Weed communities after decades of mineral fertilization and tillage treatments in a corn–soybean rotation
Bibliographic record
Abstract
Abstract Soil fertility and disturbance can potentially modify weed dynamics in a corn–soybean rotation. Knowing how added mineral fertilizers and tillage influence weed populations in the long term can provide insight into weed community shifts, which may affect future weed management requirements. The first objective of this study was to evaluate the effect of 24 to 25 years of nitrogen and phosphorus fertilization treatments and tillage (moldboard vs. no-till) on weeds (density, biomass, and composition) before and after herbicide applications in 2016/corn and 2017/soybean. The second objective was to evaluate the effect of the same treatments 6 yr after no postemergence weed management in 2022/corn. Since the last evaluation performed in 2004, weed density, richness, and diversity increased, and more annual grasses were observed under both tillage regimes. No fertilization effect was observed on any weed variables, including composition, except for increased biomass when left to grow all season after crop planting. In managed plots, the density and biomass of annuals and perennials were generally higher in no-till, and discrepancies were highest for annual grass densities before herbicide application. Weed species richness and diversity based on counts were equivalent between tillage regimes, but total biomass was distributed between more species in no-till. Higher weed densities and concurrent weed biomass, observed in no-till, reduced crop yields in 2016/soybean only. The combination of low crop diversity and low use of residual herbicides during the trial potentially led to the observed species shifts and increased weed density.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".