Evidence map›Paper›PMID 42071901›Full record

ArticleAnimals : an open access journal from MDPI2026

Evaluating the Impact of Scanning Factors on Ultrasound Imaging for Predicting Semen Quality in Boars.

Shihong Yang, Yijian Huang, Jeremy Howard, Vance Brown, Chun-Peng James Chen

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Shihong YangSchool of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA.ORCID 0009-0008-4315-0830
Yijian HuangSmithfield Premium Genetics, Smithfield Foods, Rose Hill, NC 28458, USA.
Jeremy HowardSmithfield Premium Genetics, Smithfield Foods, Rose Hill, NC 28458, USA.
Vance BrownSmithfield Premium Genetics, Smithfield Foods, Rose Hill, NC 28458, USA.
Chun-Peng James ChenSchool of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA.ORCID 0000-0002-2018-0702

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early prediction of semen quality in young boars is crucial to reduce operational costs associated with low-productivity boars at boar studs, where high genetic merit is key. B-ultrasound imaging, a non-invasive method using echo signals to visualize tissue density, has been evaluated as a potential tool for this purpose. Stronger echoes indicate denser tissues, such as the seminiferous tubules responsible for sperm production. This study focuses on investigating the predictive power of using B-ultrasound imaging from boars around 6 to 9 months old to predict semen quality over the next six months in industrial settings. Several scanning factors were considered, including image brightness, imaging area of the testicle, and the imaging angle of the probe. The studied dataset included 1417 images and 3254 semen records from 107 boars. Results showed that the model's performance was significantly influenced by the imaging area, the angle of the testicle, and the pixel brightness of the image without being standardized. While the accuracy of B-ultrasound imaging is not yet sufficient to replace traditional assessments, this study highlights key features in testicular images that may significantly impact model predictions, providing practical guidance for leveraging B-ultrasound imaging in predicting semen quality in young boars.

Indexed as

computer visionfeature extractionprecision livestock farmingsemen qualityultrasound imaging

Identifiers

PMID42071901
PMCPMC13113066

What OpenQuestion holds

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Registered trials

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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.