Development of mathematical model for prediction of adulteration levels of cow ghee with vegetable fat using image analysis.

The present study was undertaken to develop a protocol for acquisition and analysis of images of ghee samples to derive mathematical parameters related to adulteration of cow ghee with vegetable fat and to develop a model to predict the adulteration levels. The images acquired using a flatbed scanner were quantified in terms of their pixel intensity, colour, morphological, textural and skeleton parameters using ImageJ software. The selected parameters were measured for images of pure cow ghee and compared with that obtained for ghee adulterated with 5%, 10%, 15% and 20% vegetable fat. The parameters were assessed for their ability to detect the fixed adulteration levels on a discrete scale was assessed using discriminant analysis and the adulteration levels of the samples were correctly classified to the extent of 92.2%. An equation for predicting adulteration levels on a continuous scale using regression analysis (adjusted R 2 value 0.94) was developed, tested and further validated using a fresh data set including a commercially popular market sample of ghee giving a good fit (R 2 value of 0.85).

Physico-chemical and textural properties of Santra burfi as influenced by orange pulp content.

The burfi prepared with addition of orange pulp in sweetened khoa is popularly known as Santra burfi in Maharashtra and it has great commercial potential owing to its typical taste. The present investigation was carried out with a view to generate technological data, which is requisite in product standardization and mechanization. The santra burfi was prepared by varying the rates of orange pulp addition and was tested for various textural properties such as hardness, cohesiveness, gumminess, chewiness, adhesiveness and springiness with TA-XT2i Texture Analyzer using two-bite compression. The data of product composition and quantified properties were analyzed using correlation and regression techniques. The hardness was found to have positive correlation with proteins, fat and ash content while the moisture and level of orange pulp had negative correlation. Similar trends were observed for springiness, gumminess, chewiness and cohesiveness with the exception of ash. On the contrary, the mean adhesiveness showed negative correlation with protein, fat and ash content and shown positive correlation with moisture content and level of orange pulp. The regression equations were also fitted for explaining the interrelationships between the textural properties as functions of product composition.