01928naa a2200301 a 450000100080000000500110000800800410001910000220006024501310008226000090021350001600022252008420038265000180122465000160124265000200125865300300127865300240130865300210133265300320135365300290138565300260141465300170144070000260145770000170148370000190150070000180151977300890153720892442019-02-25       2018    bl uuuu     u00u1 u    #d1 aSANTOS, L. R. dos  aRapid non-invasive assessment of quality parameters in ground soybean using near-infrared spectroscopy.h[electronic resource]  c2018  aTítulo em português: Avaliação rápida não invasiva de parâmetros de qualidade em soja triturada com uso de espectroscopia de infravermelho próximo.  aThe 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.  aCrude protein  aGlycine Max  aProteína bruta  aCalibração multivariada  aChemometric methods  aLipídios totais  aMínimos quadrados parciais  aMultivariate calibration  aPartial least squares  aTotal lipids1 aZANGIROLAMI, M. de S.1 aSILVA, N. O.1 aVALDERRAMA, P.1 aMARÇO, P. H.  tPesquisa Agropecuária Brasileira, Brasília, DFgv. 53, n. 1, p. 97-104, jan. 2018.