Effect of Household Processing on the Removal of Pesticide Residues in Okra Vegetable
Bibliographic record
Abstract
The study has been designed to determine the extent of pesticide residues removal from okra through household processing. For this, okra crop was grown on university farm and application of pesticides were carried out at recommended dosage. After 24 hours, the okra was harvested, labeled and brought to the laboratory of Institute of Food Sciences and Technology, Sindh Agriculture University, Tandojam for their analyses and further processing such as washing, detergent washing, sun-drying and cooking, etc. being practiced at various households. Pesticide residues were extracted from okra by solvent partitioning and cleaned by C18 cartridges/activated charcoal by using acetonitrile for elution and then cleaned up residues were analyzed through HPLC-UV. The analysis of data revealed that imidacloprid is highly effective against pests at low dosages and its residues in processed as well as unprocessed okra samples were within MRLs (0.5ppm). Imidacloprid residues 0.31 ppm in unwashed okra was reduced to 0.082 ppm by detergent washing (73% removal). Emamectin benzoate residues were high in unwashed okra (0.51 ppm as against MRLs of 0.2ppm), however, its residues were reduced to MRLs by detergent washing and subsequent processing by frying, thermal dehydration or sun-drying of detergent washed okra.
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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 | 0.005 | 0.000 |
| 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".