基于荧光光谱和径向基函数神经网络的合成食品色素测定和鉴别

以合成食品色素胭脂红、苋菜红溶液为例，提出了应用荧光光谱结合径向基函数神经网络对合成食品色素溶液进行浓度测定和种类鉴别的方法。应用SP-2558多功能光谱测量系统，测得胭脂红和苋菜红溶液分别在波长为300和400 nm的光激发下产生的荧光光谱。对每个胭脂红溶液样本选取15个发射波长值所对应的荧光强度作为网络特征参数，训练、建立用于浓度预测的径向基函数神经网络。据此，对3种胭脂红溶液样本的浓度进行预测，预测结果相对误差分别为1.42%，1.44%和3.93%。另外，以胭脂红和苋菜红溶液荧光波长值所对应的荧光强度作为特征参数，训练、建立了用于种类鉴别的径向基函数神经网络，进行合成食品色素溶液种类识别，准确率达100%。这些结果表明，该方法方便、快捷、准确度较高，可应用于合成食品色素检测及食品安全监管。

Determination and Identification of Synthetic Food Colors Based on Fluorescence Spectroscopy and Radial Basis Function Neural Networks

Taking ponceau 4R and amaranth as an example,concentration prediction and kind identification of synthetic food colors by fluorescence spectroscopy and radial basis function neural networks are introduced.By using SP-2558 multifunctional spectral measuring system,the fluorescence spectra were measured for solution of ponceau 4R and amaranth excited respectively by the light with the wavelength of 300 and 400 nm.For each sample solution of ponceau 4R,15 emission wavelength values were selected.The fluorescen...