IMPLEMENTING NEW PREDICTIVE FUNCTIONAL MODEL FOR MILK FAT VALUE IN MACEDONIAN WHITE BRINED CHEESE PRODUCTION

Abstract

By using a combination of statistical analysis and machine learning techniques, the model enables a more precise and real-time prediction of milk fat content, addressing challenges related to seasonal variations in milk composition and other unpredictable factors in dairy production. According to the Codex Alimentarius (Codex Stan 208-1999), white brined cheese belongs to the category of "Cheese in Brine." The main objectives are as follows: to analyze the dynamics of milk fat content during the ripening process of cheese produced under different production conditions and to develop and validate a predictive functional model that accurately estimates milk fat levels based on critical factors, including initial milk composition, processing parameters, and technological conditions. After 20 days of ripening, the milk fat content ranged between 22.88±0.05% for Variant C and 24.8±0.10% for Variant D. As ripening progressed, on the 30th day, a noticeable increase in fat content was recorded across all variants, with values ranging from 23.0±0.10% to 25.07±0.05%.