Greenhouse Pepper Growth and Yield Response to Copper Application
Bibliographic record
Abstract
Copper (electrolytically generated or from cupric sulfate) is increasingly used to control diseases and algae in the greenhouse industry. However, there is a shortage of information regarding appropriate management strategies for Cu 2+ (Cu) in greenhouse hydroponic production. Three greenhouse studies were conducted to examine the growth and yield responses of sweet pepper ( Capsicum annuum L. , Triple 4, red) to the application of Cu in hydroponic production systems. In the first two experiments, plants were grown on rockwool and irrigated with nutrient solutions containing Cu at concentrations of 0.05, 0.55, 1.05, 1.55, and 2.05 mg·L –1 . Copper treatments were started either when plants were 32 days old and continued for 4 weeks, or when plants were 11 weeks old and continued for 18 weeks, respectively. In the third experiment, roots of solution cultured pepper seedlings were exposed to Cu (1.0, 1.5, and 2.0 mg·L –1 ) containing nutrient solutions for 2 hours per day for 3 weeks. Higher Cu treatment initialized when plants were 32 days old significantly reduced plant leaf number, leaf area, leaf biomass, specific leaf area, stem length and shoot biomass. The calculated Cu toxicity threshold was 0.19 mg·L –1 . However, when treatment initialized at plants were 11 weeks old, Cu did not have significant effects on leaf chlorophyll content, leaf area or specific leaf area. Copper started to show significant negative effects on leaf biomass and shoot biomass at 1.05 mg·L –1 or higher levels. Copper treatments did not have any significant effect on fruit number, fresh weight or dry weight. Under all the Cu levels, fresh fruit copper contents were lower than 0.95 mg·kg –1 which is below the drinking water standard of 1.3 mg·kg –1 . Seedling growth was significantly reduced by exposing roots to Cu (≥1.0 mg·L –1 ) containing solutions even for only 2 h·d –1 .
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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".