Deficit Irrigation of Durum Wheat (Triticum durum Desf): Effects on Total Dry Matter Production, Light Interception and Radiation Use Efficiency Under Different Nitrogen Rates
Bibliographic record
Abstract
On-farm trial was conducted from 2005 to 2008 to test the hypothesis that reduction of total dry matter (TDM) in crops can occur after a decreased radiation use efficiency (RUE) due to shortage of nitrogen and irrigation, we applied three irrigations treatments (D1, D2 and D3) and four nitrogen rates (N1, N2, N3 and N4). Photosynthetic active radiation absorbed or cumulative light interception (PARabs) and RUE of Durum wheat were measured. Results showed that D1N1 treatment recorded the highest LAI, PARabs, TDM and RUE. The maximum LAI was obtained 140 DAS (days after sowing) under treatment D1N2 (6.42) and the lowest LAI at the same phase belonged to treatment D2N4 (3.86). At the harvest, the maximum of TDM was 1487 g m-2 recorded under treatment D1N1. The minimum value obtained was 930 g m-2 under treatment D3N4. Also, PARabs was improved under D1N1 and D1N2 treatments. With reduced N application rates and irrigation doses, PARabs was decreased and the lowest values were observed under D3N4 condition. The RUE, varied from 1.55 g MJ-1 (D1N1) to 1.24 g MJ-1 (D3N4), was affected and decreased under deficit irrigation and low nitrogen conditions. In conclusion, the results of this study seem to show that D1N1 and D1N2 treatments can be beneficial for Durum wheat under field conditions in semi arid zone of Tunisia, for the purpose of improving RUE and maximizing grain 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".