Prediction of Severe Epidemics of Chickpea Ascochyta Blight Using Weather Variables

Abstract

ABSTRACT Chickpea production is threatened by severe epidemics of Ascochyta blight occurring in main chickpea growing lands under appropriate weather conditions worldwide. In this 4‐year research, occurrence of Ascochyta blight was monitored across nine main chickpea growing areas of Kermanshah province, western part of Iran. Each year, commercial chickpea fields were studied on a weekly basis from March to June. Disease data were collected as disease incidence (percentage of infected plants) and severity (percentage of infected tissues) and occurrence of epidemics. Weather data were collected as air temperature, rainfall, and relative humidity (RH) on a daily basis. According to a factor analysis, which explained 83% of data variance, 13 weather predictors were selected to estimate disease epidemics developed across different areas. Before modeling, a principal component analysis determined predictive values for these selected weather variables. Then, eight predictors of rainy days in March and April, mean RH in February, mean minimum temperature in January–March–April, and rainfalls in May and June were involved in model based on their predictive values. Current findings advanced our knowledge on the best weather predictors of severe epidemics of Ascochyta blight in chickpea crops at large scale.

Keywords

• epidemiology
• legumes
• multivariate regression
• occurrence