Quantitative analysis of morphometric traits affecting yield performance in diverse soybean lines (<i>Glycine max</i> L. Merr)

Developing superior soybean lines with high productivity requires thorough identification of morphological diversity to select desirable agronomic traits. This study focuses on the morphometric analysis of various soybean lines (<i>Glycine max</i> L. Merrill) to support the development of high-yield varieties. Conducted at the BSIP AKABI Kendalpayak Malang Experimental Farm, the study employed a randomised complete block design with 30 selected lines and six parent varieties. Key yield-related traits including pod length, pod width, and seed thickness were analysed. Results showed substantial variability; for example lines UBASK41 and UBASK22 exhibited median pod lengths of approximately 9.2 cm, which correlates positively with yield potential, whereas UBASK14 and UBASK33 had shorter pod lengths around 6.5 cm. Seed width and thickness also varied, with UBASK64 reaching a maximum pod width of 22 mm, and UBASK32 showing greater seed thickness, indicating these lines’ potential for larger, high-quality seeds. Path analysis and PCA revealed strong associations between specific morphometric traits and yield-related outcomes. These findings underscore the utility of morphometric analysis in selecting soybean lines with superior agronomic traits, thus supporting breeding programs aimed at yield optimisation.

Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.29254568.v1
Primary Topic
Molecular Spectroscopy and Structure
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantitative analysis of morphometric traits affecting yield performance in diverse soybean lines (Glycine max L. Merr)

Figshare
Molecular Spectroscopy and Structure
article

Quantitative analysis of morphometric traits affecting yield performance in diverse soybean lines (Glycine max L. Merr)

article en

Abstract

Developing superior soybean lines with high productivity requires thorough identification of morphological diversity to select desirable agronomic traits. This study focuses on the morphometric analysis of various soybean lines (<i>Glycine max</i> L. Merrill) to support the development of high-yield varieties. Conducted at the BSIP AKABI Kendalpayak Malang Experimental Farm, the study employed a randomised complete block design with 30 selected lines and six parent varieties. Key yield-related traits including pod length, pod width, and seed thickness were analysed. Results showed substantial variability; for example lines UBASK41 and UBASK22 exhibited median pod lengths of approximately 9.2 cm, which correlates positively with yield potential, whereas UBASK14 and UBASK33 had shorter pod lengths around 6.5 cm. Seed width and thickness also varied, with UBASK64 reaching a maximum pod width of 22 mm, and UBASK32 showing greater seed thickness, indicating these lines’ potential for larger, high-quality seeds. Path analysis and PCA revealed strong associations between specific morphometric traits and yield-related outcomes. These findings underscore the utility of morphometric analysis in selecting soybean lines with superior agronomic traits, thus supporting breeding programs aimed at yield optimisation.

Figshare
Zero hunger
Openalex Percentile: Top 57%
Molecular Spectroscopy and Structure
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Quantitative analysis of morphometric traits affecting yield performance in diverse soybean lines (<i>Glycine max</i> L. Merr) · Figshare (2025) | TGRS Research Map | TGRS