天津农学院学报 ›› 2018, Vol. 25 ›› Issue (3): 70-73.doi: 10.19640/j.cnki.jtau.2018.03.015

• 研究与简报 • 上一篇    下一篇

中红外光谱快速检测牛奶中土霉素的可行性研究

徐琛善, 吴楠通信作者, 海霞, 王军, 田佳, 刘香檬, 鲍振博, 彭锦星   

  1. 天津农学院 工程技术学院,天津 300384
  • 收稿日期:2018-06-19 出版日期:2018-09-20 发布日期:2019-11-12
  • 通讯作者: 吴楠(1984–),女,讲师,博士,主要从事环境污染物方面的研究。E-mail:nwu@tjau.edu.cn。
  • 作者简介:徐琛善(1996–),男,本科在读,主要从事环境与新能源方面的研究。E-mail:1209148248@qq.com。
  • 基金资助:
    国家自然科学基金项目(21607114,41771357); 大学生创新创业训练计划项目(201810061206)

Feasibility of rapid detection of oxytetracycline in milk by mid-infrared spectroscopy

XU Chen-shan, WU NanCorresponding Author, HAI Xia, WANG Jun, TIAN Jia, LIU Xiang-meng, BAO Zhen-bo, PENG Jin-xing   

  1. College of Engineering and Technology, Tianjin Agricultural University, Tianjin 300384, China
  • Received:2018-06-19 Online:2018-09-20 Published:2019-11-12

摘要: 将中红外光谱技术与偏最小二乘判别法相结合,建立一种牛奶中残留土霉素的快速检测方法。配置62个纯牛奶和62个掺杂有不同浓度土霉素(所掺土霉素浓度区间为0.02~30.00 mg/L)的牛奶样品,在400~4 000 cm-1区间进行中红外光谱采集。对原始光谱数据进行预处理之后,分别在全波段和分波段区间内建立偏最小二乘判别模型,并进行对比分析。结果显示,不同波数区间建模对掺杂土霉素牛奶的预判模型有较大影响。全波段和分波段区间所建模型对校正集样品的判别正确率均达 100%,预测集样品建模相关系数在0.995~0.997之间,表明所建模型的拟合效果良好,其中全波段和2 000~4 000 cm-1波段内所建模型对预测集样品的判别正确率均达90.0%。

关键词: 牛奶, 抗生素, 中红外光谱, 偏最小二乘判别分析

Abstract: The method for rapid detection of oxytetracycline residues in milk was established by combining mid-infrared (MIR) spectroscopy with partial least squares discriminant analysis(PLS-DA). Firstly, 62 pure milk samples and 62 milk samples adulterated with different concentrations of oxytetracycline(0.02-30.00 mg/L)were prepared respectively. The MIR spectra of all samples were collected in the range of 400-4 000 cm-1. After the pretreatment of original spectral data, the PLS-DA models were established in the full band and sub band ranges, respectively. The results show that different wave-number ranges had a great influence on the prediction model of milk adulterated with oxytetracycline. The classification accuracies of the constructed PLS-DA models were 100% for calibration set in the full band and sub band ranges, and the correlation coefficients of models were between 0.995 and 0.997 for prediction set, which shows that the models had a good fitting effect. The classification accuracies of constructed models in the full band and in the range of 2 000-4 000 cm-1 were 90.0% for prediction set.

Key words: milk, antibiotics, mid-infrared spectroscopy, partial least squares discriminant analysis

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