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Characterization and Authentication of “Ricotta” Whey Cheeses through GC-FID Analysis of Fatty Acid Profile and Chemometrics
The fatty acid (FA) profiles of 240 samples of ricotta whey cheese made from sheep, goat, cow, or water buffalo milk were analyzed by gas-chromatography (GC). Then, sequential preprocessing through orthogonalization (SPORT) was used in order to classify samples according to the nature of the milk th...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9658715/ https://www.ncbi.nlm.nih.gov/pubmed/36364228 http://dx.doi.org/10.3390/molecules27217401 |
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author | Biancolillo, Alessandra Reale, Samantha Foschi, Martina Bertini, Emanuele Antonelli, Lavinia D’Archivio, Angelo Antonio |
author_facet | Biancolillo, Alessandra Reale, Samantha Foschi, Martina Bertini, Emanuele Antonelli, Lavinia D’Archivio, Angelo Antonio |
author_sort | Biancolillo, Alessandra |
collection | PubMed |
description | The fatty acid (FA) profiles of 240 samples of ricotta whey cheese made from sheep, goat, cow, or water buffalo milk were analyzed by gas-chromatography (GC). Then, sequential preprocessing through orthogonalization (SPORT) was used in order to classify samples according to the nature of the milk they were made from. This strategy achieved excellent results, correctly classifying 77 (out of 80) validation samples. Eventually, since 36 (over 114) sheep ricotta whey cheeses were PDO products, a second classification problem, finalizing the discrimination of PDO and Non-PDO dairies, was faced. In this case, two classifiers were used, SPORT and soft independent modelling by class analogy (SIMCA). Both approaches provided more than satisfying results; in fact, SPORT properly assigned 63 (of 65) test samples, whereas the SIMCA model accepted 14 PDO individuals over 15 (93.3% sensitivity) and correctly rejected all the other samples (100.0% specificity). In conclusion, all the tested approaches resulted as suitable for the two fixed purposes. Eventually, variable importance in projection (VIP) analysis was used to understand which FAs characterize the different categories of ricotta. Among the 22 analyzed compounds, about 10 are considered the most relevant for the solution of the investigated problems. |
format | Online Article Text |
id | pubmed-9658715 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96587152022-11-15 Characterization and Authentication of “Ricotta” Whey Cheeses through GC-FID Analysis of Fatty Acid Profile and Chemometrics Biancolillo, Alessandra Reale, Samantha Foschi, Martina Bertini, Emanuele Antonelli, Lavinia D’Archivio, Angelo Antonio Molecules Article The fatty acid (FA) profiles of 240 samples of ricotta whey cheese made from sheep, goat, cow, or water buffalo milk were analyzed by gas-chromatography (GC). Then, sequential preprocessing through orthogonalization (SPORT) was used in order to classify samples according to the nature of the milk they were made from. This strategy achieved excellent results, correctly classifying 77 (out of 80) validation samples. Eventually, since 36 (over 114) sheep ricotta whey cheeses were PDO products, a second classification problem, finalizing the discrimination of PDO and Non-PDO dairies, was faced. In this case, two classifiers were used, SPORT and soft independent modelling by class analogy (SIMCA). Both approaches provided more than satisfying results; in fact, SPORT properly assigned 63 (of 65) test samples, whereas the SIMCA model accepted 14 PDO individuals over 15 (93.3% sensitivity) and correctly rejected all the other samples (100.0% specificity). In conclusion, all the tested approaches resulted as suitable for the two fixed purposes. Eventually, variable importance in projection (VIP) analysis was used to understand which FAs characterize the different categories of ricotta. Among the 22 analyzed compounds, about 10 are considered the most relevant for the solution of the investigated problems. MDPI 2022-10-31 /pmc/articles/PMC9658715/ /pubmed/36364228 http://dx.doi.org/10.3390/molecules27217401 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Biancolillo, Alessandra Reale, Samantha Foschi, Martina Bertini, Emanuele Antonelli, Lavinia D’Archivio, Angelo Antonio Characterization and Authentication of “Ricotta” Whey Cheeses through GC-FID Analysis of Fatty Acid Profile and Chemometrics |
title | Characterization and Authentication of “Ricotta” Whey Cheeses through GC-FID Analysis of Fatty Acid Profile and Chemometrics |
title_full | Characterization and Authentication of “Ricotta” Whey Cheeses through GC-FID Analysis of Fatty Acid Profile and Chemometrics |
title_fullStr | Characterization and Authentication of “Ricotta” Whey Cheeses through GC-FID Analysis of Fatty Acid Profile and Chemometrics |
title_full_unstemmed | Characterization and Authentication of “Ricotta” Whey Cheeses through GC-FID Analysis of Fatty Acid Profile and Chemometrics |
title_short | Characterization and Authentication of “Ricotta” Whey Cheeses through GC-FID Analysis of Fatty Acid Profile and Chemometrics |
title_sort | characterization and authentication of “ricotta” whey cheeses through gc-fid analysis of fatty acid profile and chemometrics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9658715/ https://www.ncbi.nlm.nih.gov/pubmed/36364228 http://dx.doi.org/10.3390/molecules27217401 |
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