Assessment of Variability Based on Morphometric Characteristics in the Core Set of Soybean Germplasm Accessions

Shruthi, K.; Siddaraju, R.; Naveena, K.; Ramanappa, T. M.; Vishwanath, K.

doi:10.18805/lr-4286

Cited by 2 publications

(2 citation statements)

References 11 publications

(11 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An attempt was made to develop the model for identify suitable morpho metric variables which project seed yield of soybean germplasm accessions which is having higher genetic variability (Shruthi et al, 2021). The results from the Multiple linear regression (MLR) indicates the VIF values of the most of the variables are more than 10 (Table 1) and high correlation between independent variables (Fig 2 ) indicting multicollinearity problem in the data set.…”

Section: Resultsmentioning

confidence: 99%

Trait Based Modelling Approach for Selection of Elite Germplasm Accessions in Soybean [Glycine max (L). Merrill]

Shruthi

Siddaraju

Naveena

et al. 2021

Self Cite

View full text Add to dashboard Cite

Background: Identification of suitable factors that influence significantly to the response is crucial for the traits based breeding program to make a better decision about improvement in productivity. Multiple linear regression (MLR) is the benchmark method commonly using to identify suitable factors for crop improvement. It doesn’t work always due to stringent assumption (Multicollinearity, Linearity) behind the MLR model. Here we tried to develop an efficient model for the selection of major traits that contribute to seed yield in soybean by comparing different models.Methods: Field experiment was conducted using 98 soybean core population through augmented design.18 morphometric traits obtain from soybean core population were considered under the study as regressors.Multiple linear regression (MLR), Principle component Regression (PCR), Regression tree and Random Forest models were compared to select traits based on prediction accuracy.Result: All the models identified the number of pods per plant (NPP) has the most influencing variable to the soybean yield. However random forest has a much higher prediction power (RMSE=4.59, MAPE=0.18) compared to other models under study. The results of random forest revealed that the number of pods per plant, number of branches per plant and other associated characters like plant height at harvest as highly influencing traits for seed yield in soybean.Finally, tried to identify genotypesthat possess superiority about most influencing morphological characters on seed yield using cluster analysis.

show abstract

Section: Resultsmentioning

confidence: 99%

Trait Based Modelling Approach for Selection of Elite Germplasm Accessions in Soybean [Glycine max (L). Merrill]

Shruthi

Siddaraju

Naveena

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…Broad-sense heritability was higher (> 60%) for all the traits. Estimates of expected GAM were higher for all the traits except days to 80 per cent maturity (10.89%) (Table 5) (Darai et al, 2020;Shruthi et al, 2020).…”

Section: Quantitative Traitsmentioning

confidence: 98%

Development and Validation of Soybean [Glycine max (L.) Merrill] Core Sets and Identification of Trait-specific Accessions from the Best Core Set

Chawan,

Ravishankar,

Ramesh

et al. 2024

View full text Add to dashboard Cite

Background: Core collection of germplasm accelerates breeding objective of a crop. A core set of trait specific accessions reduces time, money and valuable man power in any crop breeding system and Standard stratified clustering approach is the most preferred approach to construct the coreset. Methods: During summer of 2020-21, the genetic variability of 2000 soybean germplasm accessions were assessed at University of Agricultural Sciences, Bengaluru. The clustering approach was deployed to develop 8 core sets from the base collection based on 13 qualitative and 7 quantitative traits. The core sets were validated using various univariate and multivariate statistics to assess their representativeness of the base collection. During kharif 2021, 300 germplasm accessions (15% core size) were evaluated at two sites viz., GKVK, Bengaluru and KVK Doddaballapur, to identify trait-specific accessions from the best core set. Result: Eight core sets were developed in the current study using the SSC approach. Logarithmic sampling with preferred allocation approach-based core set of 15% size was identified as the best representative of the base collection. Many trait-specific accessions were found promising for the combination of desirable traits from the best core set suggesting their preferential use in breeding programme.

show abstract

Assessment of Variability Based on Morphometric Characteristics in the Core Set of Soybean Germplasm Accessions

Cited by 2 publications

References 11 publications

Trait Based Modelling Approach for Selection of Elite Germplasm Accessions in Soybean [Glycine max (L). Merrill]

Trait Based Modelling Approach for Selection of Elite Germplasm Accessions in Soybean [Glycine max (L). Merrill]

Development and Validation of Soybean [Glycine max (L.) Merrill] Core Sets and Identification of Trait-specific Accessions from the Best Core Set

Contact Info

Product

Resources

About