Detection of nutrient elements and contamination by pesticides in spinach and rice samples using laser-induced breakdown spectroscopy (LIBS)

Direct Determination of Ca, K, and Mg in Soy Leaf Samples Using Laser-Induced Breakdown Spectroscopy

This study was dedicated to developing analytical methods for determining macronutrients (Ca, K, and Mg) in soy leaf samples with and without petioles. The study's primary purpose was to present Laser-induced breakdown spectroscopy (LIBS) as a viable alternative for directly analyzing leaf samples using chemometric tools to interpret the data obtained. The instrumental condition chosen for LIBS was 70 mJ of laser pulse energy, 1.0 µs of delay time, and 100 µm of spot size, which was applied to 896 samples: 305 of soy without petioles and 591 of soy with petioles. The reference values of the analytes for the proposition of calibration models were obtained using inductively coupled plasma optical emission spectroscopy (ICP-OES) technique. Twelve normalization modes and two calibration strategies were tested to minimize signal variations and sample matrix microheterogeneity. The following were studied: multivariate calibration using partial least squares and univariate calibration using the area and height of several selected emission lines. The notable normalization mode for most models was the Euclidean norm. No analyte showed promising results for univariate calibrations. Micronutrients, P and S, were also tested, and no multivariate models presented satisfactory results. The models obtained for Ca, K, and Mg showed good results. The standard error of calibration ranged from 2.3 g/kg for Ca in soy leaves without petioles with two latent variables to 5.0 g/kg for K in soy leaves with petioles with two latent variables.

Rapid quantitative analysis of rare earth elements Lu and Y in rare earth ores by laser induced breakdown spectroscopy combined with iPLS-VIP and partial least squares

Rare earth ores are complex in composition and diverse in mineral composition, requiring high technical requirements for the selection of rare earth ores. It is of great significance to explore the on-site rapid detection and analysis methods of rare earth elements in rare earth ores. Laser induced breakdown spectroscopy (LIBS) is an important tool to detect rare earth ores, which can be used for in situ analyses without complicated sample preparation. In this study, a rapid quantitative analysis method for rare earth elements Lu and Y in rare earth ores was established by LIBS combined with an iPLS-VIP hybrid variable selection strategy and partial least squares (PLS) method. First, the LIBS spectra of 25 samples were studied using laser induced breakdown spectrometry. Second, taking the spectrum processed by wavelet transform (WT) as the input variables, PLS calibration models based on interval partial least squares (iPLS), variable importance projection (VIP) and iPLS-VIP hybrid variable selection were constructed to quantitatively analyze rare earth elements Lu and Y, respectively. The results show that the WT-iPLS-VIP-PLS calibration model has better prediction performance for rare earth elements Lu and Y, and the optimal coefficient of determination (R²) of Lu and Y were 0.9897 and 0.9833, the root mean square error (RMSE) were 0.8150 μg g^-1 and 97.1047 μg g^-1, and the mean relative error (MRE) were 0.0754 and 0.0766, respectively. It shows that LIBS technology combined with the iPLS-VIP and PLS calibration model provides a new method for in situ quantitative analysis of rare earth elements in rare earth ores.

Fast detection of minerals in rice leaves under chromium stress based on laser-induced breakdown spectroscopy

Minerals in rice leaves is a crucial indicator of plant health, and their concentrations can be used to guide plant management. It is important to predict mineral content in contaminated rice rapidly. In this study, laser-induced breakdown spectroscopy (LIBS) was applied to quantify minerals (Ca, Cu, Fe, K, Mg, Mn, and Na) in rice leaves under chromium (Cr) stress. Two feature extraction methods, including principal component analysis (PCA) and extreme gradient boosting (XGBoost), were compared to identify important variables that related to mineral concentrations. Results showed that partial least square regression (PLSR) achieved good performance in Ca, Fe Mg, K, Mn, and Na, with correlation coefficient of 0.9782, 0.8712, 0.8933, 0.9206, 0.9856, and 0.9865, root mean square error of 219.25, 14.78, 1192.47, 385.12, 9.56, and 124.32 mg/kg, respectively. In addition, the correlation between different spectral lines were further analyzed. Cr exhibited a positive correlation with Ca, Mg, and Na, and a negative correlation with Mn, Cu, and K. The proposed method provides a high-accuracy and fast approach for minerals prediction in rice leaves under Cr stress, which is important for environmental protection and food safety.

Rapid Food Authentication Using a Portable Laser-Induced Breakdown Spectroscopy System

Laser-induced breakdown spectroscopy (LIBS) is an atomic-emission spectroscopy technique that employs a focused laser beam to produce microplasma. Although LIBS was designed for applications in the field of materials science, it has lately been proposed as a method for the compositional analysis of agricultural goods. We deployed commercial handheld LIBS equipment to illustrate the performance of this promising optical technology in the context of food authentication, as the growing incidence of food fraud necessitates the development of novel portable methods for detection. We focused on regional agricultural commodities such as European Alpine-style cheeses, coffee, spices, balsamic vinegar, and vanilla extracts. Liquid examples, including seven balsamic vinegar products and six representatives of vanilla extract, were measured on a nitrocellulose membrane. No sample preparation was required for solid foods, which consisted of seven brands of coffee beans, sixteen varieties of Alpine-style cheeses, and eight different spices. The pre-processed and standardized LIBS spectra were used to train and test the elastic net-regularized multinomial classifier. The performance of the portable and benchtop LIBS systems was compared and described. The results indicate that field-deployable, portable LIBS devices provide a robust, accurate, and simple-to-use platform for agricultural product verification that requires minimal sample preparation, if any.

Diagnosis of HLB-asymptomatic citrus fruits by element migration and transformation using laser-induced breakdown spectroscopy

Huanglongbing (HLB) is one of the most devastating bacterial diseases in citrus growth and there is no cure for it. The mastery of elemental migration and transformation patterns can effectively analyze the growth of crops. The law of element migration and transformation in citrus growth is not very clear. In order to obtain the law of element migration and transformation, healthy and HLB-asymptomatic navel oranges collected in the field were taken as research objects. Laser-induced breakdown spectroscopy (LIBS) is an atomic spectrometry technique for material component analysis. By analyzing the element composition of fruit flesh, peel and soil, it can know the specific process of nutrient exchange and energy exchange between plants and the external environment, as well as the rules of internal nutrient transportation, distribution and energy transformation. Through the study of elemental absorption, the growth of navel orange can be effectively monitored in real time. HLB has an inhibitory effect on the absorption of navel orange. In order to improve the detection efficiency, LIBS coupled with SVM algorithms was used to distinguish healthy navel oranges and HLB-asymptomatic navel oranges. The classification accuracy was 100%. Compared with the traditional detection method, the detection efficiency of LIBS technology is significantly better than the polymerase chain reaction method, which provides a new means for the diagnosis of HLB-asymptomatic citrus fruits.

An overview on multi-elemental profile integrated with chemometrics for food quality assessment: toward new challenges

Food products, especially those with high value-added, are commonly subjected to strict quality controls, which are of paramount importance, especially for attesting to some peculiar features related, for instance, to their geographical origin and/or the know-how of their producers. However, the sophistication of fraudulent practices requires a continuous update of analytical platforms. Different analytical techniques have become extremely appealing since the instrumental analysis tools evolution has substantially improved the capability to reveal and understand the complexity of food. In light of this, multi-elemental composition has been successful implemented solving a plethora of food authentication and traceability issues. In the last decades, it has existed an ever-increasing trend in analysis based on spectrometry analytical platforms in order to obtain a multi-elemental profile that combined with chemometrics have been noteworthy analytical methodologies able to solve these problems. This review provides an overview of published reports in the last decade (from 2011 to 2021) on food authentication and quality control from their multi-element composition in order to evaluate the state-of-the-art of this field and to identify the main characteristics of applied analytical techniques and chemometric data treatments that have permit achieve accurate discrimination/classification models, highlighting the strengths and the weaknesses of these methodologies.

Improving Calibration Strategy for LIBS Heavy Metals Analysis in Agriculture Applications

A new calibration procedure, known as mapping conditional-calibration laser-induced breakdown spectroscopy (LIBS), has been suggested to improve analysis results for heterogeneous samples. The procedure is based on LIBS elemental mapping, followed by signal conditioning in every sampling spot to skip signal outliers, then by finalizing the calibration curve construction. The suggested mapping conditional calibration procedure was verified for zinc analysis in soybean grist samples. The laser parameters correspond to those of the hand-held LIBS instrument in order to estimate the influence of sample surface heterogeneity under on-site analysis conditions. The laser spot (60 μm) was equal to or smaller than the typical size of grist particles (40–500 μm) but laser crater dimensions were significantly greater and varied widely (150–450 μm). The LIBS mapping of different spectral signals (atomic and ionic lines for major and minor components) was achieved. Elemental maps were normalized to achieve signal maps that were conditionally spotted to skip signal outliers. It was demonstrated that the suggested mapping conditional-calibration LIBS provided 15 ppm RMSECV for zinc determination in heterogeneous samples, which is typical for agricultural products.

Analysis of corn and sorghum flour mixtures using laser-induced breakdown spectroscopy

BACKGROUND

In a world constantly challenged by climate change, corn and sorghum are two important grains because of their high productivity and adaptability, and their multifunctional use for different purposes such as human food, animal feed, and feedstock for many industrial products and biofuels. Corn and sorghum can be utilized interchangeably in certain applications; one grain may be preferred over the other for several reasons. The determination of the composition corn and sorghum flour mixtures may be necessary for economic, regulatory, environmental, functional, or nutritional reasons.

RESULTS

Laser-induced breakdown spectroscopy (LIBS) in combination with chemometrics, was used for the classification of flour samples based on the LIBS spectra of flour types and mixtures using partial least squares discriminant analysis (PLS-DA) and the determination of the sorghum ratio in sorghum / corn flour mixture based on their elemental composition using partial least squares (PLS) regression. Laser-induced breakdown spectroscopy with PLS-DA successfully identified the samples as either pure corn, pure sorghum, or corn-sorghum mixtures. Moreover, the addition of various levels of sorghum flour to mixtures of corn-sorghum flour were used for PLS analysis. The coefficient of determination values of calibration and validation PLS models are 0.979 and 0.965, respectively. The limit of detection of the PLS models is 4.36%.

CONCLUSION

This study offers a rapid method for the determination of the sorghum level in corn-sorghum flour mixtures and the classification of flour samples with high accuracy, a short analysis time, and no requirement for time-consuming sample preparation procedures. © 2020 Society of Chemical Industry.

Determination of the nutrient profile in plant materials using laser-induced breakdown spectroscopy with partial least squares-artificial neural network hybrid models

Nutrient profile determination for plant materials is an important task to determine the quality and safety of the human diet. Laser-induced breakdown spectroscopy (LIBS) is an atomic emission spectrometry of the material component analytical technique. However, quantitative analysis of plant materials using LIBS usually suffers from matrix effects and nonlinear self-absorption. To overcome this problem, a hybrid quantitative analysis model of the partial least squares-artificial neural network (PLS-ANN) was used to detect the compositions of plant materials in the air. Specifically, fifty-eight plant materials were prepared to split into calibration, validation and prediction sets. Nine nutrient composition profiles of Mg, Fe, N, Al, B, Ca, K, Mn, and P were employed as the target elements for quantitative analysis. It demonstrated that the prediction ability can be significantly improved by the use of the PLS-ANN hybrid model compared to the method of standard calibration. Take Mg and K as examples, the root-mean-square errors of calibration (RMSEC) of Mg and K were decreased from 0.0295 to 0.0028 wt.% and 0.2884 to 0.0539 wt.%, and the mean percent prediction errors (MPE) were decreased from 5.82 to 4.22% and 8.82 to 4.12%, respectively. This research provides a new way to improve the accuracy of LIBS for quantitative analysis of plant materials.

Application of laser-induced breakdown spectroscopy for detection of elements in flowback water samples from shale gas wells

Laser-induced breakdown spectroscopy (LIBS) was applied to rapidly detect elements in flowback water samples from shale gas wells in Oklahoma. Two types of LIBS systems (aerosolization and collection on a substrate) were used. The LIBS with an aerosolization system provided rapid determination of elements in flowback water, but moisture present in the chamber and variation in the water droplet size could make quantification difficult. In the substrate collection system, a comparison among substrate types showed that a hydrophilic cellulose filter gave the most homogeneous sample distribution after drying and provided the best performance. The elements in flowback water samples were also determined by inductively coupled plasma-optical emission spectroscopy (ICP-OES). ICP-OES data showed spatial variations for the elements among the different wells. Among the elements, K showed the highest variation (relative standard ${\rm deviation} = {62.8}\% $deviation=62.8%) and Mg the lowest (relative standard ${\rm deviation} = {39.1}\% $deviation=39.1%). Good correlations (${ r} = {0.98 - 0.99}$r=0.98-0.99) were observed between Ca, K, Mg, and Na LIBS peak areas determined using the cellulose filter and their mass concentrations (ppm) measured by ICP-OES for aqueous solutions. The limits of detection for Ca, K, Mg, and Na by LIBS were 122 ppm, 68 ppm, 36 ppm, and 142 ppm, respectively. Both the LIBS and ICP-OES data showed that element concentrations in the flowback water samples were in the order of Na, Ca, Mg, and K from highest to lowest. Our data suggest that the LIBS technique could rapidly detect elements in flowback water samples on site. However, accurate quantification of elements present in low concentrations in water samples is limited.

Proposed a self-absorption internal standard model to detect element concentrations of complex constituent material with a single emission line of element in laser plasmas

Laser induced plasmas (LIPs) method is a highly regarded approach to evaluate the chemical composition of materials. But the strong self-absorption of the radiation seriously affects its accuracy. Meanwhile, the model based on self-absorption phenomenon makes its application very difficult. In this work, a self-absorption internal standard (SAIS) model is proposed for detection of the multi-element concentrations of complex constituent material with a single emission line of the element in laser plasmas. A typical LIPs experiment system is set up to generate plasmas, and the soil is selected as a test sample. The average electron temperature (0.975 eV) and electron density (1.44×10¹⁸ cm^-3) are determined by the Boltzmann plot and emission lines Stark broadening, respectively. The plasmas are diagnosed as in local thermodynamic equilibrium condition. The emission lines selected to calculate the concentration of sample contain a wide set of kt values (0.575×10^-30∼37.2×10^-30 m³). Then, the concentrations of some elements are calculated by the model using single emission line of each element. It is found that the concentrations of the five elements (Ti, Fe, Mg, Al, Si) calculated by SAIS model are relatively consistent with the results of the traditional chemical testing methods. This indicated that the SAIS model is an effective and neat method for multi-element concentrations detection of complex constituent materials.

Early prediction of sugarcane genotypes susceptible and resistant to Diatraea saccharalis using spectroscopies and classification techniques

The aim of this work was to use spectroscopic methods and partial least squares discriminant analysis (PLS-DA) for the early prediction of genotype resistance or susceptibility to sugarcane borer. The sugarcane leaf +1 was directly analyzed with no sample preparation by ultraviolet-visible-near-infrared (UV-VIS-NIR), middle-infrared (MID), and near-infrared (NIR) spectroscopies. Also, laser-induced breakdown spectroscopy (LIBS) was used to analyze pellets of dried and ground leaves and stalks of sugarcane. Classification models were built using PLS-DA. The models built using UV-VIS-NIR, MID or NIR spectra exhibited ideal sensitivity, specificity, and classification errors, i.e., 1 for both sensitivity and specificity and 0 for classification errors. Regarding the models built using LIBS spectra, those using spectra of pellets made from dried and ground leaves also presented ideal sensitivity, specificity, and classification errors; on the other hand, models built using the spectra of pellets made of dried and ground stalks did not present ideal values for these parameters. Thus, the models built, except for the one using LIBS of pellets made of stalks, showed excellent predictive capacity, making them suitable for predicting the resistance or susceptibility of sugarcane genotypes in the early stages of a plant's life.

Macro-elements in the hemolymph of adult Euschistus heros (Fabr.) (Hemiptera: Pentatomidae) treated with pyriproxyfen

Euschistus heros is an important pest in many crops in Brazil, and different control strategies, mainly involving chemicals, have been evaluated; however, the side effects of these chemicals on the balance of inorganic element levels in the hemolymph are unknown. Thus, the aim of this work was to determine the concentration of inorganic elements (focusing on macro-elements) in the hemolymph of female and male E. heros adults, after applying pyriproxyfen at a sublethal concentration (LC₃₀ = 6.68 mL L^-1 diluted in distilled water) to 4th instar nymphs, which were kept in controlled conditions. The hemolymph pool was removed 48 h after adult emergence, centrifuged and placed on an acrylic disk added with Gallium as internal standard for the analysis of total reflection X-ray fluorescence. Most of the elements in the control treatment did not differ between females and males. However, following insecticide application to females and males, respectively, there was a significant increase in sulfur (19 and 51%), chlorine (33 and 137%) and calcium (47 and 82%) in the hemolymph. The significantly higher increase in macro-elements in males' hemolymph indicates that the action of pyriproxyfen may be sex-specific. Phosphorus and potassium concentrations also differed between females and males in the control and treated groups. The observed variation in inorganic elements in the insect's hemolymph may be related to the unknown effects of pyriproxyfen, mainly on immune and reproductive performance.

Feasibility of Laser-Induced Breakdown Spectroscopy and Hyperspectral Imaging for Rapid Detection of Thiophanate-Methyl Residue on Mulberry Fruit

An effective and rapid way to detect thiophanate-methyl residue on mulberry fruit is important for providing consumers with quality and safe of mulberry fruit. Chemical methods are complex, time-consuming, and costly, and can result in sample contamination. Rapid detection of thiophanate-methyl residue on mulberry fruit was studied using laser-induced breakdown spectroscopy (LIBS) and hyperspectral imaging (HSI) techniques. Principal component analysis (PCA) and partial least square regression (PLSR) were used to qualitatively and quantitatively analyze the data obtained by using LIBS and HSI on mulberry fruit samples with different thiophanate-methyl residues. The competitive adaptive reweighted sampling algorithm was used to select optimal variables. The results of model calibration were compared. The best result was given by the PLSR model that used the optimal preprocessed LIBS–HSI variables, with a correlation coefficient of 0.921 for the prediction set. The results of this research confirmed the feasibility of using LIBS and HSI for the rapid detection of thiophanate-methyl residue on mulberry fruit.

Detecting and Mapping Harmful Chemicals in Fruit and Vegetables Using Nanoparticle-Enhanced Laser-Induced Breakdown Spectroscopy

Residues of harmful chemicals in fruit and vegetables pose risks to human health. Ordinary laser-induced breakdown spectroscopy (LIBS) techniques are unsatisfactory for detecting harmful chemicals in fruit and vegetables. In this study, we applied metal nanoparticles to fruit and vegetables samples to improve the ability of LIBS to detect trace pesticide and heavy metal residues in the samples. The nanoparticle-enhanced LIBS technique gave pesticide residue detection limits for fruit and vegetables two orders of magnitude lower than achieved using standard LIBS and heavy metal detection limits markedly better than achieved using standard LIBS. We used the nanoparticle-enhanced LIBS technique to study the distributions of harmful chemicals in vegetable leaves. We found that heavy metals are distributed unevenly in edible plant leaves, the heavy metal concentrations being higher in the veins than in the mesophyll.

Traditional Calibration Methods in Atomic Spectrometry and New Calibration Strategies for Inductively Coupled Plasma Mass Spectrometry

Applications, advantages, and limitations of the traditional external standard calibration, matrix-matched calibration, internal standardization, and standard additions, as well as the non-traditional interference standard method, standard dilution analysis, multi-isotope calibration, and multispecies calibration methods are discussed.

Determination of Macronutrient and Micronutrient Content in Rice Grains Using Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES)

The rice grain endosperm is mostly composed of starch , which serves as the major source of calories for more than half of the world's population. Macro and micronutrients make a minor proportion of the rice grain, which particularly gets accumulated in outer aleurone layer, which are in general eliminated upon milling. Because rice is the major staple, it is seen as an efficient mechanism for delivering both macro- and micronutrients, particularly for the poor who do not have ample access to diversified diets. Enriching micronutrient and macronutrient concentrations in milled rice of endosperm and/or in brown rice, is an important dietary intervention to create health benefits of rice consumers. Efforts are underway to increase the nutritional content of rice through bio/fortification approaches. The plant takes up these same elements from the soil, redirect the transport of these elements into the grain. Thus besides biofortification strategies, scientists can also use the knowledge to design proper soil nutrient management to enrich micronutrients in the grains. Therefore, it is important to be able to determine the macro- and the micronutrient composition of the vegetative parts of the rice plant and of the rice grain. In this chapter, nitric-perchloric acid digestion and inductively coupled plasma-optical emission spectrometry (ICP-OES) methods routinely used in IRRI's Grain Quality and Nutrition Services Laboratory (GQNSL) to determine the concentrations of various macro- and micronutrients found in the rice grain and the rice plant, are described.

Laser-induced breakdown spectroscopy assisted chemometric methods for rice geographic origin classification

The problems of adulteration and mislabeling are very common in the food industry. Laser-induced breakdown spectroscopy (LIBS) coupled with chemometric methods has many intrinsic advantages on adulteration analysis of various materials. In this work, several chemometric algorithms, i.e., principal component analysis (PCA), decision tree (DT), random forest (RF), partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and support vector machine (SVM), were carried out assisted by LIBS technology to study the classification performances on rice geographic origins. A series of samples, including 20 kinds of rice samples from different geographic origins, was detected using LIBS with no pretreatment processes. For data analysis, PCA was employed to reduce the input variables, and to reduce the collinearity of LIBS spectral results as well. The results showed the classification accuracies of the mentioned chemometric algorithms of DT, RF, PLS-DA, LDA, and SVM with 89 input variables of 86.80%, 96.30%, 96.80%, 98.60%, and 99.20%, respectively. At the same time, the operation times of these algorithms were 3.81 s, 54.64 s, 3.63 s, 2.09 s, and 531.01 s, respectively. On the other hand, 30 principal components of input variables were also tested under the same conditions. The classification accuracies for the above algorithms were 81.60%, 98.00%, 95.70%, 98.40%, and 99.20%, respectively. The operation times were 2.01 s, 4.88 s, 3.67 s, 0.36 s, and 308.55 s, respectively. In addition, the five-fold cross-validation classification accuracies with 30 input variables for DT, RF, PLS-DA, LDA, and SVM were 83.75%, 97.95%, 94.75%, 98.35%, and 99.25%, respectively. As a result, LDA was demonstrated to be the best and most efficient tool for rice geographic origin classification assisted by LIBS with high accuracy and analytical speed, which has great potential for rapid identification of adulterated products in agriculture without use of any chemical reagent.

High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy

Stability and sensitivity of toxic elements determination is still unsatisfactory in agricultural product using laser-induced breakdown spectroscopy (LIBS). A simple and low cost sample pretreatment method named solid-liquid-solid transformation method was proposed in this work. The target analytes of cadmium (Cd) and lead (Pb) from rice samples were prepared through ultrasound assisted extraction in hydrochloric acid solution. The solution was dropped on the glass slide after centrifuging process and was further dried on a heater. Finally, the glass slide contained the analytes was carried out for LIBS determination. Compare with conventional pellet method, the spectral intensity of Cd and Pb element were enhanced significantly using LIBS. The limits of detection were 2.8 and 43.7 μg/kg, respectively. The limits of quantification were 9.3 and 145.7 μg/kg, respectively. The results demonstrated that LIBS coupled with ultrasound assisted extraction should be a promising tool to detect toxic elements in rice.

Quantitative Analysis of Nutrient Elements in Soil Using Single and Double-Pulse Laser-Induced Breakdown Spectroscopy

Rapid detection of soil nutrient elements is beneficial to the evaluation of crop yield, and it’s of great significance in agricultural production. The aim of this work was to compare the detection ability of single-pulse (SP) and collinear double-pulse (DP) laser-induced breakdown spectroscopy (LIBS) for soil nutrient elements and obtain an accurate and reliable method for rapid detection of soil nutrient elements. 63 soil samples were collected for SP and collinear DP signal acquisition, respectively. Macro-nutrients (K, Ca, Mg) and micro-nutrients (Fe, Mn, Na) were analyzed. Three main aspects of all elements were investigated, including spectral intensity, signal stability, and detection sensitivity. Signal-to-noise ratio (SNR) and relative standard deviation (RSD) of elemental spectra were applied to evaluate the stability of SP and collinear DP signals. In terms of detection sensitivity, the performance of chemometrics models (univariate and multivariate analysis models) and the limit of detection (LOD) of elements were analyzed, and the results indicated that the DP-LIBS technique coupled with PLSR could be an accurate and reliable method in the quantitative determination of soil nutrient elements.

Application of laser-induced breakdown spectroscopy for real-time detection of contamination particles during the manufacturing process

A stand-off laser-induced breakdown spectroscopy (LIBS) system was developed to determine the elemental composition of contamination particles during semiconductor manufacturing. It successfully detected laboratory-generated monodisperse (size=200  nm and 300 nm) CaCl₂ particles and internally mixed particles of CaCl₂, MgCl₂, NaCl, and KCl. Temperature and pressure effects on the LIBS emission signals were investigated. The peak area and signal-to-noise ratio of the emission lines increased with the temperature (25°C-250°C). Stronger emission lines were observed at higher pressure. Although temperature and pressure affect the LIBS signals, the developed stand-off LIBS could be employed for real-time detection of the elemental composition of contamination particles.

Analysis of Plant Leaves Using Laser Ablation Inductively Coupled Plasma Optical Emission Spectrometry: Use of Carbon to Compensate for Matrix Effects

Direct solid sampling by laser ablation into an inductively coupled plasma synchronous vertical dual view optical emission spectroscope (LA-SVDV-ICP-OES) was used for the elemental analysis of nutrient elements Ca, B, Mn, Mg, K, and Zn and essential (non-metallic) elements P and S in plant materials. The samples were mixed with paraffin as a binder, an approach that provides better cohesion of the particles in the pellets in addition to supplying carbon to serve as an internal standard (atomic line C I 193.027 nm) as a way to compensate for matrix effects, and/or variations in the ablation process. Precision was in the range of 1-8% relative standard deviation (RSD) with limit of detection in the range of 0.4-1 mg/kg^-1 and 25-640 mg/kg^-1 for metallic and non-metallic elements, respectively.

Determination of whey adulteration in milk powder by using laser induced breakdown spectroscopy

A rapid and in situ method has been developed to detect and quantify adulterated milk powder through adding whey powder by using laser induced breakdown spectroscopy (LIBS). The methodology is based on elemental composition differences between milk and whey products. Milk powder, sweet and acid whey powders were produced as standard samples, and milk powder was adulterated with whey powders. Based on LIBS spectra of standard samples and commercial products, species was identified using principle component analysis (PCA) method, and discrimination rate of milk and whey powders was found as 80.5%. Calibration curves were obtained with partial least squares regression (PLS). Correlation coefficient (R(2)) and limit of detection (LOD) values were 0.981 and 1.55% for adulteration with sweet whey powder, and 0.985 and 0.55% for adulteration with acid whey powder, respectively. The results were found to be consistent with the data from inductively coupled plasma - mass spectrometer (ICP-MS) method.

Analysis of bakery products by laser-induced breakdown spectroscopy

In this study, we focused on the detection of Na in bakery products by using laser-induced breakdown spectroscopy (LIBS) as a quick and simple method. LIBS experiments were performed to examine the Na at 589 nm to quantify NaCl. A series of standard bread sample pellets containing various concentrations of NaCl (0.025-3.5%) were used to construct the calibration curves and to determine the detection limits of the measurements. Calibration graphs were drawn to indicate functions of NaCl and Na concentrations, which showed good linearity in the range of 0.025-3.5% NaCl and 0.01-1.4% Na concentrations with correlation coefficients (R(2)) values greater than 0.98 and 0.96. The obtained detection limits for NaCl and Na were 175 and 69 ppm, respectively. Performed experimental studies showed that LIBS is a convenient method for commercial bakery products to quantify NaCl concentrations as a rapid and in situ technique.

Detection of pesticide residues on fruit surfaces using laser induced breakdown spectroscopy

The detection of chlorpyrifos residue on the surface of apples by laser induced breakdown spectroscopy (LIBS) was explored, establishing a new method for the fast detection of pesticide residues on fruit.

Rapid detection of soils contaminated with heavy metals and oils by laser induced breakdown spectroscopy (LIBS)

A laser induced breakdown spectroscopy (LIBS) coupled with the chemometric method was applied to rapidly discriminate between soils contaminated with heavy metals or oils and clean soils. The effects of the water contents and grain sizes of soil samples on LIBS emissions were also investigated. The LIBS emission lines decreased by 59-75% when the water content increased from 1.2% to 7.8%, and soil samples with a grain size of 75 μm displayed higher LIBS emission lines with lower relative standard deviations than those with a 2mm grain size. The water content was found to have a more pronounced effect on the LIBS emission lines than the grain size. Pelletizing and sieving were conducted for all samples collected from abandoned mining areas and military camp to have similar water contents and grain sizes before being analyzed by the LIBS with the chemometric analysis. The data show that three types of soil samples were clearly discerned by using the first three principal components from the spectral data of soil samples. A blind test was conducted with a 100% correction rate for soil samples contaminated with heavy metals and oil residues.