Effect of land configuration and moisture conservation techniques on pearl millet in arid regions
Bibliographic record
Abstract
For centuries, dryland farmers have shaped the land surface to capture scarce rainfall, yet modern arid-zone agriculture often ignores these practices. This research evaluated four land configurations flatbed (control), ridge and furrow, Broad Bed Furrow (BBF), and compartment bunding combined with three moisture conservation treatments (no mulch, crop residue mulch at 5 t ha⁻¹, and hydrogel at 2.5 kg ha⁻¹) on pearl millet (Pennisetum glaucum L.) productivity at the University of Guelph arid-simulation facility during 2022-2023. Compartment bunding with residue mulch conserved 78.4% more soil moisture at the flowering stage compared with the flatbed control and increased grain yield by 61.3% (from 1,287 to 2,076 kg ha⁻¹). Water use efficiency peaked at 15.2 kg ha⁻¹ mm⁻¹ under compartment bunding versus 8.4 kg ha⁻¹ mm⁻¹ for the flatbed. These results show that combining appropriate land shaping with surface mulching can substantially stabilize pearl millet yields under moisture-limited conditions.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".