Phosphorus status of a Humic Gleysol after 10 year of cultivation under contrasting cropping practices
Bibliographic record
Abstract
Cropping practices interactively affect soil P status. Previous studies mostly focused on cropping practices individually and limited assessments within the plow layer. This study assessed the P status of a Labarre silty clay (Humic Gleysol) profile after 10 yr cultivation under contrasting practices. Soils of 0–15, 15–30, 30–60, and 60–90 cm layers were sampled from a split-plot experiment comprising barley (Hordeum vulgare L.) monoculture and a 3-yr barley-red clover-timothy rotation both tilled with either chisel or moldboard plow as main plots, and receiving fertilizer P or liquid dairy manure as subplots. A modified Hedley sequential fractionation was used to characterize soil P status. Labile P pools were more affected than stable ones by cropping practices. The P fractions depended more on nutrient sources than cropping systems in the 0- to 30-cm soil layer, whereas the impacts were predominated by cropping systems in the subsoil. Compared to the manure, fertilizer P resulted in higher contents of Mehlich III extractable P, resin-P, NaHCO3-Pi and NaOH-Pi, and lower contents of NaHCO3-Po, NaOH-Po and H2SO4-P in the 0- to 30-cm layers. The rotation produced larger labile P fractions than the monoculture in the 30- to 60-cm layer. The impacts of the investigated cropping practices on labile P fractions extended deeper in the soil profile than the depth disturbed by primary tillage. Crop sequence, primary tillage and nutrient source had large effects on P status in the soil profile, of this clayey and poorly drained soil. Key words: rotation; primary tillage; liquid dairy manure; P forms, Mehlich III extractable P (M3P)
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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 | 0.000 | 0.000 |
| 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".