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Author: search.filters.author.Kaewsorn, KannapotSubject: search.filters.subject.Germinated brown rice

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    Non-linear viscoelastic behavior of cooked white, brown, and germinated brown Thai jasmine rice by large deformation relaxation test
    (2017-07-03)
    Sirisomboon, Panmanas
    ;
    Kaewsorn, Kannapot
    ;
    Thanimkarn, Satthawat
    ;
    Phetpan, Kittisak
    Stress relaxation tests at high strain were conducted on scoops of cooked white, brown, and germinated brown Thai jasmine rice using a King Mongkut’s Institute of Technology Ladkrabang test rig. The diameter of the scoop was 35 mm and the height was 10 mm. Non-linear modeling, consisting of four relaxation models, was applied to the data obtained for each type of rice. The modeling methods included Peleg and Normand’s; Yadav, Roopa, and Bhattacharya’s; Jaya and Durance’s; and Myhan, Markowski, and Daszkiewicz’s. The cooked white rice showed greater tenderness compared to the others. The toughness of the three types of cooked rice was not found to be different. The Myhan et al. model was the most accurate in describing the non-linear viscoelastic behavior of all types of cooked rice. The cooked brown rice showed the highest initial decay rate, but the lowest relaxation, lowest elasticity, and greatest viscosity. In contrast, the cooked white rice had opposite characteristics.
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    Study on evaluation of gamma oryzanol of germinated brown rice by near infrared spectroscopy
    (2014-01-01)
    Kaewsorn, Kannapot
    ;
    Sirisomboon, Panmanas
    Germinated brown rice (GBR) is rich in gamma oryzanol which increase its consumption popularity, particularly in the health food market. The objective of this research was to apply the near infrared spectroscopy (NIRS) for evaluation of gamma oryzanol of the germinated brown rice. The germinated brown rice samples were prepared from germinated rough rice (soaked for 24 and 48 h, incubated for 0, 6, 12, 18, 24, 30 and 36 h) and purchased from local supermarkets. The germinated brown rice samples were subjected to NIR scanning before the evaluation of gamma oryzanol by using partial extraction methodology. The prediction model was established by partial least square regression (PLSR) and validated by full cross validation method. The NIRS model established from various varieties of germinated brown rice bought from different markets by first derivatives+vector normalization pretreated spectra showed the optimal prediction with the correlation of determination (R<sup>2</sup>), root mean squared error of cross validation (RMSECV) and bias of 0.934, 8.84 × 10<sup>-5</sup> mg/100 g dry matter and 1.06 × 10<sup>-5</sup> mg/100 g dry matter, respectively. This is the first report on the application of NIRS in the evaluation of gamma oryzanol of the germinated brown rice. This information is very useful to the germinated brown rice production factory and consumers. © 2014 The Authors.