Impact of Sodium Hypochlorite Applied as Nutrient Solution Disinfectant on Growth, Nutritional Status, Yield, and Consumer Safety of Tomato (Solanum lycopersicum L.) Fruit Produced in a Soilless Cultivation
Bibliographic record
Abstract
Soilless crop production is spread worldwide. It is a cultivating technique that enhances yield quality and quantity, thus contributing to both food safety and food security. However, in closed-loop soilless crops, the risk of spreading soil-borne pathogens through the recycled nutrient solution makes the establishment of a disinfection strategy necessary. In the current study, sodium hypochlorite was applied to the recycled nutrient solution as a chemical disinfectant to assess its impact on plant growth, leaf gas exchange, fruit yield, tissue mineral composition, and possible accumulation of chlorate and perchlorate residues in tomato fruits. The application of 2.5, 5, and 7.5 mg L−1 of chlorine three times at fortnightly intervals during the cropping period had no impact on plant growth or gas exchange parameters. Furthermore, the application of 2.5 mg L−1 of chlorine led to a significant increase in the total production of marketable fruits (total fruit weight per plant). No consistent differences in nutrient concentrations were recorded between the treatments. Moreover, neither chlorate nor perchlorate residues were detected in tomato fruits, even though chlorate residues were present in the nutrient solution. Therefore, the obtained tomatoes were safe for consumption. Further research is needed to test the application of chlorine in combination with crop inoculation with pathogens to test the efficiency of chlorine as a disinfectant in soilless nutrient solutions.
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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) | 0.000 | 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) | 0.001 | 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 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".