Three-dimensional elemental imaging of material surface using image-assisted laser-induced breakdown spectroscopy

Deng, Zongquan; Chu, Yanwu; Ma, Shixiang; Sheng, Ziqian; Chen, Feng; Hu, Zhenlin; Zhang, Siyu; Wang, Bin; Guo, Lianbo

doi:10.1016/j.apsusc.2020.147601

Cited by 13 publications

(7 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, the volume, average depth, maximum depth, and horizontal Feret's diameter of craters were recognized as X-variables in the following analysis, thus together contributing significantly to the linear model. The selected craters' parameters are marked in Figure 7 to provide straightforward information, which is roughly consistent with the findings of other studies [52]. The blue line indicates the moving path of the X-Y-Z motorized stage.…”

Section: The Crater Morphology Analysissupporting

confidence: 81%

Crater–Spectrum Feature Fusion Method for Panax notoginseng Cadmium Detection Using Laser-Induced Breakdown Spectroscopy

Chen,

Li,

et al. 2024

Foods

View full text Add to dashboard Cite

Panax notoginseng (P. notoginseng) is a valuable herbal medicine, as well as a dietary food supplement known for its satisfactory clinical efficacy in alleviating blood stasis, reducing swelling, and relieving pain. However, the ability of P. notoginseng to absorb and accumulate cadmium (Cd) poses a significant environmental pollution risk and potential health hazards to humans. In this study, we employed laser-induced breakdown spectroscopy (LIBS) for the rapid detection of Cd. It is important to note that signal uncertainty can impact the quantification performance of LIBS. Hence, we proposed the crater–spectrum feature fusion method, which comprises ablation crater morphology compensation and characteristic peak ratio correction (CPRC), to explore the feasibility of signal uncertainty reduction. The crater morphology compensation method, namely, adding variables using multiple linear regression (MLR) analysis, decreased the root-mean-square error of the prediction set (RMSEP) from 7.0233 μg/g to 5.4043 μg/g. The prediction results were achieved after CPRC pretreatment using the calibration curve model with an RMSEP of 3.4980 μg/g, a limit of detection of 1.92 μg/g, and a limit of quantification of 6.41 μg/g. The crater–spectrum feature fusion method reached the lowest RMSEP of 2.8556 μg/g, based on a least-squares support vector machine (LSSVM) model. The preliminary results suggest the effectiveness of the crater–spectrum feature fusion method for detecting Cd. Furthermore, this method has the potential to be extended to detect other toxic metals in addition to Cd, which significantly contributes to ensuring the quality and safety of agricultural production.

show abstract

Section: The Crater Morphology Analysissupporting

confidence: 81%

Crater–Spectrum Feature Fusion Method for Panax notoginseng Cadmium Detection Using Laser-Induced Breakdown Spectroscopy

Chen,

Li,

et al. 2024

Foods

View full text Add to dashboard Cite

show abstract

“…In this study, the objective function is defined as the difference between the predicted values and actual values. To evaluate the output results of the three prediction models of the NPK fertilizer application rate, the mean square error (MSE), the explained variance score (EVS), and the coefficient of determination (R 2 ) were used to verify the effectiveness of the prediction models of the NPK fertilizer application rate for greenhouse tomatoes [62][63][64]. Their concepts and calculation methods are as follows:…”

Section: Evaluation Indexesmentioning

confidence: 99%

Prediction Model of Nitrogen, Phosphorus, and Potassium Fertilizer Application Rate for Greenhouse Tomatoes under Different Soil Fertility Conditions

Yu,

Luo,

Bai

et al. 2024

Agronomy

View full text Add to dashboard Cite

To reach the target yield of crops, nutrient management is essential. Selecting the appropriate prediction model and adjusting the nutrient supply based on the actual situation can effectively improve the nutrient utilization efficiency, crop yield, and product quality. Therefore, a prediction model of the NPK fertilizer application rate for greenhouse tomatoes under the target yield was studied in this study. Under low, medium, and high soil fertility conditions, a neural network prediction model based on the sparrow search algorithm (SSA-NN), a neural network prediction model based on the improved sparrow search algorithm (ISSA-NN), and a neural network prediction model based on the hybrid algorithm (HA-NN) were used to predict the NPK fertilizer application rate for greenhouse tomatoes. The experimental results indicated that the evaluation indexes (i.e., the mean square error (MSE), explained variance score (EVS), and coefficient of determination (R2)) of the HA-NN prediction model proposed in this study were superior than the SSA-NN and ISSA-NN prediction models under three different soil fertility conditions. Under high soil fertility, compared with the SSA-NN prediction model, the MSE of the ISSA-NN and HA-NN prediction models decreased to 0.007 and 0.005, respectively; the EVS increased to 0.871 and 0.908, respectively; and the R2 increased to 0.862 and 0.899, respectively. This study showed that the HA–NN prediction model was superior in predicting the NPK fertilizer application rate for greenhouse tomatoes under three different soil fertility conditions. Due to the significance of NPK fertilizer application rate prediction for greenhouse tomatoes, this technique is expected to bring benefits to agricultural production management and decision support.

show abstract

“…Moreover, recent research has shown that the brightness of the plasma image can represent plasma temperature, and the area of the plasma image can characterize the laser ablation quality. 37,38 It can be veried that plasma image information has a certain correlation with spectral line intensity. Otherwise, the plasma image is the direct expression of the plasma which contains more message about laser-material interaction.…”

Section: Correlation Between the Plasma Image Area And Spectrummentioning

confidence: 99%

An image auxiliary method for laser-induced breakdown spectroscopy analysis of coal particle flow

Chen

Dong

Cai

et al. 2022

J. Anal. At. Spectrom.

View full text Add to dashboard Cite

show abstract

Three-dimensional elemental imaging of material surface using image-assisted laser-induced breakdown spectroscopy

Cited by 13 publications

References 25 publications

Crater–Spectrum Feature Fusion Method for Panax notoginseng Cadmium Detection Using Laser-Induced Breakdown Spectroscopy

Crater–Spectrum Feature Fusion Method for Panax notoginseng Cadmium Detection Using Laser-Induced Breakdown Spectroscopy

Prediction Model of Nitrogen, Phosphorus, and Potassium Fertilizer Application Rate for Greenhouse Tomatoes under Different Soil Fertility Conditions

An image auxiliary method for laser-induced breakdown spectroscopy analysis of coal particle flow

Contact Info

Product

Resources

About