Unverified paper record
Root Nodule Categorization and Their Relation with Plant Growth in Peanut Crop Grown in Alfisols
Agricultural Science Digest - A Research Journal · 18 Oct 2022 · 10.18805/ag.d-5604
Abstract
To investigate the relationship between nodule category and plant growth characteristics in peanut, nodules were classified into three categories: large size nodule (LSN) ( greater than 2 mm), medium size nodule (MSN) (1-2 mm) and small size nodule (SSN) ( less than 1 mm) and their position on roots (primary and lateral roots). The number of LSNs on primary roots was found to be much higher than on lateral roots. The number of MSN developed on primary and lateral roots was comparable, whereas, lateral roots had a higher SSN number. In addition, when comparing the LSN and MSN numbers to SSN number, the plant growth parameters showed a high positive correlation. Multivariate regression analysis yielded similar results. This nodule classification technique aids in the identification of peanut nodules and their role in quantification of plant growth characteristics. Further, this technique can be used in identifying/screening of efficient nodulating peanut genotypes.
Plant phenotyping relevance
落花生根粒を大きさと根上の位置で分類・定量する手法が中心で、植物の生育特性との関連評価や効率的な根粒形成遺伝子型のスクリーニングに利用可能としているため、植物フェノタイピング手法に該当する。
abstractnodules were classified into three categories: large size nodule (LSN) ( greater than 2 mm), medium size nodule (MSN) (1-2 mm) and small size nodule (SSN) ( less than 1 mm) and their position on roots (primary and lateral roots).
abstractThis nodule classification technique aids in the identification of peanut nodules and their role in quantification of plant growth characteristics.
abstractFurther, this technique can be used in identifying/screening of efficient nodulating peanut genotypes.
Code and data availability
The article reports manual nodule categorization and SPSS-based correlation/regression analysis of peanut growth measurements, but contains no data availability statement, no public dataset or image deposit, no author code release, and no supplementary assets. No paper-specific public asset is identifiable.
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