Predicting the quality attributes related to geographical growing regions in red-fleshed kiwifruit by data fusion of electronic nose and computer vision systems

Predicting the quality attributes related to geographical growing regions in red-fleshed kiwifruit by data fusion of electronic nose and computer vision systems

Abstract The ability of a data fusion system composed of a computer vision system (CVS) and an electronic nose (e-nose) was evaluated to predict key physiochemical attributes and distinguish red-fleshed kiwifruit produced in three distinct regions in northern Iran. Color and morphological features f...

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Bibliographic Details
Main Authors: Mojdeh Asadi, Mahmood Ghasemnezhad, Adel Bakhshipour, Jamal-Ali Olfati, Mohammad Hossein Mirjalili
Format: Article
Language:English
Published: BMC 2024-01-01
Series:BMC Plant Biology
Subjects:
Image processing
Machine learning
Origin
Physicochemical attributes
Volatile Organic compounds
Online Access:https://doi.org/10.1186/s12870-023-04661-6

Internet

https://doi.org/10.1186/s12870-023-04661-6

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