Phytochemical analysis of trifoliate orange during fermentation by HPLC–DAD–ESI–MS/MS coupled with multivariate statistical analysis
نویسندگان
چکیده
Abstract During the process of fermentation, chemical compositions trifoliate orange ( Poncirus (L). Raf) changed greatly. To provide a completely phytochemical profile, high-performance liquid chromatography-diode array detector-hyphenated with tandem mass spectrometry (HPLC–DAD–ESI-MS/MS) has been successfully applied to screen and identify unknown constituents during which make it available for quality control fermented products. Multivariate statistical analysis was performed classify oranges based on status fermentation. A total 8 components were identified among samples. Hierarchical Clustering Analysis (HCA) Principal Component (PCA) demonstrated unfermented obviously different, an effective reliable Partial Least Square Discriminate (PLS-DA) technique more suitable accurate discrimination test samples their different patterns. Furthermore, permutation validated reliability PLS-DA variable importance plot revealed that characterized syringing, naringin, poncirin showed high ability distinguish The present investigation could detailed information evaluation fermentation process.
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چکیده ندارد.
15 صفحه اولMultivariate Statistical Analysis
Classical multivariate statistical methods concern models, distributions and inference based on the Gaussian distribution. These are the topics in the first textbook for mathematical statisticians by T.W. Anderson that was published in 1958 and that appeared as a slightly expanded 3rd edition in 2003. Matrix theory and notation is used there extensively to efficiently derive properties of the m...
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ژورنال
عنوان ژورنال: Acta Chromatographica
سال: 2021
ISSN: ['2083-5736', '1233-2356']
DOI: https://doi.org/10.1556/1326.2020.00818