Evidence map›Paper›PMID 42188879›Full record

ArticleVeterinary sciences2026

Study on Early Pregnancy Diagnosis of Sows Based on Body Fluid Metabolite Detection Combined with Machine Learning Models.

Yun Feng, Ruonan Gao, Wengang Yang, Huiwen Lu, Weizeng Sun, Yun Zhang, Yujun Ren, Liming Gao, Mengxun Li, Qingchun Li and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Veterinary sciences, 2026. 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
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

15 authors.

Yun FengCollege of Animal Science and Technology, Shihezi University, Shihezi 832003, China.
Ruonan GaoAgricultural and Rural Bureau of Qitai County, Changji 831800, China.
Wengang YangXinjiang Production and Construction Corps Seventh Division Animal Husbandry and Aquatic Products Development Service Center, Huyanghe 834034, China.
Huiwen LuXinjiang Pig Breeding Engineering Technology Research Center, Xinjiang Tecon Husbandry S&T Co., Ltd., Changji 831100, China.
Weizeng SunXinjiang Pig Breeding Engineering Technology Research Center, Xinjiang Tecon Husbandry S&T Co., Ltd., Changji 831100, China.
Yun ZhangCollege of Animal Science and Technology, Shihezi University, Shihezi 832003, China.
Yujun RenCollege of Animal Science and Technology, Shihezi University, Shihezi 832003, China.
Liming GaoJinyi Farmers' Breeding Cooperative, Huyanghe 834034, China.
Mengxun LiCollege of Animal Science and Technology, Shihezi University, Shihezi 832003, China.
Qingchun LiCollege of Animal Science and Technology, Shihezi University, Shihezi 832003, China.
Guang PuCollege of Animal Science and Technology, Shihezi University, Shihezi 832003, China.
Yongsheng ZhangCollege of Animal Science and Technology, Shihezi University, Shihezi 832003, China.
Zikai AiCollege of Animal Science and Technology, Shihezi University, Shihezi 832003, China.
Kun YanCollege of Animal Science and Technology, Shihezi University, Shihezi 832003, China.
Tao HuangCollege of Animal Science and Technology, Shihezi University, Shihezi 832003, China.ORCID 0000-0003-2943-5131

Funding

the National Natural Science Foundation of China 31960645the "Solving Key Problems by Tendering for Solutions" Program of the 7th Division and Huyanghe City: Identification and Application of Body Fluid Biomarkers for Early Pregnancy in Sows QS2023010the Youth Top-notch Talents Program of the Tianshan Talent Cultivation Plan 2022TSYCCX0047
6 · The paper itself

Abstract

The conventional window for ultrasonic pregnancy diagnosis in sows is 22-25 days post-insemination, which often results in missed opportunities for the optimal re-insemination of non-pregnant sows and elevated production costs. This present study aimed to establish an early pregnancy detection method for sows at 12-18 days post-insemination, thereby providing a reference for efficient reproductive management. Saliva, urine and vaginal secretions were collected from sows during this period, and seven metabolites were quantified. Seven machine learning models were employed for data analysis, after which the optimal combination was determined, and the detection protocol was refined using recursive feature elimination. The results revealed that the majority of metabolites in saliva and urine differed significantly between pregnant and non-pregnant groups (

Indexed as

chemical quantitative detectionearly pregnancy diagnosismachine learningmetabolitessows

Identifiers

PMID42188879
PMCPMC13211673

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.