Dispersive-solid phase extraction of diniconazole from water and fruit juice samples using MnCoCu-LDHs@MOF-235 nanocomposite


SALAMAT Q., Elzain Hassan Ahmed H., GÜMÜŞ Z. P., SOYLAK M.

Microchemical Journal, cilt.205, 2024 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 205
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1016/j.microc.2024.111239
  • Dergi Adı: Microchemical Journal
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, CAB Abstracts, Chemical Abstracts Core, Chimica, Food Science & Technology Abstracts, Index Islamicus, Veterinary Science Database
  • Anahtar Kelimeler: Nanocomposite, Diniconazole, Liquid chromatography, Central composite design, Greenness, Layer double hydroxides, Metal organic frameworks
  • Erciyes Üniversitesi Adresli: Evet

Özet

In this study, a new, affordable, and promising adsorbent based on MnCoCu-LDHs@MOF-235(Fe) nanocomposite was successfully synthesized, characterized, and utilized for the solid phase extraction of diniconazole (DNC) pesticide from water and food samples before it was determined by liquid chromatography. The structural characteristics of the synthesized nanocomposite were confirmed by various techniques, including FTIR, XRD, FE-SEM, and FE-SEM-EDX. The central composite design (CCD) technique was used for multi-response optimization of effective parameters including the sample solution's pH (6.0), adsorbent amount (15 mg), adsorption time (5 min), sample volume (30 mL) and eluent volume (2.5 mL), and desorption time (3 min) to achieve optimum extraction efficiency. Under optimal conditions, the method's analytical performance was assessed. The results showed that the calibration graphs showed linearity for DNC in the range of 1.3–500 µg L−1, with a detection limit of 0.4 µg L−1 and a correlation coefficient of 0.9988. Additionally, 2.9 intra-day RSD, 6.1 inter-day RSD, 12.0 preconcentration factor, and 2.53–11.53 enrichment factors was attained. The performance of the method to extract DNC from nine different real samples was realized with high relative recoveries (88.0–108 %). In addition, the greenness of the method was assessed with the AGREE metric tool, confirming that the method is environmentally friendly.