Avaliação rápida não invasiva de parâmetros de qualidade em soja triturada com uso de espectroscopia de infravermelho próximo

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.

• Publication year

  2018

• Venue

  Pesquisa Agropecuaria Brasileira

• Publication date

  2018-02-16

• Fields of study

  Agricultural and Food Sciences, Biology

• Identifiers
  DOI 10.1590/S0100-204X2018000100011
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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