Chemometrics-assisted calibration transfer strategy for determination of three agrochemicals in environmental samples: Solving signal variation and maintaining second-order advantage

化学计量学 校准 生物系统 计算机科学 基质(化学分析) 信号(编程语言) 电子舌 数学 化学 统计 机器学习 色谱法 食品科学 品味 生物 程序设计语言
作者
Xiao-Dong Sun,Hai‐Long Wu,Yue Chen,Junchen Chen,Ru‐Qin Yu
出处
期刊:Chemometrics and Intelligent Laboratory Systems [Elsevier BV]
卷期号:194: 103869-103869 被引量:8
标识
DOI:10.1016/j.chemolab.2019.103869
摘要

This manuscript proposes a chemometrics-assisted calibration transfer strategy to determine three agrochemicals (indole-3-acetic acid, 1-naphthylacetic acid and thiabendazole) in environmental samples by excitation-emission matrix (EEM) fluorescence detection. The fluorescence landscapes of target compounds are heavily overlapped with each other and also with the extracts of real samples, making it impractical to be quantified by conventional spectroscopy methods. The second-order calibration methods based on “mathematical separation” are carried out to handle these headaches as its potential capacity to get successful resolution and quantification even in the presence of overlapped peaks and unknown interferences, known as the famous “second-order advantage”. Piecewise direct standardization (PDS) method, one calibration transfer strategy, is applied for updating chemometric multivariate calibration model to compensate for the signal instability and variation in responses recorded on different instruments, which avoids overhead of a full recalibration usually involves considerable effort, cost, and time. Both root-mean-square error of prediction (RMSEP) and average recoveries calculated from simulated and experimental data are analyzed to validate the feasibility and applicability of this strategy. Result reveals that the number of calibration standard used was reduced from 10 to 3 for later determinations while producing comparable analytical results in terms of RMSEPs and recovery values to those obtained by a full recalibration strategy. The developed strategy takes advantage of less experimental effort and cost, which can be an alternative one for fast screening of agrochemicals and long-term process analysis in environmental samples or related food matrices.
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