Quantitative Multi-Element Analysis in Soil Using 532 nm and 1064 nm Lasers in LIBS Technique

Plasma Chemistry and Plasma Processing - Laser-induced breakdown spectroscopy (LIBS) has been considered a promising tool for agricultural analysis in the recent years due to its advantages over...     

Artificial neural network for Cu quantitative determination in soil using a portable Laser Induced Breakdown Spectroscopy system

Laser Induced Breakdown Spectroscopy (LIBS) is an advanced analytical technique for elemental determination based on direct measurement of optical emission of excited species on a laser induced plasma. In the realm of elemental analysis, LIBS has great potential to accomplish direct analysis independently of physical sample state (solid, liquid or gas). Presently, LIBS has been easily employed for qualitative analysis, nevertheless, in order to perform quantitative analysis, some effort is still required since calibration represents a difficult issue. Artificial neural network (ANN) is a machine learning paradigm inspired on biological nervous systems. Recently, ANNs have been used in many applications and its classification and prediction capabilities are especially useful for spectral analysis. In this paper an ANN was used as calibration strategy for LIBS, aiming Cu determination in soil samples. Spectra of 59 samples from a heterogenic set of reference soil samples and their respective Cu concentration were used for calibration and validation. Simple linear regression (SLR) and wrapper approach were the two strategies employed to select a set of wavelengths for ANN learning. Cross validation was applied, following ANN training, for verification of prediction accuracy. The ANN showed good efficiency for Cu predictions although the features of portable instrumentation employed. The proposed method presented a limit of detection (LOD) of 2.3 mg dm^− 3 of Cu and a mean squared error (MSE) of 0.5 for the predictions.     

Evaluation of the effects of Candidatus Liberibacter asiaticus on inoculated citrus plants using laser-induced breakdown spectroscopy (LIBS) and chemometrics tools

This study investigated the organic and inorganic constituents of healthy leaves and Candidatus Liberibacter asiaticus (CLas)-inoculated leaves of citrus plants. The bacteria CLas are one of the causal agents of citrus greening (or Huanglongbing) and its effect on citrus leaves was investigated using laser-induced breakdown spectroscopy (LIBS) combined with chemometrics. The information obtained from the LIBS spectra profiles with chemometrics analysis was promising for the construction of predictive models to identify healthy and infected plants. The major, macro- and microconstituents were relevant for differentiation of the sample conditions. The models were then applied to different inoculation times (from 1 to 8 months). The models were effective in the classification of 82-97% of the diseased samples with a 95% significance level. The novelty of this method was in the fingerprinting of healthy and diseased plants based on their organic and inorganic contents.     

Measurement of the absolute total electron impact cross section on Cs atoms using a magnetooptical trap

Laser cooling and trapping of neutral atoms has been employed for the measurement of the total electron impact cross sections of the ground state 6² S _1/2 of ¹³³Cs atoms in the energy range from 80 to 500 eV. The total electron impact cross sections of the cold Cs atoms in the MOT were measured by observing the decay of the MOT after the interaction with the electron beam, and were found to depend only on the electron flux and not on the total number of atoms in the MOT. We confirm and extend the existing data on these measurements.     

Discrimination of Genetically Very Close Accessions of Sweet Orange (Citrus sinensis L. Osbeck) by Laser-Induced Breakdown Spectroscopy (LIBS)

The correct recognition of sweet orange (Citrus sinensis L. Osbeck) variety accessions at the nursery stage of growth is a challenge for the productive sector as they do not show any difference in phenotype traits. Furthermore, there is no DNA marker able to distinguish orange accessions within a variety due to their narrow genetic trace. As different combinations of canopy and rootstock affect the uptake of elements from soil, each accession features a typical elemental concentration in the leaves. Thus, the main aim of this work was to analyze two sets of ten different accessions of very close genetic characters of three varieties of fresh citrus leaves at the nursery stage of growth by measuring the differences in elemental concentration by laser-induced breakdown spectroscopy (LIBS). The accessions were discriminated by both principal component analysis (PCA) and a classifier based on the combination of classification via regression (CVR) and partial least square regression (PLSR) models, which used the elemental concentrations measured by LIBS as input data. A correct classification of 95.1% and 80.96% was achieved, respectively, for set 1 and set 2. These results showed that LIBS is a valuable technique to discriminate among citrus accessions, which can be applied in the productive sector as an excellent cost–benefit tool in citrus breeding programs.     

Effect of Er:YAG laser energy on the morphology of enamel/adhesive system interface

The aim of this study was to evaluate in vitro the influence of Er:YAG laser energy variation to cavity preparation on the morphology of enamel/adhesive system interface, using SEM. Eighteen molars were used and the buccal surfaces were flattened without dentine exposure. The specimens were randomly assigned to two groups, according to the adhesive system (conventional total-etching or self-etching), and each group was divided into three subgroups (bur carbide in turbine of high rotation, Er:YAG laser 250 mJ/4 Hz and Er:YAG laser 300 mJ/4 Hz) containing six teeth each. The enamel/adhesive system interface was serially sectioned and prepared for SEM. The Er:YAG laser, in general, produced a more irregular adhesive interface than the control group. For Er:YAG laser 250 mJ there was formation of a more regular hybrid layer with good tag formation, mainly in the total-etching system. However, Er:YAG laser 300 mJ showed a more irregular interface with amorphous enamel and fused areas, for both adhesive systems. It was concluded that cavity preparation with Er:YAG laser influenced on the morphology of enamel/adhesive system interface and the tissual alterations were more evident when the energy was increased.     

Total carbon measurement in whole tropical soil sample

Soils are an important component in the biogeochemical cycle of carbon, storing about four times more carbon than biomass plants and nearly three times more than the atmosphere. Moreover, the carbon content is directly related on the capacity of water retention, fertility, among other properties. Thus, soil carbon quantification in field conditions is an important challenge related to carbon cycle and global climatic changes.     

Evaluation of laser induced breakdown spectroscopy for multielemental determination in soils under sewage sludge application

Laser induced breakdown spectroscopy (LIBS) is an atomic emission spectroscopy technique for simple, direct and clean analysis, with great application potential in environmental sustainability studies. In a single LIBS spectrum it is possible to obtain qualitative information on the sample composition. However, quantitative analysis requires a reliable model for analytical calibration. Multilayer perceptron (MLP), an artificial neural network, is a multivariate technique that is capable of learning to recognize features from examples. Therefore MLP can be used as a calibration model for analytical determinations. Accordingly, the present study proposes to evaluate the traditional linear fit and MLP models for LIBS calibration, in order to attain a quantitative multielemental method for contaminant determination in soil under sewage sludge application. Two sets of samples, both composed of two kinds of soils were used for calibration and validation, respectively. The analyte concentrations in these samples, used as reference, were determined by a reference analytical method using inductively coupled plasma optical emission spectrometry (ICP OES). The LIBS-MLP was compared to a LIBS-linear fit method. The values determined by LIBS-MLP showed lower prediction errors, correlation above 98% with values determined by ICP OES, higher accuracy and precision, lower limits of detection and great application potential in the analysis of different kinds of soils.