New insights into the Argan oil categories characterization: chemical descriptors, FTIR fingerprints, and chemometric approaches
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New insights into the Argan oil categories characterization : chemical descriptors, FTIR fingerprints, and chemometric approaches. / Kharbach, Mourad; Yu, Huiwen; Kamal, Rabie ; Barra, Issam ; Marmouzi, Ilias ; Cherrah, Yahia ; Alaoui, Katim ; Bouklouze, Abdelazize ; Vander Heyden, Yvan .
In: Talanta, Vol. 225, 122073, 2021.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - New insights into the Argan oil categories characterization
T2 - chemical descriptors, FTIR fingerprints, and chemometric approaches
AU - Kharbach, Mourad
AU - Yu, Huiwen
AU - Kamal, Rabie
AU - Barra, Issam
AU - Marmouzi, Ilias
AU - Cherrah, Yahia
AU - Alaoui, Katim
AU - Bouklouze, Abdelazize
AU - Vander Heyden, Yvan
PY - 2021
Y1 - 2021
N2 - The characterization of Argan oils to classify them in three categories (‘Extra Virgin’, ‘Virgin’ and ‘Lower quality’) was evaluated. A total of 120 Moroccan Argan oils samples from the Taroudant Argan forest was investigated. The free acidity, peroxide value, spectrophotometric indices (K232 and K270), fatty acids, sterols, and tocopherol contents were assessed. The samples were also scanned by FTIR spectroscopy. The Principal Component Analysis (PCA) and four classification methods, Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modelling of Class Analogy (SIMCA), K-nearest Neighbors (KNN), and Support Vector Machines (SVM), were applied on both the chemical and spectral data. Besides the conventional chemical profiling, FTIR spectra were evaluated for their feasibility as a rapid non-invasive approach for classifying and predicting the oil quality categories.The most important variables for differentiating the oil categories were identified as K232, peroxide value, ɣ-tocopherol, δ-tocopherol, acidity, stigma-8-22-dien-3β-ol, stearic acid (C18:0) and linoleic acid (C18:2) and could be used as quality indicators. Eight chemical descriptors or key features from the FTIR spectra (selected by interval-PLS) could also be established as indicators of quality and freshness of Argan oils.
AB - The characterization of Argan oils to classify them in three categories (‘Extra Virgin’, ‘Virgin’ and ‘Lower quality’) was evaluated. A total of 120 Moroccan Argan oils samples from the Taroudant Argan forest was investigated. The free acidity, peroxide value, spectrophotometric indices (K232 and K270), fatty acids, sterols, and tocopherol contents were assessed. The samples were also scanned by FTIR spectroscopy. The Principal Component Analysis (PCA) and four classification methods, Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modelling of Class Analogy (SIMCA), K-nearest Neighbors (KNN), and Support Vector Machines (SVM), were applied on both the chemical and spectral data. Besides the conventional chemical profiling, FTIR spectra were evaluated for their feasibility as a rapid non-invasive approach for classifying and predicting the oil quality categories.The most important variables for differentiating the oil categories were identified as K232, peroxide value, ɣ-tocopherol, δ-tocopherol, acidity, stigma-8-22-dien-3β-ol, stearic acid (C18:0) and linoleic acid (C18:2) and could be used as quality indicators. Eight chemical descriptors or key features from the FTIR spectra (selected by interval-PLS) could also be established as indicators of quality and freshness of Argan oils.
U2 - 10.1016/j.talanta.2020.122073
DO - 10.1016/j.talanta.2020.122073
M3 - Journal article
C2 - 33592791
VL - 225
JO - Talanta
JF - Talanta
SN - 0039-9140
M1 - 122073
ER -
ID: 249874682