4.4 Article

Quantitative detection of mixed pesticide residue of lettuce leaves based on hyperspectral technique

期刊

出版社

WILEY
DOI: 10.1111/jfpe.12654

关键词

-

资金

  1. National Natural Science [31471413]
  2. Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
  3. Six Talent Peaks Project in Jiangsu Province [ZBZZ-019]

向作者/读者索取更多资源

To explore the best method for non-destructively and accurately quantitative detection of mixed pesticide residue in vegetables, the mixed pesticide (fenvalerate and dimethoate) of lettuce leaves was used as the research object detected by hyperspectral technique. The hyperspectral data was preprocessed using standard normalized variable. Then two different kinds of characteristic wavelengths were selected using competitive adaptive reweighed sampling (CARS) and random forest-recursive feature elimination (RF-RFE), respectively. The least squares support vector regression (LSSVR) model results of predicting fenvalerate and dimethoate showed that the CARS-screened wavelengths had the best modeling results for fenvalerate with RP2 of 0.8203 and RMSEP of 0.0222, and the RF-RFE-screened wavelengths had the best results for dimethoate with RP2 of 0.8712 and RMSEP of 0.0186. To simplify the calibration model, successive projections algorithm (SPA) was used for the second selection of characteristic wavelengths. Finally, the CARS-SPA-LSSVR model for predicting fenvalerate achieved the accuracy with RP2 of 0.8890 and RMSEP of 0.0182, RF-RFE-SPA-LSSVR model for predicting dimethoate with RP2 of 0.9386 and RMSEP of 0.0077. Thus, hyperspectral technique can be applied to quantitatively detect the mixed pesticide residue of lettuce leaves. Practical applicationsLettuce leaves can be used for raw food, and lettuce leaves with mixed pesticide residues is more likely to bring harm to people's health. Traditional methods of detecting pesticide residues are time-consuming and destructive to samples, so they cannot meet the requirement of modern agriculture. Whereas, hyperspectral imaging technology is a new rapidly growing method which integrates spectroscopic and imaging techniques in one system for providing both spectral and spatial information simultaneously, of which the spectral information can detect the physical structure and chemical composition of unknown samples. Therefore, the hyperspectral technique is a fast and nondestructive detecting method, and this study showed it is feasible for quantitative detection of the mixed pesticide residue of lettuce leaves.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据