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出 处:《中国农业科技导报》2015年第5期33-39,共7页Journal of Agricultural Science and Technology
基 金:公益性行业(农业)科研专项(201003008)资助
摘 要:为了对面粉中的非法或过量添加剂进行无损、快速识别。以过氧化苯甲酰为检测对象,基于拉曼光谱技术采集面粉和过氧化苯甲酰的纯品拉曼光谱,筛选出识别过氧化苯甲酰的拉曼特征峰。为了进一步验证拉曼光谱检测面粉中混合过氧化苯甲酰的可行性,分别配置了10个不同质量比的混合物样品,采集混合物的拉曼光谱数据,并通过Savitzky-Golay(S-G)算法和8次多项式曲线拟合算法去除混合样品拉曼光谱中的噪声和荧光背景信号,保留原始数据的拉曼光谱信号。对过氧化苯甲酰纯品拉曼分析后,发现在619 cm-1、848 cm-1、890 cm-1、1 001 cm-1、1 234 cm-1、1 603 cm-1及1 777 cm-1处具有明显的拉曼峰,其中1 001 cm-1处的拉曼峰强度最高,因此选取1 001 cm-1处的拉曼峰作为识别过氧化苯甲酰的特征峰。经过平滑和基线校正后的10个混合样品的拉曼散射光谱中能够清晰地检测到1 001 cm-1位置处的拉曼峰。该结果表明基于拉曼光谱技术,能够有效、快速、非接触地识别掺杂在面粉中过氧化苯甲酰。In order to carry out the non-destructive,rapid identification of illegal or excessive additives in flour,this study took benzoyl peroxide as detecting object,adopting Raman scattering spectroscopy technology to acquire sterling Raman spectrum from flour and benzoyl peroxide,screened out Raman characteristic lines,which could identify benzoyl peroxide. In order to further verify the feasibility of mixing benzoyl peroxide with flour when detecting by Raman spectrum,10 samples with different ratioes of mixture were prepared to collect the Raman spectrum data. The Savitzky-Golay( S-G) algorithm and 8th order polynomial fitting algorithm were applied to smooth the noises and correct the background signal in Raman spectrum to retain Raman spectrum signal in initial data. After analyzing the pure benzoyl peroxide Raman spectrum,many obvious Raman peaks were found at 619 cm-1,848 cm-1,890 cm-1,1 001 cm-1,1 234 cm-1,1 603 cm-1,1 777 cm-1. Among them the intensity of Raman peak at 1 001 cm-1was the highest. Therefore,the of Raman peak was selected at 1 001 cm-1as characteristic peak for identifying benzoyl peroxide. Raman peak could clearly be detected at the location of 1 001 cm-1from the Raman scattered spectrum of the 10 mixed samples after smooth and baseline correction. These results indicated that Raman spectrum technology could identify benzoyl peroxide adulteration in wheat flour effectively,rapidly and without touching.
关 键 词:面粉 过氧化苯甲酰 拉曼系统 散射光谱 基线校正
分 类 号:TS207[轻工技术与工程—食品科学] S123[轻工技术与工程—食品科学与工程]
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