A New Discrimination Method of Maize Seed Varieties Based on Near-Infrared Spectroscopy

A new discrimination method for the maize seed varieties based on the near-infrared spectroscopy was proposed. The reflectance spectra of maize seeds were obtained by a FT-NIR spectrometer (12 000-4 000 cm(-1)). The original spectra data were preprocessed by first derivative method. Then the principal component analysis (PCA) was used to compress the spectra data. The principal components with the cumulate reliabilities more than 80% were used to build the discrimination models. The model was established by Psi-3 neuron based on biomimetic pattern recognition (BPR). Especially, the parameter of the covering index was proposed to assist to discriminating the variety of a seed sample. The authors tested the discrimination capability of the model through four groups of experiments. There were 10, 18, 26 and 34 varieties training the discrimination models in these experiments, respectively. Additionally, another seven maize varieties and nine wheat varieties were used to test the capability of the models to reject the varieties not participating in training the models. Each group of the experiment was repeated three times by selecting different training samples at random. The correct classification rates of the models in the four-group experiments were above 91. 8%. The correct rejection rates for the varieties not participating in training the models all attained above 95%. Furthermore, the performance of the discrimination models did not change obviously when using the different training samples. The results showed that this discrimination method can not only effectively recognize the maize seed varieties, but also reject the varieties not participating in training the model. It may be practical in the discrimination of maize seed varieties.

Evaluation of the thermal/optical reflectance method for discrimination between char- and soot-EC

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Discrimination of Type 2 diabetic patients from healthy controls by using metabonomics method based on their serum fatty acid profiles

Metabonomics, the study of metabolites and their roles in various disease states, is a novel methodology arising from the post-genomics era. This methodology has been applied in many fields, including work in cardiovascular research and drug toxicology. In this study, metabonomics method was employed to the diagnosis of Type 2 diabetes mellitus (DM2) based on serum lipid metabolites. The results suggested that serum fatty acid profiles determined by capillary gas chromatography combined with pattern recognition analysis of the data might provide an effective approach to the discrimination of Type 2 diabetic patients from healthy controls. And the applications of pattern recognition methods have improved the sensitivity and specificity greatly. (C) 2004 Elsevier B.V. All rights reserved.

Improvement and observation of immunoelectron microscopic method for the localization of frog Rana grylio virus (RGV) in infected fish cells

In this paper, to understand the roles of amorphous structures which were observed within the viromatrix of Rana grylio virus (RGV), an improved immunoelectron microscopy (IEM) method was developed to detect the localization of RGV in carp Epithelipma papulosum cyprinid (EPC) cells. Infected EPC cells were fixed with 4% paraformaldehyde-0.25% glutaraldehyde mixture, dehydrated completely, and embedded in LR White resin. This method allowed good ultrastructural preservation and specific labeling with anti-RGV antibodies. The results of IEM showed that colloidal gold mainly bound to the capsids of viral particles at the stage of viral assembly, while during the viral maturation colloidal gold bound to the envelop of virions. In addition, within the viromatrix, the amorphous structures, including dense floccules, membranous materials and tubules, also had strong colloidal gold signals, revealing that those amorphous structures were participated in RGV assembly. In contrast, no significant gold labeling signals were obtained in negative controls. The present study not only provided further evidence that amorphous structures within the viromatrix were involved in the process of RGV assembly, but also developed an improved IEM method for studying the interaction between iridovirus and host cells. (C) 2006 Elsevier Ltd. All rights reserved.

Binding energy of excitons bound to neutral donors in two-dimensional semiconductors

The binding energies of excitons bound to neutral donors in two-dimensional (2D) semiconductors within the spherical-effective-mass approximation, which are nondegenerate energy bands, have been calculated by a variational method for a relevant range of the effective electron-to-hole mass ratio sigma. The ratio of the binding energy of a 2D exciton bound to a neutral donor to that of a 2D neutral donor is found to be from 0.58 to 0.10. In the limit of vanishing sigma and large sigma, the results agree fairly well with previous experimental results. The results of this approach are compared with those of earlier theories.

Fast Discrimination of Commerical Corn Varieties Based on Near Infrared Spectra

The existing methods for the discrimination of varieties of commodity corn seed are unable to process batch data and speed up identification, and very time consuming and costly. The present paper developed a new approach to the fast discrimination of varieties of commodity corn by means of near infrared spectral data. Firstly, the experiment obtained spectral data of 37 varieties of commodity corn seed with the Fourier transform near infrared spectrometer in the wavenurnber range from 4 000 to 12 000 cm (1). Secondly, the original data were pretreated using statistics method of normalization in order to eliminate noise and improve the efficiency of models. Thirdly, a new way based on sample standard deviation was used to select the characteristic spectral regions, and it can search very different wavenumbers among all wavenumbers and reduce the amount of data in part. Fourthly, principal component analysis (PCA) was used to compress spectral data into several variables, and the cumulate reliabilities of the first ten components were more than 99.98%. Finally, according to the first ten components, recognition models were established based on BPR. For every 25 samples in each variety, 15 samples were randomly selected as the training set. The remaining 10 samples of the same variety were used as the first testing set, and all the 900 samples of the other varieties were used as the second testing set. Calculation results showed that the average correctness recognition rate of the 37 varieties of corn seed was 94.3%. Testing results indicate that the discrimination method had higher precision than the discrimination of various kinds of commodity corn seed. In short, it is feasible to discriminate various varieties of commodity corn seed based on near infrared spectroscopy and BPR.

Linearization Method and Linear Complexity

We focus on the relationship between the linearization method and linear complexity and show that the linearization method is another effective technique for calculating linear complexity. We analyze its effectiveness by comparing with the logic circuit method. We compare the relevant conditions and necessary computational cost with those of the Berlekamp-Massey algorithm and the Games-Chan algorithm. The significant property of a linearization method is that it needs no output sequence from a pseudo-random number generator (PRNG) because it calculates linear complexity using the algebraic expression of its algorithm. When a PRNG has n [bit] stages (registers or internal states), the necessary computational cost is smaller than O(2n). On the other hand, the Berlekamp-Massey algorithm needs O(N2) where N ( 2n) denotes period. Since existing methods calculate using the output sequence, an initial value of PRNG influences a resultant value of linear complexity. Therefore, a linear complexity is generally given as an estimate value. On the other hand, a linearization method calculates from an algorithm of PRNG, it can determine the lower bound of linear complexity.

Roundness parameters in barrier-lagoon systems in northeastern Shandong Peninsula, China: limitations to environmental discrimination

Twenty-five samples from six subenvironments in the barrier-lagoon systems in northeastern Shandong province, China, are examined. A statistical method is used to study the roundness variation of grains of different sizes. Roundness of very fine pebble and very coarse sand varies significantly in different subenvironments. It is possible to discriminate among aqueous depositional environments using the roundness of grains of these sizes. Roundness of grains finer than 0.84 φ is not distinguishable in different subenvironments.

Synthesis and characterization of magnetite dodecahedron nanostructure by hydrothermal method

Magnetite dodecahedral nanocrystals were fabricated using ethlenediamine tetraacetic acid (EDTA)-mediated hydrothermal route. Scanning electron microscopy images displayed that the products were almost dodecahedrons. The length of two different ribs were about 300 and 200 nm, respectively. X-ray diffraction patterns showed that the products were the cubic inverse spinel structure. Fourier transform infrared spectrum directly provided evidence of the EDTA bound to a specific surface of the precipitated magnetic nanocrystal.

Discrimination of herbal medicines by molecular spectroscopy and chemical pattern recognition

The molecular spectroscopy (including near infrared diffuse reflection spectroscopy, Raman spectroscopy and infrared spectroscopy) with OPUS/Ident software was applied to clustering ginsengs according to species and processing methods. The results demonstrate that molecular spectroscopic analysis could provide a rapid, nondestructive and reliable method for identification of Chinese traditional medicine. It's found that the result of Raman spectroscopic analysis was the best one among these three methods. Comparing with traditional methods, which are laborious and time consuming, the molecular spectroscopic analysis is more effective.