COMPREHENSIVE ASSESSMENT OF QUALITY OF MILK AS A RAW MATERIAL OF FARM ANIMALS
Abstract
The issues of comprehensive (organoleptic and physical-and-chemical) assessment of quality
of milk obtained from various types of lactating farm animals are considered. Samples of milk of
Alpine goats, Ostfrisian sheep, white-and-black cows were chosen as objects of the research. Organoleptic
evaluation was carried out in two ways: with the help of expert tasters and using the
Voc-metr multi-sensor system called "electronic nose". Physical-and-chemical assessment was
based on the results of determining the chemical composition, as well as measuring the acidity,
density, viscosity, freezing temperature, dispersion of fat globules, and the presence of somatic
cells of milk samples. “Visual impressions” of smells of the objects under study are obtained. The
sample of cow's milk possessed the most intense smell (the area of “visual impression” was 24.64
c.u.), which was formed due to the presence of aldehydes, ketones, free amino acids and lowmolecular
nitrogen compounds in the gas phase of the milk. The results of the organoleptic evaluation,
obtained from professional tasters, are corresponding with the instrumental ones; this allows
us to recommend the multi-sensor system called “electronic nose” for implementation in order to
carry out assessment of quality of milk as raw material during its acceptance at milk-processing
plants. The results of assessing physical-and-chemical parameters of the quality of raw milk samples
show that they are within the optimal ranges established by regulatory documentation. Protein
content in sheep milk is 45 % higher compared to cow milk, and 37 % higher compared to goat
milk. It was determined that the minimal degree of dispersion of fat globules, which determines
milk’s availability, is contained in goat milk, which causes its wide use for child nutrition. The
“density” and “freezing point” indicators are indicators of the possible falsification of raw milk.
The obtained results of the abovementioned indicators' assessment prove the absence of falsifications
in the samples’ composition.
