scholarly journals Fast Detection of Copper Content in Rice by Laser-Induced Breakdown Spectroscopy with Uni- and Multivariate Analysis

Sensors ◽  
2018 ◽  
Vol 18 (3) ◽  
pp. 705 ◽  
Author(s):  
Fei Liu ◽  
Lanhan Ye ◽  
Jiyu Peng ◽  
Kunlin Song ◽  
Tingting Shen ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Copper Content ◽  
Laser Induced Breakdown Spectroscopy ◽  
Fast Detection ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown

Fast Determination of Copper Content in Tobacco (Nicotina tabacum L.) Leaves Using Laser-Induced Breakdown Spectroscopy with Univariate and Multivariate Analysis

2018 ◽  
Vol 61 (3) ◽  
pp. 821-829 ◽  
Author(s):  
Jiyu Peng ◽  
Lanhan Ye ◽  
Tingting Shen ◽  
Fei Liu ◽  
Kunlin Song ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Multivariate Analysis ◽  
Copper Content ◽  
Laser Induced Breakdown Spectroscopy ◽  
Fast Determination ◽  
Tobacco Leaves ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
Determination Of Copper

Abstract. Fast and effective measures to determine heavy metals play an important role in ensuring food quality and safety. In this experiment, laser-induced breakdown spectroscopy (LIBS) was used to detect copper content (Cu) in tobacco ( L.) leaves. The experimental parameters for detection, including laser energy, delay time, and camera gate width, were optimized by response surface methodology (RSM). Univariate analysis and multivariate analysis, including partial least squares regression (PLSR) and extreme learning machine (ELM), were used to establish calibration models. In addition, different preprocessing methods were used to eliminate the signal variations and further improve the calibration performance, including baseline correction, background normalization, area normalization, and standard normal variate (SNV) normalization. The results showed that LIBS combined with both univariate and multivariate methods could be used to detect copper content in tobacco leaves. SNV and area normalization were efficient in dealing with signal variations and improving the calibration performance. The ELM model with SNV normalized variables in the spectral region of 324.02 to 325.98 nm achieved the best performance (R2 = 0.9552 and RMSE = 4.8416 mg kg-1 in the testing set). The results provide the first proof-of-principle data for fast determination of copper content in tobacco leaves. Keywords: Copper content, Laser-induced breakdown spectroscopy, Multivariate calibration, Response surface methodology, Tobacco leaves, Univariate calibration.

scholarly journals Quantification of copper content with laser induced breakdown spectroscopy as a potential indicator of offal adulteration in beef

Talanta ◽  
2017 ◽  
Vol 169 ◽  
pp. 123-129 ◽  
Author(s):  
Maria P. Casado-Gavalda ◽  
Yash Dixit ◽  
David Geulen ◽  
Raquel Cama-Moncunill ◽  
Xavier Cama-Moncunill ◽  
...  
Keyword(s):  
Copper Content ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Potential Indicator ◽  
Laser Induced Breakdown

Multivariate Analysis of Laser-Induced Breakdown Spectroscopy Spectra of Soil Samples

Soil Science ◽  
2010 ◽  
Vol 175 (9) ◽  
pp. 447-452 ◽  
Author(s):  
Ningfang Yang ◽  
Neal S. Eash ◽  
Jaehoon Lee ◽  
Madhavi Z. Martin ◽  
Yong-Seon Zhang ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Soil Samples ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown
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