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AI-Driven prediction of body weight in chicken genotypes with different growth rates.

Tropical animal health and production - 20 Feb 2026

Musa Aliyu Abduljalal, Idrus Zulkifli, Chung Eric Lim Teik, Samat Noraini, Abdulkadir Rabiu Aliyu, Abayomi Rotimi Emmanuel, Setiaji Asep, Mamat-Hamidi Kamalludin

Abstract excerpt

This study evaluates four machine learning algorithms: Gaussian Exponential Regression (GER), Feedforward Neural Networks (FFNN), Support Vector Machines (SVM), and Decision Trees (DT) for predicting body weight in chickens with different growth rates (slow-, medium-, and fast-growing breeds). It fills a major research gap by benchmarking these models under uniform conditions across multiple growth categories....

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Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

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Source

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Identifiers

PMID: 41718905
DOI: 10.1007/s11250-026-04925-x
PMCID: PMC12923440

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