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

Author:

Keller B.1,Russo T.1,Rembold F.2,Chauhan Y.3,Battilani P.4,Wenndt A.5,Connett M.1

Affiliation:

1. Global Good, 3150 139th Ave SE, Bellevue, WA 98005, USA.

2. European Commission, Joint Research Centre, Via E. Fermi 2749, 21027 Ispra, Italy.

3. Department of Agriculture and Fisheries, 214 Kingaroy Cooyar Road, Kingaroy, QLD 4610, Australia.

4. Department of Sustainable Crop Production (DI.PRO.VE.S.): Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122 Piacenza, Italy.

5. Plant Pathology and Plant-Microbe Biology, School of Integrative Plant Sciences, Cornell University, 334 Plant Science Building, Ithaca, NY 14853-4203, USA.

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.

Publisher

Wageningen Academic Publishers

Subject

Public Health, Environmental and Occupational Health,Toxicology,Food Science

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