Abstract
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.
Highlights
Soybean [Glycine max (L.) Merrill] plays an important role in the Brazilian and worldwide markets (Cavalcante et al, 2011) due to its versatility as human and animal food, as well as to its economic value (Hirakuri & Lazzarotto, 2014).Considering Brazil is among the largest soybean producers in the world, this legume is an important Brazilian commodity, responsible for more than 56% of the cultivated area
A portion of the ground soybean samples was exposed to analysis by near-infrared region (NIR) and other portion was set to be analyzed regarding its total lipid, crude protein and moisture content by methods recommended by the American Oil Chemists’ Society (AOCS, 2009), in the soybean processing industry itself, for further production of oil and bran
Spectra were measured from previously ground soybean samples with the MicroNIR 1,700 nearinfrared ultracompact equipment (Viavi Solutions Inc., Milpitas, CA, USA) at room temperature using diffusion reference, being each sample evaluated in duplicate
Summary
Soybean [Glycine max (L.) Merrill] plays an important role in the Brazilian and worldwide markets (Cavalcante et al, 2011) due to its versatility as human and animal food, as well as to its economic value (Hirakuri & Lazzarotto, 2014). Considering Brazil is among the largest soybean producers in the world, this legume is an important Brazilian commodity, responsible for more than 56% of the cultivated area. The total domestic consumption should reach 47.7 million tons, and approximately 59.9 million tons should be exported; China is one of the main importers of Brazilian soybean (Acompanhamento..., 2017). Soybean dominates vegetable protein and edible oil’s production in world market. The grain quality is an important parameter for producers and for industry, and in many countries soybean price is determined by its physicochemical characteristics (Huang et al, 2008)
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