Xiaoyue Yue

Dr. Xiaoyue Yue


Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2019 in Food Chemistry
Verified
Journal Article
Closed access
Xiaoyue YueXiaoyue Yue
Xiaoyue Yue
XLXiaoyu Luo
Xiaoyu Luo
ZZZijun Zhou
Zijun Zhou
YBYanhong Bai
Yanhong Bai

9 October 2022 in Foods
Verified
Journal Article
Open access
PDF file
Xiaoyue YueXiaoyue Yue
Xiaoyue Yue
CWChaoyun Wu
Chaoyun Wu
ZZZijun Zhou
Zijun Zhou
LFLong Fu
Long Fu
YBYanhong Bai
Yanhong Bai
Rapid, facile, and accurate detection of antibiotic residues is vital for practical applications. Herein, we designed a sensitive, visual, and rapid analytical method for sensitive detection of ciprofloxacin and chloramphenicol based on a nanosized rod-shaped Europium metal organic framework (Eu-MOF). The fluorescent Eu-MOF was firstly synthesized by a simple synthetic route at room temperature, which displays a red emission. The mechanisms of detecting ciprofloxacin and chloramphenicol were confirmed to be the inner filter effect (IFE) and photoinduced electron transfer (PET). Under the optimized experimental conditions, the detection limits of the developed method for ciprofloxacin and chloramphenicol detection were 0.0136 and 3.16 μM, respectively. Moreover, the sensor was effectively applied for quantitative determination of ciprofloxacin and chloramphenicol milk samples with satisfactory recoveries of 94.5–102% and 97–110%, respectively. This work developed a new method for rapid detection of ciprofloxacin and chloramphenicol residues. In addition, the established method has potential practical application value for on-site safety regulation on antibiotic residues in animal-derived food.

26 September 2023 in Foods
Verified
Journal Article
Open access
PDF file
Xiaoyue YueXiaoyue Yue
Xiaoyue Yue
LFLong Fu
Long Fu
CWChaoyun Wu
Chaoyun Wu
SXSheng Xu
Sheng Xu
BYBai Yan-Hong
Bai Yan-Hong
As a commonly used food additive, sulfite (SO32−) is popular with food manufacturers due to the functions of bleaching, sterilizing, and oxidation resistance. However, excess sulfites can pose a threat to human health. Therefore, it is particularly important to achieve rapid and sensitive detection of SO32−. Herein, a colorimetric sensor was invented for visual, meticulous, and rapid detection of SO32− based on MIL-53(Fe/Mn). Bimetallic nanozyme MIL-53(Fe/Mn) was prepared by a one-pot hydrothermal reaction. The prepared MIL-53(Fe/Mn) can effectively catalyze the oxidation of colorless TMB to a blue oxidation product (oxTMB). The introduction of SO32− causes significant discoloration of the reaction system, gradually transitioning from a visible blue color to colorless. Hence, a sensitive colorimetric sensor for SO32− detection was developed based on the decolorization degree of the detection system. Further, the discoloration was ascribed to the inactivation of nanozyme and the strong reducing ability of SO32−. Under the optimal experimental conditions, there was a good linear relationship between the absorbance at 652 nm and SO32− concentration in the linear range of 0.5–6 μg mL−1 with a limit of detection (LOD) of 0.05 μg mL−1. The developed method was successfully applied to the detection of actual samples of white wine with good accuracy and recovery. Compared to traditional methods, this colorimetric sensor produces similar detection results but significantly reduces the detection time. Compared to traditional methods, this colorimetric sensor can not only reduce the detection costs effectively but also help the food industry maintain quality standards. Strong anti-interference capability, simple operation, and low detection limits ensure the excellent performance of the colorimetric sensor in detecting SO32− in white wine. The combination of a smartphone and a colorimetric analysis application has also greatly facilitated the semi-quantitative, visual on-site detection of SO32−, which has opened up an application prospect of an MIL-53(Fe/Mn)-based detection platform. Our work has indicated a new direction for the detection of SO32− and provided important assurance for food safety.