Using GIS techniques to aid in predicting a plant virus in beans

Abstract

Geographical information systems (GIS) assist us in mapping and analyzing outbreaks of diseases in plants, animals and humans. This paper describes how GIS are being used to model the intensity of the outbreak of a plant virus, bean golden mosaic virus (BGMV) in Guatemala, Honduras and El Salvador. BGMV is a geminivirus affecting beans (Phaseolus vulgaris) and is transmitted by a vector, the sweet potato whitefly (Bemisia tabaci). Once a plant is infected by the virus yield losses, at varying locations, can range from 40% to 100%. Plant pathologists can improve upon integrated pest management strategies to monitor virus movement and outbreaks by estimating the likelihood of risk in a cropping systems. For the purpose of this analysis three techniques were selected (multivariate logistic regression, Fourier transform with principle components analysis and a multi-process boolean analysis) to predict the spatial occurrence of BGMV in beans. The methods selected are based on the location of the virus (presence/absence) and the environmental factors determining the distribution of the vector. The process involves predicting the distribution of the vector by modeling and mapping the probability of occurrence using environmental variables, such as minimum and maximum temperature ranges, elevation, rainfall and number of dry months. The results of the methods are compared, evaluated and discussed.