João Carlos de Andrade

Determination of organic matter in soil using near-infrared spectroscopy and partial least squares regression

An alternative approach for the determination of organic matter content in soil is proposed, using near infrared spectroscopy and partial least squares regression for data modeling. This method was applied to two different types of soils: Oxisol and Ultisol. One hundred soil samples, collected at different depth intervals, with organic matter content from 0.40 to 4.83 mg g−1 were obtained from the Instituto Agronômico (Campinas-Brazil). For test the reference data were obtained by titration of the excess of Cr(VI) with standard Fe(II) solution, after sample digestion with potassium dichromate in an acid medium in digestion tubes. The organic matter contents determined by the so called digestion tube method were also correlated with those obtained by near infrared spectroscopy, using partial least squares regression. A root mean squares error of prediction equal to 0.20 mg g−1 was obtained. The digestion tube method was also compared with the Walkley–Black method for twelve soil samples and no difference in results for the organic matter determination was found.

Rapid determination of zinc and iron in foods by flow-injection analysis with flame atomic-absorption spectrophotometry and slurry nebulization.

A rapid method of determining zinc and iron in food by flame atomic-absorption spectrophotometry with slurry nebulization into an air-acetylene flame has been developed. A V-groove, clog-free Babington-type nebulizer, coupled to a single-line flow-injection analysis (FIA) system, was employed to introduce the slurry into the spray chamber. Under the FIA conditions described, an injection frequency of 120/hr is possible, with negligible carry-over and memory effects. The calibration graphs were obtained by using various concentrations (up to 0.1 g/ml) of white bean homogenate as standards, rather than solutions. The method has been applied to various kinds of foods, including grains, vegetables, fruits and sausage. Homogenization of semi-prepared samples to form slurries took only 4 min. Relative deviations between results by the slurry and solution methods for both elements averaged 2-3%. Detection limits by the slurry method were 0.3 mug/ml Zn and 0.6 mug/ml Fe.

Restrictions in the use of correlation coefficients in comparing methods for the determination of the micronutrients in soils

Abstract Fifty nine soil samples from the State of Sao Paulo were collected from the plow layer, with about half of these samples presenting low or medium concentrations of micronutrients. Micronutrients were extracted by one of the following solutions: DTPA at pH 7.3, DTPA at pH 5.3, Mehlich‐1 BR, Mehlich‐1 USA, Mehlich‐3, and 0.01 mol L‐1 calcium chloride (CaCl2), and then determined by inductively coupled plasma emission spectrometry (ICP‐AES). Simple linear correlations were calculated for the results of all methods against the DTPA method at pH 7.3. Two sets of calculations were always considered: one including all 59 soil samples and another set including only those samples containing low and medium amounts for each element. Higher correlation coefficients were observed when samples with high contents were included. For example, the range of correlations (R2) obtained for zinc (Zn) varied from 0.41 to 0.98, if all samples were considered in the calculations, but the range decreased to 0.41 ‐ 0.55 if...

Direct voltammetric determination of Mo(VI) in plants: the need for a multivariate study of interferences

A multivariate modelling procedure using a second order composite design showed that the adsorptive stripping voltammetry (AdSV) technique used for molybdenum determination in a N,N-dimethylformamide (DMF)–ethanol–water homogeneous ternary solvent system (HTSS) using-benzoinoxime (BO) as the complexing agent and a sodium acetate–acetic acid buffer as the supporting electrolyte is much more tolerant to the presence of phosphorous (as phosphate) and iron than it could be presumed. Instead of the concentration ratios of P/Mo = 100 and Fe/Mo = 500, determined by univariate experiments, these values were respectively raised to 97,500 and 4200 when the phosphate and Fe(III) levels are varied simultaneously from 0.625 to 2.500 and from 0.006 to 0.150 mg l −1 , respectively, in the voltammetric cell, keeping the molybdenum concentration constant at 3.00 gl −1 . This allowed us to propose a straightforward AdSV–HTSS procedure for the determination of Mo(VI) in plants. The AdSV results compared favourably with those obtained by using graphite furnace atomic absorption spectrometry (GFAAS) and with the results of samples from the International Plant-Analytical Exchange (IPE) programme of Wageningen University (The Netherlands).

Determination of molybdenum in steel by adsorptive stripping voltammetry in a homogeneous ternary solvent system.

A new alternative approach for the determination of molybdenum in steel is proposed, using adsorptive stripping voltammetry (AdSV). The determinations are performed in a homogeneous ternary solvent system (HTSS) composed of N,N-dimethylformamide, ethanol and water, with alpha-benzoinoxime (alpha BO) as the complexing agent and a sodium acetate-acetic acid buffer as the support electrolyte. The HTSS composition was optimized by mixture design modelling. The AdSV measurements were performed in the differential pulse mode using an accumulation potential of -1050 mV. Under these optimized experimental conditions, the Mo(VI)-alpha BO reduction current peak potential is observed at potentials near -1250 mV, much lower than those usually reported, and the calibration plot follows the polynomial equation I = 0.359 + 0.265 [CMo(VI)] - 0.015 [CMo(IV)]2 (r2 = 0.997), for Mo concentrations up to 10.0 micrograms L-1. There is a linear range in this calibration plot for Mo(VI) concentrations up to 0.20 microgram L-1, defined by the equation I = 0.353 + 0.385 [CMo(VI)] (r2 = 0.980). In both cases, I is the absolute value for the current in microA and CMo(VI) is the concentration of Mo in microgram L-1. The detection limit for this linear concentration range was estimated as 20 pg L-1. A RSD of 0.43% is associated with the signals at a Mo(VI) level of 0.72 microgram L-1. From the common method-interfering species tested, only iron at Fe/Mo(VI) ratios above 500 and vanadium and tungsten at M/Mo(VI) ratios above 100 appear to affect the analytical response significantly. Phosphorous may also reduce the analytical signal at P/Mo(VI) ratios above 100, due to the formation of the competitive P-Mo complex. The suggested routine procedure was tested by analyzing four stainless steel samples and the results compared well with the ICP-AES measurements. The higher sensitivity of this method permits direct determination of Mo(VI) in steels, eliminating the need of analyte concentration or separation steps in the sample processing procedure.

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.

PLS regression using real sample calibration for aluminum and iron determination in plant extracts

Real samples were used for PLS model calibration and validation steps, showing that this approach can be of value in preventing deviations in the results caused by the matrix effects for the simultaneous spectrophotometric determination of aluminum and iron in plant extracts. One hundred UV-vis spectra, obtained from samples of the 1997 to 2000 International Plant-Analytical Exchange (IPE) program (The Netherlands), were used for model development, with ICP-AES aluminum and iron determinations as reference values for model calculation. The plant extracts were analyzed both by ICP-AES and by the PLS models developed in this work, using calibrations with both aqueous standard solutions and with real sample extracts. In addition, since the use of smaller calibration sets could be of value in reducing both the cost and the time of analysis, sets with fewer calibration samples were also investigated, with the help of the Kennard and Stone algorithm for sample selection. Comparison of the predictability of the best model obtained with each calibration set was made using the ratio of their relative root mean square error (%RMSEV) for samples in the validation set, for aluminum or iron determinations, and were compared against F-test tabulated values. For all the models developed with real samples, the differences in the %RMSEV values for the aluminum or iron determinations were found not to be statistically significant, at a confidence level of 95%. Although it was observed that the aluminum, but not the iron, determinations with the PLS 2 model prepared with aqueous standards tend to be slightly lower than the ICP-AES determinations, this model has a good global prediction ability, as observed through the correlation curves presented, and can be used for screening determinations or for other agricultural purposes.

O ajuste de funções matemáticas a dados experimentais

The least square method is analyzed. The basic aspects of the method are discussed. Emphasis is given in procedures that allow a simple memorization of the basic equations associated with the linear and non linear least square method, polinomial regression and multilinear method.

Study of the Mo(VI) catalytic response in the oxidation of iodide by hydrogen peroxide using a monosegmented continuous-flow system

Abstract Fractional factorial, modified simplex and response surface studies of the Mo(VI)-catalysed and non-catalysed oxidation of iodide by hydrogen peroxide in acidic were executed using a monosegmented continouos-flow system (MCFS). As this reaction is commonly used for the spectrophotometric catalytic determination of Mo(VI), the behavior of the analytically useful response, Δ A , the difference of the average absorbance values of the Mo(VI)-catalysed and non-catalysed reactions, was studied over a large range of experimental conditions. The effects of simultaneous changes in the sample flow-rate, the H 2 SO 4 , KI and H 2 O 2 concentrations and the reaction time on the signals were measured. The optimum concentrations found using MCFS are 0.0665, 0.1528 and 0.0041 M for H 2 SO 4 , KI and H 2 O 2 , respectively. Rigorous control of the acid concentration is essential to maintain the sensitivity of the analytical signal for operating conditions close to the optimum values recommended here. On the other hand, the Δ A values are much less sensitive to variations in the H 2 O 2 concentration. Increasing KI concentrations can improve the sensitivity but can also cause baseline instability. The response surface is convenient for visualizing the overall behavior of the system for the experimental control values investigated.

Pruning neural network for architecture optimization applied to near-infrared reflectance spectroscopic measurements. Determination of the nitrogen content in wheat leaves

The pruning neural network, based on the algorithm called optimum brain surgeon, was used for network architecture optimization. This network pruning procedure was applied for estimating the nitrogen contents in wheat leaves, using near-infrared diffuse reflectance spectroscopy. The results obtained with pruning were compared with those obtained by using ordinary procedures with neural networks, partial least squares, polynomial partial least squares and neural networks/partial least squares methodologies. Comparison of the results with those obtained by the conventional Kjeldahl method showed that the results with pruning neural networks were as good as those with ordinary neural networks and with PLS/neural networks, but better than those with the other methodologies. Although the comparison was performed for one data set, the pruning procedure has the advantage of introducing an automatic architecture optimization, which is cumbersome when performed by the other neural network procedures used in this work, generating a simplified model with better generalization abilities.