Evidence map›Paper›PMID 36830438›Full record

ReviewAnimals : an open access journal from MDPI2023

Robot Technology for Pork and Beef Meat Slaughtering Process: A Review.

Juntae Kim, Yun-Kil Kwon, Hyoun-Wook Kim, Kuk-Hwan Seol, Byoung-Kwan Cho

Abstract readReview
In one paragraph

Review in Animals : an open access journal from MDPI, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. 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.

Juntae KimDepartment of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of Korea.ORCID 0000-0002-5398-8839
Yun-Kil KwonXCore System Co., Ltd., Sejong 30141, Republic of Korea.
Hyoun-Wook KimAnimal Products Research and Development Division, National Institute of Animal Science, Wanju 55365, Republic of Korea.
Kuk-Hwan SeolAnimal Products Research and Development Division, National Institute of Animal Science, Wanju 55365, Republic of Korea.ORCID 0000-0002-0907-882X
Byoung-Kwan ChoDepartment of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of Korea.ORCID 0000-0002-8397-9853

Funding

Rural Development Administration PJ017041
6 · The paper itself

Abstract

Recently, many slaughterhouses have begun to introduce automation and quality evaluation sensing equipment to the slaughter processing line to overcome insufficient human resources, improve the efficiency of the slaughter process, and standardize meat quality. Various processing instruments and sensing technologies may be used depending on the livestock to be slaughtered, but a standardized process design for a smart slaughterhouse remains to be established. Slaughterhouses are becoming more industrialized, leveraging data collection and analysis to drive growth and increase production. Therefore, slaughterhouse automation is essential for meeting production demand, and an optimized design suitable for the size of each company is required to maximize economical equipment and systems. We introduce robot technology used in the slaughterhouse and detail the visceral laparotomy, carcass preprocessing, and deboning robot technology. In this study, we examine slaughterhouse automation equipment and technologies, focusing on optimizing the processing lines, the direction of application, and the hygiene of robot technique. We hope this review will provide insight into slaughterhouse automation for decision making in the slaughter industry.

Indexed as

beefporkrobotizationslaughterhouse automationsmart slaughterhouse

Identifiers

PMID36830438
PMCPMC9951719

What OpenQuestion holds

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LicenceCC BY
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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.