Planting Times and Varieties on Incidence of Bacterial Disease and Yield Quality of Broccoli during Rainy Season in Southern Thailand
Bibliographic record
Abstract
The aims of this study were to determine the effect of planting times and varieties on incidence of bacterial disease and yield quality of broccoli grown during rainy season in southern Thailand. The research was carried out at Prince of Songkla University from July, 2011 to January, 2012. The design was a split-plot in a randomized complete block with four replications. The result showed that the Yok Kheo grown in July was observed with the lowest incidence of soft rot disease of 27.68% while the highest incidence of 80.11% was found in the Top Green when planting in November. In July, all varieties of broccoli had not been affected by black rot disease. After that, their incidences increased when planting between August and December. The four broccoli varieties had the highest disease incidence of 87.42-97.57% when planting in October, followed by September, November and December of 74.72-94.97%. The Yok Kheo had the highest yield quality when planting in July and December with total yield of 4.70-5.29 t/ha. It is an interesting new hybrid variety. It gave higher yield quality than Top Green which is popular variety grown in southern Thailand.
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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 | 0.001 |
| 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".