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Validation of Parboiling Rice Quality Simulation Mathematical Model

机译:煮大米品质模拟数学模型的验证

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Parboiling (hydrothermal treatment) of paddy/rough rice is an ancient traditional process of South Asian countries and it’s reducing the level of grain breakage and increase in head yield of rice during milling. However, parboiling of rice associated minor drawbacks such as reduce rice kernel whiteness and increase in kernel hardness. Level of grain breakage, kernel whiteness and hardness can be altered by parboiling treatments such as water temperature and duration of soaking. The mathematical model developed by Gunathilake can be used to predict the rice quality values such as kernel whiteness, harness and broken grains however, model should be validated (verified) before applied. Hence, this research study was carried out to validate the mathematical model for checking its suitability and accuracy to predict above mentioned rice quality values in local rice variety. BG 358 short grain rice was used for validation/verification the model. In this model single paddy grain parboiling (hydration) was considered. Results were shown that mathematical model is fit for predict rice quality values of kernel whiteness, hardness, broken grain percentage and head rice yield percentage, by the function of water temperature and duration of soaking are the major treatments of paddy parboiling. Goodness of fit (E) value of actual values and predicted values of kernel whiteness, hardness broken grain percentage and head rice yield were showed 5.91, 6.73, 8.32 and 7.92 respectively. The average Goodness of fit (E) value was 7.22. Hence, it was revealed, that the mathematical model was capable to predict rice quality values by water temperature and soaking duration similar to actual values of rice qualities. Hence, it can be concluded that mathematical model was good fit to simulate above rice qualities by the paddy parboiling treatments of water temperature and soaking duration for BG 358 paddy.
机译:稻米/糙米的煮煮(水热处理)是南亚国家的古老传统工艺,可减少碾磨过程中谷物的破损程度并提高稻米的单产。但是,煮饭会带来一些小缺点,例如降低米粒的白度和增加米粒的硬度。破损程度,籽粒白度和硬度可以通过煮沸处理(例如水温和浸泡时间)来改变。 Gunathilake开发的数学模型可用于预测稻米质量值,例如籽粒白度,线束和破碎的谷物,但是在应用之前应进行验证(验证)。因此,本研究旨在验证数学模型,以检验其适用性和准确性,以预测当地水稻品种中上述稻米质量值。 BG 358短粒大米用于模型的验证/验证。在该模型中,考虑了单个稻谷煮沸(水合作用)。结果表明,通过水温和浸水持续时间的函数分析,该数学模型适用于预测稻米品质,籽粒白度,硬度,破碎谷粒率和糙米得率的质量值,是稻谷煮水的主要方法。实测值的拟合度(E)值和籽粒白度,硬度破碎谷粒百分比和糙米产量的预测值分别显示为5.91、6.73、8.32和7.92。拟合优度(E)的平均值为7.22。因此,揭示出该数学模型能够通过水温和浸泡时间来预测稻米质量值,类似于稻米质量的实际值。因此,可以得出结论,通过对BG 358稻谷进行水温和浸泡时间的稻谷煮沸处理,数学模型非常适合模拟上述稻米品质。

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