Improvement of the Grain Quality Assessment System in Context of the North Kazakhstan Region

Abstract

Nowadays, the manufacturing of pasta products using flour from soft wheat has become a common trend. In connection with the digitalization of production, a special place in producing high-quality pasta products is occupied by improving methods of estimating and forecasting the quality of wheat varieties. Recent studies do not systematize recommendations for determining wheat quality depending on its genotype and the influence of agroecological factors. Existing methods for determining wheat quality require long-term research experience. Simultaneously, the quality of the products obtained in the laboratory does not correspond to natural conditions. Therefore, it is necessary to conduct statistical and factor analysis to determine the product’s quality. This paper explores and demonstrates the possibilities of statistical methods for analyzing the use of new wheat varieties in the manufacturing of pasta products. The research developed and analyzed regression and factor models of the use of new soft wheat in the manufacturing of pasta products on the example of the North Kazakhstan Region. The authors developed the regression equations for primary factors, key components, and panel data to identify the strength of the relationships between different factors and indicators of wheat quality.