Ecophysiology and Mycotoxigenesis of Aspergillus flavus in Nigerian Groundnut Production Systems: Towards a Predictive Contamination Risk Model

Aspergillus flavus-mediated aflatoxin contamination of groundnut is the most significant mycotoxin-related food safety and export compliance challenge in Nigeria, costing the economy an estimated 450 million USD annually in trade value foregone and public health impacts. Despite this economic significance, a mechanistic, ecophysiology-grounded predictive model for aflatoxin contamination risk calibrated to Nigerian groundnut production conditions does not exist. This doctoral research programme addresses this gap through an integrated ecophysiological, molecular, and predictive modelling approach. The research combines: systematic characterisation of A. flavus population ecology in groundnut soils across the North West, North Central, and North East zones; mechanistic experiments quantifying the effects of temperature, water activity, soil texture, and host phenological stage on aflatoxin biosynthesis gene expression and aflatoxin B1 accumulation under controlled and field conditions; and the development and cross-validation of a spatially explicit contamination risk prediction model incorporating remotely sensed drought stress indicators, soil type classification, and seasonal temperature data. Original contributions include a standardised A. flavus aflatoxigenicity assay adapted for tropical isolates, a mechanistic water activity-temperature response surface for Nigerian A. flavus strains, and a validated GIS-integrated prediction platform for aflatoxin risk mapping. The contamination risk model is designed to interface with the Nigerian Meteorological Agency's seasonal forecasting system to enable prospective risk communication for extension and policy purposes. Keywords: Aspergillus flavus, aflatoxin, groundnut, ecophysiology, predictive model.