Introduction

Sugar beet is a crop of strategic importance for global food security, serving as the second major source of the world's sugar. Beyond its role in food production, sugar beet is increasingly recognized as a key feedstock for the bio-based economy, particularly for biofuel production. However, maximizing its yield potential is consistently challenged by various biotic stresses. In many production regions, soil-borne diseases such as Rhizomania, Rhizoctonia root rot, and the beet cyst nematode are major limiting factors that cause substantial economic losses by reducing both root yield and quality. The development of high-yielding and disease-resistant hybrids is the most effective and sustainable strategy to mitigate these threats. A prerequisite for a successful hybrid breeding program is a thorough understanding of the genetic architecture of key traits, including the nature of gene action and the combining ability of parental lines. This study was therefore designed to evaluate the general (GCA) and specific (SCA) combining abilities, estimate genetic parameters, and determine the predominant gene actions controlling root yield, sugar content, and sugar yield in a newly developed set of sugar beet germplasm.



Materials and Methods

The genetic materials for this study consisted of five cytoplasmic male sterile (CMS) maternal lines (testers) and nineteen pollinator lines (lines). These parental lines were crossed according to a line × tester mating design to produce 95 F1 hybrids. The resulting hybrids, along with several commercial check varieties, were evaluated in a multi-environment trial across six diverse locations in Iran. An augmented experimental design was employed at each location. Data were collected for key agronomic and quality traits, including root yield (t·ha⁻¹), sugar content (%), and sugar yield (t·ha⁻¹). Statistical analysis was performed using R software. Raw data were first adjusted based on the performance of the replicated checks within each block to account for field heterogeneity. Subsequently, a combined analysis of variance (ANOVA) was conducted on the adjusted data to assess the significance of genotypes, environments, and their interaction. Finally, a combined line × tester analysis was performed to partition the genetic variance into components attributable to GCA (lines and testers) and SCA (line × tester interaction) and their interactions with the environment.



Results and Discussion

The combined ANOVA revealed highly significant differences (P<0.01) among the genotypes for all studied traits, indicating the presence of substantial genetic variability created through the hybridization program. The effects of environment and the genotype by environment (G×E) interaction were also highly significant, highlighting the differential performance of hybrids across diverse agro-ecological conditions and underscoring the necessity of multi-location testing. The line × tester analysis provided crucial insights into the genetic control of the traits. For root yield, both GCA (mainly from pollinators) and SCA effects were significant, suggesting that both additive and non-additive gene actions are important in its inheritance. In contrast, the genetic control of sugar content was predominantly governed by non-additive gene action, as evidenced by the highly significant SCA effects. The most critical finding was related to sugar yield, the primary economic trait, where the GCA of the pollinator lines was the main and most significant source of variation. This strongly indicates that additive gene action is the key driver for improving sugar yield, making the selection of superior pollinator parents a highly effective breeding strategy. The pollinator line S1-960104 was identified as an outstanding general combiner, exhibiting significant positive GCA effects for all three traits. The hybrid S1-960104 × 201-25/301-28 showed the highest significant positive SCA effect for both root yield and sugar yield, marking it as the most promising hybrid combination for commercial consideration.



Conclusion

This research successfully elucidated the genetic basis of key performance traits in a novel sugar beet germplasm. It was concluded that an efficient breeding strategy for this material should follow a two-stage approach: first, selecting superior pollinator parents based on high GCA for sugar yield, and second, evaluating their specific cross-combinations to identify elite hybrids that capitalize on favorable non-additive effects (SCA). The pollinator S1-960104 and the hybrid S1-960104 × 201-25/301-28 were identified as exceptionally valuable genetic resources. The significant G×E interaction further emphasizes that future breeding efforts should focus on developing hybrids with either broad or specific adaptation to target environments.