Identification of agricultural Mediterranean soils using mid-infrared photoacoustic spectroscopy

Du, Changwen; Linker, Raphael; Shaviv, A.

doi:10.1016/j.geoderma.2007.10.012

Cited by 70 publications

(28 citation statements)

References 23 publications

(22 reference statements)

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“…The Fourier transform mid-infrared photoacoustic spectroscopy (FTIR-PAS) spectra for the root samples were recorded using a Nicolet 6700 spectrophotometer (Thermo Fisher Scientific, USA) equipped with a photoacoustic cell (Model 300, MTEC, USA) (Du et al 2008). After a dry and scrap sample were placed in the cell-holding cup (diameter 10 mm, height 3 mm), the cell was purged with dry helium at 10 mL min −1 for 10 s and then the sample was scanned 32 times, from 4000 to 500 cm −1 , with a resolution of 4 cm −1 and a mirror velocity of 0.3165 cm s −1 .…”

Section: Characterization Of Functional Groups On Plant Rootsmentioning

confidence: 99%

The forms and distribution of aluminum adsorbed onto maize and soybean roots

Liu

2014

J Soils Sediments

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Purpose The Al forms on maize and soybean roots were investigated to determine the main factors affecting the distribution of Al forms and its relationship with Al plant toxicity. Materials and methods Solution culture experiments were conducted to obtain the fresh roots of maize and soybean. KNO 3 , citric acid, and HCl were used to extract the exchangeable, complexed, and precipitated forms of Al on the roots. Results and discussion The complexed Al was higher than the exchangeable and precipitated Al. Root CECs of soybean and maize were 77 and 55 cmol kg −1 , and functional groups on the soybean roots (262.4 cmol kg −1 ) were greater than on maize roots (210.8 cmol kg −1 ), which resulted in more exchangeable and complexed Al on soybean roots than on maize roots, and was one of the reasons for the increased Al toxicity to soybean. The total and exchangeable Al were the highest on the plant root tips and decreased gradually with increasing distance from the tips. Ca 2+ , Mg 2+ , and NH 4 + cations reduced the exchangeable Al on the roots. Oxalate and malate also reduced the adsorption and absorption of Al by roots, and the effect of oxalate was greater than malate. Conclusions Higher exchangeable and complexed Al on plant roots led to increased Al plant toxicity. Ca 2+ , Mg 2+ , and NH 4 + and oxalate and malate can effectively alleviate Al plant toxicity.

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Section: Characterization Of Functional Groups On Plant Rootsmentioning

confidence: 99%

The forms and distribution of aluminum adsorbed onto maize and soybean roots

Liu

2014

J Soils Sediments

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“…artificial neural networks (ANN) have got much less attention and were rarely explored for the spectral analysis in soil sciences. Du and Zhou (2007) and Du et al ( , 2008 have successfully implemented ANN based on principal components (PCs) obtained from principal component analysis (PCA) on mid infrared (MIR) and photoacoustic MIR soil spectra. Only two examples on using ANN-PC technique for soil analysis with NIR spectroscopy could be found in literature.…”

Section: Introductionmentioning

confidence: 99%

Comparison among principal component, partial least squares and back propagation neural network analyses for accuracy of measurement of selected soil properties with visible and near infrared spectroscopy

et al. 2010

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“…The PCA algorithm ensures that the covariance of any of the components with any other component is zero. As it is quite possible that the PCs accounting for a lesser amount of variance in the data may be significant for the classification task, and also since the computed PCs are uncorrelated to each other, it is always reasonable to step through the first few PCs for building the classification model [21,22,54,55]. In the present work, the optimal number of PCs to be retained for classification task is determined empirically by repeated experiments carried out by stepping through first 15 PCs to build the classification models.…”

Section: Classification Modulementioning

confidence: 99%

Neural Network Ensemble Based CAD System for Focal Liver Lesions from B-Mode Ultrasound

et al. 2014

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A neural network ensemble (NNE) based computeraided diagnostic (CAD) system to assist radiologists in differential diagnosis between focal liver lesions (FLLs), including (1) typical and atypical cases of Cyst, hemangioma (HEM) and metastatic carcinoma (MET) lesions, (2) small and large hepatocellular carcinoma (HCC) lesions, along with (3) normal (NOR) liver tissue is proposed in the present work. Expert radiologists, visualize the textural characteristics of regions inside and outside the lesions to differentiate between different FLLs, accordingly texture features computed from inside lesion regions of interest (IROIs) and texture ratio features computed from IROIs and surrounding lesion regions of interests (SROIs) are taken as input. Principal component analysis (PCA) is used for reducing the dimensionality of the feature space before classifier design. The first step of classification module consists of a five class PCA-NN based primary classifier which yields probability outputs for five liver image classes. The second step of classification module consists of ten binary PCA-NN based secondary classifiers for NOR/Cyst, NOR/HEM, NOR/HCC, NOR/MET, Cyst/HEM, Cyst/HCC, Cyst/MET, HEM/HCC, HEM/MET and HCC/MET classes. The probability outputs of five class PCA-NN based primary classifier is used to determine the first two most probable classes for a test instance, based on which it is directed to the corresponding binary PCA-NN based secondary classifier for crisp classification between two classes. By including the second step of the classification module, classification accuracy increases from 88.7 % to 95 %. The promising results obtained by the proposed system indicate its usefulness to assist radiologists in differential diagnosis of FLLs.

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Identification of agricultural Mediterranean soils using mid-infrared photoacoustic spectroscopy

Cited by 70 publications

References 23 publications

The forms and distribution of aluminum adsorbed onto maize and soybean roots

The forms and distribution of aluminum adsorbed onto maize and soybean roots

Comparison among principal component, partial least squares and back propagation neural network analyses for accuracy of measurement of selected soil properties with visible and near infrared spectroscopy

Neural Network Ensemble Based CAD System for Focal Liver Lesions from B-Mode Ultrasound

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