Effect of crop rotation and soil amendments on Sclerotinia stem rot on soybean in two soils
Bibliographic record
Abstract
The effect of 4-yr soybean rotations with corn (CCCS vs. CCSS vs. SSSS) and soil amendments (urban compost vs. mineral fertilizer) on Sclerotinia stem rot of soybean (disease severity index, apothecia number, sclerotia survival), caused by Sclerotinia sclerotiorum, was studied on two soils (clay loam and sandy loam) at Saint-Hyacinthe, in southwestern Québec, from 1999 to 2002. In 2002, the 3-yr-corn rotation had a significant effect on the disease severity index (DSI) at the clay loam site; DSI was greatly reduced by rotation (5.2%) compared with monoculture (44.3%). At the sandy loam site, an interaction between rotation and fertility amendments reduced DSI from 71.7% in the monoculture to 37.8% in the 3-yr-corn rotation amended with compost. Canonical redundancy analysis (RDA) of the DSI-apothecia matrix in 2002 confirmed the suppressiveness of the 3-yr-corn rotation and revealed a significant conducive effect on DSI of compost at the clay loam site. At the sandy loam site, RDA of the DSI-apothecia matrix confirmed suppressive interaction between corn-soybean rotations and compost amendment. Key words: Sclerotinia stem rot of soybean, crop rotation, urban compost, multiple regression, canonical redundancy analysis, permutations test
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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 | 0.001 |
| 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) | 0.001 | 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".