Exploratory VOC profiling and chemometric differentiation of naturally and calcium carbide ripened bananas using GC-MS and electronic nose analysis

Abstract In the world of rapid technological changes, artificially induced methods are often used to accelerate the ripening process particularly in banana fruits for more profit, despite quality and safety concerns. This study highlights noticeable differences in the chemical composition and quality of ‘Karpuravalli’ ,Pisang Awak type, ABB bananas that are ripened naturally and those subjected to calcium carbide during ripening. With the rationale of classifying naturally and calcium carbide treated banana fruits, this paper proposes a novel smart sensory method using headspace solid-phase micro extraction coupled with gas chromatography–mass spectrometry (GC-MS) technique. To implement our proposed method, an electronic nose equipped with TGS, MQ, and MP sensor arrays is developed to analyze and capture the distinctions existing in the chemical compositions of naturally and artificially ripened fruits using calcium carbide. Based on our empirical analysis, naturally ripened bananas exhibit higher concentrations of esters and long-chain hydrocarbon compounds resulting in their sweet and fruity aroma. Conversely, calcium carbide based artificially ripened fruits characterize higher amounts of acetylene (18.95%), ethylene (1.99%), causing physiological stress and harmful to health. Moreover, the classification is supported with a multivariate analysis using Principal Component Analysis (PCA), which accounted for 87.8% of the total variance, whereas further validation of chemical fingerprints of each ripening method is performed using partial least squares discriminant analysis. This proof-of-concept cross-validated exploratory chemometric analysis using modest sample size demonstrated moderate correlation between GC-MS-derived VOC profiles and E-nose sensor responses (R² = 0.80), indicating the feasibility of large-scale sensor-assisted differentiation of ripening methods under controlled experimental conditions.

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Publication Details

Journal
Scientific Reports
Published
2026-08-27
DOI
https://doi.org/10.1038/s41598-026-65350-6
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
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Exploratory VOC profiling and chemometric differentiation of naturally and calcium carbide ripened bananas using GC-MS and electronic nose analysis

Lakshmi Divya Kalidindi, John Panneerselvam, Suresh Kumar Paramasivam, Vijaya Baskar V
Scientific Reports
Advanced Chemical Sensor Technologies
article

Exploratory VOC profiling and chemometric differentiation of naturally and calcium carbide ripened bananas using GC-MS and electronic nose analysis

Lakshmi Divya Kalidindi, John Panneerselvam, Suresh Kumar Paramasivam, Vijaya Baskar V
article en

Abstract

Abstract In the world of rapid technological changes, artificially induced methods are often used to accelerate the ripening process particularly in banana fruits for more profit, despite quality and safety concerns. This study highlights noticeable differences in the chemical composition and quality of ‘Karpuravalli’ ,Pisang Awak type, ABB bananas that are ripened naturally and those subjected to calcium carbide during ripening. With the rationale of classifying naturally and calcium carbide treated banana fruits, this paper proposes a novel smart sensory method using headspace solid-phase micro extraction coupled with gas chromatography–mass spectrometry (GC-MS) technique. To implement our proposed method, an electronic nose equipped with TGS, MQ, and MP sensor arrays is developed to analyze and capture the distinctions existing in the chemical compositions of naturally and artificially ripened fruits using calcium carbide. Based on our empirical analysis, naturally ripened bananas exhibit higher concentrations of esters and long-chain hydrocarbon compounds resulting in their sweet and fruity aroma. Conversely, calcium carbide based artificially ripened fruits characterize higher amounts of acetylene (18.95%), ethylene (1.99%), causing physiological stress and harmful to health. Moreover, the classification is supported with a multivariate analysis using Principal Component Analysis (PCA), which accounted for 87.8% of the total variance, whereas further validation of chemical fingerprints of each ripening method is performed using partial least squares discriminant analysis. This proof-of-concept cross-validated exploratory chemometric analysis using modest sample size demonstrated moderate correlation between GC-MS-derived VOC profiles and E-nose sensor responses (R² = 0.80), indicating the feasibility of large-scale sensor-assisted differentiation of ripening methods under controlled experimental conditions.

Scientific Reports
University of Exeter (GB), National Research Centre for Banana (IN), Sathyabama Institute of Science and Technology (IN)
Reduced inequalities, Peace, Justice and strong institutions
Openalex Percentile: Top 19%
Advanced Chemical Sensor Technologies
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