Characterizing the Phytotoxic Effects of Hydrogen Peroxide on Common Microgreen Species and Lettuce Cultivars
Bibliographic record
Abstract
Hydrogen peroxide (H 2 O 2 ) is an oxidizing agent used to disinfect recirculated irrigation water during the production of organic crops under controlled environmental systems (e.g., greenhouses). To characterize the phytotoxic effects and define a concentration threshold for H 2 O 2 , three microgreen species [arugula ( Brassica eruca ssp. sativa ), radish ( Raphanus sativus ), and sunflower ( Helianthus annuus ‘ Black Oil’)], and three lettuce ( Lactuca sativa ) cultivars, Othilie, Xandra, and Rouxai, were foliar sprayed once daily with water containing 0, 25, 50, 75, 100, 125, 150, or 200 mg·L −1 of H 2 O 2 from seed to harvest under greenhouse conditions. Leaf damage was assessed at harvest using two distinct methods: 1) the percentage of damaged leaves per tray and 2) a damage index (DI). Applied H 2 O 2 concentrations, starting from 25 mg·L −1 , increased the percentage of damaged leaves in every species except ‘Black Oil’ sunflower, which remained unaffected by any applied concentration. Symptoms of leaf damage manifested in similar patterns on the surface of microgreen cotyledons and lettuce leaves, while mean DI values and extent of damage were unique to each crop. Fresh weight, dry weight, and leaf area of all crops were not significantly affected by daily H 2 O 2 spray. Identifying how foliar H 2 O 2 damage manifests throughout the crop, as well at individual cotyledon or leaf surfaces, is necessary to establish an upper concentration threshold for H 2 O 2 use. On the basis of the aforementioned metrics, maximum recommended concentrations were 150 mg·L −1 (radish), 100 mg·L −1 (arugula) for microgreens and 125 mg·L −1 (‘Othilie’), 75 mg·L −1 (‘Rouxai’), and 125 mg·L −1 (‘Xandra’) lettuce.
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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".