摘要
天然食用色素应用广泛,三原色色素依其浓度可调配各种不同色调,传统配色方法高度依赖配色经验,生产效率低,误差大,产品质量稳定性差。基于吸收光谱匹配法,利用天然食用色素在混合时特征吸收峰保持不变的特性,在色素质量浓度和特征吸收峰的吸光度之间建立了多元线性和神经网络配色模型,通过误差对比分析,选择较优模型并进行试验验证。结果表明:神经网络模型的预测精度、稳定性均优于多元线性回归模型,其预测配方和原配方的色差在3以内,肉眼无法区分两者的差别,神经网络模型能更好地满足染色配色的要求。希望研究结果为天然食用色素的智能配色工艺提供理论依据。
Natural food pigments are widely used,and trichromatic pigments can be mixed with different colors according to their concentrations.Traditional color matching methods are highly dependent on experience of color matching,which result in low production efficiency,big variation and poor product quality stability.In this study,according to the characteristic absorption peak of natural food pigments had no change during mixing,and based on the matching method of absorption spectrum,color matching models of multiple linear and neural network were established between the concentration of pigments and the absorption value of the characteristic absorption peak.And the optimal model was selected and tested by errors analysis.The results showed that the prediction accuracy and stability of neural network model were better than those in multivariate linear model,and the color differences between the prediction formula and the original formula were within 3,which could not be distinguished by naked eyes.Thus the neural network models were more suitable for color matching requirements.These results provided theoretical basis for the intelligent color matching of natural food pigments.
作者
刘亚
雷声
朱大洲
高莉
刘国荣
王成涛
刘娟
郭青
LIU Ya;LEI Sheng;ZHU Dazhou;GAO Li;LIU Guorong;WANG Chengtao;LIU Juan;GUO Qing(Technical Center of China Tobacco Yunnan Industrial Co Ltd,Kunming 650202,China;Beijing Engineering and Technology Research Center of Food Additives,Beijing Technology and Business University,Beijing 100048,China;Institute of Food and Nutrition Development,Ministry of Agriculture and Rural Affairs,Beijing 100081,China)
出处
《食品科学技术学报》
CAS
CSCD
北大核心
2020年第6期76-83,共8页
Journal of Food Science and Technology
基金
云南中烟工业有限责任公司科技项目(2018CP03)
云南省科技厅青年项目(2018FD164)。
关键词
天然食用色素
多元线性回归模型
神经网络模型
三原色色素
复配配色
natural food pigment
multivariate linear model
neural network model
trichromatic pigment
complex color matching
