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首页> 外文期刊>Journal of Food Measurement and Characterization >Optimization of process parameters for the production of taro chips using RSM with fuzzy modeling
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Optimization of process parameters for the production of taro chips using RSM with fuzzy modeling

机译:使用RSM具有模糊建模的RAOM芯片生产工艺参数的优化

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摘要

Response surface methodology (RSM) with fuzzy modeling was applied for taro chips production and to optimize the process conditions. Four independent variables, slice thickness, soaking time (ST), cooking time (CT), frying temperature (FT) were selected in range of 1–5 mm, 1–3 h, 10–30 min, 150–190 °C respectively. The optimum conditions for taro chips production were obtained as slice thickness, 2 mm ST, 2 h CT, 15 min and FT, 180 °C. Under the optimum conditions, taro chips had good color (AE= 28.15), medium hardness (280 g force), lower oil uptake (31.25 %) and OAA score of 8.59. Fuzzy modeling through Mamdani type fuzzy inference also used to acquire the best optimum conditions under the set of rules and designed input and output variables, and it rendered competitive results as obtained with RSM. The experimental results obtained under the optimum conditions were in good agreement with the predicted values obtained through the RSM and fuzzy modeling.
机译:应用模糊建模的响应表面方法(RSM)用于芋头芯片生产,并优化工艺条件。 四个独立变量,切片厚度,浸泡时间(ST),烹饪时间(CT),分别选择1-5毫米,1-3小时,10-30分钟,150-190°C。 。 芋头芯片生产的最佳条件是作为切片厚度,2mM ST,2 H CT,15分钟和Ft,180℃的切片产生的条件。 在最佳条件下,芋头芯片具有良好的颜色(AE = 28.15),中硬度(280g力),较低的耐油吸收(31.25%)和OAA得分为8.59。 通过Mamdani型模糊推理的模糊建模还用于在规则集和设计的输入和输出变量下获得最佳的最佳条件,并且呈现使用RSM获得的竞争结果。 在最佳条件下获得的实验结果与通过RSM和模糊建模获得的预测值吻合良好。

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