Data/hora: 27/07/2024 07:43:39

Provedor de dados: 	86	
País: 	Brazil	
Título: 	Rapid non-invasive assessment of quality parameters in ground soybean using near-infrared spectroscopy	
Autores: 	Santos,Larissa Rocha dos; Zangirolami,Marcela de Souza; Silva,Núbia Oliveira; Valderrama,Patrícia; Março,Paulo Henrique.	
Data: 	2018-01-01	
Ano: 	2018	
Palavras-chave: 	Glycine max; Chemometric methods; Crude protein; Multivariate calibration; Partial least squares; Total lipids.	
Resumo: 	Abstract: The objective of this work was to evaluate multivariate calibration models to predict total lipids, crude protein, and moisture content in grinded soybean grains using near-infrared spectroscopy and partial least squares (PLS). Three hundred samples of grinded soybean, evaluated in duplicate, were used for reference and spectral measurements. The PLS models for total lipids, crude protein, and moisture were validated by figures of merit for accuracy and precision, respectively, of 0.75 and 0.67 for total lipids, 0.51 and 0.46 for crude protein, and 0.97 and 0.99 for moisture. The PLS models developed for total lipids, crude protein, and moisture can be used as an alternative methodology for the determination of physicochemical parameters, and, therefore, they can be applied in quality control in soybean processing industries.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2018000100097	
Editor: 	Embrapa Secretaria de Pesquisa e Desenvolvimento

Pesquisa Agropecuária Brasileira	
Relação: 	10.1590/s0100-204x2018000100011	
Formato: 	text/html	
Fonte: 	Pesquisa Agropecuária Brasileira  v.53 n.1 2018	
Fonte: 	info:eu-repo/semantics/openAccess