膜芯片技术对牛、羊、牦牛、驴肉源食品的掺伪鉴别
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摘要
采用膜芯片技术,通过对牛、羊、驴、牦牛、鸡、鸭、兔、貂、狐、鼠、猪11种目标物种的检测,实现对牛、羊、驴、牦牛物种的掺伪鉴别。结果表明:该方法具有良好的特异性和适用性,检测灵敏度和掺伪灵敏度均可达到0.1%,能快速、准确地同时鉴别牛、羊、驴、牦牛、鸡、鸭、兔、貂、狐、鼠、猪11种动物源性成分,可满足肉类食品样品中对牛、羊、牦牛、驴等掺伪鉴别的检验需求。
A membrane chip technology to detect 11 target animal species including cattle, sheep, donkey, yak, chicken,duck, rabbit, mink, fox, mouse and pig was developed in order to identify adulteration in beef, mutton, donkey and yak meat products. Our experimental results showed that the method had good specificity and applicability. The method sensitivity and its sensitivity in detecting adulterated meat samples were both up to 0.1%. This method could quickly and accurately identify 11 animal origin components of cattle, sheep, donkey, yak, chicken, duck, rabbit, mink, fox, mouse and pig, and could meet the requirements for the identification of adulteration in beef, mutton, yak and donkey meat samples.
A membrane chip technology to detect 11 target animal species including cattle, sheep, donkey, yak, chicken,duck, rabbit, mink, fox, mouse and pig was developed in order to identify adulteration in beef, mutton, donkey and yak meat products. Our experimental results showed that the method had good specificity and applicability. The method sensitivity and its sensitivity in detecting adulterated meat samples were both up to 0.1%. This method could quickly and accurately identify 11 animal origin components of cattle, sheep, donkey, yak, chicken, duck, rabbit, mink, fox, mouse and pig, and could meet the requirements for the identification of adulteration in beef, mutton, yak and donkey meat samples.
引文
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[12]高敬,魏迪,张癸荣,等.常见肉类鉴别技术研究进展[J].食品科学,2014,35(11):356-360.
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[15]钱俊平,郭梁,海小,等.肉制品中羊源性成分的定性和定量检测[J].肉类研究,2018,32(12):42-47.DOI:10.7506/rlyj1001-8123-201812008.
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[18]周李华,马丽侠,李怀平,等.牛源性成分核酸检测方法研究进展及技术标准分析[J].中国测试,2017,43(12):50-57.
[19]李婷婷,张桂兰,赵杰,等.肉及肉制品掺假鉴别技术研究进展[J].食品安全质量检测学报,2018,9(2):409-415.
[20]杨冬燕,李浩,杨永存.肉制品掺假鉴别与定量检测[J].卫生研究,2016,45(2):324-328.
[21]FISS E H,CHEHAB F F,BROOKS G F.DNA amplification and reverse dot blot hybridization for detection and identification of mycobacteria to the species level in the clinical laboratory[J].Journal of Clinical Microbiology,1992,30(5):1220-1224.
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[23]贺晨,孙鸿燕,邵丽筠,等.多重PCR结合基因芯片技术检测11种致病菌方法的建立[J].中国实验诊断学,2011,15(4):587-591.
[24]YUN Zhenyu,PENG Liping,HUO Shengnan,et al.Auto-microfluidic thin-film chip for genetically modified maize detection[J].Food Control,2017,80:360-365.
[25]李永进,熊涛,吴华伟,等.利用可视化膜芯片检测9种转基因玉米[J].湖北农业科学,2016,55(11):2926-2929.DOI:10.14088/j.cnki.issn0439-8114.2016.11.055.
[26]韦世录,何敏,何晓,等.结核杆菌耐药基因膜芯片检测[J].中国公共卫生,2012,28(4):425-427.
[27]朱业培,王玮,吕青骎,等.基于基因芯片技术检测6种动物源性成分[J].南京农业大学学报,2015,38(6):1003-1008.
[28]范宏伟,吴鑫,朱应飞,等.膜芯片用于肉制品中动物源性成分检测的研究[J].食品安全质量检测学报,2017,8(9):3479-3484.
[29]苏焕斌,张燕,彭宏威.生物芯片在食品安全检测中的应用研究进展[J].食品安全质量检测学报,2018,9(11):2756-2761.
[30]WANG Wei,HAN Jianxun,WU Yajun,et al.Simultaneous detection of eight food allergens using optical thin-film biosensor chips[J].Journal of Agricultural and Food Chemistry,2011,59(13):6889-6894.DOI:10.1021/jf200933b.
[2]海小,刘国强,罗建兴,等.基于Taq Man实时荧光PCR检测鲜肉及加工肉制品中的驴源性成分[J].肉类研究,2018,32(4):62-67.DOI:10.7506/rlyj1001-8123-201804011.
[3]刘畅,张奇,王思颖,等.驴肉及其制品真伪鉴别技术研究进展[J].食品安全质量检测学报,2017,8(7):2657-2663.
[4]李维红,高雅琴,杨晓玲,等.不同牦牛肉氨基酸质量分析[J].湖北农业科学,2018,57(12):89-90;105.DOI:10.14088/j.cnki.issn0439-8114.2018.12.024.
[5]段庆梓,尚柯,张彪,等.肉及肉制品中牦牛源性成分的PCR鉴别[J].食品研究与开发,2017,38(9):157-160.
[6]唐善虎,李雪,王柳.用LAMP法快速鉴别熟制牦牛肉饼中的猪肉和鸡肉成分[J].西南民族大学学报(自然科学版),2018,44(3):237-242.
[7]邱翔,张磊,文勇立,等.四川牦牛、黄牛主要品种肉的营养成分分析[J].食品科学,2010,31(15):112-116.
[8]沙才华,汪文辉,黄海超,等.Taq Man荧光PCR法检测肉制品中牛源性成分及定量研究[J].中国动物检疫,2016,33(12):89-93.
[9]罗绍楠,戴奕杰,孙端方.贵阳市纯牛源性食品真实性鉴定调查[J].食品安全导刊,2018(3):149-150.DOI:10.16043/j.cnki.cfs.2018.03.104.
[10]李楠,王佳慧,沈青,等.北京地区牛、羊肉片中鸭、鸡、猪源性成分调查[J].中国食品卫生杂志,2014,26(3):227-232.DOI:10.13590/j.cjfh.2014.03.006.
[11]王成程,韩国全,张琴,等.肉及肉制品真伪鉴别技术研究进展[J].食品安全质量检测学报,2018,9(22):5930-5935.
[12]高敬,魏迪,张癸荣,等.常见肉类鉴别技术研究进展[J].食品科学,2014,35(11):356-360.
[13]AL-KAHTANI H A,ISMAIL E A,ASIF AHMED M.Pork detection in binary meat mixtures and some commercial food products using conventional and real-time PCR techniques[J].Food Chemistry,2017,219:54-60.DOI:10.1016/j.foodchem.2016.09.108.
[14]陈文炳,邵碧英,廖宪彪,等.加工食品中若干动物成分的PCR检测技术应用研究[J].食品科学,2005,26(8):338-342.
[15]钱俊平,郭梁,海小,等.肉制品中羊源性成分的定性和定量检测[J].肉类研究,2018,32(12):42-47.DOI:10.7506/rlyj1001-8123-201812008.
[16]REN Junan,DENG Tingting,HUANG Wensheng,et al.A digital PCRmethod for identifying and quantifying adulteration of meat species in raw and processed food[J].PLoS One,2017,12(3):e0173567.DOI:10.1371/journal.pone.0173567.
[17]SHEHATA H R,LI J,CHEN S,et al.Droplet digital polymerase chain reaction(ddPCR)assays integrated with an internal control for quantification of bovine,porcine,chicken and turkey species in food and feed[J].PLoS One,2017,12(8):e0182872.DOI:10.1371/journal.pone.0182872.
[18]周李华,马丽侠,李怀平,等.牛源性成分核酸检测方法研究进展及技术标准分析[J].中国测试,2017,43(12):50-57.
[19]李婷婷,张桂兰,赵杰,等.肉及肉制品掺假鉴别技术研究进展[J].食品安全质量检测学报,2018,9(2):409-415.
[20]杨冬燕,李浩,杨永存.肉制品掺假鉴别与定量检测[J].卫生研究,2016,45(2):324-328.
[21]FISS E H,CHEHAB F F,BROOKS G F.DNA amplification and reverse dot blot hybridization for detection and identification of mycobacteria to the species level in the clinical laboratory[J].Journal of Clinical Microbiology,1992,30(5):1220-1224.
[22]YUN Zhenyu,ZENG Lian,HUANG Weijian,et al.Detection and categorization of diarrheagenic escherichia coli with auto-microfluidic thin-film chip method[J].Scientific Reports,2018,8(1):12926.DOI:10.1038/s41598-018-30765-3.
[23]贺晨,孙鸿燕,邵丽筠,等.多重PCR结合基因芯片技术检测11种致病菌方法的建立[J].中国实验诊断学,2011,15(4):587-591.
[24]YUN Zhenyu,PENG Liping,HUO Shengnan,et al.Auto-microfluidic thin-film chip for genetically modified maize detection[J].Food Control,2017,80:360-365.
[25]李永进,熊涛,吴华伟,等.利用可视化膜芯片检测9种转基因玉米[J].湖北农业科学,2016,55(11):2926-2929.DOI:10.14088/j.cnki.issn0439-8114.2016.11.055.
[26]韦世录,何敏,何晓,等.结核杆菌耐药基因膜芯片检测[J].中国公共卫生,2012,28(4):425-427.
[27]朱业培,王玮,吕青骎,等.基于基因芯片技术检测6种动物源性成分[J].南京农业大学学报,2015,38(6):1003-1008.
[28]范宏伟,吴鑫,朱应飞,等.膜芯片用于肉制品中动物源性成分检测的研究[J].食品安全质量检测学报,2017,8(9):3479-3484.
[29]苏焕斌,张燕,彭宏威.生物芯片在食品安全检测中的应用研究进展[J].食品安全质量检测学报,2018,9(11):2756-2761.
[30]WANG Wei,HAN Jianxun,WU Yajun,et al.Simultaneous detection of eight food allergens using optical thin-film biosensor chips[J].Journal of Agricultural and Food Chemistry,2011,59(13):6889-6894.DOI:10.1021/jf200933b.