电子鼻对羊奶中三种抗生素残留的快速检测

Rapid detection of three kinds of antibiotic residues in goat milk by electronic nose

中文关键词:  丙烯腈-丁二烯-苯乙烯  丙烯腈-苯乙烯  食品接触材料  法规

英文关键词:electronic nose  goat milk  antibiotic  rapid detection

中文摘要:

      目的 实现羊奶中常用抗生素残留的快速检测。方法 以电子鼻作为快速无损的检测仪器, 将含有不同浓度的青霉素G、硫酸庆大霉素、硫酸链霉素的羊奶作为研究对象, 利用线性判别分析(Linear Discriminant Analysis, LDA)和多层感知器神经网络(Multilayer Perceptron Neural Network, MLPN)等方法进行数据处理。结果 LDA的判别结果总体上能够将不同浓度的抗生素区分开来, 效果良好; MLPN的训练集和预测集的正确率也都在94.9%以上, 取得了很好的预测效果。结论 LDA 判定分组和MLPN预测模型可以用于羊奶中不同浓度青霉素G、硫酸庆大霉素、硫酸链霉素的快速检测。

英文摘要:

      Objective To develop a rapid detection method of usual antibiotics resedues in goat milk by electronic nose. Methods The goat milk with four concentrations (0, 50, 100, and 200 μg/L) antibiotics, including penicillin, gentamycin and streptomycin was detected by electronic nose as a rapid non-destructive de-tecting equipment, to collect the volatiles emitted from the goat milk.. Then the linear discriminant analysis (LDA) was applied to analyze the results and the response signals were chosen for the pattern recognitions by multilayer perceptron neural network (MLPN). Results LDA results showed that the response signals of the goat milk could distinguish the concentrations of antibiotics. The correct rates of the training group and the testing group of MLPNs were both more than 94.9%. Conclusion MLPN can be used as an effective forecasting tool for predicting the concentration of three kinds of antibiotic in goat milk using the signals of electronic nose.