Selection of models of lactation curves to use in milk production simulation systems

Detalhes bibliográficos
Autor(a) principal: Cunha,Daniel de Noronha Figueiredo Vieira da
Data de Publicação: 2010
Outros Autores: Pereira,José Carlos, Silva,Fabyano Fonseca e, Campos,Oriel Fajardo de, Braga,José Luis, Martuscello,Janaina Azevedo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Zootecnia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982010000400026
Resumo: The objective of this study was to select models of lactation curves with a better adjustment to the observed data in models of milk production simulation systems. A data base on 6,459 recordings of daily milk production was used. These data were obtained from monthly and fortnightly controls of milk between 2004 and 2007, from 472 lactations of animals from ten different milking cow herd farms. Based on rolling averages of milk production (MP-L/day) per cow, the ten herd farms were divided into low (L < 15), medium (15 <M < 20) and high (H &gt; 20). Data were also divided according to the lactation numbers in first, second, third or greater. Eight lactation curve models commonly used in literature were compared. The models were individually adjusted for each lactation. The goodness of fit used for comparison of those models was the coefficient of determination, mean square error, mean square prediction error and the Bayesian information criterion. The values for the goodness of fit obtained in each model were compared by using 95% probability confidence interval. Wilmink (1987) model showed a better adjustment for cows of the first lactation numbers, whereas the Wood (1967) model showed a better adjustment for cows of the third or greater lactations numbers for the low milk production groups. Wood model showed a better adjustment for all the lactation numbers for the medium milk production group. Dijkstra (1997) model showed a better adjustment for all lactation numbers for the high milk production group. Despite of being more recent, the model by Pollott (2000), mechanist based and with a higher number of parameters, showed a good convergence for the used data.
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spelling Selection of models of lactation curves to use in milk production simulation systemsdairy cattlemodelingnon-linear modelThe objective of this study was to select models of lactation curves with a better adjustment to the observed data in models of milk production simulation systems. A data base on 6,459 recordings of daily milk production was used. These data were obtained from monthly and fortnightly controls of milk between 2004 and 2007, from 472 lactations of animals from ten different milking cow herd farms. Based on rolling averages of milk production (MP-L/day) per cow, the ten herd farms were divided into low (L < 15), medium (15 <M < 20) and high (H &gt; 20). Data were also divided according to the lactation numbers in first, second, third or greater. Eight lactation curve models commonly used in literature were compared. The models were individually adjusted for each lactation. The goodness of fit used for comparison of those models was the coefficient of determination, mean square error, mean square prediction error and the Bayesian information criterion. The values for the goodness of fit obtained in each model were compared by using 95% probability confidence interval. Wilmink (1987) model showed a better adjustment for cows of the first lactation numbers, whereas the Wood (1967) model showed a better adjustment for cows of the third or greater lactations numbers for the low milk production groups. Wood model showed a better adjustment for all the lactation numbers for the medium milk production group. Dijkstra (1997) model showed a better adjustment for all lactation numbers for the high milk production group. Despite of being more recent, the model by Pollott (2000), mechanist based and with a higher number of parameters, showed a good convergence for the used data.Sociedade Brasileira de Zootecnia2010-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982010000400026Revista Brasileira de Zootecnia v.39 n.4 2010reponame:Revista Brasileira de Zootecnia (Online)instname:Sociedade Brasileira de Zootecnia (SBZ)instacron:SBZ10.1590/S1516-35982010000400026info:eu-repo/semantics/openAccessCunha,Daniel de Noronha Figueiredo Vieira daPereira,José CarlosSilva,Fabyano Fonseca eCampos,Oriel Fajardo deBraga,José LuisMartuscello,Janaina Azevedoeng2010-08-31T00:00:00Zoai:scielo:S1516-35982010000400026Revistahttps://www.rbz.org.br/pt-br/https://old.scielo.br/oai/scielo-oai.php||bz@sbz.org.br|| secretariarbz@sbz.org.br1806-92901516-3598opendoar:2010-08-31T00:00Revista Brasileira de Zootecnia (Online) - Sociedade Brasileira de Zootecnia (SBZ)false
dc.title.none.fl_str_mv Selection of models of lactation curves to use in milk production simulation systems
title Selection of models of lactation curves to use in milk production simulation systems
spellingShingle Selection of models of lactation curves to use in milk production simulation systems
Cunha,Daniel de Noronha Figueiredo Vieira da
dairy cattle
modeling
non-linear model
title_short Selection of models of lactation curves to use in milk production simulation systems
title_full Selection of models of lactation curves to use in milk production simulation systems
title_fullStr Selection of models of lactation curves to use in milk production simulation systems
title_full_unstemmed Selection of models of lactation curves to use in milk production simulation systems
title_sort Selection of models of lactation curves to use in milk production simulation systems
author Cunha,Daniel de Noronha Figueiredo Vieira da
author_facet Cunha,Daniel de Noronha Figueiredo Vieira da
Pereira,José Carlos
Silva,Fabyano Fonseca e
Campos,Oriel Fajardo de
Braga,José Luis
Martuscello,Janaina Azevedo
author_role author
author2 Pereira,José Carlos
Silva,Fabyano Fonseca e
Campos,Oriel Fajardo de
Braga,José Luis
Martuscello,Janaina Azevedo
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Cunha,Daniel de Noronha Figueiredo Vieira da
Pereira,José Carlos
Silva,Fabyano Fonseca e
Campos,Oriel Fajardo de
Braga,José Luis
Martuscello,Janaina Azevedo
dc.subject.por.fl_str_mv dairy cattle
modeling
non-linear model
topic dairy cattle
modeling
non-linear model
description The objective of this study was to select models of lactation curves with a better adjustment to the observed data in models of milk production simulation systems. A data base on 6,459 recordings of daily milk production was used. These data were obtained from monthly and fortnightly controls of milk between 2004 and 2007, from 472 lactations of animals from ten different milking cow herd farms. Based on rolling averages of milk production (MP-L/day) per cow, the ten herd farms were divided into low (L < 15), medium (15 <M < 20) and high (H &gt; 20). Data were also divided according to the lactation numbers in first, second, third or greater. Eight lactation curve models commonly used in literature were compared. The models were individually adjusted for each lactation. The goodness of fit used for comparison of those models was the coefficient of determination, mean square error, mean square prediction error and the Bayesian information criterion. The values for the goodness of fit obtained in each model were compared by using 95% probability confidence interval. Wilmink (1987) model showed a better adjustment for cows of the first lactation numbers, whereas the Wood (1967) model showed a better adjustment for cows of the third or greater lactations numbers for the low milk production groups. Wood model showed a better adjustment for all the lactation numbers for the medium milk production group. Dijkstra (1997) model showed a better adjustment for all lactation numbers for the high milk production group. Despite of being more recent, the model by Pollott (2000), mechanist based and with a higher number of parameters, showed a good convergence for the used data.
publishDate 2010
dc.date.none.fl_str_mv 2010-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982010000400026
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982010000400026
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S1516-35982010000400026
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Zootecnia
publisher.none.fl_str_mv Sociedade Brasileira de Zootecnia
dc.source.none.fl_str_mv Revista Brasileira de Zootecnia v.39 n.4 2010
reponame:Revista Brasileira de Zootecnia (Online)
instname:Sociedade Brasileira de Zootecnia (SBZ)
instacron:SBZ
instname_str Sociedade Brasileira de Zootecnia (SBZ)
instacron_str SBZ
institution SBZ
reponame_str Revista Brasileira de Zootecnia (Online)
collection Revista Brasileira de Zootecnia (Online)
repository.name.fl_str_mv Revista Brasileira de Zootecnia (Online) - Sociedade Brasileira de Zootecnia (SBZ)
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