Techniques for Determining the Authenticity of Food Products

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

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