Evidence map›Paper›PMID 36287780›Full record

ReviewJournal of animal science and technology2022

Current advances in detection of abnormal egg: a review.

Jun-Hwi So, Sung Yong Joe, Seon Ho Hwang, Soon Jung Hong, Seung Hyun Lee

Abstract readReview
In one paragraph

Review in Journal of animal science and technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Can eggshells indicate stressor exposure in free-range laying hens?Animal welfare (South Mimms, England) · 2024
    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.

Jun-Hwi SoDepartment of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0001-9479-6000
Sung Yong JoeDepartment of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0002-8482-9777
Seon Ho HwangDepartment of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0002-0736-0370
Soon Jung HongDepartment of Liberal Arts, Korea National University of Agriculture and Fisheries, Jeonju 54874, Korea.ORCID https://orcid.org/0000-0003-2584-5379
Seung Hyun LeeDepartment of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0002-2096-3053

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Internal and external defects of eggs should be detected to prevent cross-contamination of intact eggs by abnormal eggs during storage. Emerging detection technologies for abnormal eggs were introduced as an alternative to human inspection. The advanced technologies could rapidly detect abnormal eggs. Abnormal egg detection technologies using acoustic response, machine vision, and spectroscopy have been commercialized in the poultry industry. Non-destructive egg quality assessment methods meanwhile could preserve the value of eggs and improve detection efficiency. In order to improve detection efficiency, it is essential to select a proper algorithm for classifying the types of abnormal eggs. This review deals with the performance of the detection technologies for various types of abnormal eggs in recently published resources. In addition, the discriminant methods and detection algorithms of abnormal eggs reported in the published literature were investigated. Although the majority of the studies were conducted on a laboratory scale, the developed detection technologies for internal and external defects in eggs were technically feasible to obtain the excellent detection accuracy. To apply the developed detection technologies to the poultry industry, it is necessary to achieve the detection rates required from the industry.

Indexed as

Abnormal egg detectionAcoustic responseHyperspectral imagingMachine visionModified pressureSpectroscopy

Identifiers

PMID36287780
PMCPMC9574607

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.