APPLICATION OF DISCRIMINANT ANALYSIS IN THE CHARACTERIZATION OF PHYSICOCHEMICAL DATA OF BUFFALO MILK
Journal Title: Annals. Food Science and Technology - Year 2011, Vol 12, Issue 1
Abstract
Milk is a very important food. Physical and chemical quality of milk is affected by addition of water and ice. Milk quality monitoring program that provides a representative and reliable estimation of the quality of milk has become an important necessity. A comprehensive monitoring program provides large meaningless data. In this research work discriminant analysis (DA) was used to analyze the physicochemical data of milk of buffalo’s dairy farms of Gujranwala, Pakistan. Parameters were divided into three groups, physical (pH, Electrical conductivity, specific gravity, titratable acidity, total solid), chemical (Ash, Fat, Protein, Lactose) and minerals (Na, Ca, Mg, K, Fe). Discriminant analysis indicates that only 57.1% of parameters were correctly classified. This is due the overlapping nature of parameters. Discriminant analysis (DA) identified ten significant parameters (Ca, Na, Mg, Fe, titratable acidity (TTA), Fat, specific gravity (SG), Ash and K which discriminate (distinguish) the milk quality of seven dairy farms. Discriminant analysis classified seven dairy farms 100.0% correctly. The result of classification shows that there are significant differences between the quality of milk of seven dairy farms, which are expressed by six discriminate functions. This study illustrates the benefit of discriminant analysis for interpreting complex data sets in the analysis of spatial variations in milk quality, and to plan for future studies.
Authors and Affiliations
Asif Mahmood, Sumaira Naeem
Keywords
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