Phosphorus efficiency in a long-term wheat–rice cropping system in China
Bibliographic record
Abstract
SUMMARY Long-term (over 14 years) experiments on winter wheat (Triticum aestivumL.)–rice (Oryza sativaL.) crop rotations were conducted in Southwest China to investigate phosphorus (P) fertilizer utilization efficiency, including the partial factor productivity (PFP), agronomic efficiency (AE), internal efficiency (IE), partial P balance (PPB), recovery efficiency (RE) and the mass (input–output) balance. The seven treatments were Control, N, NP, NK, NPK, NPKM and NPKSt, representing various combinations of inorganic fertilizers (N, P and K), manure (M) and the application of rice straw (St). Without P application, the soil could supplyc. 14·7–22·5 kg P/ha annually and produce, on average,c. 1·8 t/ha wheat and 6·0 t/ha rice. Phosphorus fertilization increased crop yields by 65·5 and 11·4% for wheat and rice, respectively, over the 14 years. The PFP values ranged from 80·2 to 177 kg grain/kg P fertilizer for wheat and from 222 to 255 kg/kg for rice in the NPK treatments. However, the mean AE over the 14-year period was 31·9 and 21·3 kg grain/kg inorganic P fertilizer for wheat and rice, respectively. The mean IE was 214 and 318 kg grain/kg P uptake for wheat and rice, respectively, during the cultivation period. The PPB for the whole rotation system over the 14 years ranged from 0·58 to 0·64. However, the mean RE of P fertilizer was 0·26 (varying from 0·22 to 0·29) in the wheat–rice cropping system over the 14-year period. For every 100 kg surplus P/ha per year, the concentration of soil P extracted by 0·5mNaHCO3at pH 8·5 (Olsen-P) would increase by, on average, 4·12 mg/kg in soil. For the wheat–rice cropping system, the current P application rate of 55–65 kg P/ha per year is able to sustain annual yields of about 3 t/ha for wheat and 7 t/ha for rice. This study suggests that, in order to achieve higher crop yields, the P fertilizer utilization efficiency should be considered when making P fertilizer recommendations in wheat–rice cropping systems.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".