Development of mathematical models to predict dry matter intake in feedlot Santa Ines rams
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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Development of mathematical models to predict dry matter intake in feedlot Santa Ines rams. / Vieira, Pablo Almeida Sampaio; Pereira, Luiz Gustavo Ribeiro; Azevêdo, José Augusto Gomes; Neves, André Luiz Alves; Chizzotti, Mário Luiz; Dos Santos, Rafael Dantas; De Araújo, Gherman Garcia Leal; Mistura, Claudio; Chaves, Alexandre Vieira.
I: Small Ruminant Research, Bind 112, Nr. 1-3, 05.2013, s. 78-84.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Development of mathematical models to predict dry matter intake in feedlot Santa Ines rams
AU - Vieira, Pablo Almeida Sampaio
AU - Pereira, Luiz Gustavo Ribeiro
AU - Azevêdo, José Augusto Gomes
AU - Neves, André Luiz Alves
AU - Chizzotti, Mário Luiz
AU - Dos Santos, Rafael Dantas
AU - De Araújo, Gherman Garcia Leal
AU - Mistura, Claudio
AU - Chaves, Alexandre Vieira
N1 - Funding Information: Financial assistance for this research from Banco do Nordeste do Brasil, Universidade Federal do Vale do São Francisco, Empresa Brasileira de Pesquisa Agropecuária and Conselho Nacional de Desenvolvimento Científico e Tecnológico is gratefully acknowledged.
PY - 2013/5
Y1 - 2013/5
N2 - Mathematical models to predict the dry matter intake (DMI) of feedlot Santa Ines rams were developed and evaluated in this study. The available database had 100 experimental units from 13 studies. Study effect was integrated and random effects of their interactions as components of a hybrid model. The independent variables were initially adjusted to a model which included fixed effects for y-intercept and slope and random effects in y-intercept and slope study, using unstructured covariance model (e.g.: UN-unstructured). Study effect on database was verified, and then a meta-analysis procedure to develop DMI prediction equations was performed. For validation and comparisons between existing prediction equations in the national and international literature, independent data from one survey with 21 animals were used. Validation methods of the observed and predicted DMI were based on linear regression model adjustment of the observed values over predicted values. The following variables: average live weight (ALW), metabolic live weight (MLW0.75), average daily gain (ADG) and average daily gain2 (ADGsq) presented positive correlation with DMI. In contrast diet concentrate level showed a negative correlation. Among eight models examined, the following resulting equation [DMI (g/day)=238.74±114.56 (0.0398)+31.3574±4.2737 (<0.0001)×MLW+1.2623 ±0.2128 (<0.0001)×ADG-5.1837±0.7448 (<0.0001)×CON] has been found as the best fit model to predict DMI in feedlot Santa Ines rams.
AB - Mathematical models to predict the dry matter intake (DMI) of feedlot Santa Ines rams were developed and evaluated in this study. The available database had 100 experimental units from 13 studies. Study effect was integrated and random effects of their interactions as components of a hybrid model. The independent variables were initially adjusted to a model which included fixed effects for y-intercept and slope and random effects in y-intercept and slope study, using unstructured covariance model (e.g.: UN-unstructured). Study effect on database was verified, and then a meta-analysis procedure to develop DMI prediction equations was performed. For validation and comparisons between existing prediction equations in the national and international literature, independent data from one survey with 21 animals were used. Validation methods of the observed and predicted DMI were based on linear regression model adjustment of the observed values over predicted values. The following variables: average live weight (ALW), metabolic live weight (MLW0.75), average daily gain (ADG) and average daily gain2 (ADGsq) presented positive correlation with DMI. In contrast diet concentrate level showed a negative correlation. Among eight models examined, the following resulting equation [DMI (g/day)=238.74±114.56 (0.0398)+31.3574±4.2737 (<0.0001)×MLW+1.2623 ±0.2128 (<0.0001)×ADG-5.1837±0.7448 (<0.0001)×CON] has been found as the best fit model to predict DMI in feedlot Santa Ines rams.
KW - Meta-analysis
KW - Modelling
KW - Nutritional requirements
KW - Ruminants
KW - Santa Ines
UR - http://www.scopus.com/inward/record.url?scp=84876308919&partnerID=8YFLogxK
U2 - 10.1016/j.smallrumres.2012.10.007
DO - 10.1016/j.smallrumres.2012.10.007
M3 - Journal article
AN - SCOPUS:84876308919
VL - 112
SP - 78
EP - 84
JO - Small Ruminant Research
JF - Small Ruminant Research
SN - 0921-4488
IS - 1-3
ER -
ID: 324593509