UPLC-MS/MS测定猪肝中五氯酚残留量的不确定度评定

根据GB 23200.92—2016规定的方法对样品中五氯酚的残留量进行测定,通过建立数学模型,确定不确定度来源并分别进行量化,计算合成不确定度。结果显示:当猪肝中的五氯酚残留量为14μg/kg时,在95%的置信区间下,合成不确定度为1.4μg/kg,扩展不确定度为3μg/kg(k=2)。样品净化后的定容体积、样品测量重复性、标准溶液的配制与标准曲线的拟合等环节引入不确定度分量的相对贡献最大。     

多波长高效液相色谱法测定米豆腐中4种色素

目的建立多波长高效液相色谱法监测米豆腐中添加柠檬黄、胭脂红、日落黄、亮蓝等4种人工色素。方法氨碱性条件下用水作溶剂超声提取米豆腐中色素,提取液用柠檬酸溶液调节p H值至弱酸性,高效液相色谱在线分离。经Waters C_(18)色谱柱(250 mm×4.6 mm,5μm)分离;以0.02 mol/L乙酸铵(p H值5.5)—甲醇为流动相进行梯度洗脱,流速为1.0 m L/min,柱温30℃,以各组分的最大吸收波长为检测波长,外标法定量。结果 4种组分在1.00~100μg/m L范围内线性关系良好,相关系数在0.9993~0.9997(n=7),平均加标回收率在87.4%~89.5%(n=3)。结论该斱法同时测定米豆腐中4种人工色素,前处理简单、快速,定量准确,灵敏度高,可用于米豆腐的质量控制。     

液相色谱-串联质谱法同时测定中草药保健食品中15种有机磷和氨基甲酸酯类农药残留

目的建立高效液相色谱-串联质谱法同时测定中草药保健食品中15种有机磷和氨基甲酸酯类农药残留。方法样品经乙腈提取后,高速离心,经分散型固相萃取小柱净化。采用Atlantis C_(18)(2.1 mm×100 mm,3μm)柱,以0.1%甲酸-乙腈为流动相,梯度洗脱分离。质谱采用正离子模式(electrospray ionization,ESI+),多反应监测模式(multiple reaction monitoring,MRM)进行检测,基质曲线外标法定量。结果该方法对15种农药残留的线性范围为0.001~0.1μg/mL,线性相关系数r≥0.993,加标回收率为82.7%~113.3%,相对标准偏差为2.7%~10.6%,检出限为0.8~24.6μg/kg。结论本方法操作简单、快捷,适用于中草药保健食品中15种有机磷和氨基甲酸酯类农药残留的同时检测,为保健食品质量控制提供依据。     

顶空—气相色谱法测定食品中亚硝酸盐

对顶空—气相色谱测定饮用水、烟笋、外婆菜和烤耳尖中亚硝酸含量进行研究,建立亚硝酸盐的快速、准确、定量检测方法,对该方法的反应机理进行推断,并用顶空—气质联用仪对反应产物进行验证。烟笋、外婆菜和烤耳尖经粉碎、沸水提取、沉淀剂沉淀和过滤后,取样品溶液分析,饮用水直接取样分析。样品处理液中先后加入环己基氨基磺酸钠溶液和硫酸溶液,在顶空瓶中50℃条件下发生重氮化反应,以衍生产物环己烯作为目标产物,定量分析。结果表明,低浓度标准物质标准曲线r~2为0.999 0,取样量为5 mL时,对应的检测范围为0.001~0.200 mg/L;高浓度标准物质标准曲线r~2为0.999 5,取样量为3g时,对应的检测范围为0.67~167.00mg/kg。该方法检出限低,线性范围宽,重复性和回收率好,是快速检测食品中亚硝酸盐较好的方法。     

《保健食品检验与评价技术规范》中肉碱含量测定方法适用性的探讨

目的对《保健食品检验与评价技术规范》(2003年版)肉碱含量测定的高效液相色谱法进行适用性研究。方法通过对检测波长、色谱柱、流动相比例等色谱条件,提取剂、提取温度及提取时间等提取条件的试验研究,探讨不同提取方法及色谱条件对检验结果的影响。结果以纯化水为提取剂、30℃超声20 min,采用色谱柱Phenomenex Gemini C18,流动相p H 2.5 0.05 mol/L磷酸氢二钾:0.002 mol/L辛烷磺酸钠:乙腈(52:45:3),检测波长210 nm,0.8 m L/min,肉碱浓度在47.86~2390μg/m L范内呈良好的线性关系,(r2=1.0000),平均回收率为101.58%,RSD值为1.46%。结论该方法简化了提取剂配制步骤,优化了流动相的比例,改善了色谱柱的专属性,该试验条件适用于不同产品中左旋肉碱含量的测定,可提高肉碱质量标准的实验操作性。     

Retail electricity price savings from compliance flexibility in GHG standards for stationary sources

The EPA will issue rules regulating greenhouse gas (GHG) emissions from existing steam boilers and refineries in 2012. A crucial issue affecting the scope and cost of emissions reductions will be the potential introduction of flexibility in compliance, including averaging across groups of facilities. This research investigates the role of compliance flexibility for the most important of these source categories—existing coal-fired power plants—that currently account for one-third of national emissions of carbon dioxide, the most important greenhouse gas. We find a flexible standard, calibrated to achieve the same emissions reductions as a traditional(inflexible) approach, reduces the increase in electricity price by 60 percent and overall costs by two-thirds in 2020. The flexible standard also leads to substantially more investment to improve the operating efficiency of existing facilities, whereas the traditional standard leads to substantially greater retirement of existing facilities.     

QuEChERS-高效液相色谱法同时测定植物固体饮料中10种植物毒素

建立了植物固体饮料中原百部碱、侧柏酮、香豆素、黄连素、黄樟素、山道年、芦荟苷、细辛脑、异黄樟素、长叶薄荷酮10种植物毒素的QuEChERS结合超高效液相色谱的检测方法。样品经乙腈提取,应用QuEChERS技术净化,Wlech Xtimate C_8液相色谱柱(4.6mm×250mm,5μm)分离,流动相为甲醇-10 mmol/L乙酸铵水溶液(pH 3.5),通过PDA检测器进行检测。试验表明,10种植物毒素在0.005～154.200mg/L范围内线性关系良好,相关系数均0.997,方法检出限(S/N=3)为0.010～0.270mg/kg,定量限(S/N=10)为0.032～0.830mg/kg。阴性样品的3个添加水平的平均回收率在78.46%～100.77%,相对标准偏差(RSD,n=6)1.10%～3.07%,日间精密度为1.11%～2.73%。该方法操作简单,准确高效,适用于植物固体饮料种10种植物毒素含量的测定。     

基于RSM和GA-ANN优化超声-顶空气相色谱法测定植物油中六号溶剂残留量前处理条件

建立植物油中六号溶剂残留量的超声-顶空气相色谱(UV-HGC)分析方法。采用单因素实验考察超声功率、超声时间、超声温度对六号溶剂残留量检测的影响,并用响应面法(RSM)和遗传算法-人工神经网络(GA-ANN)对UV-HGC条件进行优化。结果表明:RSM和GA-ANN相对误差、决定系数(R~2)分别为9. 15%、0. 891 4和5. 95%、0. 949 5,说明GA-ANN比RSM具有更强的预测和优化能力。采用GA-ANN优化获得UV-HGC最佳前处理条件为超声功率500 W、超声时间7 min、超声温度50℃。在最佳前处理条件下,植物油中的六号溶剂在9. 53～200 mg/kg质量浓度范围内线性关系良好,相关系数(r)为0. 999 4,在低、中、高3个加标水平下,平均回收率分别为95. 5%、98. 6%、100. 4%,相对标准偏差(RSD)均小于3. 5%。方法的检出限(LOD)为1. 85mg/kg,定量限(LOQ)为9. 53 mg/kg。该方法操作简单、快速、灵敏、准确,适用于植物油中六号溶剂残留量的检测。     

Authentication of Polygonati Odorati Rhizoma and other two Chinese Materia Medica of the Liliaceae family by pharmacognosy technique with GC–MS analysis

Yuzhu (Polygonati Odorati Rhizoma), Kangdingyuzhu (Polygonati Prattii Rhizoma), and zhugenqiyuzhu (Disporopsis Fuscopictae Rhizoma) are of the same family, but of different genera. They have all often used in Chinese Materia Medica (CMM) as Polygonati Odorati Rhizoma in China market. Three species of CMM are confused. For better application, we need to identify these plants accurately. This study use pharmacognosy technique and GC‐MS analysis, three species of CMM were authenticated. In macroscopic characteristics, the fruit of Polygonati Odorati Rhizoma is blue‐black, while the other two are maroon and dark purple orderly. Nodes of Polygonati Odorati Rhizoma are upward and light uplift, about 1 cm spacing, while the other are not. As for microscopic characteristics, the cortex of Polygonati Odorati Rhizoma only occupies about 1/5 of the radius of the transverse section with inconspicuous endodermis, which is much smaller than others. The type of vascular bundles of Polygonati Odorati Rhizoma is closed collateral, but the other is amphivasal. Raphides of calcium oxalate are scattered, but Raphides of the other two are like brooms and neat rows. GC–MS analysis of essential oil could provide different characteristics to distinguish three species. Twenty‐three compounds were identified from essential oil of Polygonati Odorati Rhizoma and the main components were n‐hexadecanoic acid (49.45%), while n‐hexadecanoic acid of the other two are 23.92% and 9.45%. The content of n‐hexadecanoic is strongly different. This research was aimed to establish a method by pharmacognosy and GC–MS analysis to identify three CMM and for providing scientifical data to ensure accuracy of origin of three species. Microsc. Res. Tech. 78:119–127, 2015. © 2014 Wiley Periodicals, Inc.     

QuEChERS结合气相色谱三重四极杆串联质谱法测定高粱中45种农药残留

该实验建立气相色谱三重四极杆串联质谱法（GC-MS/MS）结合改良的QuEChERS方法同时检测高粱中45种农药残留。高粱粉末加水浸润后,加入10 mL乙腈-乙酸乙酯（1∶1,V/V）溶液,加入WondaPak提取盐试剂包Ⅱ提取,取上清液加入WondaPak净化管Ⅲ净化,氮吹近干,定容至1 mL,基质内标法定量。在质量浓度为0.05～1.00 μg/mL范围内,各农药的线性关系良好,线性回归方程的相关系数（R2）均＞0.995,方法检出限为0.001 2～0.042 4 mg/kg。分别向阴性高粱样品中添加质量浓度为0.01 mg/kg、0.10 mg/kg和0.50 mg/kg的45种农药标准品,其平均加标回收率为76.32%～108.45%,精密度实验结果的相对标准偏差（RSD）为0.12%～10.95%。与其他农药残留检测方法比较,该方法具有前处理操作简单、重复性好、灵敏度高、降低分析成本等优势,适用于高粱样品中农药的高灵敏度快速检测。