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Record W2997082414 · doi:10.1111/jfpe.13351

Effective removal of organophosphorus pesticide residues in tomatoes using natural extracts

2019· article· en· W2997082414 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Food Process Engineering · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Residue Analysis and Safety
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsDimethoatePesticideDichlorvosMalathionChemistryPesticide residueFood scienceLycopeneChlorpyrifosToxicologyPhytochemicalBiologyAgronomyCarotenoidBiochemistry

Abstract

fetched live from OpenAlex

Abstract The reduction efficiency of the extracts of Albizia amara and Acacia concinna against most widely used organophosphorus pesticides such as dimethoate, malathion, dichlorvos, and chlorpyrifos on tomato samples was investigated. The pesticide residues were quantified by gas chromatography with triple quadrupole mass spectrometer (GC‐MS/MS). The maximum reduction efficiency was achieved from the samples treated with 8% A. concinna extract on dichlorvos (87%) and dimethoate (84%) followed by 6% A. amara on malathion (83%) and chlorpyrifos (64%) and comparatively higher than water wash and it shows the reduction of only 14–38% for 15 min. The sensorial property and lycopene content of tomato samples were assessed and these plant extracts showed no significant effects on color, texture, and lycopene content after washing treatment. These phytochemical rich plant extracts exhibited greater reduction ability against pesticide residues without changing the nutritional and sensorial characteristics of the treated tomato samples. The current study may be a platform for formulating a cost‐effective, safe, and natural cleanser for the effective removal of pesticide residues in fruits and vegetables. Practical applications Presence of multiple pesticide residues in fruits and vegetables is a worldwide problem in food safety. Particularly, tomatoes are most often consumed without cooking, hence it is essential to estimate the pesticide reduction efficiency of the common washing procedure. Washing of tomatoes with chemical solutions to remove pesticide residues leads to additional chemical exposure. Therefore, the reduction efficiency of natural plant extracts such as Albizia amara and Acacia concinna on four pesticides (dimethoate, malathion, dichlorvos, and chlorpyrifos) was studied. The method for the analysis of pesticide using GC‐MS/MS was validated according to SANTE 11813/2017 to detect the pesticide residues in tomatoes after each washing treatment. This study showed that the natural extracts could be a good tool for the removal of multipesticide residues effectively from the tomatoes without compromising its nutritional and sensory properties. The pesticide decontamination with plant extracts was effective, economic and safe for household and commercial applications.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.649
Threshold uncertainty score0.212

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 science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.217
Teacher spread0.211 · 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