Conservation Management and Crop Rotation Effects on Weed Populations in a 12-Year Irrigated Study
Bibliographic record
Abstract
Potato, dry bean, and sugar beet production have increased markedly in recent years on irrigated cropland in Alberta, Canada. Concerns exist about declining soil quality and increased soil erosion when these low-residue crops are grown in sequence in short-duration rotations. A 12-yr rotation study was conducted to determine the merits of adopting various conservation practices (reduced tillage, cover crops, composted manure) and longer-duration rotations to develop a more sustainable production system for these row crops. This article reports on weed density and weed seedbank data collected in the study. Weed densities recorded prior to applying postemergence herbicides indicated that conservation compared with conventional management treatments had greater weed densities in 30 to 45% of the cases in 3-, 4-, and 5-yr rotations. In contrast, a 6-yr conservation rotation that included 2 yr of timothy forage resulted in similar or lower weed densities than rotations with conventional management practices. Residual weed densities recorded 4 wk after applying postemergence herbicides were only greater in conservation than conventional rotations in 2 of 12 yr, regardless of rotation length. Weed seedbank densities at the conclusion of the 12-yr study were similar for 3- to 6-yr rotations under either conservation or conventional management. These findings indicate that implementing a suite of conservation practices poses little risk of increased weed populations in the long term. This knowledge will facilitate grower adoption of more sustainable agronomic practices for irrigated row crops in this region.
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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 | 0.001 | 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".