Use of predictive modelling as tool for prevention of fungal spoilage at different points of the food chain

Abstract

Moulds cause severe economic losses at different points of plant food commodities production, from the field to the final foodstuffs. Predictive modelling is an increasingly used tool applied to solve different issues in food production. In this opinion, we have dealt, in one hand, with the latest publications on predictive mycology used for early prediction of fungal spoilage of foods, as well as for assessing efficacy of antimicrobials in foods. Moreover, prediction models have been applied to assess the impact that climate change may have in the near future in terms of geographic fungal distribution and impact on mycotoxin occurrence. Finally, there is a growing interest on analysing fungal growth and mycotoxin contamination in cereals and nuts using infrared spectrometry models. All these cases exemplify the increasing interest of predictive modelling to assist decision making in different points of the food chain.

This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO/AEI/FEDER, UE, project AGL2017- 87755-R). Antoni Femenias acknowledges the financial support of the University of Lleida (predoctoral grant). Luisa Freire acknowledges the financial support of São Paulo Research Foundation: Grant #2016/21041-5, São Paulo Research Foundation (FAPESP). This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. A. S. Sant’Ana is thankful to the National Council for Scientific and Technological Development (CNPq): Grants #302763/2014-7 and #305804/2017-0.