ارزیابی مقاومت و شناسایی لاین‌های گرده افشان جدید چغندرقند مقاوم به پوسیدگی ریزوکتونیایی ریشه و طوقه

Extended Abstract
Introduction
Rhizoctonia root and crown rot of sugar beet is one of the most important diseases of sugar beet, which is present in most beet growing regions of the country. The soil-borne fungus Rhizoctonia solani causes root and crown rot, significantly reducing the economic yield of sugar beet. Control of rhizoctonia root and crown rot in sugar beet using crop rotation and fungicide application has reduced the disease damage, however, an unacceptable and significant amount of rot still occurs in the fields. The development of rhizoctonia-resistant cultivars has been identified as the most practical and economical approach, and in some cases, recommended as the only effective way against this disease. On the other hand, the presence of resistance in the sugar beet pollinator plays a significant role in the development of resistant hybrids. One of the steps in the development of a rhizoctonia-resistant hybrid is to identify the source of resistance in the genetic material.
Materials and Methods
In order to evaluate the resistant pollinator lines, 27 pollinator lines along with two resistant checks (FC 709-2 and Novodoro) and one susceptible check (191) were evaluated for rhizoctonia resistance under artificial inoculation with Rh133 isolate based on randomized complete block design with three replications under micro-plot condition in Hamedan in 2022. Eighty-five days after planting, artificial infection of sugar beet plants with rhizoctonia fungus was carried out. For this purpose, five corn seeds infected with Rh133 isolate of rhizoctonia solani AG 2-2 were placed nearby crown area of the roots in 5 cm depth, and plants were immediately covered with soil and irrigated. To ensure adequate spreading of the inoculum, plants were irrigated every 3-days for two weeks and then once a week to maintain moisture.
Roots were harvested 22 days after the artificial inoculation, and the root disease index was assessed using 1 to 9 scale .The disease index for each line was calculated by multiplying the score and the number of roots associated with that score, then dividing it by the total number of roots in that plot. The harvest index was obtained by dividing the number of roots with 1-3 score by the number of roots with 1-9 score in each plot. To ensure accurate test results, several random samples of infected root tissue were selected to isolate and identify the fungus causing the rot. The Selection Index of Ideal Genotype (SIIG) method was utilized to examine genetic diversity while integrating traits such as root number, disease index, and harvest index. To classify genotypes, cluster analysis (using Euclidean distance by Single method and considering 95% similarity) was used based on the disease index, harvest index and SIIG index of each line and rhizoctonia resistant lines were identified. Factor analysis was also performed based on principal component analysis. SAS v.9.1, R v.4.2.2 and Minitab v.16 software were used to analyze the data and drawing graphs.
Results and Discussion
The culture results obtained from the laboratory indicated that the disease's causative agent was the rhizoctonia solani fungus in tested samples. Based on the results of the analysis of variance, the differences between the sugar beet pollinator lines were significant in terms of root number (df=23, F=2.51, p=0.0039), disease index (df=23, F=2.69, p=0.0021), and harvest index (df=23, F=2.29, p=0.0082). In this experiment, the average number of roots evaluated for each genotype (roots with 1-9 scores) was 15.88 roots. Therefore, the number of roots required to evaluate and estimate the disease index and harvest index was sufficient and appropriate. The lowest and the highest number of roots was observed in line No.7 (S1–140292) with 9 roots and line No.11 (S1–140302) with 22 roots, respectively. The average disease index of the pollinator lines was 5.03, which indicated the effectiveness of the pathogen inoculation, as well as soil contamination in the experimental environment, along with the favorable environmental conditions (temperature and humidity) for the development of the pathogen. The disease index of resistant controls in this experiment was 3.78 and 3.35 for FC 709-2 and Novodoro, respectively, and 5.91 for the susceptible control. Among the lines studied, the lowest disease index (3.53) was observed in pollinator line No.1 (S1-140279), which was identified as the most resistant line among the pollinator lines. The results of the experiment showed that line No.1 (S1–140279) had the highest harvest index (59.02%) among the studied lines. Lines No.21 (S1–140321) and No.2 (S1–140282) were ranked in one group with harvest indices of 53.43 and 53.29%, respectively.
In this study, the minimum and maximum SIIG values ​​estimated for the studied pollinator lines were 0.914 for the resistant control Novodoro and 0.187 for pollinator lines No.8 (S1-140293) and No.13 (S1-140306), respectively. Lines No.2 (S1-140282), No.21 (S1-140321), No.1 (S1-140279), No.20 (S1-140316), No.5 (S1-140287) and No.10 (S1-140296) were the closest pollinators to the ideal pollinator line with values ​​of 0.812, 0.760, 0.755, 0.732, 0.709 and 0.704, respectively. Cluster analysis classified the studied lines into six groups, with the lines in the first cluster (lines No.1, No.2, and No.20) and the fourth cluster (lines No.5, No.9, No.10, and No.20) identified as the most resistant lines.
In factor analysis to evaluate the resistance of pollinated lines to rhizoctonia rot under micro-plot, two factors with eigenvalues ​​greater than one were selected. The first factor explained 72.05% and the second factor explained 26.05%, and in total, 98.10% of the total data variation. Factor analysis based on principal component analysis showed that the first factor explained the largest amount of data variation (72.05%) and had large and positive coefficients for the traits of harvest index and SIIG index and a negative and significant coefficient with the disease index. The second factor also explained 26.05% of the variation and had a positive and significant coefficient with the trait of number of roots. The results of the biplot graph, considering the first two components, showed that six pollinators, including lines No.1, No.2, No.20, No.21, No.10 and No.5, were in a suitable position in the biplot graph in terms of resistance indices. Results also showed that the six pollinators did not have a significant difference in terms of disease index compared with the resistant controls Novodoro and FC 709-2, and they can be introduced as resistant lines.   
Conclusion
In general, the pollinator lines No.1 (S1 – 140279), No.2 (S1 – 140282), No.5 (S1 – 140287), No.10 (S1 – 140296), No.20 (S1 – 140316) and No.21 (S1 – 140321), which were recognized as resistant lines can be suggested for future breeding programs.
Keywords: Artificial inoculation, Disease index, Pollinator, Rot disease.
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