Dissipation, half-lives, and mass spectrometric identification of endosulfan isomers and the sulfate metabolite on three field-grown vegetables
Bibliographic record
Abstract
Endosulfan 3 EC, a mixture of α- and β-stereo isomers, was sprayed on field-grown pepper, melon, and sweet potato plants at the recommended rate of 0.44 kg A.I. acre(-1). Plant tissue samples (leaves, fruits, or edible roots) were collected 1 h to 30 days following spraying and analyzed for endosulfan isomers (α- and β-isomers). Analysis of samples was accomplished using a gas chromatograph (GC) equipped with a mass detector in total ion mode. The results indicated the formation of endosulfan sulfate as the major metabolite of endosulfan sulfite and the relatively higher persistence of the β-isomers as compared to the α-isomer. The initial total residues (α- and β-isomers plus endosulfan sulfate) were higher on leaves than on fruits. On pepper and melon fruits, the α-isomer, which is the more toxic to mammals, dissipated faster (T(1/2) = 1.22 and 0.95 d, respectively) than the less toxic β-isomer (T(1/2) = 3.0 and 2.5 d, respectively). These results confirm the greater loss of the α-isomer compared to the β-isomer, which can ultimately impact endosulfan dissipation in the environment. Additionally, the higher initial residues of endosulfan on pepper and sweet potato leaves should be considered of great importance for timing field operations and the safe entry of harvesters due to the high mammalian toxicity of endosulfan.
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 | 0.000 | 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) | 0.001 | 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".