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1.
为探讨酶联免疫吸附法(ELISA)检测结果的影响因素,试验分析了ELISA法检测饲料中莱克多巴胺的不确定度.依据JF 1059-1999《测量不确定度评定与表示》和CNAS-GL06《化学分析中不确定度的评估指南》规定的测量不确定度的基本方法,分析不确定度来源并进行量化,找出主要影响因素.结果显示,ELISA法检测饲料中莱克多巴胺含量为43.75 ng/kg时,其扩展不确定度为6.77 ng/kg,k=2.影响不确定度的主要因素为样品称量、测量重复性和标准曲线拟合.  相似文献   

2.
检测莱克多巴胺胶体金免疫层析试验的建立   总被引:1,自引:0,他引:1  
采用混合酸酐法制备莱克多巴胺-OVA偶联抗原,胶体金标记莱克多巴胺单克隆抗体,建立了检测莱克多巴胺的胶体金免疫层析试验。该试验具有较好的敏感性和特异性,最低可检测10ng/mL的莱克多巴胺,而与克伦特罗和沙丁醇胺无交叉反应。胶体金免疫层析试验对尿液和饲料样品中莱克多巴胺的最低检测量分别为10ng/mL和0.01mg/kg。  相似文献   

3.
为保证实验室测试结果的准确性和可靠性,依照国家计量技术规范JJF1059—199《测量不确定度评定与表示》,对气相色谱-质谱法测定动物组织中莱克多巴胺残留量进行了不确定度的评定。分析和量化了影响测定结果的各不确定度分量,得出了被测量的合成标准不确定度和扩展不确定度。当动物组织中莱克多巴胺残留量为17.72μg/kg时,其合成标准不确定度为0.47μg/kg,扩展不确定度为0.94μg/kg(k=2)。  相似文献   

4.
为了验证ELISA方法检测猪尿中莱克多巴胺残留量的可行性,采用ELISA方法对试剂盒的校正曲线、检测限、加标回收率试验等方面进行了验证。结果为试剂盒校正曲线的线性相关系数为0.9913;样品的定性检出限为0.087ng/mL,定量检出限为0.29ng/mL;添加1.1ng/mL、2.2ng/mL、4.4ng/mL、6.6ng/mL和11.0ng/mL的莱克多巴胺标准液时,变异系数分别为3.06%、8.55%、4.41%、9.92%、8.19%;平均回收率分别为93%、113%、103%、96%、91%。结果表明,应用ELISA方法检测猪尿中莱克多巴胺残留量符合要求,适合检测猪尿中莱克多巴胺残留量的初筛。  相似文献   

5.
以莱克多巴胺单克隆抗体间接竞争酶联免疫吸附(ELISA)法测定猪肉和猪尿中莱克多巴胺残留。该法对莱克多巴胺的检测限为0.8ng/mL(g),在空白组织中的添加回收率为80.4%~109.5%,变异系数为5.8%~12.6%。  相似文献   

6.
本文通过对氟苯尼考等常用兽药对莱克多巴胺ELISA残留筛选检测的影响研究实验。结果表明,这些药物在5ng/ml(或10ng/ml)作为我国动植物检验检疫判定标准下,对莱克多巴胺ELISA检测无影响。  相似文献   

7.
本文对用ELISA法检测畜禽尿液中盐酸克伦特罗含量的不确定度分析,讨论了影响样品检测结果各分量的不确定度并量化,求出其对检测结果不确定度的相对贡献,得出样品的合成标准不确定度和扩展不确定度分别为为u(x)=43.1 ng/kg、U(p=95%)=2×u(x)=86.2 ng/kg,对检测结果进行了表述:(717.7±86.2)ng/kg,如实反映了检测的置信度和准确度。  相似文献   

8.
酶联免疫吸附试验(ELISA)检测猪尿中β-受体激动剂类药物(俗称"瘦肉精")时有假阳性出现。为摸清干扰因素,获得准确的检测结果,提高工作效率,选取生猪饲养中常用的替米考星预混剂(100g/kg)、复方磺胺氯哒嗪钠粉、氟苯尼考粉(100g/kg)、蛋氨酸铬、ZnSO4·H2O等3种兽药和2种饲料添加剂饲喂体重50kg~60kg的健康生长育肥猪。3d后采集尿样分别进行克伦特罗、莱克多巴胺、沙丁胺醇检测。发现上述3种兽药对克伦特罗、莱克多巴胺检测无假阳性结果出现;对检测沙丁胺醇有不同程度的假阳性结果出现。上述2种饲料添加剂对检测克伦特罗、莱克多巴胺、沙丁胺醇均无假阳性结果出现。  相似文献   

9.
利用液质联用检测方法测定饲料中莱克多巴胺,试验采用乙腈提取试样中的莱克多巴胺,用OasisMCX小柱净化,4mmol/l乙酸胺溶液:乙腈(80:20)为流动相,用PDA检测器分离测定。试验结果莱克多巴胺的检测限为1.37μg/kg,平均回收率为84.4%,最后用质谱进行确证。该方法简单,结果准确,可用于测定饲料中莱克多巴胺的含量。  相似文献   

10.
为分析不确定度的来源并对其量化,从而提高检测结果的准确性,对酶联免疫吸附(ELISA)法检测家禽活疫苗中禽白血病病毒污染的测量不确定度进行评估。用禽白血病病毒ELISA检测试剂盒,对4批家禽活疫苗进行禽白血病病毒检测,依据《兽医检测实验室ELISA试验测量不确定度评估指南》(CNAS-GL043),分析试验的不确定度来源,并评定各分量的标准不确定度、合成标准不确定度和扩展不确定度。结果显示,每批家禽活疫苗连续3代细胞培养物的禽白血病病毒OD_(650nm)值不确定度范围的上限值均小于0.300,判定为阴性,即所检测4批活疫苗中没有禽白血病病毒污染。ELISA法检测中引入不确定度概念,不仅可以提高检测结果的准确性和可靠性,而且还可以分析不确定度各分量对测量结果的相对贡献,找出影响检测质量的主要因素,从而有利于实验室质量控制和检测质量的提高。  相似文献   

11.
评定气相色谱法测定乳粉中1-油酸-2-棕榈酸-3-亚油酸甘油三酯(1-oleic-2-palmitic-3-linoleic acid triglyceride,OPL)含量的不确定度。根据JJF 1059.1—2012《测量不确定度评定与表示》和CNAS-GL 006:2019《化学分析中不确定度的评估指南》等标准,建立不确定度模型,分析气相色谱法测定乳粉中OPL的不确定度来源,对主要影响不确定度的要素进行评定。结果表明:6?份试样OPL测量结果的平均值为1.172?g/100?g,OPL含量测量结果的相对扩展不确定度urel为0.023 6,提供约95%的包含概率;试样溶解并定容后的溶液质量浓度引入的标准不确定度是主要不确定度来源。  相似文献   

12.
为提高检验结果的准确性,确定检验过程中的关键影响因素,对气相色谱法测定多西环素中乙醇的含量进行不确定度评估。依据《中国兽药典》2020版多西环素质量标准对其乙醇含量进行测定,分析影响不确定度的因素,参照JJF 1135-2005《化学分析测量不确定度评定》和JJF 1059.1-2012《测量不确定度评定与表示》中的规定及要求,对检验过程中的不确定因素进行评估,根据CNAS-GL006:2019构建了乙醇含量的不确定度评估数学模型,对检测过程中各种不确定度的来源进行分析,并计算合成相对标准不确定度和扩展不确定度。多西环素中乙醇含量的不确定度结果表示为(5±0.06)%,(k=2,置信区间为95%)。多西环素中乙醇含量的不确定度主要来源于供试品溶液的配制。  相似文献   

13.
为提高检验结果的准确性,确定检验过程中的关键影响因素,对液相色谱法测定氟尼辛葡甲胺注射液含量进行不确定度评估。依据《中国兽药典》2020 版氟尼辛葡甲胺注射液质量标准对其含量进行测定,分析影响不确定度的因素,参照 JJF 1135 - 2005《化学分析测量不确定度评定》和JJF 1059.1-2012《测量不确定度评定与表示》中的规定及要求,对检验过程中的不确定因素进行评估,根据CNAS-GL006:2019 构建了氟尼辛含量的不确定度评估数学模型,对检测过程中各种不确定度的来源进行分析,并计算合成相对标准不确定度和扩展不确定度?氟尼辛葡甲胺注射液含量的不确定度结果表示为(102.2 ± 2.72)% ,(k = 2,置信区间为 95% ),主要来源于仪器重复性?  相似文献   

14.
建立了高效液相色谱-串联质谱(HPLC-MS/MS)同时检测猪毛发中克仑特罗和莱克多巴胺残留的方法。猪毛发经1 mol/L氢氧化钠溶液水解、乙酸乙酯萃取、MCX固相萃取柱净化,流动相溶解后用HPLC-MS/MS进行检测。克仑特罗在1.9~463.2 ng/mL浓度范围内线性关系良好(R2=0.999 0);回收率为83.3%~86.6%,相对标准偏差为6.7%~9.2%;检出限为0.3μg/kg,定量限为0.8μg/kg。莱克多巴胺在2.8~562.9 ng/mL浓度范围内线性关系良好(R2=0.999 2);回收率为83.4%~88.4%,相对标准偏差为7.2%~9.6%;检出限为0.4μg/kg,定量限为1.2μg/kg。应用该方法研究了克仑特罗、莱克多巴胺在猪毛发中的代谢规律并进行了猪毛发样品检测。结果喂药7 d至停药21 d猪毛发中均检出克仑特罗、莱克多巴胺残留;检测猪毛发样品25份,1份样品检出克仑特罗,残留量为58.68μg/kg。  相似文献   

15.
依据JJF 1059-1999《测量不确定度评定与表示》的原理与方法,建立高效液相色谱法测定乳制品中纳他霉素结果不确定度评定的数学模型.对整个测量过程的不确定度来源进行分析,并对不确定度各个分量进行评估和合成,得出合成标准不确定度为0.014,扩展不确定度为0.28mg/kg,乳制品中纳他霉素测定结果的置信区间为(9.95±028)mg/kg,k=2.  相似文献   

16.
A total of 54 finishing barrows (initial BW = 99.8 ± 5.1 kg; PIC C22 × 337) reared in individual pens were allotted to 1 of 6 dietary treatments in a 2 × 3 factorial arrangement of treatments with 2 levels of ractopamine (0 and 7.4 mg/kg) and 3 levels of dietary energy (high, 3,537; medium, 3,369; and low, 3,317 kcal of ME/kg) to determine the effects of dietary ractopamine and various energy levels on growth performance, carcass characteristics, and meat quality of finishing pigs. High-energy diets were corn-soybean-meal-based with 4% added fat; medium-energy diets were corn-soybean meal based with 0.5% added fat; and low-energy diets were corn-soybean meal based with 0.5% added fat and 15% wheat middlings. Diets within each ractopamine level were formulated to contain the same standardized ileal digestible Lys:ME (0 mg/kg, 1.82; and 7.4 mg/kg, 2.65 g/Mcal of ME). Individual pig BW and feed disappearance were recorded at the beginning and conclusion (d 21) of the study. On d 21, pigs were slaughtered for determination of carcass characteristics and meat quality. No ractopamine × energy level interactions (P > 0.10) were observed for any response criteria. Final BW (125.2 vs. 121.1 kg), ADG (1.2 vs. 1.0 kg/d), and G:F (0.31 vs. 0.40) were improved (P < 0.001) with feeding of ractopamine diets. Feeding of the low-energy diet reduced (P = 0.001) final BW and ADG compared with the high- and medium-energy diets. Gain:feed was reduced (P = 0.005) when the medium-energy diets were fed compared with the high-energy diets. Additionally, G:F was reduced (P = 0.002) when the low-energy diets were compared with the high- and medium-energy diets. Feeding ractopamine diets increased (P < 0.05) HCW (93.6 vs. 89.9 kg) and LM area (51.2 vs. 44.2 cm(2)). The LM pH decline was reduced (P ≤ 0.05) by feeding ractopamine diets. The feeding of low-energy diets reduced (P = 0.001) HCW when compared with the high- and medium-energy diets and reduced (P = 0.024) 10th-rib backfat when compared with the high- and medium-energy diet. These data indicate that feeding ractopamine diets improved growth performance and carcass characteristics, while having little or no detrimental effect on meat quality. Reductions in energy content of the diet by adding 15% wheat middlings resulted in impaired ADG, G:F, and 10th-rib backfat. There were no ractopamine × energy level interactions in this trial, which indicates that the improvements resulting from feeding ractopamine were present regardless of the dietary energy levels.  相似文献   

17.
高效液相色谱法测定牛奶中四环素残留量的不确定度评定   总被引:1,自引:1,他引:0  
建立了高效液相色谱法测定牛奶中四环素残留量的不确定度评定的数学模型.通过对测量过程中的不确定度来源进行分析与评定,当残留量为85.3 μg/kg时,求得扩展不确定度为5.0μg/kg(k=2).结果表明,标准溶液配制、重复性测量、定容体积和回收率引入的不确定度为测量结果不确定度的主要影响因素.  相似文献   

18.
The objective of this research was to use recent ractopamine research data to develop an updated mathematical model to describe the daily compositional growth of pigs fed ractopamine. Mean increases of 18.2, 23.1, and 25.0% for daily protein accretion were assumed for 5, 10, and 20 ppm of ractopamine for an overall gain of 40 kg of BW gain during the feeding period. The relative effect of ractopamine described the rapid increase and subsequent decrease in the effect of ractopamine as a function of BW gain or days on test and ractopamine concentration (RC, ppm). The reduction in ME intake produced by ractopamine was described as 0.036 x (RC/20)(0.7) multiplied by the ME intake for the first 20 kg of BW gain, and then increasing to 0.078 x (RC/20)(0.7) at 40 kg of BW gain feeding period. The ratio of fat-free muscle gain to protein accretion increased by 14 to 16% with the feeding of ractopamine, depending on the dietary lysine/essential AA levels. The ratio of carcass fat gain to empty body lipid gain was increased when lysine and essential AA requirements were met. Daily protein accretion and fat-free lean growth were described as functions of dietary lysine/essential AA intakes. The percentage of lysine in protein accretion increased with the feeding of ractopamine from 6.80 to 7.15%, depending on ractopamine concentration. Equations predicting carcass measurements, such as fat and longissimus muscle depths from carcass weight and composition, were modified to incorporate prediction biases produced by ractopamine. For the four concentrations of ractopamine (0, 5, 10, and 20 ppm, respectively) during a 78 to 110 kg of BW feeding period, the model predicted performance levels for ADG (1.03, 1.15, 1.16, and 1.16 kg/d), gain:feed (kg of ADG/kg of ADFI; 0.360, 0.401, 0.412, and 0.425), dressing percentage (75.1, 76.0, 76.3, and 76.4), percentage fat-free lean (48.7, 51.0, 51.5, and 52.2), longissimus muscle area (38.8,41.8,42.5, and 43.5 cm2), 10th-rib fat depth (22.1, 19.8, 19.3, and 18.7 mm), and fat-free lean gain (321, 446, 467, and 495 g/d), comparable to recent research data. The model allows the effect of ractopamine to be added to farm specific pig growth curves. It can be used to evaluate ways to optimize the use of ractopamine, including duration of ractopamine feeding, concentration of ractopamine, and dietary lysine concentration.  相似文献   

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