Model of Fungal Development in Stored Barley Ecosystems as a Prognostic Auxiliary Tool for Postharvest Preservation Systems

Jolanta Wawrzyniak

doi:10.1007/s11947-020-02575-x

Abstract

Postharvest preservation and storage have a crucial impact on the technological quality and safety of grain. The important threat to stored grain quality and nutritional safety of cereal products is mould development and their toxic metabolites, mycotoxins. Models based on predictive microbiology, which are able to estimate the kinetics of fungal growth, and thus, the risks of mycotoxin accumulation in a mass of grain are promising prognostic tools that can be applied in postharvest management systems. The study developed a modelling approach to describe total fungal growth in barley ecosystems stored at different temperatures (T = 12–30 °C) and water activity in grain (aw = 0.78–0.96). As the pattern of fungal growth curves was sigmoidal, the experimental data were modelled using the modified Gompertz equation, in which constant coefficients reflecting biological parameters of mould development (i.e. lag phase duration (τlag), maximum growth rate (μmax) and the maximum increase in fungal population level (Δmaxlog(CFU)) were expressed as functions of storage conditions, i.e. aw and T. The criteria used to evaluate the overall model performance indicated its good precision (R2 = 0.95; RMSE = 0.23) and high prediction accuracy (bias factor and accuracy factor Bf = 1.004, Af = 1.035). The formulated model is able to estimate the extension of fungal contamination in a bulk of grain versus time by monitoring temperature and intergranular relative humidity that are readily measurable in practice parameters; therefore, it may be used as a prognostic support tool in modern postharvest management systems.

Highlights

Postharvest preservation and storage treatments have a crucial impact on the technological quality and safety of cereal grain
As the presence of mycotoxins in stored grain is mainly related to the activity of toxigenic fungal genera of Aspergillus and Penicillium (Cabañes et al 2010; Magan 2006; Medina et al 2017; Wawrzyniak and Waśkiewicz 2014), grain naturally contaminated with moulds after wetting was inoculated with a mixture of spores of two toxigenic fungal strains, i.e. A. ochraceus Wilhelm (KKP 439) and P. verrucosum, (KKP 480) (Cabañes et al 2010; Pitt 1987) obtained from the Collection of Industrial Microorganisms (IAFB 212), Institute of Agricultural and Food Biotechnology in Warsaw, Poland, which are representative of storage mycobiota, commonly
Since modelling approach can forecast changes of microbial populations exposed to specific conditions it may be utilized in planning Hazard Analysis and Critical Control Points (HACCP) programs (Gil et al 2017)

Summary

Introduction

Postharvest preservation and storage treatments have a crucial impact on the technological quality and safety of cereal grain. One of the important threats to grain quality and to the nutritional safety of cereal products is the presence of fungal propagules (spores, sclerotium, fragments of mycelia) in stored grain ecosystems. Fungi can penetrate into grain during plant growth, transport or postharvest processes. They are able to develop in a wide range of water availability and temperature levels; under conditions conductive to their development they can grow rapidly, even if the grain is initially contaminated with a small amount of fungal. Much research has been conducted in order to develop new methods for a rapid and reliable detection of fungal infections. Despite the considerable efforts made, we still lack universal, simple and rapid methods to assess grain contamination with fungi. Apart from that existing methods perceive the signs of fungal activity that

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