不同液相色谱-串联质谱法检测标准测量不确定度的评定

分别依据标准方法 GB/T 20769-2008 《水果和蔬菜中450种农药及相关化学品残留量的测定液相色谱-串联质谱法》和GB 23200.121-2021 《食品安全国家标准植物源性食品中331种农药及其代谢物残留量的测定液相色谱-质谱联用法》,对大白菜中吡虫啉的残留量测定进行了不确定度评定。通过对两种方法测定步骤的具体分析并建立相应的数学模型,详细评定了包括标准溶液、样品称量、前处理过程、标准溶液峰面积、样品峰面积及方法精密度在内的不确定度分量,并计算出两种方法各自的合成相对标准不确定度及相对扩展不确定度。结果显示,在相同实验室条件下,在95%的置信限(k=2)内,方法GB 23200.121-2021的测量相对扩展不确定度为4.0%,小于GB/T 20769-2008的测量相对扩展不确定度5.6%;决定方法 GB 23200.121-2021不确定度大小的关键因素为标准溶液(占比64.3%);决定方法 GB/T 20769-2008不确定度大小的关键因素为标准溶液(占比33.1%)和方法精密度(占比51.7%)。     

两种蔬菜中甲胺磷、氧乐果和克百威的残留量分析

分别选取一种瓜菜 (黄瓜 )和一种叶菜 (生菜 ) ,选择了两种有机磷 (甲胺磷、氧乐果 )和一种氨基甲酸酯类 (克百威 )农药 ,对这 3种农药在两种蔬菜中的残留测定方法进行了研究。采用弗罗里硅土柱提取的方法进行前处理 ,淋洗液浓缩后用 GC- NPD测定 ,建立了一种简便快速的检测方法 ,并采用该方法对实际处理样本进行了测定。从方法添加回收率和实测数据可以看出 ,该方法净化提取效果好 ,结果平行性好 ,灵敏度较高 ,是一次快速准确测定蔬菜中农药残留的成功尝试。     

高效液相色谱法测定苹果中多菌灵残留量的测量不确定度分析

建立了评定NY/T 1680－2009“蔬菜水果中多菌灵等4种苯并咪唑类农药残留量的测定——高效液相色谱法”中影响测量不确定度的各因素的数学模型,考察了样品前处理和液相色谱测定的各个环节,并根据所建立的数学模型计算了评定测量不确定度的各分量。采用该方法测得市售苹果中多菌灵的残留量为0.23 mg/kg。分析表明:多菌灵残留量测定的不确定度主要来源于样品溶液的平行测定、样品稀释以及萃取、净化等处理过程产生的回收率差异;此外,标准溶液的配制和检测过程以及提取处理等其他环节对其也有一定影响。经计算,在置信概率P=95%时,采用该方法测定试样中多菌灵残留的扩展不确定度为0.02 mg/kg,若不考虑多菌灵残留在样品中分布的均匀性,则苹果试样中多菌灵残留的检测结果可表示为(0.23±0.02) mg/kg（包含因子k=2）。     

不同贮存条件对蔬菜基质中13种农药残留稳定性的影响

针对不同质量浓度13种农药,在室温(25℃)、冷藏(4℃)和冷冻(-18℃)贮存条件下,测定不同时间间隔(46、241和379d)农药残留含量的变化趋势。结果表明:贮存温度条件对蔬菜中农药残留稳定性影响较大。部分农药残留在冷冻贮存时最稳定,随贮存温度升高稳定性逐渐降低,不同农药降解趋势不同。尤其是百菌清,常温贮存时降解最快,5～10d即降解90%左右,其次为甲拌磷,其它农药降解率在30%～50%不等。稳定性较好的农药受浓度的影响不大(如毒死蜱、三唑酮等)。可以得出:样品采集后应尽快处理,若需要存贮,应贮存在等同于冷冻条件下,并且为确保结果的准确和可靠,检测应控制在3d内进行。     

实验室农药残留检测的测量不确定度评定——以GB 23200.8—2016测定草莓中4种农药残留为例

自2018年《CNAS-GL006化学分析中不确定度的评估指南》颁布后,不确定度计算方法的需求日益增强。本研究依据GB 23200.8-2016《水果和蔬菜中500种农药及相关化学品残留量的测定气相色谱-质谱法》,采用气相色谱-质谱法,结合内标定量法,对草莓中丙溴磷、亚胺硫磷、五氯硝基苯和氯氟氰菊酯的残留进行了测量不确定度的详细评定,共涉及标准品纯度、储备液配制、工作液配制、称样量和前处理过程5个B类评定分量,以及标准溶液峰面积、样品溶液峰面积和添加回收率3个A类评定分量。结果显示:在0.08 mg/kg添加水平下,丙溴磷、亚胺硫磷、五氯硝基苯和氯氟氰菊酯的测量合成相对标准不确定度依次为3.55%、3.22%、2.20%和3.66%,样品溶液峰面积和添加回收率2个A类不确定度分量对4种农药合成不确定度的贡献较高,其中丙溴磷、亚胺硫磷和氯氟氰菊酯均超过60%,五氯硝基苯超过31%。本研究中4种农药在草莓样品中的测量结果在95%的置信限(k=2)内可表示为:丙溴磷,0.085±0.006 mg/kg;亚胺硫磷,0.084±0.005 mg/kg;五氯硝基苯,0.079±0.003 mg/kg;氯氟氰菊酯,0.082±0.006 mg/kg。不确定度评定结果将最大限度地减少待测物在最大残留限量附近的残留值判定可能存在的争议。     

三种基质中15种农药及其代谢物的不确定度评估

依据GB 23200.113—2018《食品安全国家标准 植物源性食品中208种农药及其代谢物残留量的测定 气相色谱-质谱联用法》中的QuEChERS方法，建立了一种气相色谱-串联质谱法 (GC-MS/MS) 测定茶叶、普通白菜和苹果3种基质中15种农药及其代谢物残留量的数学模型，通过分析测定过程的主要不确定度来源，对各个分量进行评估。结果表明:工作曲线拟合和回收率所引入的不确定度较大，其次为标准溶液配制和样品制备，而测量重复性和仪器引入的不确定度相对较小；不同基质对工作曲线拟合、回收率和测量重复性所引入的不确定度存在一定差异；不匹配基质校正曲线会对部分农药造成一定程度的基质增强或抑制效应。该方法适用于GC-MS/MS法测定植物源性食品中农药残留量的不确定度评估，可为农药残留测量结果的准确性提供科学可靠的依据。     

黄瓜中乙烯菌核利残留测定的测量不确定度评定

依据NY/T761—2008标准第二部分,采用气相色谱法对黄瓜中乙烯菌核利残留进行测定,分析检测过程中的各不确定度分量来源,建立了不确定度评定的数学模型,进而对各不确定分量进行合成与扩展。结果表明:黄瓜中乙烯菌核利残留测量结果的合成相对标准不确定度和扩展不确定度分别为2.78%和5.56%（k=2）,其中标准溶液的稀释与定容过程、乙烯菌核利残留的提取和净化过程所产生的回收率差异、色谱峰面积测量导致的误差是测量不确定度的主要来源。本研究结果可为客观评价蔬菜中农药残留检测结果提供参考。     

分散固体萃取法测定蔬菜水果中25种农药残留

本文研究了分散固体萃取方法快速测定蔬菜水果中的25种农药残留的方法。采用一种新的样品前处理技术,用0.1%冰乙酸乙腈溶液从蔬菜水果中提取净化25种农药残留,运用GC/MS进行分析。用内标法定量,加标浓度分别为0.01、0.05、0.1μg/mg时,回收率在75.06～108.26%之间,相对偏差不>10%。方法检出下限为0.01～0.05μg/mg,用该方法可实现对蔬菜水果中农药残留的检测。     

蔬菜中毒死蜱等几种农药残留量测定不确定度分析

本文结合NY/T 761-2004农药残留分析方法,把毒死蜱、氯氰菊酯、茚虫威、烯酰吗啉等4种农药残留量测定不确定度分为称量、提取、净化、色谱测定等分量,用校正因子来表征测定过程中的重复性不确定度,并加以评定,为试验室质量管理和控制提供科学依据。结果表明,色谱定量重复性误差及同一样品的重复性误差所引入的不确定度是影响残留量测定不确定度的较大因素。     

瑞士汽巴-嘉基公司农药残留分析前处理的情况

瑞士汽巴一嘉基公司农药残留分析室是一个具有国际水平的现代化研究室.该室不仅具有自动化、电子化的现代仪器设备,而且更主要的是拥有一定数量的具有国际水平的专家,在长期工作中,积累了一整套残留分析方法的经验,特别是在样本抽提、净化等方面具有独到之处,现将有关经验介绍如下. 一、样本贮存从田间取回的样本,往往不能及时进行分析,必须保存在低温条件下,以防止残留农药的分解,在瑞士要求放在-20℃条件下保存.盛装样本的容器有玻璃瓶、聚丙稀(或聚乙     

A model of the decision‐support scheme for express pest risk analysis using a Bayesian network implemented in Excel

A model was developed to accompany the EPPO decision support scheme for express pest risk analysis (PRA) and provide a calculated overall risk and uncertainty for the PRA and so act as a reference for the judgement of overall risk and uncertainty provided by expert working groups. Implemented in Excel, it is readily accessible to PRA practitioners and offers: (a) a consistent and explained weighting of the different risk factors and a rationale for the way they are combined, (b) a calculated integration of the risk factor distributions to facilitate judgement of overall uncertainty, and (c) an account of the interaction between the rating and the uncertainty score so that, for example, an overall rating of moderate is not necessarily used to reflect uncertainty about assessments in which the risk is neither obviously high nor low. Of the nine published express PRAs examined, the rating and uncertainty predicted by the model were: in agreement with five; differed in both rating and uncertainty in one case; differed in rating only in one case; and differed in uncertainty only in two cases. Possible reasons for these differences were examined and the interpretation of model results to inform assessments is discussed.     

毒死蜱及其代谢物3,5,6-三氯-2-吡啶酚在黄瓜腌制过程中的残留水平变化

采用超高效液相色谱-串联质谱(UPLC-MS/MS)检测了毒死蜱及其有毒代谢物3,5,6-三氯-2-吡啶酚(TCP)在黄瓜腌制加工过程中残留水平的变化。结果表明:用水常规清洗能使黄瓜中毒死蜱的残留水平降低34%,清洗后的黄瓜经初腌和复腌2次处理后,其中毒死蜱的残留水平有所升高,3步处理的总加工因子为0.97;清洗对TCP的残留水平影响不大(仅降低2.6%),但经初腌和复腌处理后,其残留水平明显高于清洗前,3步加工的总加工因子为1.63。本研究表明,黄瓜经腌制前后毒死蜱的残留水平无明显变化,而代谢物TCP的残留水平明显升高。     

Tools for visualizing and integrating pest risk assessment ratings and uncertainties*

The application of pest risk analysis (PRA) decision‐support schemes, such as that used by the European and Mediterranean Plant Protection Organization (EPPO), generates many ratings for likelihood or magnitude of risk factors, each with an associated uncertainty. In accordance with the international standard ISPM 11 ( FAO, 2004 ), questions have been devised to assess the key elements of pest risk in the four main sections of pest risk assessment: Entry, Establishment, Spread and Impact. After completing each section, risk assessors are required to give a summary rating and an uncertainty score for that section. The large number of question ratings and uncertainty scores make the task of summarizing each section and its uncertainty quite difficult. Two graphical tools have been developed to aid this task: the PRA Risk score and uncertainty visualizer (Visualizer) and the Rule‐based matrix model (RBMM). The Visualizer presents a case summary graph on a single page in such a way that the risk assessors and peer reviewers can see rating scores and uncertainties in a pictorial manner; the RBMM integrates all the individual questions in the assessment through a hierarchy of rules that attempt to mimic the logic used by the assessors and are arranged in the form of a flow chart to give an overall rating with an accompanying expression of uncertainty.     

Performance and uncertainty analysis of a short-term climate reconstruction based on multi-source data in the Tianshan Mountains region,China

Short-term climate reconstruction, i.e., the reproduction of short-term(several decades) historical climatic time series based on the relationship between observed data and available longer-term reference data in a certain area, can extend the length of climatic time series and offset the shortage of observations. This can be used to assess regional climate change over a much longer time scale. Based on monthly grid climate data from a Coupled Model Inter-comparison Project phase 5(CMIP5) dataset for the period of 1850–2000, the Climatic Research Unit(CRU) dataset for the period of 1901–2000 and the observed data from 53 meteorological stations located in the Tianshan Mountains region(TMR) of China during the period of 1961–2011, we calibrated and validated monthly average temperature(MAT) and monthly accumulated precipitation(MAP) in the TMR using the delta, physical scaling(SP) and artificial neural network(ANN) methods. Performance and uncertainty during the calibration(1971–1999) and verification(1961–1970) periods were assessed and compared using traditional performance indices and a revised set pair analysis(RSPA) method. The calibration and verification processes were subjected to various sources of uncertainty due to the influence of different reconstructed variables, different data sources, and/or different methods used. According to traditional performance indices, both the CRU and CMIP5 datasets resulted in satisfactory calibrated and verified MAT time series at 53 meteorological stations and MAP time series at 20 meteorological stations using the delta and SP methods for the period of 1961–1999. However, the results differed from those obtained by the RSPA method. This showed that the CRU dataset produced a low degree of uncertainty(positive connection degree) during the calibration and verification of MAT using the delta and SP methods compared to the CMIP5 dataset. Overall, the calibrated and verified MAP had a high degree of uncertainty(negative connection degree) regardless of the dataset or reconstruction method used. Therefore, the reconstructed time series of MAT for the period of 1850(or 1901)–1960 based on the CRU and CMIP5 datasets using the delta and SP methods could be used for further study. The results of this study will be useful for short-term(several decades) regional climate reconstruction and longer-term(100 a or more) assessments of regional climate change.     

六种新烟碱类杀虫剂残留在苹果实验室模拟加工中的变化

为明确苹果中残留的烯啶虫胺、噻虫嗪、吡虫啉、噻虫胺、呋虫胺和啶虫脒6种新烟碱类药剂在不同加工过程中的变化情况,采用高效液相色谱法研究了6种药剂在苹果实验室罐头、果酱、果酒和果醋模拟加工过程中的残留量变化。结果表明:在苹果罐头加工过程中,6种药剂在罐头中残留量与初始浓度相比均显著降低,其中吡虫啉和噻虫胺在罐头中的加工因子较高,均为0.8,啶虫脒在罐头中的加工因子最低,为0.1。罐头汁中烯啶虫胺的加工因子最高,为0.5,其次为啶虫脒和噻虫嗪,均为0.4。在果酱加工过程中,烯啶虫胺、噻虫嗪、吡虫啉、噻虫胺、呋虫胺和啶虫脒的加工因子分别为0.8、0.9、0.9、1.0、0.9和0.9。在果酒中除吡虫啉的加工因子为0.1外,其余药剂加工因子均小于0.1。在果醋中除噻虫胺有少量残留(0.05 mg/kg)外,其余药剂均低于检出限。6种新烟碱类药剂在苹果实验室模拟加工过程中,加工因子均小于1,残留降低。     

Descriptive assessment of uncertainties of qualitative real‐time PCR for detection of plant pathogens and quality performance monitoring

In most cases, plant pest diagnostic methods are interpreted as providing qualitative data. However, although qualitative, it is still important to identify all the sources and components of uncertainty in the diagnostic process and to ensure that appropriate measures are taken to reduce the uncertainty and that the form of reporting the result does not give the wrong impression of the uncertainty. This process was illustrated using real‐time PCR testing of grapevine yellows phytoplasma. Some additional quality performance monitoring of real‐time PCR is also described. This approach has been used by the National Institute of Biology, Slovenia, since 2012, in support of accreditation under ISO 17025, and it can also be applied to other detection methods and other pests.     

烟嘧磺隆降解菌枯草芽孢杆菌YB1颗粒剂的加工及应用

YB1是从农药厂污水中分离筛选得到的一株对烟嘧磺隆具有较好降解作用的枯草芽孢杆菌Bacillus subtilis。为探究YB1对土壤中烟嘧磺隆的降解能力，本研究对YB1固体发酵产物进行了颗粒剂加工，并对菌株载体和保护剂进行了筛选。优化后的YB1颗粒剂的加工方法为:将YB1固体发酵产物与载体活性白土按质量比1:1混合，加入质量分数为3%的保护剂酪氨酸和5%的淀粉进行挤压造粒，所得颗粒剂的有效活菌数为8.75×108 CFU/g。以小麦为指示植物，应用室内盆栽法研究了YB1颗粒剂对土壤中烟嘧磺隆的降解效果。结果表明，1 kg土壤中添加20 g YB1颗粒剂28 d后可将土壤中1 mg/kg的烟嘧磺隆降解至对小麦无明显药害水平。研究结果表明，YB1颗粒剂对含有烟嘧磺隆残留的土壤具有一定的修复能力。