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The potential for aflatoxin predictive risk modelling in sub-Saharan Africa: a review

Keller, B., Russo, T., Rembold, F., Chauhan, Y., Battilani, P., Wenndt, A. and Connett, M. (2021) The potential for aflatoxin predictive risk modelling in sub-Saharan Africa: a review. World Mycotoxin Journal, In pre . pp. 1-18. ISSN 1875-0710

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Abstract

This review presents the current state of aflatoxin risk prediction models and their potential for value actors throughout the food chain in sub-Saharan Africa, with a specific focus on improving smallholder farmer management practices. Several empirical and mechanistic models have been developed either in academic research or by private sector aggregators and processors in high-income countries including Australia, the USA, and Southern Europe, but these models have been only minimally applied in sub-Saharan Africa, where there is significant potential and increasing need due to climate variability. Predictions can be made based on historic occurrence data using either a mechanistic microbiological framework for aflatoxin accumulation or an empirical model based on statistical correlations with climate conditions and local agronomic factors. Model results can then be distributed to smallholders through private, public, or mobile extension services, used by policymakers for strategy or policy, or utilised by private sector institutions for management decisions. Specific agricultural advice can be given during the three most critical points in the phenological cycle: preseason insight including sowing timing and crop varieties, preharvest advice about management and harvest timing, and postharvest optimal practices including storage, drying, and market information. Model development for sub-Saharan Africa is limited by a dearth of georeferenced aflatoxin occurrence data and real-time high resolution climate data; the wide diversity of farm typologies each with significant information and technology gaps; a prevalence of informal market structures and lack of economic incentives systems; and general lack of awareness around aflatoxins and best management practices to mitigate risk. Given advancements towards solving these challenges, predictive aflatoxin models can be integrated into decision support platforms to focus on optimisation of value for smallholders by minimising yield and nutritional losses, which can propagate value throughout the production and postharvest phases.

Item Type:Article
Business groups:Crop and Food Science
Additional Information:Open access
Keywords:food safety, mycotoxin, dry chain, risk management, smallholder
Subjects:Science > Statistics > Statistical data analysis
Science > Statistics > Statistical software
Plant culture > Food crops
Plant culture > Fruit and fruit culture > Nuts
Plant pests and diseases
Deposited On:06 Sep 2021 00:12
Last Modified:06 Sep 2021 00:12

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