Evaluation of resistance and determination of stability of different sugar beet (Beta vulgaris L.) genotypes in rhizomania‐infected conditions

Abstract

Plant diseases are considered one of the main factors reducing yield and quality of crops, which are constantly developing and creating more virulent races and cause the resistance of more genes to break. Identifying resistance sources and including them in breeding programs will improve resistant genotypes. Rhizomania is the most common, widespread, and devastating disease of sugar beet in Iran and worldwide.Breeding genotypes with disease resistance genes is one of the most important ways to deal with this destructive disease. Twenty sugar beet genotypes along with five controls were evaluated in a randomized complete block design with four replications in rhizomania-infected conditions in four regions of Mashhad, Shiraz, Miandoab, and Hamedan for 2 years. The results of genotypic reaction to rhizomania showed that the genotypes with resistance reaction were much more frequent than those with susceptibility reaction. The analysis of multiplicative effects of the AMMI model showed that the first six components were significant and explained 98.80% of the interaction variations. The biplot obtained from the mean white sugar yield and the first interaction principal component confirmed the superiority of the RM5 genotype due to its high white sugar yield and stability in infected conditions. The results obtained from the first three principal components biplot showed that the RM9 genotype with a mean white sugar yield of 11.91 t. ha −1 was a genotype with vast general stability in all disease-infected environments. Based on the results of the MTSI index, RM3, RM17, RM9, RM13, and RM15 are introduced as stable genotypes under rhizomaniainfected conditions. In conclusion, it seems that the studied genotypes have valuable and useful genes inherited from their parents to deal with rhizomania disease.Applying these genotypes in sugar beet breeding programs can effectively prevent the threat of rhizomania.

Stability analysis and selection of sugar beet (Beta vulgaris L.) genotypes using AMMI, BLUP, GGE biplot and MTSI

“…In another study using AMMI model, the first IPC was significant and explained about 63% of GEI variation 34 . Rajabi, et al 40 also reported the significant effect of first six IPCs explaining 98.80% of the total GEI variations. The biplot of mean performance versus WAAS which is called the WAAS biplot (Figure 2), unlike AMMI model which considers only the first IPC, shows stability based on all scores of the IPCs.…”

“…Sharifi, et al50 used the MTSI in the evaluation of yield and other agricultural traits in a set of rice genotypes and showed that this index is able to identify superior genotypes in terms of yield stability and other agricultural traits. Based on the MTSI results, Rajabi, et al40 introduced five sugar beet genotypes as stable genotypes under field condition infected with rhizomania disease. These results were consistent with the findings obtained from this study regarding the efficiency of MTSI in identifying superior genotypes.…”

Evaluation of resistance and stability of new sugar beet hybrids in field conditions infected with rhizoctonia root and crown rot disease

“…In a study conducted using the AMMI, the IPC1 was significant and explained about 63% of the data variation (16). In Rajabi, Ahmadi (18) study, the first six IPCs had a significant effect and explained 98.80% of the total variations in GEI.…”

“…Methods for the analysis of phenotypic stability are constantly evolving to provide more precision in the assessment of genotypes and the study of environmental interaction components. In phenotypic stability analysis, a combination of several stability analysis methods is often used instead of relying on a single analysis (16)(17)(18)(19).…”

Selection of Superior sugar beet (Beta vulgaris L.) genotypes using Selection Indexes of multi-trai under rhizomania-contaminated areas

“…Therefore, identifying and managing these effects is essential for breeding programs (El-Soda et al 2021). Previous studies mentioned the interaction between genotype and environment as significant in evaluating sugar beet genotypes (Ebmeyer et al 2021;Taleghan et al 2023;Rajabi et al 2022) The analysis revealed that the significant main components for the examined traits ranged from 4 to 5. The first four components were significant (p≤ 0.01), explaining 88% of RY's GEI variation.…”