Discrimination of Spanish-Style Green Olives Inoculated with Undesirable Microbiota Using E-Nose, Chemometrics and Volatile Compound Profiles

TL;DR

This study shows how an electronic nose can detect spoilage in Spanish-style green olives caused by harmful bacteria, using smell and chemical analysis.

Contribution

The novel use of E-nose and chemometric analysis to detect and classify spoilage in olives caused by specific bacterial strains.

Findings

E-nose and VOC analysis successfully distinguished spoiled from non-spoiled olives with 90.4% accuracy.

Bacillus cereus and Enterobacter cloacae showed the highest spoilage tolerance and caused distinct aroma defects.

PCA of E-nose data explained 84.8% of variance, separating spoiled and non-spoiled samples.

Abstract

This study evaluated the potential of electronic nose (E-nose) technology to discriminate Spanish-style green table olives spoiled by different bacterial strains. Microbial growth, physicochemical properties, sensory attributes, and volatile organic compounds (VOCs) profiles were analyzed to assess spoilage patterns. The results indicated strain-dependent microbial survival during incubation, with Bacillus cereus and Enterobacter cloacae showing the highest tolerance. Inoculated olives exhibited significant changes in color, texture, pH, phenolic content, and antioxidant activity compared to the Control. Sensory evaluation revealed a reduction in positive attributes and the emergence of defects such as cooked, rancid, and woody aromas, particularly in olives inoculated with B. cereus and Escherichia coli. VOC analysis confirmed these alterations, showing strain-specific increases in aldehydes, phenols, and esters, along with reductions in alcohols and acids. Principal component analysis (PCA) of E-nose data successfully distinguished two groups—spoiled and non-spoiled samples—explaining 84.8% of variance, while Partial Least Squares Discriminant Analysis (PLS-DA) achieved a classification accuracy of 90.4%. These findings highlight the E-nose as a rapid, non-destructive, and reliable tool for detecting bacterial spoilage in table olives, with potential applications in quality control and early spoilage detection.

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