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Protein and Apparent Amylose Contents of Milled Rice by NIR-FT/Raman Spectroscopy

¹USDA, ARS, R. B. Russell Agricultural Research Center, Athens, GA 30604-5677. Names are necessary to report factually on available data; however, the USDA neither guarantees nor warrants the standard of the product, and the use of the name by the USDA implies no approval of the product to the exclusion of others that may also be suitable. ²Corresponding author. E-mail: dshimmel@qaru.ars.usda.gov ³USDA, ARS, Rice Research Laboratory, Beaumont, TX 77713. ⁴USDA, ARS, Southern Regional Research Center, New Orleans, LA 70179-0687.

The chemometric calibration of near-infrared Fourier-transform Raman (NIR-FT/Raman) spectroscopy was investigated for the purpose of providing a rigorous spectroscopic technique to analyze rice flour for protein and apparent amylose content. Ninety rice samples from a 1996 collection of short, medium, and long grain rice grown in four states of the United States, as well as Taiwan, Korea, and Australia were investigated. Milled rice flour samples were scanned in rotating cups with a 1,064 nm (NIR) excitation laser using 500 mW of power. Raman scatter was collected using a liquid N₂ cooled Ge detector over the Raman shift range of 175–3,600 cm^-1. The spectral data was preprocessed using baseline correction with and without derivatives or with derivatives alone and normalization. Nearly equivalent results were obtained using all of the preprocessing methods with partial least squares (PLS) models. However, models using baseline correction and normalization of the entire spectrum, without derivatives, showed slightly better performance based on the criteria of highest r² and the lowest SEP with low bias. Calibration samples (n = 57) and validation samples (n = 33) were chosen to have similar respective distributions for protein and apparent amylose. The best model for protein was obtained using six factors giving r² = 0.992, SEP = 0.138%, and bias = -0.009%. The best model for apparent amylose was obtained using eight factors giving r² = 0.985, SEP = 1.05%, and bias = -0.006%.