Characterization and evaluation of some genotypes of soybean [Glycine max(L.) Merrill] under acidic soil condition in Meghalaya / by
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Date
2019
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College of Post Graduate Studies in Agricultural Sciences, CAU-Imphal, Umiam
Abstract
In the world scenario, India is holding 5th position by contributing about 3.95% share in total production of soybean. Although soybean is considered an important oilseed crop in the world, its production in North-eastern region of India especially in Meghalaya is quite less due to its acidic soil condition. This necessitates the requirement of better performing genotypes along with the study for genetic diversity of genotypes to develop new and improved cultivars. In the light of the above fact, the present research was conducted using 40 different soybean genotypes from different regions in the country. At different growth stages of the plant, 22 DUS characters and 12 quantitative characters were recorded. Analysis of variance gave highest significant value for number of seeds per plant succeeded by number of pods per plant and the lowest was found for number of seeds per pod and primary branches per plant. Among all the characters which were found to have high heritability, days to maturity and number of pods per cluster had the highest value. Number of seeds per plant showed highest genetic advance with high GCV, PCV and heritability followed by number of pods per cluster. Studying the correlation analysis of the agronomic traits, seed yield per plant was showing positive correlation with characters viz., number of seeds per pod, number of pods per plant, 50% flowering, plant height, days to maturity, primary branch as per plant and protein content while characters like number of seeds per pods, number of pods per cluster and 100 seed weight was found nonsignificant. The maximum yield per plant was recorded in the genotype TS-53 followed by SKF-SPS-11 and MACS-1493. Lowest yielder genotypes were MACS-1575 followed by NRC-130. Genotype CSB-10112 had the highest protein content (45.1%) and genotype NRC-131 was found to have highest oil content (20.1%). Clustering of genotypes for studying genetic diversity was performed by Tocher’s method of clustering in D2 analysis. A total of 4 clusters were formed with cluster I having 23 genotypes, cluster II with 4 genotypes, cluster III with 3 genotypes, cluster IV with 5 genotypes while cluster V, VI, VII, VIII and IX had one genotype each and remained distinct individually. Highest inter-cluster distance was found between the cluster VI and IX suggesting wider diversity between the groups and thus, could be used for hybridization programme and lowest was found between the cluster IV and V showing less diversity between them. Highest intra-cluster distance was recorded by the cluster IV indicating greater heterogeneity among the genotypes. Further, study was carried out to identify the better performing genotypes in the acidic condition through hydroponic study for tolerance to Al toxicity by using two concentrations of 25μM and 75μM Al solution along with the re-growth study in the latter. The ranking of genotypes based on yield performance was closely related with ranking based on the re-growth length of the genotypes after treatment. Linear regression of difference in taproot length of treated root from the control solution was negatively regressed to the yield data and that of root regrowth was found positively regressed to the yield data. Since, it is a preliminary finding; further validation in repeated trials might be useful for further strengthening of the relationship between hydroponic performance and yield performance under acidic soil. With these findings, it will be useful for breeders as they can use the characters which were found positively correlated with yield as selection criteria in crop improvement work and the diverse parents could be used for hybridization work. Also, the genotypes showing tolerance to Al toxicity could be used for further molecular level analysis to find the gene responsible for tolerance and also for further field analysis.