Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

Predicting rapeseed oil content with near-infrared spectroscopy

The objective of this work was to establish a calibration equation and to estimate the efficiency of near-infrared reflectance (NIR) spectroscopy for evaluating rapeseed oil content in Southern Brazil. Spectral data from 124 half-sib families were correlated with oil contents determined by the chemical method. The accuracy of the equation was verified by coefficient of determination (R²) of 0.92, error of calibration (SEC) of 0.78, and error of performance (SEP) of 1.22. The oil content of ten genotypes, which were not included in the calibration with NIR, was similar to the one obtained by the standard chemical method. NIR spectroscopy is adequate to differentiate oil content of rapeseed genotypes.

High pressure near infrared study of the mutated light-harvesting complex LH2

The pressure sensitivities of the near infrared spectra of the light-harvesting (LH2) complex and a mutant complex with a simplified BChl-B850 binding pocket were compared. In the mutant an abrupt change in the spectral properties occurred at 250 MPa, which was not observed with the native sample. Increased disorder due to collapse of the chromophore pocket is suggested.

Discrimination of native wood charcoal by infrared spectroscopy

Brazil is one of the largest producers and consumers of charcoal in the world. About 50% of its charcoal comes from native forests, with a large part coming from unsustainable operations. The anatomic identification of charcoal is subjective; an instrumental technique would facilitate the monitoring of forests. This study aimed to verify the feasibility of using medium and near infrared reflectance spectroscopy to discriminate native (ipê) from plantation charcoals (eucalyptus). Principal Components Analysis, followed by Discriminant Factorial Analysis formed two different groups indicated by Mahalanobis distances of 40.6 and 80.3 for near and mid infrared, respectively. Validation of the model showed 100% efficacy.

Nucleotide excision repair pathway assessment in DNA exposed to low-intensity red and infrared lasers

Low-intensity lasers are used for prevention and management of oral mucositis induced by anticancer therapy, but the effectiveness of treatment depends on the genetic characteristics of affected cells. This study evaluated the survival and induction of filamentation of Escherichia coli cells deficient in the nucleotide excision repair pathway, and the action of T4endonuclease V on plasmid DNA exposed to low-intensity red and near-infrared laser light. Cultures of wild-type (strain AB1157) E. coli and strain AB1886 (deficient in uvrA protein) were exposed to red (660 nm) and infrared (808 nm) lasers at various fluences, powers and emission modes to study bacterial survival and filamentation. Also, plasmid DNA was exposed to laser light to study DNA lesions produced in vitro by T4endonuclease V. Low-intensity lasers:i) had no effect on survival of wild-type E. coli but decreased the survival of uvrA protein-deficient cells,ii) induced bacterial filamentation, iii) did not alter the electrophoretic profile of plasmids in agarose gels, andiv) did not alter the electrophoretic profile of plasmids incubated with T4 endonuclease V. These results increase our understanding of the effects of laser light on cells with various genetic characteristics, such as xeroderma pigmentosum cells deficient in nucleotide excision pathway activity in patients with mucositis treated by low-intensity lasers.

Low-intensity red and infrared laser effects at high fluences on Escherichia coli cultures

Semiconductor laser devices are readily available and practical radiation sources providing wavelength tenability and high monochromaticity. Low-intensity red and near-infrared lasers are considered safe for use in clinical applications. However, adverse effects can occur via free radical generation, and the biological effects of these lasers from unusually high fluences or high doses have not yet been evaluated. Here, we evaluated the survival, filamentation induction and morphology of Escherichia coli cells deficient in repair of oxidative DNA lesions when exposed to low-intensity red and infrared lasers at unusually high fluences. Cultures of wild-type (AB1157), endonuclease III-deficient (JW1625-1), and endonuclease IV-deficient (JW2146-1) E. coli, in exponential and stationary growth phases, were exposed to red and infrared lasers (0, 250, 500, and 1000 J/cm2) to evaluate their survival rates, filamentation phenotype induction and cell morphologies. The results showed that low-intensity red and infrared lasers at high fluences are lethal, induce a filamentation phenotype, and alter the morphology of the E. coli cells. Low-intensity red and infrared lasers have potential to induce adverse effects on cells, whether used at unusually high fluences, or at high doses. Hence, there is a need to reinforce the importance of accurate dosimetry in therapeutic protocols.

Multi-temporal analysis of radiometric changes in satellite images of forest edges to infer selective-logging areas in the Amazon forest

Radiometric changes observed in multi-temporal optical satellite images have an important role in efforts to characterize selective-logging areas. The aim of this study was to analyze the multi-temporal behavior of spectral-mixture responses in satellite images in simulated selective-logging areas in the Amazon forest, considering red/near-infrared spectral relationships. Forest edges were used to infer the selective-logging infrastructure using differently oriented edges in the transition between forest and deforested areas in satellite images. TM/Landsat-5 images acquired at three dates with different solar-illumination geometries were used in this analysis. The method assumed that the radiometric responses between forest with selective-logging effects and forest edges in contact with recent clear-cuts are related. The spatial frequency attributes of red/near infrared bands for edge areas were analyzed. Analysis of dispersion diagrams showed two groups of pixels that represent selective-logging areas. The attributes for size and radiometric distance representing these two groups were related to solar-elevation angle. The results suggest that detection of timber exploitation areas is limited because of the complexity of the selective-logging radiometric response. Thus, the accuracy of detecting selective logging can be influenced by the solar-elevation angle at the time of image acquisition. We conclude that images with lower solar-elevation angles are less reliable for delineation of selecting logging.

Numerical modeling of the effect of variation of boundary conditions on vadose zone hydraulic properties

An accurate estimation of hydraulic fluxes in the vadose zone is essential for the prediction of water, nutrient and contaminant transport in natural systems. The objective of this study was to simulate the effect of variation of boundary conditions on the estimation of hydraulic properties (i.e. water content, effective unsaturated hydraulic conductivity and hydraulic flux) in a one-dimensional unsaturated flow model domain. Unsaturated one-dimensional vertical water flow was simulated in a pure phase clay loam profile and in clay loam interlayered with silt loam distributed according to the third iteration of the Cantor Bar fractal object Simulations were performed using the numerical model Hydrus 1D. The upper and lower pressure heads were varied around average values of -55 cm for the near-saturation range. This resulted in combinations for the upper and lower constant head boundary conditions, respectively, of -50 and -60 cm, -40 and -70 cm, -30 and -80 cm, -20 and -90 cm, and -10 and -100 cm. For the drier range the average head between the upper and lower boundary conditions was set to -550 cm, resulting in the combinations -500 and -600 cm, -400 and -700 cm, -300 and -800 cm, -200 and -900 cm, and -100 and -1,000 cm, for upper and lower boundary conditions, respectively. There was an increase in water contents, fluxes and hydraulic conductivities with the increase in head difference between boundary conditions. Variation in boundary conditions in the pure phase and interlayered one-dimensional profiles caused significant deviations in fluxes, water contents and hydraulic conductivities compared to the simplest case (a head difference between the upper and lower constant head boundaries of 10 cm in the wetter range and 100 cm in the drier range).

Espectroscopia de infravermelho na determinação da textura do solo

A aplicação de técnicas espectroscópicas que utilizam a radiação infravermelha (NIRS-Near Infrared Spectroscopy e DRIFTS-Diffuse Reflectance Fourier Transformed Spectroscopy) na análise inorgânica do solo tem sido proposta desde a década de 1970, mas até os dias atuais são raros os métodos implementados rotineiramente no Brasil. Isso deve-se à dificuldade em construir modelos de calibração, por meio de métodos estatísticos multivariados, utilizando-se amostras reais de solo, de constituição complexa, que varia geograficamente e de acordo com o manejo. Por isso, os objetivos deste trabalho foram construir modelos de calibração em NIRS e DRIFTS para a quantificação das frações de argila e areia, em amostras de solos de classes diferentes - Latossolo Vermelho (predominante), Nitossolo, Argissolo Vermelho e Neossolo Quartzarênico - e avaliar qual dessas duas técnicas é mais adequada para essa finalidade, assim como a interferência do agrupamento de amostras e da seleção de variáveis espectrais na qualidade desses modelos. Para isso, valores de referência obtidos pelo método do densímetro, método largamente utilizado nos laboratórios de análise de solo, foram correlacionados com valores de absorbância em NIRS e DRIFTS pela ferramenta estatística PLS (Partial Least Squares), obtendo-se altos coeficientes de determinação (R²), de 0,95, 0,90 e 0,91 para argila, silte e areia, respectivamente, na validação externa. Isso confirma a aplicabilidade das técnicas espectroscópicas na análise granulométrica do solo para fins agrícolas. O agrupamento das amostras segundo a localização e a seleção de variáveis espectrais pouco influenciou na qualidade dos modelos. A técnica espectroscópica mais indicada para essa finalidade foi a DRIFTS.

Multispectral remote sensing for site-specific nitrogen fertilizer management

The objective of this work was to evaluate the use of multispectral remote sensing for site-specific nitrogen fertilizer management. Satellite imagery from the advanced spaceborne thermal emission and reflection radiometer (Aster) was acquired in a 23 ha corn-planted area in Iran. For the collection of field samples, a total of 53 pixels were selected by systematic randomized sampling. The total nitrogen content in corn leaf tissues in these pixels was evaluated. To predict corn canopy nitrogen content, different vegetation indices, such as normalized difference vegetation index (NDVI), soil-adjusted vegetation index (Savi), optimized soil-adjusted vegetation index (Osavi), modified chlorophyll absorption ratio index 2 (MCARI2), and modified triangle vegetation index 2 (MTVI2), were investigated. The supervised classification technique using the spectral angle mapper classifier (SAM) was performed to generate a nitrogen fertilization map. The MTVI2 presented the highest correlation (R²=0.87) and is a good predictor of corn canopy nitrogen content in the V13 stage, at 60 days after cultivating. Aster imagery can be used to predict nitrogen status in corn canopy. Classification results indicate three levels of required nitrogen per pixel: low (0-2.5 kg), medium (2.5-3 kg), and high (3-3.3 kg).

Redes neurais e suas aplicações em calibração multivariada

Neural Networks are a set of mathematical methods and computer programs designed to simulate the information process and the knowledge acquisition of the human brain. In last years its application in chemistry is increasing significantly, due the special characteristics for model complex systems. The basic principles of two types of neural networks, the multi-layer perceptrons and radial basis functions, are introduced, as well as, a pruning approach to architecture optimization. Two analytical applications based on near infrared spectroscopy are presented, the first one for determination of nitrogen content in wheat leaves using multi-layer perceptrons networks and second one for determination of BRIX in sugar cane juices using radial basis functions networks.

Determination of the HMX and RDX content in synthesized energetic material by HPLC, FT-MIR, and FT-NIR spectroscopies

A new method has been developed for determining the content of mixtures of octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) and hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), the HMX/RDX ratio, in explosive compositions by Fourier transform infrared spectroscopy (FT-IR), in the regions MIR (mid infrared) and NIR (near infrared) with reference values obtained by chromatographic analysis (HPLC). Plots of relative MIR (A917 / A783) or NIR absorbance values (A4412 / A4317) versus HMX/RDX ratio determined by HPLC analysis revealed good linear relationships.

Espectroscopia de correlação bidimensional: fundamentos, aplicações e perspectivas

This paper presents the basic theory of generalized two-dimensional correlation spectroscopy. This method is applicable to various types of spectroscopy, including Infrared, Near Infrared and Raman Spectroscopy and it emphasizes spectral features not readily observable in conventional one-dimensional spectra. Some applications are cited, including work developed in Brazil.

Determinação de açúcar total em café cru por espectroscopia no infravermelho próximo e regressão por mínimos quadrados parciais

In this work a fast method for the determination of the total sugar levels in samples of raw coffee was developed using the near infrared spectroscopy technique and multivariate regression. The sugar levels were initially obtained using gravimety as the reference method. Later on, the regression models were built from the near infrared spectra of the coffee samples. The original spectra were pre-treated according to the Kubelka-Munk transformation and multiplicative signal correction. The proposed analytical method made possible the direct determination of the total sugar levels in the samples with an error lower by 8% with respect to the conventional methodology.

LS-SVM: uma nova ferramenta quimiométrica para regressão multivariada. Comparação de modelos de regressão LS-SVM e PLS na quantificação de adulterantes em leite em pó empregando NIR

Least-squares support vector machines (LS-SVM) were used as an alternative multivariate calibration method for the simultaneous quantification of some common adulterants found in powdered milk samples, using near-infrared spectroscopy. Excellent models were built using LS-SVM for determining R², RMSECV and RMSEP values. LS-SVMs show superior performance for quantifying starch, whey and sucrose in powdered milk samples in relation to PLSR. This study shows that it is possible to determine precisely the amount of one and two common adulterants simultaneously in powdered milk samples using LS-SVM and NIR spectra.