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DOI 10.1039/d6ay00924g

Медицинская библиотека · Analytical methods : advancing methods and applications · 2026

Extraction method prior to HPLC-DAD analysis for halauxifen-methyl herbicide in water.

Maria Silva Santos Brenda, Soares Sandro Braga, Sicupira Lazaro Chaves, Pinho Gevany Paulino de, Silvério Flaviano Oliveira

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Аннотация

Halauxifen-methyl is a new pre-emergent herbicide used to control weeds in corn and soybean crops. Although its use and commercialization have recently been authorized in Brazil, studies involving the development of extraction methods for this herbicide are still rare. Therefore, the present study aimed to optimize and validate liquid-liquid extraction with low-temperature partitioning (LLE-LTP) to determine halauxifen-methyl in water using high-performance liquid chromatography with diode array detection (HPLC-DAD). The optimal chromatographic conditions were acetonitrile and water (80 : 20 v/v) as the mobile phase, Kinetex column, flow of 0.2 mL min-1, injection volume of 10 µL and 250 nm as wavelength. The best extraction conditions were 4 mL of sample, acetonitrile and dichloromethane (7.5 : 0.5 v/v) as the extracting phase, with the addition of 0.2 g of NaCl salt and 90 min for freezing. The method validation showed that LLE-LTP was selective, precise, accurate, with a quantification limit of 0.448 µg L-1, linearity range of 0.448 to 120 µg L-1 and matrix effect of -11.19%. The study also revealed that the half-life of this herbicide in water is 6 days under sunlight and close to 50 days in the absence of sunlight. LLE-LTP proved to be efficient for monitoring halauxifen-methyl in water. The Analytical Eco-Scale metric assessment revealed it reached 84 points, meaning this method is classified as an excellent green analysis technique.

Для цитирования: Maria Silva Santos Brenda, Soares Sandro Braga, Sicupira Lazaro Chaves, Pinho Gevany Paulino de, Silvério Flaviano Oliveira. Extraction method prior to HPLC-DAD analysis for halauxifen-methyl herbicide in water.. Analytical methods : advancing methods and applications. 2026. DOI: 10.1039/d6ay00924g.
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