  abstract     = {{Despite great efforts to forecast plant diseases, many of the existing systems often fall short in providing farmers with accurate predictions. One of the main problems arises from the existence of year and location effects, so that more advanced procedures are required for evaluating existing systems in an unbiased manner. This paper illustrates the case of Fusarium head blight of winter wheat in Belgium. We present a new cross-validation strategy that enables the evaluation of the predictive performance of a forecasting system for years and locations that are different from the years and locations on which the forecast was developed. Four different cross-validation strategies and five regression techniques are used. The results demonstrated that traditional evaluation strategies are too optimistic in their predictions, whereas the cross-year cross-location validation strategy yielded more realistic outcomes. Using this procedure, the mean squared error increased and the coefficient of determination decreased in predicting disease severity and deoxynivalenol content, suggesting that existing evaluation strategies may generate a substantial optimistic bias. The strongest discrepancies between the cross-validation strategies were observed for multiple linear regression models.}},
  author       = {{Landschoot, Sofie and Waegeman, Willem and Audenaert, Kris and Vandepitte, J. and Haesaert, Geert and De Baets, Bernard}},
  issn         = {{0191-2917}},
  journal      = {{PLANT DISEASE}},
  keywords     = {{WINTER-WHEAT,DEOXYNIVALENOL CONTENT,CROSS-VALIDATION,MODEL,REGRESSION,PREDICTION,CROPS,CLASSIFICATION,POPULATION,EPIDEMICS}},
  language     = {{eng}},
  number       = {{6}},
  pages        = {{889--896}},
  title        = {{Toward a reliable evaluation of forecasting systems for plant diseases : a case study using fusarium head blight of wheat}},
  url          = {{http://doi.org/10.1094/PDIS-08-11-0665}},
  volume       = {{96}},
  year         = {{2012}},
}
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