Poultry manure and inorganic fertiliser effects on soil fertility and microbial communities in wheat and corn agroecosystems
Bibliographic record
Abstract
Many producers in North America are finding it profitable to make the transition from conventional farming to organic agriculture. Organic fertilisers may affect crop production and soil quality differently than inorganic fertilisers. The objectives of this study conducted in Ste.-Anne-de-Bellevue. Quebec were to examine crop yield, grain quality, soil fertility and microbial community parameters in wheat and corn agroecosystems receiving poultry manure or inorganic fertiliser. Wheat grain yield declined and corn grain yield did not increase with higher N rates, suggesting that increased N supply did not encourage grain production. Soil analyses demonstrated high inherent soil fertility at the study site, and fertilisation led to an environmentally undesirable increase in residual soil NO3 concentrations. Microbial biomass and respiration in corn agroecosystems were greater with poultry manure amendments than inorganic fertiliser, but not in wheat agroecosystems due to significant variation among field replicates. Phospholipid fatty acid analysis revealed significant differences between wheat and corn soil microbial community composition, but differences due to fertilisation were less evident. Further work is needed to uncover the relationships among N fertilisation, crop nutrition and soil microbiology in organic agroecosystems.
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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".