ArticleFood science & nutrition2023
A data fusion approach for nondestructive tracking of the ripening process and quality attributes of green Hayward kiwifruit using artificial olfaction and proximal hyperspectral imaging techniques.
Article in Food science & nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Advances in Kiwifruit Postharvest Management: Convergence of Physiological Insights, Omics, and Nondestructive Technologies.Current issues in molecular biology · 2025Review
- Advances in predicting human olfactory perception: from data acquisition to computational models.RSC advances · 2025Review
- Transcriptome Analysis Unveils the Molecular Mechanisms of Ethylene-Induced Ready-to-Eat Kiwifruit-Picking Ripening.Foods (Basel, Switzerland) · 2025Article
- Automated detection of stale beef from electronic nose data.Food science & nutrition · 2024Article
- A data fusion approach for nondestructive tracking of the ripening process and quality attributes of green Hayward kiwifruit using artificial olfaction and proximal hyperspectral imaging techniques.Food science & nutrition · 2023Article
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Abstract
A data fusion strategy based on hyperspectral imaging (HSI) and electronic nose (e-nose) systems was developed in this study to inspect the postharvest ripening process of Hayward kiwifruit. The extracted features from the e-nose and HSI techniques, in single or combined mode, were used to develop machine learning algorithms. Performance evaluations proved that the fusion of olfactory and reflectance data improves the performance of discriminative and predictive algorithms. Accordingly, with high classification accuracies of 100% and 94.44% in the calibration and test stages, the data fusion-based support vector machine (SVM) outperformed the partial least square discriminant analysis (PLSDA) for discriminating the kiwifruit samples into eight classes based on storage time. Moreover, the data fusion-based support vector regression (SVR) was a better predictor than partial least squares regression (PLSR) for kiwifruit firmness, soluble solids content (SSC), and titratable acidity (TA) measures. The prediction
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