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The neurotransmitter γ-aminobutyric acid (GABA) is a functional food ingredient of growing importance in the preparation of GABA-enriched germinated brown rice (GBR). Quantification of GABA levels during germination in a locally developed high yielding red rice variety (UKMRC-9) was carried out via high-performance liquid chromatography (HPLC) analysis using pre-column chemical derivatisation with 2-hydroxynaphthaldehyde (HN) using a UV detection system. Factors that influence rice germination such as soaking time and temperature were also studied. The results of this study showed that the UKMRC-9 rice variety soaked in water for 6 hours at 35 °C yielded the highest value for both germination percentage (95.4±1.2%) and GABA content (411 μg g-1). This suggests that long soaking times of 1-4 days can be substituted by short soaking times to produce high GABA levels in germinated brown rice.

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Acta Alimentaria
Authors:
J.J. Lin
,
Q.H. Meng
,
Z.F. Wu
,
S.Y. Pei
,
P. Tian
,
X. Huang
,
Z.Q. Qiu
,
H.J. Chang
,
C.Y. Ni
,
Y.Q. Huang
, and
Y. Li

Abstract

This paper explores the prediction of the soluble solid content (SSC) in the visible and near-infrared (400–1,000 nm) regions of Baise mango. Hyperspectral images of Baise mangoes with wavelengths of 400–1,000 nm were obtained using a hyperspectral imaging system. Multiple scatter correction (MSC) was chosen to remove the effect of noise on the accuracy of the partial least squares (PLS) regression model. On this basis, the characteristic wavelengths of mango SSC were selected using the competitive adaptive reweighted sampling (CARS), genetic algorithm (GA), uninformative variable elimination (UVE), and combined CARS + GA-SPA, CARS + UVE-SPA, and GA + UVE-SPA characteristic wavelength methods. The results show that the combined MSC-CARS + GA-SPA-PLS algorithm can reduce redundant information and improve the computational efficiency, so it is an effective method to predict the SSC of mangoes.

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