Effects of Integrated Plant Nutrient Management (IPNM) Practices on the Sustainability of Maize-based Farming Systems in Nepal
Bibliographic record
Abstract
Maize is a staple summer crop grown in the hilly areas of Nepal, where the soil is fragile and fertility is declining over years due primarily to degradation of natural resource base, high rates of soil erosion, increased cropping intensity and inadequate replenishment of soil nutrients. Forum for Rural Welfare and Agricultural Reform for Development (FORWARD) with the financial support from Hill Maize Research Program (HMRP/CYMMIT) conducted eight Integrated Plant Nutrient Systems (IPNS) trials, 16 Farm Yard Manure (FYM) improvement demonstrations and 16 conservation farming demonstrations each year through two women farmer groups since 2003 in Makawanpur District in order to raise the awareness of farmers on sustainable soil management practices through better utilization of locally available and external resources. The three years' trial results revealed that the maize crop with IPNS (15 t ha-1 FYM + 60:30:30 NPK kg ha-1) was better with respect to crop vigor and grain yields compared to the control treatment (farmers' practice with FYM and urea top dressing). The Improved cultivar with IPNS practices increased the grain yield by 64% (p
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".