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      Headspace GC/MS and fast GC e-nose combined with chemometric analysis to identify the varieties and geographical origins of ginger (Zingiber officinale Roscoe)

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      Food Chemistry
      Elsevier BV

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          Nutritional implications of ginger: chemistry, biological activities and signaling pathways

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            Is Open Access

            Rapid direct analysis to discriminate geographic origin of extra virgin olive oils by flash gas chromatography electronic nose and chemometrics.

            At present, the geographical origin of extra virgin olive oils can be ensured by documented traceability, although chemical analysis may add information that is useful for possible confirmation. This preliminary study investigated the effectiveness of flash gas chromatography electronic nose and multivariate data analysis to perform rapid screening of commercial extra virgin olive oils characterized by a different geographical origin declared in the label. A comparison with solid phase micro extraction coupled to gas chromatography mass spectrometry was also performed. The new method is suitable to verify the geographic origin of extra virgin olive oils based on principal components analysis and discriminant analysis applied to the volatile profile of the headspace as a fingerprint. The selected variables were suitable in discriminating between "100% Italian" and "non-100% Italian" oils. Partial least squares discriminant analysis also allowed prediction of the degree of membership of unknown samples to the classes examined.
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              Use of headspace GC/MS combined with chemometric analysis to identify the geographic origins of black tea.

              Some black teas demand high market prices. Black tea samples (306) collected from 10 geographic origins, including China (Guxi, Likou, Jinzipai, Guichi, Dongzhi, Changning, Wuyishan, Shaowu), India (Darjeeling), and Sri Lanka (Kandy), were analyzed using headspace volatilization followed by GC/MS (HS-GC/MS). Forty-eight volatile compounds were identified. The aroma compounds were mainly identified as alcohols, aldehydes, ketones, and esters. Analysis of either full-spectrum data or 22 tea compounds shared among the samples with k-Nearest Neighbor (k-NN) and Random Forest (RF) models discriminated all origins at 100% using KNN and 95% with RF using either data set. The discrimination rates using 2 key aroma compounds (linalool and geraniol) by k-NN were 100% for nine origins, with the rate for Guxi area at 89%, because 3 samples were classified to Jinzipai. The findings support the use of HS-GC/MS combined with chemometrics as a tool to identify the origin of black tea.
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                Author and article information

                Journal
                Food Chemistry
                Food Chemistry
                Elsevier BV
                03088146
                December 2022
                December 2022
                : 396
                : 133672
                Article
                10.1016/j.foodchem.2022.133672
                99dba780-0330-436d-8766-b15b4e6ce790
                © 2022

                https://www.elsevier.com/tdm/userlicense/1.0/

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