Abstract

Big data analytics is revolutionizing predictive pest modelling by enhancing the accuracy and timeliness of pest management strategies. This paper explores the integration of big data techniques with various pest modelling approaches, including phenology models, life table models, pest simulation models and mathematical models. Phenology models leverage large datasets to predict the timing of pest life stages, facilitating proactive control measures. Life table models utilize extensive demographic data to understand pest population dynamics and inform sustainable management practices. Pest simulation models, powered by big data, simulate complex interactions within ecosystems, offering insights into potential pest outbreaks under different environmental scenarios. Additionally, mathematical models provide a robust framework for quantifying pest behaviour and predicting future infestations. By harnessing the power of big data analytics, these models can significantly improve the precision and effectiveness of pest management, ensuring better crop protection and yield optimization.