Development of an empirical tomato crop disease model: a case study on gray leaf spot
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This paper deals with the development and evaluation of a disease model to forecast the risk and incidence associated with tomato gray leaf spot (Ascochyta lycopersici Brun) - one of the reasons for significant tomato yield loss in the Mediterranean area and in other countries. It comprises a leaf wetness model, a disease occurrence warning model and a disease incidence model. The methodology followed was based on studying plant disease epidemiology to clearly understand how the disease progresses, analyzing input parameters used in the published literature and selecting the most suitable methods for calibrating the model thresholds and evaluating its performance. The developed sub-models were evaluated according to the following performance indexes: (1) the area under the receiver operating characteristic curve for choosing the threshold of the leaf wetness model using three methods (a classification tree, support vector machines and the Naive Bayes method); (2) the root mean square error; and (3) the mean absolute error, both for evaluating the curve fitting based on disease incidence models (using Power, Exponential, Polynomial, Gaussian, Logistic and Gompertz approximations). The obtained results provided a calibrated relative humidity threshold of 84.5% from the classification tree method, while the best fitting function was the Logistic equation providing a root mean square error of 3.17 and a mean absolute error of 2.54; the evaluation results of two plant seasons in 2017 and 2018 proved that the Logistic equation can simulate gray leaf spot incidence good, with an R2 of 0.97 and 0.92, and a RMSE of 2.7 and 1.8. This work contributes to tomato gray leaf spot management by providing a basis for decision support to help growers make timely and precise decisions and thus avoid major economic losses.
KeywordsData classification Tomato gray leaf spot Disease model Greenhouse Leaf wetness duration Disease onset and disease incidence
This work has been developed within the IoF2020-Internet of Food and Farm 2020 Project framework, and it was funded by the European Union’s Horizon 2020 Framework Program (Grant Agreement no. 731884) and by the National Natural Science Foundation of China (31401683). The authors would like to thank the Experimental Station of the Cajamar Foundation for all of their invaluable help.
Compliance with ethical standards
Our manuscript “Design of a plant disease model that models leaf wetness duration, disease onset and disease incidence: a case study on tomato gray leaf spot” has no potential conflicts of interest (financial or non-financial) and did not involve research with human participants and/or animals.
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