Worldwide mycotoxins contamination is a Food Safety concern that affects markets, with millions of tonnes of food wasted, and billions of dollars spent in prevention, sampling, mitigation, litigation and research. Many fungal species produce mycotoxins as a defense against their changing environmental conditions.
As a result, it is not possible to fully avoid mycotoxins contamination in food. First, because the contamination occurs in the field, where environmental conditions cannot be controlled. Second, because the thermostability of mycotoxins constraints their possible reduction following industrial processing.
However, fungal behavior can be modeled, and the risk of mycotoxin production can be assessed. In the last two decades, scientific literature on modelling has been increasing, the development of predictive models arose as a potential tool that can support strategies to manage and control mycotoxin risk along the food chain.
Despite the efforts to improve knowledge of such, have not yet marked the beginning of a downward trend in model implementation; thus it is essential to stress the needs for a more significant knowledge transfer between the academia and the industry.
This Frontiers in Microbiology Research Topic will support those experts working in all aspects of food and feed production and processing along the food chain by meeting the following goals:
(a) Retrieve information on mycotoxigenic fungi ecophysiological needs, as a first tile of a modelling frame, in order to understand the complexity of fungal behavior and its interactions with host, environment and other fungi.
(b) Summarize the state of the art regarding the actual trends in the development of mathematical models and decision support system for mycotoxin control and management along the food chain.
(c) Lay the ground and serve as a guideline for both researchers and professional managers about the future trends in fungal and mycotoxin control using predictive approaches
In order to achieve the above mentioned goals, we welcome high-quality original research and review papers covering the broad spectrum of mycotoxin-oriented food microbiology with a focus on predictive mycology. The specific themes we invite the contributors to address include:
i. Modelling fungi and mycotoxin production in relation to environmental factors, both in-planta or in-vitro also under the influence of climate change
ii. Modelling approaches for estimating the fate of mycotoxins into the feed/food supply chain as well as the contamination risk of the final products.
iii. Any machine learning methods for the assessment of fungal growth and mycotoxin production.
iv. The support from big data in mycotoxin prediction and management.
v. Modelling fungal colonization and toxins release in three-dimensional food matrices to provide consumer recommendations in regards to storage management and consumption
Worldwide mycotoxins contamination is a Food Safety concern that affects markets, with millions of tonnes of food wasted, and billions of dollars spent in prevention, sampling, mitigation, litigation and research. Many fungal species produce mycotoxins as a defense against their changing environmental conditions.
As a result, it is not possible to fully avoid mycotoxins contamination in food. First, because the contamination occurs in the field, where environmental conditions cannot be controlled. Second, because the thermostability of mycotoxins constraints their possible reduction following industrial processing.
However, fungal behavior can be modeled, and the risk of mycotoxin production can be assessed. In the last two decades, scientific literature on modelling has been increasing, the development of predictive models arose as a potential tool that can support strategies to manage and control mycotoxin risk along the food chain.
Despite the efforts to improve knowledge of such, have not yet marked the beginning of a downward trend in model implementation; thus it is essential to stress the needs for a more significant knowledge transfer between the academia and the industry.
This Frontiers in Microbiology Research Topic will support those experts working in all aspects of food and feed production and processing along the food chain by meeting the following goals:
(a) Retrieve information on mycotoxigenic fungi ecophysiological needs, as a first tile of a modelling frame, in order to understand the complexity of fungal behavior and its interactions with host, environment and other fungi.
(b) Summarize the state of the art regarding the actual trends in the development of mathematical models and decision support system for mycotoxin control and management along the food chain.
(c) Lay the ground and serve as a guideline for both researchers and professional managers about the future trends in fungal and mycotoxin control using predictive approaches
In order to achieve the above mentioned goals, we welcome high-quality original research and review papers covering the broad spectrum of mycotoxin-oriented food microbiology with a focus on predictive mycology. The specific themes we invite the contributors to address include:
i. Modelling fungi and mycotoxin production in relation to environmental factors, both in-planta or in-vitro also under the influence of climate change
ii. Modelling approaches for estimating the fate of mycotoxins into the feed/food supply chain as well as the contamination risk of the final products.
iii. Any machine learning methods for the assessment of fungal growth and mycotoxin production.
iv. The support from big data in mycotoxin prediction and management.
v. Modelling fungal colonization and toxins release in three-dimensional food matrices to provide consumer recommendations in regards to storage management and consumption
