Effect of Varieties on Growth and Yield of Yard Long Bean under Songhkla Conditions, Southern Thailand
Bibliographic record
Abstract
Yard long bean (<em>Vigna sesquipedalis</em> L. Fruw) is one of the most popular vegetables in many countries of Southeast Asia. Especially in Thailand, it has given high productivities for export in both fresh and frozen types. Yard long bean is considered as relatively low pod yield productivity and stability because it is quite sensitive to unfavorably environmental conditions, particularly for humid tropical regions with turmoil weather. The effect of varieties on growth and yield of yard long bean was conducted at Department of Plant Science, Faculty of Natural Resources, Prince of Songkla University, Hat Yai campus, Thailand to test for yield and other horticultural characteristics of seven varieties of yard long bean. All varieties of yard long bean were well grown under Songkhla’s conditions. Randomized complete block design (RCBD) was used with four replications. The experiment was taken from February to April, 2014. The results showed that the Mae Ping, Euro, Green Arrow, Kheow Dok, and Saifa varieties exhibited good growth and high yield. The Mae Ping variety gave the highest marketable yield of 12.25 t<sup>.</sup>ha<sup>-1</sup> not significantly different (p≤0.05) from the Euro, Green Arrow, Kheow Dok, and Saifa varieties which gave the marketable yield of 15.16, 14.13, 13.51, and 13.34 t<sup>.</sup>ha<sup>-1</sup>, respectively. The Negro and Taiwan varieties were the second high yielding varieties which gave the marketable yield of 11.90 and 11.92 t<sup>.</sup>ha<sup>-1</sup>, respectively. The Euro, Kheow Dok, Saifa, and Taiwan were interesting varieties because they had pod length longer than 60 cm to meet the needs of the consumers in Songkhla province and around this area. It is concluded that the Mae Ping, Euro, Green Arrow, Kheow Dok, and Saifa varieties were the most suitable for growing under Songkhla conditions, southern Thailand due to its high growth and yield.
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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 | 0.001 |
| 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".