Headspace single drop microextraction based digital image colorimetry and ICP-MS for dual-mode analysis of sulfide in condiments and beverage samples.
Xiaoxiang Zhou, Chunhui Wu, Yang Zuo, Nuo Chen, Xiaojie Lin, Yi Zhang +3 more
Food chemistry
Abstract
In this work, a headspace single-drop microextraction (HS-SDME) based digital image colorimetry and inductively coupled plasma mass spectrometry (ICP-MS) dual-mode sensing platform was developed for portable or sensitive detection of sulfide, based on the bifunctionality of MnO2 nanosheets (NSs) as oxidant and chromogenic agent. MnO2 NSs were suspended as droplets to headspace extract and react with H2S generated by acidification of S2-. The color change could be directly read by a smartphone with RGB value, followed by the sensitive Mn2+ detection with ICP-MS, thus successfully constructing a dual-mode S2- sensing platform. Limit of detection for S2- based on colorimetry was calculated to be 1.3 μmol L-1, while it was as low as 1.2 nmol L-1 by ICP-MS. This method shown excellent selectivity among more than 30 interferents, thus it has been successfully utilized to analysis of condiments and beverage rich in salinity or small molecule organics, with recoveries of 90-109 %.