基于遗传算法BP神经网络的猫粮糊化特性研究  

A study on the gelatinization characteristics of cat food based on neural networks optimized by genetic algorithm

作　　者：张琦[1] 许耀辉 陈阳 韩栋梁 张润哲 严骅彬 Lela Susilawati 魏文广 奚小波[1] ZHANG Qi;XU Yaohui;CHEN Yang;HAN Dongliang;ZHANG Runzhe;YAN Huabin;Lela Susilawati;WEI Wenguang;XI Xiaobo(College of Mechanical Engineering,Yangzhou University,Yangzhou,Jiangsu Province 225127,China;Jiangsu Famsun Intelligent Technology Co.Ltd.,Yangzhou,Jiangsu Province 225120,China;Faculty of Science and Technology,UIN Sunan Kalijaga Yogyakarta(State Islamic University of Yogyakarta),Indonesia)

机构地区：[1]扬州大学机械工程学院,江苏扬州225127 [2]江苏丰尚智能科技有限公司,江苏扬州225120 [3]科学和技术学院,印尼日惹国立伊斯兰大学,印度尼西亚

出　　处：《中国饲料》2025年第9期87-92,共6页China Feed

基　　金：江苏省科技合作项目(BZ2024049);扬州市科技合作项目(SGH2024010007)。

摘　　要：为了解猫粮的糊化特性,本试验采用快速黏度分析仪(RVA)对不同RVA转子转速(160、200、240、280、320、360、400、440、480 r/min),不同保持温度(75、80、85、90、95℃),不同质量猫粮和蒸馏水比值(1/21、2/21、3/21、4/21、5/21、6/21、7/21)进行研究。结果表明:随着转子转速的增加,峰值黏度、谷值黏度、终值黏度显著降低,衰减值变小,热糊稳定性增强。随着保持温度的增加,峰值黏度增加,谷值黏度和终值黏度先上升后下降,淀粉糊稳定性变差,原料更容易糊化。随着猫粮质量的增加,糊化温度降低,峰值黏度、谷值黏度、终值黏度增大,淀粉糊稳定性降低,凝胶性增强。另外,以本试验数据为基础,提出一种基于遗传算法的神经网络预测峰值黏度的模型。To understand the gelatinization characteristics of cat food,this experiments studied different rotor speeds(160,200,240,280,320,360,400,440,480 r/min),different holding temperatures(75,80,85,90,95℃),and different ratios of cat food to distilled water(1/21,2/21,3/21,4/21,5/21,6/21,7/21)using a Rapid Visco Analyzer(RVA).The results showed that with the increase of rotor speed,peak viscosity,trough viscosity,and final viscosity significantly decreased,while the breakdown value decreased and the thermal paste stability increased.With the increase of holding temperature,peak viscosity increased,trough viscosity and final viscosity first increased and then decreased,starch paste stability deteriorated,and the raw material became more prone to gelatinization.With the increase of cat food weight,gelatinization temperature decreased,peak viscosity,trough viscosity,and final viscosity increased,starch paste stability decreased,and gel strength increased.Based on the experimental data,a genetic algorithm-based neural network model was proposed to predict peak viscosity.

关 键 词：转速 温度 淀粉 糊化特性 神经网络 遗传算法 快速黏度分析仪(RVA) 

分 类 号：S816[农业科学—饲料科学]