Effect of tillage and crop rotation on root and foliar diseases of wheat and pea in Saskatchewan from 1991 to 1998: Univariate and multivariate analyses
Bibliographic record
Abstract
Disease severity and incidence of fungal species on wheat and pea were evaluated under zero, minimum, and conventional tillage in three rotations with increasing broad-leaved crop diversity from 1991 to 1998 at Indian Head, SK. The objective was to determine whether differences in crop rotation and crop residue at the soil surface would increase crop disease problems. Rotation and tillage had little impact on disease relative to the environment. Reduced tillage did not substantially increase disease severity from leaf spot diseases of wheat or on diseases of field pea. However, the relative importance of root pathogens of wheat was affected; under reduced tillage Bipolaris sorokiniana and Gaeumannomyces graminis decreased, but Fusarium spp. increased on wheat roots. These changes did not affect overall root severity or yield. Rotations had limited impact on wheat disease severity and the prevalence of fungal species, but wheat grown in diversified crop rotations using cereal, pea and flax had consistently higher yields than wheat following wheat. Growing wheat after summerfallow or pea reduced foliar diseases of wheat compared with wheat after wheat. Increased crop diversity in rotations reduced populations of B. sorokiniana, Septoria tritici, and Stagonospora nodorum in wheat leaves and roots, but growing wheat after flax increased the incidence of Fusariumspp. in wheat roots. Key words: Rotation, tillage, root rot, leaf spot, Triticum aestivum, Pisum sativum
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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 | 0.001 | 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) | 0.001 | 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".