Logotipo do repositório
 

Publicação:
Empirical equations for drinking water intake prediction of growing lambs: Meta-analysis

Carregando...
Imagem de Miniatura

Orientador

Coorientador

Pós-graduação

Curso de graduação

Título da Revista

ISSN da Revista

Título de Volume

Editor

Tipo

Artigo

Direito de acesso

Resumo

A meta-analysis was conducted to develop and evaluate new empirical predictive models for drinking water intake (DWI) of growing lambs. A large dataset containing 213 experimental diets from 47 experiments published in 44 peer-reviewed papers was built. Selected explanatory variables were grouped into animal (bodyweight initial (BWi); body weight final (BWf); average daily gain (ADG); feed conversion ratio (FCR); nitrogen intake (Nint), diet composition (dry matter; ash; crude protein (CP); neutral detergent fiber; forage), dry matter intake (DMI) and total digestible nutrient (TDN) and/or total digestible nutrient intake (TDNI) inputs. To develop predictive models, the dataset (peer-reviewed papers) was randomly divided into two subsets for statistical analyses. The first data subset was used to develop equations to predict DWI (27 peer-review papers; 28 experiments; 139 experimental diets), and the second data subset was used to assess the adequacy of the predictive models (17 peer-review papers; 19 experiments; 74 experimental diets). Ash was the main diet input affecting DWI in growing lambs, while FCR affected DWI more than ADG and Nint among the animal inputs. For growing lambs, the use of predictor variables associated with energy requirements improved the accuracy of the models when compared to those which used DMI. Among the developed models, the complete ones, which include diet and animal input, present better predictive quality. The use of the Diet + Animal Ib Model is recommended for the prediction of DWI in growing lambs.

Descrição

Palavras-chave

Mathematical models, Meat production, Nutritional systems

Idioma

Inglês

Como citar

Small Ruminant Research, v. 203.

Itens relacionados

Coleções

Unidades

Departamentos

Cursos de graduação

Programas de pós-graduação