摘要
为了实现快速便捷鉴别混合肉的目的,尝试以动物线粒体COI基因为识别元件,以一次性丝网印刷生物传感器为器件,搭建鉴别猪肉和牛肉混合二元物的传感平台,并评价检测的灵敏度、选择性和商业应用前景。结果显示,生牛肉和生猪肉靶标序列在10-13~10-5mol/L范围内与还原峰电流线性关系良好,牛肉鉴别的线性相关系数为0.96136,猪肉鉴别的线性相关系数为0.9874,检测限分别为5.048×10-14和3.491×10-14mol/L;另设计模拟生猪肉/牛肉混合二元物掺假实验,当混合生肉量为50 ng时,活性染料亚甲基蓝的电信号值更加稳定,对混合二元物的识别能力几乎不受掺假比例影响。结果表明,电化学传感技术的检测范围更广、可免去复杂的分子扩增中间实验、成本更低、操作技术更加简便化,故更加适合低比例掺假、现场快速检测要求。
In order to identify mixed meat quickly and conveniently,this research attempted to build a sensor platform to identify binary blends of pork and beef,and to evaluate its specificity,sensitivity and commercial applications by using animal mitochondrial COI gene as recognition elements and disposable screen-printed electrode biosensors as devices.The research demonstrated that raw beef and raw pork with the target sequence in the range of 10-13-10-5 mol/L showed a good linear relationship with reduction peak current;the linear correlation of beef and pork were 0.96136 and 0.9874 respectively,while the detection limits were 5.048×10-14 mol/L and 3.491×10-14 mol/L respectively.The experiment was performed to simulate the adulteration of pork/beef mixture.When the amount of raw meat mixture was 50 ng,the electric signal value of the reactive dye methylene blue was more stable.On the other hand,when the adulteration ratio was less than 25%or greater than 25%,the binary mixture could be identified.The research reveals that the electrochemical sensor is a sensitively wide detecting,amplification-free,lower cost,and more convenient operation technology.Therefore,it is more in line with the requirements of low-proportion adulteration and rapid on-site detection.
作者
蒋娟娟
丁新怡
倪俊
董益阳
陈浣
闻红
刘佳蕙
JIANG Juanjuan;DING Xinyi;NI Jun;DONG Yiyang;CHEN Huan;WEN Hong;LIU Jiahui(Beijing University of Chemical Technology,College of Life Science and Technology,Beijing 100029,China;Beijing Guangqumen Middle School,Beijing 100062,China;Peking University,College of Chemistry and Molecular Engineering,Beijing 100000,China)
出处
《食品与发酵工业》
CAS
CSCD
北大核心
2019年第23期270-275,共6页
Food and Fermentation Industries
基金
国家重点研发计划项目(2016YFF0203703)
北京市翱翔计划课题(ZS20180018)
