IMPACTS OF TILLAGE, STUBBLE MANAGEMENT AND NITROGEN ON WHEAT PRODUCTION AND SOIL PROPERTIES
Bibliographic record
Abstract
In continuous cereal-based crop rotation, inappropriate residue management such as burning and removing may deteriorate soil properties and crop productivity. The objective of this study was to evaluate the effects of different tillage systems (TSs), nitrogen fertilization, and maize (Zea mays L.) stubble management (SM) on subsequent wheat (Triticum aestivum L.) crop and soil properties. The experiment consisted of three TSs, i.e., shallowing with rotavator (0–10 cm), conventional (0–20 cm), and deep tillage (0–30 cm) as main plots, whereas the subplots were SM (removal, burning, or incorporation) with or without 120 kg N ha−1 as urea. The treatments were laid out in a split-plot fashion with whole-plot factor in a randomized complete block design. Shallow tillage (ST) increased wheat yield and soil moisture retention, soil mineral N, total N, and organic carbon. Similarly, stubble incorporation with N fertilization enhanced grain yield and soil properties as compared with the stubble removed or burning treatments. Synergetic effects were noted between ST and residue incorporation with N fertilization for grain yield and soil N response. We conclude that in a cereal-based cropping system, ST and maize stubble incorporation accompanied by N fertilization can improve soil properties and productivity of subsequent wheat crop in existing soil 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 | 0.001 | 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 | 0.001 |
| 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".