Graphical evaluation of combining ability for root and sugar yield, quality traits, and rhizomania resistance in sugar beet (Beta vulgaris L.) lines using line× tester design

Document Type : Scientific - Research

Authors

1 Associate Professor of Sugar Beet Seed Institute (SBSI) - Associate professor of Sugar Beet Seed Institute (SBSI), Agricultural Research, Education, and Extension Organization (AREEO), Karaj, Iran.

2 Assitant Professor, Sugar Beet Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran

3 Associate Professor, Mashhad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Khorasan Razavi, Iran

4 Shiraz Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Fars, Iran

10.22092/jsb.2026.371078.1399

Abstract

Introduction
Sugar beet plays a vital role in meeting the global sugar demand. Breeding this plant has always faced several challenges. On the one hand, the strong negative correlation between root yield and sugar content makes it difficult to simultaneously improve these traits, and on the other hand, biological stresses such as rhizomania threaten production sustainability; therefore, it is essential to develop an efficient breeding approach that can identify superior parents for the production of resistant and high-yielding hybrids. In this regard, success in breeding programs requires a detailed understanding of the genetic basis of the traits. The line× tester mating design is one of the most common methods for estimating these parameters. However, the traditional line× tester analysis method has some limitations. To overcome these challenges, the use of graphical multivariate methods such as GGE Biplot can be useful. Therefore, in the present study, the genetic potential of new sugar beet lines was evaluated, the combining ability of lines for quantitative and qualitative performance and resistance to rhizomania disease were determined, and superior hybrids were identified using a comprehensive graphical analysis approach.
Materials and Methods
The plant material used in this study was a selected collection of genetic resources of the Sugar Beet Seed Institute. This collection included 19 pollinating lines of the S1 generation with favorable performance potential as lines and 5 cytoplasmic male sterile (CMS) lines as testers, all of which had resistance to rhizomania in their genetic background. In order to produce the experimental population, a line× tester crossing design was used. In the crossing blocks, each maternal line was grown in the central rows and its specific paternal lines in two adjacent rows to ensure controlled and maximum pollination. At the end of the season, seeds from the maternal lines were harvested separately, thus producing 95 F1 hybrids for further evaluation. The evaluation experiments of the produced hybrids were conducted in six agricultural research stations including Karaj, Mashhad, Miandoab, Shiraz, Kermanshah and Hamedan. The planting operations were carried out in all regions in 2023. At each station, 95 hybrids along with four commercial control varieties were planted in five incomplete blocks in the form of an augmented design. Considering the implementation of the experiment in the form of an augmented design, first the raw data of root yield, sugar content and sugar yield of each hybrid in each environment were adjusted separately using control varieties to eliminate the heterogeneous effects of blocks in each location. Then, to eliminate environmental error and achieve an accurate estimate of the genetic potential of hybrids, a linear mixed model was used. Then, the adjusted data matrix consisting of 19 lines in 5 testers was used as the basis for graphical analysis.
Results and discussion
The results of the graphical analysis revealed distinct heterotic patterns of lines for root yield and sugar yield traits. For root yield, line L03 was the best combiner for testers T01, T02, and T03, while line L17 was the best combiner for testers T04 and T05. Regarding to sugar content, line L09 showed the highest combining ability with tester T03, and line L03 exhibited the best performance with four testers T01, T02, T04, and T05. For sugar yield, line× tester interaction pattern indicated that lines L03, L05, and L18 shoed a good combination with testers T01, T02, T04, and T05, whereas lines L09 and L10 displayed highest specific combining ability (SCA) with tester T03. Furthermore, in the overall evaluation, lines L03 and L05 possessed the highest general combining ability (GCA). In case of Rhizomania resistance, crosses of line L09 with tester T03, line L14 with testers T02 and T05, line L13 with tester T04 and line L15 with tester T01 were identified as the best combination of resistance based on specific combining ability (SCA). The results demonstrated that lines L03 and L05 have significant potential for use in breeding programs due to their high GCA.
Conclusion
The present study was conducted using a graphical analysis approach on data obtained from the line × tester design, and its results clearly showed that the genetic control of root yield, sugar content, and sugar yield is a function of both additive and non-additive effects of genes, but the contribution and pattern of these effects differ depending on the type of trait. Regarding functional traits, identifying distinct heterotic groups between testers and lines allows planning for crosses. Lines L03 and L05, with high GCA for sugar yield, are suitable candidates for population improvement programs. In contrast, line L09 has good potential for heterosis exploitation due to its high SCA. In the field of rhizomania resistance, lines L09 in crosses with tester T03, L14 in crosses with testers T02 and T05, L13 in crosses with tester T04 and L15 in crosses with tester T01 were the best sources of resistance. The identification of stable lines such as L18 along with SCA lines such as L14 suggests the use of stable sources to stabilize resistance and the use of dedicated sources to achieve high levels of resistance through gene pyramiding.

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