Quantitative Analysis of Lead in Tea Samples by Laser-Induced Breakdown Spectroscopy

Wang, J.; Shi, M.; Zheng, Peichao; Xue, Shuwen

doi:10.1007/s10812-017-0448-9

Cited by 21 publications

(7 citation statements)

References 20 publications

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“…A pipette was used to add the CuSO 4 solution to the A. sinensis and S. baicalensis samples and prepare standard samples with Cu concentrations of 10, 20, 40, 60, 80, 100, and 200 µg/g, respectively. The samples were then placed in a constant temperature drying oven at 60°C for 24 h. Once dry, the samples were pressed in a tablet press at 15 MPa to form tablets (thickness: 5 mm) 18 . Because the content of heavy metals in Chinese medicinal materials is usually very low or even free, to verify the accuracy of different quantitative methods, using the same sample preparation method, A. sinensis and S. baicalensis samples were prepared with Cu concentrations of 35 and 25 µg/g as test samples, respectively.…”

Section: Experiments and Sample Preparationmentioning

confidence: 99%

“…Sirven et al 17 used LIBS combined with neural networks to perform qualitative and quantitative analysis of chromium‐contaminated soil. Wang et al 18 used external and internal standard methods, and multiple linear regression to quantitatively analyze Pb in tea. In another study, LIBS was combined with multiple linear regression to determine the Pb and Cu concentrations in Ligusticum wallichii 2 .…”

Section: Introductionmentioning

confidence: 99%

“…The quantitative analysis methods based on stoichiometry or machine learning methods can effectively reduce matrix effects and improve the quantitative analysis performance of LIBS. 19 This study aims to use LIBS technology for quantitative analysis of TCMM samples to evaluate the accuracy of different quantitative analysis methods. We used two authentic medicinal materials, Angelica sinensis and Scutellaria baicalensis, from Longxi County, Gansu province, China.…”

Section: Introductionmentioning

confidence: 99%

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Quantitative analysis of Cu in Traditional Chinese medicinal materials using laser‐induced breakdown spectroscopy

Sun

Yang

et al. 2022

Micro & Optical Tech Letters

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Section: Experiments and Sample Preparationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quantitative analysis of Cu in Traditional Chinese medicinal materials using laser‐induced breakdown spectroscopy

Sun

Yang

et al. 2022

Micro & Optical Tech Letters

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“…Model. MLR is a common calibration method in quantitative spectroscopy, which focuses on the correlation between an attribute of interest and each wavelength [35][36][37]. Te basic form is…”

Section: Multiple Linear Regressionmentioning

confidence: 99%

A New Method for Spectral Wavelength Selection Based on Multiple Linear Regression Combined with Ant Colony Optimization and Genetic Algorithm

Huang

Xue

Liu

et al. 2022

Journal of Spectroscopy

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Wavelength selection is one of the key steps in quantitative spectral analysis, which reduces the computation time while also improving the prediction accuracy of the model. In this paper, we propose a wavelength selection algorithm based on the ant colony optimization (ACO), in which the absolute value of the regression coefficient of the multiple linear regression (MLR) model is used as the basis for evaluating the importance of wavelengths, and the absolute value of the regression coefficient after full wavelength MLR modeling is used as the initial pheromone value of the ant colony optimization (MLR-ACO). In each iteration, the absolute value of the regression coefficient corresponding to each wavelength of the individual with the highest fitness value is used as the basis for a pheromone update. The crossover operator is introduced in MLR-ACO (MLR-ACO-GA), and the individuals with the top 100 fitness values in MLR-ACO are used as the initial population of the genetic algorithm (GA). A selected frequency of wavelengths greater than the threshold among MLR-ACO individuals is calculated. A number of coarse interval points are generated according to the selected frequency, and a coarse crossover operation is performed at the coarse interval points. Fine crossover points are randomly generated within the coarse interval, and fine crossover operations are performed within the coarse interval to exploit the potential of combining excellent individuals in MLR-ACO with each other as much as possible. MLR-ACO can well solve the problem of traditional ACO initial pheromone scarcity, and MLR-ACO-GA can avoid MLR-ACO falling into a local optimum to a certain extent and be more flexible in the selection of the number of wavelengths, which can give full play to the advantages of MLR-ACO.

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“…However, these models need further investigation to achieve the best results for analyzing fertilizer complex matrix. On the other hand, the Multiple Linear Regression (MLR) method could be a possible solution to compensate for the matrix effect of complex solid fertilizer [16,17]. This study aims to apply LIBS analytical method for multi-element analysis of solid fertilizers.…”

Section: Introductionmentioning

confidence: 99%

Laser-Induced Breakdown Spectroscopy for Determination of Toxic Metals in Fertilizers: emphasis on Lead

Salloom

Hamad

Rajab

2022

eijs

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The present work aims to evaluate the content of some toxic metals in chemical and organic fertilizers purchased from local markets in Baghdad, Iraq. The analysis was performed by laser-induced breakdown spectroscopy (LIBS) system. The emission spectral lines of lead (Pb), chromium (Cr), cadmium (Cd) and cobalt (Co) have been recorded to determine the best peak representing each element according to the NIST database. The validity of the LIBS procedure was checked by cross-validating the obtained results using atomic absorption spectroscopy (AAS) with a maximum relative error of 5.3%. Moreover, for qualitative analysis, Pb I 296.64 nm emission line was determined to be superior for the evaluation of lead content in terms of three calibration methods: the external standard (ES), the internal standard (IS), and the multiple linear regression (MLR). The linear correlation coefficient values were : 0.94, 0.97 and 0.992, respectively. LIBS results based on the multiple linear regression (MLR) model have demonstrated better performance and were adopted in the assessment of the Pb content in solid fertilizer samples.

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Quantitative Analysis of Lead in Tea Samples by Laser-Induced Breakdown Spectroscopy

Cited by 21 publications

References 20 publications

Quantitative analysis of Cu in Traditional Chinese medicinal materials using laser‐induced breakdown spectroscopy

Quantitative analysis of Cu in Traditional Chinese medicinal materials using laser‐induced breakdown spectroscopy

A New Method for Spectral Wavelength Selection Based on Multiple Linear Regression Combined with Ant Colony Optimization and Genetic Algorithm

Laser-Induced Breakdown Spectroscopy for Determination of Toxic Metals in Fertilizers: emphasis on Lead

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