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Application of chemometric modeling for ionic liquid-based ultrasonic-assisted dispersive liquid-liquid microextraction: Analysis of fosetyl-aluminum in fruit and vegetable samples.

Authors :
Haq, Hameed Ul
Elik, Adil
Durukan, Hasan
Sarac, Handan
Demirbas, Ahmet
Boczkaj, Grzegorz
Gürsoy, Nevcihan
Altunay, Nail
Source :
Journal of Food Composition & Analysis. Dec2023, Vol. 124, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

This manuscript presents a new method for selective extraction and determination of fosetyl-aluminum in fruits and vegetable samples based on ultrasonic-assisted dispersive liquid-liquid microextraction method using ionic liquids (IL-UA-DLLME). A UV-Visible spectrophotometer was used for detection and quantification. Plants used for sample collection were grown under controlled conditions in a greenhouse. Central composite design (CCD)-response surface methodology (RSM) analysis was used for the optimization of significant factors (volume of IL, pH, ultrasonication time, and THF volume). Under optimal conditions, the limit of detection and limit of quantification of the IL-UA-DLLME procedure were 1.5 ng mL−1 and 5.0 ng mL−1 respectively with relative standard deviation 1.9–3.3%. The developed IL-UA-DLLME procedure demonstrated linearity within the concentration range of 5–600 ng mL−1 with an R2 value of 0.9914. The enrichment factor was 114 with a recovery% of 94.2–98.6% (n = 3) at optimal conditions. The IL-UA-DLLME assay was used for the analysis of fosetyl-aluminum in a variety of food samples and was found highly selective and efficient. [Display omitted] • Ionic liquid-based pre-concentration method for fosetyl-aluminum analysis in foods. • Increased mass transfer via DLLME for fungicide isolation from plant material. • Fully validated method with proved applicability to real samples and routine analysis. • A highly sensitive, selective, and robust assay for environmental monitoring. • Fast analyte isolation followed by spectroscopic final determination stage [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08891575
Volume :
124
Database :
Academic Search Index
Journal :
Journal of Food Composition & Analysis
Publication Type :
Academic Journal
Accession number :
172979700
Full Text :
https://doi.org/10.1016/j.jfca.2023.105725