scholarly journals MEATabolomics: Muscle and Meat Metabolomics in Domestic Animals

Metabolites ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 188 ◽  
Author(s):  
Susumu Muroya ◽  
Shuji Ueda ◽  
Tomohiko Komatsu ◽  
Takuya Miyakawa ◽  
Per Ertbjerg

In the past decades, metabolomics has been used to comprehensively understand a variety of food materials for improvement and assessment of food quality. Farm animal skeletal muscles and meat are one of the major targets of metabolomics for the characterization of meat and the exploration of biomarkers in the production system. For identification of potential biomarkers to control meat quality, studies of animal muscles and meat with metabolomics (MEATabolomics) has been conducted in combination with analyses of meat quality traits, focusing on specific factors associated with animal genetic background and sensory scores, or conditions in feeding system and treatments of meat in the processes such as postmortem storage, processing, and hygiene control. Currently, most of MEATabolomics approaches combine separation techniques (gas or liquid chromatography, and capillary electrophoresis)–mass spectrometry (MS) or nuclear magnetic resonance (NMR) approaches with the downstream multivariate analyses, depending on the polarity and/or hydrophobicity of the targeted metabolites. Studies employing these approaches provide useful information to monitor meat quality traits efficiently and to understand the genetic background and production system of animals behind the meat quality. MEATabolomics is expected to improve the knowledge and methodologies in animal breeding and feeding, meat storage and processing, and prediction of meat quality.

1995 ◽  
Vol 73 (12) ◽  
pp. 3596 ◽  
Author(s):  
M Koohmaraie ◽  
S D Shackelford ◽  
T L Wheeler ◽  
S M Lonergan ◽  
M E Doumit

2001 ◽  
Vol 79 (11) ◽  
pp. 2812 ◽  
Author(s):  
D J de Koning ◽  
B Harlizius ◽  
A P Rattink ◽  
M A Groenen ◽  
E W Brascamp ◽  
...  

2015 ◽  
Vol 95 (1) ◽  
pp. 31-36 ◽  
Author(s):  
Jung Hye Hwang ◽  
Seul Gi Kwon ◽  
Da Hye Park ◽  
Tae Wan Kim ◽  
Deok Gyeong Kang ◽  
...  

Hwang, J. H., Kwon, S. G., Park, D. H., Kim, T. W., Kang, D. G., Ha, J., Kim, S. W. and Kim, C. W. 2015. Molecular characterization of porcine PGM1 gene associated with meat quality traits. Can. J. Anim. Sci. 95: 31–36. The PGM1 gene from four porcine breeds (Berkshire, Duroc, Landrace, and Yorkshire) is highly expressed in liver tissue at the transcriptional level. Single nucleotide polymorphisms (SNPs) of PGM1 were examined to analyze association with increased expression of PGM1 gene in the Berkshire liver. A Leu525 synonymous SNP of Chr6:137174682A>G (c.1575A>G) was identified and showed significant (P<0.05) differences to backfat thickness, drip loss, protein content, fat content, Warner–Bratzler shear force, and post-mortem pH24h. Therefore, it is concluded that PGM1 synonymous SNP is an important factor regulating meat quality.


2018 ◽  
Vol 41 (1) ◽  
pp. 125-136 ◽  
Author(s):  
Katarzyna Piórkowska ◽  
Kacper Żukowski ◽  
Katarzyna Ropka-Molik ◽  
Mirosław Tyra ◽  
Artur Gurgul

2006 ◽  
Vol 37 (3) ◽  
pp. 219-224 ◽  
Author(s):  
A. Mercade ◽  
J. Estelle ◽  
M. Perez-Enciso ◽  
L. Varona ◽  
L. Silio ◽  
...  

2013 ◽  
Vol 38 (1) ◽  
pp. 64-68
Author(s):  
Ji ZHU ◽  
Jian LIU ◽  
Jian-bang SUN ◽  
Shi-liu YANG ◽  
Jing-ru LI ◽  
...  

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Simone Savoia ◽  
Andrea Albera ◽  
Alberto Brugiapaglia ◽  
Liliana Di Stasio ◽  
Alessio Cecchinato ◽  
...  

Abstract Background The possibility of assessing meat quality traits over the meat chain is strongly limited, especially in the context of selective breeding which requires a large number of phenotypes. The main objective of this study was to investigate the suitability of portable infrared spectrometers for phenotyping beef cattle aiming to genetically improving the quality of their meat. Meat quality traits (pH, color, water holding capacity, tenderness) were appraised on rib eye muscle samples of 1,327 Piemontese young bulls using traditional (i.e., reference/gold standard) laboratory analyses; the same traits were also predicted from spectra acquired at the abattoir on the intact muscle surface of the same animals 1 d after slaughtering. Genetic parameters were estimated for both laboratory measures of meat quality traits and their spectra-based predictions. Results The prediction performances of the calibration equations, assessed through external validation, were satisfactory for color traits (R2 from 0.52 to 0.80), low for pH and purge losses (R2 around 0.30), and very poor for cooking losses and tenderness (R2 below 0.20). Except for lightness and purge losses, the heritability estimates of most of the predicted traits were lower than those of the measured traits while the genetic correlations between measured and predicted traits were high (average value 0.81). Conclusions Results showed that NIRS predictions of color traits, pH, and purge losses could be used as indicator traits for the indirect genetic selection of the reference quality phenotypes. Results for cooking losses were less effective, while the NIR predictions of tenderness were affected by a relatively high uncertainty of estimate. Overall, genetic selection of some meat quality traits, whose direct phenotyping is difficult, can benefit of the application of infrared spectrometers technology.


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