Fakhrul Anwar, Nur Irdina and Za'bah, Nor Farahidah and Md Ralib @ Md Raghib, Aliza 'Aini (2024) Ripeness assessment and quality control of mango gold susu using an e-nose system. Asian Journal of Electrical and Electronic Engineering, 4 (2). pp. 35-42. E-ISSN 2785-8189
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Abstract
In this paper, the development and implementation of an electronic nose (e-nose) system utilizing the MQ sensor series from MOS-type gas sensors to classify mango gold susu ripeness is presented. The system's performance was enhanced through machine learning techniques, including Principal Component Analysis (PCA) for data dimensionality reduction and Support Vector Machine (SVM) for classification. The SVM classifier demonstrated high accuracy, particularly in identifying unripe and overripe mangoes, with accuracy scores of 1.00 and 0.99, respectively. A comprehensive database of volatile organic compound (VOC) profiles was established, leading to a precise prediction model for assessing the different stages of ripeness based on the mango’s VOC profile.
| Item Type: | Article (Journal) |
|---|---|
| Additional Information: | 5466/114717 |
| Uncontrolled Keywords: | e-nose, VOC, Support Vector Machine, Principal Component Analysis |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices |
| Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Engineering Kulliyyah of Engineering > Department of Electrical and Computer Engineering |
| Depositing User: | Dr. Nor Farahidah Za'bah |
| Date Deposited: | 30 Sep 2024 10:08 |
| Last Modified: | 30 Sep 2024 10:19 |
| URI: | http://irep.iium.edu.my/id/eprint/114717 |
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