2016
DOI: 10.1016/j.foodchem.2016.02.149
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An evaluation of the bioaccessibility of arsenic in corn and rice samples based on cloud point extraction and hydride generation coupled to atomic fluorescence spectrometry

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Cited by 31 publications
(3 citation statements)
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“…This might be associated with the increasing viscosity from SLNS1 (∼10 –3 Pa·s) to SLNS4 (∼10 0 Pa·s). It is commonly believed that liquid samples with higher viscosity would be more “sticky” on the devices inner wall and more difficult to aerosolize, resulting in a greater residue . Thus, the loaded sample should not be highly viscous (e.g., 10 1 Pa·s or higher) to minimize the residue.…”
Section: Resultsmentioning
confidence: 99%
“…This might be associated with the increasing viscosity from SLNS1 (∼10 –3 Pa·s) to SLNS4 (∼10 0 Pa·s). It is commonly believed that liquid samples with higher viscosity would be more “sticky” on the devices inner wall and more difficult to aerosolize, resulting in a greater residue . Thus, the loaded sample should not be highly viscous (e.g., 10 1 Pa·s or higher) to minimize the residue.…”
Section: Resultsmentioning
confidence: 99%
“…Cloud point extraction of metal ions requires complexation of metal ions with a suitable ligand. For example, ligands such as ammonium pyrrolidinedithiocarbamate [6][7][8] and O,O-diethyldithiophosphate [9][10][11] were used in CPE for As (III). For binding of As (V), ammonium molybdate, [12][13][14] acridine orange in combination with tartaric acid, [15] Pyronine B, [16,17] 2',7'dichlorofluorescein [18] were proposed.…”
Section: Introductionmentioning
confidence: 99%
“…Response surface methodologies (RSM) are multivariate optimization techniques, which allow for the finding of the critical conditions of the factors (maxima or minima) through the establishment of quadratic models [26]. Doehlert Matrix is one of the RSM that is often employed for optimization of analytical strategies [27,28]. This design has advantages compared to the other RSM because it allows for the obtaining of quadratic models, in which the number of levels of the factors is different, it has good efficiency, and also its matrix does not contemplate experiments with all factors in the positive or negative levels [29][30][31].…”
Section: Introductionmentioning
confidence: 99%