Development of Common Bean (Phaseolus Vulgaris L.) Production Under Low Soil Phosphorus and Drought in Sub-Saharan Africa: A Review
Bibliographic record
Abstract
Owing to its nutritional value, especially proteins, carbohydrates, vitamins and micronutrients, common bean (Phaseolus Vulgaris L.) has been recognised as a crop that could ensure food security mostly, in Sub-Saharan Africa, where its productivity is low. Its low productivity is attributed to a milliard of constraints, of which low plant-available phosphorus (P) and limited moisture in soil are among the major limiting factors. Synergistic effects of the two factors are accentuated in Sub-Saharan African region. This paper discloses the importance of the synergistic effects of plant-available P and moisture in soils on common bean production. It has been observed that studies investigating impacts of interactions of low P levels and moisture deficit conditions in soils are yet to be conducted. Identification of traits that contribute to high performance under low P availability and moisture deficit in the same genotypes remains a major research and development challenge. However, engineering new genotypes alone may not alleviate the problem of ensuring improvement of high bean yields. Root architecture and root exploration of the soil that enable the plant to access the two soil resources, traditional methods that preserve good status of organic matter in soils and moisture and soil preparation techniques are equally important. This, calls for holistic investigations that include soil plant-available P and moisture, common bean genotypes and their root systems, and agronomic measures to facilitate a comprehensive evaluation of impacts of deficiencies in soils on common bean yields. This paper explores and synthesizes existing research and development of common bean grown in soils deficient in plant-available P and moisture, aiming at designing future research to enhance common bean productivity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".