Qiao-Ying Chang
Yanshan University
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Featured researches published by Qiao-Ying Chang.
Analytical Methods | 2015
Zhibin Wang; Qiao-Ying Chang; Jian Kang; Yan-Zhong Cao; Na Ge; Chunlin Fan; Guo-Fang Pang
Efficient analysis of large amounts of raw data for detection and identification of chemical adulterants is always a difficult challenge in the field of food safety. The present study proposed a combined strategy for qualitative screening and identification of 317 pesticides in vegetables and fruits using high performance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (HPLC-Q-TOF/MS) based on a homemade accurate mass database (MS1) and a novel MS/MS spectral library (MS2). An accurate mass database and a collision-induced-dissociation (CID) accurate mass spectral library were developed prior to actual application. The screening strategy involved two injections of each sample extract. Firstly, HPLC-Q-TOF/MS in full MS scan mode was conducted and all potential compounds in the MS1 database were matched against the raw data of samples for target screening. Secondly, targeted MS/MS analysis was carried out by using hybrid Q-TOF/MS and the fragment ions were identified by the MS2 spectral library. To validate the performances of the in-house MS1 database and the MS2 spectral library, cucumber and orange matrices were prepared by traditional solid phase extraction, spiked with 317 pesticides at three concentration levels, 1, 10 and 50 μg kg−1 for most of the pesticides, and analyzed by HPLC-Q-TOF/MS. The results showed that over 83.9% of pesticides at 10 μg kg−1 or lower could be detected by TOF/MS combined with the MS1 database, and 76.7% of them could be identified by targeted MS/MS coupled with the MS2 library in each matrix. The total false negative rate of the proposed qualitative screening method was as low as 4.7% at 50 μg kg−1. Consequently, the proposed method was applied to 328 real fresh vegetables and fruits. Finally, 57 pesticides and 799 positive results were found. The approach to detect and to identify pesticides based on the accurate mass database integrated CID accurate mass spectral library was proved to be a cost-effective and powerful strategy for routine qualitative screening of pesticides.
Journal of AOAC International | 2015
Xi Chen; Yan Li; Qiao-Ying Chang; Xueyan Hu; Guo-Fang Pang; Chun-Lin Fan
This paper describes a comparative study of the influence of three sample preparation techniques (M1: hydration+oscillating extraction+partial extraction solution hexane partitioning cleanup; M2: hydration+oscillating extraction+overall extraction solution SPE cleanup; and M3: pure acetonitrile homogeneous extraction+overall extraction SPE cleanup) on the determination efficiency of 456 pesticide multiresidues in tea. First, it was discovered from the mathematical correlation equation of 329 pesticide recoveries established and log Kow values that the extraction efficiency of hydration method M1 has obvious correlation with pesticide log Kow, making the extraction efficiency of M1 take the shape of an arc trend line with a certain arc hanging down from both ends of polar pesticides and nonpolar pesticides. Second, regarding the M1 method, the interfering matter after co-extraction increased in large quantities, which markedly lowered the S/N of the target pesticides and method sensitivity, leading to an obvious decrease of the method efficiency. The fortification experiment of the uniform limit 0.010 mg/kg proved that with the M1 hydration method there are 23 pesticides with recoveries between 70 and 120% and RSD<20%, accounting for only 5.0%, while with nonhydration method M3 there are 229 pesticides, making up 50%.
Analytical Methods | 2018
Zhibin Wang; Yan Li; Qiao-Ying Chang; Jian Kang; Guo-Fang Pang
A strategy for the quantification and confirmation of 40 multi-class veterinary drugs in honey by QuEChERS (quick, easy, cheap, effective, rugged, and safe) combined with liquid chromatography coupled quadrupole time-of-flight mass spectrometry (LC-Q-TOF/MS) is described. The veterinary drugs examined belong to four classes: quinolones, sulfonamides, macrolides, and tetracyclines. Before analysis by LC-Q-TOF/MS, the sample was diluted with a solution of Na2EDTA-McIlvaine buffer solution (0.1 M, pH = 4), extracted with 5% acetic acid in acetonitrile, and cleaned up with an NH2 sorbent. The average recoveries for the majority of analytes (86.9%), based on matrix-matched external calibration curves, were between 70% and 120%, and there was no significant difference in the recoveries between different honey matrices. The repeatability and reproducibility of the method expressed as the RSDs were less than 20% for all analytes. The data acquired by LC-Q-TOF/MS were cross-referenced with an accurate mass database of veterinary drugs, and the suspected analytes were finally confirmed based on a full product ion library match. Compared with the low-resolution MS technique, obvious advantages were obtained in terms of confirmation and identification by LC-Q-TOF/MS. The applicability of the method was verified by applying it to 12 different honey samples, and ciprofloxacin residue (at 99.7 μg kg−1) was detected in one sample.
Journal of AOAC International | 2015
Guo-Fang Pang; Chun-Lin Fan; Yan-Zhong Cao; Fang Yan; Yan Li; Jian Kang; Hui Chen; Qiao-Ying Chang
Thirty laboratories from fom North and South America, Europe, and Asia participated in this AOAC collaborative study (15 from China; five from Germany; two each from Italy and the United States; and one each from the Republic of Korea, Canada, Spain, Japan, Belgium, and India). Participants represented government regulatory, commercial testing, university, research institute, and private laboratories. The single-laboratory validated (SLV) tea method was evaluated in the collaborative study to determine the recovery and reproducibility of the method under multilaboratory conditions. Since there were no restrictions regarding the type of analytical instrumentation to use for the analyses, laboratories used a combination of equipment that included GC/MS, GC/MS/MS, and LC/MS/MS instruments from 22 different manufacturers, 21 brands of GC and LC columns, 13 different GC temperature programming profiles, 11 LC gradient elution programs, and six different vendor manufactured SPE cartridges. Even though all the analytical performance parameters for all the 653 compounds had been determined in the SLV study, guidance was obtained from an expert review panel of the AOAC Method-Centric Committee on Pesticide Residues to conduct the multilaboratory collaborative study based on 20 selected compounds that can be analyzed by GC/MS and 20 compounds that can be analyzed by LC/MS/MS. Altogether, 560 samples covering the 40 selected pesticides were analyzed in the study. These samples included green tea and oolong tea samples fortified typically at the European Union maximum residue limit for regulatory guidance and compliance, aged tea samples incurred with 20 pesticides, and green tea and oolong tea samples incurred with five pesticides. The analysis of the 560 samples generated a total of 82 459 test results by the 30 participating laboratories. One laboratory failed to meet the proficiency requirements in the precollaborative study. Therefore, its data submitted for the collaborative study were excluded from further analysis and interpretation. The results presented are therefore the 6638 analytical results obtained from the 29 remaining laboratories, which included 1977 results generated by GC/MS, 1704 results by GC/MS/MS, and 2957 results by LC/MS/MS. It was determined after application of the Grubbs and Dixon tests for outliers to the data sets that there were 65 outlier results from the 1977 GC/MS results (3.3%), 65 outlier results from the 1704 GC/MS/MS results (3.8%), and 57 outlier results out of 2957 LC/MS/MS results (1.9%), representing 0.98, 0.98, and 0.86%, respectively, of the 6638 results generated in the study. Analysis with the AOAC statistical software package also confirmed that the method is rugged, and average recovery, average concentration, RSDr, RSDR, and HorRat values all meet recovery and reproducibility criteria for use in multiple laboratories. The Study Director is recommending this method for adoption as an AOAC First Action Official MethodSM.
Journal of AOAC International | 2011
Guo-Fang Pang; Chun-Lin Fan; Zhang F; Yan Li; Qiao-Ying Chang; Yan-Zhong Cao; Yongming Liu; Zeng-Yin Li; Wang Qj; Xueyan Hu; Liang P
Journal of AOAC International | 2013
Chun-Lin Fan; Qiao-Ying Chang; Guo-Fang Pang; Zeng-Yin Li; Jian Kang; Guo-Qing Pan; Shu-Zhan Zheng; Wenwen Wang; Cui‐Cui Yao; Xin‐Xin Ji
Journal of AOAC International | 2013
Guo-Fang Pang; Chun-Lin Fan; Qiao-Ying Chang; Yan Li; Jian Kang; Wenwen Wang; Jing Cao; Yan-Bing Zhao; Nan Li; Zeng-Yin Li; Zongmao Chen; Fengjian Luo; Zheng-Yun Lou
Analytical and Bioanalytical Chemistry | 2016
Zhibin Wang; Yan-Zhong Cao; Na Ge; Xiaomao Liu; Qiao-Ying Chang; Chunlin Fan; Guo-Fang Pang
Journal of AOAC International | 2015
Chun-Lin Fan; Yan Li; Qiao-Ying Chang; Guo-Fang Pang; Jian Kang; Jing Cao; Yan-Bing Zhao; Nan Li; Zeng-Yin Li
High-Throughput Analysis for Food Safety | 2014
Yan-Zhong Cao; Yongming Liu; Na Wang; Xin‐Xin Ji; Cui‐Cui Yao; Xiang Li; Lili Shi; Qiao-Ying Chang; Chun‐Lin Fan; Guo-Fang Pang