Influence of Drip Irrigation and Mulch on Leaf Area Maximization, Water Use Efficiency and Yield of Potato (Solanum tuberosum L.)
Bibliographic record
Abstract
This study critically assessed the influence of frequent availability of water i. e. drip irrigation and mulch on optimum leaf area development of potato that control light interception and soil moisture conservation. Crop growth was stimulated in terms of early pick up of leaf areas that quickly covered the ground and improved transpiration efficiency. Drip irrigation increased water use efficiency three times as compared with furrow irrigation (conventional method of irrigation). Black Polyethylene mulch (25µm) conserved soil moisture, raised soil temperature by 9oC, stimulated shoot, solon and root growth, increased the total tuber number and yield but reduced the grade of tubers. Drip irrigation may prove a viable tool for source-sink alteration; stimulating early stolon initiation combined with ability to quick ground cover and sustained leaf growth for new tuber initiation for seed production as well as extended tuber bulking of early formed tubers for obtaining maximum yield with 50% saving of irrigation water and efficient use of nitrogen fertilizer.
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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) | 0.000 | 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".