Four varieties of red garlic (Allium sativum L.) cultivated in different Italian territories, Sulmona (Abruzzo), Proceno and Castelliri (Lazio), and Nubia (Sicily), were analysed by Attenuated Total Reflectance-Fourier Transformed Infrared (ATR-FTIR) spectroscopy. ATR-FTIR spectra of bulbils and bulbil tunics were separately acquired and processed by Partial Least Squares Discriminant Analysis (PLS-DA) with the aim of classifying the garlic samples on the basis of their geographical origin. Finally, two multi-block strategies (based on Sequential and Orthogonalized Partial Least Squares and Sequential and Orthogonalized Covariance Selection, coupled with Fisher's Linear Discriminant Analysis) have been applied in order to test whether a joint analysis of data could lead to higher prediction rates. Eventually, the best results were achieved by the multi-block approach based on SO-PLS, which allows obtaining a total classification rate of 95 % (corresponding to one misclassified sample over 20) in external validation.
Geographical discrimination of red garlic (Allium sativum L.) using fast and non-invasive Attenuated Total Reflectance-Fourier Transformed Infrared (ATR-FTIR) spectroscopy combined with chemometrics / Biancolillo, A.; Marini, F.; D'Archivio, A. A.. - In: JOURNAL OF FOOD COMPOSITION AND ANALYSIS. - ISSN 0889-1575. - 86:(2020). [10.1016/j.jfca.2019.103351]
Geographical discrimination of red garlic (Allium sativum L.) using fast and non-invasive Attenuated Total Reflectance-Fourier Transformed Infrared (ATR-FTIR) spectroscopy combined with chemometrics
Biancolillo A.
Primo
;Marini F.Secondo
;
2020
Abstract
Four varieties of red garlic (Allium sativum L.) cultivated in different Italian territories, Sulmona (Abruzzo), Proceno and Castelliri (Lazio), and Nubia (Sicily), were analysed by Attenuated Total Reflectance-Fourier Transformed Infrared (ATR-FTIR) spectroscopy. ATR-FTIR spectra of bulbils and bulbil tunics were separately acquired and processed by Partial Least Squares Discriminant Analysis (PLS-DA) with the aim of classifying the garlic samples on the basis of their geographical origin. Finally, two multi-block strategies (based on Sequential and Orthogonalized Partial Least Squares and Sequential and Orthogonalized Covariance Selection, coupled with Fisher's Linear Discriminant Analysis) have been applied in order to test whether a joint analysis of data could lead to higher prediction rates. Eventually, the best results were achieved by the multi-block approach based on SO-PLS, which allows obtaining a total classification rate of 95 % (corresponding to one misclassified sample over 20) in external validation.File | Dimensione | Formato | |
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