Siyah Alacalar’ın K-Ortalamalı Kümeleme Yöntemi İle Sınıflandırılması

Anahtar Kelimeler:

Siyah alaca, süt verimi, kümeleme, K-ortalamalı kümeleme

Clustering of Holstein Friesians Using K-Means Method

By cluster analysis units or variables can be grouped according to similarities or differences in terms of their properties. In this study total of 4496 Holstein Friesian cows were grouped two, three and four clusters according to their herd, age at first calving, lactation length and 305 day milk yields. Nonhierarchical k-means clustering technique is used for this purpose. Related traits were found statically significant for clustering of Holsteins (P<0.01). Holsteins were divided into three clusters and these clusters were found statistically different (P<0.01). The correct classification percentage of cows was 98%. In the third cluster Holsteins which have the highest milk yield, the lowest age of first calving and 305-day lactation period were proposed for breeding programs.

Keywords:

Holstein, milk yield, cluster, K-means classification nonhierarchical,

PDF

___

Akıllı A and H. Atıl. 2013. Classification of milk yield characteristics with cluster analysis. 7th International Balkan Animal Conference, BALNIMALCON. Namık Kemal University, Faculty of Agriculture, Department of Animal Science, 3-5 October, Tekirdağ, Turkey.
Chernoff H. 1972. Metric considerations in cluster analysis. Proceedings of the 7th Berkeley. Symposium on Mathematical Statistics and Probability. 1:621-629.
Çokluk Ö., G. Şekercioğlu and S. Büyüköztürk. 2010. Multivariable Statistics for Social Sciences (In Turkish). Pegem Akademi Yayıncılık, Ankara.
Görgülü Ö. 2010. Classification of dairy cattle in terms of some milk yield characteristics using by fuzzy clustering. Journal of Animal and Veterinary Advances 9:1947-1951 DOI 10.3923/javaa.2010. 1947.1951.
Gürcan S. and H. Akçapınar. 2002. Alman et ve Karacabey Merinosu koyunlarının canlı ağırlık, vücut ölçüleri ve yapağı inceliği yönünden kümeleme analizi ile incelenmesi. Turkish Journal of Veterinary and Animal Sciences 26:1255-1261.
Hair J, B. Black, B. Babin, R. Anderson and R. Tatham. 2006. Multivariate Data Analysis. 6th ed. Prentice Hall, Upper Saddle River, New Jersey.
Johnson R.A. and D.W. Wichern. 2005. Applied Multivariate Statistical Analysis. 5th ed. Prentice Hall, Upper Saddle River, New Jersey.
Kılıç İ. ve C. Özbeyaz. 2010. Bulanık kümeleme analizinin koyun yetiştiriciliğinde kullanımı ve bir uygulama. Kocatepe Veterinary Journal 3: 31-37.
Küçükönder H, E. Efe, E. Akyol, M. Şahin ve F. Üçkardeş. 2004. Çok değişkenli istatistiksel analizlerin hayvancılıkta kullanımı. 4th National Animal Science Congress, 1-3 September, Isparta, Turkey.
Küçükönder H, T. Ayaşan and H. Hızlı. 2015. Classification of Holstein dairy cattles in terms of parameters some milk component belongs by using the fuzzy cluster analysis. Kafkas Universitesi Veteriner Fakültesi Dergisi, 23: 601-606 DOI 10.9775/kvfd.2015.12987.
McMahon R.G.P. 2001. Deriving an empirical development taxonomy for manufacturing smes using data from Australia’s business longitudinal survey. Small Business Economics 17:197–212.
Ruttner F, L. Tassencour and J. Louveaux. 1978. Biometrical statistical analysis of the geographic variability of Apis Mellifera L. Apidologie 9:363-381.
Singh N. and D. Singh. 2012. Performance evaluation of k-means and heirarichal clustering in terms of accuracy and running time. International Journal of Computer Science and Information Technologies 3:4119-4121.
Tabachnick B.G. and L.S. Fidell. 2007. Using Multivariate Statistics. 5th ed. Pearson.
Vogt W. and D. Nagel. 1992. Cluster analysis in diagnosis. Clinical Chemistry 38:182–198.
Yakubu A. and S.B. Ugbo. 2011. An assessment of biodiversity in morphological traits of Muscovy ducks in Nigeria using discriminant analysis. International Conference on Biology, Environment and Chemistry, Singapore, 1:389-391.
Yim O. and K.T. Ramdeen. 2015. Hierarchical cluster analysis: comparison of three linkage measures and application to psychological data. The Quantitative Methods for Psychology 1:8-21.