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Updated: Dec 29, 2025

Fruit Volatile Analysis Using an Electronic Nose
Published on: March 30, 2012
Quality evaluation of table grapes during storage by using 1H NMR, LC-HRMS, MS-eNose and multivariate statistical
Valentina Innamorato1, Francesco Longobardi2, Salvatore Cervellieri3
1Dipartimento di Chimica, Università di Bari "Aldo Moro", Via Orabona 4, 70126 Bari, Italy; Consiglio Nazionale delle Ricerche (CNR), Istituto Scienze delle Produzioni Alimentari (ISPA), Via Amendola 122/O, 70126 Bari, Italy.
Abstract:
Three non-targeted methods, i.e. 1H NMR, LC-HRMS, and HS-SPME/MS-eNose, combined with chemometrics, were used to classify two table grape cultivars (Italia and Victoria) based on five quality levels (5, 4, 3, 2, 1). Grapes at marketable quality levels (5, 4, 3) were also discriminated from non-marketable quality levels (2 and 1). PCA-LDA and PLS-DA were applied, and results showed that, the MS-eNose provided the best results. Specifically, with the Italia table grapes, mean prediction abilities ranging from 87% to 88% and from 98% to 99% were obtained for discrimination amongst the five quality levels and of marketability/non-marketability, respectively. For the cultivar Victoria, mean predictive abilities higher than 99% were achieved for both classifications. Good models were also obtained for both cultivars using NMR and HRMS data, but only for classification by marketability. Satisfying models were further validated by MCCV. Finally, the compounds that contributed the most to the discriminations were identified.
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