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转基因定量检测结果测量不确定度的自上而下评定方法研究及应用 被引量:2

Development and Application of Top-Down Approaches for Estimating Measurement Uncertainty of GMO Quantitative Results
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摘要 【目的】定量检测标准体系是实施转基因定量标识的基础,而不确定度评定是定量检测标准体系的重要组成部分。急需建立适合一般实验室采用的标准化转基因定量检测结果不确定度的自上而下评定方法,以便检测实验室自行评定定量检测结果的测量不确定度。【方法】测量方法精密度不确定度评定有2种方法,一种是根据“不确定度函数”的一般概念,利用15个不同浓度的常规样品,建立测量方法精密度引入的不确定度评定公式;另一种是重复测量有证标准物质,根据检测数据的中间精密度,计算方法精密度引入的不确定度。用有证标准物质或实验室配制样品作阳性定量质控品进行偏倚不确定度评定,实验室配制样品标称值的不确定度由实验室根据制备过程采用简易程序自行评定。将测量方法精密度引入的不确定度和测量过程的偏倚不确定度合成,评定试样定量结果的标准不确定度,然后乘以包含因子k,获得扩展不确定度。【结果】以转基因玉米DBN9936定量检测方法为例,分别用模拟的DBN9936常规样品和有证基体标准物质(GBW(E)100901)评定测量方法精密度引入的不确定度,分别为0.76%和0.33%,与常规样品相比,用有证标准物质评定的测量方法精密度不确定度显著偏小。用有证标准物质(GBW(E)100901)评定的偏倚不确定度为0.26%;用实验室配制粉末样品和基因组DNA样品(标称值均为3.0%)评定的偏倚不确定度分别为0.20%和0.19%。采用简易程序评定实验室配制样品标称值引入的不确定度时,部分不确定度分量被忽略,评定的偏倚不确定度偏小。将测量方法精密度不确定度和偏倚不确定度分别合成,用常规样品评定的扩展不确定度为1.26%、1.20%和1.20%;用有证标准物质评定的扩展不确定度为0.84%、0.78%和0.76%。【结论】建立了转基因定量检测结果自上而下的不确定度评定方法,检测实验室要优先选择用常规样品评定测量方法精密度引入的不确定度。在评定偏倚不确定度时,检测实验室原则上要优先选择有证标准物质作阳性定量质控品。 【Objective】The enforcement of labeling regulations on genetically modified organisms(GMOs)requires establishing a standard system for accurate quantification of GMOs that includes the standard or guide for estimating measurement uncertainty(MU).It is urgent to establish a standardized top-down approach for estimating MU of quantitative results,which is conveniently adopted by the general testing laboratories.【Method】There are two approaches for estimating the MU introduced by precision of quantitative method,one is to establish the equation of MU estimation using data obtained on 15 routine samples based on the"uncertainty function",the other is to evaluate the MU by repeatedly measuring a certified reference material(CRM)and calculating the intermediate precision.The uncertainty introduced by bias is evaluated using a CRM or a sample prepared by laboratory as bias control.The uncertainty of the nominal value of the sample prepared by laboratory is evaluated by using a simplified program based on the preparation process.The MU contributed by method precision and bias are combined into the standard uncertainty of the quantitative results,and then multiplied by the coverage factor k to obtain the expanded uncertainty.【Result】The event-specific PCR method of genetically modified maize DBN9936 was took as an example.The MU of method precision was evaluated to be 0.76%using simulated DBN9936 routine samples,and to be 0.33%using a CRM(GBW(E)100901).Compared with routine samples,the MU of method precision evaluated using a CRM is significantly underestimated.The uncertainty introduced by bias was evaluated to be 0.26%using a CRM(GBW(E)100901)as a bias control.Using a laboratory prepared powder sample and a genomic DNA sample(nominal values of 3.0%)as bias control,the bias uncertainty was evaluated to be 0.20%and 0.19%,respectively.Since the simplified program ignored some uncertainty components,the uncertainty of the nominal value of laboratory prepared samples was estimated to be smaller.By combining the MU of method precision and bias,the expanded uncertainty using routine samples was obtained to be 1.26%,1.20%,and 1.20%,respectively,the expanded uncertainty using a CRM was 0.84%,0.78%,and 0.76%,respectively.【Conclusion】This study established the top-down approaches for MU estimation of quantitative results,testing laboratories should prioritize routine samples to estimate the MU contributed by the method precision,and select CRMs as bias control in principle to evaluate bias uncertainty during GMO quantification.
作者 李俊 赵新 陈红 李飞武 梁晋刚 李允静 王颢潜 高鸿飞 张华 陈子言 吴刚 沈平 徐利群 武玉花 LI Jun;ZHAO Xin;CHEN Hong;LI FeiWu;LIANG JinGang;LI YunJing;WANG HaoQian;GAO HongFei;ZHANG Hua;CHEN ZiYan;WU Gang;SHEN Ping;XU LiQun;WU YuHua(Oil Crops Research Institute,Chinese Academy of Agricultural Sciences/Key Laboratory of agricultural genetically modified organism traceability,Ministry of Agriculture and Rural Affairs,Wuhan 430062;Tianjin Academy of Agricultural Sciences,Tianjin 300384;Development Center of Science and Technology,Ministry of Agriculture and Rural Affairs,Beijing 100025;Jilin Academy of Agricultural Sciences,Changchun 130033)
出处 《中国农业科学》 CAS CSCD 北大核心 2023年第22期4371-4385,共15页 Scientia Agricultura Sinica
基金 科技创新2030—重大项目(2022ZD0402010)。
关键词 转基因定量结果 测量不确定度 自上而下 有证标准物质 阳性定量质控品 quantitative results of GMO content measurement uncertainty top-down approach certified reference materials bias control
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