Determination of Paraquat (Herbicide) Residue Level in Sandy Clay Loam Soil Using High Performance Liquid Chromatography
Bibliographic record
Abstract
Pesticide is considered as the most widely used form of agricultural chemical. Pesticide residue is the remaining pesticide on or in soil after pesticide is applied on agriculture soil. Soil is a component that is crucial to life. The research purposely concerned on major effects that could be contributed from medium to unlimited application of pesticide. The soil samples were systematically collected from 5 plots and Paraquat residues concentrations were determined in dissimilar depth of soil layers. The herbicide used was Paraquat that contained Paraquat Dichloride. High Performance Liquid Chromatography (HPLC) analysis detected the peak area volumes of Paraquat in soil samples at level ranging from 0.3 to 5.9 mg/l. The concentration of Paraquat in sandy clay loam soil showed that herbicide leached downward to the depth of 15 cm. The maximum concentration of Paraquat residue was detected at 0 to15 cm of soil depth at 2.783 mg/l. In highly organic soils, adsorption is weaker and Paraquat remains herbicidally active for longer, up to 29 days in one trial on soil with 98% organic matter [1]. Oral dose, LD50 for human is equal to 40-60 mg/kg [2] while the lowest fatal dose recorded for human was 17 mg/kg, but even lower doses may be fatal for children [3].
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 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 | 0.001 | 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) | 0.001 | 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".