Metabolomics in ruminant food: Bridging nutritional quality and safety evaluation

Abstract Ruminant-derived foods, predominantly milk and meat, are globally recognized as staples of a high-quality diet. Despite their widespread popularity, there is a notable deficiency in comprehensive standards addressing the nutritional values and safety of these products. This gap significantly limits both the supply of and demand for premium quality milk and meat. This review endeavors to highlight the benefits of utilizing metabolomics for the evaluation of quality and safety in milk and meat products from ruminants. It identifies critical metabolites, genetic signals, and metabolic pathways related to the synthesis of ruminant-derived milk and meat, proposing their potential as nutritional or regulatory targets and biomarkers. These biomarkers are instrumental in predicting and assessing the quality and safety of dairy and meat products, offering guidance for quality-based pricing and food safety inspections in the market. This review offers a critical overview of current metabolomics-based platforms and tools for interpreting the quality and safety of ruminant foods. The core metabolic biomarkers and biological biosynthetic processes of milk and meat enhance our understanding of the interplay between conventional food production from animals and new synthetic biological technologies.

Authors

Institutions

Publication Details

Journal
Animal Nutriomics
Published
2025-01-01
DOI
https://doi.org/10.1017/anr.2024.30
Citations
4
Primary Topic
Animal Nutrition and Health
Type
article
Field-Weighted Citation Impact
7.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Metabolomics in ruminant food: Bridging nutritional quality and safety evaluation

Jiakun Wang, Bing Wang, Boyan Zhang
4 citations
Animal Nutriomics
Animal Nutrition and Health
7.00
article

Metabolomics in ruminant food: Bridging nutritional quality and safety evaluation

Jiakun Wang, Bing Wang, Boyan Zhang
article en
4 citations

Abstract

Abstract Ruminant-derived foods, predominantly milk and meat, are globally recognized as staples of a high-quality diet. Despite their widespread popularity, there is a notable deficiency in comprehensive standards addressing the nutritional values and safety of these products. This gap significantly limits both the supply of and demand for premium quality milk and meat. This review endeavors to highlight the benefits of utilizing metabolomics for the evaluation of quality and safety in milk and meat products from ruminants. It identifies critical metabolites, genetic signals, and metabolic pathways related to the synthesis of ruminant-derived milk and meat, proposing their potential as nutritional or regulatory targets and biomarkers. These biomarkers are instrumental in predicting and assessing the quality and safety of dairy and meat products, offering guidance for quality-based pricing and food safety inspections in the market. This review offers a critical overview of current metabolomics-based platforms and tools for interpreting the quality and safety of ruminant foods. The core metabolic biomarkers and biological biosynthetic processes of milk and meat enhance our understanding of the interplay between conventional food production from animals and new synthetic biological technologies.

Animal NutriomicsVol. 2
Ministry of Education of the People's Republic of China (CN), China Agricultural University (CN), Zhejiang University (CN)
National Natural Science Foundation of China, China Agricultural University
Zero hunger
Openalex Percentile: Top 4%
Animal Nutrition and Health
7.00
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.