Impact of planting dates on yield and pod quality traits of snap bean under short-temperate season climates
Bibliographic record
Abstract
Snap bean, a warm-season crop, have low frost tolerance. The optimal temperature for seed emergence and plant growth is important. Therefore, appropriate planting dates for adapted varieties has paramount significance in improving pod yield and quality of snap bean under short cool season climates. Three snap bean cultivars planted at 3 different dates were examined to evaluate the effects of planting dates on snap bean pod yield and quality traits in a 2-year study in a short season climate in Manitoba, Canada. Results of this study showed that three, two weeks apart, planting dates had a non- significant effect on marketing yield of three different cultivars tested in this study. Planting dates showed significant effect on un-marketable yield, pod fresh weight, pod length and total soluble solids. Higher marketable and un-marketable yields along with longer pod length and soluble solids, in all three cultivars, were more profound when seeded at mid and late planting dates. Snap bean grew under higher temperature and accumulated more growing degree days (GDD) when planted in mid June and early July when compared to early June planting. These results conclude that marketable yields of snap bean were not significantly affected by planting dates when seeded-two weeks apart-in shorter growing environments which allow commercial and market gardeners, in northern areas with shorter growing seasons to optimise planting snap bean, without reducing pod yield and quality.
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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 | 0.001 | 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".