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作 者:Xin-ming Nie Jing Wang Xun Wang Ya-ping Tian Si Chen Zhou-yang Long Cheng-hua Zong 聂新明;王静;王勋;田亚平;陈斯;龙洲洋;宗成华(江苏师范大学物理与电子工程学院,徐州221116;江苏师范大学化学与材料科学学院,徐州221116;江苏师范大学科文学院,徐州221116)
机构地区:[1]School of Physics and Electronic Engineering, Jiangsu Normal University, Xuzhou 221116, China [2]School of Chemistry and Materials Science, Jiangsu Key Laboratory of Green Synthesis for Functional Materials, Jiangsu Normal University, Xuzhou 221116, China [3]Kewen College, Jiangsu normal university, Xuzhou 221116, China
出 处:《Chinese Journal of Chemical Physics》2019年第4期444-450,I0002,共8页化学物理学报(英文)
基 金:supported by the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province (No.16KJB510009 and No.17KJB510017);Jiangsu Province Natural Science Foundation of China (BK20150228)
摘 要:As an effective and universal acaricide, amitraz is widely used on beehives against varroasis caused by the mite Varroa jacobsoni. Its residues in honey pose a great danger to human health. In this study, a sensitive, rapid, and environmentally friendly surface-enhanced Raman spectroscopy method (SERS) was developed for the determination of trace amount of amitraz in honey with the use of silver nanorod (AgNR) array substrate. The AgNR array substrate fabricated by an oblique angle deposition technique exhibited an excellent SERS activity with an enhancement factor of -10^7. Density function theory was employed to assign the characteristic peak of amitraz. The detection of amitraz was further explored and amitraz in honey at concentrations as low as 0.08 mg/kg can be identified. Specifically, partial least square regression analysis was employed to correlate the SERS spectra in full-wavelength with Camitraz to afford a multiple-quantitative amitraz predicting model. Preliminary results show that the predicted concentrations of amitraz in honey samples are in good agreement with their real concentrations. Compared with the conventional univariate quantitative model based on single peak’s intensity, the proposed multiple-quantitative predicting model integrates all the characteristic peaks of amitraz, thus offering an improved detecting accuracy and anti-interference ability.
关 键 词:AMITRAZ surface-enhanced Raman spectroscopy method Oblique angle deposition HONEY DETECTION SENSING Ag nanorod Density function theory Partial least squares regression
分 类 号:S896.1[农业科学—特种经济动物饲养] O657.37[农业科学—畜牧兽医]
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