HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Full Text (PDF) Interpretive Summary Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Benedetti, S. Articles by Riva, M. Search for Related Content PubMed PubMed Citation Articles by Benedetti, S. Articles by Riva, M.

Shelf Life of Crescenza Cheese as Measured by Electronic Nose

Department of Food Science and Technology, University of Milan, Italy

Corresponding author: Nicoletta Sinelli; e-mail: nicoletta.sinelli{at}unimi.it.

The shelf life of Crescenza, a traditional Italian soft cheese, was measured using classical analysis and a commercial electronic nose. Two lots of samples directly supplied by a manufacturer at the beginning of their commercial life were stored at 2 constant temperatures (8 and 15°C) and analyzed until their respective expiration dates. Among the physicochemical parameters, pH, acidity, hue, and apparent yield rheological index appeared to be the best predictors of the quality decay. Changes in these indices were described with a sigmoidal transition function allowing definition of a loose and a severe shelf-life protocol, based on the trend of first and second time derivatives. A time range of 1 to 3 d at 15°C and 4 to 8 d at 8°C was accordingly assessed to maintain the freshness of Crescenza cheese. The quality decay of cheese aroma was evaluated by inspecting the headspace fingerprint of the same set of samples using the electronic nose. Sample classification through the aroma fingerprint confirmed the predicted shelf-life time ranges. A clear discrimination between "fresh," "aged," and "very aged" samples was obtained using principal components analysis, cluster analysis, and linear discriminant analysis statistical techniques. The predictive ability of the linear discriminant analysis classification model was confirmed by considering a new set of cheese samples purchased at the beginning of their commercial life from a local market and analyzed until their expiration date.

Key Words: shelf life • electronic nose • Crescenza cheese • headspace analysis

Abbreviation key: CA = cluster analysis, EN = electronic nose, LDA = linear discriminant analysis, PCA = principal components analysis.

This article has been cited by other articles:

				P. Burns, F. Patrignani, D. Serrazanetti, G. C. Vinderola, J. A. Reinheimer, R. Lanciotti, and M. E. Guerzoni Probiotic Crescenza Cheese Containing Lactobacillus casei and Lactobacillus acidophilus Manufactured with High-Pressure Homogenized Milk J Dairy Sci, February 1, 2008; 91(2): 500 - 512. [Abstract] [Full Text] [PDF]