Greenhouse Cucumber Growth and Yield Response to Copper Application
Bibliographic record
Abstract
To determine the nutrient solution copper (Cu 2+ ) level above which Cucumis sativus L. (cucumber, cv. LOGICA F1) plant growth and fruit yield will be negatively affected, plants were grown on rockwool and irrigated with nutrient solutions containing Cu 2+ at 0.05, 0.55, 1.05, 1.55, and 2.05 mg·L −1 . Copper treatment began when plants were 4 weeks old and lasted for 10 weeks. During this 10-week period, plants were harvested at 3 weeks (short-term) and 10 weeks (long-term) after the start of Cu 2+ treatment. Neither visible leaf injury nor negative Cu 2+ effect was observed on plant growth (leaf number, leaf area, leaf dry weight, and stem dry weight) after 3 weeks of continuous Cu 2+ treatment. However, after 10 weeks of continuous Cu 2+ application, cucumber leaf dry weight was significantly reduced by Cu 2+ levels 1.05 mg·L −1 or greater; leaf number, leaf area, and stem dry weight were significantly reduced by Cu 2+ levels 1.55 mg·L −1 or greater. Copper (Cu 2+ levels 1.05 mg·L −1 or greater) also caused root browning. Some plants under the 2.05 mg·L −1 Cu 2+ treatment started to wilt after 6 weeks of continuous Cu 2+ treatment. Copper treatment did not result in any change in leaf greenness until after Week 9 from the start of the treatments. There was no sign of a negative Cu 2+ effect on cucumber fruit numbers after the first 2 weeks of production, but plants under the highest Cu 2+ concentration treatment (2.05 mg·L −1 ) gradually produced fewer cucumber fruit than the control (0.05 mg·L −1 ) and eventually resulted in lower cucumber yield. Nutrient solution can be treated with 1.05 mg·L −1 of Cu 2+ in cucumber production greenhouses; however, it is not recommended to use Cu 2+ concentrations 1.05 mg·L −1 or greater continuously long-term (more than 3 weeks). When applying Cu 2+ , it is suggested that cucumber roots be examined regularly because roots are a better indicator for Cu 2+ toxicity than leaf injury.
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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 | 0.000 | 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".