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Assessment of Pumpkin Seed Oil Adulteration Supported by Multivariate Analysis: Comparison of GC-MS, Colourimetry and NIR Spectroscopy Data
Because of its high market value, pumpkin seed oil is occasionally adulterated by cheaper refined oils, usually sunflower oil. The standard method for detecting its authenticity is based on expensive and laborious determination of the sterol composition. Therefore, the objective of this study was to...
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/PMC8954646/ https://www.ncbi.nlm.nih.gov/pubmed/35327258 http://dx.doi.org/10.3390/foods11060835 |
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author | Balbino, Sandra Vincek, Dragutin Trtanj, Iva Egređija, Dunja Gajdoš-Kljusurić, Jasenka Kraljić, Klara Obranović, Marko Škevin, Dubravka |
author_facet | Balbino, Sandra Vincek, Dragutin Trtanj, Iva Egređija, Dunja Gajdoš-Kljusurić, Jasenka Kraljić, Klara Obranović, Marko Škevin, Dubravka |
author_sort | Balbino, Sandra |
collection | PubMed |
description | Because of its high market value, pumpkin seed oil is occasionally adulterated by cheaper refined oils, usually sunflower oil. The standard method for detecting its authenticity is based on expensive and laborious determination of the sterol composition. Therefore, the objective of this study was to determine the sterol content and authenticity of retail oils labelled as pumpkin seed oil and also to investigate the potential of near-infrared spectroscopy (NIR) and colourimetry in detecting adulteration. The results show that due to the significant decrease in Δ7-sterols and increase in Δ5-sterols, 48% of the analysed oils can be declared as adulterated blends of pumpkin seed and sunflower oil. Significant differences in NIR spectroscopy data, in the range of 904–922 nm and 1675–1699 nm, and colourimetric data were found between the control pumpkin seed oil and sunflower oil, but only the NIR method had the potential to detect the authenticity of pumpkin seed oil, which was confirmed by principal component analysis. Orthogonal projection on latent structures (OPLS) discriminant analysis, resulted in working classification models that were able to discriminate pure and adulterated oil. OPLS models based on NIR spectra were also able to successfully predict the content of β-sitosterol and Δ7,22-stigmastadienol in the analysed oils. |
format | Online Article Text |
id | pubmed-8954646 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-89546462022-03-26 Assessment of Pumpkin Seed Oil Adulteration Supported by Multivariate Analysis: Comparison of GC-MS, Colourimetry and NIR Spectroscopy Data Balbino, Sandra Vincek, Dragutin Trtanj, Iva Egređija, Dunja Gajdoš-Kljusurić, Jasenka Kraljić, Klara Obranović, Marko Škevin, Dubravka Foods Article Because of its high market value, pumpkin seed oil is occasionally adulterated by cheaper refined oils, usually sunflower oil. The standard method for detecting its authenticity is based on expensive and laborious determination of the sterol composition. Therefore, the objective of this study was to determine the sterol content and authenticity of retail oils labelled as pumpkin seed oil and also to investigate the potential of near-infrared spectroscopy (NIR) and colourimetry in detecting adulteration. The results show that due to the significant decrease in Δ7-sterols and increase in Δ5-sterols, 48% of the analysed oils can be declared as adulterated blends of pumpkin seed and sunflower oil. Significant differences in NIR spectroscopy data, in the range of 904–922 nm and 1675–1699 nm, and colourimetric data were found between the control pumpkin seed oil and sunflower oil, but only the NIR method had the potential to detect the authenticity of pumpkin seed oil, which was confirmed by principal component analysis. Orthogonal projection on latent structures (OPLS) discriminant analysis, resulted in working classification models that were able to discriminate pure and adulterated oil. OPLS models based on NIR spectra were also able to successfully predict the content of β-sitosterol and Δ7,22-stigmastadienol in the analysed oils. MDPI 2022-03-14 /pmc/articles/PMC8954646/ /pubmed/35327258 http://dx.doi.org/10.3390/foods11060835 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 Balbino, Sandra Vincek, Dragutin Trtanj, Iva Egređija, Dunja Gajdoš-Kljusurić, Jasenka Kraljić, Klara Obranović, Marko Škevin, Dubravka Assessment of Pumpkin Seed Oil Adulteration Supported by Multivariate Analysis: Comparison of GC-MS, Colourimetry and NIR Spectroscopy Data |
title | Assessment of Pumpkin Seed Oil Adulteration Supported by Multivariate Analysis: Comparison of GC-MS, Colourimetry and NIR Spectroscopy Data |
title_full | Assessment of Pumpkin Seed Oil Adulteration Supported by Multivariate Analysis: Comparison of GC-MS, Colourimetry and NIR Spectroscopy Data |
title_fullStr | Assessment of Pumpkin Seed Oil Adulteration Supported by Multivariate Analysis: Comparison of GC-MS, Colourimetry and NIR Spectroscopy Data |
title_full_unstemmed | Assessment of Pumpkin Seed Oil Adulteration Supported by Multivariate Analysis: Comparison of GC-MS, Colourimetry and NIR Spectroscopy Data |
title_short | Assessment of Pumpkin Seed Oil Adulteration Supported by Multivariate Analysis: Comparison of GC-MS, Colourimetry and NIR Spectroscopy Data |
title_sort | assessment of pumpkin seed oil adulteration supported by multivariate analysis: comparison of gc-ms, colourimetry and nir spectroscopy data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8954646/ https://www.ncbi.nlm.nih.gov/pubmed/35327258 http://dx.doi.org/10.3390/foods11060835 |
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