期刊论文

Prediction of sensory quality of fried battered and breaded fish nuggets using artificial neural network

中文

武汉轻工大学学报

2095-7386

2018

37

06

1-13+40

10.3969/j.issn.2095-7386.2018.06.001

国家自然科学基金面上项目(31471612)； 国家大宗淡水鱼产业技术体系建设专项(CARS-45)；

本校为第一机构

为实现对油炸外裹糊鱼块感官品质的预测,采用响应面试验设计收集试验数据,建立以黄原胶和大豆纤维复配比例、外裹糊鱼块干燥时间、大豆油品质、油炸温度、油炸时间为输入值,油炸外裹糊鱼块的色度(L*、a*、b*)和质构(硬度、脆度、弹性、咀嚼性)为输出值的人工神经网络模型(Artificial Neural Network,ANN),预测外裹糊鱼块深度油炸过程色度和质构的变化,并用训练集拟合,测试集评估模型的预测能力。结果显示:黄原胶和大豆纤维复配比例、外裹糊鱼块干燥时间、大豆油品质、油炸温度、油炸时间对油炸外裹糊鱼块的色度(L*、a*、b*)和质构(硬度、脆度、弹性、咀嚼性)均有显著影响。该ANN模型训练后相关系...

In this work,the prediction of sensory quality of fried battered and breaded fish nuggets(BBFNs)was performed through combined response surface methodology(RSM)and artificial neural network(ANN).An ANN model was established to predict the changes of color and textural characteristics of BBFNs during deep-fat frying via RSM for gathering the experimental data,for which the ratio of xanthan gum to soybean fiber,drying time of BBFNs,soybean oil quality,frying temperature,and time were considered as the input.Furthermore,the training set was utilized for model fitting and test set was used to eval...