Rapid non-invasive assessment of quality parameters in ground soybean using near-infrared spectroscopy

Authors

  • Larissa Rocha dos Santos Universidade Tecnológica Federal do Paraná, Via Rosalina Maria dos Santos, no 1.233, Caixa Postal 271, CEP 87301-899 Campo Mourão, PR.
  • Marcela de Souza Zangirolami Universidade Tecnológica Federal do Paraná, Via Rosalina Maria dos Santos, no 1.233, Caixa Postal 271, CEP 87301-899 Campo Mourão, PR.
  • Núbia Oliveira Silva Universidade Tecnológica Federal do Paraná, Via Rosalina Maria dos Santos, no 1.233, Caixa Postal 271, CEP 87301-899 Campo Mourão, PR.
  • Patrícia Valderrama Universidade Tecnológica Federal do Paraná, Via Rosalina Maria dos Santos, no 1.233, Caixa Postal 271, CEP 87301-899 Campo Mourão, PR
  • Paulo Henrique Março Universidade Tecnológica Federal do Paraná, Via Rosalina Maria dos Santos, no 1.233, Caixa Postal 271, CEP 87301-899 Campo Mourão, PR.

DOI:

https://doi.org/10.1590/S1678-3921.pab2018.v53.25076

Keywords:

Glycine max, chemometric methods, crude protein, multivariate calibration, partial least squares, total lipids

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 inquality control in soybean processing industries.

Author Biographies

Larissa Rocha dos Santos, Universidade Tecnológica Federal do Paraná, Via Rosalina Maria dos Santos, no 1.233, Caixa Postal 271, CEP 87301-899 Campo Mourão, PR.

Lattes: http://lattes.cnpq.br/0320894292639373

Marcela de Souza Zangirolami, Universidade Tecnológica Federal do Paraná, Via Rosalina Maria dos Santos, no 1.233, Caixa Postal 271, CEP 87301-899 Campo Mourão, PR.

Lattes: http://lattes.cnpq.br/4478946778069991

Núbia Oliveira Silva, Universidade Tecnológica Federal do Paraná, Via Rosalina Maria dos Santos, no 1.233, Caixa Postal 271, CEP 87301-899 Campo Mourão, PR.

Lattes: http://lattes.cnpq.br/0761226642391144

Patrícia Valderrama, Universidade Tecnológica Federal do Paraná, Via Rosalina Maria dos Santos, no 1.233, Caixa Postal 271, CEP 87301-899 Campo Mourão, PR

 Lattes: http://lattes.cnpq.br/7543235815267877

Paulo Henrique Março, Universidade Tecnológica Federal do Paraná, Via Rosalina Maria dos Santos, no 1.233, Caixa Postal 271, CEP 87301-899 Campo Mourão, PR.

 lattes: http://lattes.cnpq.br/6686357500300571

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Published

2018-02-16

How to Cite

dos Santos, L. R., Zangirolami, M. de S., Silva, N. O., Valderrama, P., & Março, P. H. (2018). Rapid non-invasive assessment of quality parameters in ground soybean using near-infrared spectroscopy. Pesquisa Agropecuaria Brasileira, 53(1), 97–104. https://doi.org/10.1590/S1678-3921.pab2018.v53.25076

Issue

v.53, n.1, jan. 2018

Section

SEED TECHNOLOGY