Abstract
Fish freshness detector (FFD) currently plays an important role in assessing fish for consumers. There are FFDs available out there in the market, but they are not conveniently accessible by common users. Therefore, it is important to design an FFD that can deliver accurateness which can be adopted for its users to make instant purchasing decisions. To achieve that, this paper proposed FFD model based on fuzzy logic as system, while Rastrelliger kanagurta and Umbrina roncador as fish samples species for evaluation. The proposed model consists of two evaluation parts, sensory quality index method (QIM) assessment and digital image processing. Both were only focusing on the fish eye, which a sensory assessment for QIM and the redness value (RV) for the image processing. Based on distinct species evaluation against days of storage and condition after death, the eye sensory QIM for both species starts to change from clear to dull throughout 12 days in ice storage. R. kanagurta showed a rapid rate of deterioration compared to U. roncador. The RV distribution recorded ranges between 81 and 129 for both species. Finally, a fish freshness indicator as input setting in fuzzy logic inference system based on sensory QIM and RV were successfully developed in this pilot test.
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Abd.Aziz, K.N., Anthonysamy, S.I., Zainol, Z.E., Roslani, M.A., Kamaruddin, S.A. (2020). Fish Freshness Detector Using Sensory Quality Index Method and Digital Image Processing Evaluation. In: Alias, N., Yusof, R. (eds) Charting the Sustainable Future of ASEAN in Science and Technology . Springer, Singapore. https://doi.org/10.1007/978-981-15-3434-8_2
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DOI: https://doi.org/10.1007/978-981-15-3434-8_2
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