The spatial amplitude modulation for spectropolarimetry measurement technology modulates polarization information to spatial dimension vertical to spectral dimension by modulation module composed of wedges and polarizers. Polarization information and spectral information can be acquired at the same time with a single observation. Firstly, this paper explores the basic principle of spatial amplitude modulation for spectropolarimetry measurement technology. Then, theoretical simulation and experimental research is carried on. By comparing the simulation and experimental images and verify the reliability of the experiment. The theoretical simulation scheme and experimental scheme is proposed. The incident polarized light (Q=0, U=1, V=0 and Q=1, U=0, V=0) is used in the experiment respectively.10 sets of data are sampled in the range of 500~600 nm and exit polarized light is demodulated through the least square method. According to the experimental results, the error between linear polarization degree of the demodulation incident light and reference incident light is less than 2.5% and 4% and the error of polarization angle is less than 1.8% and 2%, which verifies the feasibility of the experiment and algorithm, the brief analysis of the double combo wedges center error influence on the polarization measurement, the results show that center error is greatly influenced on Q and V.

Fused silica glass is a kind of indispensable material in high-energy laser system, and the damage of it has been one of the bottlenecks restricting the energy of system. In this paper, laser pulse shock wave was used to break down the fused glass samples, then the cause of the morphology of fractures on fused silica glass surface as well as internal phase transition were investigated experimentally and theoretically by multi-spectrum detecting of the samples before and after fracture, and the relationship between fracture morphologies and phase transition structure was explained from macro to micro. The fracture of the fused silica was induced by laser plasma shock wave, and during the shock wave, the tip of hoop stress produced from the inside glass would promote the crack propagation outward. We found that the whole fracture region could be divided into hackle zone, mist zone and mirror zone by morphology differences produced by the tip of hoop stress. The transmittance spectra and energy dispersive spectrometer were used to detect the samples before and after fracture. The results showed that the decrease of the transmittance and band gap of the glass were induced by the cracks, and the oxygen free or absent appeared in the fracture zone. Using the Raman spectrum to detect the different morphological areas of samples before and after broken, we found that the Si—O—Si band of fused glass breakage and recombination could reduce the relative content of three- and four-number rings structures corresponding to the stishovite and coesite of hackle zone, mist zone and mirror zone at the macro level. This kind of changes destroyed the mesh topology severely and induced the material fracture zone transforming to a higher density phase. From the micro level, the non-bridging oxygen hole center and E’center led to the decrease of the optical band gaps as well as transmittance which seriously affected the performance of glass.

Paint thickness management has a significant impact on waterproofing, rust-proof function and color effects of products in the field of automotive, aircraft, ships, etc. However, commercially available coating thickness meters are contact-type, and it is difficult to determine the individual paint thickness for each layer of the multilayer coating directly. In this paper, the terahertz pulse waveforms of samples were detected with reflection terahertz time-domain spectroscopy (THz-TDS) system, and the simple single-point thickness measurement model was established based on the time-of-flight measurement of the pulse echo. Besides, the refractive indexes of 12 kinds of paint samples coated on aluminum panels were calculated from the linear relationship between the optical thickness and geometrical thickness, which was fitted by the least squares method. It was found that there was a big difference of refractive index between the metallic paint and nonmetallic paint in the terahertz band, and the measuring refractive index was 5.15 for shining silver paint and 2.64 for white paint. The thickness of monolayer white paint sample was measured by detecting the thickness of 50 points in the region that the thickness distribution was uniform, and the average value of thickness was 72 μm with an error of 4 μm when the reference standard was the data measured by the electromagnetic/eddy current thickness meter. By two-dimensional (2-D) scanning, the observed uniformity of the thickness distribution of two-layer paint sample was (233±13) μm for white paint and (130±11) μm for primer. Similarly, the individual paint thickness for each layer and the distribution uniformity of the three-layer paint black samples or silver samples was determined by analyzing the thickness 2-D map. The results showed that terahertz pulse spectroscopy provided a feasible method of measuring film thickness and assessing uniformity of 1~3 layer paint, and the method could provide a higher thickness resolution for metallic paint. It was easy to assess the quality of the multilayer paint with the thickness data and 2-D distribution information extracted from terahertz pulsed waveforms detected in non-contact way.

In order to improve the measurement precision of identification models, multisource information fusion technique was employed to identify four types of wheat grain (normal, worm-eaten, moldy, and sprouting wheat grains). The terahertz (THz) spectra of wheat grains with various degrees of deterioration were investigated; classification fusion models were constructed by using THz absorption spectra combined with refractive index spectra. The adaboost and SVM were used in the feature level fusion models. The results showed that the different wheat samples were identified with an accuracy of nearly 95%. Furthermore, fusion models results of wheat detection were compared with results from other methods, the comparisons showed that the recognition ratio of fusion models had a great improvement, and the SVM model outperformed the others.

Terahertz wave imaging has many advantages such as small ionizing radiation and high discrimination of organic matter, so it is very suitable for non-contact, non-destructive imaging detection. However, this imaging method is susceptible to unavoidableproblems such as disturbance of electromagnetic environment and fluctuation ofequipment power, which makes it difficult to obtain high resolution terahertzimages. In this paper, terahertz imaging is realized by using the terahertz continuous-wave source imaging system. The terahertz images of four samples of cards, leaves, coins and keys are denoised by ourimproved threshold gray-scale transformation algorithm. Then, the images are sharpened and enhanced by the Laplacian operator. The results are evaluated bymean square error and peak signal to noise ratio estimation. After the denoising, the estimated peak signal to noise ratio of some samples increased by 4～5 dB, so the image quality was improved obviously. This research proves that the built-up terahertz imaging system has a pomosing application prospect.

In a hydrothermal atmosphere with high temperature and long reaction time, a kind of special rare earth doped fluoride microcrystal was obtained with Sc3+ co-doping. The crystal phase and morphology of as-prepared samples were characterized with X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray detector (EDX) and element mapping. It is found that the Sc3+-free sample can be ascribed to the pure hexagonal NaGdF4, and the Sc3+-doped samples are composed of hexagonal NaGdF4- and monoclinic Na3ScF6-based microcrystals. With increasing of the doped concentration of Sc3+, the morphology of NaGdF4-based microcrystal changes from lantern with cracked ends to octadecahedron with smooth surfaces, accomplished with a decreased size. It is worth mentioning that the concentration of Sc3+ that really entered into the host lattice is much less than the Sc3+ concentration in the precursor. Excited by 980 nm laser, the upconversion emission spectrum of single microcrystal was obtained by laser scanning confocal microscopy technology. For a single NaGdF4∶Yb3+,Er3+ microcrystal, the significant upconversion fluorescence regulation was obtained by doping a few Sc3+ into the host lattice, and the relative intensity of the green upconversion emission (2H11/2/4S3/2→4I15/2) to the red counterpart (4F9/2→4I15/2) increases gradually with the increasing of Sc3+ doped concentration. Combining with the suggested upconversion mechanisms, the influence of Sc3+ doped concentration on the rise time of upconverion fluorescence decay curve and the dependence of integrated intensity of upconverion emission band vs excitation power have been explored. It is found that the rise time of the upconversion fluorescence decay curve decreases gradually with the increase of the doped concentration of Sc3+, which confirms that the energy transfer rate (from Yb3+ to Er3+) obtains a significant increase by the introduction of Sc3+. It makes the population of 2H11/2/4S3/2 excited state easier than the 4F9/2 counterpart, then induces the considerable upconversion fluorescence regulation. As the emission color of the NaGdF4-based microcrystal is easy to adjust, it is excepted to show a great potential in the fields of fluorescence anti-counterfeiting, optical waveguide, and so on. The upconversion fluorescence regulation of single rare earth doped microcrystal induced by codoping with small radius ion can be applied to other luminous hosts.

Ultrasonic synthesis of carbon dots has broad application prospects because of its simple process, low cost and less secondary pollution. To optimize the technological parameters of ultrasonic synthesis, carbon dots samples were prepared with different critical process parameters. Emission and excitation spectra were measured, and the effects of quantum dot concentration, types of solvent, auxiliary agent type and concentration, and ultrasonic power and time on luminescence properties of carbon dots were analyzed. The results showed that carbon dots prepared by ultrasonic had a excitation wavelength dependence, and their emission peaks significantly changed with the excitation wavelengths. When carbon dots concentrations increased, their Luminous intensities first increased and then decreased because of the radiation energy transfers and quantum dots reunion. Due to solvent effect, luminous intensities of carbon dots in ethanol were stronger than that in water, and wavelengths of carbon dots in ethanol were shorter than that in water. And the greater the concentrations of carbon dots were, the more obvious the wavelengths of emission spectra moved. Compared with hydrochloric acid, carbon dots prepared with sodium hydroxide as adjuvant had a better surface passivation and stronger luminous intensities. Besides, surface passivation of carbon dots could be improved by increasing the NaOH concentration, and much more carbon dots could be obtained by increasing ultrasonic power or time appropriately, but if the ultrasonic time was too long, carbon dots were prone to reunite quenching. The above analysis of influencing factors provides a theoretical basis for parameter optimization of carbon quantum dots prepared by ultrasonic, which is conducive to the mass production and application of carbon quantum dots at a low cost.

Near-ultraviolet phosphors SrAl2Si2O8∶xCe3+(x=0.01, 0.05%, 0.10% and 0.30%) were synthesized with high temperature solid state method. X-ray diffraction (XRD) and scanning electron microscope (SEM) were used to reflect crystal phase structure, and the luminescent properties of fluorescent powder were characterized with emission spectrum (PL) and excitation spectrum (PLE). Under ultraviolet-B (UVB) irradiation excitation, wide emission bands were observed in ultraviolet-A (UVA) region, which were assigned to the 5d→2F5/2 and 5d→2F7/2 transitions of Ce3+. Along with a redshift of the emission peak about 23nm, the luminescence intensity of SrAl2Si2O8 phosphor increased first and then decreased, when Ce3+ doping contents had been increased. The diversity of emission behavior under selected 280 and 325 nm excitation shows that SrAl2Si2O8∶Ce3+ have luminescence centers with two different natures, and that was further confirmed by the obviously distinct excitation spectral shapes of 320 and 390 nm emissions. Ce3+ gives priority to instead Sr2+ owing to the compatibility of ionic radius, and the crystallograhic sites are deduced by Van Uitert formula. The results indicate that Ce(Ⅰ) luminescence center originates from nine coordination of the Ce3+ ions in low concentration doping, and Ce(Ⅱ) center is due to the fact that effective coordination numbers of partial Ce3+ decrease to 8 in high concentration doping cases. The emission bands centered at 348 nm under 280 nm excitation are derived from the cooperation of both Ce(Ⅰ) and Ce(Ⅱ), and that located at 378 nm under 325 nm excitation are mainly attributed to Ce(Ⅱ). Strong near-ultraviolet fluorescence of Ce3+ under ultraviolet excitation reveals that SrAl2Si2O8∶Ce3+ phosphors are one potential material suitable for developing UV fluorescent light source.

The applications of atmospheric carbon isotope are becoming more and more important, which are used widely in the transfer tracer of environmental pollution and the geochemical development. So it is significative to develop novel technologies for carbon isotope detection. Currently, the laser absorption spectroscopy compared with other techniques, which has great advantages of small volume, and high sensitivity which realises real-time online testing,. A large number of researchers have paid close attention to gas isotope probing with laser absorption spectroscopy. In this paper, the tunable semiconductor laser DFB of 2.7 μm wavelength is studied as to the performance. At the same time, the absorption lines of 12CO2 and 13CO2 isotopic molecules are chosen according to selection principles of the characteristics and the isotope molecules absorption line. On the basis, the appropriate wavelength from the laser output is determined. Afterwards, the δ13C isotopic abundances of the CO2 molecule are probed in the atmosphere by the laser absorption spectroscopy under the help of the new multi-pass cell with the 690.3 m optical path length.

In order to explore an efficient method of timber species identification, the near-infrared spectral data of the eucalyptus, the Chinese fir, the larch, the Pinus massoniana and the Pinus sylvestris were selected as the research object. The qualitative identification model of timber species based on principal component analysis and support vector machine were established respectively. In the principal component analysis identification model, the 2D and 3D principal component analysis scores were drawn after preprocessing the sample spectral data. It is found that five kinds of timber species can be distinguished effectively in the principal component analysis score scatter plots, and the 3D principal component analysis score scatter plot shows the difference between the timber species more intuitively and clearly than the 2D principal component analysis score scatter plot. It is shown that the principal component analysis can distinguish the small sample timber species at the visual level. In the support vector machine identification model, the methods of genetic algorithm and particle swarm optimization were selected respectively for parameter optimization. Results showed that, the best discrimination accuracy of cross-validation was 95.71%, and the prediction accuracy rate of test set was 94.29% in the genetic algorithm-support vector machine model, which cost 134.08 s. While in the particle swarm optimization-support vector machine model, the best discrimination accuracy of cross-validation was 94.29%, and the prediction accuracy rate of test set was 100.00%, which cost 19.98 s. It indicates that the model based on intelligent algorithm and support vector machine can effectively identify the timber species. This study has made a useful exploration of the application of near infrared spectroscopy in the wood science, and provided a new method for rapid identification of timber species.

This article discusses the feasibility of immersed visible / near-infrared spectroscopy for rapidly detecting the content of haematococcus pluvialis chlorophyll. Combined with chemometrics methods, we chose the best pretreatment to predict the content of haematococcus pluvialis chlorophyll a and chlorophyll b. We compared the results of PLS modeling of full-wave band and the successive projections algorithm combined with PLS (SPA-PLS) modeling, and chose the better one for prediction. For chlorophyll a and b, SPA-PLS modeling was better than PLS modeling of full-wave band. The RPD value of chlorophyll a by SPA-PLS modeling reached 2.946 1 and that of chlorophyll b by SPA-PLS modeling was 1.902 3. Research showes that this method can predict the chlorophyll a, chlorophyll b content well through some pretreatments algorithms and modeling algorithms which can provide a new approach for detecting the content of chlorophyll a and chlorophyll b.

PAiRFP1 is one Near-infrared fluorescent protein modified from Agp2, one bacteriophytochrome from Agrobacterium tumefaciens, using protein engineering strategy. Being different from other bacteriophytochrome-based fluorescent protein, PAiRFP1 exhibited specific photoactivatable behavior. This property favored the enhancement of signal-to-noise ratio when PAiRFP1 was used as fluorescence probe in vivo imaging. Little useful information has been available concerning what factors would affect the photoactivation behavior of PAiRFP1. We herein investigated the effect of protein concentration, pH, metal ion and redox condition on the photoactivation of PAiRFP1. It was found that (1) there is no linear relationship between the maximum photoactivation efficiency and the protein concentration. (2) The maximum photoactivation efficiency increased from 36.8% to 52.0% and 60.8% upon increasing pH from 6.5 to 7.8 and 9.0. (3) The metal ions exerted no significant effect on the maximum photoactivation efficiency of PAiRFP1. Similar phenomenon was observed following the treatment of hydrogen peroxide or dithiothreitol. Apart from these factors, one mutant named V276G was constructed, where the valine residue at site 276 was mutated to glycine residue. This displacement resulted in one decrease of the maximum photoactivation efficiency from ~50.0% to 19.4%. Additionally, when DTT was used to the V276G mutant, the maximum photoactivation efficiency was observed to increase from 19.4% to 27.1%. In this paper, we also studied the changes of photoactivation rate induced by these factors. These results will provide useful information and guidance for the application of PAiRFP1 into in-vivo imaging.

Near infrared spectroscopy is widely applied in remote sensing and recognition. In this manuscript, the classification method which is based on principal component analysis (PCA) and fuzzy clustering is applied to recognize typical objects with near-infrared diffuse reflectance spectra. The diffuse reflectance spectra of four types of ground targets are measured in the range of 1 100～2 500 nm. Firstly, the spectral features are extractedwith PCA analysis. Secondly, the principal components is set to be the input to the fuzzy clustering model to calculate the closeness degree between different samples. Finally, the typical objects were classified based on principle of fuzzy closeness optimization. The results indicated that the proposed method is beneficial for automatic recognition and classificationof typical ground. Thenear-infrared diffuse reflectance spectroscopy reflects the feature of typical ground object. Taking the advantage of spectral features extracting and data dimensions reduction, the PCA algorithm can effectively improve the recognition efficiency. The fuzzy classification method also improve the robustness of the model. This method provides a new concept for the analysis and processing of remote sensing spectroscopy.

In terms of the near-infrared spectroscopy, the concentration measurement for a substance in aqueous solution samples would be greatly influenced by the samples’ temperature since the water’s absorption in the solution will be obviously changed when the temperature varies. Especially for the measurement of glucose, which exhibits relatively weak absorption to the near-infrared light, the measurement accuracy would drop even with the slightest change of the solution’s temperature. It is found by experiment that the absorbance of glucose aqueous solutions would be changed in 0.344 7% at 1 160 nm when their temperature varies by 1 ℃ from around 30 ℃. Some recently developed methods based on chemometrics are presented, which can calibrate the solution’s spectra affected by temperature, to improve the glucose measurement accuracy under various temperatures. The methods include generalized least squares weighting (GLSW) and external parameter orthogonalisation (EPO). These methods are tested on the glucose aqueous solutions’ spectral data of 900~1 350 nm recorded at various temperatures, the prediction errors are evaluated using the spectra calibrated by the methods. The results show that the spectra of the same solution with various temperatures can be well calibrated to an equivalent result to the spectrum at the reference temperature. Moreover, the methods are compared with the multivariable regression of (partial least squares, PLS) regression, which includes temperature as a variable in the prediction model. The result shows that GLSW and EPO can well calibrate the solutions’ spectra from various temperature values because the coefficient of variation was reduced. And then the calibrated spectra show better performance on the prediction of glucose concentration than PLS because the complexity and the prediction errors of the models were well improved. The research in this paper could be referenced for the other substance measurements in the aqueous samples, and it can also be referredto the blood glucose measurement in human tissues.

As a kind of popular food, aquatic product is rich in water, protein, unsaturated fatty acids and free amino acids. However, due to temperature fluctuations or improper operation and other factors during storage, it leads to a series of food safety issues. Near infrared Reflectance spectroscopy (NIRS) is a kind of technology which can determine the content of components with the absorption, scattering, reflection and transmission of light. As one method for food detection, it is widely used in the field of food which ranging from gas to liquid, from homogenate to powder, from solid materials to biological tissues. It can achieve the goal of qualitative or quantitative analysis for various samples instantly and accurately. It has the characteristics of rapid, nondestructive, safe and efficient, multi-component determination simultaneously. In this paper, the characteristic of common nondestructive detection technologies for aquatic products were comparatively analyzed, the principle of NIRS were illustrated, the application and the latest research progress of NIRS in the detection of aquatic products, such as freshness evaluation, physicochemical detection, food adulteration, quality classification and shelf-life prediction, were introduced respectively. Meanwhile it also tries to come up with some problems on the quality detection of aquatic products with NIRS according to the current development trends. On the basis of deeply improving the detection precision, the correlation analysis of various physicochemical indexes and the integration of various non-detection techniques will be investigated in order to give the overall evaluation of its quality and get more extensive application in aquatic products.

Lignin genetic engineering can effectively reduce the lignin content ofthe cell walls in poplars, while improving utilization characteristic of poplars as the lignocellulosic material. In this paper, the transgenic poplars with C3H downregulated and control poplars were selected. Fourier transform infrared (FTIR) spectroscopic was used to quickly characterize the lignin content and the other cell wall constituents of transgenic poplars with C3H-downregulated. CLSM and histochemistry reaction were used to reveal the influence of lignin content reduction on their micro-area distribution in situ. The results showed that the FTIR spectrum shape, the number and wavenumbers of characteristic bands of transgenic poplars and control poplars were similar which means that the reduction of C3H activity had no effect on the chemical composition of poplar cell walls. However, the height ratios of I1 508/I1 379, I1 508/I1 425, and I1 508/I1 740 associated with lignin content reduced 8.2% to 9.5% in transgenic poplars compared with control poplars. The difference in intensity of spectrum peaks between the transgenic poplars and the control poplars illustrated that the C3H-downregulated can change the cell wall constituents content of the transgenic poplars. The CLSM images showed that the micro-area distribution trends of the lignin of the cell walls in transgenic poplars and control poplars were similar, and the sequence of lignin distribution was the cell wall corner>the middle lamellar>the second cell wall, and the images also showed the lower lignin content of the cell walls in transgenic poplars than that of the control group. The Wiesner and Mule staining images also showed that S lignin monomer was uniformly distributed in fiber cell walls of the two kinds of poplars, and the G lignin monomer deposition was nonhomogeneous, the sequence was also the cell wall corner>the middle lamellar>the second cell wall. These results also illustrated that reducing the activity of C3H gene had no influence on distribution trend of G and S lignin monomer, but changed the lignin monomer content of the cell walls of fiber and vessel in transgenic poplars.

The method of useful information extraction is one of the most important one in the detection application for complex samples using near infrared (NIR) spectroscopy. Due to various noise, baseline drift, peak overlapping and complex background, informative spectra were hidden and cannot be extracted by conventional methods. Thus, a new hybrid algorithm (EWPIE) was proposed for informative spectra extraction based on wavelet packet transform (WPT) and entropy theory in this study. In EWPIE algorithm, WPT algorithm and its reconstruction algorithm were adopted to split the raw spectra into serval subspectra in different frequency bands. To take advantage of the multiscale property of NIR spectroscopy, each subspectra was further processed through entropy-based phase and orthogonal signal correction (OSC)-based phase. In entropy-based phase, the information entropy theory was used as a filter to remove the interference, which are uncorrelated to analyte contents and would increase the uncertainty of whole spectra. According to the variation of entropy value, some subspectra representing basedline in low frequency band and some subspectra representing noise in high frequency band were filtered out. In OSC-based phase, the OSC algorithm was applied to each of the remaining subspectra and the useful spectra were obtained with accumulation of all the OSC-filtered subspectra. To validate this algorithm, a real NIR spectral dataset of milk was prepared to extract the correlated spectra about the content of fat and protein. Using the EWPIE-filtered spectra, a series of PLS prediction model were constructed. Experimental results show that the prediction ability and robustness of PLS_based prediction models developed with EWPIE algorithm are superior to those developed by conventional algorithms. The root mean square errors of the prediction models for fat and protein can reach up to 0.132% and 0.121%, which indicates that the EWPIE algorithm is a promise tool to extract the useful information from NIR spectra and has certain theoretical significance and practical application value for detection in complex systems.

NIR (near-infrared) spectroscopy is a fast, non-destructive quantitative analysis tool. In order to improve the detection of yellow rice wine, NIR is employed for the quantitative analysis. In the detection, due to the varying factors (e. g. environment, raw material, instrument aging), the performance of model developed by the old samples may deteriorate over time. To guarantee the prediction accuracy, the recursive partial least square (RPLS) method is introduced to update the prediction model. However, the whole spectrum used to be involved in the model update, and the number of spectral variables in a whole spectrum is very large, which may result in intensive computation and no obvious improvement in prediction accuracy due to interference information included. Considering the insignificant change of characteristic wavelengths in yellow rice wine production, a model updating method is proposed in this paper based on characteristic wavelength. The correlation coefficient method is employed to extract the characteristic wavelength, and then the RPLS model is developed by incorporating the new sample information in the method. This method is applied to update the NIR detection model of total acid in yellow rice wine. The correlation coefficient r, root mean square errors of prediction (RMSEP) and residual predictive deviation (RPD) are employed to evaluate model performance. These three indices reach 0.965 7, 0.184 3 and 3.736 2 by using the proposed method. Therefore, the proposed method may optimize the model stability, improve the computational efficiency and provide an useful practical reference.

The moisture content of leaves is an important index to evaluate the health condition of the Euphrates poplar, and spectrum detection method is an effective method. But in the process of near infrared spectrum measurement, spectral data will be affected by instrument noise, morphological differences and environment interference. The paper proposed how to establish spectrum detection method of water content of populus euphratica leaf. In the first place, the influence of scattering, noise and baseline drift of spectral data are reduced by using multiple scattering correction (MSC）, and increase signal to noise ratio (SNR) of spectrum data andstrengthen band features. The effective spectral information is relatively clear, so the choice of characteristic wavelength becomes easier. Then, in order to reduce the complexity of the model, to prevent overfitting and to reduce the influence of collinearity, the successive projections algorithm (SPA) is used to select the feature variables. And a multiple linear regression model is used to analysis and compare the simulated residual squared of different models, evaluate the contribution of each wavelength and eliminate the wavelengths of small contribution value. Then we obtained the optimal characteristic wavelength to improve the conditions of modeling. Finally, the partial least squares regression method is used to establish the test model. The experimental results show that the successive projections algorithm screens six effective variables on the basis of using the original spectrum data, the prediction accuracy is 90.144%, the correlation coefficient (r) is 0.674 24, the root mean square error is 0.021 434, and the successive projections algorithm screens five effective variables after using multiple scattering correction algorithm to optimize the original spectrum data, the prediction accuracy is 97.734%, the correlation coefficient (r) is 0.781 63, the root mean square error is 0.016 776. Sothe multiple scattering correction algorithm and successive projections algorithm has been successfully applied to eliminate the scattering noise, reduce the total linear interference, simplify the complexity of the model, then increase the accuracy and correlation coefficient, reduce the error. This method can be used for fast nondestructive testing of water content of the Euphrates poplar leaf, besides it also has some reference significance for moisture detection of other crops leaf.

Meat and meat products are important components of the human food chain. Their quality is an important issue to consumers, government agencies and retailers. In China, the research and application of rapid and reliable methods for on-line detection of meat quality is still in badly need. Near infrared spectroscopy (NIRS) is an attractive technique for such applications, since it is fast, non-destructive method which requires small samples with a high-penetration radiation beam and free from further preparation of the samples is needed. Therefore, in this study, the overall objective was to investigate the use of a NIR hyperspectral imaging technique for accurate, fast and objective detection of fat content in various meat, and to compare with traditional standard chemical results. With near infrared scanning technology to pork, beef, mutton, and the national standard method (soxhlet extraction method) to determination of chemical values of fresh meat fat, with PLS (partial least squares) as a modeling method, and through the different spectral preprocessing methods respectively established the pigs, beef and mutton samples of near infrared spectrum parameters and the corresponding relationship between the fat content of model. Results show that for pork, select band 4 260～6 014 cm-1+a derivative+Norris derivative model built by the best effect, the correction coefficient of correlation and prediction correlation coefficient of 0.955 6 and 0.961 6 respectively; For beef, choose 5 226～7 343 cm-1 band+a derivative+S-G model built by the best effect, the correction coefficient of correlation and prediction correlation coefficient of 0.923 5 and 0.942 7 respectively; For mutton, select band 5 207～7 362 cm-1+a derivative + Norris derivative model built by the best effect, the correction coefficient of correlation and prediction correlation coefficient of 0.915 7 and 0.939 6 respectively; For fresh meat, choose select band of 5 156～6 065 cm-1+second derivative+S-G model built by the best effect, the correction coefficient of correlation and prediction correlation coefficient were 0.916 3 and 0.919 4, above all model correction of the correlation coefficient is greater than 0.91. Thus, the model has higher precision, meeting the needs of different meat products in the actual production.It is a nondestructive method with advantages such as fast analysis speed, low cost and high resolution.

It has been a hotspot to looking for high performance electromagnetic attenuation material. At present, the conventional inorganic materials, such as aluminum foil, copper, graphite, have been widely used in electromagnetic attenuation field. However, there are certain restrictions on the use of inorganic materials, such as high cost of raw material, low generating efficiency, and environment unfriendly. Recently, considerable attention has been paid to microbial materials, which has the potential to solve the problems above. In this study, three biological materials, fungi An0429 spores, fungi Bb0919 spores and fungi Cx0507 spores were used to measure infrared extinction performance. They were subjected to specular reflection spectra measurements in the range of 4 000～400 cm-1 (2.5～25 μm) by squash method. The real (n) and imaginary (k) parts of the complex refractive index of biological materials were calculated by using Kramers-Kroning relation based on the measured data. The complex refractive index with real part n and imaginary part k in the infrared band satisfies the following conditions n≥1 and k≥0. The static mass extinction coefficient was calculated based on Mie theory. Compared with common inorganic materials, biological materials possess a good extinction performance. In the smoke box test, the transmittances of fungi An0429, fungi Bb0919 spores and fungi Cx0507 spores were 5.1%, 8.2% and 7.4%, the mass extinction coefficients were 1.257, 1.065 and 1.009 m2·g-1. These results showed that have higher extinction characteristics. In addition, biological microbial materials have other advantages, such as short growth cycle, low production cost, absence of toxic in the casting process, and environmental friendliness. Therefore, microbial materials have great potential in extinction applications.

With the help of Surface-enhanced Raman scattering (SERS) technique, it is easy to acquire information on molecular structures that cannot be obtained by normal Raman spectroscopy, which overcomes the disadvantage of low sensitivity of Raman spectroscopy. Thus, it has become one of the most important methods for the trace detection of molecules and even single molecules, has been widely used in the life science, analytical chemistry and other fields. SERS substrate is the core component in SERS detection, however, only a few noble metal substrates have strong SERS effect, which are usually single-using, leading to the waste of resources in practical use. Herein, the history of SERS is reviewed, and the advance in the preparation of recyclable SERS substrates is highlightened. The discussion underscores the exciting prospect of developing the recyclable SERS substrates.

Based on the photocatalytic properties of oxide semiconductors and the ability to degrade organic molecules, the surface-enhanced Raman scattering (SERS) substrates can be reused, a composite structure based on Ag nanoparticles decorated on TiO2 nanorod arrays with graphene (TiO2/graphene/Ag) for surface Raman enhancement is presented. The TiO2 nanorods are synthesized with a hydrothermal method, the TiO2/graphene/Ag composites are fabricated by wet transfer graphene and a photoreduction method. Rhodamine 6G serves as the probe analyte. The results indicate that with the increase of UV irradiation time, the Raman signal of probe molecules weakened, the maximum enhancement factor value is calculated to be about 2.6×106. In addition, the UV self-cleaning properties of TiO2/graphene/Ag composite structure have been studied experimentally, the results indicate that after UV irradiation for 20 min, the Raman intensity dropped to 42.3%, which has a certain UV cleaning effect.

Using AgNO3 and NaCl as enhnacers, highly SERS active AgNRs/AgCl nanosol substrate were prepared, in which the hydrophobic AgCl molecules formed and absorbed on the AgNRs surface by mens of strong hydrophobic forces between AgNRs and AgCl. The Vitoria blue B molecular probes on the surfaces of AgNRs/AgCl displayed a strong SERS paek at 1 611 cm-1. VBB was used to dye the Escherichia coli (E. coli), which exhibited the SERS proprerty with a Raman peak at 1 611 cm-1. Under the optimal conditions, the SERS intensities were linear to E. coli concentration in the range of 5×106～3×109 cfu·mL-1, with a detection of 2×106 cfu·mL-1. The new SERS method was applied for detection of E. coli in real samples, with features such as simplicity, rapidity and sensitivity. The results were in agreement with that of plate-count method.

Understanding the Raman spectra of different types of hydrocarbons is fundamental for analyzing hydrocarbon inclusions with Raman spectroscopy. In this paper, statistics and analysis were done for the Raman characteristics of cycloalkanes and unsaturated hydrocarbons. According to the statistical results, some important conclusions can be drawn. The strongest Raman peak of C—C bond of cyclopentane and cyclohexane mainly concentrated in 1 440~1 460 cm-1. But cyclopentane and cyclohexane can be distinguished by the stable characteristic peak at 890 and 785 cm-1 in the Raman spectrogra. With the increasing of the number of branch chain of cyclopentane, the wave number of the strongest Raman peak of C—C bond will also increase, and reach to 1 460 cm-1. The strongest Raman peak of C—C bond cyclopentane appears at 1 445, 1 450 and 1 460 cm-1 corresponding to one, two and three or more than three branch chains respectively. The strongest Raman peak of C—C bond cyclopentane containing four chains is constant at 1 460 cm-1. With the increasing of the number of branch chain of cyclohexane, the wave number of the strongest Raman peak of C—H bond will decrease. The strongest Raman peak of C—C bond is mainly distributed in the range of 1 440~1 460 cm-1. Cyclohexane containing one branch chain which can be identified by stable Raman band at 1 445 cm-1±, 1 034 cm-1± and 2 853 cm-1±, 2 934 cm-1±. The combination of strongest Raman peaks at 1 440~1 460 and 2 926 cm-1 are the evidence of the cyclohexane containingtwo branch chains, while the strongest Raman peaks of 1 459 cm-1± and 2 924 cm-1± are the evidence of the cyclohexane containingthreebranch chains. The CC bonds of alkene can be identified by 1 641 cm-1±, and the CC bonds of alkyne can be identified by 1 445 cm-1±, 2 908 cm-1± and 2 933 cm-1±. All these typical Raman bands can be used to identify cycloalkanes and alkynes.

This paper established a rapid quantitative detection method for the content of potassium sorbate in orange flavoreddrink by using surface-enhanced Raman technique, which is based on the self-built laboratory Raman point scanning system. Through the comparative analysis of these Raman spectra and surface-enhanced Raman spectra of potassium sorbate under different states, such as standard potassium sorbate, aqueous solution of potassium sorbate and so on, identified 1 159.3, 1 398.9 and 1 653.0 cm-1 were characteristic Raman peaks of potassium sorbate, 1 648.4, 1 389.3 and 1 161.8 cm-1 were surface-enhanced Raman characteristic peaks of potassium sorbate. Confirmed this method had better repeatability by doing Raman shift peak intensity reproducibility experiment of the parallel samples and calculating the relative standard deviation (RSD) of the peak intensity. The results showed that the peak intensity average relative standard deviation RSD value was 9.88%. Gathered the surface enhanced Raman spectra of 33 orange flavored beverage samples from the concentration range of 0.180 7~1.706 g·kg-1 and all these Raman spectra did the pretreatments of S-G 5 point smoothing and Baseline removal of fluorescence background. Combined with the commonly used quantitative analysis method (Linear regression analysis method, multiple linear regression analysis method, and partial least squares regression analysis method), three prediction models which were based on these three different principles were established for the content prediction of potassium sorbate. By comparison, the multiple linear regression model which used three Raman shifts (1 161.8, 1 389.3 and 1 648.4 cm-1) had the smallest prediction error and highest model precision. In the multiple linear regression model, correlation coefficients of correction set and validation set (R2C and R2P) were 0.983 7 and 0.969 9, root mean square error of correction set and validation set (RMSEC and RMSEP) were 0.051 7 and 0.052 8 g·kg-1. And the relative standard deviation (RSD) of this model was 9.93% and the relative error (RPD) of this model was 5.06. By using the surface enhanced Raman technique combined with multiple linear regression analysis method, a more accurate and rapid prediction of potassium sorbate in orange beverage can be realized, which lays a technical foundation for the rapid monitoring of potassium sorbate in other foods.

Carotenoids are one of the most important components to reflect the physiological state of plant, such as environmental stress, photosynthesis as well as growing state. An effective and nondestructive detection method for the contents of carotenoids in Longjing-43 leaves was established based on Raman spectroscopy in this research. A total of 315 tea sample were used for the spectral collection and spectrophotometry determination. Quantitative models were established to predict the content of carotenoids. Firstly, in order to eliminate the interference from noise, 5 preprocessing methods were applied before calibration stage. Partial least square regression (PLS) was applied as calibration method to establish the Raman spectra quantitative model of the carotenoids in Longjing-43’s leaves. The results of PLS models based on these methods were used to evaluate the performances of these pretreatments. The best performance was achieved with wavelet transformed spectra, obtaining correlation coefficient (r) value of 0.817 and 0.786 for validation and prediction, respectively. Secondly, to further explore the Raman spectral response properties of carotenoids in tea, Successive Projections Algorithm (SPA) was applied to extract the characteristic wavenumbers for carotenoids in tea. Then, the selected 17 wavenumbers were used to build PLS model and good results are reached, obtaining Rv of 0.808 and Rp of 0.777. Based on the PLS model, this article studied the carotenoids content of tea leaves in 4 different growth periods. Results indicated that the content of carotenoids was firstly increased then decreased. The above results revealed that it was feasible to apply Raman spectroscopy for the determination of the carotenoids content in Longjing-43 leaves.

Non-invasive detection based on optical imaging and spectroscopy is an important development direction in the field of biomedical optics. Among which, Raman spectroscopy was widely applied for biomolecular, cellular and bio-tissue level diagnosis due to its advantage of providing biochemical “fingerprint” information of the targets being detected. The detection of thyroid disease, especially the clinical detection of thyroid tumors often involves the combination of multiple methods and techniques, and it faces some degrees of diagnostic challenge, so the development of new detection methods is of great significance. This review mainly focuses on research advances of Raman spectroscopic detection and analysis of single thyroid cells, differentiation and diagnosis between pathological thyroid tissue and normal thyroid tissue (especially our recent research work about silver nanoparticle based surface-enhanced Raman analysis and diagnosis between pathological thyroid tissue and normal thyroid tissue) and recent Raman analysis of thyroid hormones as well. The application prospect and future directions of Raman spectroscopy in this area was also briefly discussed.

The content of cephradine capsules was determined by a system of FOS-μSIA-LOV(fiber optic sensor-micro sequential injection-valve laboratory), based on the principle of cefradine quenching fluorescein in methanol solvent, optimize experimental conditions. The order of inhalation was anhydrous methanol, cefradine, fluorescein and anhydrous methanol; the carrier liquid suction volume was 500 μL; cefradine inhalation volume was 100 μL. Cefradine quenched fluorescein fluorescence intensity and concentration in 0.05～0.5 mg·mL-1 linear relationship as ΔF=812.6+284.41, r=0.999 5, precision RSD was 4.4%, the recovery was 101%～103%. FOS-SIA-LOV and personalized drug testing and programming resulted in automated on-line process analysis with the good reproducibility, less reagent consumption, time and labor saving.

The fluorescence characteristics of 8 kinds of fuel oil, 7 kinds of Middle East crude oil and 14 kinds of non-Middle East crude oil were analyzed by a constant-wavelength synchronous fluorescence spectrometry. Discrete wavelet transform and Fisher discriminant were combined to establish a model for the identification of marine oil spills. Twenty-nine kinds of oil before and after weathering had typical fluorescence peaks at the wavelength of (280±2), (302±2), (332±2) and (380±2) nm, but the dispersion degree of fluorescence intensity of weathered oil at (380±2) nm was too high, which was not suitable for the identification of oil species. The db7 wavelet basis function was used to resolve 6 levels for fluorescence spectra of 29 kinds of original oil samples, and the d3 detailed coefficient characteristics were extracted. The wavelet coefficients corresponding to (255±2), (280±2), (302±2), (332±2) and (354±2) nm were determined which were used to establish the Fisher discriminant model. All of oil samples all had extreme points at (280±2) nm, the wavelet coefficients of marine fuels were between 44.06±5.62, and that of crude oils were between 22.47±5.12. These two wavelet coefficients could be used to distinguish the marine fuel and crude oil. The established Fisher discriminant model distinguished not only marine fuel and crude oil but also further Middle East crude oil. The P-values corresponding to Wilks’s lambda distribution were 0 and 0.02, respectively, which indicated the model was feasible. The validated results of the model showed that the identification accuracy reached 96.6% for modeling oils after weathering and 95.7% for 23 kinds of non-modeling oils. Since adjusted cosine similarity of modeling oil before and after weathering was ranged from 0.91 to 0.98, the identification model established by the original oils can also be used for the identification of weathered oil species.

Studies on interactions between drugs and carrier proteins in blood is important for elucidating the transport, distribution, metabolism and efficacy of drugs in vivo. In this report, the fluorescence quenching mechanism of anti-HIV drug stavudine (D4T) with human serum albumin (HSA), bovine serum albumin (BSA) and hemoglobin (Hb) were determined with investigatingsteady state fluorescence, UV-Vis absorption spectra , kinetic transient emission spectra and cyclic voltammetry. The binding constant Ka (the size of the order of Ka is Hb＞HSA＞BSA) and binding sites n (n=1) of D4T binding with carriers were obtained in different temperatures (300, 310 and 320 K). Analysis of thermodynamic parameters ΔH, ΔS and ΔG of binding process, we can know that these three types of blood proteins are the ΔG＜0 and ΔH＜0, illustrating that combination of d4T and carriersare a spontaneous exothermic process, also by the ΔH＜0 and ΔS＜0, we can deduce that the binding force between D4T and HSA, BSA and Hb are hydrogen bonds and van der Waals force. The possibility of energy transfer and binding distance (R0 and r) between donor (proteins) and acceptor (D4T) were obtained according to non-radiative energy transfer theory (FRET). The r is less than 7 nm and 0.5R０＜ｒ＜1.5R０ show that from HSA, BSA and Hb to D4Tthe energy transfer occurs a great possibility. Simultaneously using synchronous fluorescence, three-dimensional fluorescence and circular dichroism spectroscopy, we can draw that the secondary structure are not affected and the changes of the tertiary conformation are not very large in the process of D4T combining with carriers (HSA, BSA and Hb). All these experimental results suggest that HSA, BSA and Hb three kinds of blood proteins can be used as good carriers in delivering D4T to the target location. These results provide an experimental basis for further study on the application of D4T in drug design and anti HIV effect.

The atmospheric conditions will lead to the distortion of the ground radiance or reflectance recorded by satellite sensors which inevitably hampers the successful regional scale aboveground carbon density quantification which is critical to the understanding of forest contribution to the regional carbon cycles. Hence, the appropriate algorithms of atmospheric correction are necessary. The objective of this paper was to assess the utility of radiation correction algorithms for estimating aboveground forest carbon storage with the multi-temporal Landsat remote images(TM/OLI) and quantify the carbon storage in a forest plantation, and five atmospheric correction methods, two absolute modeling methods (6S, FLAASH), two absolute image-based methods (IACM, QUAC), and one relative method (PIF) were compared. Forest carbon storage was estimated using the viable biomass empirical statistical models. Parameters for the regression equation were determined by analyzing the relationship between the data of the selected vegetation indices derived from Landsat images and the field-measured data (height and diameter) using data from different tree stands in study area. In order to evaluate the accuracy of the carbon storage of Pinus massoniana forest derived from multi-temporal remote sensing images, we acquired the forest subcompartment survey data in 1997, 2002 and 2006 and conducted several field surveys in 2010 and 2013. Consequently, we found that the surface reflectance of Pinus massoniana forest decreased evidently after atmospheric correction in visible band, but the surface reflectance in nearinfrared band and shortwave-infrared band, as well as NDVIs had a significant increase. And different atmospheric correction models had significant different effects on the estimation of the carbon storage of Pinus massoniana forest. By studying the correlation between the field-measured data, the IACM-corrected and 6S-corrected MNDVI data were most suitable for estimating the carbon storage of Pinus massoniana forest in the study area, with an exponential regression model appeared to have the highest degree of agreement and the lowest relative error with the measured data. In addition, we also found that the relative error of NDVIs of Pinus massoniana forest in multi-temporal remote sensing images decreasd 85.16% after PIF correction, and the estimation accuracy of the forest carbon storage was improved simultaneously. The results suggested that more attentions should be paid to choose the appropriate atmospheric correction when remote sensing images were applied to quantitative analyzing and information collecting in field. And relative radiometric correction of remote sensing images is quite an important preprocessing technique, which can significantly improve the precision of the estimated results, especially in multi-temporal remote sensing monitoring. This study also confirmed that the combination of IACM and PIF could preferably reduce the atmosphere effect, which would be suitable for multi-temporal forest carbon storage estimation and other related quantitative remote sensing researches.

Adsorption is widely used in heavy metals wastewater treatments because of its economy and efficiency. Developing recyclable specific Pb(Ⅱ) adsorption materials is important for lead wastewater treatment and lead recycling. Fe3O4/GO-IIP, with properties of adsorb ability (GO) and magnetism (Fe3O4), was successfully synthesized combined with surface imprinting technology by using magnetic Fe3O4/GO as supporter, lead nitrate as a template, methylacrylic acid as functional monomer, and ethylene glycol dimethacrylate as the cross-linker. The reusability and specific adsorption for Pb(Ⅱ) of Fe3O4/GO-IIP were discussed. X-ray diffraction(XRD), scanning electron microscope(SEM) and Fourier transform infrared spectroscopy(FTIR) were used to determine the characteristics of Fe3O4/GO-IIP and analyze the removal mechanism for Pb(Ⅱ). Fe3O4/GO-IIP was used as sorbents to selectively remove Pb(Ⅱ) from aqueous solutions. Results indicated that Fe3O4/GO-IIP had a high affinity to Pb(Ⅱ), the removal rate of Pb(Ⅱ) reached 70% within 5 minutes and the reaction achieved adsorption equilibrium within 20 minutes. Pseudo second order kinetics and Langmuir isotherm adsorption model could preferably express the adsorption process. Transmission electron microscopy(TEM) and SEM images demonstrated that Fe3O4 was uniformly loaded on the surface of GO, and the size rang was from 10 to 20 nm. The imprinted cavity existing on the surface of Fe3O4/GO-IIP enhanced the selective adsorption of Pb(Ⅱ). The selectivity coefficient of Fe3O4/GO-IIP was 2～5 times higher than that of Fe3O4/GO-NIP in the presence of competitive ions ［Cd(Ⅱ), Zn(Ⅱ), Cu(Ⅱ) and et al］. XRD and FTIR spectra confirmed the synthesis of Fe3O4/GO-IIP.Fe3O4/GO-IIP and exhibited favorable characteristics of re-utilizing.

Diaspore is one of industrial minerals used for extracting aluminum and making fireproofing materials. In recent years, diaspore has been found as a gemstone with alexandrite effect. However, little research has been performed on its spectral characteristics and cause of alexandrite effect. In this study, three diaspore samples with alexandrite effect were investigated with XRF, FTIR, Raman spectrometer, UV-Vis-NIR spectrometer together with measuring CIE colored parameters, and these testing results were compared with those of ordinary diaspore without alexandrite effect. It was found that all of the samples with alexandrite effect displayed yellowish green color in sunlight and brownish red color in incandescent light. Their infrared spectra and Raman spectra are the same as those of ordinary diaspore: the infrared absorption bands are concentrated at 400~1 200, 1 800~2 110 and 2 900~3 000 cm-1, and the Raman characteristic peaks are mainly at 154, 331, 448, 665 and 1 189 cm-1. Compared the UV-Vis-NIR spectra with the results of chemical analysis, it is suggested that the d—d electron transition of Fe3+ and Cr3+ in diaspore made approximate transmittance between green-yellowish green （500~560 nm） and orange-red regions （600~780 nm） in visible light. Therefore, the difference in the relative spectral power distribution of ambient light source sheds great influence on the color of such diaspore. This research is the first to obtain color parameters of diaspore in simulated daylight and incandescent light. The alexandrite effect of diaspore can be quantitatively described by the change of a* and h0 color parameters obtained in different light sources. These results will not only provide scientific evidence and data support for the application extension and performance improvement of diaspore, but also serve to inspire deeper research on the optical properties of hydroxides.

Blood and blood products which are special products should be controlled strictly in the process of circulation. The traditional methods to identify the species of the blood use antihuman hemoglobin(Hb) antibodies which recognize and bind to human Hb, or use high-performance liquid chromatography(HPLC) and mass spectrometry (MS). During the identification, the samples may exposure to the external environment. To avoid the pollution of the samples and the environment, a non-connect technique for species of blood identification is needed. The experiment tests 24 human and bovine whole blood samples, including 10 samples for each and 4 unknown samples. The PET tube which contains the blood sample sets in the integrating sphere, which is illuminated by the supercontinuum laser. Each sample takes 5 times of the absorb spectrogram as average in range of 420~740 nm. A PCA method is used to reduce the dimension of original spectral data. Finally, the reduced data are fitted by two-dimensional normal distribution. The species of unknown samples can be identified by using the probability distribution in confidence space or the distance to the known classification center. In conclusion, the visible absorb spectrum of whole blood can be well identified by using the combination of PCA and two-dimensional normal distribution.

Two novel polyoxotungstates {(H2Biim)2}［SiW12O40］·8H2O (1) and {Ni2(Biim)5}［SiW12O40］·4H2O (2) have been hydrothermally synthesized. The two compounds are formed by classic Keggin configuration cluster anions as building blocks. The compound 1 belongs to the tetragonal system with protonated (H2Biim)2+ as counter cation, while compound 2 belongs to the monoclinic system, with dual-core ［Ni2(Biim)5］4+ complex as a counter cation of which the Ni2＋ ion is five-coordinated. The relationship between their properties and structures were studied by using XRD, FTIR, two-dimensional (2D) correlation infrared spectroscopy under thermal perturbation, and Uv-Vis DRS spectrum ect. Infrared spectra showed that the stretching vibration of Keggin cluster anion skeleton appeared in the range of 1 050～700 cm-1, furthermore the two-dimensional infrared correlation spectroscopy illustrated that the anion cluster skeleton is very sensitive with the thermal response; UV-Vis DRS found the Oμ→W(LMCT) of the two compounds was in 254 and 251 nm respectively.

In the analysis of the body component with spectroscopic techniques, transmission method and reflection method are two common approaches that used for the signal acquisition. Based on the position relationship between the optical fiber probe and the biological tissue, the reflection method can be further divided into two forms: contact measurement and non-contact measurement. The traditional contact measurement can easily realize the extraction of useful signals from deep tissue by adjusting the position between the light source and receiving fiber. However, study shows that the contact pressure and the heat transfer between the probe and tissue are known to cause the change of measurement conditions, which will further influence the stability of spectral data. By comparison, non-contact method is free from the influence of changes of pressure and temperature. Nonetheless, large amounts of surface reflectance that do not carry any useful information will be gathered into the fiber. The surface reflectance is so strong and concentrated that it would easily influence the dynamic range of the detector. Therefore, how to eliminate the impact of surface reflectance is the biggest problem the non-contact measurement faces. In view of this, a systemic study is conducted in this article and the cross- polarization method proposed by our group is investigated through both theoretical deduction and experimental analysis. First, the polarization state of surface reflection with different objects as experimental materials is studied. Results indicate that the polarization state of the surface reflectance is closely related to the surface roughness, the smaller the roughness is, the higher the polarization state will be. As a result, it can be concluded that the surface reflectance of Intralipid solution possesses with the polarization-maintaining property. Then, the extinction effect of the cross-polarization method was verified in Intralipid-20% solutions. Results showed that 97 percent of the surface reflections were eliminated effectively through this method. Finally, a comparative analysis on spectral data respectively obtained by contact and non-contact measurement was carried out. Result showed that there was a high coincidence between the two curves, which further illustrated the cross-polarization method can effectively eliminate the surface reflectance. Overall, this research explored the ability of cross-polarization method to eliminate the surface reflectance, aiming at abolishing the effect caused by the variations of measurement conditions and further promoting the development of non-invasive sensing with NIR spectroscopy technique.

Moisture content had a close relationship with the microbial growth and therefore it profoundly affected the dried scallop quality and safety, which is harmful to human health. In this study, a hyperspectral imaging system in the 380~1 030 nm was used for rapid detection of the moisture content of scallops. 90 hyperspectral images of six different dehydration periods were obtained. The mean spectra value of scallops from hyperspectral images were extracted and arranged in a matrix. Successive Projection Algorithm (SPA) and Weighted Regression Coefficient (Bw) were used to establish Partial Least Squares Regression (PLSR) models to correlate the spectral feature with moisture content. Seven and four optimal wavelengths were selected respectively to develop new simplified models called SPA-PLSR and Bw-PLSR, which brought about sound prediction results (correlation coefficients were higher than 0.95, the root mean square error were less than 10%). Then the best model called SPA-PLSR with less wavelength variables and higher prediction of 97.28%, was applied to create visualization map to observe the distribution of moisture content by pseudo color image programming technology. The results revealed the feasibility of hyperspectral imaging technique combined with the optimal wavelengths for estimating and visualizing the moisture content of scallops.

Fluorescence spectroscopy and UV-Vis absorption spectrometry assays were used to investigate the interaction mechanism of Fullerols and human serum albumin and bovine serum albumin under different temperature.The results revealed that Fullerols was capable of quenching SA’s fluorescence in both static modes. Binding constant values,binding site numbers and thermodynamics parameters of fixation reaction between Fullerols and serum albumin under different temperature were obtained with measurement and numeration. On the basis of thermodynamics data,the interaction forces of serum albumin after binding with Fullerols were mainly hydrophobic force.The binding strength of Fullerols and BSA was remarkably greater than that of Fullerols and HSA.Binding constants of Fullerols and BSA affected by temperature displayed dominant when bound to HSA. The binding sites of Fullerols and BSA were slightly larger.Then modes and mechanisms were observed by means of quenching mechanism analysis and molecular docking simulation method.Using AlignX amino acid Sequence Analys it was found that similarity of amino acid sequence of the two proteins were higher. Besides, significant difference in some small sequence fragments was observed.The distinctness was mostly in the vicinity of 160 and 185 of amino acid sequence,which proved that presumably affected the key sites of mode between the two proteins and Fullerols.

In recent years, proximal hyperspectral technology provides a new approach in timely, effectively and nondestructive way to detect soil organic matter (SOM). However, the hyperspectral dataset contains too many wavelengths which could lead to the collinearity, redundancy and noise to models. The Normalized Difference Spectral Index (NDSI) derived from soil spectral reflectance could enhance the relationship between spectral features and SOM, and also could eliminate the irrelevant wavelengths. In this paper, 56 topsoil samples at 0～20 cm depth were collected as research objects from Gong’an County in Jianghan Plain, the spectral reflectance was measured using the ASD FieldSpec3 spectrum analyzer, and the SOM was determined using potassium dichromate external heating method in the laboratory. In the next stage, the raw spectral reflectance (Raw) was prepared for three spectral transformations, i.e. inverse-log reflectance (LR), first order differential reflectance (FDR) and continuum removal reflectance (CR). 2-D correlograms of the determination coefficients (R2) were constructed using all two-band combinations of 4 spectral transformations in NDSI against SOM in the range of 400～2 400 nm. Then, the determination coefficients (R2) of the 4 spectral transformations for 1-D determination coefficients and 2-D determination coefficients by F significant test were got (ｐ<0.001), which could be used to extract sensitive bands and spectral index. At last, partial least squares regression (PLSR) method were used to build quantitative inversion model of SOM based on sensitive bands and spectral index for this study area, respectively. Feasibility of 2-D spectral index for building model was this study aimed to explore. The results showed that, the 2-D determination coefficients were better than 1-D determination coefficients, especially the determination coefficients of LR was improved by about 0.26. Compared to the sensitive bands derived from 1-D determination coefficients, on the whole, the sensitive spectral index derived from 2-D determination coefficients using PLSR method could obtain more robust prediction accuracies. The prediction accuracy of NDSILR-PLSR was the best, and its values of R2, RPD for the predicted model were 0.82, 2.46, which could estimate SOM comprehensively and stably. In the future, this method could be applied to air- or space-borne images with a lower spectral resolution (e.g. ASTER, Landsat TM), and the results could also provide great potential in the field of sensor design for portable proximal sensing researching.

In mountainous areas, a large number of rock cut slopes have been left due to railway constructions. Our previous investigations have demonstrated that the artificial soil has been polluted by Pb significantly. Re-vegetation time and vegetation modes are important factors that influenced the migration characteristics of Pb in the artificial soil. However, little is known regarding the effects of these factors on the migration characteristics of Pb and its mechanisms. In this paper, the adsorption and desorption characteristics of Pb in the artificial soils have been studied with microwave digestion-atomic absorption spectroscopy and infrared spectrum. The migration process of Pb in the artificial soils on the slopes with different vegetation modes were analyzed by artificial rainfall experiments. The results indicated that the adsorption amount of Pb increased with the increasing equilibrium concentration of Pb, and the isothermal curve liked "S". Freundlich equation could better fit the adsorption process of Pb in the artificial soils (R2=0.91). Power function equation could better fit the desorption process of Pb by NH4AC(R2=0.96). The infrared spectra of the artificial soil were kaolinite spectrum with characteristic absorption peaks of Kaolinite. The functional groups which were —OH on the surface of kaolinite and —OH and —COOH on the surface of humus played major roles in the adsorption process of Pb. Hence Pb from transportation can be immobilized with the artificial soil but it may be released out secondarily with the change of environmental factors. The loss of Pb in the runoff and sediment from slopes with different vegetation modes showed the order as grass＞grass-shrub＞grass-shrub-arbor. The loss of Pb from sediment was much higher than that from runoff. The erosion of the artificial soils on the slops played the main role on the migration of Pb. Therefore, effective measures should be taken to reduce the erosion of the artificial soils. Besides, the diffusion of Pb can be reduced and the impact of Pb to environment can be minimized.

Hyperspectral remote sensing is increasingly used to determine the feature components of mixed pixels and their proportions. In this paper, the vegetation soil mixed pixels of different area ratio were set as the research object, and polarization means and ASD FieldSpec3 spectrometer was applied to obtain polarized reflectance spectrum curve of vegetation soil mixed pixels to calculated the proportion of 8 different vegetation index and discuss the hyperspectral polarization characteristics of vegetation soil mixed pixels under different area ratio and different polarization angle. The study found that as the increasing of the proportion of leaves, vegetation soil spectral curves increasingly appeared “5 valleys and 4 peaks”, and the positions of the peak and bottom were basically the same. The larger the angle of polarization, the greater the spectral reflectance ratio of mixed pixels was; In mixed pixels, the larger the proportion of the vegetation, the greater the influence of the polarization angle. The vegetation index and the size of vegetation in mixed pixels were in a linear relationship and the correlation coefficient between the vegetation attenuation index and the improved red edge normalized difference vegetation index was the largest, which could reach about 98%, suitable for establishing the correlation model between vegetation index and vegetation proportion of mixed pixel area.. When vegetation area changes, the sensitivity of vegetation index is better by improving the red edge ratio. In the use of spectral absorption characteristic parameters to estimate vegetation index, the two order function model of absorption valley depth and photochemical vegetation index had the strongest fitting degree with the determination coefficient R2 of 0.963 3; The two degree function model of spectral absorption index and photochemical vegetation index had the strongest fitting degree, and the coefficient of determination R2 was 0.960 5.

Due to the advantages of high detection speed, real-time measurement, and non-destructive process, spectroscopy analysis technique is widely used in every field and has becomes one of the most effective methods in modern agricultural control. In this paper, we collected soil samples with different nutrient contents, measured the infrared attenuated total reflection (ATR) and diffuse reflection infrared Fourier transform (DRIFT) data of every sample in order to built models and predicted the content of total carbon, total nitrogen and available nitrogen quantitively in soil by using pretreatment and partial least squares(PLS) methods. It indicated that the determination coefficients of PLS models improved after using standard normal variate transformation (SNV). For the ATR and DRIFT models, the determination coefficients of total carbon were improved to 0.826, 0.919 and 0.841, 0.928 of total nitrogen respectively. By combining with ATR and DRIFT spectra, the prediction accuracy became higher than that of using ATR or DRIFT spectra. The coefficient of determinations of the total carbon, total nitrogen and available nitrogen models were 0.942, 0.951 and 0.919 respectively. It provided a reasonable method to improve the analytical ability in mid infrared spectroscopy.

Visible and near infrared spectroscopy analysis technique has many advantages, including simultaneous determination of multiple parameters, non-destructive assay, remote measurement and real-time analysis. And it is simple, fast, low-cost, and needs no sample preparation or simple preprocessing. It will be the preferred technology for soil nutrients determination in future. This research discussed the method and application of visible and near infrared spectroscopy for the off-line and rapid determination of total nitrogen (TN), total phosphorus (TP), total potassium (TK) and total carbon (TC) in soil. In this paper, 60 soil samples from three different and highly heterogeneous regions (2 mountains and 1 riverside) of Qingdao were collected respectively. The concentrations of TN, TP, TK, and TC in soils and their visible and near infrared reflectance spectroscopy were determined. First, the calibration set and the test set were divided as 2∶1 by Kennard-Stone method. Second, the typical wavelengths were selected by genetic algorithm. Finally, the quantitative analysis model between soil nutrients and soil spectroscopy was established by partial least square method. The correlation coefficients of the calibration set for TN, TP, TK, and TC were 0.970, 0.964, 0.680 and 0.967, respectively, and the correlation coefficients of the test set for TN, TP, TK, and TC were 0.980, 0.937, 0.717 and 0.972, respectively. RPD values for TN, TP, TK, and TC were 4.570, 2.424, 1.411 and 4.135, respectively. These results showed that the method could accurately predict the content of TN, TC and TP in soils and roughly predict the content of TK in soils. This study mainly used the visible spectroscopy to predict the concentrations of N, P and K in heterogeneous soils, which could reduce the costs for rapid determination of soil nutrients. This study also provided soil nutrient spectroscopy of Qingdao soils, which would support the setup of Chinese large soil database.

A classification method of oilseed rape and weeds based on hyperspectral information was put forward. Standard normal variate transformation (SNV), de-trending, multiplicative scatter correction (MSC), moving average (MA), savitzky-golay smoothing(SG), baseline and normalize were applied to data preprocess. Principal component analysis loadings (PCA loadings), x-loading weights, regression coefficient (RC) and successive projection algorithm (SPA) were used to extract feature wavelengths. Partial least-squares discriminant analysis (PLS-DA), extreme learning machine (ELM) and support vector machine(SVM) were employed to establish classification models. The overall results shows that the ELM models with the selected wavelengths of PCA loadings, x-loading weights and SPA based on de-trending preprocessed spectra has obtained the best results, with 100% classification accuracy for both the calibration set and the prediction set. The index of average classification accuracy is introduced to evaluate classification models accuracy under different experimental time. The results indicates that it is feasible to use near-infrared hyperspectral imaging to identify the oilseed rape and weeds.

This paper analyzed the spectrum characteristic which is sensitive to the fractional vegetation cover (FVC). The red-edge slope(k) was set as the parameter of the FVC estimation model in the study. The relationship between vegetation cover and mixed spectrum was studied by controlling vegetation coverage of lawn with avafield-3 spectrometer (measuring range 300~2 500 nm). The result showed that the red edge region(680~760 nm) was most sensitive to the fractional vegetation cover and the correlation between the first derivative of red edge region’s spectrum and fractional vegetation cover was the highest (>0.98) which was steady at the same time. By referring to spectral misture analysis method for the classical inversion FVC model using NDVI as the parameter of the FVC estimation model, this paper established two new inversion models using red-edge slope instead of NDVI, improving the classical model. The accuracy of the models was verified by experiment using UVA hyperspectral data and vegetation coverage data measured in the study area. We calculated the slope between 680~760 nm of each pixel in hyperspectral image, extracted pure pixels by PPI, calculated the maximum spectral slope value of pure vegetational pixel and the minimum spectral slope value of pure soil pixel, and assessed the FVC by the two new models. The FVC of measured data were calculated by the method of photography after geometric correction and supervised classification. The result of the fitting analysis showed that the accuracy of two new red-edge slope models (R2=0.893 3, 0.892 7) were higher than the NDVI model (R2=0.839 9, 0.829 9). This model has higher physical and biologic meanings, application potentiality and promotion value.

When a small volume (<50 μL) of liquid is sampling, it is easy to produce large sampling error. In order to reduce the uncertainty of analytical results, the quantification based on the sample volume is usually replaced by the quantification based on the sample mass. The conventional standard addition method (SAM), in which the quantification is based on the sample volume, cannot be applied when the quantification is based on the sample mass. Therefore, a modified SAM with mass-based quantification is proposed. As a demonstration, the modified SAM has been applied to determine low or trace elements Hg, Mo and Rh in complex solution with ICP-OES. The aim of the SAM is to correct the matrix effect, while the matrix effect includes two kinds of interferences: constant interference and proportional interference. Only the proportional interference can be corrected with the modified SAM, which can characterize the extent of the proportional interference with a quantitative index k: k=1 means there is no proportional interference; while the larger difference between k and 1 means greater proportional interference existing in the sample. As for constant interference, it can be reduced or eliminated by applying the background correction function of the ICP-OES instrument. The uncertainty of analytical results mainly comes from background correction, and depends on the signal-to-background ratio of the analytical line selected. The lower the signal-to-background ratio is, the greater the uncertainty of background correction is. Therefore, in the actual analysis, we should try to choose the analytical line which has as high signal-to-background ratio as possible. Otherwise, the final analytical result maybe contains very large uncertainty, even though the background correction has been made in advance.

Using spectroscopy sensing technology to measure water COD is the trend of development of modern environmental monitoring. Compared to the traditional chemical analysis is has the benefits of online continuous detection of environmental water samples for real-time monitoring of water COD. This paper collected real water samples, using laser-induced breakdown spectroscopy (LIBS) to obtain water samples of spectral data. Establish water sample COD quantitative prediction model combining Partial Least Squares regression (PLS) by different spectral pretreatment method, then quantitative prediction of LIBS spectrum measurement method of water COD and the relevant model parameters were analyzed. Found that the baseline correction superimposed S-Golay derivative partial least-squares model had better prediction results. The determination coefficient of calibration samples were 0.995 8, while the determination coefficient of prediction were 0.975 3, with RMSEC of 4.438 7 and RMSEP of 9.733 9. The experimental results showed that spectrum sensing technology can be used in the actual environment of water COD quantitative predictive analysis, laid the theoretical foundation for the development of portable water testing equipment.

To validate the feasibility of laser induced breakdown spectroscopy (LIBS) in detecting Cr in rice of polluted areas of Poyang Lake in Jiangxi province, rice husk samples, coarse rice samples and polished rice samples in the area were selected randomly as targets. In this work, these samples were tested with LIBS and the content of Cr was acquired by flame atomic absorption (AAS) in fresh samples. LIBS spectra showed that Cr Ⅰ 425.43 nm, Cr Ⅰ 427.48 nm, Cr Ⅰ 428.97 nm and abundant mineral elements such as Fe and Si were detected clearly , but they were undetectable directly in coarse rice and polished rice. The results of AAS shows that Cr in rice husk is more than the corresponding coarse rice and the Cr in polished rice does not exceed the limited content of 1 mg·kg-1 according to qualified national standards GB 2762—2012. The ratio between rice husk and coarse rice is about 78.95, it displayed the distribution is clear. This shows that compared with coarse rice, the concentration enrichment ratio of Cr in rice husk is higher than the coarse rice. The results demonstrate that it is feasible to detect Cr in rice husk and coarse rice. Therefore, it is helpful to predict the distribution of heavy metals in agricultural products by means of green method without pollution.

With the rapid development of science and technology, infrared measurement technology has gained an important application potential in remote sensing, radiation temperature measurement, infrared stealth, agriculture, medical science and other fields. In many patterns of radiation measurement, the emissivity of the material is always one of the most important parameters to determine the level of measurement accuracy. In order to meet the demand of the emissivity data for the measurement technology, the spectral emissivities of A3 iron, 304 steel and 201 steel at different temperatures are measured accurately by using a self-developed spectral emissivity measurement device, and several important factors influencing the emissivity of the three materials are explored. The results show that the emissivity of the three materials increases with the increase in temperature, and the emissivity of A3 iron is higher than the values of 304 steel and 201 steel, which were measured under the same conditions. What’s more, the chromium content in the material will reduce the emissivity value. XRD is used to analyze the oxidized components of the three materials, and the influence of surface composition on the emissivity is discussed. The results show that the oxide of A3 iron is composed of Fe3O4 and FeO, and the mutual changes of the various components will lead to the change of the spectral emissivity. The oxide of 304 steel and 201 steel consist mainly chromium oxide, thus their spectral emissivities are relatively stable. In addition, the emissivity of the three kinds of material achieves the maximum at the vicinity of 10 μm, and this phenomenon has been successfully explained by the superposition of two kinds of radiation and the Christiansen effect. This paper greatly enriches the spectral emissivity data of the three materials and provides strong data support for the application of radiation measurement technology in the three kinds of material.

The traditional ways of waste plastics processing mainly use the burning landfill, which lead to environmental pollution and the waste of resources. Waste plastic recycling is very important on the circulation economy and the sustainable development.The traditional instruments have some shortcomings in plastic classification, such as lower precision, higher cost, the influence of the sample color and a serious threat to operating personnel’s health. Laser induced breakdown spectroscopy has many advantages, such as simultaneous multielement detection of elements, free from sample preparation, rapid and real-time analysis, slight damages to sample and no impact on the sample color. The method of Chemometrics combined with LIBS technique is applied to the plastic, which improves the accuracy of plastic classification. But at present,the classification has many problems, such as more parameters and the poor universality. Using on a self built LIBS instrument, we can study the laser energy, delay time, integration time and the angle of the optical fiber, which can achieve a better experiment condition. With the experimental platform, we analyze the 2 200 sample points and choose the partial least squares to analyze the spectral data. In order to achieve the correlation between the sample label and the data, we discuss the better ratio of the training set and validation set. The experimental results show that replacing the interference spectra, classification accuracy of all 11 plastic is increased to 100%, while the validation set’s accuracy is only 99.8% and the test set is 99.09% without replacing the interference spectra . It can be seen that the laser induced breakdown spectroscopy combined with partial least squares method can be successfully used for the plastic sample classification.

Rice samples were digested by a mixture of nitric and perchloric acids (4∶1, V/V). Dithizone was used to chelate mercury ion in the sample solution, and the mercury complex was dispersed in ethanol before being extracted into carbon tetrachloride. Thus, a method of determining mercury in rice by dispersion liquid micro extraction-atomic fluorescence spectrometry was established. The operating parameters of the instrument and optimal experimental conditions of dispersive liquid-liquid microextraction were optimized, including the best complex acidity, the amount of complexing agent, extraction solvent type, the amount of dispersant dosage, and the extraction time. Experiments showed that under optimal conditions, the linear range was 0.005~25 μg·L-1 and the correlation coefficient was 0.996 6 with the detection limit of 0.003 μg·L-1, the relative standard deviation (RSD) of 3.84%, and the recovery 95%~105% . The method is proven to be a sensitive, rapid, and accurate,way which can detect effectively trace amounts of mercury in rice.

Trace elements of bronze vessels, which are from Zongyang County, Anhui Province and dated from the Western Zhou Dynasty to Warring States Period, and copper prills in the slag from Tangjiadun Site, were analyzed with LA-ICP-MS to determine their copper ores sources. Results show that contents of elements Co, As, Sb, Ag and Bi, et al. in the copper prills of slags from Tangjiadun site are high, which are different from the elements characteristics of smelted copper metal from Tongling and Tonglvshan site of mining and smelting. Copper ores sources of the bronze vessels from Zongyang County are stable from the Western Zhou Dynasty to Warring States Period. The copper ores mainly come from the vicinity around Tangjiadun site in Zongyang County and a small proportion is from Tongling area in the south of the Yangtze River. It is feasible that LA-ICP-MS can be used to determine trace elements in the ancient bronze vessel and copper prills in the slag from the site of mining and smelting, which provides a in situ nondestructive analysis technology for bronze vessel analysis and has important potential applications in the study on copper ores sources of ancient bronze vessels.

To correct astigmatism of UV high-resolution Rowland grating for influencing the image height broaden, a train of thought is proposed, which is based on an asymmetric exposure ofthe spherical wave at the Rowland circle. First of all, applying Rowland grating’ｓ aberration expressions derive the defocus and meridian coma full corrected equations. From these equations, a variety of limitations of Rowland grating record structure is discussed, which proves to be a suitable method for the optimization of UV high-resolution Rowland grating. Then, by the vertical ray deviation’s expression in the image plane, the paper refer to the astigmatism and sagittal coma as the principal factor to spectrum image-height, which is allocated the weight of aberration coefficients distribution. Taking advantage of this optimization thought, the waveband 110～200 nm, UV high-resolution Rowland grating is design. Meanwhile a series of contrastive analysis for the traditional grating and astigmatism correction Rowland grating, such as the variation tendency of aberration coefficients and spectrum image-height, image structure and spectral resolution. The results indicate, that in the same order of the spectral resolution, astigmatism correction Rowland grating spectral’ｓimage-height isreduced by 25 to 1.5 mm, spectrum energy is more concentrated.

In this paper, a creative and novel composite waveguide based monolayer graphene-clad microfiber (MGCM) device was designed to achieve ultra-broadband (730～1 700 nm) microfiber waveguide all-optical modulator. We took the biconical microfiber from a standard telecom single mode fiber with flame biconical taper method with low transmission loss, which enhances the evanescent wave and material interaction on the microfiber surface. Using the super-features of graphene, such as atomically thin, linearly dispersive band structure, ultra broadband light-matter interaction, strong interband transitions and ultra-fast carrier relaxation time, monolayer graphene was wrapped as a saturable absorber on the cone of the biconical taper fiber to enhance the interaction between the evanescent wave and monolayer graphene on the surface of the composite waveguide. Both the static and dynamic all-optical modulation experiments were carried out and we achieved supercontinuum (480～1 700 nm) light modulation by chopping the conventional low-power CW laser diode (808 nm) with pump power under 50 mW and the modulation depthsare more than 5.7 dB, the modulation speed is measured to be ~4 kHz. The all-optical modulator based on microfiber composite waveguide achieves ultra-broadband all-optical modulation with lower pump power while ensuring the depth of modulation. It was compatible with the current high-speed optical fiber communication networks in a simple, effective and inexpensive way, which paes the way for to micro/nano ultrafast optical signal processing.

This paper presented a high precision solar tracker for laser heterodyne radiometer with high resolution about MHz, which inversed a column concentration and vertical profile of the atmospheric composition. The solar tracking system using the sun tracking and tracking method had the characteristics of high precision, full time and space. This paper measured tracking precision of the sun tracker, and it’s X, Y axis tracking accuracy were 0.068° and 0.06°, respectively, which met the requirements of laser heterodyne radiometer in the atmosphere and in the field of astronomy. The system, combining the homemade sun tracker with laser heterodyne radiometer, obtained the absorption of CH4 in the atmosphere by solar spectrum around 3.5 μm, which laid the foundation for the inversion of the whole column concentration CH4 and the vertical profile of CH4 in the atmosphere.

Freshness is a key index for quality regulation and assurance during the processing and storage of ready-to-eat sea cucumbers. The usual freshness detection methods, sensory evaluation and physicochemical detection, are inadequate for mass standardized and industrial production. In this study, a nondestructive freshness detection method based on hyperspectral imaging was proposed for ready-to-eat sea cucumber (RTESC). The characteristic wavelengths and images were first selected using Principal Component Analysis (PCA) and band ratio algorithm. According to the rottenness mechanism of RTESC, the correlation model between the texture features of hyperspectral images and the freshness degree of RTESC was established to achieve a fast, non-destructive and non-invasive evaluation of RTESC freshness. The effective dimensional-reduction method was adopted to address the massive data of hyperspectral images. According to the spectral absorption characteristics of the sea cucumber body wall, the wavelengths (474 and 985 nm) with significant chemical absorption characteristics were used as dividing points for band division. Thus, five sub-bands and the full band (400～1 000 nm) were acquired for data processing. Next, the bands were optimized using Image Principle Component Analysis (IPCA). Based on the calculated weight coefficients, the band-ratio image at 686 and 985 nm was selected as the characteristic image. On that basis, the gray-gradient co-occurrence matrix (GGCM), gray-level co-occurrence matrix (GLCM), and local binary pattern (LBP) descriptor were constructed to extract texture features. Meanwhile, the measured total volatile basic nitrogen (TVB-N) contents were used as the criterion. Using these three types of texture features as the input data, three freshness evaluation models based on particle swarm optimization (PSO) and back propagation neural network (BPNN) were established. The detection accuracies of these three models are 90%, 95%, and 80%, respectively. The results show that, using the texture characteristics extracted by GGCM from the hyperspectral images, the detection performances are favorable. The present study provides theoretical foundations and technological supports for the development of fast and non-destructive detection methods for RTESC.

It is important to determinate uranium concentration in nuclear fuel reprocessing. The L-edge transmission spectrum of uranium, which is obtained by exposing uranium solution to an X-ray beam, can be applied for uranium determination. The L-edge transmission spectrum measurement system is introduced and the working curve for uranium determination is established with 1~200 g·L-1 uranium standard solutions. In order to verify the system, the precision, accuracy and stability experiments are carried out. The results show that the linear fitting parameter of the working curve is R2=0.999 9. The precision for 57.004 g·L-1 uranium solution is 0.21%, while the relative error is 0.32% for 38.255 g·L-1 uranium solution. It shows that 99.67% of the measurement results fall within μ±3 s range for 2.236 g·L-1.

An ultrasonic extraction-multiskan spectrum-microtitration assay method has been developed to detect the total petroleum hydrocarbons in environmental matrix. With a study into the parameters and variables that affected the extraction and detection of petroleum, it was found that the optimal conditions for extraction and detection are as follows: the detecting wavelength being 304 nm, using petroleum ether as extracting reagent, soil and liquid ratio being 1∶4, ultrasonic extracting two times with each one lasting 20 minutes, and ultrasonic extracting power, 100 W. Under these conditions, the recovery rates of total petroleum hydrocarbons ranged from 88.4% to 101.6%, with all the relative standard deviations less than 4.7%. Compared to the traditional extracting method which involves the use of lots of organic reagents such as dichloromethane, it would be more environment-friendly, for it is less harmful to the environment. Replacing ultraviolet spectrophotometer with multiskan spectrum, the samples can be detected more easily and rapidly with a relatively small amount of solution. Consequently, this method proves to be an efficient, green, rapid and inexpensive approach for extraction and determination of total petroleum hydrocarbons from environmental samples, which can be widely used in the quantitative determination of the trace environmental samples of petroleum contamination.