Characterisation of Neonicotinoid Insecticides in the Cocoa-producing Owena River Basin of Nigeria by a QuEChERS Method Coupled to Liquid Chromatography-Tandem Mass Spectrometry
Bibliographic record
Abstract
Background: Neonicotinoids (hereafter called “neonics”) are systemic insecticides used for the protection of agricultural crops. However, their dispersion in nature has been the subject of global concern due to reports of adverse effects on some living organisms. One of the applications of neonics in Nigeria is to protect the cocoa cash crop. Objective: Previous studies on pesticide-related pollution in Nigeria focused mainly on organochlorines, but research on neonics is sparse, and the knowledge gap needs to be filled. This work aimed at confirming the presence of four neonics, namely, imidacloprid, thiacloprid, acetamiprid, and thiamethoxam, within the Owena River Basin. Methods: Neonics were extracted from cocoa-growing soil, river water, and sediments by a modified QuEChERS method, followed by clean-up of the extractant by dispersive solid phase extraction and analysis by an optimized liquid chromatography/tandem mass spectrometry analytical procedure. The overall performance of these developed methods was then evaluated by set criteria. Results: The Limit of Detection (LOD) and Limit of Quantitation (LOQ) ranged from 0.0005 to 0.002 μg/g and 0.002 to 0.005 μg/g, respectively. The recovery for the four target analytes exceeded 75% across all matrices from laboratory-prepared samples. It was discovered that the average concentrations of three of the four neonics of interest in the individual media were: 10.34 nmol/g in cocoa-producing soil, 1.03 nmol/g in river sediment, and 1.08 nM (1.08 x 10 -3 nmol/g) in surface river water. No imidacloprid was identified in any of these three environmental compartments. Conclusion: The concentration of neonics in the river water, i.e ., 0.23 µg/L (230 ng/L), is identical to that of the maximum value recommended in the Canadian Water Quality Guidelines for the Protection of Freshwater Aquatic Life.
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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 | 0.014 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".