Assessment of Polygenic Traits Association with Yield in Soybean Genotypes

Arjun Sharma

Department of Plant Breeding and Genetics, RNT, University, Bhopal (MP), India.

Kanak Saxena

Department of Plant Breeding and Genetics, BAU, Sabour, Bhagalpur, Bihar, India.

Nitesh Kumar Panwar *

Department of Plant Breeding and Genetics, RVSKVV, College of Agriculture, Indore (MP), India.

K.P Singh

Faculty of Agriculture, Tantiya University, Shri Ganganagar, Riico, Rajasthan-335002, India.

*Author to whom correspondence should be addressed.


Abstract

Soybean is one of the important oilseed crop at global level with special concern to India. Despite its global dominance, India's contribution to the soybean scene remains relatively modest, with a production ranking of fourth but only a 5% share of the world's output. For this concern, the analysis of the relationships among yield attributing characters and their associations with seed yield is essential to establish selection criteria. The experimental material used in the present study comprised of fourteen lines (8 F1s and 6 parental lines). The characters viz., number of pods/plant, primary branches/plant, harvest index, plant height, secondary branch/plant, biological yield, 100-seed weight and days-to-50% flowering recorded significant positive correlation coefficient with seed yield both at genotypic and phenotypic level.  Path coefficient analysis further pinpointed 100-seed weight, harvest index, and pods per plant as the traits with the most direct positive impact on seed yield. Additionally, the study identified plant height, pods/plant, primary branches/plant, 100-seed weight, and the harvest index as the key contributors to soybean yield, suggesting these traits as primary targets for manipulation in breeding programs aimed at yield improvement.

Keywords: Correlation coefficient, path analysis, soybean


How to Cite

Sharma, Arjun, Kanak Saxena, Nitesh Kumar Panwar, and K.P Singh. 2024. “Assessment of Polygenic Traits Association With Yield in Soybean Genotypes”. Journal of Advances in Biology & Biotechnology 27 (6):693-701. https://doi.org/10.9734/jabb/2024/v27i6929.

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