Identification of Cows Susceptible to Mastitis based on Selected Genotypes by Using Decision Trees and A Generalized Linear Model

The aim of the present study was to: 1) check whether it would be possible to detect cows susceptible to mastitis at an early stage of their utilization based on selected genotypes and basic production traits in the first three lactations using ensemble data mining methods (boosted classification tr...

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Autores principales:	Zaborski Daniel, Proskura Witold Stanisław, Wojdak-Maksymiec Katarzyna, Grzesiak Wilhelm
Formato:	article
Lenguaje:	EN
Publicado:	Sciendo 2016
Materias:	lactoferrin tumor necrosis factor alpha lysozyme defensins mastitis susceptibility classification trees Veterinary medicine SF600-1100
Acceso en línea:	https://doaj.org/article/c8ef11f33c26413f8bf8a3b2a906ca7d
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spelling	oai:doaj.org-article:c8ef11f33c26413f8bf8a3b2a906ca7d2021-11-17T21:27:51ZIdentification of Cows Susceptible to Mastitis based on Selected Genotypes by Using Decision Trees and A Generalized Linear Model1820-744810.1515/acve-2016-0028https://doaj.org/article/c8ef11f33c26413f8bf8a3b2a906ca7d2016-09-01T00:00:00Zhttps://doi.org/10.1515/acve-2016-0028https://doaj.org/toc/1820-7448The aim of the present study was to: 1) check whether it would be possible to detect cows susceptible to mastitis at an early stage of their utilization based on selected genotypes and basic production traits in the first three lactations using ensemble data mining methods (boosted classification tress – BT and random forest – RF), 2) find out whether the inclusion of additional production variables for subsequent lactations will improve detection performance of the models, 3) identify the most significant predictors of susceptibility to mastitis, and 4) compare the results obtained by using BT and RF with those for the more traditional generalized linear model (GLZ). A total of 801 records for Polish Holstein-Friesian Black-and-White cows were analyzed. The maximum sensitivity, specificity and accuracy of the test set were 72.13%, 39.73%, 55.90% (BT), 86.89%, 17.81%, 59.49% (RF) and 90.16%, 8.22%, 58.97% (GLZ), respectively. Inclusion of additional variables did not have a significant effect on the model performance. The most significant predictors of susceptibility to mastitis were: milk yield, days in milk, sire’s rank, percentage of Holstein-Friesian genes, whereas calving season and genotypes (lactoferrin, tumor necrosis factor alpha, lysozyme and defensins) were ranked much lower. The applied models (both data mining ones and GLZ) showed low accuracy in detecting cows susceptible to mastitis and therefore some other more discriminating predictors should be used in future research.Zaborski DanielProskura Witold StanisławWojdak-Maksymiec KatarzynaGrzesiak WilhelmSciendoarticlelactoferrintumor necrosis factor alphalysozymedefensinsmastitis susceptibilityclassification treesVeterinary medicineSF600-1100ENActa Veterinaria, Vol 66, Iss 3, Pp 317-335 (2016)
institution	DOAJ
collection	DOAJ
language	EN
topic	lactoferrin tumor necrosis factor alpha lysozyme defensins mastitis susceptibility classification trees Veterinary medicine SF600-1100
spellingShingle	lactoferrin tumor necrosis factor alpha lysozyme defensins mastitis susceptibility classification trees Veterinary medicine SF600-1100 Zaborski Daniel Proskura Witold Stanisław Wojdak-Maksymiec Katarzyna Grzesiak Wilhelm Identification of Cows Susceptible to Mastitis based on Selected Genotypes by Using Decision Trees and A Generalized Linear Model
description	The aim of the present study was to: 1) check whether it would be possible to detect cows susceptible to mastitis at an early stage of their utilization based on selected genotypes and basic production traits in the first three lactations using ensemble data mining methods (boosted classification tress – BT and random forest – RF), 2) find out whether the inclusion of additional production variables for subsequent lactations will improve detection performance of the models, 3) identify the most significant predictors of susceptibility to mastitis, and 4) compare the results obtained by using BT and RF with those for the more traditional generalized linear model (GLZ). A total of 801 records for Polish Holstein-Friesian Black-and-White cows were analyzed. The maximum sensitivity, specificity and accuracy of the test set were 72.13%, 39.73%, 55.90% (BT), 86.89%, 17.81%, 59.49% (RF) and 90.16%, 8.22%, 58.97% (GLZ), respectively. Inclusion of additional variables did not have a significant effect on the model performance. The most significant predictors of susceptibility to mastitis were: milk yield, days in milk, sire’s rank, percentage of Holstein-Friesian genes, whereas calving season and genotypes (lactoferrin, tumor necrosis factor alpha, lysozyme and defensins) were ranked much lower. The applied models (both data mining ones and GLZ) showed low accuracy in detecting cows susceptible to mastitis and therefore some other more discriminating predictors should be used in future research.
format	article
author	Zaborski Daniel Proskura Witold Stanisław Wojdak-Maksymiec Katarzyna Grzesiak Wilhelm
author_facet	Zaborski Daniel Proskura Witold Stanisław Wojdak-Maksymiec Katarzyna Grzesiak Wilhelm
author_sort	Zaborski Daniel
title	Identification of Cows Susceptible to Mastitis based on Selected Genotypes by Using Decision Trees and A Generalized Linear Model
title_short	Identification of Cows Susceptible to Mastitis based on Selected Genotypes by Using Decision Trees and A Generalized Linear Model
title_full	Identification of Cows Susceptible to Mastitis based on Selected Genotypes by Using Decision Trees and A Generalized Linear Model
title_fullStr	Identification of Cows Susceptible to Mastitis based on Selected Genotypes by Using Decision Trees and A Generalized Linear Model
title_full_unstemmed	Identification of Cows Susceptible to Mastitis based on Selected Genotypes by Using Decision Trees and A Generalized Linear Model
title_sort	identification of cows susceptible to mastitis based on selected genotypes by using decision trees and a generalized linear model
publisher	Sciendo
publishDate	2016
url	https://doaj.org/article/c8ef11f33c26413f8bf8a3b2a906ca7d
work_keys_str_mv	AT zaborskidaniel identificationofcowssusceptibletomastitisbasedonselectedgenotypesbyusingdecisiontreesandageneralizedlinearmodel AT proskurawitoldstanisław identificationofcowssusceptibletomastitisbasedonselectedgenotypesbyusingdecisiontreesandageneralizedlinearmodel AT wojdakmaksymieckatarzyna identificationofcowssusceptibletomastitisbasedonselectedgenotypesbyusingdecisiontreesandageneralizedlinearmodel AT grzesiakwilhelm identificationofcowssusceptibletomastitisbasedonselectedgenotypesbyusingdecisiontreesandageneralizedlinearmodel
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Identification of Cows Susceptible to Mastitis based on Selected Genotypes by Using Decision Trees and A Generalized Linear Model

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