Determination of trichlorfon using a molecularly imprinted electrochemiluminescence sensor on multi-walled carbon nanotubes decorated with silver nanoparticles.

Considering the limitations associated with existing methods for the detection of trace amounts of trichlorfon, this paper proposes a novel molecularly imprinted electrochemiluminescence (ECL) sensor for the detection of trichlorfon by utilizing the double enhancement effect of trichlorfon and Ag nanoparticles supported by multi-walled carbon nanotubes (MWCNTs/Ag NPs) in a luminol-H2O2 ECL system. Here, trichlorfon was electropolymerized on the surface of the MWCNT/Ag NP-modified gold nanoelectrode with o-phenylenediamine to prepare the molecularly imprinted polymer-based sensor. After eluting the trichlorfon, imprinted holes for the identification of trichlorfon were retained on the sensor, which were used as signal switches to obtain different ECL intensities through the adsorption of different concentrations of trichlorfon. The ECL signal of the sensitized luminol-H2O2 was doubly enhanced by the MWCNTs/Ag and trichlorfon, improving the sensitivity of the sensor. The trichlorfon concentration was positively correlated with the enhanced ECL intensity of the sensor in the range 5.0 × 10-8-5.0 × 10-11 mol L-1, and the detection limit of trichlorfon was 3.9 × 10-12 mol L-1. Moreover, the proposed sensor was successfully applied to the detection of trichlorfon residues in real samples, and the recovery ranged between 91.8 and 109%. A molecularly imprinted electrochemiluminescence sensor for trichlorfon detection by utilizing the double enhancement effect of trichlorfon and Ag nanoparticles supported by multi-walled carbon nanotubes in a luminol-H2O2 ECL system. The dual enhancement of the ECL signal improved the sensitivity of the sensor.

Development of a novel green tea quality roadmap and the complex sensory-associated characteristics exploration using rapid near-infrared spectroscopy technology.

Nondestructive instrumental identification of the green tea quality instead of professional human panel tests is highly desired for industrial application recently. The special flavor is a key quality-trait that influence consumer preference. However, flavonoids, as well as sensory-associated compounds, which play a critical role in the quality-traits profile of green tea samples have been poorly investigated. In this study, we were proposing an objective and accurate near infrared spectroscopy (NIRS) profile to support quality control within the entire green tea sensory evaluation chain, the complexity of green tea samples' sensory analysis was performed by two complementary methods: the standard calculation and the novel NIRS roadmap coupled with chemometrics. The green tea samples' physical quality, gustatory index, and nutritional index were measured respectively, which taking into consideration the gustatory evaluation of green tea for five commercially representative overall quality ("very bad", "bad", "regular", "good" and "excellent"). Our findings highlight the underexplored role of NIRS in chemical-to-sensory relationships and its widespread importance and utility in green tea quality improvement. Collectively, the comprehensive characterization of sensory-associated attribution allowed the identification of a wide array of spectrometric features, mostly related to moisture, soluble solids (SS), tea polyphenol (TPP), epigallocatechin gallate (EGCG), epicatechin (EC) and tea polysaccharide (TPS), which can be used as putative biomarkers to rapidly evaluate the green tea flavor variations related to rank differences. Otherwise, the NIRS' data were split into the calibration (n = 80) and prediction (n = 40) set independently, which showed high correlation coefficient with Rp-values of 0.9024, 0.9020 in physical and total cup quality, respectively. In this research, we demonstrated that NIRS was an easily-generated strategy and able to close the loop to feedback into the process for advanced process control. However, the established models should be improved by more green tea samples from different regions.