Agronomical and Physiological Response of Common Bean (Phaseolus vulgaris L.) Genotypes to Low Soil Fertility at the Southern Highland Region of Yemen
Bibliographic record
Abstract
Production of common bean (Phaseolus vulgaris L.) is often limited by the low soil fertility (LF). Identification of common bean genotypes adapted to LF may be a feasible strategy to overcome the poor plant growth and production in NP-deficient soils. Eight bean genotypes samples/derived from International Center for Tropical Agriculture (CIAT) and three local common bean cultivars were evaluated in low soil fertility (LF) and recommended fertilizers (RF) at three locations representing high (Mashwarah), medium (Shaban) and low (Al-Qaidah) rainy seasons at Southern Highland Region (SHR), Ibb, Yemen in 2011, 2012 and 2013 following a completely randomized block design, arranged as split plot with either (LF) or (RF) as the main plots and the genotypes as sub plots. Three replications were used. The LF plots was absolute control, it did not receive any fertilizer (LF) and in (RF) plots, it received only 34.5 kg N and 92 kg P2O5 kg. The common bean genotypes varied in phenotypic, nutrient efficiency traits and low fertility tolerant indices. The genotypes G2381B, MIB-156, BFB-140, BFB-141 performed favorably under both (RF and LF) environments. These genotypes were associated with higher values of pod number/plant, seed number/plant and 100 seed weight and leaf area, root nodules mass, shoot mass and root mass, shoot mass, physiological, nutrients and recovery efficiency and geometric mean percent (GMP), mean percent (MP) and susceptible tolerant index (STI) and low values of agronomy efficiency, percent of reduction (PR), low fertility susceptible index (LFSI) and tolerant (TOL). The results also showed that high and significant positive correlation of low fertility yield (LFY) and recommended fertility yield (RFY) with seed number/plant and 100 seed weight, NP recovery and use efficiency, geometric mean percent (GMP), mean percent (MP) and susceptible tolerant index (STI) under LF or RF. These correlations indicates that direction selection for yield under LF or RF would result into improved LF tolerant genotypes. Using phenotypic, nutrient efficiency traits, low fertility tolerant indices and stability indices criteria, only G2381B, MIB-156, BFB-140, BFB-143 and BFB-144 showed high average of yields, with b-value of 1.00 and a very low standard deviation (s2d) approaching zero, low ecovalence value (W) and highly significant coefficient of determination (r2). However, the regression coefficients indicating stability (b’s) and residuals were highly correlated with slopes (r = 0.943; P < 0.001) and coefficient of determination (r = 0.711; P < 0.001) and equivalent value (r = 0.809; P < 0.001), respectively. Thus the data collected from three locations x three years can be used to select low fertility tolerant (or ‘stable’) genotypes. Such low fertility tolerant genotypes would be better suited for poor farmers in the SHR-Ibb and other similar production regions in Yemen.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".