Abstract
Triticale, a hybrid of wheat (Triticum aestivum) and rye (Secale cereale), is a promising cereal crop due to its high protein content, balanced amino acid composition, and adaptability to diverse environmental conditions. However, the strong adhesion between the bran layers and endosperm complicates flour extraction and requires optimization of milling parameters. To optimize the technological parameters of a reduced milling scheme for the Kazakhstani triticale varieties “Kozha”, “Taza”, and “Asiada” in order to maximize flour yield while maintaining ash content within regulatory limits. Experimental milling was performed using a LabMill Chopin laboratory mill. A central composite experimental design and response surface methodology were applied to determine the optimal extraction rates of the first and second break systems. Second-order regression models were developed to describe the relationship between the integral efficiency coefficient (K), flour yield, and ash content. The developed models demonstrated high predictive accuracy (R² > 0.95). The optimal milling conditions were x₁ = 9.58% and x₂ = 10.23% for “Kozha”, x₁ = 7.82% and x₂ = 14.15% for “Taza”, and x₁ = 7.24% and x₂ = 14.91% for “Asiada”. Under these conditions, flour yield ranged from 70.1% to 75.9% with ash content between 0.70% and 0.72%, indicating stable technological performance. The study establishes, for the first time, optimized reduced-milling conditions for Kazakh-bred triticale varieties and develops regression models capable of predicting milling efficiency, providing practical recommendations for improving flour production without additional equipment modernization.