Quality Assessment of Reconstructed Cow, Camel and Mare Milk Powders by Near-Infrared Spectroscopy and Chemometrics

Milk powders are becoming a major attraction for many industrial applications due to their nutritional and functional properties. Different types of powdered milk, each with their own distinct chemical compositions, can have different functionalities. Consequently, the development of rapid monitorin...

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Veröffentlicht in:Molecules (Basel, Switzerland) Switzerland), 2024-08, Vol.29 (17), p.3989
Hauptverfasser: Majadi, Mariem, Barkó, Annamária, Varga-Tóth, Adrienn, Maukenovna, Zhulduz Suleimenova, Batirkhanovna, Dossimova Zhanna, Dilora, Senkebayeva, Lukacs, Matyas, Kaszab, Timea, Mednyánszky, Zsuzsanna, Kovacs, Zoltan
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Sprache:eng
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Zusammenfassung:Milk powders are becoming a major attraction for many industrial applications due to their nutritional and functional properties. Different types of powdered milk, each with their own distinct chemical compositions, can have different functionalities. Consequently, the development of rapid monitoring methods is becoming an urgent task to explore and expand their applicability. Lately, there is growing emphasis on the potential of near-infrared spectroscopy (NIRS) as a rapid technique for the quality assessment of dairy products. In the present work, we explored the potential of NIRS coupled with chemometrics for the prediction of the main functional and chemical properties of three types of milk powders, as well as their important processing parameters. Mare, camel and cow milk powders were prepared at different concentrations (5%, 10% and 12%) and temperatures (25 °C, 40 °C and 65 °C), and then their main physicochemical attributes and NIRS spectra were analyzed. Overall, high accuracy in both recognition and prediction based on type, concentration and temperature was achieved by NIRS-based models, and the quantification of quality attributes (pH, viscosity, dry matter content, fat content, conductivity and individual amino acid content) also resulted in high accuracy in the models. R CV and R pr values ranging from 0.8 to 0.99 and 0.7 to 0.98, respectively, were obtained by using PLSR models. However, SVR models achieved higher R CV and R pr values, ranging from 0.91 to 0.99 and 0.80 to 0.99, respectively.
ISSN:1420-3049
1420-3049
DOI:10.3390/molecules29173989