An artificial neural network (ANN) calibration model was developed to determine aluminum in the presence of iron in soil extracts, using xylenol orange as chromogenic reagent. The spectral data of synthetic mixtures of Al(3+) and Fe(3+) as well as of the soil extracts, were recorded in the range between 410 and 580 nm. Method validation was carried out using 18 soil extracts. The results gave good linear correlations between the ANN model and the ICP OES measurements for both species.241147-5
We are evaluating artificial neural networks (ANNs) as tools for assessing changes in soil microbial...
International audienceThe assessment of copper and chromium concentrations in plants requires the qu...
The accurate identification of the nitrogen content in crop plants is extremely important since it i...
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)An artificial neural network (AN...
Nowadays, due to environmental concerns, fast on-site quantitative analyses of soils are required. L...
International audienceArtificial neural networks were applied to process data from on-site LIBS anal...
International audienceDetermination of trace elements in soils with laser-induced breakdown spectros...
The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to ...
In this paper, by using of laser induced breakdown spectroscopy (LIBS) method, the elemental concent...
International audienceThe assessment of chromium concentrations in plants requires the quantificatio...
The aim of this paper is to decide on heavy metal levels based on ecological parameters by effective...
An artificial neural network (ANN) has been trained with real-sample PIXE (particle X-ray induced em...
Increasing the working calibration range by means of artificial neural networks for the determinatio...
Soil physical and chemical analyses are relatively high-cost and time-consuming procedures. In the s...
A method for predicting the five species contents of cadmium was developed by combining the back-pro...
We are evaluating artificial neural networks (ANNs) as tools for assessing changes in soil microbial...
International audienceThe assessment of copper and chromium concentrations in plants requires the qu...
The accurate identification of the nitrogen content in crop plants is extremely important since it i...
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)An artificial neural network (AN...
Nowadays, due to environmental concerns, fast on-site quantitative analyses of soils are required. L...
International audienceArtificial neural networks were applied to process data from on-site LIBS anal...
International audienceDetermination of trace elements in soils with laser-induced breakdown spectros...
The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to ...
In this paper, by using of laser induced breakdown spectroscopy (LIBS) method, the elemental concent...
International audienceThe assessment of chromium concentrations in plants requires the quantificatio...
The aim of this paper is to decide on heavy metal levels based on ecological parameters by effective...
An artificial neural network (ANN) has been trained with real-sample PIXE (particle X-ray induced em...
Increasing the working calibration range by means of artificial neural networks for the determinatio...
Soil physical and chemical analyses are relatively high-cost and time-consuming procedures. In the s...
A method for predicting the five species contents of cadmium was developed by combining the back-pro...
We are evaluating artificial neural networks (ANNs) as tools for assessing changes in soil microbial...
International audienceThe assessment of copper and chromium concentrations in plants requires the qu...
The accurate identification of the nitrogen content in crop plants is extremely important since it i...