Detecting Adulteration in Camel Milk Using Color Change Modeling by Image Processing and Mixture-process Variable Experiments

Nowadays, food ingredient fraud and economically motivated adulteration are emerging risks, being addition of low cost ingredients creates not only an economical problem but also a health risk for consumers. Due to the limitations of camel milk production and high economic value that has traditionally been done in the fraud. Therefore, rapid analysis methods has gained increased interested for analytical chemistry applications due the simplicity, low-cost, speed and a performance that is similar to those instruments normally found in the laboratory. The aim of this study was to detect fraud, adding water, caustic soda to camel milk with thermal process, color detector and color parameter modeling (L٭, a٭, b٭, DE, chroma Index, Hue angel and browning index) using mixture-process experiments. Due to the significant effects mentioned it can be concluded that to detect of adding cow milk to camel milk can be used heating a mixture and browning index. adding cow milk and water to camel milk can be detect by L٭, a٭, b٭, DE, hue angel and browning index also adding caustic soda to camel milk can be detect by L٭, a٭, b٭, DE, Chroma index, hue angel and browning index.