Prediction of leaf rust severity and yield loss in wheat based on environmental factors

Abstract

Six commercial bread wheat (Triticum aestivum L.) cultivars were evaluated against leaf rust (Puccinia triticina) at two different locations in Egypt during three successive growing seasons, i.e., 2016/2017, 2017/2018 and 2018/2019. Correlation between eight weekly environmental factors: solar radiation, total precipitation, average wind speed, maximum wind speed, minimum air temperature, maximum air temperature, minimum relative humidity and maximum relative humidity to leaf rust severity (%) and yield losses (%), was determined using stepwise regression analysis. Predictive models for each tested cultivar for final leaf rust severity (%) and yield losses using environmental data were determined. Generally, maximum relative humidity was positively correlated with final leaf rust severity (%). Significant correlation between yield losses (%) and the two factors, i.e., final leaf rust severity (%) and maximum relative humidity, was also found in this study. Meanwhile, negative correlation was found between final leaf rust severity (%) and yield losses (%) and the two environmental factors, i.e., solar radiation and minimum relative humidity. The effectiveness of tested models was estimated by using R2 values for all models, and these models were validated to predict leaf rust severity (%) and yield loss.