Forecasting of exotic bondars nesting whitefly, Paraleyrodes bondari Peracchi (Hemiptera: Aleyrodidae) by prediction models

Abstract Whiteflies, as polyphagous pests, hold global significance due to their substantial economic impact. In recent times, the exotic bondar’s nesting whitefly (BNW), Paraleyrodes bondari Peracchi (Hemiptera: Aleyrodidae) Martin, has profoundly disrupted the horticultural ecosystem in India. This disruption has garnered significant attention of agricultural communities. The severity of its influence has been exacerbated by shifting of weather patterns and climatic conditions. To address these challenges, a comprehensive study was initiated in a coconut plantation. The primary objectives of this study were to unravel the factors that exert influence on the behavior of the bondar’s nesting whitefly and furthermore, to develop predictive models aimed at forecasting its incidence. The correlation studies conducted between biotic and abiotic factors and the population of BNW revealed noteworthy findings. Notably, maximum temperature (with a correlation coefficient i.e. r = 0.28*), bright sunshine hours (r = 0.3*), and canopy temperature (r = 0.28*) exhibited a significant positive influence on the whitefly population build up. These results underscore the crucial role that climatic conditions play in driving the dynamics of BNW population. The prediction of BNW outbreaks based on prevailing weather conditions and the timely implementation of appropriate control measures for effective pest management are of paramount importance. Among the prediction models assessed, artificial neural network (ANN) models emerged as the most promising. The model demonstrated superior performance and were identified as the optimal choice for accurately predicting BNW incidence.