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.

Electrically-controlled near-infrared chiroptical switching of enantiomeric dinuclear ruthenium complexes

Enantiomerically pure dinuclear ruthenium complexes with 1,2-dicarbonylhydrazide as a bridging ligand are optically active in the visible and near infrared spectral regions depending on the oxidation states of the metal centers and are useful as an electrochemically driven near infrared chiroptical switch.

Determination of ethenzamide and acetoaminophen in quaternary powdered samples by near infrared spectroscopy and searching combination moving window partial least squares algorithm: effects of spectral resolution and signal-to-noise ratio

The present study reports an application of the searching combination moving window partial least squares (SCMWPLS) algorithm to the determination of ethenzamide and acetoaminophen in quaternary powdered samples by near infrared (NIR) spectroscopy. Another purpose of the study was to examine the instrumentation effects of spectral resolution and signal-to-noise ratio of the Buchi NIRLab N-200 FT-NIR spectrometer equipped with an InGaAs detector. The informative spectral intervals of NIR spectra of a series of quaternary powdered mixture samples were first located for ethenzamide and acetoaminophen by use of moving window partial least squares regression (MWPLSR). Then, these located spectral intervals were further optimised by SCMWPLS for subsequent partial least squares (PLS) model development. The improved results are attributed to both the less complex PLS models and to higher accuracy of predicted concentrations of ethenzamide and acetoaminophen in the optimised informative spectral intervals that are featured by NIR bands. At the same time, SCMWPLS is also demonstrated as a viable route for wavelength selection.

Bi-doped BaF2 crystal for broadband near-infrared light source

Bi-doped BaF2 crystal was grown by the temperature gradient technique and its spectral properties were investigated. The absorption, emission and excitation spectra were measured at room temperature. Two broadband emissions centered at 1070 and 1500 nm were observed in Bi-doped BaF2 crystal. This extraordinary luminescence should be ascribed to Bi-related centers at distinct sites. We suggest Bi2+ or Bi+ centers adjacent to F vacancy defects are the origins of the observed NIR emissions. (C) 2009 Optical Society of America

Enhanced broadband near-infrared luminescence in transparent silicate glass ceramics containing Yb3+ ions and Ni2+-doped Li Ga5 O8 nanocrystals

Spectral properties of Yb3+/Ni2+ codoped transparent silicate glass ceramics containing LiGa5O8 nanocrystals were investigated. The near-infrared emission intensity of Ni2+ was largely increased with Yb3+ codoping due to Yb3+-> Ni2+ energy transfer. The qualitative calculation of the energy transfer constant Cs-a and rate Ps-a showed that the Yb3+-> Ni2+ energy transfer was much greater than in the opposite direction. Yb3+/Ni2+ codoped glass ceramics with 0.75 mol % Yb2O3 exhibited a near-infrared emission with full width at half maximum of 290 nm and fluorescent lifetime of 920 mu s. The glass ceramics are promising for broadband optical amplification.

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.

Synthesis and Application of Thiadiazoloquinoxaline-Containing Chromophores as Dopants for Efficient Near-Infrared Organic Light-Emitting Diodes

series of a donor-acceptor-donor type of near-infrared (NIR) fluorescent chromophores based on [1,2,5]thiadiazolo[3,4-g]quinoxaline (TQ) as an electron acceptor and triphenylamine as an electron donor are synthesized and characterized. By introducing pendent phenyl groups or changing the pi-conjugation length in the TQ core, we tuned tile energy levels of these chromophores, resulting in the NIR emission in a range from 784 to 868 nm. High thermal stability and glass transition temperatures allow these chromophores to be used as dopant emitters, which can be processed by vapor deposition for the fabrication of organic light-emitting diodes (OLEDs) having the multilayered structure of ITO/MoO3/NPB/Alq(3):dopant emitter/BCP/Alq(3)/LiF/Al. The electroluminescence spectra of the devices based on these new chromophores cover a range from 748 to 870 nm. With 2 wt % of dopant 1, the LED device shows an exclusive NIR emission at 752 nm with the external quantum efficiency (EQE) as high as 1.12% over a wide range of current density (e.g., around 200 mA cm(-2)).