Stability analysis through multiplicative interaction models among promising accessions of brassica rapa var yellow sarson prain

Abstract

ABSTRACT newlineThe present study entitled Stability Analysis through Multiplicative Interaction Models among promising accessions of Brassica rapa var. yellow sarson Prain was under taken with the objectives to estimate the selection parameters and character association among traits, path-coefficient analysis, assessment of genetic divergence using Mahalanobis D2 statistics, stability analysis of accessions using different methods of stability analysis and brief comparison between the methods of stability. Forty-one accessions of Brassica rapa var. yellow sarson along with 5 checks i.e., Pant Pili Sarson-1, YSH-0401, Pitambari, Pant Shweta and Binoy, constituted the experimental material, which was grown for three consecutive years i.e., 2018-19 (E1), 2019-20 (E2) and 2020-21 (E3). The accessions were evaluated in a randomised block design with three replications at Norman E. Borlaug Crop Research Centre, G. B. Pant University of Agriculture and Technology, Pantnagar. The data was analysed using appropriate statistical techniques. The results revealed that the mean squares among the genotypes for all the yield and yield attributing characters were highly significant in all the environments. The estimates of PCV and GCV were found highest for seed yield and lowest for oil content in all the environments. Heritability in broad sense along with genetic advance as percent of mean was registered highest for seed yield in all the environments while it was lowest for siliqua length in E1 and siliqua density in E2 and E3. The studies on correlation revealed that seed yield has highly significant positive genotypic and phenotypic correlation with almost all the traits and in all the environments except siliquae density and siliqua length. Positive direct effects through days to maturity, number of primary branches per plant, siliqua length, number of seeds per siliqua, oil content and thousand seed weight and positive indirect effects through length of main newlineraceme and siliquae on main raceme were observed for see yield, both at genotypic and phenotypic level. Genetic divergence studies grouped the 41 accessions into 11, 8 and 12 clusters in E1, E2 and E3 respectively. On the basis of inter-cluster distance, cluster XI and IX were found to be most diverse in E1, cluster VII and I in E2 and Cluster VIII and III in E3. The maximum contribution of characters towards genetic divergence was registered by seed yield in E1 and E2 and thousand seed weight in E3. The ANOVA for Eberhart and Russell s model revealed that the mean sum of squares due to accessions was highly significant and mean sum of squares due to genotype × environment interaction when tested against pooled error was found to be significant for all the traits. The joint analysis of variance showed that the mean sum of squares due to genotype and due to genotype × environment interaction was significant. Using Eberhart and Russell s model, the accessions PYS-2018-4 (G25), PYS-2016-8 (G14), PYS-2016-13 (G16), PYS-2015-3 (G10) and PYS-2020-12 newline(G35) were found to be stable for seed yield while AMMI biplot analysis marked PYS-2018-3 (G24), YSH-401 (G39), PYS-2020-3 (G33), PYS-2016-15 (G17), PYS-2015-3 (G10), PYS-2016-13 (G16), PYS-2016-10 (G15), PYS-2016-7 (G13), PYS-2016-8 (G14), YSH-401 (G39), PYS-2015-3 (G10) and PYS-2017-6 (G18) accessions to be stable. In which-won-where graph the accessions PYS-2016-8 (G14), PYS-2016-10 (G15) for E1 and PYS-2020-12 (G36) for E2 and E3 were found stable for seed yield and the accessions PYS-2016-10 (G15), PYS-2015-3 (G10), PYS-2020-7 (G35) and PYS-2016-13 (G16) were marked stable in mean v/s stability biplot. The multi trait stability index depicted that the accessions G35 (PYS-2020-7), G19 (PYS-2017-8), G25 (PYS-2018-4), G10 (PYS-2015-3), G23 (PYS-2018-2) and G16 (PYS-2016-13) were the most stable for multiple traits while G31 (PYS-2019-2), G26 (PYS-2018-7) and G6 (PYS-2013-6) were the least stable accessions. Comparative studies revealed that the genotypes found stable for multiple traits according to the MTSI model were also reported to be stable for different traits individually by the rest of the three models. The estimation of selection parameters will help to identify the suitable accessions on the basis of their distinctness for different traits in future breeding programs. Moreover, the correlation and path coefficient studies provide information regarding the association between traits and also give an idea regarding adoption of suitable breeding technique. Stability analysis of accessions using different models will help in marking the best stable accessions and also help in identifying the best method as per the objectives of the study. By use of stability analysis genotype can be identified for general as well as for specific condition. Identified genotypes can be utilized as parents for target specific research or can be used as variety for targeted areas. newline newline