ArticlePloS one2016
Different Statistical Approaches to Investigate Porcine Muscle Metabolome Profiles to Highlight New Biomarkers for Pork Quality Assessment.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 30 citations in OpenAlex.
- Muscle Characteristics Comparison Analysis Reveal Differences in the Meat Quality and Nutritional Components of Three Shanghai Local Pig Breeds.Foods (Basel, Switzerland) · 2025Article
- Research Progress of Machine Learning in Extending and Regulating the Shelf Life of Fruits and Vegetables.Foods (Basel, Switzerland) · 2024Review
- Metabolomic comparison of meat quality and metabolites of geese breast muscle at different ages.Food chemistry: X · 2023Article
- - Invited Review - Postmortem skeletal muscle metabolism of farm animals approached with metabolomics.Animal bioscience · 2023Article
- Plasma Metabolomic Profiling Reveals Preliminary Biomarkers of Pork Quality Based on pH Value.Foods (Basel, Switzerland) · 2022Article
- Application of the Metabolomics Approach in Food Authentication.Molecules (Basel, Switzerland) · 2021Review
- Systematic selection of competing metabolomics methods in a metabolite-sensory relationship study.Metabolomics : Official journal of the Metabolomic Society · 2021Article
- Sexual Dimorphism of Metabolite Profiles in Pigs Depends on the Genetic Background.Metabolites · 2021Article
- MEATabolomics: Muscle and Meat Metabolomics in Domestic Animals.Metabolites · 2020Review
- Effect of Gender, Rearing, and Cooking on the Metabolomic Profile of Porcine Muscles.Metabolites · 2019Article
- MS-Based Analytical Techniques: Advances in Spray-Based Methods and EI-LC-MS Applications.Journal of analytical methods in chemistry · 2018Review
- Integrative Analysis of Metabolomic, Proteomic and Genomic Data to Reveal Functional Pathways and Candidate Genes for Drip Loss in Pigs.International journal of molecular sciences · 2016Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this study was to elucidate the underlying biochemical processes to identify potential key molecules of meat quality traits drip loss, pH of meat 1 h post-mortem (pH1), pH in meat 24 h post-mortem (pH24) and meat color. An untargeted metabolomics approach detected the profiles of 393 annotated and 1,600 unknown metabolites in 97 Duroc × Pietrain pigs. Despite obvious differences regarding the statistical approaches, the four applied methods, namely correlation analysis, principal component analysis, weighted network analysis (WNA) and random forest regression (RFR), revealed mainly concordant results. Our findings lead to the conclusion that meat quality traits pH1, pH24 and color are strongly influenced by processes of post-mortem energy metabolism like glycolysis and pentose phosphate pathway, whereas drip loss is significantly associated with metabolites of lipid metabolism. In case of drip loss, RFR was the most suitable method to identify reliable biomarkers and to predict the phenotype based on metabolites. On the other hand, WNA provides the best parameters to investigate the metabolite interactions and to clarify the complex molecular background of meat quality traits. In summary, it was possible to attain findings on the interaction of meat quality traits and their underlying biochemical processes. The detected key metabolites might be better indicators of meat quality especially of drip loss than the measured phenotype itself and potentially might be used as bio indicators.
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