Effects of drip irrigation frequency on the yield and nutrient utilization efficiency of tomato under long-season cultivation in solar greenhouse.
Bibliographic record
Abstract
treatment, plant dry matter accumulation and the accumulation of N, P and K increased by 4.9%, 8.0%, 8.0%, 16.8%, the partial productivity of fertilizer and the utilization efficiency of water increased by 142.8% and 12.2%, the use efficiency of N, P and K was better than CK by 241.4%, 466.6% and 235.9%, respectively, and the tomato yield increased by 12.2%. Under the experimental conditions, drip irrigation with the Yamazaki nutrient solution at a frequency of 4 days could increase the tomato yield, as well as the use efficiency of nutrients and water. Under long-season cultivation, these trends would result in considerable saving of water and fertilizer. Overall, our findings provided a basis for improving the scientific management of water and fertilizers under long-season tomato cultivation in protected facilities.
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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".