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Prediction of live body weight based on body measurements in Thalli sheep under tropical conditions of Pakistan using CART and MARS

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Abstract

Thalli sheep is a significant breed reared under tropical region of Punjab province of Pakistan. The present study was conducted to predict live body weight (LBW) by means of from some body measurements, i.e., chest girth (CG), belly girth (BG), rump height (RH), withers height (WH), neck girth (NG), and body length (BL) taken from 155 Thalli indigenous sheep of Pakistan. Age factor is determined to be a significant source of variation for BL, BG, CG, BG, WH, and NG (p < 0.05). LBW is correlated significantly with BL (0.850), CG (0.825), BG (0.849), RH (0.579), WH (0.547), and NG (0.7760), respectively (p < 0.01). For LBW prediction, CART and MARS data mining algorithms were comparatively used based on ten cross-validation method. Among 185 candidate MARS models with 1–5 degrees of interaction and 2–38 terms, the MARS model with 7 terms and no interaction effect in R software was the best model for LBW prediction on the basis of the smallest cross-validated RMSE value. Also, the optimal CART tree structure was obtained with 9 terminal nodes for the smallest cross-validated RMSE value. MARS algorithm outperformed CART in LBW prediction and explained 90.3 (%) of variability in LBW of Thalli sheep. Results of the optimal CART structure reflected that Thalli sheep with BL > 75 cm, RH > 83 cm, and NG > 55 cm has the heaviest LBW of 72 kg. The optimal MARS model displays that the heaviest LBW can be produced by Thalli sheep with BL > 71.12 cm, BG > 106.68 cm, WH > 76.2 cm, NG > 50.8 cm in 5th age group. In conclusion, it coud be recommended that MARS predictive modeling may enable animal breeders to obtain elite Thalli sheep population and to detect body measurement positively influencing LBW as indirect selection criteria for not only describing breed characterization and developing flock management standards, but also ensuring sustainable meat production and rural development in Pakistan.

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Data availability

All data generated or analyzed during this study are included in this published article.

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All codes analyzed during this study are included in this published article.

Abbreviations

LBW:

Live body weight

CG:

Chest girth

BG:

Belly girth

RH:

Rump height

WH:

Withers height

NG:

Neck girth

BL:

Body length

MARS:

Multivariate adaptive regression splines

CART:

Classification and regression tree

ANNs:

Artificial neural networks

CHAID:

Chi-squared automatic interaction detection

Exhaustive CHAID:

Exhaustive chi-squared automatic interaction detection

CP:

Complexity parameter

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Authors and Affiliations

  1. Department of Livestock and Poultry Production, Bahauddin Zakariya University, Multan, Pakistan

    Asim Faraz & Abdul Waheed

  2. Agricultural Faculty, Department of Animal Science, Biometry and Genetics Unit, Iğdır University, Iğdır, Turkey

    Cem Tirink

  3. Faculty of Economics and Administrative Sciences, Department of Business Administration, Iğdır University, Iğdır, Turkey

    Ecevit Eyduran

  4. Department of Animal Science, University of Sargodha, Sargodha, Pakistan

    Nasir Ali Tauqir

  5. Livestock & Dairy Development Department, Camel Breeding and Research Station Rakh Mahni, Punjab, Pakistan

    Muhammad Shahid Nabeel

  6. Center for Advanced studies in Vaccinology and Biotechnology (CASVAB), University of Balochistan, Quetta, Pakistan

    Mohammad Masood Tariq

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  1. Asim Faraz
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Contributions

AF, AW, NAT, MSN, and MMT conceived, designed research, and conducted experiments. CT and EE analyzed data and wrote the manuscript. EE revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Cem Tirink.

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Faraz, A., Tirink, C., Eyduran, E. et al. Prediction of live body weight based on body measurements in Thalli sheep under tropical conditions of Pakistan using CART and MARS. Trop Anim Health Prod 53, 301 (2021). https://doi.org/10.1007/s11250-021-02748-6

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