THE EFFECT OF DIFFERENT TILLAGE SYSTEMS ON SUBSURFACE DRIP IRRIGATION EFFICIENCY IN DELTA LAND
Bibliographic record
Abstract
The water shortage is becoming one of Egypt's biggest concerns as the country relies almost entirely on the Nile while experiencing rapid population growth and intensifying climate change. The continuous decline in per-capita water availability poses serious challenges, particularly for agriculture as the country’s largest water-consuming sector. A reduced water supply directly affects crop yields and soil moisture management, making effective irrigation systems and improved soil practices essential for maintaining crop production under these challenging conditions. Two tillage treatments were applied: one used a chisel plow both horizontally and vertically combined with a wooden leveling (T1), and the other used a chisel plow only horizontally combined with a rotary plow in the perpendicular direction (T2). Additionally, two irrigation systems were used: conventional surface irrigation (basin) and subsurface drip irrigation D10, and D15 along with a lateral line at 10 cm and 15 cm under soil surface, and conventional irrigation as the third treatment options. The highest production was obtained from D15, with yields of 5,596.26 kg feddan-1 under T1 and 5,165.57 kg feddan-1 under T2. When the drip irrigation system with D15 treatment was compared to the surface irrigation (basin) system, the results revealed that total yield increased by 22.86% and 20.7 for T1 and T2 treatments, respectively. The percentages of the increases in water use efficiency (WUE) compared with traditional treatment were 68.16% and 82.87% for D10 and D15 under T1, and by 60.45% and 70.72% under T2, respectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".