ArticleTropical animal health and production2021
Use of MARS algorithm for predicting mature weight of different camel (Camelus dromedarius) breeds reared in Pakistan and morphological characterization via cluster analysis.
Article in Tropical animal health and production, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 20 citations in OpenAlex.
- Weighted Single-Step Genomic Evaluation of Body Structural Traits for Early Selection of Growth Performance in Thai Swamp Buffalo.Animals : an open access journal from MDPI · 2026Article
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- Using Multivariate Adaptive Regression Splines to Estimate the Body Weight of Savanna Goats.Animals : an open access journal from MDPI · 2023Article
- Estimation of Body Weight Based on Biometric Measurements by Using Random Forest Regression, Support Vector Regression and CART Algorithms.Animals : an open access journal from MDPI · 2023Article
- Using the artificial bee colony technique to optimize machine learning algorithms in estimating the mature weight of camels.Tropical animal health and production · 2023Article
- Modeling and predicting the growth of indigenous Harnai sheep in Pakistan: non-linear functions and MARS algorithm.Tropical animal health and production · 2021Article
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8 authors at 4 institutions in 3 countries.
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Abstract
Mature weight is a significant trait that can be influenced by age, sex, breed, production system, and climate conditions in camels. In camel breeding, it is essential to describe breed standards of the studied camel breeds as part of morphological characterization and to determine morphological traits positively influencing mature weight within the scope of indirect selection criteria. This study was to find the best one among candidate models in prediction of mature weight from several morphological traits measured for eight camel breeds (Bravhi, Kachi, Kharani, Kohi, Lassi, Makrani, Pishin, and Rodbari) raised under Pakistan conditions. The morphological measurements taken from the camels in the study were birth weight (BW), weaning weight (WW), mature weight (MW), age of ridding (ARD), face length (FL), face width (FW), head length (HL), head width (HW), ear length (EL), ear width (EW), neck length (NL), neck width (NW), hump length (HL), hump width (HuW), heart girth (HG), withers height (WH), body length (BL), fore leg length (FLL), and hind leg length (HLL), respectively. In the prediction of mature body weight as a response variable, the optimal MARS predictive model with 15 terms selected by train function of the caret package produced very high predictive performance without encountering overfitting problem. Goodness of fit criteria were estimated to measure predictive quality of the MARS model using ehaGoF package available in R environment. Morphological characterization of the camel breeds was performed with hierarchical cluster analysis (HCA) on the basis of Euclidean distance-Single linkage. At the first step of hierarchical cluster analysis, the similarity level of Bravhi and Kachi camel breeds was the highest with 85.3569 (%). At the second step, Makrani joined to new cluster of Bravhi and Kachi camels found at the first step, and the similarity level of the new cluster comprising Bravhi, Kachi, and Makrani breeds was found as 84.5562 (%). MW was significantly correlated with BW (0.677), WW (0.536), HL (0.524), HuW (0.529), and ARD (0.375) at P < 0.01, and there was the highest correlation of 0.994 between HHL and FLL (P < 0.01). As a result, it could be suggested that results of MARS modeling may help camel breeders to reproduce the elite camel populations and to describe characteristics associated positively with MW within the scope of indirect selection criteria.
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