The determination of fatty acids in cheeses of variable composition (cow, ewe's, and goat) by means of near infrared spectroscopy
•NIRS allows predicting the lipid profile of cheese of varying composition.•NIRS technology can be used to know the fatty acids of cheese throughout ripening.•NIR calibration using extracted fat and intact samples offers comparable results. The fat composition is one of the factors which has the gre...
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Veröffentlicht in: | Microchemical journal 2020-07, Vol.156, p.104854, Article 104854 |
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Sprache: | eng |
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Zusammenfassung: | •NIRS allows predicting the lipid profile of cheese of varying composition.•NIRS technology can be used to know the fatty acids of cheese throughout ripening.•NIR calibration using extracted fat and intact samples offers comparable results.
The fat composition is one of the factors which has the greatest influence on cheese. The fatty acids present in the same influence sensory parameters such as color, texture, and flavor (rancid and pungent). They likewise influence the nutritional composition of cheese as different fatty acids have beneficial or harmful effects on human health. On the other hand, the determination of the fatty acids present in cheese has been put forward as a useful tool for distinguishing the various cheeses according to the milk used in their production. Finding a tool which allows the determination of the fatty acids present in cheese in a rapid and non destructive manner is of great interest to the cheese industry. In this study we examine the use of Near-Infrared Spectroscopy (NIRS) technology in the determination of 19 fatty acids in cheese from C8:0 to C20:0 including ∑SFA and ∑UFA. Cheeses were made with known and varying percentages of cow, ewe's, and goat milk (112 samples) and ripening controls were carried out for 6 months. Two ways of recording the spectra are compared, one using a remote reflectance fiber-optic probe on a slice of cheese and another using the fatty extracts obtained from the same cheeses and recorded with cam-lock cells. The regression method used is MPLS. The results obtained reveal that it is possible to predict the fatty acid composition of cheese by means of the use of NIRS, irrespective of the method used to record it. Furthermore, the results obtained in the validation of the method used indicate that the equations obtained allow their application to unknown cheese samples. |
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ISSN: | 0026-265X 1095-9149 |
DOI: | 10.1016/j.microc.2020.104854 |