Alternative Vine Management Programs for Fresh-Market Potatoes
Bibliographic record
Abstract
Abstract Economically solvent fresh-market potato production is predominantly dependent on the ability to efficiently produce consistent tuber quality and high yield, and the ability to meet first-to-market demand with early-season potatoes. Unfortunately, these two qualifiers often work against each other in terms of production management. In response, we studied integrated potato vine management programs that support timely early-season potato harvest. Vine management with a flail chopper, roller, and flame burner used alone or followed by diquat was evaluated when initiated 21 or 14 d prior to harvest in 2015 and 2016. Potato varieties included ‘Yukon Gold’ and ‘Dark Red Norland’. Potato leaf and stem management, as well as tuber skinning, stolon separation, grade, and yield were quantified. Among mechanical methods, potato leaf and stem management were poor when vines were rolled or mowed but better when flail chopped. In general, vine management and tuber skin set was better when treatments were initiated 21 d prior to harvest as opposed to 14 d. Vine management, tuber skin set, and yield were comparable when potato vines were flail chopped followed by flame burning and where diquat was applied twice, offering a viable program for smaller scale or organic production.
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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 | 0.001 | 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".