Academic Journal

Non-targeted volatilomics for the authentication of saffron by gas chromatography-ion mobility spectrometry and multivariate curve resolution.

التفاصيل البيبلوغرافية
العنوان: Non-targeted volatilomics for the authentication of saffron by gas chromatography-ion mobility spectrometry and multivariate curve resolution.
المؤلفون: Parastar, Hadi1 (AUTHOR) h.parastar@sharif.edu, Yazdanpanah, Hassan2,3 (AUTHOR), Weller, Philipp1,4 (AUTHOR) p.weller@hs-mannheim.de
المصدر: Food Chemistry. Feb2025:Part 2, Vol. 465, pN.PAG-N.PAG. 1p.
مصطلحات موضوعية: *PATTERN recognition systems, *PRINCIPAL components analysis, *SAFFRON crocus, *LEAST squares, *CHEMOMETRICS
مستخلص: In the present contribution, a novel non-targeted volatilomic study based on headspace GC-IMS (HS-GC-IMS) was developed for the authentication and geographical origin discrimination of saffron. In this regard, multivariate curve resolution-alternating least squares (MCR-ALS) was employed to recover the pure GC elution and IMS profiles of saffron metabolites. Iranian saffron samples from seven important areas were analyzed by HS-GC-IMS. The resulting second-order GC-IMS datasets were organized in a augmented matrix and processed using MCR-ALS with various constraints. The MCR-ALS resolved GC profiles were analyzed by different pattern recognition techniques; principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and data driven-soft independent modeling of class analogy (DD-SIMCA). The saffron samples were assigned to their seven geographical origins with an accuracy of 89.0 %. Additionally, four adulterants (style, safflower, madder and calendula) were reliably detected with over 94.0 % accuracy. In this context, GC-IMS substantially outperformed the commonly used FT-NIR spectroscopy approach. • A non-targeted GC-IMS volatilomic approach is proposed for saffron authentication. • MCR-ALS is developed for exploiting pure GC-IMS profiles of saffron metabolites. • PLS-DA is used for geographical discrimination of saffron from seven regions. • DD-SIMCA is utilized for detection of the adulterated saffron samples. • GC-IMS outperformed FT-NIR for saffron authentication. [ABSTRACT FROM AUTHOR]
قاعدة البيانات: Academic Search Index
الوصف
تدمد:03088146
DOI:10.1016/j.foodchem.2024.142074