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Using a combined neural network ─ genetic algorithm approach for predicting the complex rheological characteristics of microfluidized sugarcane juice
LWT - Food Science and Technology ( IF 6.0 ) Pub Date : 2020-01-20 , DOI: 10.1016/j.lwt.2020.109058
Ayon Tarafdar , Barjinder Pal Kaur , Prabhat K. Nema , Onkar A. Babar , Deepak Kumar

The effect of multi-cycle multi-pressure microfluidization on the rheological properties of sugarcane juice has been reported for the first time in this work. Microfluidization pressure was varied in defined steps from 50 to 200 MPa with 1–7 cycles of processing. Rheological measurements were carried out at 30, 40 and 50 °C. Increase in microfluidization pressure up to 150 MPa showed an increase in consistency index. Beyond 150 MPa, an observed reduction in consistency index was attributed to the reduction in carbohydrate polymer chains, agglomeration and molecular degradation. At low processing pressures, microfluidized sugarcane juice exhibited pseudoplastic behavior but showed a dilatant tendency at higher pressures (>150 MPa). Microfluidization increased the flow behavior index by 24–38% as compared to unprocessed sugarcane juice. No prominent trend in rheological data was observed with change in microfluidization cycles. Consistency index was reduced with increase in temperature and was found in the range of 1.5 × 10−3 ─ 5.3 × 10−3 Pa.sn whereas the flow behavior index was found in the range of 0.71 ─ 0.99. A GA mediated ANN model with 12 hidden layer neurons was found to predict the rheological properties of microfluidized sugarcane juice with a reasonable level of accuracy (R2 = 0.86–0.93).



中文翻译:

使用组合神经网络─遗传算法方法预测微流化甘蔗汁的复杂流变特性

在这项工作中首次报道了多循环多压力微流化对甘蔗汁流变性质的影响。微流化压力在1到7个处理循环中从50 MPa逐步变化到200 MPa。在30、40和50℃下进行流变学测量。微流化压力增加到150 MPa时,稠度指数增加。超过150 MPa,观察到的稠度指数降低归因于碳水化合物聚合物链的减少,团聚和分子降解。在低加工压力下,微流化甘蔗汁表现出假塑性行为,但在较高压力(> 150 MPa)下表现出膨胀趋势。与未加工的甘蔗汁相比,微流化将流动行为指数提高了24–38%。随着微流化周期的变化,未观察到流变学数据的显着趋势。一致性指数随温度的升高而降低,在1.5×10的范围内-3 ─5.3×10 -3 帕斯卡·秒Ñ而流动行为指数在0.71─0.99的范围内找到。发现具有12个隐层神经元的GA介导的ANN模型可以合理程度地预测微流化甘蔗汁的流变特性(R 2  = 0.86-0.93)。

更新日期:2020-01-21
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