[1]李文.基质对光谱法快速检测蔬菜中残留乙酰甲胺磷的影响[J].江苏农业学报,2018,(05):1169-1173.[doi:doi:10.3969/j.issn.1000-4440.2018.05.028]
 LI Wen.Influence of matrix on rapid detection of acephate residue in vegetables by spectral technology[J].,2018,(05):1169-1173.[doi:doi:10.3969/j.issn.1000-4440.2018.05.028]
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基质对光谱法快速检测蔬菜中残留乙酰甲胺磷的影响()
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江苏农业学报[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2018年05期
页码:
1169-1173
栏目:
加工贮藏·质量安全
出版日期:
2018-10-25

文章信息/Info

Title:
Influence of matrix on rapid detection of acephate residue in vegetables by spectral technology
作者:
李文
(北京工商大学计算机与信息工程学院食品安全大数据技术北京市重点实验室,北京100048)
Author(s):
LI Wen
(Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer Science and Information Engineering, Beijing Technology and Business University, Beijing 100048, China)
关键词:
基质差示分光光度法比色光谱农药残留
Keywords:
matrixdifferential spectrophotometrycolorimetric spectroscopypesticide residues
分类号:
X836
DOI:
doi:10.3969/j.issn.1000-4440.2018.05.028
文献标志码:
A
摘要:
为避免蔬菜残留农药理化检测中耗时长、污染环境等不足,研究了蔬菜基质对光谱检测乙酰甲胺磷的影响,建立了一种直接检测蔬菜中残留农药的方法。选用白菜、芹菜提取液和去离子水分别配制3组农药样品,与乙酸氯化钯溶液进行比色反应,对比分析 300~900 nm波段的吸收光谱和建立的偏最小二乘回归(PLSR)模型。结果表明,两种基质均可改变农药样品的特征波长,降低样品吸光值的区分度,使PLSR模型预测精度明显降低。改用差示分光光度法后, 加入白菜、芹菜两种基质后的PLSR模型验证集的决定系数从0.90、0.92均提高到0.95,均方根误差分别从10.64和9.89下降到7.64和6.98。说明采用差示分光光度法与PLSR模型相结合,可建立简单易行的蔬菜残留农药快速定量检测方法。
Abstract:
To avoid the problems such as long time and polluting environment caused by physicochemical technology, effect of vegetable matrixes on the spectral detection of acephate was studied, and a method for direct detection of pesticide residues in vegetables was established. Three groups of acephate samples prepared by extract of cabbage, celery and deionized water were reacted with PdCl2 dissolved in acetic acid. The absorption spectrum in 300-900 nm waveband and established partial least squares regression (PLSR) models were analyzed. The results showed that the two kinds of matrixes could decrease significantly the prediction accuracy of PLSR models by changing the characteristic wavelength and decreasing the discrimination of absorption. PLSR models were improved by differential spectrophotometry, the determination coefficient of validation set of cabbage and celery matrixes was increased from 0.90 and 0.92 to 0.95, the root mean square error was decreased from 10.64 and 9.89 to 7.64 and 6.98 respectively. Differential spectrophotometry combined with PLSR models provides a simple and feasible method for the rapid detection of pesticide residues in vegetables.

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备注/Memo

备注/Memo:
收稿日期:2017-12-25 基金项目:国家自然科学基金项目(31271619);河北省科技计划项目(16272916) 作者简介:李文(1971-),女,山东德州人,博士,副教授,研究方向为光谱技术检测农产品安全。(E-mail)wen_li2011@163.com
更新日期/Last Update: 2018-11-05