MYCOTOXIGENIC MOULD GROWTH PARAMETERS AS AFFECTED BY SUBOPTIMAL ENVIRONMENTAL CONDITIONS AND INOCULUM SIZE

DAIANA GARCIA; ANTONIO J. RAMOS; VICENTE SANCHIS; SONIA MARÍN

Congreso; Second International Congress: Novel Technologies and Food Quality, Safety and Health; 2009

Mould growth and mycotoxin production are associated to the presence of fungal inoculum on predisposed foods and feeds. The presence of mycotoxins in food products is a chemical risk of increasing concern due to the wide range of food types where they can be found. Despite the absence of direct correlation between mould growth and mycotoxins production, prevention of fungal growth effectively conduces to prevention of mycotoxin accumulation. Predictive models can be a tool to prevent mould development. Kinetic models determine microbial responses in relation to time and environmental conditions, and provide estimates for parameters of growth: lag phase (λ) and growth rate (μ). The aim of this work was to assess the impact of a) high/low levels of inoculum and b) optimal/suboptimal environmental conditions on the distribution of the estimated kinetic parameters. Two mycotoxigenic moulds, Aspergillus carbonarius and Penicillium expansum, were chosen for this study, and experiments were performed with 50 replicates. While optimum conditions led to a colony diameter increase which followed Baranyi?s function, suboptimal conditions, in particular low temperatures led to different grow functions. In general, μ and λ were normally distributed. μ showed similar distributions under optimal growth conditions, regardless of the inoculum level, with similar medians, while suboptimal aw and temperature conditions led to higher kurtosis distributions, mainly when the inoculum levels were low. Regarding λ, more skewed distributions were observed, mainly when the inoculum levels were low. Finally, an increasing number of ?no-growth? situations were recorded under suboptimal conditions, which suggest a high variability of results under such conditions. These results imply that low inoculum sizes and suboptimal conditions lead to high variability of the estimated growth parameters. These have to be considered in the design of kinetic predictive models.