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Record W4389094794 · doi:10.1201/9781003412236-5

Herbicide Contamination in Ground Water and Their Probable Remediation

2023· book-chapter· en· W4389094794 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueApple Academic Press eBooks · 2023
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsContaminationEnvironmental remediationEnvironmental scienceGroundwaterWater contaminationWaste managementEnvironmental chemistryEnvironmental engineeringEngineeringChemistryBiologyEcologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Herbicides become integral components in modern agriculture as it offers low cost solution to manage weed flora both crop and non-crop field. Currently, promotion of conservation agriculture (CA)-based crop cultivation practices solely depends on herbicides to counter weeds. Herbicides were dominant agricultural chemicals used for crop protection purpose and also used in higher quantities compared to others. There is large volume of research articles on persistence of herbicides in soil had been done published so far. But information on herbicide residues in ground water is scanty and majority of the studies were reported from USA, Canada, and European countries. Major citations on the presence of herbicide residues dominated by triazine (atrazine, simezine, and metribuzin), chlor acetanilides (alachlor, metalochlor, and acetachlor), phenoxy alkalonic acid (2,4-D), and organo 112phosphate (glyphosate) group of herbicides and along with their degraded products. Spatial and temporal variation of herbicide residue content in ground water was well documented by many researchers. It was observed that herbicide residues present in ground water in ranged below or more than maximum acceptable concentration (MAC) set by European Union (0.1 µg L−1). The presence of herbicide residues more than MAC level in drinking water may cause health hazard also reported from many countries like Peru, Argentina, and Sri Lanka, etc. There is necessity of strong regulatory body for monitoring of herbicide residues in ground water in each and every country. Thus, future research should be focused to minimize herbicide residue load in soil, water, and ecosystem. In this chapter, we have highlighted on the presence of herbicide residues in ground water reported from across the world, factors involved and way out pathways. Among the different methods of remediation of herbicide residue in ground water, preventive measures such as selection of appropriate herbicide, proper mixing & application procedure, prevention of runoff, and irrigation management are of sustainable approach. Phytoremediation is of widely used method amid different ground water remediation techniques. Bacterial (Comamonadaceae and Sphingomonadales) and algal (Scenedesmus species) degradation were also found effective for treatment of herbicidal ground water contamination. Apart from this, a new nano-remediation technique was found effective for remediation of atrazine and bromacil in ground water.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.743
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.226
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it