Fast visualization of distribution of chromium in rice leaves by re-heating dual-pulse laser-induced breakdown spectroscopy and chemometric methods. (September 2019)

• Record Type: Journal Article
• Authors: Peng, Jiyu; He, Yong; Zhao, Zhangfeng; Jiang, Jiandong; Zhou, Fei; Liu, Fei; Shen, Tingting
• Is Part Of: Environmental pollution. Volume 252(2019):Part B
• Page Start: 1125
• Page End: 1132
• Publication Date: 2019-09
• Subjects: Rice -- Toxic metal pollution -- Visualization -- Dual-pulse laser-induced breakdown spectroscopy -- Chemometric method; Pollution -- Periodicals; Pollution -- Environmental aspects -- Periodicals; Environmental Pollution -- Periodicals; Pollution -- Périodiques; Pollution -- Aspect de l'environnement -- Périodiques; Pollution -- Effets physiologiques -- Périodiques; Pollution; Pollution -- Environmental aspects; Periodicals; Electronic journals; 363.73
• DOI: 10.1016/j.envpol.2019.06.027
• Languages: English
• ISSNs: 0269-7491

Abstract

Abstract: Knowledge of distribution of toxic metal in crop is essential for studying toxic metal uptake, transportation and bioaccumulation, and it is important for environmental pollution monitoring. In this study, the macro spatial distribution of chromium in rice leaves was visualized by re-heating dual-pulse laser-induced breakdown spectroscopy (DPLIBS) and chemometric methods. After the optimization of two important parameters (delay time and energy ratio) in DPLIBS, chromium prediction model was established based on global spectra. The global model achieved acceptable performance while slight overfitting for model was found because of numerous irrelevant variables. Feature variables including emissions from chromium and other elements were successfully selected by the values of regression coefficient in partial least square regression model. Best performance was achieved by using the feature variables and support vector machine, with correlation coefficient of prediction of 0.959, root mean square error of prediction of 13.4 mg/kg and residual predictive deviation of 3.6. Finally, the distribution of chromium in rice leaves was visualized with the best prediction model. The distribution image showed that chromium distributed approximately symmetrically along the vein and was likely to be accumulated in leaf apex. The preliminary results provide an approach for investigating the macro spatial distribution of elements in crops, which is important for environmental protection and food safety. Graphical abstract: Image 1 Highlights: Inter-pulse delay time and energy ratio in DPLIBS were investigated and optimized. Feature variables were selected by regression coefficients in PLS model. Support vector machine model based on feature variables performed best. Macro spatial distribution of chromium in rice leaves was successfully visualized. Chromium distributed symmetrical along vein and was concentrated in leaf apex. Abstract : Re-heating DPLIBS combined with chemometric methods was successfully used to visualize the macro spatial distribution of chromium in rice leaves.