基于拉曼光谱的苹果中农药残留种类识别及浓度预测的研究

应用拉曼光谱技术结合化学计量学方法能有效的实现果蔬中农药残留的定性定量分析。本研究借助实验室自主研发的拉曼光谱检测系统,对苹果中溴氰菊酯和啶虫脒的快速无损识别和检测进行了探索。定性分析时将拉曼峰574和843cm-1分别作为识别溴氰菊酯和啶虫脒的拉曼指纹,当苹果中的溴氰菊酯和啶虫脒残留的含量分别为0.78和0.15mg·kg-1时,两种农药的特征峰仍清晰可见。定量分析首先对光谱进行多种预处理(Savitzky-Golay平滑、一阶导、二阶导、基线校准、标准正态变量变换),结合偏最小二乘法分别建立苹果中溴氰菊酯和啶虫脒含量的定量模型。结果表明,采用8次多项式拟合进行基线校准的预处理方法效果最好,对于溴氰菊酯,偏最小二乘模型预测值与气相色谱法测定值的相关系数和预测均方根误差分别为0.94和0.55mg·kg-1,对于啶虫脒,其偏最小二乘模型的相关系数与预测均方根误差分别为0.85和0.12mg·kg-1。本研究证实了利用拉曼技术对苹果农残进行无损检测的可行性,使用该方法进行检测时,在光谱测定前不需要进行前处理,光谱测定后样品无任何损伤,该技术实现了果蔬农残的现场检测,可在检测部门、果蔬加工企业、超市、市场等场所得到推广使用,为果蔬品质安全提供了一种无损、快速和环保的检测方法。     

以光散射技术研究啶虫脒的测定及其与DNA的相互作用

研究了啶虫脒与脱氧核糖核酸(DNA)之间的共振光散射(RLS)增强作用。加入啶虫脒导致DNA的共振光散射增强,在316.0 nm处,存在一处共振光散射增强峰。由此建立了一种以DNA为探针检测农药啶虫脒的新方法。体系的最佳条件为,实验选择了pH 1.73为适宜酸度;加入10μg.mL-1浓度的DNA溶液的体积为2 mL;在室温条件下,体系的反应需要30 min达到稳定;"啶虫脒-DNA-H2SO4"的加药顺序为最佳。该方法适用的线性范围为0~2.25μg.mL-1,检出限为0.2μg.mL-1,啶虫脒在河水样品中的回收率为98.0%~102.0%,并探讨了DNA与啶虫脒的相互作用机理:啶虫脒与核酸间的相互作用包含有静电引力,啶虫脒的吡啶基与DNA碱基之间的π—π堆积作用。     

Ozone initiated oxidation of long chained n -alkanes in the presence of activated charcoal or silica gel

Photolysis behavior of acetamiprid in different kinds of surfactant solutions were investigated. The results showed that acetamiprid was prone to photolysis when exposed to the irradiation of a mercury lamp, and the photolysis kinetics fit in well with the first-order kinetic equation. Surfactants did not participate in the acetamiprid’s photolysis process directly, whereas they all had obvious inhibiting effects on it.     

Determination of Fipronil in Acetamiprid Formulation by Attenuated Total Reflectance-Mid-Infrared Spectroscopy Combined with Partial Least Squares Regression

There is a high demand for rapid determination of fipronil in pesticide preparations because it has been restricted and even prohibited in many countries. An infrared-based methodology was developed for this analyte in acetamiprid formulations by attenuated total reflectance mid-infrared spectroscopy. The quantitative calibration models of fipronil were established by partial least squares regression. The determination coefficients (R²) of the model were above 0.99 while both the root mean square error of prediction and root mean square error of calibration were below 0.0011, which showed the partial least squares model accurately predicted fipronil concentrations in acetamiprid. The accuracy was further demonstrated by comparison with another two models' results of low (<1.0%, w/w) and high concentration sample sets (1.0%–4.5%, w/w). These results demonstrate the potential of infrared spectroscopy to quickly detect fipronil in acetamiprid.     

Highly Sensitive Silver Nanorod Arrays for Rapid Surface Enhanced Raman Scattering Detection of Acetamiprid Pesticides

The determination of pesticide residue on agricultural products is increasingly important.Exposure to pesticides can cause severe acute reactions in humans, including aplastic anemia and leukemia.In this work, we developed a rapid and sensitive method to detect acetamiprid pesticide residue based on surface-enhanced Raman scattering.Silver nanorod (AgNR) arrays were fabricated by oblique angle deposition technology and were used as SERS substrates.Prior to detection, the AgNR arrays were cleaned with nitric acid solution or a mixture of methanol and acetone.Compared to the unwashed AgNR arrays, the AgNR arrays washed with methanol and acetone shows a signal enhancement 1000 times greater than the unwashed AgNR array due to the effective removal of the impurities on its surface.The limit of detection of acetamiprid was determined to be 0.05 mg/L.In addition, the molecular structure of acetamiprid was simulated and the corresponding vibration modes of the characteristic bands of acetamiprid were calculated by density function theory.To demonstrate its practical application, the AgNRs array substrates were applied successfully to the rapid identification of acetamiprid residue on a cucumber's surface.These results confirmed possibility of utilizing the AgNRs SERS substrates as a new method for highly sensitive pesticide residue detection.     

Immunoassay for acetamiprid detection: application to residue analysis and comparison with liquid chromatography

This work describes the fundamental ability of a commercial ELISA to determine acetamiprid and the application of the ELISA to residue analysis in fruit and vegetable samples. The ELISA exhibited satisfactory sensitivity (I ₅₀ 0.6 ng/g; limit of detection 0.053 ng/g) and a high selectivity for acetamiprid versus other neonicotinoid analogs (thiacloprid amide). Methanol, which influenced the sensitivity of the ELISA the least, was selected as the extractant for the ELISA analysis. Simple dilution of sample extracts with water eliminated matrix interferences. Average recoveries from the acetamiprid-spiked agricultural samples were >95% using a simple extraction method. Analytical results obtained from the ELISA were comparable to those obtained from the reference HPLC method (r>0.99). The ELISA applied to the residue analysis of acetamiprid in agricultural products is a rapid, simple, and cost-effective method, and could be successfully applied to the detection of acetamiprid before the distribution of produce.     

Visual and fluorescent detection of acetamiprid based on the inner filter effect of gold nanoparticles on ratiometric fluorescence quantum dots

In this work, we develop a simple and rapid sensing method for the visual and fluorescent detection of acetamiprid (AC) based on the inner-filter effect (IFE) of gold nanoparticles (AuNPs) on ratiometric fluorescent quantum dots (RF-QDs). The RF-QDs based dual-emission nanosensor was fabricated by assembling green emissive QDs (QDs_539 nm, λ_em = 539 nm) on the surface of red emissive QDs (QDs_661 nm, λ_em = 661 nm)-doped silica microspheres. The photoluminescence (PL) intensity of RF-QDs could be quenched by AuNPs based on IFE. Acetamiprid can adsorb on the surface of AuNPs due to its cyano group that has good affinity with gold, which could induce the aggregation of AuNPs accompanying color change from red to blue. Thus, the IFE of AuNPs on RF-QDs was weakened and the PL intensity of RF-QDs was recovered accordingly. Under the optimized conditions, the PL intensity of the RF-QDs/AuNPs system was proportional to the concentration of AC in the range of 0.025–5.0 μg mL⁻¹, with a detection limit of 16.8 μg L⁻¹. The established method had been used for AC detection in environmental and agricultural samples with satisfactory results.     

高灵敏银纳米棒阵列对农药啶虫脒的表面增强拉曼散射快速检测

The determination of pesticide residue on agricultural products is increasingly important.Exposure to pesticides can cause severe acute reactions in humans,including aplastic anemia and leukemia.In this work,we developed a rapid and sensitive method to detect acetamiprid pesticide residue based on surface-enhanced Raman scattering.Silver nanorod (AgNR) arrays were fabricated by oblique angle deposition technology and were used as SERS substrates.Prior to detection,the AgNR arrays were cleaned with nitric acid solution or a mixture of methanol and acetone.Compared to the unwashed AgNR arrays,the AgNR arrays washed with methanol and acetone shows a signal enhancement 1000 times greater than the unwashed AgNR array due to the effective removal of the impurities on its surface.The limit of detection of acetamiprid was determined to be 0.05 mg/L.In addition,the molecular structure of acetamiprid was simulated and the corresponding vibration modes of the characteristic bands of acetamiprid were calculated by density function theory.To demonstrate its practical application,the AgNRs array substrates were applied successfully to the rapid identification of acetamiprid residue on a cucumber''s surface.These results confirmed possibility of utilizing the AgNRs SERS substrates as a new method for highly sensitive pesticide residue detection.     

HPLC法同时测定苹果及浓缩苹果汁中吡虫清等4种农药的残留量

建立了反相高效液相色谱-双波长检测法同时测定苹果及浓缩苹果汁中多菌灵、噻菌灵、吡虫啉、吡虫清4种农药残留量的方法。苹果样品经乙腈提取,加水稀释,而浓缩苹果汁样品直接用体积分数20%乙腈稀释后,利用CH2Cl2液-液萃取净化。分析时用C18色谱柱分离,以乙腈-0.05%冰乙酸系统梯度洗脱,选择246 nm和280 nm双波长检测。该方法4种农药的线性关系良好(r≥0.9999),检出限均为0.002 mg/kg,加标回收率在84.3%~109.1%范围内,相对标准偏差为2.0%~5.4%。本方法能够满足农药残留检测要求。     

Sensitive determination of thiamethoxam, imidacloprid and acetamiprid in environmental water samples with solid-phase extraction packed with multiwalled carbon nanotubes prior to high-performance liquid chromatography

This paper describes a novel method for sensitive determination of thiamethoxam, imidacloprid and acetamiprid based on solid-phase extraction with multiwalled carbon nanotubes as the packed materials. Factors that maybe influence the enrichment efficiency, such as sample flow rate, sample pH, and sample volume, were investigated in detail. Under the optimized conditions, the detection limits of thiamethoxam, imidacloprid and acetamiprid were 6.1, 5.4 and 6.7 ng L⁻¹, respectively. The experimental results indicated that there was good linearity (R ²>0.9993) over the range of 0.08~100 ng mL⁻¹ and good reproducibility with the relative standard deviations over the range of 0.7~1.1% (n=6). The proposed method has been applied to the analysis of real-world water samples, and satisfactory achievements were obtained. The average spiked recoveries were in the range of 87.5~109.8%. All the results indicated that the proposed method could be used for the simultaneous determination of the three pesticides in environmental water samples at trace levels.