Demand-Supply Balance of the Nitrogen Nutrients Converted from Regional Agricultural Organic Wastes for Agricultural Utilization
Bibliographic record
Abstract
To promote the recycling of agricultural organic wastes (AOWs), e.g., crop straws, and livestock and poultry (LP) manures, it is very important to analyze the demand-supply balance of the nitrogen nutrients converted from AOWs for agricultural utilization on a regional basis. Focusing on Shangshui County in central China’s Henan Province, this paper thoroughly analyzes this demand-supply balance through literature query and field survey. Firstly, the amount of nitrogen nutrients converted from the crop straws, and LP manures were calculated for the study area. Next, the demand for nitrogen nutrients of agricultural planting in the study area was estimated based on the soil properties and agricultural planting area. Based on the calculation results, the demand-supply balance of the nitrogen nutrients converted from AOWs for agricultural utilization in the study area was subject to quantitative analysis. The results show that: In 2017, the agricultural planting in Shangshui County demanded 35.16 kilotons of nitrogen nutrients; the total supply of nitrogen nutrients converted from AOWs stood at 25.86 kilotons, including 12.41 kilotons from crop straws (47.99%) and 13.45 kilotons (52.01%) from LP manures; the demand-supply ratio (amount of demand/supply quantity) of nitrogen nutrients was 1.36, that is, the demand surpassed the supply; therefore, the nitrogen nutrients provided by the AOWs in the study area can be fully utilized by the agricultural soil in the region.
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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 | 0.001 | 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".