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

Author(s)

Marin, Sonia ^[1] ; Freire, Luisa ^[2] ; Femenias, Antoni ^[1] ; Sant'Ana, Anderson S. ^[2]

Affiliation

^[1] Univ Lleida, Agrotecn Ctr, Food Technol Dept, Appl Mycol Unit, Av Rovira Roure 191, Lleida 25198 - Spain

^[2] Univ Estadual Campinas, Fac Food Engn, Dept Food Sci & Nutr, Campinas, SP - Brazil

• Document type: Journal article
• Source: CURRENT OPINION IN FOOD SCIENCE; v. 41, OCT 2021.
• Web of Science Citations: 2

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. (AU)

• FAPESP's process: 16/21041-5 - Fungi and modified mycotoxins in grapes and wines: modeling the variability of formation, stability during the processing and health effects
• Grantee: Luisa Freire Colombo
• Support Opportunities: Scholarships in Brazil - Doctorate