Evaluation of Household Cleaning Methods for Reducing Chlorantraniliprole Residues on Cowpea Fruits
Bibliographic record
Abstract
All pesticide residues are toxic by design and pose seriously health dangers to people. We explored an effective cleaning technique of food safety and handling guidelines. Chlorantraniliprole residues on cowpea fruits were determined by LC-MS/MS (liquid chromatography-tandem mass spectrometry) after different cleaning methods. Both soaking the cowpea fruits in water for 15 min and soaking in 0.1% edible vinegar for 15 min followed by rinsing with running tap water for 2 min could effectively remove the chlorantraniliprole residues on cowpea fruits. Cleaning with running tap water for 2 min was the worst cleaning method. Both the treatments of soaking in acidic and neutral pH cleaning solution could generate good removal efficiency of chlorantraniliprole residues on cowpea. Different cleaning solution concentration did not give significant difference removal efficiency. Our research provided the inherent relationship between pesticide residues and cleaning approaches, also the important theoretical basis for risk assessments of food.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".