1. Machine learning–based chemometric methods for quality and authentication of milk and dairy products
- Author
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Luis Cuadros-Rodríguez, Badredine Souhail, Ana M. Jiménez-Carvelo, Sanae Bikrani, and Mounir Nechar
- Subjects
Authentication ,Artificial neural network ,Computer science ,business.industry ,media_common.quotation_subject ,Machine learning ,computer.software_genre ,Field (computer science) ,Random forest ,Support vector machine ,Quality (business) ,Artificial intelligence ,business ,computer ,media_common - Abstract
This chapter aims to explain the main frauds in milk and dairy products and the different multivariate analytical solutions to evaluate the quality and the authenticity of them, followed by a brief explanation of current state of the art and the future prospects of the application of machine learning methods in this field. The application of the nontargeted approach (fingerprinting methodology) as analytical solution is discussed. In addition, an overview of the applications of machine learning methods reported in the literature, such as artificial neural network, support vector machine, and random forest, to ensure the quality and authenticity of dairy products and milk is presented.
- Published
- 2022
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