Food spoilage by fungi

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Moulds are responsible for significant spoilage and economic losses in the food chain. In addition, some species belonging to the genera Aspergillus, Fusarium and Penicillium are mycotoxigenic. Mycotoxins are a class of highly toxic chemical compounds produced under specific environmental conditions by several moulds. The presence of this diverse group of fungal secondary metabolites on feed or food presents wide fluctuation from year to year mainly because of the large number of factors affecting fungal invasion and growth. Some of these critical factors include fungal strain and inoculum concentration, climate and geographical conditions, cultivation techniques and postharvest handling. Consumption of food contaminated with mycotoxins has been linked with carcinogenic, nephrotoxic and teratogenic potency and, generally, suppressive actions on the immune system. Mycotoxin outbreaks in developing countries have led to numerous toxicosis incidents and deaths due to the high consumption of contaminated food products. These contaminants may occur in a wide range of agricultural products such as cereals, fresh and dried fruits, coffee beans, cocoa, coffee and beverages such as beer and wine, while through the consumption of contaminated feed, mycotoxins can be found in meat and dairy products. Ochratoxin A (OTA) is a secondary metabolite of several species of filamentous fungi (Penicillium and Aspergillus spp.) with nephrotoxic, immunosuppressive, teratogenic and carcinogenic effects to animals and humans. There are several reports from many countries in the world describing the high frequency of OTA contamination in a large number of food groups, leading international organizations and authorities to thoroughly investigate and report risk assessment of the problem. Many authors report OTA contamination of cereal and vegetable products, even meat products like sausages contaminated via poor quality animal feed. Grapes, raisins, grape juice and wine can be considered as high-risk products because of colonization by Aspergillus carbonarius. This has led the EU to develop legislative limits of 2 ng ml-1 for wine and grape juice and 10 ng g-1 for vine dried fruits.
Nowadays, researchers in order to assess the effect of environmental conditions on growth and toxin production have focused on fungal ecophysiological studies. Because mycotoxins cannot simply be destroyed by heat, the development of strategies to suppress fungal growth is considered to be a primary objective. To this purpose, an innovating and promising approach has been developed in the last years based on mathematical modelling aiming at forecasting fungal responses and mycotoxin contamination of raw materials and processed food products. Fungal ecophysiology studies should result in modelling of germination, growth and mycotoxin production, and finally to the prediction of fungal contamination levels which may lead to mycotoxin contamination above the tolerable legislative limits. Mathematical modelling has proved to be a valuable tool to predict bacterial growth as a function of environmental factors such as temperature, pH, and water availability. However, the modelling of filamentous fungi has not received the same level of attention, possibly due to inherent difficulties in quantifying fungal growth and produce reliable and reproducible data. Recently, the need for improved understanding of the factors controlling fungal growth in foods has attracted the attention of several researchers who have developed probabilistic, mechanistic, semi-mechanistic, empirical and thermal death models for a variety of toxigenic and spoilage fungi.
The proposed in this project modelling and analytical approaches will help the understanding of fungal-food ecosystem relations and could be employed in risk analysis plans to predict the risk of contamination of the related products by toxigenic fungi. These approaches could constitute a useful tool for the food industry and, moreover, the development of quantitative approaches to ecology and physiology of fungi could enable product innovation through the assessment of fungal proliferation, growth limits and toxin production. In this way, critical information on developing new products and processes, reformulate existing products, and determine storage conditions and shelf-life will be available to the industry. Moreover, they will help food safety decisions that need to be made when implementing or running a food manufacturing operation, such as designing processing regimes, setting critical control points (CCPs) in HACCP, assessing impact of process deviations on safety and quality of food products. In addition, these approaches could be a helpful tool to estimate the impact on consumer safety or product quality in case of problems with mycotoxins.
Further studies are necessary to improve and expand the developed models by incorporating more ecological factors e.g., atmosphere composition, inhibitors (natamycin, essential oils, fungicides), interactions between different fungi etc., strengthening in this way the impact of the present findings and contributing to more effective control of fungal growth and toxin production in the food chain. To this end, new data sets are required to develop suitable mathematical models, making the adoption of a universal database format an urgent priority. Such databases can give birth to tertiary models which could be defined as the integration of primary and secondary models in a software using databases. A first step has already been done for the microbial responses in food and growth media, with most representative tertiary model the latest version of ComBase (www.combase.cc) that includes a modelling tool (Excel add-in “DMFit”) that utilizes its database to generate growth or inactivation curves. Similar platforms should be generated for ochratoxigenic fungi, providing information and prediction not only for growth but also for toxin production.

The project "Design and development of innovative tools for the detection of ochratoxigenic fungi in wine and table grapes - FungalPrognosis_242" has been co-financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARISTEIA-I.

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