Pesticide concentrations in multiple physical and biological stream matrices are impacted by a bioenergy production facility receiving pesticide-coated corn seeds
Bibliographic record
Abstract
Insecticide and fungicide seed coatings have become prevalent in conventional agriculture in recent decades. From 2015-2021, the AltEn bioenergy plant (Mead, Nebraska, USA) generated ethanol from almost 100% unused/expired treated corn seeds. This use of these seeds for ethanol production resulted in the accumulation of large amounts of contaminated wastewater and solid residue, a portion of which was applied to surrounding farmland. To better understand the potential long-term environmental effects from the processing of treated seeds at this facility, five nearby stream sites were sampled in 2022 after the closure of the plant; these included two sites directly affected by AltEn, one upstream and two downstream of the affected sites. Water and sediment were collected in March through July, and algae and fish samples were collected in July for chemical analysis. Overall, 60 pesticide compounds (parents and transformation products) were detected in one or more matrices, including 23 fungicides, 20 insecticides, 16 herbicides, and one bacterial growth inhibitor. Pesticide results (maximum detection frequency, maximum concentration) varied substantially by environmental compartment: water (100% multiple pesticides, 4,600 ng L-1 thiamethoxam transformation product [NOA-407475]), algae (100% multiple pesticides, 190 ng g-1 atrazine), sediment (60% dithiopyr, 2.3 ng g-1 acetochlor), and fish (20% pyraclostrobin, 2.2 ng g-1 atrazine). Pesticides associated with treated corn seeds (e.g., insecticides clothianidin and thiamethoxam, fungicides fluoxastrobin and thiabendazole) were detected at significantly higher concentrations (p < 0.05) in stream water from sites affected by the AltEn facility compared with nonaffected sites. Study results indicate that pesticides associated with the AltEn facility continue to be a source of contaminants to aquatic systems after the plant's closure in 2021.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".