A Twin-head “V” High-wire Greenhouse Cucumber Production System for Reducing Crop Start-up Costs
Bibliographic record
Abstract
A high-wire system, in which the plant is trained into a single stem, is gaining popularity in year-round greenhouse cucumber ( Cucumis sativus ) production, especially with supplemental lighting, as it allows for uniform foliar and light distribution and higher yield and quality. However, this system requires much higher plant densities than the conventional umbrella system, resulting in increased crop start-up costs. A technique for raising twin-head transplants and a twin-head “V” high-wire cucumber system were developed to address this issue. The twin-head transplants were raised by topping the seedlings after the appearance of the fourth true leaf and then two strong lateral shoots were allowed to develop and be trained into a “V” system after planting. The twin-head system achieved similar plant growth and fruit yield as the conventional single-head system on two long English seedless cucumber cultivars (Bodega and Myrthos) and two breeding lines (2005A and 24–119) tested over 2 years. The twin-head system also improved the fruit grades in ‘Bodega’ by increasing the percentage of fruit in medium size while reducing the percentage of fruit in small size. Because the twin-head system achieved the same fruit yield as the conventional single-head system while using only half the number of transplants, we can conclude that the twin-head “V” high-wire system is a more cost-effective high-wire system for year-round greenhouse cucumber production.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".