Use of response surface methodology to optimise environmental stress conditions on Penicillium glabrum, a food spoilage mould |
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Authors: | Nevarez Laurent Vasseur Valérie Debaets Stella Barbier Georges |
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Affiliation: | Université Européenne de Bretagne, France. |
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Abstract: | Fungi are ubiquitous microorganisms often associated with spoilage and biodeterioration of a large variety of foods and feedstuffs. Their growth may be influenced by temporary changes in intrinsic or environmental factors such as temperature, water activity, pH, preservatives, atmosphere composition, all of which may represent potential sources of stress. Molecular-based analyses of their physiological responses to environmental conditions would help to better manage the risk of alteration and potential toxicity of food products. However, before investigating molecular stress responses, appropriate experimental stress conditions must be precisely defined. Penicillium glabrum is a filamentous fungus widely present in the environment and frequently isolated in the food processing industry as a contaminant of numerous products. Using response surface methodology, the present study evaluated the influence of two environmental factors (temperature and pH) on P. glabrum growth to determine 'optimised' environmental stress conditions. For thermal and pH shocks, a large range of conditions was applied by varying factor intensity and exposure time according to a two-factorial central composite design. Temperature and exposure duration varied from 30 to 50 °C and from 10 min to 230 min, respectively. The effects of interaction between both variables were observed on fungal growth. For pH, the duration of exposure, from 10 to 230 min, had no significant effect on fungal growth. Experiments were thus carried out on a range of pH from 0.15 to 12.50 for a single exposure time of 240 min. Based on fungal growth results, a thermal shock of 120 min at 40 °C or a pH shock of 240 min at 1.50 or 9.00 may therefore be useful to investigate stress responses to non-optimal conditions. |
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