Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 163

The DOI matches its Crossref record.

A metabolomics-based approach investigates volatile flavor formation and characteristic compounds of the Dahe black pig dry-cured ham

Shi, Yanan, Li, Xiang, Huang, Aixiang·2019·Meat Science

Abstract

This study aimed to reveal the flavor formation and elucidate the key components responsible for the Dahe black pig dry-cured ham. In this study, 172 hams were processed using the traditional method, and volatile flavor compounds of 24 hams were investigated using gas chromatography-mass spectrometry (GC-MS) and comprehensive multivariate data analysis. 407 volatile flavor compounds were identified during total ripening process of hams, the amount of flavor components gradually increased with the increase in the processing period, reaching 187 species after ripening for 630 days. However, the principal flavor compounds had formed at 210 days for ripening. The most abundant flavor families were aldehydes and alcohols, moreover, hexanal, 3-methyl-butanal, nonanal, and octanal are the characteristics compounds of ham, which originated from oxidation of fatty acids and degradation of amino acids. Glycosaminoglycan biosynthesis pathway was strongly related with flavor compounds intense changed in 90-150 days.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.meatsci.2019.107904

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 48

  1. Ali, 2016, A comparative metabolomics approach reveals early biomarkers for metabolic response to acute myocardial infarction, Scientific Reports, 6, 36359, 10.1038/srep36359 · DOI
  2. Alonso, 2015, Analytical methods in untargeted metabolomics: State of the art in 2015, Frontiers Bioengineering and Biotechnology, 3, 23, 10.3389/fbioe.2015.00023 · DOI · Paper page
  3. Aparicio, 1996, Relationship between volatile compounds and sensory attributes of olive oils by the sensory wheel, Journal of Agricultural and Food Chemistry, 73, 1253
  4. Bolzoni, 1996, Changes in volatile compounds of parma ham during maturation, Meat Science, 43, 301, 10.1016/S0309-1740(96)00002-2 · doi:10.1016/s0309-1740(96)00002-2
  5. Buscailhon, 1994, Relations between compositional traits and sensory qualities of French dry-cured ham, Meat Science, 37, 229, 10.1016/0309-1740(94)90083-3 · DOI
  6. Carrapiso, 2004, Iberian ham headspace: Odorants of intermuscular fat and differences with lean, Journal of the Science of Food and Agriculture, 84, 2047, 10.1002/jsfa.1911 · doi:10.1002/jsfa.1911
  7. Coutron-Gambotti, 1999, Lipolysis and oxidation in subcutaneous adipose tissue during dry-cured ham processing, Food Chemistry, 64, 95, 10.1016/S0308-8146(98)00079-X · doi:10.1016/s0308-8146(98)00079-x
  8. Du, 2001, Volatile substances of Chinese traditional Jinhua ham and cantonese sausage, Journal of Food Science, 66, 827, 10.1111/j.1365-2621.2001.tb15181.x · doi:10.1111/j.1365-2621.2001.tb15181.x
  9. Fan, 2018, Classification of Chinese wine varieties using 1H NMR spectroscopy combined with multivariate statistical analysis, Food Control, 88, 113, 10.1016/j.foodcont.2017.11.002 · doi:10.1016/j.foodcont.2017.11.002
  10. Feng, 2016, Mechanisms of volatile production from amino acid esters by irradiation, Food Research International, 81, 100, 10.1016/j.foodres.2016.01.006 · DOI
  11. Flores, 1997, Correlations of sensory and volatile compounds of Spanish “Serrano” dry-cured ham as a function of two processing times, Journal of Agricultural and Food Chemistry, 45, 2178, 10.1021/jf960862c · doi:10.1021/jf960862c
  12. Garcia, 1991, Volatile components of dry cured Iberian ham, Food Chemisty, 41, 23, 10.1016/0308-8146(91)90128-B · doi:10.1016/0308-8146(91)90128-b
  13. Gaspardo, 2008, Determination of volatile compounds in San Daniele ham using headspace GC-MS, Meat Science, 80, 204, 10.1016/j.meatsci.2007.11.021 · doi:10.1016/j.meatsci.2007.11.021
  14. Heude, 2016, Metabolic characterization of caviar specimens by 1H NMR spectroscopy: Towards caviar authenticity and integrity, Food Analytical Methods, 9, 3428, 10.1007/s12161-016-0540-4 · DOI
  15. Hinrichsen, 1995, Relationship among flavor, volatile compounds, chemical changes, and microflora in Italian-type dry-cured ham during processing, Journal of Agricultural and Food Chemistry, 43, 2932, 10.1021/jf00059a030 · doi:10.1021/jf00059a030
  16. Huan, 2005, Changes in flavor compounds of dry-cured Chinese Jinhua ham during processing, Meat Science, 71, 291, 10.1016/j.meatsci.2005.03.025 · doi:10.1016/j.meatsci.2005.03.025
  17. Huang, 2010, The study of ingredients and processing techniques of Xuanwei style ham, Journal of Food Processing and Preservation, 34, 136, 10.1111/j.1745-4549.2008.00329.x · doi:10.1111/j.1745-4549.2008.00329.x
  18. Huang, 2016, Traditional foods: General and consumer aspects, Vol. 10
  19. Khan, 2015, Meat flavor precursors and factors influencing flavor precursors—A systematic review, Meat Science, 110, 278, 10.1016/j.meatsci.2015.08.002 · DOI · Paper page
  20. Klevorn, 2018, A metabolomics-based approach identifies changes in the small molecular weight compound composition of the peanut as a result of dry-roasting, Food Chemistry, 240, 1193, 10.1016/j.foodchem.2017.08.058 · DOI
  21. Liang, 2018, Investigation on microbial diversity of industrial Zhacai paocai during fermentation using high-throughput sequencing and their functional characterization, LWT-Food Science and Technology, 91, 460, 10.1016/j.lwt.2018.01.088 · DOI
  22. Luna, 2006, A tentative characterization of white dry-cured hams from Teruel (Spain) by SPME-GC, Food Chemistry, 97, 621, 10.1016/j.foodchem.2005.05.039 · doi:10.1016/j.foodchem.2005.05.039
  23. Lyu, 2016, Proteomic analysis of scallop hepatopancreatic extract provides insights into marine polysaccharide digestion, Scientific Reports, 6, 34866, 10.1038/srep34866 · doi:10.1038/srep34866
  24. Mao, 2019, Label-free quantitative proteomic analysis of milk fat globule membrane proteins of yak and cow and identification of proteins associated with glucose and lipid metabolism, Food Chemistry, 275, 59, 10.1016/j.foodchem.2018.09.044 · doi:10.1016/j.foodchem.2018.09.044
  25. Muriel, 2004, Volatile compounds in Iberian dry-cured loin, Meat Science, 68, 391, 10.1016/j.meatsci.2004.04.006 · DOI · Paper page
  26. Narváez-Rivas, 2012, Analysis of volatile compounds from Iberian hams: A review, Grasas y Aceites, 63, 432, 10.3989/gya.070112 · DOI
  27. Narvaez-Rivas, 2011, Authentication of fattening diet of Iberian pigs according to their volatile compounds profile from raw subcutaneous fat, Analytical and Bioanalytical Chemistry, 399, 2115, 10.1007/s00216-010-4387-z · doi:10.1007/s00216-010-4387-z
  28. Park, 2016, GC–MS based metabolomics approach of Kimchi for the understanding of Lactobacillus plantarum fermentation characteristics, LWT-Food Science and Technology, 68, 313, 10.1016/j.lwt.2015.12.046 · DOI
  29. Pham, 2008, Relationships between sensory descriptors, consumer acceptability and volatile flavor compounds of American dry-cured ham, Meat Science, 80, 728, 10.1016/j.meatsci.2008.03.015 · doi:10.1016/j.meatsci.2008.03.015
  30. Ramírez, 2007, Volatile profiles of dry-cured meat products from three different Iberian X Duroc genotypes, Journal of Agricultural and Food Chemistry, 55, 1923, 10.1021/jf062810l · DOI
  31. Ruiz, 1999, Volatile compounds of dry-cured Iberian ham as affected by the length of the curing process, Meat Science, 52, 19, 10.1016/S0309-1740(98)00144-2 · DOI · Paper page
  32. Sabio, 1998, Volatile compounds present in six types of dry-cured ham from south European countries, Food Chemistry, 61, 493, 10.1016/S0308-8146(97)00079-4 · DOI · Paper page
  33. Sánchez-Peña, 2005, Characterization of French and Spanish dry-cured hams: Influence of the volatiles from the muscles and the subcutaneous fat quantified by SPME-GC, Meat Science, 69, 635, 10.1016/j.meatsci.2004.10.015 · doi:10.1016/j.meatsci.2004.10.015
  34. Song, 2008, Odour-active compounds of Jinhua ham, Flavour and Fragrance Journal, 23, 1, 10.1002/ffj.1844 · doi:10.1002/ffj.1844
  35. Toldrá, 1998, Proteolysis and lipolysis in flavour development of dry-cured meat products, Meuf Science, 49, S101
  36. Toldrá, 2000, The use of muscle enzymes as predictors of pork meat quality, Food Chemistry, 69, 387, 10.1016/S0308-8146(00)00052-2 · doi:10.1016/s0308-8146(00)00052-2
  37. Toldrá, 1997, Dry-cured ham flavour: Enzymatic generation and process influence, Food Chemistry, 59, 523, 10.1016/S0308-8146(97)00013-7 · doi:10.1016/s0308-8146(97)00013-7
  38. Uk Ahn, 2016, Mechanisms of volatile production from sulfur-containing amino acids by irradiation, Radiation Physics and Chemistry, 119, 80, 10.1016/j.radphyschem.2015.09.009 · DOI
  39. Wang, 2018, Analysis of volatile compounds in Chinese dry-cured hams by comprehensive two-dimensional gas chromatography with high-resolution time-of-flight mass spectrometry, Meat Science, 140, 14, 10.1016/j.meatsci.2018.02.016 · DOI
  40. Wang, 2016, Characterization and comparison of commercial Chinese cereal and European grape vinegars using 1H NMR spectroscopy combined with multivariate analysis, Chinese Journal of Chemistry, 34, 1183, 10.1002/cjoc.201600365 · DOI
  41. Wu, 2017, Metagenomics reveals flavour metabolic network of cereal vinegar microbiota, Food Microbiology, 62, 23, 10.1016/j.fm.2016.09.010 · DOI · Paper page
  42. Xia, 2010, MetPA: A web-based metabolomics tool for pathway analysis and visualization, Bioinformatics, 26, 2342, 10.1093/bioinformatics/btq418 · DOI · Paper page
  43. Xia, 2016, Using MetaboAnalyst 3.0 for comprehensive metabolomics data analysis, Current Protocols Bioinformatics, 55, 14.10.11, 10.1002/cpbi.11 · DOI · Paper page
  44. Yang, 2005, Lipolysis in intramuscular lipids during processing of traditional Xuanwei ham, Meat Science, 71, 670, 10.1016/j.meatsci.2005.05.019 · doi:10.1016/j.meatsci.2005.05.019
  45. Yang, 2016, Metabolomic biomarkers identify differences in milk produced by Holstein cows and other minor dairy animals, Journal of Proteomics, 136, 174, 10.1016/j.jprot.2015.12.031 · DOI
  46. Zhang, 2016, Influence of barley-based diets on physico-chemical characteristics and fatty acid composition of dry-cured ham produced with Dahe black Pig's hind leg, Scientia Agricultura Sinica, 49, 331
  47. Zhao, 2016, Selection of taste markers related to lactic acid Bacteria microflora metabolism for Chinese traditional Paocai: A gas chromatography-mass spectrometry-based metabolomics approach, Journal of Agricultural and Food Chemistry, 64, 2415, 10.1021/acs.jafc.5b05332 · DOI
  48. Zhou, 2009, Study on key odor compounds of Jinhua ham, Journal of Nanjing Agricultural University, 32, 173

Cited by

See all 163

Metadata

Authors
Shi, Y., Li, X., & Huang, A.
Venue
Meat Science
Publisher
Elsevier BV
Published
2019-12
Volume
158
Pages
107904
ISSN
0309-1740 (ISSN-L)
OpenAlex
W2962679740
Cited by
163
References
0
FWCI
12.23
Type
journal article
Language
en
Open access
closed
Licence
  • www.elsevier.com/tdm/userlicense/1.0/ (tdm)
  • www.elsevier.com/legal/tdmrep-license (tdm)
Funders
  • Industry Leading Technical Program of Yunnan, China (1782)
  • Key Meat Product Development in Yunnan (2015BB020)
  • Research and Development Workstation of Yunnan provincial experts (38)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A metabolomics-based approach investigates volatile flavor formation and characteristic compounds of the Dahe black pig dry-cured ham. https://app.cochat.ai/papers/10.1016/j.meatsci.2019.107904
The paper
Shi, Y., Li, X., & Huang, A. (2019). A metabolomics-based approach investigates volatile flavor formation and characteristic compounds of the Dahe black pig dry-cured ham. Meat Science. https://doi.org/10.1016/j.meatsci.2019.107904

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.