Potato peel alleviation of the negative effects of salinity in bean (<i>Phaseolus vulgaris</i> L. ‘Valentine’)
Bibliographic record
Abstract
Soil salinity is a serious problem that negatively affects the productivity of plants. Reducing the impact of salinity to sustain production is a goal of scientists. The objective of this study was to determine the effect of potato peel amendments at different rates in reducing the negative impact of saline water. Common bean (Phaseolus vulgaris L. ‘Valentine’) was grown in soil mixed with potato peel at different rates (0%, 2.5%, 5%, and 7.5%). To achieve this objective, plants were irrigated with three levels of saline water (0, 50, and 100 mmol L−1) to induce stress at the vegetative stage. The results demonstrated the significant reduction in physiological parameters, plant growth, and yield of common bean after irrigation with saline water. Soil amendment with different rates of potato peel significantly increased the number of pods per plant, weight of pods per plant, pod length, chlorophyll content, and relative water content of common bean irrigated with saline water (50 mmol L−1) as compared with non-amended soil. Potato peel application also reduced electrolyte leakage and improved soil properties by reducing the salinity of the soil. Furthermore, among all potato peel rates used in this investigation, the 7.5% rate had a better result for common bean production. Conversely, potato peel did not improve the yield of beans grown under a high concentration of saline water (100 mmol L−1). In conclusion, soil amendments with potato peel at a 7.5% rate could be successfully used as a cost effective management practice to enhance bean production in soils stressed with high salt content.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".