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In order to investigate the effect of inoculated fermentation with different Aspergillus strains on the umami taste of Liuyang Douchi, the differences in the umami taste and protein degradation of Liuyang Douchi fermented naturally (NF) or by four dominant Aspergillus flavus strains isolated from Douchi (A. flavus 7214, A. flavus 7622, A. flavus 6112, and A. flavus 5322) alone and their mixture in an equal proportion (M4) were compared. The results showed that the major protease produced by each of the four strains was serine proteases, and A. flavus 5322 had the strongest protease activity, with significantly higher activity of acidic protease than the other three strains. The contents of amino acid nitrogen and water-soluble protein in Aspergillus fermented Douchi were higher than those in NF Douchi after the end of pile-fermentation stage. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis showed that the degradation trends of six proteins in Douchi were consistent, all of which exhibited rapid degradation during the pile-fermentation process. Additionally, the results of sensory evaluation and electronic tongue analysis showed that Douchi fermented by A. flavus 5322 showed the strongest umami taste, which significantly increased when compared with NF. Using ultra-high performance liquid chromatography-electrospray/quadrupole time-of-flight tandem mass spectrometry (UPLC-ESI-Q-TOF-MS/MS) combined with correlation and peptidomics analysis, a total of 43 potential umami peptides were identified. The total peak area of potential umami peptides in Douchi fermented by A. flavus 6112 was the highest, followed by A. flavus 5322 with little difference, significantly greater than that in NF Douchi. In summary, inoculated fermentation, especially with A. flavus 5322, could promote protein degradation and the release of potential umami peptides, thereby enhancing the umami taste of Liuyang Douchi. This study will provide theoretical guidance for improving the umami taste of Liuyang Douchi and development of industrial production strains.

Food safety incidents caused by pesticide residues are threatening the life and health of people. At present, pesticide residues in food samples are miscellaneous, low and unknown to testing personnel and thus difficult to detect. Therefore, it is of great significance to develop high-throughput and non-targeted for the detection of pesticide residues in food samples. Chromatography-mass spectrometry has been widely used in the field of pesticide residue detection because of its advantages of high separation and identification efficiency as well as high-throughput and non-targeted nature. This paper summarizes the literature on high-throughput and non-targeted detection of pesticide residues in food samples by chromatography-mass spectrometry in the past 10 years. The current status of multi-pesticide residue detection in food samples is briefly described. Besides, this paper focuses on the application of chromatography-mass spectrometry in the detection of pesticide residues in food samples from the perspectives of the development of multidimensional chromatography and high-resolution mass spectrometry, the improvement of sorbent materials and sample pretreatment techniques, and the optimization of chemometric algorithms. Some suggestions for the problems existing in this field of research are put forward aiming to provide a new reference for the application of chromatography-mass spectrometry in the detection of multi-pesticide residues in food samples.

The aroma components of two grades of Huangjincha tea 2 were investigated by using headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) to establish their aroma fingerprints. The results were analyzed using chemometrics. Totally 81 aroma components were identified, 41 of which were common to both. Based on these common aroma components, the two grades could be discriminated by orthogonal partial least squares-discrimination analysis (OPLS-DA), and nine differential aroma components between them were identified including heptanal, limonene, trans-β-ocimene, 1-octanol, (E)-4,8-dimethylnona-1,3,7-triene, trans-nerolidol, 1,10-diepicubenol, epicubenol, and methyl hexadecanoate. A linear discriminant model to distinguish the two grades was established using the differential aroma components as independent variables. The self-validation and cross-validation accuracy of this model were 100%. These results may provide an objective and quantitative reference for the classification of Huangjincha 2.