Prediction of body weight in indigenous sheep using random forest regression, support vector regression, and classification and regression trees algorithms.

Ashenafi Getachew Megersa, Fikrineh Negash, Abebe Hailu, Awoke Melak, Abraham Assefa, Tesfalem Aseged, Seble Sinkie

Abstract read

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Article in Veterinary and animal science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing 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.

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

Body Weight Prediction in Karayaka Lambs Using Morphometric Measurements: A Comparison of Regression and Machine Learning Approaches.Animals : an open access journal from MDPI · 2026
Article
Application of XGBoost and Random Forest algorithms for body weight prediction in Blackbelly sheep using biometric measurements.BMC veterinary research · 2026
Article

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5 · Who and what money

Authors and funding

7 authors.

Ashenafi Getachew MegersaSchool of Animal and Range Sciences, Haramaya University, P. O. Box 138, Dire Dawa, Ethiopia.

Fikrineh NegashFreelance Researcher and Consultant, Addis Ababa, Ethiopia.

Abebe HailuEthiopian Biodiversity Institute, P. O. Box 30726, Addis Ababa, Ethiopia.

Awoke MelakEthiopian Biodiversity Institute, P. O. Box 30726, Addis Ababa, Ethiopia.

Abraham AssefaEthiopian Biodiversity Institute, P. O. Box 30726, Addis Ababa, Ethiopia.

Tesfalem AsegedEthiopian Biodiversity Institute, P. O. Box 30726, Addis Ababa, Ethiopia.

Seble SinkieEthiopian Biodiversity Institute, P. O. Box 30726, Addis Ababa, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to develop predictive models for estimating the body weight (BW) of indigenous sheep in Ethiopia using morphometric traits, comparing the performance of random forest regression (RFR), support vector regression (SVR), and classification and regression trees (CART) algorithms. Data were collected from 306 mature sheep (249 ewes and 57 rams) in Tahtay Maichew district of Tigray region, including BW and 16 linear body measurements (LBMs). Descriptive statistics indicated low to moderate variability in BW and key LBMs, with heart girth (HG) and body length (BL) showing the strongest correlations with BW (

Indexed as

Body weight predictionClassification and regression treesEthiopian indigenous sheepMorphometric traitsRandom forest regressionSupport vector regression

Identifiers

PMID41111633

DOI10.1016/j.vas.2025.100517

PMCPMC12529536

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LicenceCC BY-NC-ND

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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.