The conducted regression analysis allowed us to obtain the equation of multiple nonlinear regression, which reflects the dependence of the raw gluten content in wheat kernels (Y, %) on the protein content (X1 = Ntotal · 5.7, %) and 1000-kernel weight (X2, g): Y = -41.928 + 0.081Х1 2 + 2.548Х2 - 0.028Х2 2. In the presented equation, all quality indicators are given at 12% humidity. If protein content and/or 1000-kernel weight are determined for absolutely dry matter (a.d.m.), the developed

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... on to predict raw gluten content in wheat kernels is recalculated with the use of coefficients of 0.88 and 1.136, respectively. The purpose of the research is to identify the effectiveness of raw gluten content prediction in wheat kernels using the developed regression equation, which reflects its dependence on protein content and 1000-kernel weight. There have been developed and presented an algorithm and results of testing the predictive capabilities of the equation based on independent data. That is, using experimental data on protein and gluten content, and 1000-kernel weight obtained by other researchers in the experiments with different wheat varieties and in other soil and climatic conditions. The summarized experimental data of 124 Soviet, Russian and foreign literary references with a total number of observations n = 2485 on more than a hundred wheat varieties grown from 1959 to 2019 in various soil and climatic zones of the USSR, Russia and abroad have shown that the number of values beyond the limits regulated by GOST R 54478 - 2011 (± 2%) was 462 or 18.6% of the total number of observations. The accuracy of the raw gluten content prediction in wheat kernels was 81.4%. The developed equation can be used to predict raw gluten content in kernels of various winter and spring soft and durum wheat varieties.