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Headspace Solid-Phase Microextraction-Gas Chromatography-Mass Spectrometry Quantification of the Volatile Profile of More than 1200 Virgin Olive Oils for Supporting the Panel Test in Their Classification: Comparison of Different Chemometric Approaches.
J Agric Food Chem. 2019 Aug 14; 67(32):9112-9120.JA

Abstract

A reliable and robust tool for supporting the panel test in virgin olive oil classification is still required. We propose four chemometric approaches based on t test, principal component analysis (PCA) and linear discriminant analysis (LDA), applied for combining sensorial data, and chemical measurements. The former was from the panel test, and the latter was from headspace solid-phase microextraction-gas chromatography-mass spectrometry quantitation of 73 volatile organic compounds (VOCs) of 1223 typical commercial virgin olive oils, with most of them recognized as difficult to classify with accuracy by the panel test. The approaches were developed and validated, and the best results, with 83.5% correct classification, were using the PCA-LDA approach. Among the other methods, developed for proposing simplified procedures based on a smaller number of VOCs, the best method gave 80.1% correct classification only using 10 VOCs. All of the approaches suggested that octane, heptanal, pent-1-en-3-ol, Z-3-hexenal, nonanal, and 4-ethylphenol should be considered as a basis of volatiles for classification of olive oil samples.

Authors+Show Affiliations

Dipartimento di NEUROFARBA , Università degli Studi di Firenze , Via Ugo Schiff 6 , 50019 Sesto Fiorentino, Florence , Italy.Carapelli Firenze S.p.A. , Via Leonardo da Vinci 31 , 50028 Tavarnelle Val di Pesa, Florence , Italy.Carapelli Firenze S.p.A. , Via Leonardo da Vinci 31 , 50028 Tavarnelle Val di Pesa, Florence , Italy.Carapelli Firenze S.p.A. , Via Leonardo da Vinci 31 , 50028 Tavarnelle Val di Pesa, Florence , Italy.Carapelli Firenze S.p.A. , Via Leonardo da Vinci 31 , 50028 Tavarnelle Val di Pesa, Florence , Italy.Dipartimento di NEUROFARBA , Università degli Studi di Firenze , Via Ugo Schiff 6 , 50019 Sesto Fiorentino, Florence , Italy.Dipartimento di NEUROFARBA , Università degli Studi di Firenze , Via Ugo Schiff 6 , 50019 Sesto Fiorentino, Florence , Italy.

Pub Type(s)

Comparative Study
Evaluation Study
Journal Article

Language

eng

PubMed ID

31314506

Citation

Cecchi, Lorenzo, et al. "Headspace Solid-Phase Microextraction-Gas Chromatography-Mass Spectrometry Quantification of the Volatile Profile of More Than 1200 Virgin Olive Oils for Supporting the Panel Test in Their Classification: Comparison of Different Chemometric Approaches." Journal of Agricultural and Food Chemistry, vol. 67, no. 32, 2019, pp. 9112-9120.
Cecchi L, Migliorini M, Giambanelli E, et al. Headspace Solid-Phase Microextraction-Gas Chromatography-Mass Spectrometry Quantification of the Volatile Profile of More than 1200 Virgin Olive Oils for Supporting the Panel Test in Their Classification: Comparison of Different Chemometric Approaches. J Agric Food Chem. 2019;67(32):9112-9120.
Cecchi, L., Migliorini, M., Giambanelli, E., Rossetti, A., Cane, A., Melani, F., & Mulinacci, N. (2019). Headspace Solid-Phase Microextraction-Gas Chromatography-Mass Spectrometry Quantification of the Volatile Profile of More than 1200 Virgin Olive Oils for Supporting the Panel Test in Their Classification: Comparison of Different Chemometric Approaches. Journal of Agricultural and Food Chemistry, 67(32), 9112-9120. https://doi.org/10.1021/acs.jafc.9b03346
Cecchi L, et al. Headspace Solid-Phase Microextraction-Gas Chromatography-Mass Spectrometry Quantification of the Volatile Profile of More Than 1200 Virgin Olive Oils for Supporting the Panel Test in Their Classification: Comparison of Different Chemometric Approaches. J Agric Food Chem. 2019 Aug 14;67(32):9112-9120. PubMed PMID: 31314506.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Headspace Solid-Phase Microextraction-Gas Chromatography-Mass Spectrometry Quantification of the Volatile Profile of More than 1200 Virgin Olive Oils for Supporting the Panel Test in Their Classification: Comparison of Different Chemometric Approaches. AU - Cecchi,Lorenzo, AU - Migliorini,Marzia, AU - Giambanelli,Elisa, AU - Rossetti,Adolfo, AU - Cane,Anna, AU - Melani,Fabrizio, AU - Mulinacci,Nadia, Y1 - 2019/07/31/ PY - 2019/7/18/pubmed PY - 2019/8/27/medline PY - 2019/7/18/entrez KW - LDA KW - PCA KW - extra virgin olive oil KW - microbiological indices KW - oxidative indices KW - volatile compounds SP - 9112 EP - 9120 JF - Journal of agricultural and food chemistry JO - J Agric Food Chem VL - 67 IS - 32 N2 - A reliable and robust tool for supporting the panel test in virgin olive oil classification is still required. We propose four chemometric approaches based on t test, principal component analysis (PCA) and linear discriminant analysis (LDA), applied for combining sensorial data, and chemical measurements. The former was from the panel test, and the latter was from headspace solid-phase microextraction-gas chromatography-mass spectrometry quantitation of 73 volatile organic compounds (VOCs) of 1223 typical commercial virgin olive oils, with most of them recognized as difficult to classify with accuracy by the panel test. The approaches were developed and validated, and the best results, with 83.5% correct classification, were using the PCA-LDA approach. Among the other methods, developed for proposing simplified procedures based on a smaller number of VOCs, the best method gave 80.1% correct classification only using 10 VOCs. All of the approaches suggested that octane, heptanal, pent-1-en-3-ol, Z-3-hexenal, nonanal, and 4-ethylphenol should be considered as a basis of volatiles for classification of olive oil samples. SN - 1520-5118 UR - https://www.unboundmedicine.com/medline/citation/31314506/Headspace_Solid_Phase_Microextraction_Gas_Chromatography_Mass_Spectrometry_Quantification_of_the_Volatile_Profile_of_More_than_1200_Virgin_Olive_Oils_for_Supporting_the_Panel_Test_in_Their_Classification:_Comparison_of_Different_Chemometric_Approaches_ DB - PRIME DP - Unbound Medicine ER -