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- Bianchi, F., et al.
(författare)
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Characterisation of the volatile profile of orange juice contaminated with Alicyclobacillus acidoterrestris
- 2010
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Ingår i: Food Chemistry. - : Elsevier BV. - 0308-8146 .- 1873-7072. ; 123:3, s. 653-658
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Tidskriftsartikel (refereegranskat)abstract
- A rapid and reliable analytical method, based on the characterisation of the volatile profile by dynamic headspace extraction followed by gas chromatography mass-spectrometry, was developed in order to early detect Alicyclobacillus acidoterrestris spoilage in orange juice. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile compounds able to differentiate contaminated from not-contaminated samples. Significant differences in the volatile profile of the analysed samples were found, assessing the reliability of the proposed method to detect the A. acidoterrestris contamination in orange juice.Neither guaiacol nor 2,6-dibromophenol, usually regarded as A. acidoterrestris contamination markers, were detected in the analysed samples.
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- Bianchi, F., et al.
(författare)
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Differentiation of the volatile profile of microbiologically contaminated canned tomatoes by dynamic headspace extraction followed by gas chromatography-mass spectrometry analysis
- 2009
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Ingår i: Talanta. - : Elsevier BV. - 0039-9140 .- 1873-3573. ; 77:3, s. 962-970
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Tidskriftsartikel (refereegranskat)abstract
- The aromatic profile of microbiologically contaminated canned tomatoes was analyzed by the dynamic headspace extraction technique coupled with gas chromatography-mass spectrometry. Canned tomatoes contaminated with Escherichia coli, Saccharomyces cerevisiae and Aspergillus carbonarius were analyzed after 2 and 7 days. About 100 volatiles were detected, among which alcohols, aldehydes and ketones were the most abundant compounds. Gas chromatographic peak areas were used for statistical purposes. First, principal component analysis was carried out in order to visualize data trends and clusters. Then, linear discriminant analysis was performed in order to detect the set of volatile compounds ables to differentiate groups of analyzed samples. Five volatile compounds, i.e. ethanol, beta-myrcene,o-methyl styrene, 6-methyl-5-hepten-2-ol and 1-octanol, were found to be able to better discriminate between uncontaminated and contaminated samples. Prediction ability of the calculated model was estimated to be 100% by the "leave-one-out" cross-validation. An electronic nose device was then used to analyze the same contaminated and not contaminated canned tomato samples. Preliminary results were compared with those obtained by dynamic headspace gas chromatography-mass spectrometry, showing a good agreement.
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- Concina, Isabella, et al.
(författare)
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Early detection of microbial contamination in processed tomatoes by electronic nose
- 2009
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Ingår i: Food Control. - : Elsevier BV. - 0956-7135 .- 1873-7129. ; 20:10, s. 873-880
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Tidskriftsartikel (refereegranskat)abstract
- Microbial contamination can easily affect processed tomato, thus determining both organoleptic adulterations and potential health risks for customers. Innovative techniques for a rapid and reliable diagnose of spoilage, such as electronic nose technology, are highly requested in order to guarantee food safety and to improve production. In this work canned peeled tomatoes were artificially spoiled with different kinds of microbial flora and then were analyzed by means of an electronic nose based on thin film metal oxide gas sensors. Preliminary analyses by dynamic-headspace gas chromatographic-mass spectrometry showed significant differences in the semi-quantitative volatile compounds profile of spoiled tomato samples just after few hours from contamination, thus suggesting to employ the electronic nose for an early diagnose of microbial presence. The electronic nose was indeed able to reveal contamination, even at early stages depending on the type of contaminant (e.g. for Saccharomyces cerevisiae and Escherichia coli), and to recognize spoiled tomato samples with good classification performances.
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