蛋白质组学
温柔
能量代谢
肉的嫩度
生物
计算生物学
生物技术
计算机科学
食品科学
质量(理念)
数据科学
生物化学
基因
认识论
内分泌学
哲学
作者
Peter P. Purslow,Mohammed Gagaoua,Robyn D. Warner
出处
期刊:Meat Science
[Elsevier BV]
日期:2020-12-30
卷期号:174: 108423-108423
被引量:107
标识
DOI:10.1016/j.meatsci.2020.108423
摘要
Following a century of major discoveries on the mechanisms determining meat colour and tenderness using traditional scientific methods, further research into complex and interactive factors contributing to variations in meat quality is increasingly being based on data-driven omics approaches such as proteomics. Using two recent meta-analyses of proteomics studies on beef colour and tenderness, this review examines how knowledge of the mechanisms and factors underlying variations in these meat qualities can be both confirmed and extended by data-driven approaches. While proteomics seems to overlook some sources of variations in beef toughness, it highlights the role of post-mortem energy metabolism in setting the conditions for development of meat colour and tenderness, and also points to the complex interplay of energy metabolism, calcium regulation and mitochondrial metabolism. In using proteomics as a future tool for explaining variations in meat quality, the need for confirmation by further hypothesis-driven experimental studies of post-hoc explanations of why certain proteins are biomarkers of beef quality in data-driven studies is emphasised.
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