Can Kernel Uniformity Indices Be Used as Criteria for Variability Assessment of Wheat Breeding Lines?

Wheat is one of the main food crops, the value of which lies in the high content of protein and carbohydrates in the kernel. To improve the quality of kernel processing, it is desirable that all kernels are uniform in shape and quantitative parameters. However, the kernel technological properties are affected by agricultural technology, environmental conditions and genetic characteristics, for example, even within one ear; kernels vary in size and the degree of ripening. Therefore, the aim of this work is to test the relationship between the coefficients (indices) of kernel shape variability in winter wheat lines that were pre-selected in long-term competitive variety trials and to select the best variety accession for further targeted selection to improve the uniformity of kernels. This work examined seven lines and a control variety of winter wheat grown during 2022–2023. Sampling in the field experiment was carried out randomly. The variability of quantitative traits was assessed by the analysis of variance method. It is noted that symmetrical kernels are mainly characteristic of 188h, the intermediate position is occupied by Moskovskaya 56, 150h, 152h, 171h, 184h, 187h and variety sample 151h has clearly expressed asymmetry. Index 5 of the kernel cut has a strong correlation with gluten content (r = 0.74, p = 0.05), index 4 with kernel test weight (r = 0.84, p = 0.01), index 3 with a tillering coefficient (r = 0.83, p = 0.05) and index 1 with plant height (r = 0.81, p = 0.05). An inverse relationship was found for index 2 with kernel vitreousness (r = −0.74, p = 0.05). The kernel test weight has an inverse relationship with the grain area (r = −0.71, p = 0.05). Predictive regression equations on the relationship of plant height, tillering ratio, gluten content and indices are given. While limited by its one-year duration, this study reveals intriguing correlations between grain shape parameters and economically valuable traits in wheat, offering valuable insights for high-throughput phenotyping applications in rapidly advancing agricultural technologies. This article will be useful for breeding for kernel uniformity and, consequently, for increasing the kernels in the ear and the weight of 1000 seeds.