摘要
对羟基苯甲酸甲酯钠是一种使用广泛的防腐剂,食用过量将会危害身体健康,因此各国对对羟基苯甲酸甲酯钠的用量有严格规定。采用FS920荧光光谱仪分析了对羟基苯甲酸甲酯钠在水和橙汁溶液中的荧光光谱特性,发现水溶液的荧光特征峰位于λex/λem=380/510nm,橙汁溶液两个荧光特征峰,分别位于λex/λem=440/530nm和470/530nm,最佳激发波长为440nm。从实验结果可以看出两者的特征峰发生了明显的变化。经分析得出,对羟基苯甲酸甲酯钠橙汁溶液与对羟基苯甲酸甲酯钠水溶液相比,荧光特征峰发生变化是由橙汁的荧光特性干扰引起的。为了准确测定鲜橙汁中对羟基苯甲酸甲酯钠含量,根据对羟基苯甲酸甲酯钠橙汁溶液在激发波长λex=440nm时的相对荧光强度和对羟基苯甲酸甲酯钠含量的关系,基于GABP神经网络构建了橙汁中对羟基苯甲酸甲酯钠含量检测数学模型,当网络训练过程中误差精度达到10-3时,网络输出与期望的相关系数为0.996,预测样本的平均回收率为99.52%,平均相对标准偏差为0.86%,预测结果较为理想。结果证明,当浓度范围为0.02-1.0g·L-1时,荧光光谱技术和GA-BP神经网络相结合的方法能够准确地测定鲜橙汁中对羟基苯甲酸甲酯钠的含量,此方法具有新颖简便性,同时有望应用于一般饮品中对羟基苯甲酸酯类钠盐含量的快速测定。
Sodium methylparaben as one kind of preservatives is widely used in our life,but it will do harm to health if it is eaten too much.So there are strict rules on the dosage of sodium methylparaben in every country.The fluorescence spectral properties of sodium methylparaben in aqueous solution and orange juice solution are analyzed with FS920 fluorescence spectrometer.The research result shows that the fluorescence characteristic peak of sodium methylparaben solution is inλex/λem =380/510 nm,while sodium methylparaben orange juice solution has two fluorescence characteristic peaks which are inλex/λem =440/520 nm and 470/530 nm,and its best excitation wavelength is 440 nm.So it can be concluded from the result that there is a significant change between the characteristic peaks of sodium methylparaben in the two solution.Compared with the fluorescence characteristic peak of sodium methylparaben solution,thoses of sodium methylparaben orange juice solution are changed significantly,which are caused by the interference of orange juice fluorescence characteristics.In order to determine the content of sodium methylparaben in the fresh orange juice,a detection model of sodium methylparaben content in orange juice is built based on GABP neural network,according to the relationship between fluorescence intensity inλex=440nm and the content of sodium methylparaben orange juice solution.When the accuracy of the mean square error in the process of network training reaches 10-3,the correlation coefficient of network output and that of the expected is 0.996.At the same time,a better prediction result can be obtained that the average recovery of the forecast samples is 98.67%and the average relative standard deviation is 0.86%.When the concentration ranges from 0.02 to 1.0g·L-1,the results testify that detection method based on fluorescence spectroscopy and GA-BP neural network can accurately determine the content of sodium methylparaben in orange juice.This method has the features of novelty and simplicity and it is expected to be applied to the determination of sodium methylparaben in other kinds of drink.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2015年第6期1606-1610,共5页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金项目(61201110)
河北省自然科学基金项目(F2012203189)资助
