3.9 Article

Fingerprint of PGI Mantova Cucumis melo by ICP-MS and Chemometric Analysis

期刊

CURRENT NUTRITION & FOOD SCIENCE
卷 17, 期 1, 页码 94-104

出版社

BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/1573401316999200504094207

关键词

CA; CDA; food analysis; ICP-MS; PCA; traceability; Traditional Agro-alimentary Production (TAP)

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This study analyzed yellow and green varieties of Cucumis melo fruits to compare the selective uptakes of inorganic elements among different cultivars. By using Cluster analysis, Principal component analysis, and Canonical discriminant analysis, the research aimed to ensure fruit quality and healthiness, support producers, and assist customers in safe food purchase. The results showed a strong relation between fruit origins and trace element contents, with effective discrimination power provided by the CDA approach.
Background and Objectives: In this work, yellow and green varieties of Cucumis melo fruits belonging to different cultivars were studied. In detail, three Sicilian cultivars of winter melons tutelated by TAP (Traditional agro-alimentary products) labels were considered, whereas asun protected the Calabrian winter melon was studied too. With the aim to compare the selective uptakes of inorganic elements among winter and summer fruits, the PGI Melone Mantovano was investigated. The purpose of this work was to apply the obtained results i) to guarantee the quality and healthiness of fruits, ii) to producers defend, iii) to help the customers in safe food purchase. Methods: All samples were analyzed by ICP-MS and the obtained results, subsequently, were subjected to Cluster analysis (CA), Principal component analysis (PCA) and Canonical discriminant analysis (CDA). Results: CA results were generally in agreement with samples origin, whereas the PCA elaboration has confirmed the presence of a strong relation between fruit origins and trace element contents. In particular, two principal components justified the 57.32% of the total variance (PC1 = 40.95%, PC2 = 16.37%). Finally, the CDA approach has provided several functions with high discrimination power, confirmed by the correct classification of all samples (100%). Conclusion: CA, PCA and CDA could represent an integrated to label to discriminate the origin of agri-food products and, thus, protect and guarantee their healthiness.

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