Evidence map›Paper›PMID 41659967›Full record

ArticleFrontiers in veterinary science2025

Does age in months influence Chinese Holstein dairy cow production performance after controlling for days in milk?

Lei Zhang, Cheng-Long Luo, Qi Mu, Jia-Cheng Liu, Chun-Fang Li, Ya-Bin Ma, Qi Su, Jun-Peng Zhang, Jian-Tao Li, Shu-Yi Zhang and 2 more

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Article in Frontiers in veterinary science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Lei Zhang *College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China.
Cheng-Long Luo *College of Animal Science and Technology, China Agricultural University, Beijing, China.
Qi Mu *College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China.
Jia-Cheng LiuCollege of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China.
Chun-Fang LiHebei Livestock Breeding Station, Shijiazhuang, China.
Ya-Bin MaHebei Livestock Breeding Station, Shijiazhuang, China.
Qi SuMinistry of Education Joint International Research Laboratory of Animal Health and Food Safety, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China.
Jun-Peng ZhangCollege of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China.
Jian-Tao LiCollege of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China.
Shu-Yi ZhangCollege of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China.
Jian-Min ChaiGuangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Animal Science and Technology, Foshan University, Foshan, China.
Yao-Lu ZhaoCollege of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to assess the impact of cows' age (in months) on production performance and evaluate the feasibility of using on-site data to inform precision agricultural practices on farms. Cows were randomly categorized by age in months, and the influence of lactation days was controlled using analysis of covariance (ANCOVA). Weighted linear models (WLM) was employed to control the effect of aggregating data. Principal component analysis (PCA) was applied to explore the relationships among production traits and to elucidate their underlying principles, providing insights for precision management in large-scale farms. The findings were as follows: (1) the age in months had no significant effect on dry matter intake (DMI), residual feed intake (RFI), or daily milk yield (MY;

Indexed as

analysis of covariancefeed intakemilk yieldPCAweighted linear model

Identifiers

PMID41659967
PMCPMC12875920

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.