###### Abstract  
Weat 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 a gluten content (r = 0.74, \(p\) = 0.05), index 4 with kernel test weight (r = 0.84, \(p\) = 0.01), index 3 with a titllering 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.  
kernel symmetry; plant vegetation index; targeted selection; wheat breeding +
Footnote †: journal: applied sciences  
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Footnote †: journal: applied sciences  
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Footnote 0: _Copyright_ © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/))).
It is known that wheat ears show heterogeneity in the number of grains in an ear, as well as in the size of grains, for example, the first-order grains in a simple ear are often larger than the upper-order grains [12; 13]. The degree and rate of grain filling in each simple spikelet also depend on its location in the ear [14]. These features of wheat ear development affect the total grain weight in the ear, potential yield, and protein content of the grains [11; 15; 16].  
To improve wheat quality and processing efficiency, it is necessary to carry out selection that also focuses on uniformity and a more rounded grain shape [17; 18]. This can be achieved by developing and implementing shape analysis indices. Accordingly, the purpose of our work is to evaluate promising lines (six years of cultivation) of _Tritcium aestivum_ L. for grain shape uniformity, to check the relationship of grain morphological identification indices with economically valuable traits of wheat.