Water Stress Affects Plant Relative Water Content, Soluble Protein, Total Chlorophyll Content and Yield of Ratoon Banana
Bibliographic record
Abstract
Twelve cultivars of banana plants were grown in field conditions and were studied under two irrigation regimes under ratoon season in order to evaluate the relative water content, soluble protein content, total chlorophyll content and yield changes induced by water deficit. Irrigation was applied when soil water potential reached at 80 per cent ASM for the wet treatments and 50 per cent ASM for the stressed treatment plots. The ASM were calculated based on the soil moisture release curve. The soil moisture content was measured by using pressure plate membrane apparatus. The cultivars and hybrids of Karpuravalli, Karpuravalli × Pisang Jajee, Saba, and Sannachenkathali, the RWC was reduced in water-stressed leaves with 8 per cent over control, which could have accounted for the decreased soluble protein, total chlorophyll content and yield in the per cent reduction of 9 and 8 than the other cultivars and hybrids. The highest reduction of 24 per cent in RWC leads to 19 and 18 per cent reduction in soluble protein and chlorophyll content due to water deficit were registered by the cultivars and hybrid of Matti, Pisang Jajee × Matti, Matti × Anaikomban and Anaikomban × Pisang Jajee leads to reduce the yield.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".