51 research outputs found

    Determination of undried rough rice constituent content using near-infrared transmission spectroscopy

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    Near-infrared transmission (NIRT) spectroscopy was used in an attempt to predict moisture content, protein content and amylose content from undried whole-grain rough rice spectra. One hundred-fifty undried rough rice samples were collected. Using partial least squares calibration models obtained from undried whole-grain rough rice spectra, the coefficient of determination (r 2) and the standard error of prediction (SEP) of the validation set were r 2 = 0.96 and SEP = 0.70 for rough rice moisture content, r 2 = 0.70 and SEP = 0.24 for brown rice protein content, r 2 = 0.76 and SEP = 0.22 for milled rice protein content, and r 2 = 0.00 and SEP = 0.27 for milled rice amylose content. The results of the validation indicated that NIRT could be used to determine moisture content and protein content. Thus, NIRT technology may be used to classify undried rough rice into qualitative groups such as high protein content rice and low protein content rice upon arrival at a rice-drying facility after harvesting

    Visible and near-infrared reflectance spectroscopy for rice taste evaluation

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    Visible and near-infrared (VIS/NIR) spectroscopy calibration models for rice taste evaluation were developed using 61 short-grain rice samples. The best performance calibration model was obtained from original spectra of whole grain milled rice using multiple linear regression (MLR) analysis. The correlation coefficient (r) and the standard error of prediction (SEP) of the validation set was 0.62 and 0.27, respectively. However, this was not adequate to justify replacing sensory tests with the calibration model for evaluating rice taste. The results indicated that VIS/NIR technology could be used for classifying rice samples into qualitative groups, such as poor taste, better taste and the best taste

    Extensive Eruptive Syringoma After Liver Transplantation

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