Preliminary Study on Deltamethrin Residues in Cabbage, Soil and Water from Dalaguete, Cebu, Philippines
Bibliographic record
Abstract
Pesticides pose a threat to the environment and eventually human health. Extent of contamination of pesticides can be determined and monitored by analysis of pesticide residue in surface water, sediments, soil, and biota. Samples were collected from Manlapay, Barangay Mantalongon in Dalaguete, reportedly the vegetable basket of Cebu, from October to November 2013. Concentration of the pesticide deltamethrin was determined by Gas Chromatography-Electron Capture Detector along with organic matter content (OM), potassium (K) and cation exchange capacity (CEC) using standard methods of analysis. Data showed that deltamethrin was found to be present in soil and cabbage and beyond detection limit in water. Inverse relationship was found between residue in cabbage and in soil confirming pesticide leaching as supported by rainfall data. Organic matter and cation exchange capacity in soil showed significant correlation to detected deltamethrin residue confirming that pyrethroids are strongly bound to organic matter and free exchangeable potassium ions. Deltamethrin residue in water does not show any correlation to any other parameters as it is beyond detection limit, probably due to volatilization and photodegradation of deltamethrin in water. Temperature variation does not show significant difference to deltamethrin residue in all three matrices. The detected deltamethrin residue concentrations in the cabbage (<0.001-0.029 ppm), soil samples (0.007-0.008 ppm) and water samples (<0.0005 ppm) were all below international guideline limits (ASEAN maximum level of 0.5 ppm deltamethrin in cabbage, EC ecologically accepted concentration of 1290 mg deltamethrin/kg soil, and a maximum limit of 0.0025 ppm deltamethrin according to Canadian water quality, respectively). Inspite of the low concentrations detected in cabbage, soil and water samples, an extensive pesticide monitoring on environmental samples within the area is advisable. This will help the adoption of an efficient risk assessment strategy to inform appropriate interventions.
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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".