Evaluating Mustard Seed Meal for Weed Suppression in Potato (Solanum tuberosum)
Bibliographic record
Abstract
Mustard seed meal (MSM) derived from Sinapis alba controls weeds for several weeks following application to soil, but also has potential to injure the planted crop. Producers of certified organic potatoes typically utilize a combination of cover crops, soil hilling, harrowing, and cultivation for weed control. Once the potato canopy nears row closure, most late emerging weeds are suppressed by the dense potato canopy. MSM may have value for early season weed suppression in potato, but has not been previously tested. Our objectives were to determine the weed control efficacy and potato tolerance to MSM. We evaluated response of potatoes and weeds to MSM applied at 1.1, 2.2, and 4.5 MT ha-1 applied in a band on the potato hill just after a shallow harrowing and prior to potato emergence as part of an integrated weed management program in potatoes. MSM applied at 2.2 and 4.5 MT ha-1 reduced early season grass and broadleaf weed density 73 to 99% and 54 to 98%, respectively, in potato and reduced late season broadleaf weed biomass 71 to 94% in all three years tested. Early season grass weed density in potato was reduced by MSM at 2.2 and 4.5 MT ha-1. Late season grass weed biomass was reduced by the highest rate of 4.5 MT ha-1. MSM at 4.5 MT ha-1 caused minor injury to potato (3 to 15%) at 3 weeks after emergence, but did not reduce total tuber yields or percentage of US No.1 tubers. MSM could be a component of an integrated weed control program in potato.
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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 | 0.000 |
| 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) | 0.001 | 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".