近红外光谱结合膜富集技术测定大米中毒死蜱农药残留

发布时间：2018-08-20 15:52

【摘要】：本文以纤维滤膜富集大米中的微量农药残留,提高近红外光谱技术的检测限。向阴性大米样本中喷洒不同浓度毒死蜱标准溶液,制备含农药残留大米样品,以乙腈为溶剂提取大米中的毒死蜱农药,用氮吹仪将提取液浓缩后,使用滤纸富集提取液中的农药,真空冷冻干燥,采集滤纸的近红外漫反射光谱。运用特征波长筛选方法优选特征变量,建立大米中毒死蜱农药残留的近红外光谱分析模型。结果表明,利用联合区间偏最小二乘法方法从全光谱区优选出子区间[3 4 5 10],进一步用遗传算法从子区间中优选80个变量时,所建模型性能最好。在0.46~11.20 mg/kg浓度范围内,模型对预测集样本的相关系数为0.9798,预测均方根误差为0.604 mg/kg,将该模型预测4个未知农药含量的大米样本,其预测值与实际测量值具有较好的一致性。研究表明该方法能较好地快速检测大米中微量农药残留。
[Abstract]:In this paper, the fiber filter membrane was used to enrich the trace pesticide residues in rice, and the detection limit of near infrared spectroscopy was improved. Chlorpyrifos was sprayed into negative rice samples with different concentrations of chlorpyrifos standard solution to prepare rice samples containing pesticide residues. Chlorpyrifos pesticide was extracted from rice with acetonitrile as solvent. Filter paper was used to enrich pesticide in the extract, and vacuum freeze-drying was used to collect the near infrared diffuse reflectance spectra of filter paper. The near infrared spectrum analysis model of chlorpyrifos pesticide residues in rice poisoning was established by using characteristic wavelength screening method to select characteristic variables. The results show that the proposed model has the best performance when the joint interval partial least square method is used to select the subinterval from the full spectral region [34510] and the genetic algorithm is used to select 80 variables from the subinterval. In the concentration range of 0.46 ~ 11.20 mg/kg, the correlation coefficient and root mean square error between the model and the predicted sample are 0.979 8 and 0.604 mg / kg, respectively. The predicted values of the model are in good agreement with the actual measured values. The results show that this method can be used for the rapid determination of trace pesticide residues in rice.
【作者单位】：江西省农业科学院农产品质量安全与标准研究所;江西出入境检验检疫局技术中心;国家食品安全风险评估中心;江西农业大学工学院;
【基金】：“十二五”国家科技支撑计划项目(2012BAK17B02)资助
【分类号】：TS210.7;O657.33

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