Laser-induced breakdown spectroscopy (LIBS) for the detection of exogenous contamination of metal elements in lily bulbs

Research on a new multiple-screening method for laser-induced plasma spectroscopy utilizing Lorentz

In the field of Laser Induced Breakdown Spectroscopy (LIBS) research, the screening and extraction of complex spectra play a crucial role in enhancing the accuracy of quantitative analysis. This paper introduces a novel approach for multiple screenings of LIBS spectra using Lorentz Screening and Sensitivity and Volatility Analysis. Initially, Create symmetrical sampling standards for Lorentz fitting. Then the Lorentz fitting is used to uniformly screen the collected spectral information on both sides in order to eliminate adjacent interference peaks. Subsequently, Sensitivity and Volatility Analysis is employed to further remove overlapping peaks and select spectra with low volatility and high sensitivity. Sensitivity and Volatility Analysis is a spectral discrimination method proposed on the premise of intensity's correlation with concentration. It utilizes a Z-score method that incorporates both deviation and standard deviation for effective analysis. Furthermore, it meticulously selects spectral lines with minimal interference and volatility, thereby augmenting the precision of quantitative analysis. The quantitative accuracy (R2) for Chromium (Cr) and Nickel (Ni) elements can reach 0.9919 and 0.9768, respectively. Their average errors can be reduced to 0.0566 % and 0.1024 %. The study demonstrates that Lorentz Screening and Sensitivity and Volatility Analysis can select high-quality characteristic spectral lines to improve the performance of the model.

Application and Research Progress of Laser-Induced Breakdown Spectroscopy in Agricultural Product Inspection

The quality and safety of agricultural products are of paramount importance in ensuring the health of the food supply chain. Additionally, the composition and trace elements in agricultural products significantly influence their quality and nutritional value. Therefore, the need for rapid and accurate analysis techniques for agricultural product composition is particularly crucial. In the current landscape of evolving compositional analysis technologies, Laser-Induced Breakdown Spectroscopy (LIBS) technology is emerging as a promising analytical tool with broad applications in agricultural product testing. Its characteristics of being rapid, real-time, and capable of simultaneous detection of multiple elements provide an efficient and reliable means for assessing the quality, monitoring safety, and tracing the origin of agricultural products. This technology is expected to play a significant role in controlling and managing the agricultural industry chain and can offer consumers safer and healthier agricultural products. This paper provides an overview of the research status and recent developments of LIBS technology in agricultural product testing applications in recent years. Based on the current research landscape, challenges and opportunities of applying LIBS technology in fields such as agricultural product quality and safety assessment, soil analysis, assessment of crop nutrition, detection of plant diseases, and identification of agricultural product varieties have been evaluated. Moreover, recommendations for further expanding the application of LIBS technology in the agricultural sector are proposed.

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

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.

Rapid Test for Adulteration of Fritillaria Thunbergii in Fritillaria Cirrhosa by Laser-Induced Breakdown Spectroscopy

Fritillaria has a long history in China, and it can be consumed as medicine and food. Owing to the high cost of Fritillaria cirrhosa, traders sometimes mix it with the cheaper Fritillaria thunbergii powder to make profit. Herein, we proposed a laser-induced breakdown spectroscopy (LIBS) technique to test the adulteration present in the sample of Fritillaria cirrhosa powder. Experimental samples with different adulteration levels were prepared, and their LIBS spectra were obtained. Partial least squares regression (PLSR) was adopted as the quantitative analysis model to compare the effects of four data standardization methods, namely, mean centring, normalization by total area, standard normal variable, and normalization by the maximum, on the performance of the PLSR model. Principal component analysis and least absolute shrinkage and selection operator (LASSO) were utilized for feature extraction and feature selection, and the performance of the PLSR model was determined based on its quantitative analysis. Subsequently, the optimal number of features was determined. The residuals were corrected using support vector regression (SVR). The mean absolute error and root mean square error of prediction obtained from the quantitative analysis results of the combined LASSO-PLSR-SVR model for the test set data were 5.0396% and 7.2491%, respectively, and the coefficient of determination R² was 0.9983. The results showed that the LIBS technique can be adopted to test adulteration in the sample of Fritillaria cirrhosa powder and has potential applications in drug quality control.

Rapid determination of lead (Pb) in the soil-plant system by laser-induced breakdown spectroscopy (LIBS): case study of Pb-pollution from perovskite solar cells

With the widespread usage of lead (Pb)-containing perovskite solar cells (PSCs), it is critical to monitor Pb pollution from PSCs in the environment. Among different analytical techniques, laser-induced breakdown spectroscopy (LIBS) has demonstrated good performance in the fast quantification of many elements in solid samples, without using toxic and expensive chemical reagents. Therefore, LIBS offers significant potential for detecting and quantifying Pb in the environment. In this study, a Pb migration model in the PSCs-soil-Houttuynia plants system was assessed based on the LIBS data. The Pb transfer rates and the Pb uptake coefficients were calculated to evaluate Pb migration from PSCs to plants. The results showed that the R² of quantitative results were all greater than 0.98, with the root-mean-square error of cross-validation (RMSECV) being less than 1.53 wt.%. Furthermore, above 49% Pb from PSCs was swiftly diffused into soil under watering conditions, while Houttuynia plants absorbed over 10% Pb from polluted soil. This study revealed that Pb leakage from PSCs should not be underestimated and that LIBS is a viable and fast analytical method for monitoring Pb in the environment.