Techniques for Determining the Authenticity of Food Products
A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Engineering and Technology".
Deadline for manuscript submissions: 25 December 2024 | Viewed by 109
Special Issue Editor
Interests: multivariate data analysis; spectroscopy; qualitative performance parameters; food fraud; data fusion
Special Issue Information
Dear Colleagues,
Concerns about food safety by consumers, producers and regulators grow annually due to ongoing food scandals, despite regulations. This increases the demand for innovative analytical methods to prevent food fraud, focusing on speed, sustainability and non-destructiveness. Modern techniques often provide multivariate data, with spectroscopic methods coupled with machine learning or deep learning standing out for minimal chemical use and sample manipulation. However, complexities in multivariate qualitative modeling, compounded by a lack of consensus on reporting parameters and estimation methods, pose challenges. Therefore, there is a need for pioneering strategies to standardize these parameters.
Applying these methodologies to real-world food fraud scenarios is crucial. Their effectiveness and practical relevance must be unequivocally validated to ensure lasting impacts on food fraud analysis.
Prof. Dr. Ruisanchez Itziar
Guest Editor
Manuscript Submission Information
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Keywords
- analytical methods to prevent food fraud
- development of qualitative methods
- validation of multivariate qualitative methods
- definition of qualitative performance parameters
- methodologies applied to real-world food fraud
