ArticleAnimal nutrition (Zhongguo xu mu shou yi xue hui)2026
Predicting beef diet nutritional composition and intake from rumen metagenomic profiles.
Article in Animal nutrition (Zhongguo xu mu shou yi xue hui), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Optimisation of selection for methane mitigation by integrating production traits with ruminal microbiome-driven breeding in beef cattle.Genetics, selection, evolution : GSE · 2026Article
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7 authors.
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Abstract
Knowledge of diet composition and intake levels in beef cattle is valuable for post hoc feed traceability and for more accurate modelling of the diet impact on methane emissions and performance traits. However, a direct measure of this information can be costly and labour-intensive and is not always feasible. In this study, rumen metagenomic data combined with machine learning algorithms were used to predict diet type, nutritional composition, and intake levels. An external validation to assess the generalizability of the models was also performed. Rumen samples were collected from 142 animals belonging to two breeds, Luing (
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