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Author: search.filters.author.Sirisomboon, PanmanasSubject: search.filters.subject.Rice

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    Sensory quality evaluation of rice using visible and shortwave near-infrared spectroscopy
    (2015-05-04)
    Lapchareonsuk, Ravipat
    ;
    Sirisomboon, Panmanas
    This research aimed to develop both visible and shortwave near-infrared spectroscopy to evaluate the sensory qualities of cooked rice. In this study, four different types of milled rice were used: parboiled, white, new Jasmine, and aged Jasmine. The sensory qualities of cooked rice (adhesiveness, hardness, stickiness, dryness, whiteness, and aroma) were evaluated by a trained sensory panel. The results demonstrated that these sensory attributes correlated with visible and shortwave near-infrared spectral data. Both visible and shortwave near-infrared spectroscopy models used for predicting the sensory qualities of cooked rice were established using partial least squares regression. All prediction results for sensory qualities showed a range of R<sup>2</sup><inf>val</inf> between 0.837 and 0.918, with the highest found for aroma (0.918). The proposed models can be utilized in quality control by the rice industry.
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    Eating quality of cooked rice determination using Fourier transform near infrared spectroscopy
    (2014-10-20)
    Lapcharoensuk, Ravipat
    ;
    Sirisomboon, Panmanas
    The goal of this research was to study the relationship between the eating quality of cooked rice and near infrared spectra measured by a Fourier Transform near infrared (FT-NIR) Spectrometer. Samples of milled: parboiled rice, white rice, new Jasmine rice (harvested in 2012) and aged Jasmine rice (harvested in 2006 or during the period 2007-2011) were used in this study. The eating quality of the cooked rice, i.e., adhesiveness, hardness, dryness, whiteness and aroma, were evaluated by trained sensory panelists. FT-NIR spectroscopy models for predicting the eating quality of cooked rice were established using the partial least squares regression. Among the eating quality, the stickiness model indicated its highest prediction ability (i.e., R <inf>val</inf><sup>2</sup> = 0:71; RMSEP = 0:65; Bias = 0:00; RPD = 1:87) and SEP/SD of 2. In addition, it was clear that the water content did not affect the eating quality of cooked rice, rather the main chemical component implicated was starch.
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    Classification of Hom Mali rice with different degrees of milling based on physicochemical measurements by principal component analysis
    (2011-09-01)
    Imsil, Areerat
    ;
    Rittiron, Ronnarit
    ;
    Sirisomboon, Panmanas
    ;
    Areekul, Varipat
    The effect of the degree of milling on the physicochemical properties of Hom Mali rice compared with low, intermediate and high amylose rice groups was investigated in order to differentiate Hom Mali rice from the other groups at different degrees of milling by principal component analysis (PCA). For all the rice groups, the apparent amylose content, alkali spreading value and pasting properties such as maximum viscosity, breakdown, final viscosity and setback viscosity increased with increases in the degree of milling except for the gel consistency which was reduced. Milled rice with a degree of milling of 15% showed the highest apparent amylose content, alkali spreading value and pasting properties compared with milled rice with degrees of milling of 10% and 5% and with brown rice. PCA could be applied to classify Thai rice varieties into four groups-Hom Mali, low, intermediate and high amylose rice groups-by two principal components (PCs). Rotated PC <inf>1</inf> and PC <inf>2</inf> using the Varimax method were better at explaining the variance of the parameters than the unrotated PCs. PCA clearly differentiated the classification of Rice Department 15 variety from the Pathum Thani 1 variety at the same degree of milling. Therefore, the stability of the degree of milling using PCA based on physicochemical measurements made it a preferable classification procedure for rice.