Skip to main content
Log in

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

  • Regular Articles
  • Published:
Tropical Animal Health and Production Aims and scope Submit manuscript


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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data availability

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

Code availability

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



Live body weight


Chest girth


Belly girth


Rump height


Withers height


Neck girth


Body length


Multivariate adaptive regression splines


Classification and regression tree


Artificial neural networks


Chi-squared automatic interaction detection

Exhaustive CHAID:

Exhaustive chi-squared automatic interaction detection


Complexity parameter


  • Akin, M., Eyduran, E., Niedz, R.P., Reed, B.M., 2017a. Developing hazelnut tissue culture free of ion confounding, Plant Cell, Tissue and Organ Culture 13(3), 483-494.

    Article  Google Scholar 

  • Akin, M., Eyduran, E., Reed, B.M., 2017b. Use of RSM and CHAID data mining algorithm for predicting mineral nutrition of hazelnut, Plant Cell, Tissue and Organ Culture 128(2), 303-316.

    Article  CAS  Google Scholar 

  • Akin, M., Hand, C., Eyduran, E., Reed, B.M., 2018. Predicting minor nutrient requirements of hazelnut shoot cultures using regression trees, Plant Cell, Tissue and Organ Culture, 132(3), 545-559

    Article  CAS  Google Scholar 

  • Akin, M., Eyduran, S.P., Eyduran, E., Reed, B.M., 2020. Analysis of macro nutrient related growth responses using multivariate adaptive regression splines, Plant Cell, Tissue and Organ Culture, 140, 661-670.

    Article  Google Scholar 

  • Aksoy, A., Erturk, Y.E., Eyduran, E., Tariq, M.M., 2019. Utility of MARS Algorithm for Describing Non-Genetic Factors Affecting Pasture Revenue of Morkaraman Breed and Romanov × Morkaraman F1 Crossbred Sheep under Semi Intensive Conditions, Pakistan Journal of Zoology, 51(1), 235-240.

    Google Scholar 

  • Ali, M., Eyduran, E., Tariq, M. M., Tirink, C., Abbas, F., Bajwa, M. A., Baloch, M. H., Nizamani, A. H., Waheed, A., Awan, M. A., Shah, S. H., Ahmad, Z., Jan, S., 2015. Comparison of artificial neural network and decision tree algorithms used for predicting live weight at post weaning period from some biometrical characteristics in Harnai sheep. Pakistan Journal of Zoology 47:1579-1585.

    CAS  Google Scholar 

  • Ambarcioglu, P., Kaya, U., Ozen, D., Gurcan,I.S., 2017. An Examination of the Relationships Between Live Weight and BodyMeasurements in Karacabey Merino Sheep Through the Path Analysis Approach. Journalof the Faculty of Veterinary Medicine, Kafkas University, 23 (6), 857-863.

  • Arthur, C.K., Temeng, V.A., Ziggah, Y.Y., 2020. Multivariate Adaptive Regression Splines (MARS) approach to blast-induced ground vibration prediction, International Journal of Mining, Reclamation and Environment, 34(3), 198-222.

    Article  Google Scholar 

  • Aytekin, I., Eyduran, E., Karadas, K., Aksahan, R., Keskin, I., 2018. Prediction of Fattening Final Live Weight from some Body Measurements and Fattening Period in Young Bulls of Crossbred and Exotic Breeds using MARS Data Mining Algorithm. Pakistan Journal of Zoology 50(1), 189-195.

    Article  Google Scholar 

  • Breiman,L., Friedman, J. H., Olshen, R. A., Stone, C. J., 1984. Classification andregression trees. Chapman and Hall, WadsworthInc., New York, NY, USA.

  • Celik, S., Yilmaz, O., 2018. Prediction of body weight of Turkish tazi dogs using data mining Techniques: Classification and Regression Tree (CART) and multivariate adaptive regression splines (MARS), Pakistan Journal of Zoology, 50(2), 575-583.

    Article  Google Scholar 

  • Celik, S., Eyduran, E., Karadas, K., Tariq, M.M., 2017. Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan. Brazilian Journal of Animal Science, 46(11), 863-872.

    Google Scholar 

  • Eyduran, E., 2020. ehaGoF: Calculates Goodness of Fit Statistics. R package version 0.1.1.

  • Eyduran, E., Karakus K., Keskin S., Cengiz, F., 2008. Determination of factors influencing birth weight using regression tree (RT) method. Journal of Applied Animal Research, 34, 109–112.

    Article  Google Scholar 

  • Eyduran, E., Zaborski, D., Waheed, A., Celik, S., Karadas, K., Grzesiak, W., 2017. Comparison of the Predictive Capabilities of Several Data Mining Algorithms and Multiple Linear Regression in the Prediction of Body Weight by Means of Body Measurements in the Indigenous Beetal Goat of Pakistan. Pakistan Journal of Zoology 49(1), 257-265.

    Article  Google Scholar 

  • Eyduran, E., Akin, M., Eyduran, S.P., 2019. Application of Multivariate Adaptive Regression Splines through R Software, Nobel Academic Publishing, Ankara.

    Google Scholar 

  • Friedman, J., 1991. Multivariate adaptive regression splines, Annals of Statistics 19(1), 1–67.

    Google Scholar 

  • Grzesiak, W., Zaborski, D., 2012. Examples of the use of data mining methods in animal breeding. In: Data mining applications in engineering and medicine (ed. A Karahoca). InTech, Rijeka, Croatia, in IntechOpen 303–324.

  • Hussain, A., Akhtar, P., Ali, S., Younas, M., Shafiq, M., 2006a. Effect of inbreeding on pre-weaning growth traits in Thalli sheep. Pakistan Veterinary Journal, 26(3), 138-140.

    Google Scholar 

  • Hussain, A., Akhtar, P., Ali, S., Younas, M., Javed, K., 2006b. Inbreeding effects on post-weaning growth traits of Thalli sheep in Pakistan. Pakistan Journal of Agricultural Sciences, 43, 89-92.

    Google Scholar 

  • Hussain, A., Akhtar, P., Ali, S., Younas, M., Yaqoob, M., Babar, M.E., Kaved, K., Shakoor, A., 2013. Factors influencing body weights at different ages in Thalli sheep. Journal of Animal and Plant Sciences, 23(1), 1-6.

    Google Scholar 

  • Hussain, A., Akhtar, P., Ali, S., Javed, K., Younas, M., Shakoor, A., Waheed, U., 2014. Genetic analysis of post-weaning growth traits of Thalli sheep under tropical conditions. Tropical Animal Health and Production 46, 1527–1531.

    Article  Google Scholar 

  • Khan, M.A., Tariq, M.M., Eyduran, E., Tatliyer, A., Rafeeq, M., Abbas, F., Rashid, N., Awan, M.A., Javed, K., 2014. Estimating body weight from several body measurements in Harnai sheep without multicollinearity problem, The Journal of Animal & Plant Sciences, 24(1), 120-126.

    Google Scholar 

  • Kovalchuk, I.Y., Mukhitdinova, Z., Turdiyev, T., Madiyeva, G., Akin, M., Eyduran, E., Reed, B.M., 2017. Modeling some mineral nutrient requirements for micropropagated wild apricot shoot cultures, Plant Cell, Tissue Organ Culture, 129, 325–335.

    Article  CAS  Google Scholar 

  • Kovalchuk, I.Y., Mukhitdinova, Z., Turdiyev, T., Madiyeva, G., Akin, M., Eyduran, E., Reed, B.M., 2018. Nitrogen ions and nitrogen ion proportions impact the growth of apricot (Prunus armeniaca) shoot cultures. Plant Cell, Tissue Organ Culture, 133, 263–273.

    Article  CAS  Google Scholar 

  • Kuhn, M., 2020. caret: Classification and Regression Training. R package version 6.0-86.

  • Kuhn, M., Johnson, K., 2013. Applied Predictive Modeling. New York: Springer.

    Book  Google Scholar 

  • Kunene, N.W., Nesamvuni, A.E., Nsahlai, I.V., 2009. Determination of prediction equations for estimating body weight of Zulu (Nguni) sheep. Small Ruminant Research, 84, 41-46.

    Article  Google Scholar 

  • Matika, O., van Wyk, J.B., Erasmus, G.J., Baker, R.L., 2003. A description of growth, carcass and reproductive traits of Sabi sheep in Zimbabwe. Small Ruminant Research, 48, 119-126.

    Article  Google Scholar 

  • Mendes M. , Akkartal E., 2009. Regression tree analysis for predicting slaughter weight in broilers. Italian Journal of Animal Science, 8, 615-624.

    Article  Google Scholar 

  • Mendiburu, F.D., 2020. agricolae: Statistical Procedures for Agricultural Research. R package version 1.3-3.

    Google Scholar 

  • Milborrow, S., 2020a. rpart.plot: Plot ‘rpart’ Models: An Enhanced Version of ‘plot.rpart’. R package version 3.0.9.

  • Milborrow. Derived from mda:mars by Trevor Hastie and Rob Tibshirani. Uses Alan Miller’s Fortran utilities with Thomas Lumley’s leaps wrapper. 2020b. earth: Multivariate Adaptive Regression Splines. R package version 5.3.0.

  • Mohammad, M.T., Rafeeq, M., Bajwa, M.A., Awan, M.A., Abbas, F., Waheed, A., Bukhari, F.A., Akhtar, P., 2012. Prediction of body weight from body measurements using regression tree (RT) method for indigenous sheep breeds in Balochistan, Pakistan. The Journal of Animal & Plant Sciences, 22(1), 20-24.

    Google Scholar 

  • Olfaz, M., Tirink, C., Onder, H., 2019. Use of CART and CHAID algorithms in Karayaka sheep breeding. Journal of the Journal of the Faculty of aculty of Veterinary Medicine, Kafkas Uni erinary Medicine, Kafkas University, 25(1), 105-110.

    Google Scholar 

  • Petrović, M.P., Petrović, V.C., Muslić, D.R., Ilić, Z., Spasić, Z., Stojković, J., Milenković, M., 2012. Genetic and phenotypic aspects of the body measured traits in Merinolandschaf breed of sheep. Biotechnology in Animal Husbandry, 28(4), 733-741.

    Article  Google Scholar 

  • R Core Team 2020. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL

  • Rahim, S.M.A., Hasnain, S. and Farkhanda, J., 2011. Effect of calcium, magnesium, sodium and potassium on farm plantations of various agroecological zones of Punjab, African Journal of Plant Science, 5, 450-459.

    Google Scholar 

  • Revelle, W., 2020. psych: Procedures for Personality and Psychological Research, Northwestern University, Evanston, Illinois, USA, Version=2.0.12,.

  • Sabbioni, A., Beretti, V., Superchi, P., Ablondi, M., 2020. Body weight estimation from body measures in Cornigliese sheep breed, Italian Journal of Animal Science, 19:1, 25-30.

    Article  CAS  Google Scholar 

  • Taye, M., Bimerow, T., Yiyayew, A., Mekuriaw, S., Mekuriaw, G., 2012. Estimation of live body weight from linear body measurements for Farta Sheep. Online Journal of Animal and Feed Research, 2(1), 98-103.

    Google Scholar 

  • Therneau, T., Atkinson, B., 2019. rpart: Recursive Partitioning and Regression Trees. R package version 4.1-15.

  • Topal, M., Macit, M., 2004. Prediction of body weight from body measurements in morkaraman sheep, Journal of Applied Animal Research, 25(2), 97-100.

    Article  Google Scholar 

  • Tyasi, T.L., Eyduran, E., Celik, S., 2021. Comparison of tree-based regression tree methods for predicting live body weight from morphological traits in Hy-line silver brown commercial layer and indigenous Potchefstroom Koekoek breeds raised in South Africa. Tropical Animal Health and Production 53, 7.

    Article  Google Scholar 

  • Yakubu, A., 2012. Application of regression tree methodology in predicting the body weight of Uda sheep. Animal Science and Biotechnologies, 45 (2), 484-490.

    Google Scholar 

  • Zaborski, D., Ali, M., Eyduran, E., Grzesiak, W., Tariq, M.M., Abbas, F., Waheed, A., Tirink, C., 2019. Prediction of selected reproductive traits of indigenous Harnai sheep under the farm management system via various data mining algorithms. Pakistan Journal of Zoology, 51, 421-431.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations



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.

Corresponding author

Correspondence to Cem Tirink.

Ethics declarations

Ethics approval

The manuscript does not contain clinical studies or patient data.

Consent to participate

All the authors approved the final manuscript.

Consent to publication

All the authors consented the final manuscript.

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: