A review: milk spoilage and staleness detection approaches, technique, and technology trends

Hashim, Nik Mohd Zarifie and Mohd Yusoff, Salizawati and Jaafar, Anuar and Musa, Muhammad Muhayudeen and Sahaimi, Sazly Azizuddin and Abd Karim, Mohd Khairuddin and Mat Noor, Nur Anis Izzati (2022) A review: milk spoilage and staleness detection approaches, technique, and technology trends. International Journal of Scientific and Research Publications, 12 (4). pp. 130-135. ISSN 2250-3153

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Abstract

Milk is one of the primary food nutrition consumed by almost all countries globally. The milk is commonly packed with several containers such as carton, can, glass bottle, and pet bottle. The milk, however, has limited time for the buyer to consume it, as it has an expiring date. The expired date could be unclear and uncertain as the milk could be spoiled by itself according to how we kept it after the first container was opened. To encounter the milk spoilage and staleness problems, many research works were proposed from 1949 until recent for having a sound system on detecting the milk. Since this food safety and quality is one of the crucial areas, this paper analyzes the trends and approaches towards milk spoilage and staleness detection systematically. The category of the detection system, sensor technology, ingredient technology, image processing technique, and deep learning technique will be discussed technically. The paper also provides a brief comment and idea on the existing methods conducted by the previous researcher in their work. Finally, this paper will conclude the milk spoilage and staleness detection system trends and predict what could happen in a few years facing the industrial revolution 4.0.

Item Type:	Article
Uncontrolled Keywords:	Deep learning, Food safety and quality, Image processing, Milk staleness, pH, Sensors
Divisions:	Faculty of Electronics and Computer Engineering
Depositing User:	mr eiisaa ahyead
Date Deposited:	28 Feb 2023 08:02
Last Modified:	28 Feb 2023 08:02
URI:	http://eprints.utem.edu.my/id/eprint/26477
Statistic Details:	View Download Statistic

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