Detection and Quantification of Milk Adulteration by Laser Induced Instumentation
Lalita Moharkar, Suprava Patnaik
Abstract
Lalita Moharkar, Suprava Patnaik
Abstract
Tracing and detecting adulteration in milk is a challenging concern. Milk adulteration can lead to deterioration of dairy industry products and health risks for end users. The need of a reliable low cost adulteration detection methodology has remained an ever desired requirement, not only of the customers but also of food quality control organizations of various levels. In this paper, the design of a low cost instrumentation system to trace and quantify milk adulteration has been reported. This paper is based on the outcome of sensor technology combined with computational technology. It involves sensing of variation in laser diffraction corresponding to variation in particle density. The particle distributions in milk are nothing but the contributions from casein micelles and fat globules. The sensed data are computationally processed to calibrate and predict the percentage of water present in a given sample of milk.
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Tracing and detecting adulteration in milk is a challenging concern. Milk adulteration can lead to deterioration of dairy industry products and health risks for end users. The need of a reliable low cost adulteration detection methodology has remained an ever desired requirement, not only of the customers but also of food quality control organizations of various levels. In this paper, the design of a low cost instrumentation system to trace and quantify milk adulteration has been reported. This paper is based on the outcome of sensor technology combined with computational technology. It involves sensing of variation in laser diffraction corresponding to variation in particle density. The particle distributions in milk are nothing but the contributions from casein micelles and fat globules. The sensed data are computationally processed to calibrate and predict the percentage of water present in a given sample of milk.
Key concepts: Dairy industry, Globules of fat, Casein, Process engineering, Computer science, Instrumentation (computer programming), Micelle, Environmental science