The point discharge is a kind of discharge phenomenon which is produced by the sharp point of the object. It belongs to a kind of corona discharge. It has been widely used in lightning rod and electrostatic dust removal technology. At present, the research on point discharge is mainly focused on the discharge intensity, and the research on its spectrum is not much. In this paper, it is found that the point discharge has strong radiation in the ultraviolet band. The ionization characteristics of the tip discharge were simulated by Comsol software, and the discharge spectrum was analyzed by means of mathematical physics model. In addition, the ionization characteristics of the point discharge are simulated by Comsol software. The radiation spectrum and radiation intensity of the discharge are analyzed by the mathematical physical model. The radiation intensity is first increased and then decreased with time, and the UV band can be estimated according to the distribution intensity of N2+ of the radiation intensity. The ultraviolet spectrum of the point discharge was analyzed by three ultraviolet spectra channels. The results show that the emission spectrum of the point discharge is distributed in the 240～340 nm band, 340 nm is the strongest. At the same time, the intensity of ultraviolet radiation of the point discharge decreases with the increase of the tip distance, and has a linear relationship with the imaging integration time. Besides, the linear slope decreases with the tip distance increasing in the same channel. The quantitative relationship between the radiation energy and the tip distance, the tip voltage and the integration time is obtained, and the mathematical model of the point discharge is validated. It is shown that, for the first time, this study provides a solid support for the depth study of UV discharge characteristics of the tip.

Terahertz time-domain spectroscopy (THz-TDS) has been used to study various materials including liquids, semiconductors, explosives, and gases etc. However, the conventional free-space terahertz spectroscopy technology has fundamental limitations in the field of trace analysis, and the signal attenuation caused by the absorption of water in the air is also great. To solve these problems, the researchers designed the integrated terahertz chip based on a metal waveguide transmission line structure. What’s more, the terahertz waves are generated and detected by the photoconductive materials laid on the transmission lines. However, the spectral width of the terahertz signal transmitted on chip is difficult to reach the bandwidth of the free-space THz-TDS signal, because the signal is attenuated due to the loss of the transmission line with increasing frequency. These losses are mainly composed of three parts: conductor loss, dielectric loss and radiation loss. It has shown that low permittivity of the materials as the substrates for coplanar transmission lines will reduce this mismatch of dielectric constants and avoid shock wave radiation losses, and the usage of substrate materials with low loss tangents can reduce the dielectric loss. Cyclic olefin polymers (COPs) are considered as alternative substrate materials that can reduce terahertz transmission line losses due to their high transmission in the terahertz band. To clarify whether this material can be used for the substrate, we need to analyze its spectral and dielectric properties by both THz-TDS and dielectric theory, and the transmission characteristics of the substrate materials on the terahertz transmission lines were simulated and analyzed. Three types of COPs, fused silica and PMMA were tested by transmission THz-TDS. In addition, the complex dielectric function were calculated from the time-domain data according to the physical model proposed by Dorney and Duvillaret et al.. Compared with the other two materials, the COP material has a higher transmittance of 94.5% at 1 THz, while the dielectric loss with 4.31×10-4 at 1 THz and the dielectric constant are lower. Therefore, when the COP is used as the substrate of the transmission line, the dielectric loss of the substrate can be effectively reduced. The dielectric constant was about 2.3 in the range of 0.2～2.8 THz, which also effectively reduced the radiation loss. What’s more, the coplanar waveguide transmission lines made from different substrate materials were simulated by HFSS and their forward transmission attenuation coefficients (S21 parameter) were obtained. Meanwhile, the dielectric loss and radiation loss caused by the substrates were also compared. Both the simulation results and dielectric analysis show that the COP has lower loss compared to other materials as the substrate of transmission line structure. Based on terahertz dielectric response analysis, COP material with lower dielectric constant in the terahertz band is more suitable as the substrate material for the terahertz transmission line, which can effectively reduce the dielectric loss and radiation loss caused by the substrate. This provides experimental and theoretical basis for the choice and application of suitable substrate materials in the design of terahertz transmission lines.

Solar spectroradiometer, as a special instrument for measuring solar spectral radiation, accurate and complete characterization of whose spectral properties is very important for the wide spectral range and the large dynamic range of solar radiation. The purpose of this paper is to provide explicit theory evidence and test method for the development and validation of solar spectroradiometer, and also to give clear and accurate mechanism models and characteristic indicator models for design and evaluation of the spectroradiometer system. Therefore, this paper focuses on the derivation and modeling process from signal transfer model to performance indicator model of spectroradiometer system. Spectral line spread function model, which is a convolution of series kernel functions, could synthetically indicate the influence of each component of the instrument on the system, and it’s easy to obtain by measuring a narrow band spectral line light source, and spectral line spread function matrix can clearly and completely show the instrument characteristics in details of the spectroradiometer. On the basis of spectral line spread function, the key geometric features are extracted further. Defined by simple algorithms, three characteristic indicators such as the full width at half maximum (FWHM), out-of-band rejection and out-of-band radiation are obtained. They can be used to quantitatively characterize the performance of the instrument for spectrometry, and are very effective characteristic indicator models for evaluating the performance of spectroradiometer system.

This paper proposes a new method of PM2.5 concentration inversion based on difference index through analyzing the spectrum characterization which is sensitive to the particular PM2.5. In addition, the spectral curves of typical land culture vegetation and soil are measured using Avafield-1 spectrometer (range of measurement 300～1 100 nm) under different PM2.5 concentration. The result showsthat the PM2.5 makes the reflectance of vegetation and soilincrease in red band and decrease in near-infrared. Therefore, the difference index (difference, index, DI) of sensitive red and near-infrared is used to characterize the particlesconcentration. This paper uses TM image to obtain the difference index and the PM2.5 concentration inversion of Beijing with the measured dataprovided by the ground air quality monitoring station in Beijing and surrounding areas. The result of the fitting analysis shows that the accuracy (r=0.796) of DI model onMar 1st(average PM2.5=105.8) is higher than that (r=0.628) on Dec14st (average PM2.5=15.8), namelythe accuracy of the DI models is lower when haze pollution degree is weak because the spectral characteristics change caused by particles are not obvious with low particulate content. On the other hand, the quality of remote sensing image is poor when the haze pollution degree is too serious, so this method is suitable for particle concentration inversion under mild and moderate haze pollution. The new method can obtain high spatial resolution (30 m) result with very simple inversion process. In addition, this method can obtain the PM2.5 concentration distribution of different temporal and spatial resolution just by selecting different remote sensing imagescontaining sensitive band data. The new method has wide application prospect.

Grain germination begins in the interior embryo, the early germination is difficult to be detected, which is a bottleneck restricting the safety of grain storage. The biological process of wheat grain germination mainly translates the starch into maltose for growth. In this paper, Terahertz(THz)imaging technology is used to investigate the image characteristics of maltose with different concentration. A THz spectrum is extracted from each pixel of the sample area in the image, and an average spectrum is obtained by averaging. The cumulative variance contribution rate of the first 5 principal components is over 98% according to the Principal Component Analysis(PCA) method, then the support vector machine (SVM) quantitative analysis regression model based on radial basis function is constructed by using the first 5 principal components score matrix. The comparison showed that THz imaging technology combined with chemometrics method is efficient and feasible for identifying maltose of different concentration and also indicated that the SVM obtains the best prediction results, which provides the theoretical basis for the detection of the state of germinated grain, guarantees the quality of stored grain and enhances the level of national storage technology.

In this paper, in order to ascertain the effects and influence laws of some factors on the photoacoustic detection of blood glucose, we firstly established a set of a blood glucose photoacoustic measurement system based on the optical parameters oscillators (OPO) pulsed laser induced ultrasonic detection in the lateral mode. In this system, the wavelength tunable pulsed laser was used as the excitation source of photoacoustic signals of blood glucose, and the ultrasonic transducer with high sensitivity was used to capture the photoacoustic signals of blood glucose. Moreover, the lateral detection mode was built because the irradiation direction of pulsed laser was perpendicular to the detection direction of ultrasonic transducer, which greatly overcame the interference of irradiation light directly penetrated the test solutions into the surface of ultrasonic transducer for the photoacoustic signals of samples. In addition, in the system, the effects of several factors on the photoacoustic detection of blood glucose were combined from the viewpoint of structural design. Then, the glucose solutions with different concentrations were used as the test samples. The effects of several factors (excitation wavelength, laser output energy, detection frequency and temperature) on the photoacoustic detection of glucose and concentration prediction were experimentally investigated. Besides, the time-resolved photoacoustic signals and photoacoustic peak-to-peak values of glucose with different concentrations under the different influence factors were experimentally obtained. At the same time, in order to know the influence laws of factors on the photoacoustic values and concentration prediction of glucose, the linear fitting algorithm was used to establish the models between the photoacoustic peak-to-peak values and the factors, as well as the prediction models between the photoacoustic peak-to-peak values and the concentration gradients of glucose. In experiments, the captured time-resolved photoacoustic signals of glucose were all averaged in 512 times, which effectively overcame the interference of noises to the photoacoustic signals of glucose, and improved the accuracy and effectivity of experimental data. Experimental results and the prediction results of models showed that compared with the wavelengths at 1 200 and 1 300 nm, the prediction model’s effect between the photoacoustic peak-to-peak values and the concentration of glucose at the wavelength of 1 064 nm was the best because its correlation coefficient of model was 0.986, which demonstrated that the glucose molecular had good absorption at characteristic wavelength of 1 064 nm. The photoacoustic peak-to-peak values of glucose linearly increased with the laser output energy, and the concentration prediction accuracy of glucose improved with the increase of the laser output energy. According to different concentration prediction results obtained by the ultrasonic transducers with different detection frequencies, compared with the ultrasonic transducers with frequency of 2.5 and 10 MHz, the photoacoustic detection effect of the glucose was the best for the ultrasonic transducer with frequency of 1 MHz. Finally, it was experimentally found that the photoacoustic peak-to-peak values of glucose linearly increased with the increasing of the temperatures and the concentrations. Especially, the concentration prediction error of glucose gradually increased with the increase of temperature.

In this paper, Zinc oxide phosphors (ZnO∶Zn) were prepared at a variety of sintering temperatures with solid state reaction. In addition, the annealing was done at 900～1 000 ℃ for 3 h. The characterization of the samples was done by different techniques such as X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), photoluminescence (PL) spectra and visible spectrum analysis system, respectively. The results indicate that all samples are in agreement with the hexagonal wurtzite structure of the ZnO phase. The phosphors can be effectively excited by near-UV and emit the broad green emission band with the peak located at 502 nm which was attributed to oxygen vacancies. Samples sintered at 940 ℃ exhibit the brightest. In addition, the green and white LED devices were fabricated with the green and RGB phosphors, respectively. The results indicate that the green LED show stable spectral emission under different driving currents (250～500 mA), the emission spectra and color coordinates are basically unchanged, and the emission intensity increases with the increasing of current, the packaged white LED with the CCT 3 212 K, Ra94.1 and luminous efficiency reach 85.6 lm·W-1(@300 mA, 9.3 V)which also show stable spectral emission under different driving currents (250～500 mA). The ZnO∶Zn green phosphor prepared in this paper has potential application value in the preparation of high color rendering and high quality white light LED.

Infrared spectral analysis technology has become one of the most important research techniques in the field of action mechanism of flotation reagents. Due to the high adsorptivity of mineral, it is difficult to detect the weak signal of adsorbed reagents on mineral surface by traditional transmission infrared KBr disc spectroscopy. In this study, the adsorption form and morphology of oleate on collophane surface were measured by microscopic reflectance infrared Fourier transform at various oleate concentrations. We found that the reflectance infrared spectroscopy had greater sensitivity for adsorbed oleate species on surface when being compared with transmission infrared technique, which was more suitable to reveal the adsorption mechanism at normal flotation concentrations of oleate. The results showed that the chemisorbed oleate at a single peak of 1 552 cm-1 and calcium oleate precipitate physically adsorbed at doublet peaks of 1 570 and 1 535 cm-1 coexisted on the collophane surface at lower oleate concentration under alkaline condition. In addition, when the oleate concentration was over critical micelle concentration, the collophane surface became hydrophilic due to the adsorption of oleate micelles, which made sodium oleate solution leave on the surface, so the above peaks were covered by the sodium oleate peak of 1 560 cm-1. What’s more, the peak intensity of adsorbed oleate sharply decreased after being washed with deionized water, because the residual sodium oleate and calcium oleate precipitate physically adsorbed could be rinsed. Besides, according to the two-dimensional micrographs, with the increase of sodium oleate concentration the adsorbed oleate aggregated into the laminated structure from a dot structure, and its coverage enlarged but it was not a complete coverage. This was attributed to the surface heterogeneity. These could provide a better understanding of the interaction mechanism between oleate and collophane in the flotation of phosphate ores and high-phosphorus iron ores.

Seed aging affects seed vigor and the quality of seeds as food. In this paper, barley, wheat, rice, corn and sorghum seeds of different storage years were discriminated by Fourier transform infrared (FT-IR) spectroscopy combined with second derivative infrared (SD-IR) spectroscopy and two-dimensional correlation infrared (2D-IR) spectroscopy. The results showed that several peak intensity ratios in the original spectra were different. In addition, the SD-IR spectra showed differences concerned with peak shape and intensity particularly in the range of 1 800～800 cm-1. Besides, the 2D-IR spectra showed that the number and intensities of auto-peaks and cross-peaks have clear differences in the range of 1 350～1 800 cm-1 for barley, and in the range of 860～1 690 cm-1 for wheat, rice, corn and sorghum. It is demonstrated that FT-IR and 2D-IR spectroscopy could be used to discriminate grain seeds of different storage years rapidly and effectively.

As a kind of natural and environmental paving materials, the solid wood flooring has become popular among people whose demand is increasing day by day. However, how to understand and detect wood properties quickly has been a urgent problem to be solved for material selection and quality inspection. So the profile densities of two kinds of import solid wood floorings made of Dipteryx odorata, Pometia spp. were quickly detected for physical properties and major chemical compositions by using rapid detection technology, X-ray scanning method and fourier transfoum infrared spectrum(FTIR). At the same time, the basic density of wood was measured by direct measurement and we also analyzed the correlation between the rapid detection density and the basic density of the two kinds floors. The profile density results showed that the density of Dipteryx odorata was higher than that of Pometia spp. and the heterogeneity of two kinds solid wood were great, correlation analysis data showed that there was a high correlation between the average of profile density and the basic density, the correlation coefficients of fitted parameters were 0.983 and 0.981, respectively. Besides the correlation coefficients of all materials was 0.991. The FTIR results showed that the extracts of Dipteryx odorata was higher than that of Pometia spp., the lignin characteristic peaks intensity ratio of I1 507/I1 425, I1 507/I1 740 of Dipteryx odorata was higher thanthat of Pometia spp., while the cellulose characteristic peaks intensity ratio of I1 507/I1 425, I1 507/I1 740 was less than that of Pometia spp.. The results showed that the lignin content of Dipteryx odorata was higher than that of Pometia spp., while the cellulose content was less than that of Pometia spp. Thus, the X-ray scanning method can quickly detect the heterogeneity of the wood and also can predict the basic density. While the FTIR can quickly detect the relative content of wood chemical components, so the combination of the two methods can detect the physical and chemical properties of solid floor woods and other lumbers rapidly.

The type of plastics is the serial number that manufacturing companies formulated based on thenature and application of raw materials. Detecting the physical and chemical properties of plasticscan indirectly identify their types, but these test methods are time-consuming and destructive. In this work, near-infrared spectroscopy technology was used to identify different types of Poly(lactic acid)(PLA). In addition, three models, PCA-MD, PCA-ANN and PCA-SVM, were applied for the analysis and prediction of the sample. In the wavelength range of 900～1 700 nm, a total of 90 samples of three different types of PLA were used to establish the model and another 90 samples of these three types of PLA were taken for prediction and identification. Comparing the identification ability of three prediction models to PLA types, we can find that the scatter plot of the first two principal components scores of the validation set had an obvious clustering phenomenon after the PCA of the spectral data. The first nine principal component scores were taken as the input variables of Mahalanobis distance, ANN and SVM discriminants, and these discriminants effectively identified the type of PLA, among which the accuracy of the best discriminant——Mahalanobis distance can reach 98.9%. Therefore, near infrared spectroscopy can be used for nondestructive, fast and accurate identification of different types of PLA.

Soluble sugar is an effective regulator of the taste of vegetables and fruits. It is also a necessary carbohydrate absorbed and used by human beings. The head cabbage is a common vegetable rich in carbohydrates. Soluble sugar content is an important parameter in determining the nutrient quality of head cabbage. Carbohydrates are made up of carbon, hydrogen and oxygen, and the molecular absorption spectra are mainly composed of the combination bands and overtone bands of C—H, O—H and CO groups, and contain abundant organic matter information. The experiment was conducted to study the rapid detection method of soluble sugar content in head cabbage by near infrared spectroscopy and chemometrics. The experiment collected a total of 161 samples of head cabbage. The spectral data were measured by the MATRIX-I FT-NIR spectrometer made in Bruker Company, Germany, and the soluble sugar was measured by the anthrone colorimetric method. Mahalanobis Distance (MD) method and Monte Carlo cross validation (MCCV) method were used to eliminate the abnormal samples. And then the Kennard-Stone (K-S) method was used to divide all samples into a calibration set and a validation set according to the given ratio. All 12 spectral pretreatment methods including Savitzky-Golay convolution smoothing (S-G), first derivative (FD), second derivative (SD), multiple scatter correction (MSC), variable Standardization (SNV), and their combinations, were used to improve the S/N ratio to find the best pretreatment method from them. The competitive adaptive reweighted sampling (CARS) algorithm was used to select and screen out the optimal wavenumbers with the greater absolute values of the regression coefficients in the PLS model, and to remove the wavenumbers with the small regression coefficients. Thus, the best wave number combination related to the nature of the measurement can be selected to get a good calibration model with good robustness and prediction ability. The coefficient of determination (R2), root mean squared error of cross validation (RMSECV), and root mean squared error of prediction (RMSEP) were used to evaluate models. According to the principles of Monte Carlo cross validation method and Mahalanobis distance method, 10 abnormal samples were eliminated, and finally 151 samples were used in modelling. The samples were divided into calibration set (110 samples) and validation set (41 samples) according to 3∶1 by K-S method. Three PLS models were established by using the original spectral data, the preprocessed spectral data, and the spectral data with optimal wavenumbers, respectively. The modeling results showed that the spectral preprocessing method using MSC combined with FD could well improve modeling accuracy, and the R2 of the calibration model increased from 0.68 to 0.93 and was thought to be the best spectral data preprocessing method in this experiment. The CARS method was applied to select optimal wave numbers for modelling. From 12 000 to 10 000 cm-1, there exist O—H str. second overtone and C—H third overtone, and the main background information in this area is water and other groups containing hydrogen. In this region 36 optimal wavenumbers were selected. From 8 500 to 10 000 cm-1, there exist sugar’s and water’s O—H str. first overtone and glucosamine O—H str. first overtone. This region is the main spectral region containing soluble sugar information and is less affected by the background. 15 optimal wavenumbers were selected in this region. The region of 5 800 to 4 000 cm-1 is similar to the region of 12 000 to 10 000 cm-1, and contains 36 selected optimal wavenumbers. Based on the results of the CARS wave number optimization, a full spectrum PLS model and a CARS-PLS model to estimate the head cabbage soluble sugar content were established. The R2, RMSECV, and RMSEP of the full spectrum PLS model were 0.93, 0.157 2%, and 0.132 8%, respectively. While the R2, RMSECV, and RMSEP of the CARS-PLS model were 0.96, 0.076 8%, and 0.059 4%, respectively. The experimental results showed that both CARS-PLS model and full spectrum PLS model had the similar R2, but the RMSECV of the CARS-PLS model was the 1/2 of that of the full spectrum PLS model, and the RMSEP of the CARS-PLS model was also close to 1/2 of that of the full spectrum PLS model. The CARS algorithm reduced the modeling variables so that the complexity of the model was reduced, and the accuracy of CARS-PLS model was improved. The CARS-PLS model is used to predict 41 samples of the validation set. The R2 of the prediction set is 0.86 and the prediction standard error is 0.059 4%, which meant that the prediction model of soluble sugar content in head cabbage was practical. CARS algorithm can reduce the unrelated information and the complexity of the model, and the wavenumbers selected can introduce both the spectra related components information and the spectra related the background information to improve the adaptivity of the calibration model. It provides a new approach for quality evaluation of head cabbage.

Attenuated total reflectance Fourier transform infrared spectrograph (ATR-FTIR) has become a common way to analyze and represent dyes as it can be used to acquire the far infrared spectra of powder samples (only less dosage) conveniently, easily, and sensitively apart from being able to identify the unknown samples in terms of their finger-print features. Five dyes, including ciba blue 2B, deoxyshikonin, indigo, 1H-Indole-2, 3-dione, and thioindigo, were measured by ATR-FTIR with the condition of vacuum. We acquired the absorption spectra within the region of 50~610 cm-1. The experimental results showed that there were obvious characteristic peaks in these five dyes and the corresponding peak positons were identified. And then Gaussian 09 software was used for simulating the vibrational assignments of thioindigo molecule and identifying the fingerprint spectra. It can be seen from the visualization results that the absorption peaks of thioindigo from 50~610 cm-1 were mainly caused by the collective vibration and the vibration modes ranged from low frequency to high frequency. Although the simulation results corresponded well with the experimental results, there were some differences between experimental and simulated results. For example, the values between experimental and simulated results were dissimilar; the positions of absorption peaks in the experiment shifted; the new peak positions were acquired in simulation. The main reason was that the temperature of simulation went far from that of experiment; the intermolecular activity was not considered in the theory calculation; the weak effect of contacting between the ATR crystal and powder; and the resolution of the instrument was not high enough.

There are some limitations in geographical discrimination of wild edible mushroom using single organic or mineral element fingerprint technique. According to the complementarity and synergy of two different fingerprint analysis techniques, the chemical profiles of different parts and sources were fused to explore the feasibility of this protocoland supply a novel reference and basis for tracing the origin of wild edible fungi 124 sporocarps of Boletus edulis collected from seven origins in Yunnan Provinces. The content of 15 mineral elements in the caps and stipes was detected, respectively. In addition, Fourier transform infrared spectroscopy (FTIR) was collected using the powder of fruit body. The original spectra were preprocessed by standard normal variable (SNV), second derivative (2D) algorithm et al. Based on the low and mid-level fusion strategy, the preprocessed spectra and mineral elements of caps and sipes were fused to established support vector machine (SVM) models, including the models of stipe, cap, FTIR, low-level data fusion (stipe+cap, stipe+cap+FTIR) and mid-level data fusion (The cap+stipe +FTIR). The most reliable method that was used to discriminate the B. edulis quickly, was chosen by comparing the model parameters. The results indicated that: (1) the content of Cd, Cr, Cu, Li, Mg, Na, P and Zn elements in caps was higher than the average content of stipe, the average content of Ba, Ca, Co, Ni, Rb, Sr and V elements in the stipe is higher than that in caps. The mineral elements Ca, Cu, Mg, P and Zn), which were essential mineral elements of human, were much higher than the average content of wheat, rice and fresh vegetables, whose content was similar to that in dried animal food. (2) the optimal pretreatment protocol of mineral element dataset was EWMA. The combination of 3D and SNV was the best in FTIR dataset. (3) c value of SVM model of stipe, cap, FITR, low- and mid- level fusion was 8 192, 4 096, 1.414 2, 11.313 7, 1 and 0.707 11, respectively, which indicated that potential over-fitting risk existed in the SVM model using the single mineral element dataset of stipe and cap. (4) the number of samples was misclassified in three models (FTIR, low- and mid- level fusion) was 7, 9, 7 and 0. The accuracy of mid-level fusion model (stipe+cap+FTIR) was the highest. The results illustrated that the mid-level fusion strategy fused the mineral element and FTIR spectra of fruit body was an effective pathway for geographical origins of wild edible mushroom.

To study the chemical composition change of the extracted coal in different macrolithotype, the cocking coal samples were taken from the Pingdingshan coal fields, and the extract solution of tetrahydrofuran (THF), carbon disulfide (CS2) and acetic acid (HAc) were experimentally conducted on the samples in this paper. Based on the chromatography and fourier transform infrared spectroscopy (FTIR), coal solution-extraction rate, chemical component and major functional group changes were investigated. The study find extraction yield of organic solvents on the vitrain is the highest, followed by the clarian, the durian, among different lithotype of coal. Further, the extraction yield of CS2 is the highest and THF is relatively higher than HAc. The hydrocarbon contents in the extraction decrease in the sequence of the vitrain, the clarian, and the durian, whereas the non- hydrocarbon components increase correspondingly. More bituminic is extracted from the coal sample under THF extraction, but more saturated hydrocarbon is done under CS2 extraction. Further comparison of function group between the pre-extracted coal and the pro-extracted coal of the same sample, fatty hydrocarbon content and oxygenic functional groups of the vitrain are the highest, the fat structure parameter is the largest, the aromatization of the coaland the proportion of aromatic to the fatty hydrocarbon are the smallest, while the durian has the largest proportion of aromatic to the fatty hydrocarbon. In addition, in all the solutions treated to the coal, the fatty hydrocarbon and oxygenic functional groups in the pro-extracted coal decrease in different degrees, the vitrain is the most obvious, whereas the aromatization of the durian residue and the proportion of aromatic to the fatty hydrocarbon are the largest. In these cases, oxygen-containing functional group can be significantly extracted by CS2, while the hydrogen-bond hydroxyl, phenols groups and fatty hydrocarbon are dramatically extracted by THF.

Recently there have been many natural minerals which are similar to turquoise in the market, commonly known as “turquoise associated minerals”, and are sold for business as a natural turquoise. These natural turquoise associated minerals are similar to natural turquoises in appearance while there are some difficulties in its identification. In this paper, the natural turquoise associated minerals of white and yellow varieties are selected, and their gemological characteristics and mineral composition are analyzed and studied by conventional gemological test, infrared absorption spectroscopy and X-ray powder diffraction. The results show that white and yellow natural turquoise associated minerals show earthy luster-weak glassy luster in different degrees. They are opaque and show relatively loose structure. The refractive index of the white sample is about 1.51 and the relative density is 1.86~2.28. The refractive index of the yellow sample is about 1.57~1.60 and the relative density is 2.32~2.72. The mineral compositions of white and yellow natural turquoise associated minerals are complex, and different even in the same color samples. The test of the spectrum by infrared absorption spectrum cannot effectively indicate the specific mineral composition, while the X-ray powder is the effective means to study the mineral composition of natural turquoise associated minerals. X-ray powder diffraction test results show that the main minerals of the white sample are phosphorus alum and phosphorus calcium alum; and the main mineral of the yellow sample is sodium alunite. The infrared absorption spectra of white and yellow samples show that the groups of SO4/PO4 had different vibrations, peak shapes and peak positions. According to the main mineral composition characteristics, the classification of infrared absorption spectrum for different samples can be fast and effective for its non-destructive identification.

In this study, human serum albumin (HSA) glycated products in dry processing, HSA and glucose were mixed into solution with mass proportion of 1∶1, free-drying for 48 h, totally 20 samples were obtained according to different reaction times. This study mainly used multi-spectral technology (UV, fluorescence, near infrared spectroscopy, infrared spectroscopy, CD spectroscopy) to analyze the changes of protein secondary tertiary structure, functional groups after glycation of HSA, glycated product and progress of protein. The results show that, the glycation process is easy to occur when HSA was mixed with the glucose in hot and dry conditions, with the increase of reaction time, UV absorption intensity weakened, fluorescence absorption intensity increased and reveal the higher degree of glycation and Maillard reaction, the secondary tertiary structure of protein had small changes. The reaction took about 140 min, the glycation was complete, the Amadori product was formed, and then was further heated to about 240 min, the reaction entered the middle and late period, and the aldehydes and ketones were formed. The reaction took about 280 min, protein amino groups and carbonyl compounds occurred decarboxylation and deamination.

It is important and challenging to select the variable for the spectral information automatically and establish a sparse linear model between the spectrum and the sample content under the circumstance that the near-infrared spectral information is much larger than the sample size. In this paper, Elastic Net was used for the measurement of o-cresol in the polyphenylene ether by utilizing the near infrared spectroscopy and a quantitative calibration model between near infrared spectroscopy and o-cresol content was established. Then, the model prediction effect is compared with the Lasso method. In the case where the number of variables is much larger than that of the samples. Although Lasso method can achieve variable selection, the prediction accuracy of the model is affected due to excessive compression to variable coefficients. Elastic Net avoids excessive censorship by increasing L2 penalty, which can improve model prediction accuracy. In order to verifymodel performance indicators ofElastic Net method, we use the complex correlation coefficient R2 and the adjusted complex correlation coefficient R2a to evaluate the interpretability of the model, meanwhile, the prediction accuracy of the model is evaluated by using the mean relative prediction error MRPE and the prediction correlation coefficient Rp. Lasso method to establish the model performance indicators are: R2=0.94, R2a=0.93, MRPE=4.51％, Rp=0.96; Elastic Net method performance indicators are: R2=0.97, R2a=1, MRPE=3.25％, Rp=0.98. From the result we could draw the conclusion that Elastic Net’s model is better than Lasso method. A sparse linear model with higher interpretability and high prediction accuracy can be obtained by the Elastic Net regression.

In order to develop a real-time measuring instrument based on NIR spectral absorption method for forest surface litter moisture content, the relationship between water content and absorption spectrum of litter in forest was analyzed in this paper. In addition, four kinds of forest surface litter were selected and the infrared absorption spectrum measuring device was constructed. Besides, the infrared absorption spectrum corresponding to different water content were obtained. The relationship between the different moisture content and the peak absorption intensity, the absorption valley areaand the vertical axis of the valley connection and the valley connection are analyzed. The results showed that the peak value of water absorption was near 1 450 nm, and the correlation between water content and peak absorption intensity of forest litter was better. The single regression equation was well tested by F-test, and the relative uncertainty of slope was less than 1.0% and the intercept of the relative uncertainty of less than 0.51%, the correlation coefficient r>0.95. It provides the basis for the light source and calibration process of the moisture content real-time measuring instrument.

VOCs (Volatile organic compounds) not only cause global environmental pollution, but also have negative impact on people’s daily life. Efficient and accurate monitoring of VOCs has become a hot issue in China’s atmospheric environment governance. Compared with other gaseous pollutants, VOCs are more volatile and easily react with other gaseous pollutants. The complexity of their physical and chemical characteristics sets higher requirements on existing detection methods. Among various gas detection methods, spectral detection technology has been widely used due to its advantages of convenience, rapidity, and accuracy. As an important spectrum detection technology, FTIR (Fourier transform infrared spectroscopy) is multi-channel, which could analyze hundreds of pollutants and calculate real-time pollutant concentrations as well, solving the problems caused by the complex nature of VOCs gas. This paper has tested the online monitoring system of VOCs emitted by stationary pollution source, which is based on FTIR. The infrared interference signal emitted by the interferometer is absorbed by the target gas in the 10-m path length gas pool and subjected to Fourier Transform to obtain the infrared spectrum containing the characteristic absorption peak of the gas. In addition, the comparison between the infrared spectrum and standard database helps with identification of the target gas and concentration measurement. This system covers a spectral range of 650～4 000 cm-1. Since most VOCs have relatively independent absorption peaks in the mid-infrared fingerprint area, the analysis of multiple gases can be completed with a spectral resolution of 1 cm-1 and a concentration detection range of 1.6～319.47 mg·m-3 (Take Benzene as an example). What’s more, the system analyzes and tests dozens of VOCs, such as toluene, acetone, and ethyl acetate, obtaining infrared spectra of different gases, which coincides well with the standard database and can be differentiated according to the absorption peaks of different gases. In order to obtain the exact gas concentration, instruments need calibration as well as to reduce the adsorption of gas in the inner chamber and the mirror and control the water vapor content, a temperature control system is added to monitor the temperature of the gas pool in real time. Meanwhile, with xylene standard gas with different concentrations inflated, this experiment uses the five-point calibration method to obtain the relationship between the analytical concentration and the standard concentration, leading to a relative deviation of the analytical concentration less than 0.06%. To verify the performance of the system in actual working scenario, this paper selects a coating workshop to monitor the VOCs pollution caused by volatilization of solvents and diluents in coating process for one week obtaining concentration changes of benzene, methyl ethyl ketone, isopropyl alcohol and ethyl acetate. Concentration safety threshold is set to guarantee safe operations. From the long-time data analysis, the system MTBF (Mean Time Between Failure) is as long as 1 000 h, which provides a lasting, stable and reliable real-time monitoring.

In this paper, indomethacin are characterized by the spectroscopy of UV and Raman and surface enhanced Raman scattering (SERS) on the substrate of L-Cys@Ag. And compared with the conventional Raman spectra (NRS) of solid indomethacin, it was found that L-Cys@Ag had significant Raman enhancement for indomethacin, but the characteristic peak was almost unchanged. The Raman spectra of indomethacin on L-Cysteine/silver were analyzed by the adsorption model of L-Cysteine and silver under acidic and basic conditions. The results showed that L-Cysteine and silver were mainly adsorbed by Ag—S bonds, but neutral and alkaline conditions carboxyl were also adsorbed to the surface of silver. The reson why the overall energy decreases is that the amino groups in the cysteine react with the carboxyl groups in the indomethacin and the π electrons in the benzene ring. After adding bovine serum albumin (BSA), the SERS intensity was significantly decreased at pH 5. At pH 7, and pH 9, the NH stretching vibration and amide II vibration were obviously enhanced, as well as the benzene ring and indole ring of indomethacin. The peak vibration disappeared due to the disappearance of indole mesacin, and the nitrogen and carbonyl groups in indomethacin were adsorbed by amino groups in BSA, and the C—N And —COO’s SERS signal is stable. This provides a reliable method for the identification and analysis of the future improvement of indomethacin and related non-Zhiban anti-inflammatory drugs and new drugs.

Accurate diagnosis of oil-paper insulation material is an essential technology to ensure the safe operation of equipment insulation. Raman spectroscopy has been widely used in material composition analysis and state diagnosis. In this paper, the oil-paper insulation samples obtained from the accelerated thermal ageing experiment were divided into four ageing stages according to the degree of polymerization of the paper, and researched based on the Raman spectroscopy platform. By analyzing the energy information contained in the Raman spectra of different ageing samples, the feature vector was extracted by Wavelet Packet Energy Entropy, and the discriminant function was constructed by Fisher discriminant method. What’s more, the ageing model of oil-paper insulation based on Raman spectroscopy was established, and oil samples of running transformers were collected to verify the generalization ability of diagnostic model. The results show that two discriminant functions can distinguish different ageing stages, and the accuracy rate of ageing samples reaches 84.2%. Raman spectroscopy combined with wavelet packet entropy and Fisher discriminant analysis can effectively diagnose the ageing state of oil-paper insulation.

In the process of rapid scanning or low power excitation, low SNR Raman usually spectra of biological samples can be acquired. In order to remove the noise in the low SNR spectra, we decomposed the spectra by the CEEMD method and separated the noise from spectra according to the Normalization Permutation Entropy in this paper. The method proposed was named as Complementary Ensemble Empirical Mode Decomposition (CEEMD). LCEEMD method can be used to denoise the Raman spectra, which effectively overcame the modal aliasing between high frequency Raman signals and noise components in EMD. Furthermore, CEEMD reduced residual noise, which were presented in EEMD. Simulation experiments showed that LCEEMD method can improve the SNR of data from 10 dB to 39.615 0 db with a standard deviation of 0.001 17 and correlation coefficient 0.999 9. The denoising experiments indicated that the skin Raman spectrum denosied by LCEEMD showed Raman strong characteristic peaks excited by the amide I-belt of cuticle lipid and weak peak of triglycerides (CO), and most peak intensities were consistent with the references. What’s more, the measurement for water-soluble sugar (rice leaf) was modeled with the removal noise data processed by LCEEMD. The prediction coefficient was 0.871 7 and standard error of prediction was 0.912 0, however they were 0.511 4, 1.647 8 and 0.638 2, 1.508 8 in models denosied by EMD and EEMD. In the process of noise removal by LCEEMD, the threshold of the Normalization Permutation Entropy was adjusted according to denoising performance indexes automatically where parameters needn’t to be set and the LCEEMD method is an adaptive noise filtering.

Sunset Yellow (SY) is a potentially harmful artificial synthetic pigment. This paper, taking human serum albumin (HSA) as the research object, analyzes the quenching effect of SY on HSA and determines the quenching constant Ksv of the quenching reaction with the fluorescence spectroscopy method. The results show that the quenching effect of SY on HSA is static quenching. In addition, based on the analysis of the binding of SY and HSA with the synchronous fluorescence spectroscopy method, it is found that the binding of SY and HSA is near tryptophan, whose residue is caused to be in a stretching state and the structure of HSA has changed. Furthermore, this paper selects ten types of metal ion, adds them into the reaction system of SY and HSA under the simulated human physiological conditions, and detects the impacts of the metal ions on the system with the three-dimensional fluorescent spectrometry method, which demonstrating that Cu2+, Pb2+, Ni2+ and Mn2+ exert facilitation effects on the quenching process, and Ni2+ shows the largest impacts, with an increase of 22.6%, while Fe2+ and Zn2+ have inhibition effects on the quenching process, with an inhibition ratio of 14.12% and 14.2%, respectively. Therefore, the experimental method is applicable to the study on the toxicity of food additives and conducive to ensureing food safety as well as maintaining human health.

There is no doubt that spectrum technology has a positive role in applied prospects of biological and medical testing. Because of the complexity and the similarity ofblood component, study on recognition and classificationof different animal’s blood is still an open issue. Based on the theory of machine learning, by BP neural network, the authorsproposed a methodoffeature extraction and classification for different animal’s blood fluorescence spectra. In this experiment, fluorescence spectra data of whole blood and red blood cell with different concentration (1% and 3%) is collected, respectively. By neighborhood average method, the original data is denoised in order to reduce the impact of noiseon thefeature extraction and classification. For the specialty of blood fluorescence spectra, the authors proposed a new feature extraction method of “Combination and Amplification method”, and established a BP neural network classifier. Compared with other common spectrafeature, “Combination and Amplification”feature and the BP neural network classifiercan achieve good recognition and classification for different animal’s blood fluorescence spectra, and the test error is much less than allowable variation. The technologies in this paper can play an important role inmedical examination, agriculture, and food safety testing.

In this paper, the feasibility of using aqueous fingerprint based on fluorescence excitation-emission matrix to reveal organic components of veterinary antibiotic wastewater was studied. There were 4 peaks in the aqueous fingerprint of the wastewater with excitation and emission wavelengths (ex/em) of 225/345, 275/345, 325/405 and 405/470 nm and marked as A, B, C and D, respectively. The intensity ordering of these 4 peaks is B>A>C>D. The intensities of peak B and A were relatively high, which were (0.64±0.21), (0.99±0.30) R. U, respectively, and had linear relationship with correlation coefficient of 0.95. Besides, same emission wavelength of these two peaks indicated they were likely to be produced by the same substance. The intensity of each peak demonstrated significantly positive correlation with COD (R2=0.66～0.70). The substances related to peak C were partially degraded or possessed low degradation rate, while the substances related to other three peaks could be degraded well. The new peak (ex/em 260/425) appeared in effluent water might relate to humic substance generated in microbial metabolism of the wastewater treatment. Above all, the properties of aqueous fingerprint of veterinary antibiotic wastewater were distinct and distinguishable. Aqueous fingerprint identifying technology could be a novel tool to identify such wastewater from water body. The information about total organic matters and organic compounds composition provided by aqueous fingerprint is of great value to refractory wastewater treatment designing and operating.

In recent years, environmental endocrine disruptors have attracted more and more attention. Traditional detection methods are time-consuming, complex and expensive, which means the development of fast response, high sensitivity and low cost detection method is of vital importance. Herein we described a planar waveguide-based array evanescent wave fluorescent biosensor. Based on the simulation and optimization of the optical parameters of the system, it allows the measurements of up to twenty-four sensing spots simultaneously, rapidly and highly sensitive. By using the indirect competitive immunoassay, the detection conditions of the array evanescent wave fluorescent biosensor were optimized and established for the environmental endocrine disruptor of estradiol. The experimental results show that the system has the highest sensitivity at 61.8°. The linear response ranged from 0.08~2.52 μg·L-1 has the detection limit of 0.05 μg·L-1 and the 50% inhibition concentration (IC50) of 0.46 μg·L-1. One test cycle was completed within 20 min. The recoveries of estradiol in all sorts of wastewater effluents ranged from 84% to 120% has relative standard deviation values of less than 15%, confirming the application potential in the measurement of estradiol in reality.

Fluorescent carbon dots (CDs) with a fluorescent quantum yield of 23% was successfully synthesized by one-step solid-state approach with citric acid and urea as carbon source and nitrogen source. It was found that the obtained CDs have highly disordered carbon structure and show sphere with an average diameter of 3~4 nm. In addition, the surfaces of CDs were covered with hydroxyl, carboxyl and amine groups. Based on the fluorescence resonance, energy transfers from fluorescence carbon dots to ADM (doxorubicin or adriamycin), the fluorescence of CDs can effectively quenched by ADM and a novel method for the sensitive and selective determination of ADM was proposed in this paper. Some experimental parameters, such as pH value of the reaction solution and reaction time were investigated. Under the optimum conditions, the decrease of CDs fluorescence intensity was in a good linearity with ADM in the concentration range of 0.67～16.67 μg·mL-1 (R2=0.995), the detection limit of the method was found to be 0.22 μg·mL-1, and the spiked recoveries ranged from 83.0% to 89.2% with RSD no more than 2.5%. he result showed that common relevant substance, cations and anions did not significantly interfere with the detection of ADM．

Cellulasel plays an very important role in the ecosystem and the nutrient cycling. It can decomposite cellulose to small molecules of sugar and provide energy for biological activities. How to measure cellulase activity quickly and accurately is of great significance for the diagnosis and restoration for soil ecosystem. Different nitrogen treatments and cultivate would influenced enzyme activity. This study use automatic TECAN Infinite 200 Multi-Mode Microplate Reader (made in Germany) bombined with 96 microplates and fluorescence (4-Methylumbelliferyl β-D-cellobiopyranoside (Cel)) detection method to detect the activity of cellulasel under different tartary buckwheat (DiQing-low nitrogen toleration, HeiFeng 1-low nitrogen intoleration). During the process, the experiment use less substrate and put the control and sample together in the same plat,then reduced the culture space and operation time. The results showed that except the normal nitrogen treatment under the maturation stage, cellulasel was higher in DiQing than in HeiFeng 1 in the stage of seeding and flowering. In addition, the activity of cellulase in root trace of Diqing was higher than that of Heifeng 39.50% under low nitrogen treatment at seedling stage. Cellulasel had a significant difference among nitrogen treatments in the flowering and maturation stage, much higher activity in normal treatment when compared with the others under DiQing, but Heifeng only showed the same trend in flowering stage. The enzymatic activity of sterilizing treatment was significantly lower than that of normal nitrogen treatment of 54.29%, which indicated that some of cellulase in root trace of Diqing Tartary buckwheat originated from the contribution of microorganism, and the activity of microorganism was higher when the nutrient was sufficient. The analysis of cellulase activity by fluorescence spectrum showed that the resistant variety Diqing Tartary buckwheat could resist the stress of external environment by increasing the activity of soil enzyme in root trace. While in the poor nutrient soil in Loess Plateau, maybe selecting barren-tolerant varieties would reduce costs and increase the benefits for farmers. Compared with traditional method, fluorescence microplate fluorescence microplate method is quick, accurate and economical. It is also suitable for mass sample determination, which can provide timely data support for foreign precision agriculture production and soil testing formula fertilization in the further.

The variation of temperature is one of the main interference factors that affect the accuracy of near-infrared (NIR) non-invasive blood glucose sensing. In order to reduce the influence of temperature variation on NIR diffuse reflectance, a measurement method based on temperature insensitive source-detector separation was proposed in this paper, i. e., the temperature insensitive source-detector separation, whose diffuse reflectance was insensitive to temperature variations, was chosen to obtain the spectrum. The Monte Carlo method was used to simulate the diffuse reflectance at multiple source-detector separations with temperatures of 30～40 ℃ and glucose concentrations of 0～300 mmol·L-1. According to the simulation results, the existence of temperature insensitive source-detector separation in human skin tissue model and the influence of glucose concentration on the separation were analyzed. At wavelength of 1 000 nm, the correlation between the diffuse reflectance and glucose concentration at different source-detector separations under random temperature and constant temperature were compared. Furthermore, the partial least square (PLS) model of glucose were established using the diffuse reflectance at temperature insensitive source-detector separations and other separations under six wavelengths (1 000, 1 050, 1 100, 1 150, 1 350 and 1 410 nm), and the prediction accuracy of the model under random temperature and constant temperature were compared. The results showed that, in the range of 1 000～1 440 nm, there were temperature insensitive source-detector separations in human tissue, and the influence of glucose concentration variationon it can be ignored. When the temperature of the sample variates, both the correlation between glucose concentrations and diffuse reflectance and the prediction accuracy of model obtained at the temperature insensitive source-detector separation were significantly better than that of other separations, which was almost close to the situation of constant temperature. Therefore, the measurement method based on the temperature insensitive source-detector separation can effectively reduce the influence of temperature variations on NIR diffuse reflectance, and it is expected to improve the accuracy of NIR diffuse reflectance in non-invasive blood glucose sensing.

Accurate and timely crops classification information is of great significance for arid food security monitoring and ecological management. Adding sensitive waveband and improving classification methods are the major development trends of crops classification. In this paper, we carry out crop classification study based on Sentinel 2A time-series remote sensing data, and establish an object-oriented parcel point set in study area, trying to explore the influence of using different classification features on machine learning classification accuracy. Results indicate as follows: (1)Random forest classifier can effectively integrate the benefits of multidimensional vectors such as spectral or vegetation index, all the accuracy of different groups in this study are above 89%, while the supreme overall accuracy up to 94.02%. (2) The classification features extraction method, which was supported by object-oriented parcel point set, can resolve the issue of salt-and-pepper noise and fuzzy parcel boundary well. Meanwhile, it also improves the efficiency and accuracy of machine learning classifier, which can be demonstrated by the result that the classification accuracy of spectral group and index group increased by 3.13% and 4.07% respectively. (3)Red-edge features can help the classifier to capture the phenological differences and unique growth characteristics of different crops. And the introduction of the red-edge spectrum and red-edge index can improve the classification accuracy by 2.39% and 1.63% respectively, while the recognition ability of spring and winter wheat also improved significantly. The result of this study can be referred for the application of the machine learning method and the Sentinel 2A remote sensing data in arid agriculture remote sensing.

Gold nanoclusters (Au NCs) consists of a few to several hundred gold atoms and modified reagents, is a new kind of labeled nanoprobes, which have good luminescent properties and biocompatibility due to its size close to the electron Fermi wavelength. Up to now, gold nanoclusters have attracted wide attention in the fields of biological detection, cell imaging, cancer diagnosis and treatment. However, the stability of gold nanoclusters under irradiation condition is still unclear. In this manuscript, histidine and glutathione modified gold nanoclusters were prepared, and the fluorescence changes of gold nanoclusters under the irradiation conditions at different pH (5.0, 7.4 and 9.0) were investigated. The results show that the fluorescence of gold nanoclusters decreases with the increase of irradiation time of xenon light, which is decreased faster at pH =9.0 than that at pH=5.0 and 7.0, indicating that the gold nanoclusters have better light photostability at pH=5.0 and 7.4. On this basis, the changing rule of surface groups of gold nanoclusters before and after irradiation were studied by UV-Vis absorption spectrum and Infrared spectrum. The results showed that the UV-Vis absorption spectrum and Infrared spectrum of the gold nanoclusters change obviously after irradiation, indicating irradiation leads to changes in surface modified groups of gold nanoclusters. When nitrogen is introduced into the system, the fluorescence intensity at λmax wavelength of the gold nanoclusters changed more slowly with the irradiation time than that without nitrogen, indicating that the surface groups of the gold nanoclusters react with the dissolved oxygen in the solution, resulting in changes of the surface charge and the condition of modified reagents, then leading to reducting the fluorescence intensity of gold nanoclusters. The results of this study have some reference value for the further application of gold nanoclusters in life sciences and analytical chemistry.

Printer characterization is of crucial importance for the color management of color printing. The updating of spectral printer characterization model aims at maintaining the accuracy of the existed printer characterization model by certain corrective algorithm, when the printing substrate or ink cartidge is changed. In this study, a novel method was proposed to improve the modification performance for current printer characterization model, which derived the modification samples from ink limitation process. The superiority of the proposed method was verified by comparing its performance to a typical approach with regard to three different printing substrates. The experimental results show that the proposed approach outperformed its counterpart by promoting the spectral accuracy by 15%～20% while promoting the colorimetric accuracy by 10%～20%, with no need of extra sampling.

A new method for visual detection of trace Hg2+ ions was successfully established based on the single-stranded DNA (ssDNA) and T-Hg2+-T complex have different interaction with graphene oxide(GO), which owns mimetic enzyme catalytic performance. In NaAc-HAc buffer of pH 4.0, ssDNA can be adsorbed on the GO surface, which will efficiently decrease the peroxidase-like activity of GO to catalyze the oxidation of peroxidase substrate TMB to form blue product in the presence of H2O2, which presented a characteristic absorbance at 652 nm. When Hg2+ ions exist, the ssDNA formed double-stranded DNA via thymine-Hg2+-thymine complex coordination structure, which hardly absorbed on the surface of GO for the interactionbetween dsDNA and GO is much weaker, the peroxidase mimetic activity of GO is not affected, accompanying with the color darkening and increase of absorbance at 652 nm. Under the optimal conditions, the absorbance versus Hg2+ concentration is linear in the range from 3.26×10-8 to 9.0×10-7 mol·L-1, which can make a calibration graph. The regression equation is ΔA=41.75c(nmol·L-1)+0.048 7, r=0.997 3. The limit of detection is 9.79×10-9 mol·L-1. This method has the advantages of simplicity, cost saving and good specificity, thus can be applied for determinating mercury ion in the environment samples.

CeO2 has been widely used because of its abundant resources on earth, price advantages and excellent catalysis properties in many fields. The lattice size and the concentration of the lattice defects of CeO2, which can be deemed as the key features to improve the catalysis properties, can be adjusted by doping foreign ions to form CeO2 based solid solution. At present, numerous researches mainly focus on doping metal cations into the lattice of CeO2, while introducing non-metal anions is still under exploration. In this paper, nanosized CeO2-xNx solid solutions with different N doped contents (x=0.00, 0.05, 0.10, 0.15, 0.20) were synthesized by using CO(NH2)2 as the N source via hydrothermal method. In addition, the microstructure and spectral characteristics of the solid solutions were analyzed systematically. The XRD results showed that all of the CeO2-xNx solid solutions exhibited cubic fluorite single phase structure. Compared with the pure CeO2, the cell parameters of the sample with N 0.05 increased obviously, while it decreased gradually with the further increasing N content. The Raman spectrum indicated that the vibration mode of F2g peak shift to higher wavenumbers. This could ascribe to the enhanced electrostatic attraction of Ce—N with the shorten bond length, which was formed in the lattice of CeO2 when the O2- was substituted by N3-. The change of the electron transition state of the samples was illustrated by UV-Vis spectra. It was found that the doping of N element into the CeO2 gives rise to the absorption in the visible light region, and the band gap energies decreased obviously. It could be explained that the formed intermediate energy level, which was caused by the interaction effect of N(2p) and O(2p) electron orbits, induced the decreased energy of the electron transition. The photoluminescence spectra indicated that the intensity of the emission peak was enhanced by increasing the N doped content. This could be illustrated from two aspects. On the one hand, the promotion of the concentrations of the lattice defects and the oxygen vacancies precipitate the increased rate of the transition between the bands, and then improve the relative intensity of the emission peak; on the other hand, the intermediate energy level formed between the valence band of O(2p) and the conduction band of Ce(4f) because of the introduction of N element also resulted in the strength of the emission peak. In order to characterize the catalysis properties of the nanosized solid solutions, the sample of CeO1.95N0.05 with the minimum N doped content, the sample of CeO1.80N0.20 with the highest N content and the pure CeO2 were chosen as the typical catalysts to synthesize the Mg2Ni/Ni/CeO2-xNx composites via the ball milling method. The cell kinetic properties of the composites were measured systematically. The electrochemical impedance spectrum (EIS) test found that the solid solutions catalysts could enhance the charge transfer abilities on the surface of the Mg2Ni hydrogen storage alloy electrodes effectively. And the more the N content was doped, the higher the catalysis activity of the CeO2-based solid solutions showed. The potentiodynamic polarization curves measurement displayed that the diffusion rates of the H atom in the bulk of Mg2Ni were also improved by adding the doped catalysts, and the catalysts of CeO1.95N0.05 has better catalysis effect than that of CeO1.80N0.20. The catalysis mechanism of the solid solutions was investigated from the point of the microstructure and the spectra features of the nanosized catalysts. As discussed above, it was found that the concentration of the oxygen vacancies and the degree of distortion of the lattice were increased by improving the N content, and the band gap energies of the solid solutions were decreased by N doping, which made the catalysts in favor of the electrons exchange interactions on the alloy surface. Meanwhile, the more refining of the crystalline size indicated the higher content defects on the particle surface, and further illustrated the improvement of the effect of the catalysts. Thus, these features of the catalysts could be used to explain why the catalysts with higher N content, the smaller radius of the AC impedance of the composites electrode showed. Or in other words, the catalysts of CeO1.80N0.20 could enhance the surface activity of the composites more obviously. What’s more, the enlargement of the cell volume of the catalyst would provide larger space for the H atoms when they were moving across the surface of composites. Under this condition, the transition of H atoms became easier, for the composite with CeO1.95N0.05 has larger cell parameter than CeO1.80N0.20. Therefore, diffusion rates of H atoms in the bulk of the alloys were closely related to the cell volumes of the catalysts.

Until now, multinational related color scientists have accumulated more than 40 color formula, but the current use of all the color difference formula can only be limited to the given observation conditions in the CIE. Solid-state lighting as the focus of recent years, the focus of research, related research, such as related research based on LED lighting conditions has not started yet. So in this experiment, following the CIE color of the guiding principle of the study, we first selected CIE recommended 17 color centers in the five colors, which were made of experimental color proofs, followed by U30, TL84, D65 standard light source was set as the reference light source, To LED light bulb as experimental light source. The CIE1976LUV color difference formula, CIE1976LAB color difference formula and CIEDE2000 color difference formula were used to calculate the color difference of the printed patches respectively. Then, 20 visual observers were used to evaluate the subjective color difference of the printed patches by the visual evaluation experiment based on psychophysics. Finally, the objective calculation residual value (STRESS) is used to compare the objective calculation value with the subjective evaluation data. Found in this test selected three color formula in the LED lighting conditions, the color prediction performance is not very satisfactory. Overall, in the LED lighting conditions, CIE1976LUV formula predictive performance is relatively better, followed by CIEDE2000 formula, CIE1976LAB formula the third.

Differential near infrared optical density has the advantages of rapid and noninvasive detection when detecting the traumatic subdural hematoma . This technology is a hot research topic in recent years, it has an important application in emergency treatment. To further improve the accuracy of traumatic subdural hematoma degree predication, the multi-channel differential absorbance method is used in this paper. We use 5 detectors that have different distance to the source to obtain absorbance data. In addition, we use partial least square method to establish the calibration model between the optical absorption coefficient of the brain and differential optical density. The model prediction results show that average relative error of absorption coefficient is 11.16%, and average relative error of hematoma depth is less than 1%. The model basically meets the demand of traumatic subdural hematoma degree predication. By introducing multi-channel differential optical density in the detection, it could eliminate the effects of individual differences and improve the accuracy of traumatic subdural hematoma degree predication. This method provides a new idea and an important reference for the brain detection with near infrared spectroscopy.

Model transfer among different soils is the key point and obstacle and obstacle for rapidly determining soil nutrients by Vis-NIR spectroscopy. Here, we studied the methods and results of model transfer for total nitrogen(TN) between two types of soils in Qingdao, China. A main spectral model was firstly set up using soils sampled from Licun River. Then, by using piecewise direct standardization combined slope/bias algorithm (PDS-S/B), PDS combined linear intercept algorithm(LI), canonical correlation analysis (CCA) combined S/B (CCA-S/B), CCA-LI, direct standardization (DS) combined S/B (DS-S/B), and DS-LI, the concentrations of total N in soils sampled from Fushan Montain were predicted by the main spectral model with different accuracy. Results of model transfer by PDS-S/B was the best, whose root mean square error (RMSE), mean relative error, and maximum relative error were 0.04, 6.6%, and 19.0%, respectively. Pretreatment before building the spectral model could influence the transfer results. Here, the main spectral model built after extracting the diagnostic spectra genetric algorithm had better results than those built without any pretreatment. Transfer methods could also affect the transfer results. The transfer methods related to LI had a larger increase in accuracy than those related to S/B. The best model transfer was from PDS-S/B, suggesting that PDS-S/B was the better method for this study. This study resolved a specific model transfer for TN between two different types of soils under the same conditions by the same instrument, different from other studies which studied the model transfer of the same soil under different instrument and work conditions. This study explored the possibility that a spectrometer shared a same spectral model, which will improve the efficiency and promote the use of soil nutrient rapid determination by spectroscopy.

In this paper, the spectral characteristics of potato key growth period are analyzed by using hyperspectral remote sensing technology, and a quick method to distinguish different potato varieties was proposed. In addition, two potato varieties with early maturity and medium maturity are taken as the research materials, and the canopy reflectance spectrum curves of tuber formation stage, tuber expansion stage and starch accumulation stage are collected, Savitzky-Golay filtering smoothing and first order differential processing are applied to the measured reflectance spectrum curve, hyperspectral position parameters, amplitude parameters, area parameters, width parameters and reflectance parameters are used as evaluation indices, according to the contribution rate of 21 hyperspectral characteristic parameters, their ability to distinguish different potato varieties is evaluated. The results show that: (1) The ability of the same type of high spectral characteristic parameters to distinguish potato varieties at different growth stages is different. Hyperspectral position parameters, width parameters and reflectance parameters have the strongest ability to distinguish different potato varieties during tuber expansion stage, followed by starch accumulation stage; high spectral amplitude parameters and area parameters have the strongest differentiation ability in starch accumulation stage, followed by tuber expansion stage, and the 5 types of hyperspectral characteristic parameters have the worst differentiation ability in tuber formation stage. (2) In the same growth stage, there are differences between the 5 kinds of hyperspectral characteristic parameters in distinguishing potato varieties. In the tuber formation stage, the ability of distinguishing 5 kinds of hyperspectral characteristic parameters from strong to weak is as follows: reflectance parameter>amplitude parameter>area parameter>width parameter>position parameter; In the period of tuber expansion and starch accumulation, the order from strength to weakness is as follows: area parameter>amplitude parameter>reflectance parameter>width parameter>position parameter. The comprehensive ability from strong to weak is as follows: area parameter>amplitude parameter>reflectivity parameter>width parameter>position parameter.

Nitrogen is one of the most important fertilizers and closely related to the growth, development, yield and quality of crops. Rapid, accurate and non-destructive assessment of nitrogen content in crops is critical for nutrition diagnosis and growth monitoring. Traditional detection methods of nitrogen content are complicated, time-consuming and destructive, which makes the continuous dynamic monitoring of nitrogen content in time and space impossible. It is a hot topic for rapid and non-destructive estimation of crop nitrogen content based on spectral remote sensing technology in recent years. Nevertheless, existing researches about the estimation of nitrogen content were mostly focused on the original or integer differential spectra (first order, second order). Some studies indicated that the original or integer differential spectra might ignore the effective information, which would influence the estimation accuracy of nitrogen content in crops. Fractional order differential algorithm has the advantages in background noise removal and effective information extraction compared with the integer differential methods. Hence, the objective of this study was to explore the feasibility of detecting nitrogen in crops by fractional order differential algorithm. 256 datasets, which were consisted of canopy spectral data and the relevant canopy nitrogen content (CNC) data, were collected during seedling, flowering, pod and drum stages in soybean plants. The plants were treated with different fertilizer components under pot conditions. 0~2 order differentials of spectral data were computed by Grünwald-Letnikov fractional differential equation with differential interval of 0.1. Afterwards, the correlation between the preprocessed spectra and soybean CNC under different fractional order differential were analyzed using the normalized difference spectral index (NDSI) and ratio spectral index (RSI). The maximums of correlation coefficient between soybean CNC and NDSIα (α is the fractional differential order), and between soybean CNC and RSIα were determined under each fractional order differentials. Simultaneously, the corresponding optimal band combinations of NDSIα(opt) and RSIα(opt) were obtained respectively. Eventually, the estimation models of soybean CNC based on NDSIα(opt) and RSIα(opt) under different fractional order differential were established and compared using linear regression method. The estimation models of soybean CNC based on five common vegetation indices including VOG II, MTCI, DCNI, NDRE and TCARI were also established and compared. The results showed that: (1) With the increasing of differential order, the correlation coefficients between soybean CNC and NDSIα(opt), soybean CNC and RSIα(opt) increased firstly and then decreased in the fractional differential range of 0～2. For NDSIα, the maximum correlation coefficient was obtained between soybean CNC and NDSI0.8(R725, R769) under 0.8 order differential, and the relevant value was 0.875 9. For RSIα, the maximum correlation coefficient was obtained between soybean CNC and RSI0.7 (R548, R767) under 0.7 order differential, and the relevant value was 0.865 1; (2) The useful information in spectral data could be extracted and refined using fractional differential algorithm. Therefore, the sensitivity of spectra to soybean CNC could be enhanced. Specifically, the positive correlation between soybean CNC and the band near red edge platform, and the negative correlation between soybean CNC and near the band near green region were enhanced; (3) Compared with the models developed by integer differential and common vegetation indices, the estimation models based on fractional differential were more accurate. For integer differential, the determination coefficients of calibration (R2C) and prediction (R2P) based on RSI0.7(R548, R767) under 0.7 order differential improved 0.061 9 and 0.016 6 compared with the model based on RSI0 (R725, R769) under 0 order differential, respectively. The relevant root mean square errors of the calibration (RMSEC) and prediction (RMSEP) were reduced 0.552 5 and 0.180 9, respectively. The relevant ratio of prediction to deviation (RPD) increased 0.110 4. For common vegetation indices, the R2C and R2P based on RSI0.7(R548, R767) under 0.7 order differential improved 0.086 6 and 0.025 5 compared with the model based on VOG II, respectively. The relevant RMSEC and RMSEP were reduced 0.757 5 and 0.248 3, respectively. The relevant RPD increased 0.146 88; (4) The model based on the ratio spectral index RSI0.7(R548, R767) under 0.7 order differential had the best performance in estimation of soybean CNC with R2C of 0.748 4, R2P of 0.800 3, RMSEC of 4.752 9, RMSEP of 3.511 1 and RPD of 2.253 7 in this study. The results indicated that fractional differential algorithm had the advantages in the quantitative estimation of soybean CNC, which provided a new view for the estimation of crop nitrogen content based on spectral remote sensing technology.

Under the background of carrying out the “potato staple food” strategy in China, it is of great significance to do more related researches of the potato crop. In this paper, the comparison and analyses of spectral differences of different potato cultivars in different periods were aimed to provide theoretical and technical support to the identification of potato varieties, the distinction of potatoes and other crops, the extraction of potato spatial distribution, the monitoring of potato pests and diseases, the impacts of potato stresses as well as the various crop identification studies and provide a new idea for the crop hyperspectral correlation research. What’s more, the canopy hyperspectral reflectance data of the early maturing potato cultivar (Favorite), the middle-late maturing cultivar (Yanshu 4) at the tuber stage and expansion stage were obtained through field experiments in Jilin area. Firstly, the noise was removed by the method of Savitzky-Golay filtering. Then the spectra of continuum removal were obtained by the method of continuum removal and 6 parameters (the maximum absorption depth, total area, left area, right area, symmetry and area normalized maximal absorption depth) were extracted. Meanwhile, the first-order derivatives were calculated using the filtered spectral reflectance data and the spectral reflectance data of continuum removal. On the basis of the comparison of the two spectral reflectance curves of different potato cultivars, 8 different indices of 3 groups (reflectance difference index, first order derivative difference index, spectral parameters of continuum removal difference index) were constructed as evaluation indices. The reflectance difference index and first order derivative difference index were calculated using the bands of green light at 550 nm, red light at 670 nm and near-infrared light at 760 nm. Furthermore, we quantitatively analyzed the hyperspectral differences of different potato cultivars using these difference indices. In this paper, the method of continuum removal was applied to the analyses of hyperspectral differences of different potato cultivars with different growth stages. The difference indices in the article finally achieved good evaluation performence. The results showed that: (1) Compared with the reflectance difference index and maximum absorption depth difference index, the first order derivative difference index, total area difference index, left area difference index, right area difference index, symmetry difference index and normalized difference index could show the hyperspectral difference of different potato cultivars well. The spectra of continuum removal partially magnified the hyperspectral differences of two different potato cultivars. (2) The wavelength position and growth period of the filtered spectra and the spectra of continuum removal with the largest difference were the same located at the wavelength of 671.24 nm on August 16. The value of maximum absorption depth difference index was only 0.01. The value of first order derivative difference index of the filtered spectra reached 0.977 at the wavelength of 673.55 nm on June 24. The value of the first order derivative difference index of the continuum removed spectra reached 47.87 at the wavelength of 759.74 nm on June 24, which worked the best in spectral difference analyses of different potato cultivars. Besides, the total area difference index, right area difference index, symmetry difference index and normalized difference index all reached the maximum on June 24, with the values of 0.13, 0.214, 0.205 and 0.113, respectively. The left area difference index value reached the maximum of 0.199 on July 24. (3) According to the quantitative evaluation results of the difference indices, we could see that the period with the biggest hyperspectral difference of the two different potato cultivars is in the medium-late stage of tuber stage of early-maturing variety and initial stage of tuber stage of medium-late maturing variety.

Although the analysis of the reflectance spectral characteristics of pure minerals and the establishment of a database have been carried out, the test of primary minerals and clay minerals in soils is mainly qualitative, which means that it is possible to determine what minerals are contained in soils. However, it is difficult to accurately determine the contents of minerals. Soil minerals are the intersection of pedology and geology, which is easy to be ignored, especially the effects of soil minerals on soil reflectance spectral curves has been neglected in other researches. In this paper, we discussed the effects of soil minerals on the characteristics of soil reflectance spectra in the visible and near infrared region (400~2 500 nm), and clarified the main mechanism about affecting the characteristics of soil reflectance spectra. Soil samples were collected in the Heilongjiang part of Songnen Plain in 2014, including four great groups and seven genera, a total of 54 soil samples. After grinding and sifting, the soil samples were measured in the darkroom to obtain reflectance spectrum data. The reflectance spectrum data of soil minerals were obtained from the 2017 USGS mineral spectral library. We smoothed spectral reflectance data with nine points, resampled at 10-nm intervals and continuum removal. The mineralogical phases of the samples were detected by an X’Pert-Pro XRD (Philip, Holland). The contents of primary minerals, such as quartz, feldspar, calcite and amphibole, and clay minerals such as montmorillonite, illite and kaolinite were measured. First of all, we analyze the reflectance spectral characteristics of seven genera, and determine the shape characteristics and absorption position of spectral curves of each genus. Secondly, we analyze the mineral content of genera, and find out the commonness and difference of each mineral content of different genera. Thirdly, we analyze reflectance spectral characteristics of different primary minerals and clay minerals, and determine the shape characteristics and absorption position of different soil minerals. Finally, we combine the spectral characteristics of different genera, mineral content of different genera and spectral characteristics of soil minerals, the following conclusions are obtained: (1) The skeleton characteristics of soil reflectance spectra are determined by soil minerals, and the effect of soil minerals on reflectance spectra of genera is the most obvious, however, the effect at great group level isn’t obvious due to the existence of various reflectance spectral characteristics of great group. (2) The effect of clay minerals on soil reflectance spectral characteristics is greater than primary minerals, mainly by clay minerals such as montmorillonite and illite, but feldspar and kaolinite affect sandy soils. (3) Montmorillonite determines the characteristics of the first absorption valley, the illite determines the second valley, kaolinite determines the two small absorption valleys before 1 400 and 1 900 nm, and microcline and albite determine the first and second valleys of sandy soils. (4) When the content of montmorillonite is high enough, the spectral characteristics of kaolinite and feldspar will be completely masked, and the spectral characteristics of illite will be partially masked. With the decrease of montmorillonite content, the spectral characteristics of illite will be gradually reflected. When the content of montmorillonite and illite decreases to a very low level, the spectral characteristics of kaolinite and feldspar minerals gradually manifest. The results explain the reasons for the differences in spectral characteristics of different genera, which can provide theoretical basis for soil spectral classification, detailed soil mapping and mineral distribution based on hyperspectral images.

Soil is an important carrier of the human living environments. Therefore, the problem of soil heavy metal pollution has always attracted attention. With the development of remote sensing technology, much progress has been made in the area of hyperspectral remote sensing, which is used for the study of the heavy metal content of soil. However, this method works basically in accordance with spectral absorption features, as well as the content of soil organic matter, iron and clay minerals, when retrieving the heavy metal content of soil. It has been found to be unable to distinguish the slight differences in the soil heavy metal pollution spectra. In this study, a potting soil pollution experiment with different concentrations of copper (Cu) and lead (Pb) was used to obtain the potting soil spectral curve, as well as the water and organic matter content of the soil under different concentrations of Cu and Pb stress. The purpose of the experiment was to put forward a type of second-order differential Gabor expansion method for the detection of the slight differences between the soil’s spectral curves under different concentrations of Cu and Pb stress. Firstly, based on the second-order difference method, the soil spectrawere converted into sparse spectra by the method, then the sparse spectrum of soil and Gabor expansion theory were combined to detect the weak differences of heavy metal stress spectra in different concentration soils in the frequency domain. Therefore, instead of studying the content of soil heavy metal solely by the spectral reflectance information, this method performed time-frequency analysis on the spectral information of soil heavy metal stress and finally achieved the purpose of detecting the instantaneous spectrum of soil heavy metal pollution. The results showed that the Cu-contaminated potting soil spectra displayed major differences in the scale distribution of the second-order differential Gabor expansion coefficient when compared with the Pb-contaminated potting soil spectra. In addition, the scale of second-order differential Gabor expansion coefficient of the Cu-contaminated soil spectra ranged from 1 800th to 3 600th items sparse, the scale of second-order differential Gabor expansion coefficient of the Pb-contaminated soil spectra ranged from 3 200th to 3 600th items coarctate. By utilizing a second-order differential Gabor expansion method, the detected results of the Cu and Pb pollution in the soil were found to be closely related to soil’s Cu and Pb content, water content and organic matter. As a result of the different Cu and Pb content in the soil, as well as the organic matter content and water content, the second-order differential Gabor expansion spectra of the soil’s Cu and Pb pollution displayed different scale distributions. According to the correlation analysis results, the soil’s Cu and Pb pollution were divided into three grades respectively: Cu(50)~Cu(300), Cu(400)~Cu(800), Cu(1 000) or more; lowerthan Pb(50), Pb(100)~Pb(300), Pb(400)~Pb(1 200).

Due to the low accuracy of soil Cd concentrations estimation and the great difficulty of characteristic spectral wavelength identification using hyperspectraldata, a comparative study on quantitative estimation of soil Cd concentrations was carried out in this paper by using the type standard soil samples and naturally contaminated soil samples from one mine in Hunan province, China. The main innovation includes the schemeproposition of type standard soil samples production and the development of comparative experiments. This study produced the type standard soil samples by adding quantitative standard solution of Cd into relatively clean background soil. The experimental process also includes the field collection of naturally contaminated soil samples, the determination of soil composition, such as heavy metals, organic matter, the measurement of 350～2 500 nm soil spectral reflectance, and the total factor principal component stepwise regression modeling of soil Cd concentrations using spectral reflectance. The results showed that accuracy of the model based on type standard soil samples was higher (adjR2=0.87) than traditional modeling results based on naturally contaminated soil samples (adjR2=0.39). In addition, this study defined the existence of the spectral response between soil Cd concentrations and spectral reflectance. However, the effect of Cd concentrations on the soil spectral reflectance acted on all the wavelengths in various degrees among which, the spectral response signals in the wavelength of 1 000, 2 000 and 2 300 nm were relatively stronger. In this study, the innovatory scheme of type standard soil samples production is helpful to deeply explore spectral response characteristics of soil Cd and find out the real indicative characteristic bands of soil heavy metal concentrations. Furthermore, it will provide priori knowledge for quantitative estimation of soil heavy metal concentrations in the mode of multi-factor confounding pollution.

In this paper, X-ray fluorescence spectrometry (XRF), no standard complete quantitative analysis and microwave digestion/inductively coupled plasma mass spectrometry (ICP-MS) were used to perform the elemental analysis of two types of meteorites. Determination of macro-element in meteorite samples by XRF method, and determination of micro-element in meteorite samples by ICP-MS method. Experimental results show that: The XRF method can be used to detect the meteorite samples content in 10 μg·g-1 above all metal and nonmetal elements, it is concluded that the 6 major elements in the two types of meteorites are Fe, Mg, Si, Na, Al, Ca. Iron meteorites in different regions contain large amounts of Fe, stone meteorites contain a large amount of Si . Determination of 24 elements in meteorites by ICP-MS, by comparing and analyzing the 9 elements of V, Ni, Mo, Ag, Sn, La, Gd, Hg, Pb, the content of heavy metals and rare earth elements in iron meteorite is much higher than that in stone meteorite. The content of Sn in all iron meteorite samples is about 10~25 times as much as that in stony meteorites, the contents of rare earth elements La and Gd in iron meteorites are about 6 times as much as those of stony meteorites. The content of Pb in 5A and 6A iron meteorites in Xinjiang is 5~13 times more than that in iron meteorites from Shandong (1A, 2A, 3A, 4A). The stone meteorites from Inner Mongolia (9B, 10B) have more than three elements La, Mo and Gd from the stone meteorites (7B, 8B) from Xinjiang.

A simple and efficient method for the determination of Pb and Cd in domestic water and drinking water was developed by combining low-density solvent based dispersive liquid liquid microextraction (LDS-DLLME) with graphite furnace atomic absorption spectrometry (GFAAS). In the LDS-DLLME, a mixed solution of octanol (extraction solvent) and methanol (dispersive solvent) was rapidly injected into the sample solution by a microsyringe to form a cloudy emulsion. With diethyldithiocarbamate (DDTC) as chelating agent, Pb2+ and Cd2+ were extracted into the highly dispersed octanol microdroplets. The mixture was then centrifuged and the chelates of Pb and Cd moving into the organic phase, which was analyzed by GFAAS subsequently. In addition, the experimental conditions were investigated and optimized, such as the type and volume of extractant and dispersant, pH, DDTC concentration and extraction time. Under the optimal experimental conditions, the detection limits of Pb and Cd were 0.15 and 0.03 μg·L-1, and enrichment factors were 87 and 48, respectively, with good linearity and precision. This method has the advantages of simplicity, rapidity, low cost, and high enrichment. It is successfully applied to the determination of trace Pb and Cd in tap water, drinking water and South Lake water.

As an instrument for observing astronomical spectroscopy, imaging spectroscopy plays a very important role. Due to the slit limitation of the traditional slit type imaging spectrometer, the observation of the surface source object needs to be scanned several times in order to obtain the complete three-dimensional data cube (x, y; λ), which will waste a lot of observation time. In order to realize the fast scanning of the three-dimensional data cube of the target object, this paper presents a micro-lens array with no slit, static, fast and efficient visible-to-infrared band integral field imaging spectrometer structure, and analyses its basic working principle. In order to expand the application potential of spectrometer in medicine, agriculture, geophysical prospecting and other fields, the spectral bands selected in this paper ranged from visible to near infrared. According to the working principle of field integration, the off-axis three-reverse imaging system is analyzed and designed. The system uses the field of view from the off-axis mode, the band range is 400～900 nm, relative diameter is F/5. Primary mirror, secondary mirror and three mirrors are all secondary aspherical mirrors, the second aspheric surface coefficients are -7.05, -0.92 and -1.61, respectively. In order to reduce the system volume, the mirror is placed near the focal plane of the off-axis three-reaction system. In the Nyquist space with the frequency of 60 lp·mm-1, the modulation transfer function is greater than 0.75, the image quality close to the diffraction limit. These parameters all meet the system requirements.

In this paper, the energy of pump threshold value of DCM doped liquid crystal laser is theoretically calculated (9.2×10-7 J). In addition, the most suitable pump light source are selected, and the corresponding pump experiment is designed. The characteristics of the laser are studied through detecting the light intensity and wavelength of the output laser. The results show that the laser wavelength can be tuned in the range of 100 nm (585～685 nm) by changing the grating period which accords with the theoretical calculation. In the meanwhile, the laser wavelength can be tuned by applying the applied electric field. What’s more, the output laser strength can also be switchable, and the intensity switchable ability can reach 90.2%. The application prospect of dye doped liquid crystal laser in the all optical network communication field is greatly expanded because of the switchable ability. However, when the electric field increases from 0 to 20 V·μm-1, the line width of the laser is increased from 0.4 to 1.5 nm. The change of line width should be noted in the tunable application of dye doped laser.

Hydroxyl, one of the principal oxidants in the atmosphere, determines the density of ozone and other greenhouse gases even the change of climate. In order to achieve high resolution vertical profiles of OH radical in mesosphere, an accurate forward model should be built up for its retrieval. In this paper, this forward model simulates limb-scattered signal including OH solar resonance fluorescence around 309 nm. We calculate OH band rotationalemission rate factor g based on molecular spectroscopy theory, and combine it with OH slant column calculated by SCIATRAN to synthesize OH fluorescence emission spectra. By superimposing atmospheric background signal and do a convolution with instrument line shape function, we could obtain a simulated spectra containing OH concentration information.These results are in good agreement with previous measurements by MAHRSI (Middle Atmosphere High-Resolution Spectrograph Investigation) and SHIMMER (Spatial Heterodyne Imager for Mesospheric Radicals). Then we analyze several factors that may influence the forward model. By modifying these parameters, forward model could be more accurate and closer to the actual radiative transfer process in the future.

In this paper, the standardization of natural gas composition analysis by Laser Raman Spectroscopy was studied, and the feasibility of Standardization was discussed. When using Laser Raman spectroscopy, multiple components can be measured simultaneously without separating every component, so it can save analyzing time, improve real-time effect and realize fast analysis. In addition, the technical status and developing trend for natural gas analytical method by Laser Raman through domestic and international standardized investigation were studied, and data of natural gas analysis experiments by Laser Raman were accumulated. The results show that Laser Raman spectrum will be a powerful tool for real time rapid access to gas quality data in natural gas logging, wells station, gas quality analysis of gas gathering station and natural gas purification process control due to the advantages of fast test (10 seconds), continuous record as well as simple operation. It is suggested to work on standards of natural gas analysis method by Laser-Raman to test CO2, N2, H2S, CH4, C2H6 and C3H8, and the testing ranges are CH4 is from 75% to 99.9%, C2H6 0.005%～20%, C3H8 0.005%～10%, H2S 0.001 5%～10%, N2 0.02%～10% and CO2 from 0.01% to 10%(mole fractions), offering service in the upstream area for natural gas composition monitoring to improve exploration and development.

Laser induced breakdown Spectroscopy (LIBS) was applied for the elemental analysis and exposure of the heavy metals in betel leaves in air. Pulsed Nd∶YAG (1064 nm) in conjunction with a suitable detector (LIBS 2000+, Ocean Optics, Inc) having the optical resolution of 0.06 nm was used to record the emission spectra from 220 to 720 nm. Elements like Al, Ba, Ca, Cr, Cu, P, Fe, K, Mg, Mn, Na, P, S, Sr, and Zn were found to present in the samples. The relative abundances of the observed elements were calculated through standard calibration curve method, integrated intensity ratio method, and weight percentage LIBS approach. LIBS findings were validated by comparing its results with the results obtained using a typical analytical technique of Inductively Coupled plasma-optical emission spectroscopy (ICP-OES). Limit of detection (LOD) of the LIBS system was also estimated for heavy metals. The experience gain through this work implies that LIBS could be highly applicable for testing the quality and purity of food products.

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici, is one of the most destructive diseases causing severe decreases in wheat yield. Early detection of wheat stripe rust before symptom appearance is of great significance for developing effective control strategies and taking timely management measures to ensure high and stable yield of wheat. The objective of this study is to investigate the possibility of thermal infrared imaging technology used for early detection of wheat stripe rust by assessing the temperature changes of normal and infected wheat leaves in a pot experiment under controlled conditions. Four pots of wheat plants were subjected to artificial inoculation with Puccinia striiformis once a day, lasting for 16 days, in an artificial climate chamber. Meanwhile, healthy wheat plants were chosen as the normal control. Thermal infrared images and data on leaf temperature of all the normal and infected wheat leaves were collected 16 days after inoculation (dpi) by using an infrared thermography. The results revealed that with the increasing of days after inoculation, the divergence in the average temperature and maximum temperature difference (MTD) between infected and healthy wheat leaves gradually increases. The infected wheat leaves can be distinguished from healthy ones 6 days after inoculation using infrared thermal imaging, that is, at least 4 days before visible symptoms appearance. At 16 dpi, the average temperature of the inoculated wheat leaves was 2.5 ℃ lower than that of healthy ones, and the MTD of the inoculated leaves was 2.28 ℃ larger than that of healthy ones. Fungal development was also assessed microscopically. It was found through microscopic observation and analysis that stripe rust (Puccinia striiformis) infection caused changes in the integrity of the epidermal cells, the structure of chloroplasts, as well as stomatal conductance and leaf transpiration rate involved in inducing defense. A decrease in leaf surface temperature after the infection was observed as a thermal signature of early infection of disease after successful germination, penetration and reproduction of urediniospores. Thus, thermal infrared imaging has great potential for early detection of wheat stripe rust, with noninvasive monitoring and direct visualization characteristics.

It is very difficult to distinguish samples with similar colors in color measurement. Accuracy and efficiency are very important for industries’ application. A method for color measurement based on hyper- spectral imaging technology was proposed, and a prototype was integrated in this paper. The system is able to measure the spectrum of the colorful samples rapidly. The color analysis or color coordinates were calculated after measurement. This method provided the image and spectrum at the same time. To evaluate the performance of the system, analysis and experiment were also performed. We compared the signal-to-noise ratio of each bands that are subdivided, and used the spectral mapping technique to compare the advantages and disadvantages of the color cameras and the proposed system. The results show that we proposed a more accurate method for color measurement and it can test the quality of products efficiently.

Whether the development of multi angle remote sensing, or the development of polarization and hyperspectral remote sensing all have the same purpose. They use the characteristics and spatial characteristics of electromagnetic waves to accurately identify all the surface of the earth’s object. Any single method and means cannot fully describe and reflect all the features of the ground. Polarization measurement is one of the indispensable technologies in target recognition and recognition technology, and has become a research hotspot in the field of target recognition in the world in recent years. Since the effects of strong and weak reflection intensity on vegetation remote sensing cannot be ignored in quantitative remote sensing inversion, which renders the reflected radiant signal as either saturated or too weak to be detected. Polarization is an important method for the quantitative remote sensing of vegetation. Consequently, it is necessary to develop a method to overcome the vegetation inversion error caused by strong and weak reflection intensities, which is the goal of our present research. If the reflected radiant signal is either too strong or too weak, it will affect the accuracy of remote sensing. Polarized light from vegetation can provide useful information, especially when the reflected radiant signal is saturated so that the sensor cannot obtain enough useful non-polarization information. This study developed a polarization method to overcome the vegetation inversion error caused by strong or weak reflection intensity using a ground-based polarized field imaging spectrometer system. The FISS-P polarization imaging spectrometer system was used to study the effect of reflection intensity on the utility of remote sensing vegetation NDVI and DoLP. The experiment was conducted at the Olympic Science and Technology Park of Chinese Academy of Sciences in Beijing. When targets are sampled, the vegetation with strong reflectivity, low reflectivity and moderate reflectivity is measured respectively. Meanwhile, the DoLP of target vegetation’s different bands (470, 555, 670, 864 nm) are calculated and analyzed. The degree of vegetation density (NDVI) is very low due to signal saturation and shadow effect, resulting in severe inversion error. However, strong reflection has little effect on DoLP. As the ground-based field imaging spectrometer system (FISS-P) provides high-spatial-resolution images with polarization information, we can determine the spectrum-polarization characteristics of single pixels in shaded and strong reflection areas. On the basis of the imaging spectral information, the physical properties of the ground objects are analyzed by using the polarization of light. In this paper, the Stokes component is used to characterize the polarization components of the reflected light, and the degree of polarization of the reflected light is characterized by linear polarization (DoLP). Signal saturation and shadow effects result in very low values for dense vegetation on the Normalized Difference Vegetation Index (NDVI), causing serious inversion error. However, strong reflection has few effects on the degree of linear polarization (DoLP). This study showed that polarization can improve vegetation inversion accuracy by using the appropriate band when the reflected radiant signal is saturated, and the relative error of the average NDVI is 33.8%, while that of DoLP (670 nm) is only 6.3%,the relative errors of DoLP (555, 864 nm) in other bands are much larger. The results of this study show that strong reflection can be ignored when identifying vegetation, however, the shadow (weak reflection) effects could not be ignored. FISS-P images are an effective tool for calculating polarization and non-polarization parameters for sample types with different reflection intensities. In conclusion, the polarization effect can improve the vegetation inversion accuracy when the reflected radiant signal is saturated compared with non-polarization methods. This study analyzed the reduction in error caused by strong and weak reflection intensities using a polarization method. And there are still some problems need to be solved in order to further reveal the relationship between the shadow (weak reflection) effects and DoLP of vegetation.