Comparative Analysis of RGB and Hyperspectral Imaging for Evaluating Quality Parameters of Glutinous Rice during Storage

DOI

10.2991/978-94-6463-854-7_5How to use a DOI?

Keywords

Glutinous Rice; RGB Imaging; Hyperspectral Imaging; Moisture Content; Machine Learning

Abstract

Monitoring the quality of stored glutinous rice (GR) is crucial for ensuring its shelf life and nutritional value. This study explores the potential of using RGB imaging as a simpler, more accessible alternative to hyperspectral imaging (HSI) for assessing key quality parameters, such as moisture content (MC) and water absorption capacity (WAC), under various storage conditions. GR samples were stored at -10℃, 6℃, and ~26℃, and their quality was monitored using both imaging techniques. RGB analysis showed that colder storage temperatures preserved the colour stability of GR, while HSI data revealed significant reflectance changes related to grain composition. Machine learning models trained on both RGB and HSI data demonstrated high accuracy in predicting MC and WAC. The findings suggest that RGB imaging could serve as an efficient and cost-effective method for routine monitoring of rice quality, while HSI remains valuable for more detailed analyses. This research contributes to the development of practical tools for better managing rice storage and quality, benefiting both producers and consumers.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Abhishek Dasore
AU  - Norhashila Hashim
AU  - Rosnah Shamsudin
AU  - Hasfalina Che Man
AU  - Maimunah Mohd Ali
AU  - Opeyemi Micheal Ageh
PY  - 2025
DA  - 2025/11/11
TI  - Comparative Analysis of RGB and Hyperspectral Imaging for Evaluating Quality Parameters of Glutinous Rice during Storage
BT  - Proceedings of the 2024 Brawijaya International Conference (BIC 2024)
PB  - Atlantis Press
SP  - 46
EP  - 58
SN  - 3091-4442
UR  - https://doi.org/10.2991/978-94-6463-854-7_5
DO  - 10.2991/978-94-6463-854-7_5
ID  - Dasore2025
ER  -