發(fā)布時間：2018-04-16 14:29

  本文選題：金膠顆粒 + 表面增強(qiáng)拉曼光譜　； 參考：《光譜學(xué)與光譜分析》2017年12期

【摘要】：采用金膠顆粒作為活性基底,氯化鈉溶液作為活性劑,并采用表面增強(qiáng)拉曼光譜(SERS)技術(shù)建立一種檢測鴨肉中萘夫西林殘留的檢測方法。首先分析了奈夫西林水溶液的SERS特征峰及其歸屬。然后分析了奈夫西林在鴨肉提取液中的SERS特征峰,確定了鑒定鴨肉中奈夫西林殘留的拉曼特征峰,并選取521與1 449cm~(-1)處的拉曼峰強(qiáng)度進(jìn)行條件的優(yōu)化。最后應(yīng)用內(nèi)標(biāo)法對鴨肉提取液中萘夫西林的殘留量進(jìn)行定量分析。結(jié)果表明,鴨肉提取液中萘夫西林的質(zhì)量濃度范圍在0.2~10mg·L~(-1)時,應(yīng)用拉曼峰強(qiáng)度比值所建立的四種標(biāo)定曲線均具有良好的線性關(guān)系,決定系數(shù)均大于0.95。其中三種標(biāo)定曲線具有較高的準(zhǔn)確度,其回收率介于88%~144%。由此可見,應(yīng)用SERS檢測鴨肉中萘夫西林的殘留是可行的,該方法簡便、快速,為檢測禽肉類食品中萘夫西林的殘留提供了技術(shù)支持。
[Abstract]:A method for the determination of naphthicillin residues in duck meat was established by using gold colloidal particles as active substrate, sodium chloride solution as active agent and surface enhanced Raman spectroscopy (SERS) technique.Firstly, the SERS characteristic peaks and their ascription of Nefloxicillin aqueous solution were analyzed.Then, the characteristic peaks of SERS in duck meat extract were analyzed, the Raman characteristic peaks of Nefloxicillin residues in duck meat were determined, and the intensity of Raman peaks at 521 and 1449 cm ~ (-1) were selected to optimize the conditions.Finally, the residual naphthoxicillin in duck meat extract was determined by internal standard method.The results showed that the four calibration curves established by Raman peak intensity ratio had a good linear relationship when the concentration of naphthoxicillin in duck extract was in the range of 0.2~10mg Ln (-1), and the determining coefficients were all greater than 0.95.Among them, three calibration curves have high accuracy, and the recovery rate is between 88 and 144.Therefore, it is feasible to use SERS to detect naphthicillin residues in duck meat. This method is simple and rapid, which provides technical support for the detection of naphthicillin residues in poultry meat food.
【作者單位】： 江西農(nóng)業(yè)大學(xué)工學(xué)院生物光電及應(yīng)用重點(diǎn)實(shí)驗(yàn)室;
【基金】：國家自然科學(xué)基金項(xiàng)目(31660485) 江西省科技廳對外科技合作計(jì)劃項(xiàng)目(20132BDH80005);江西省科技廳科技支撐項(xiàng)目(2012BBG70058)資助
【分類號】：O657.37;TS251.7
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本文編號：1759330