Does Deficit Irrigation Affect the Relation between Radiation Interception and Water Consumption for Durum Wheat (Triticum durum Desf)?
Bibliographic record
Abstract
Total Dray Matter (TDM), Photosynthetically Active Radiation Intercepted (PARabs), Water Consumption (WC), Water use- (WUE), Radiation use efficiency (RUE) and the Relation between Radiation Interception and Water Consumption for Durum Wheat were investigate under different irrigation amount (D1= 100 % ETc; D2= 70 % ETc; D3= 40 % ETc and D4= pluvial) and during three growing seasons (2005-2006, 2006-2007 and 2007-2008). Results showed that, the cumulative PARabs decreased with deficit irrigation. In fact, D1 treatment recorded the highest cumulative PAR abs and the lowest marked under D4 treatment. Similarly, TDM and RUE were decreased with deficit irrigation. The highest RUE observed under the D1 (from 1.32 to 1.43 g MJ-1) and the lowest under D4 (from 1.17 to 1.29 g MJ-1). However WUE increased with deficit irrigation. The highest WUE were obtained under the D4 (from 3 to 4 kg m-3) and the lowest were observed under D1 (from 2.8 to 3.1 kg m-3). Significant linear relationship was found between cumulative PAR abs and cumulative water consumption with a high correlation coefficient (R2) only under the two treatments D1 and D2.
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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".