A holistic carrot production system for season-long weed management
Bibliographic record
Abstract
Abstract Weed management in carrot is challenging, given slow and inconsistent crop emergence and early-season growth and the lack of practical season-long management tools such as herbicides. We investigated holistic carrot production systems with a focus on minimizing inputs while optimizing resource use. In an overall sense, results of this work were consistent between years, and stark. The choice of carrot variety had a moderate influence on carrot foliar canopy development and, subsequently, weed density. For example, ‘Cupar’ carrot formed a complete crop canopy sooner than the other dicer-type ‘Canada’ variety. Likely as a result, density of weed species such as spotted ladysthumb and common lambsquarters was less where ‘Cupar’ was grown compared with where ‘Canada’ was grown. Gibberellic acid as a foliar application was not successful in these studies and, in a few cases, may have even increased weed-seed germination and establishment. Adding two carrot rows to the current regional industry-standard three-row bed system not only enhanced competitiveness with weeds but also improved carrot yield without additional fertilizer, water, or pest management inputs. By far, though, the most successful strategy to reduce weed density while maintaining or improving carrot yield was to delay seeding by 17 to 19 d. We anticipate more holistic production system research that integrates low-input alternatives in other crops as herbicide-resistant weeds proliferate while few new herbicides are developed. As was demonstrated in this research, such novel approaches can be successful without adding significant economic burden to the farmer or increasing risk of crop failure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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".