Data/hora: 16/06/2024 10:18:32

Provedor de dados: 	63	
País: 	Brazil	
Título: 	Using near infrared spectroscopy to predict metabolizable energy of corn for pigs	
Autores: 	Ferreira,Silvia Letícia; Vasconcellos,Ricardo Souza; Rossi,Robson Marcelo; Paula,Vinicius Ricardo Cambito de; Fachinello,Marcelise Regina; Huepa,Laura Marcela Díaz; Pozza,Paulo Cesar.	
Data: 	2018-12-01	
Ano: 	2018	
Palavras-chave: 	Chemical composition; Prediction equations; Validation; Swine.	
Resumo: 	ABSTRACT: The chemical composition of corn is variable and the knowledge of its chemical and energetic composition is required for an accurate formulation of the diet. This study aimed to determine the chemical composition, that is, dry matter (DM), mineral matter (MM), neutral detergent fiber (NDF), acid detergent fiber (ADF), ether extract (EE), crude protein (CP), gross energy (GE) and energetic values of different varieties (batches) of corn and validate mathematical models to predict the metabolizable energy values (ME) of corn for pigs using near infrared spectroscopy (NIRS). Corn samples were scanned in the spectrum range between 1,100 and 2,500 nm, the model parameters were estimated by the modified partial least squares (MPLS) method. Ten prediction equations were inserted into the NIRS and used to estimate the ME values. The first degree linear regression models of the estimated ME values in function of the observed ME values were adjusted. The existence of a linear ratio was evaluated by detecting the significance to posterior estimates of the straight line parameters. The values of digestible energy and ME ranged from 3,400 to 3,752 and 3,244 to 3,611 kcal kg−1, respectively. The prediction equations, ME1 = 4334 – 8.1MM + 4.1EE – 3.7NDF; ME2 = 4,194 – 9.2MM + 1.0CP + 4.1EE – 3.5NDF; and ME7 = 16.13 – 9.5NDF + 16EE + (23CP × NDF) – (138MM × NDF) were the most adequate to predict the ME values of corn by using NIRS.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162018000600486	
Editor: 	São Paulo - Escola Superior de Agricultura "Luiz de Queiroz"	
Relação: 	10.1590/1678-992x-2016-0509	
Formato: 	text/html	
Fonte: 	Scientia Agricola  v.75 n.6 2018	
Fonte: 	info:eu-repo/semantics/openAccess