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Electronic-Nose as Non-destructive Tool to Discriminate "Ferrovia" Sweet Cherries Cold Stored in Air or Packed in High CO2 Modified Atmospheres.


ABSTRACT: This study aimed to explore the applicability of electronic-nose (E-nose) as a rapid method in discriminating samples of sweet cherry cv "Ferrovia" stored in high-CO2 (16% O2 + 20% CO2 + 64% N2) or air (control) up to 21 days. Projection to Latent Structures (PLS) methods applied to E-nose data showed that fresh fruit and the packaged or unpackaged samples can be distinguished, according to both the storage condition and the storage days. Moreover, a correlation analysis between E-nose sensors and 45 volatile compounds were overall, obtained from all the investigated sweet cherry samples by Headspace Solid-Phase Microextraction (HS SPME) coupled to Gas Chromatography-Mass Spectrometry (GC-MS). These methods allowed to associate samples with a specific flavour profile to one or more E-nose sensors. Finally, quality attributes (visual quality, colour, firmness, antioxidant activity, total phenols, and sugar content) were assessed during storage. Among these, visual quality and berry deformation resulted affected by storage conditions, showing that high-CO2 treatment better preserved the fruit quality than control.

SUBMITTER: Cozzolino R 

PROVIDER: S-EPMC8491769 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Electronic-Nose as Non-destructive Tool to Discriminate "Ferrovia" Sweet Cherries Cold Stored in Air or Packed in High CO<sub>2</sub> Modified Atmospheres.

Cozzolino Rosaria R   Cefola Maria M   Laurino Carmine C   Pellicano Mario Paolo MP   Palumbo Michela M   Stocchero Matteo M   Pace Bernardo B  

Frontiers in nutrition 20210921


This study aimed to explore the applicability of electronic-nose (E-nose) as a rapid method in discriminating samples of sweet cherry cv "Ferrovia" stored in high-CO<sub>2</sub> (16% O<sub>2</sub> + 20% CO<sub>2</sub> + 64% N<sub>2</sub>) or air (control) up to 21 days. Projection to Latent Structures (PLS) methods applied to E-nose data showed that fresh fruit and the packaged or unpackaged samples can be distinguished, according to both the storage condition and the storage days. Moreover, a c  ...[more]

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