Composition of milk: A comparative analysis on goat, cow and buffalo milk from Amreli region of Gujarat

Abstract

The article describes an exploration into the components of milk and its different characteristics across species found in the Amreli region of Saurashtra. Using MilkoScan™ (indiFOSS) and EUTECH PH meter, the study investigated milk constituents and other properties. Following the analysis of all samples, Principal component analysis (PCA) was employed to examine how the elements in milk relate to each other. This analysis showcased a significant (P<0.05) difference in the overall fat, protein and lactose content of goat milk (2.97%, 3.59% and 4.25%) as opposed to cow (5.97%, 3.98% and 4.72%) and buffalo (6.36%, 3.99% and 4.74%) milk, revealing substantially lower values in goat milk. The calculated calorific value of buffalo milk (92.17 Kcal) and cow milk (88.58 Kcal) was significantly (P<0.05) higher as compared to goat milk (58.13 Kcal). However, no statistically significant (P>0.05) distinctions were identified in the mean ash content across the entire sample set. Interestingly, the electrical conductivity (EC) of goat milk surpasses that of cow milk and buffalo milk. In the Principal Component Analysis (PCA), it was revealed that PC1 explained 63.1% and PC2 explained 17.0% of the total variance. The PCA analysis revealed a positive correlation among %ash, %protein, %SNF, %lactose and Freezing point depression (FPD) across different milk samples. In contrast, properties like milk conductivity showed a negative correlation with redox potential and pH. Highlights  The study encompassed the procurement of milk samples from multiple species, and these samples were subjected to analysis employing the MilkoScan™ (indiFOSS) instrument and the EUTECH PH meter.  The study indicated the variations in the composition of goat milk, cow milk and buffalo milk. Each type of milk exhibits distinct characteristics in terms of fat content, SNF, protein, lactose, calorific value, FP, pH, electrical conductivity, Eh and specific gravity.  The application of Principal component analysis (PCA) in this study revealed a direct relationship: an increase in soluble constituents such as salt and lactose in milk samples corresponded to higher Freezing point depression (FPD). Moreover, milk conductivity was adversely affected by the quantity of fat present, while the Eh exhibited an increase alongside higher percentages of fat.  The information provided in this analysis can aid in making informed choices about milk consumption based on individual preferences and nutritional requirements.