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Prediction of body weight from morphological traits of South African non-descript indigenous goats of Lepelle-Nkumbi Local Municipality using different data mining algorithm

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Abstract

Body weight is a vital trait which can assist farmers on selecting animals to use during breeding season. Therefore, the study was conducted to develop the best model to predict body weight from morphological traits through classification and regression tree (CART) and chi-square automatic interaction detector (CHAID) and to determine the relationship between body weight and some morphological traits. A total of 700 South African non-descript indigenous goats (female = 417 and male = 283) between the age of 1 and 5 years old were used in the study. Body weight and some morphological traits viz. body length (BL), heart girth (HG), withers height (WH), rump height (RH), and rump length (RL) were measured in the study. CART, CHAID, and Pearson’s correlation were used for data analysis. CART and CHAID algorithms indicated that predictor factors such as BL, HG, age, and villages had statistical influence on body weight of goats. The study suggests that BL can be used to estimate body weight of South African non-descript indigenous goats. Goodness of fit test suggests that CHAID is a suitable algorithm for prediction of body weight of South African non-descript indigenous goats. Correlation findings indicated that BW had positive highly statistical correlation (P < 0.01) with BL in male and female goats with correlation values of r = 0.65 and r = 0.65, respectively. Findings suggest that improving BL of South African non-descript indigenous goats might improve body weight.

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All data generated or analyzed during this study are included in the manuscript.

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Acknowledgements

We would like to thank goat farmers in the Lepelle-Nkumbi Local Municipality for allowing us to use their animals for this study, as well as Mr T Mogashoa, an extension officer in the Lepelle-Nkumbi Local Municipality, for assisting us in reaching the goat farmers with whom he works.

Funding

This study was supported by South African National Research Funding (NRF) reference number: UID: 129049.

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Authors and Affiliations

  1. School of Agricultural and Environmental Sciences, Department of Agricultural Economics and Animal Production, University of Limpopo, Private Bag X1106, Sovenga 0727, Polokwane, Limpopo, South Africa

    Madumetja Cyril Mathapo, Thinawanga Joseph Mugwabana & Thobela Louis Tyasi

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  1. Madumetja Cyril Mathapo
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  2. Thinawanga Joseph Mugwabana
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  3. Thobela Louis Tyasi
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Contributions

TLT designed the study, read, and approved the final manuscript. TJM read, improved, and approved the final manuscript. MCM collected, analyzed data, and wrote the manuscript.

Corresponding author

Correspondence to Thobela Louis Tyasi.

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Ethics approval

The Animal Research Ethics Committee (AREC) of University of Limpopo approved this study and issued out the certificate with the number: AREC/12/2020: PG.

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Not applicable.

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The authors declare no competing interests.

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Mathapo, M.C., Mugwabana, T.J. & Tyasi, T.L. Prediction of body weight from morphological traits of South African non-descript indigenous goats of Lepelle-Nkumbi Local Municipality using different data mining algorithm. Trop Anim Health Prod 54, 102 (2022). https://doi.org/10.1007/s11250-022-03096-9

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