Evidence map›Paper›PMID 39210801›Full record

ArticleAnimal bioscience2025

New management grading for pig farms: management grading system using pig carcass weight, back fat thickness and k-means algorithm.

Youngho Lim, Jaeyoung Kim, Gwantae Kim, Jungseok Choi

Abstract read
In one paragraph

Article in Animal bioscience, 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
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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

4 authors.

Youngho LimDepartment of Animal Science, Chungbuk National University, Cheongju 28644, Korea.
Jaeyoung KimDepartment of Animal Science, Chungbuk National University, Cheongju 28644, Korea.
Gwantae KimDepartment of Animal Science, Chungbuk National University, Cheongju 28644, Korea.
Jungseok ChoiDepartment of Animal Science, Chungbuk National University, Cheongju 28644, Korea.

Funding

Bugyeong Pig Farmers CooperativeMinistry of Education 2021RIS001National Research Foundation of Korea
6 · The paper itself

Abstract

objectiveThis study categorized farm management levels to improve the productivity and uniformity of pork from pigs shipped from farms.

methodsA total of 48,298 pigs were grouped (A, B, C, D group) using the k-means algorithm, carcass weight and backfat thickness. The results of the grouping were used to classify Farm Management Grades (A, B, C, D grade).

resultsThe proportion of primal cuts in pigs, according to the new classification method, increased from group A to group D for shoulder blade, shoulder picnic, and ham, but decreased for loin and belly. In the regression analysis of the five primal cuts (shoulder blade, shoulder picnic, loin, belly, and ham) production (kg) for each group, all regression equations showed low errors (MAE<0.7), indicating that the model can predict the production of primal cuts by group. As the Farm Management Grade decreased, the proportion of pigs in the group with large differences from the mean of carcass weight and backfat thickness of the whole pig increased.

conclusionThe results of this study confirmed the differences in primal cut traits by pig grouping and created a method to classify farms who ship non-uniform pigs. This is expected to provide indicators for improvement and supplementation to farms that ship uneven pigs, helping to enhance the production of standardized pigs at the farm level.

Indexed as

K-meansLandrace×Yorkshire×Duroc (LYD) PigManagement GradePig GradeRegression AnalysisVCS2000

Identifiers

PMID39210801
PMCPMC11725751

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