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Discrimination of milk species based on physico-chemical properties and chemometrics: application of principal component analysis and canonical discriminant analysis

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Abstract

The dairy food industry is subject to several scourges that can affect the quality of raw milk and change its destination and its ways of transformation into derived products. The determination of the dairy breed is a major challenge for both the producer and the consumer who constantly care about the quality of milk. This work and exploratory study were conducted with the objective of classifying milk based on bovine breed, utilizing physico-chemical properties and chemometric techniques. The aim was to develop a classification model that could effectively differentiate between milk samples from different breeds of cows by analyzing their specific physical and chemical characteristics. The milk of two foreign purebreds, Holstein and Montbeliarde and a third local one namedAtlas Brown breed, was qualitatively monitored through physico-chemical analyses. Principal component analysis (PCA) was applied to study the similarity between individuals and the correlation between variables. In addition, a supervised classification algorithm has been studied namely canonical discriminant analysis (CDA) to predict the species of a test sample. The results obtained by PCA indicate a separation of the different species. The prediction results of the test sets found for the supervised classification models showed that the performance of the CDA model gives efficient results for external validation. The CCR of this technique was 93.33%. The sensitivity of this technique was 83.33–100% and the specificity was 90.91–100%, which was considered excellent for the corresponding classification of samples according to their species.

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Authors and Affiliations

  1. Laboratory of Organic and Analytical Chemistry, Faculty of Science and Technics, Sultan Moulay Slimane University, Beni Mellal, Morocco

    Lamiae alami, Aimen El Orche & Manar Otmani

  2. Pharmacology and toxicology laboratory, Faculty of Medicine and Pharmacy, Cadi Ayyad University, Marrakech, Morocco

    Omar Elhamdaoui

  3. Laboratory of Analytical Chemistry & Bromatology, Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, 10100, Morocco

    Mustapha Bouatia

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  1. Lamiae alami
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  2. Aimen El Orche
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  3. Manar Otmani
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Correspondence to Aimen El Orche.

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alami, L., El Orche, A., Otmani, M. et al. Discrimination of milk species based on physico-chemical properties and chemometrics: application of principal component analysis and canonical discriminant analysis. Food Measure 17, 5175–5184 (2023). https://doi.org/10.1007/s11694-023-02025-0

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  • DOI: https://doi.org/10.1007/s11694-023-02025-0

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