Long-term application of fertilizer and manures affect P fractions in Mollisol
Bibliographic record
Abstract
Abstract Application of phosphorus (P), a major plant nutrient, as fertilizer is critical to maintain P level for crop production and yield in most cultivated soils. While, it may impact the dynamics, limited studies have examined the long-term effects of fertilization on P fractions in a soil profile in Mollisol. A long-term field experiment was conducted at the State Key Experimental Station of Agroecology of the Chinese Academy of Sciences in Hailun county, Heilongjiang Province, China. A sequential fractionation procedure was used to determine the effect of fertilizer (types) treatments including no fertilizer (CK), chemical fertilizer (NPK), chemical fertilizer plus straw (NPK + S) and pig manure (OM) on fractions of P and their distribution within 0–100 cm soil profiles. Unlike CK treatment, the long-term application of fertilizers increased the concentration and accumulation of total and available P in 0–20 and 0–40 cm soil depths than deeper soils, respectively. The phosphorus activity coefficient (PAC) ranged from 1.5 to 13.8% within 0–100 cm soil depth. The largest PAC value was observed under OM treatment at 0–40 cm soil depth and under NPK + S treatment at 40–100 cm soil depth. The Ca 2 -P and Ca 8 -P concentrations increased significantly by 0.5–7.5 times and 0.5–10.4 times, respectively in OM treatment with the largest value in 0–40 cm soil depth over CK treatment. The Al-P concentration under NPK + S and OM treatments increased throughout the soil profile. The OM treatment increased all Po concentrations in the 0–40 cm soil depth, while NPK and NPK + S treatments increased labile organic P, moderately labile organic P, and highly stable organic P in the 0–20 cm soil depth. Thus, the application of fertilizer and straw, or organic manure may enhance inorganic and organic P pool in a Mollisol in Northeast China. Thus, organic manure application in the subsoil as a potential P source and their impact should be considered in developing management practices and policies regarding nutrient management.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".