| Title: | Monitoring of fresh-cut Valerianella locusta Laterr. shelf life by electronic nose and VIS-NIR spectroscopy |
| Author(s): | Giovenzana V; Beghi R; Buratti S; Civelli R; Guidetti R; |
| Address: | "Department of Agricultural and Environmental Sciences - Production, Landscape, Agroenergy (DiSAA), Universita degli Studi di Milano, via Celoria 2, 20133 Milano, Italy. Department of Agricultural and Environmental Sciences - Production, Landscape, Agroenergy (DiSAA), Universita degli Studi di Milano, via Celoria 2, 20133 Milano, Italy. Electronic address: roberto.beghi@unimi.it. Department of Food, Environmental and Nutritional Sciences (DeFENS), Universita degli Studi di Milano, via Celoria 2, 20133 Milano, Italy" |
| DOI: | 10.1016/j.talanta.2013.12.014 |
| ISSN/ISBN: | 1873-3573 (Electronic) 0039-9140 (Linking) |
| Abstract: | "The aim of this work was to investigate the applicability of non-destructive techniques in monitoring freshness decay of fresh-cut Valerianella locusta L. during storage at different temperature. The sampling was performed for 15 days for Valerianella samples preserved at 4 and 10 degrees C, and for 7 days for samples stored at 20 degrees C. The quality decay of samples was evaluated by quality parameters (pH, water content, total phenols, chlorophyll a fluorescence) and by non-destructive systems (electronic nose and visible-near infrared spectroscopy). Cluster Analysis (CA) was performed on quality indices and four clusters were identified, namely 'fresh', 'acceptable', 'spoiled' and 'very spoiled'. Principal Component Analysis (PCA) was applied on the electronic nose data in order to evaluate the feasibility of this technique as a rapid and non-destructive approach for monitoring the freshness of fresh-cut Valerianella during storage. Linear Discriminant Analysis (LDA) and PLS-discriminant analysis (PLS-DA) models were developed to test the performance of electronic nose and VIS-NIR, respectively, to classify samples in the four classes of freshness. The average value of samples correctly classified using LDA was 95.5% and the cross validation error rate was equal to 8.7%. The results obtained from PLS-DA models, in validation, gave a positive predictive value (PPV) of classification between 74% and 96%. Finally, predictive models were performed using Partial Least Squares (PLS) regression analysis between quality indices and VIS-NIR data. RPD values <3 were obtained for water content and pH. Excellent results were obtained for total phenols with Rcv(2) and RPD equal to 0.89 and 3.19, and for chlorophyll a fluorescence with Rcv(2) and RPD equal to 0.92 and 3.22, respectively. Results demonstrated that electronic nose and VIS-NIR are complementary techniques able to support the conventional techniques in the shelf-life assessment of fresh-cut V. locusta L. providing information useful for a better management of the product along the distribution chain" |
| Keywords: | "Cluster Analysis Discriminant Analysis *Electronic Nose Food Preservation Least-Squares Analysis *Spectroscopy, Near-Infrared Valerianella/*chemistry Volatile Organic Compounds/analysis Chemometrics Non-destructive analysis Ready to eat Storage Valerianel;" |
| Notes: | "MedlineGiovenzana, Valentina Beghi, Roberto Buratti, Susanna Civelli, Raffaele Guidetti, Riccardo eng Research Support, Non-U.S. Gov't Netherlands 2014/01/29 Talanta. 2014 Mar; 120:368-75. doi: 10.1016/j.talanta.2013.12.014. Epub 2013 Dec 18" |
