Abstract

Rice rich in gamma-aminobutyric acid (GABA) has been increasing in popularity worldwide, particularly within the commercially important health food market. The aim of this research was to develop a near infrared (NIR) spectroscopic method to evaluate the GABA content of germinated brown rice. Germinated brown rice (GBR) from two groups was used in this study. The first group contained GABA adjusted rice samples produced from germinated rough rice, which had been soaked for 24h and 48h and then incubated for 0h, 6h, 12h, 18h, 24h, 30h and 36h (GBR samples). The second group was the GBR purchased from local markets (MGBR samples). The GABA content of each sample was subsequently determined by high performance liquid chromatography (HPLC). A prediction model for the GABA content was subsequently established using the NIR spectral data in conjunction with partial least square regression (PLSR), which was validated using test set validation. There were three optimal models obtained from GBR samples, MGBR-Khao Dawk Mali 105 samples and MGBR-various varieties. The first model was established using spectral data pre-treated with first derivative + multiple scatter correction and the second and third models were from first derivative + vector normalisation pre-treated spectra. The coefficient of determination (r²), root mean squared error of prediction (RMSEP) and a bias of 0.97–0.98 mg, 0.21–0.52 mg per 100g dry matter and −0.285–0.067 mg per 100g dry matter, respectively, were obtained. This is the first report on the application of NIR spectroscopy to evaluate the GABA content of the germinated brown rice, which could prove useful in an industrial applications and consumers.

© 2014 IM Publications LLP

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