Data/hora: 01/06/2024 15:46:33

Provedor de dados: | 96
País: | Brazil
Título: | Determination of factors affecting dairy cattle: a case study of Ardahan province using data mining algorithms
Autores: | Karadas,Koksal; Birinci,Avni.
Data: | 2019-01-01
Ano: | 2019
Palavras-chave: | Milk yield; Production economics; Statistical model.
Resumo: | ABSTRACT This study was conducted to compare predictive performances of different data-mining algorithms for determining factors influencing the average daily milk yield at dairy cattle enterprises of Ardahan province, located in the Eastern Anatolia region of Turkey. The algorithms employed in the present study were Classification and Regression Tree (CART), Chi-Square Automatic Interaction Detector (CHAID), Exhaustive Chi-Square Automatic Interaction Detector (Exhaustive CHAID), Multivariate Adaptive Regression Splines (MARS), and Multilayer Perceptron (MLP). The MARS algorithm outperformed the other algorithms in the study. Visual results of CART revealed that the culture-breed cows with a lactation length greater than 237.500 days had the highest milk yield (10.64 kg/day). Culture-breed cows calving earlier than the 4th month gave the highest yield of approximately 10 kg/day in the regression tree of CHAID. The Exhaustive CHAID results were almost the same as the structure of the CHAID. The use of MARS may provide an opportunity to detect factors affecting milk production (breed, feed supply, type of milking, mastitis control, cow year group, and lactation length) and their interactions. Moreover, the MARS algorithm may be useful in making an accurate decision about increasing milk yield per cow.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982019000100106
Editor: | Sociedade Brasileira de Zootecnia
Relação: | 10.1590/rbz4820170263
Formato: | text/html
Fonte: | Revista Brasileira de Zootecnia  v.48 2019
Fonte: | info:eu-repo/semantics/openAccess