用响应面法对挤压高粱豇豆早餐麦片系统参数进行建模

D.I. Gbenyi , I. Nkama , M.H. Badau , T.A. Shittu
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引用次数: 6

摘要

将高粱粉和豇豆粉(10%,20%和30%)分别在20%,22.5%和25%的水分和120°C, 140°C和160°C的桶温下,使用单螺杆挤出机挤出。采用中心复合面心(CCF)设计对高粱-豇豆挤出物的比功耗(SPC)、扭矩、质量流量(MFR)和表观比容(ASV)进行了建模。SPC、扭矩、MFR和ASV的变化范围分别为201.71 ~ 229.28 Kw h−1 kg−1、85 ~ 97 Nm、1.94 ~ 2.31 g s−1和4.01 ~ 6.36 cm3。饲料成分的线性效应以及饲料水分和挤压温度的交互作用显著(p<0.05)影响了SPC。而料液水分的线性效应和料液水分与挤压温度的交互效应(p<0.01)显著影响了挤压力矩。挤压温度的线性效应、挤压温度的二次效应以及饲料成分和饲料水分的交互作用显著影响ASV (p≤0.01)。SPC、扭矩、MFR和ASV的决定系数分别为0.78、0.79、0.63和0.86。挤出物的SPC、扭矩和MFR没有明显的不足。SPC、扭矩、MFR和ASV的观测值和预测值的相关系数r2分别为0.88、0.75、0.78和0.93,表明模型拟合良好。发现CCF可用于预测挤出物的SPC、扭矩、MFR和ASV。
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Modelling of system parameters of extruded sorghum–cowpea breakfast cereal using response surface methodology

Blends of sorghum and cowpea flour (10%, 20% and 30%) were extruded at 20%, 22.5% and 25% moisture and 120 °C, 140 °C and 160 °C barrel temperatures respectively, using a single-screw extruder. A central composite face-centered (CCF) design was used to model the specific power consumption (SPC), torque, mass flow rate (MFR) and apparent specific volume (ASV) of the sorghum–cowpea extrudates. The SPC, torque, MFR and ASV varied from 201.71 to 229.28 Kw h−1 kg−1, 85 to 97 Nm, 1.94 to 2.31 g s−1 and 4.01 to 6.36 cm3, respectively. The SPC was significantly (p<0.05) influenced by the linear effect of feed composition and the interaction effects of feed moisture and extrusion temperature. The torque was however significantly (p<0.05) influenced by the linear effect of feed moisture and the interaction effects (p<0.01) of feed moisture and extrusion temperature. The ASV was significantly (p≤0.01) influenced by the linear effect of extrusion temperature and the quadratic effect of extrusion temperature as well as the interaction effects of feed composition and feed moisture. The coefficients of determination were 0.78, 0.79, 0.63 and 0.86 for SPC, torque, MFR and ASV, respectively. There was no significant lack of fit for the SPC, torque, and MFR of the extrudates. The correlation coefficients (r2) for the observed and predicted values were 0.88, 0.75, 0.78 and 0.93 for SPC, torque, MFR and ASV, respectively, indicating a good fit for the model. The CCF was found appropriate in predicting the SPC, torque, MFR and ASV of the extrudates.

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