2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      In-depth profiling of carboxyl compounds in Chinese Baijiu based on chemical derivatization and ultrahigh-performance liquid chromatography coupled to high-resolution mass spectrometry

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Highlights

          • A systematic strategy for detection and annotation of carboxyl compound was developed.

          • 197 carboxyl compounds were detected in Chinese Baijiu for the first time.

          • Annotation was based on MS1, t R, in-silico MS/MS, and characteristic fragments.

          • Three of carboxyl compounds were newly identified in Chinese Baijiu.

          • Distribution of carboxyl compounds in Baijiu with different flavors was revealed.

          Abstract

          Carboxyl compounds have a significant influence on the flavor of Chinese Baijiu. However, because of the structural diversity and low concentration, the deep profiling of carboxyl compounds in Chinese Baijiu is still challenging. In this work, a systematic method for comprehensive analysis of carboxyl compounds in Chinese Baijiu was established. After derivatized under optimized conditions, 197 p-dimethylaminophenacyl bromide-derived carboxylic compounds were annotated by multidimensional information including accurate mass, predicted t R, in-silico MS/MS, and diagnostic ions for the first time. In addition, 48 of the 197 carboxyl compounds were positively identified, and three of them were newly identified in Chinese Baijiu. Moreover, we found the number and the concentration of carboxyl compounds in sauce-flavor Baijiu were more abundant than in strong-flavor Baijiu. This work provides a novel method for the analysis of carboxyl compounds in Baijiu and other complex samples.

          Related collections

          Most cited references35

          • Record: found
          • Abstract: not found
          • Article: not found

          The Discovery of Polyacetylene Film: The Dawning of an Era of Conducting Polymers (Nobel Lecture)

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            CFM-ID 4.0: More Accurate ESI-MS/MS Spectral Prediction and Compound Identification.

            In the field of metabolomics, mass spectrometry (MS) is the method most commonly used for identifying and annotating metabolites. As this typically involves matching a given MS spectrum against an experimentally acquired reference spectral library, this approach is limited by the coverage and size of such libraries (which typically number in the thousands). These experimental libraries can be greatly extended by predicting the MS spectra of known chemical structures (which number in the millions) to create computational reference spectral libraries. To facilitate the generation of predicted spectral reference libraries, we developed CFM-ID, a computer program that can accurately predict ESI-MS/MS spectrum for a given compound structure. CFM-ID is one of the best-performing methods for compound-to-mass-spectrum prediction and also one of the top tools for in silico mass-spectrum-to-compound identification. This work improves CFM-ID's ability to predict ESI-MS/MS spectra from compounds by (1) learning parameters from features based on the molecular topology, (2) adding a new approach to ring cleavage that models such cleavage as a sequence of simple chemical bond dissociations, and (3) expanding its hand-written rule-based predictor to cover more chemical classes, including acylcarnitines, acylcholines, flavonols, flavones, flavanones, and flavonoid glycosides. We demonstrate that this new version of CFM-ID (version 4.0) is significantly more accurate than previous CFM-ID versions in terms of both EI-MS/MS spectral prediction and compound identification. CFM-ID 4.0 is available at http://cfmid4.wishartlab.com/ as a web server and docker images can be downloaded at https://hub.docker.com/r/wishartlab/cfmid.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Determination of phenolic compounds in aromatic plants by RP-HPLC and GC-MS

                Bookmark

                Author and article information

                Contributors
                Journal
                Food Chem X
                Food Chem X
                Food Chemistry: X
                Elsevier
                2590-1575
                07 September 2022
                30 October 2022
                07 September 2022
                : 15
                : 100440
                Affiliations
                [a ]Key Laboratory of Chemical Biology and Traditional Chinese Medicine Research (Ministry of Education of China), Key Laboratory of Phytochemical R&D of Hunan Province, Hunan Normal University, Changsha 410081, China
                [b ]CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
                [c ]Liaoning Province Key Laboratory of Metabolomics, Dalian 116023, China
                [d ]School of Computer Science & Technology, Dalian University of Technology, Dalian 116024, China
                Author notes
                [* ]Corresponding authors at: CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China. mingma@ 123456hunnu.edu.cn xugw@ 123456dicp.ac.cn
                Article
                S2590-1575(22)00238-3 100440
                10.1016/j.fochx.2022.100440
                9532792
                aa08de66-82f0-4d8a-b295-9bb10664042a
                © 2022 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 5 August 2022
                : 29 August 2022
                : 2 September 2022
                Categories
                Analytical Methods

                high-coverage analysis,carboxyl compounds,chinese baijiu,chemical derivatization,high-resolution mass spectrometry

                Comments

                Comment on this article