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Research Article

Using multivariate adaptive regression splines and classification and regression tree data mining algorithms to predict body weight of Nguni cows

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Pages 534-539 | Received 16 Nov 2021, Accepted 02 Aug 2022, Published online: 08 Aug 2022

References

  • Adhianto K, Harris I, Nugroho P, Putra WPB. 2020. Prediction of body weight through body measurements in boerawa (boer × etawah crossbred) bucks at tanggamus regency of Indonesia. Bulgarian J. Agric. Sci. 26(6):1273–1279.
  • Akin M, Eyduran E, Reed BM. 2017. Use of RSM and CHAID data mining algorithm for predicting mineral nutrition of hazelnut. PCTOC. 128:303–316.
  • Alabi OJ, Egena SSA, Ng’ambi JW, Norris D. 2012. Comparative study of three indigenous chicken breeds of South Africa: Body weight and linear body measurements. Agricultural Journal. 7:220–225. doi:10.3923/aj.2012.220.225.
  • Altay Y, Boztepe S, Eyduran E, Keskin I, Tariq MM, Bukhari FA, Ali I. 2021. Description of factors affecting wool fineness in Karacabey Merino sheep using chaid and Mars algorithms. Pakistan J. Zool. 53(2):691–697.
  • Aytekin I, Eyduran E, Karadas K, Akşahan R, Keskin I. 2018b. 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. Pak J Zool. 50(1):189–195. doi:10.17582/journal.pjz/2018.50.1.189.195.
  • Aytekin I, Eyduran E, Keskin I. 2018a. Detecting the relationship of california mastitis test (CMT) with electrical conductivity, composition and quality of the milk in Holstein-Friesian and Brown Swiss cattle breeds using CART analysis. Fresenius Environ. Bull. 27(6):4559–4565.
  • Breiman L, Friedman J, Olshen R, Stone C. 1984. Classification and regression trees. Monterey, CA: Wadsworth and Brooks.
  • Celik S. 2019. Comparing predictive performances of tree-based data mining algorithms and MARS algorithm in the prediction of live body weight from body traits in Pakistan goats. Pak J Zool. 51(4):1447–1456. doi:10.17582/journal.pjz/2019.51.4.1447.1456.
  • Celik S, Yilmaz O. 2017. Comparison of different data mining algorithms for prediction of body weight from several morphological measurements in dogs. J. Anim. Plant Sci. 27(1):57–64.
  • Celik S, Yilmaz O. 2021. The relationship between the coat colors of kars shepherd Dog and its morphological characteristics using some data mining methods. Int. J. Livest. Res. 11(1):53–61.
  • Erturk YE, Aksoy A, Tariq MM. 2018. Effect of selected variables identified by MARS on fattening final live weight of crossbred beef cattle in eastern Turkey. Pak J Zool. 50(4):1403–1412. doi:10.17582/journal.pjz/2018.50.4.1403.1412.
  • 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. Pak J Zool. 49(1):257–265.
  • FAO. 2012. Phenotypic characterization of animal genetic resources. FAO Animal Production and Health Guidelines, No. 11. Rome.
  • Faraz A, Tirink C, Eyduran E, Waheed A, Tauqir NA, Nabeel MS, Tariq MM. 2021. 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):1−12. doi:10.1007/s11250-021-02748-6.
  • Fatih A, Celik S, Eyduran E, Tirink C, Tariq MM, Sheikh IS, Faraz A, Waheed A. 2021. Use of MARS algorithm for predicting mature weight of different camel (camelus dromedarius) breeds reared in Pakistan and morphological characterization via cluster analysis. Trop Anim Health Prod. 53(191)1−14. doi:10.1007/s11250-021-02633-2.
  • Haq MS, Budisatria IGS, Panjono P, Maharani D. 2020. Prediction of live body weight using body measurements for jawa brebes (jabres) cattle. J. Anim. Plant Sci. 30(3):552–559.
  • Huma ZE, Iqbal F. 2019. Predicting the body weight of balochi sheep using a machine learning approach. Turkish Journal of Veterinary and Animal Sciences. 43:500–506.
  • IBM SPSS. 2020. Statistical packages for social sciences for windows: base system user’s guide, IBM statistics, 27. Chicago: SPSS Inc. doi:10.2527/jas.2013-6967.
  • Karabacak A, Celik S, Tatliyer A, Keskin I, Erturk YE, Eyduran E, Javed Y, Tariq MM. 2017. Estimation of cold carcass weight and body weight from several body measurements in sheep through various data mining algorithms. Pak J Zool. 49(5):1731–1738.
  • Kusminanto RY, Alawiansyah A, Pramono A, Cahyadi M. 2020. Body weight and body measurement characteristics of seven goat breeds in Indonesia. IOP Conference Series: Earth and Environmental Science. 478(1):012039–012167.
  • Lukuyu MN, Gibson JP, Savage DB, Duncan AJ, Mujibi FDN, Okeyo AM. 2016. Use of body linear measurements to estimate liveweight of crossbred dairy cattle in smallholder farms in kenya. SpringerPlus. 5(63):1−14. doi:10.1186/s40064-016-1698-3.
  • Madilindi MA, Cuthbert BB, Evison B, Yandisiwe PS, Khanyisani SN, Maria GT, Bongani SM, Ntanganedzeni OM. 2020. Genetic diversity and relationships among three southern African Nguni cattle populations. Trop Anim Health Prod. 52:753–762. doi:10.1007/s11250-019-02066-y.
  • Maiwashe N, Bradfield MJ, Theron HE, Van Wyk JB. 2002. Genetic parameter estimates for body measurements and growth traits in South African bonsmara cattle. Livest Prod Sci. 75(3):293–300.
  • Mamogobo MD, Mapholi NO, Nephawe KA, Nedambale TL, Mpofu TJ, Sanarana YP, Mtileni BJ. 2021. Genetic characterisation of non-descript cattle populations in communal areas of South Africa. Animal Production Science. 61:84–91. doi:10.1071/AN20030.
  • Mathapo MC, Mugwabana TJ, Tyasi TL. 2022. 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):1−9. doi:10.1007/s11250-022-03096-9.
  • Putra WPB, Sumadi HT, Saumar H. 2015. Relationship between body weight and body measurements of aceh cattle. Mal J. Anim. Sci. 18(1):35–43.
  • R Core Team. 2018. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. https://www.R-project.org/.
  • Sahu SS, Choursia SK, Chaturvedani AK, Prakash OM. 2017. Correlation between body weight and linear body measurements in adult female sahiwal cattle. The Indian Journal of Veterinary Sciences and Biotechnology. 12(3):90–93. doi:10.21887/ijvsbt.v12i3.7103.
  • Sanarana Y, Visser C, Bosman L, Nephawe K, Maiwashe A, van Marle-Köster E. 2016. Genetic diversity in South African Nguni cattle ecotypes based on microsatellite markers. Trop Anim Health Prod. 48:379–385. doi:10.1007/s11250-015-0962-9.
  • Şengül T, Çelik Ş, Şengül Ö. 2020. Use of multivariate adaptive regression splines (MARS) for predicting parameters of breast meat in quails. J. Anim. Plant Sci. 30(4):786–793.
  • Tyasi TL, Makgowo KM, Mokoena K, Rashijane LT, Mathapo MC, Danguru LW, Molabe KM, Bopape PM, Mathye ND, Maluleke D. 2020. Multivariate adaptive regression splines data mining algorithm for prediction of body weight of Hy-line silver brown commercial layer chicken breed. Advances in Animal and Veterinary Sciences. 8(8):794–799. doi:10.17582/journal.aavs/2020/8.8.794.799.
  • Tyasi TL, Mkhonto AT, Mathapo MC, Molabe KM. 2021. Regression tree analysis to predict body weight of South African non-descript goats raised at syferkuil farm, capricorn district of South Africa. Biotechnology in Animal Husbandry. 37(4):293–304. doi:10.2298/BAH2104293T.
  • Tyasi TL, Tyasi YF, Tyasi AL, Lagu S, Ngambu S. 2015. A study of relationship between body weight and morphological traits by using path analysis in South African indigenous sheep. J. Boil. Agric. Health. 5(10):1−4.