Development of a Predictive Framework for Aflatoxin Risk Management in the Nigerian Maize Value Chain Under Climate Change Scenarios

Aflatoxin contamination of maize in Nigeria is a food safety and public health crisis of significant scale, and climate change projections indicate worsening conditions for fungal proliferation and toxin production across the maize belt in the coming decades. Existing risk management approaches are predominantly reactive and inadequately calibrated to the spatial and seasonal heterogeneity of contamination risk. This study developed and validated a predictive framework for aflatoxin risk management in the Nigerian maize value chain under present and projected future climate scenarios. The framework was constructed through four integrated research components: a systematic meta-analysis of aflatoxin-climate relationships in sub-Saharan African maize systems, development of a spatially explicit climate-mycotoxin process model calibrated with five years of field monitoring data from maize-producing states across Nigeria's three agroecological zones, scenario analysis using Intergovernmental Panel on Climate Change Shared Socioeconomic Pathway 2-4.5 and 8.5 projections to 2050, and structured expert elicitation to develop risk management decision rules. The model demonstrated strong predictive performance (R squared: 0.74 for aflatoxin concentration, area under curve: 0.83 for contamination hotspot classification) in out-of-sample validation. Under the high-emission scenario, aflatoxin exceedance probability at harvest was projected to increase by 34 percent in Middle Belt states by 2040. The framework recommends pre-harvest risk forecasting services, biocontrol deployment triggers, and climate-adaptive storage protocols as a tiered risk management system. Keywords: aflatoxin, predictive framework, climate change, maize value chain, Nigeria.