期刊论文

Prediction of moisture and fat contents of fried battered and breaded fish nuggets based on artificial neural network

中文

武汉轻工大学学报

2095-7386

2018

37

03

1-11

10.3969/j.issn.2095-7386.2018.03.001

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-46)；

本校为第一机构

为实现对油炸外裹糊鱼块的水分和油脂含量的预测,采用响应面试验设计收集数据,建立以油炸外裹糊鱼块工艺参数(黄原胶-大豆纤维复配比例、外裹糊鱼块干燥时间、不同品质的大豆油、油炸温度、油炸时间)为输入值,外壳水分和油脂含量为输出值的人工神经网络模型,并用训练集拟合,测试集评估模型的泛化能力。结果显示:外壳水分和油脂含量显著负相关,黄原胶-大豆纤维复配比例、外裹糊鱼块干燥时间、不同品质的大豆油、油炸温度对外壳水分和油脂含量均有显著影响;油炸时间显著影响外壳的水分含量,但是对油脂含量的影响不显著。模型拟合良好,有很强的逼近能力;水分和油脂含量测试集的R值分别为0.911和0.9...

In this study, the prediction of moisture and fat contents of fried battered and breaded fish nuggets ( BBFNs) was performed through combined response surface methodology (RSM) and artificial neural network (ANN). RSM was utilized to collect the experimental data to establish the ANN, which the process parameters of fried BBFNs (ratio of xanthan gum to soybean fiber, drying time of BBFNs, soybean oils with different quality, frying temperature and time) and moisture and fat contents in the crust were used as the input and output, respec-tively. The training set was used for model fitting and t...