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Computer Vision based Method to Detect Milk Adulteration with Water

Bezuayehu Gutema Asefa*

A rapid method based on digital image analysis and machine learning technique is proposed for the detection of milk adulteration with water. Several machine learning algorithms were compared, and SVM performed best with 89.48% of total accuracy and 95.10% precision. An increase in the classification performance was observed in extreme classes. Better quantitative determination of the added water was done using SVMR with R2 (CV) and R2 (P) of 0.65 and 0.71 respectively. The proposed technique can be used for the nondestructive determination of milk adulteration with water without the necessity of any additional reagent.

索引于

化学文摘社 (CAS)
谷歌学术
打开 J 门
学术钥匙
研究圣经
引用因子
宇宙IF
电子期刊图书馆
参考搜索
哈姆达大学
欧洲农业信息技术联合会 (EFITA)
学者指导
国际创新期刊影响因子(IIJIF)
国际组织研究所 (I2OR)
宇宙
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