Electromagnetic metasurface with many special electromagnetic properties can be utilized to manipulate electromagnetic wave propagation and reflection. If the metasurfaces were designed for coding, random, phase discontinuities, perfect absorber and so on, they can manipulate the scattering or the reflection of electromagnetic wave and achieve the reduction of the radar cross section(RCS). This paper mainly presents the recent progress concerning the reduction of RCS using non - directional scattering or the absorption characteristic in microwave and terahertz wave. The analysis results show that coding electromagnetic metasurface can disperse the reflection into a variety of direction by designing the specific coding sequences for different elements. The coding metasurface which are composed of different digital elements, and the reflection phase difference of these digital elements is constant in a wide frequency range, and higher bit coding metasurface can flexible manipulate electromagnetic wave. The random electromagnetic metasurface can achieve broadband phase shifter by adjusting the size parameters of array element, and can diffuse characteristic by scattering into random wave of the reflection peaks for metal target. Phase discontinuities metasurface can achieve anomalous or diffuse of wave because the phase distribution is not uniform at the surface. The absorber metasurfaces which are designed reasonably with the physical dimensions of the devices can reduce reflection by absorbing electromagnetic wave energy. So, the electromagnetic metasurfaces have a large potential application for radar stealth, broadband communications, imaging and so on. Finally, we discussed the future development of RCS reduction by using the electromagnetic metasurface. In order to satisfy the needs of practical application, the research of metasurface will continue development in broadband, flexible, large angle and other aspects.

Grapes vaporize volatiles in specific compositions and concentrations during deterioration processes. Our previous study demonstrated that it is possible to analyze grapes spoilage stages by using the infrared spectra of their volatiles. However, only the spectral characteristics of alcohol, ethyl acetate and carbon dioxide were observed in the experiment because of the low concentration of the volatiles. In this paper, the sensitivity of the spectrometry system was enhanced by increasing the optical-path with multi-reflecting mirrors. We used the new spectrometry system to study the details of the infrared spectra of the volatiles from grapes during spoilage, and observed the spectral characteristics of several kinds of ethanol, esters, aldehyde and ethylene. The concentrations of some components in the volatiles changes with storage time, which can be a biomarker to represent the spoilage stages of grapes. Chemometrics were used to analyze the spectral bands of ethanol and esters, demonstrating there are obvious differences between fresh and decayed grapes. Furthermore, we developed a simplified E-nose system comprised by sensor array, based on the results of spectral analysis. The classification and discrimination of grape spoilage were tested with E-nose. This was a further study of the previous publication and had given a more precise observation of the infrared spectral characteristics of the volatiles from decayed grapes. This study provided a basis for developing real-time monitoring techniques of fruits deterioration.

Photonic crystal fiber can generate particular dispersion properties and highly nonlinear, because of the special guiding mechanism and the adjustable structure parameters, which provides new conditions for the study of nonlinear fiber optics. There are rich nonlinear spectral properties produced by a variety of nonlinear physical effect, under different pump light pulse parameters in photonic crystal fibers with different structure and transmission properties. At present many papers have reported the experimental results of nonlinear optical properties in photonic crystal fiber, but there is little theoretical analysis about the produced mechanism and the change rule of the nonlinear spectrum. In the paper, solving nonlinear Schrodinger equation with split-step Fourier method, transmission process of femtosecond laser pulse in photonic crystal fiber is simulated. The relationship between the output spectrum and incident light pulse parameters (the peak power of pump light P, the wavelength of pump light λ, the shape of light pulse, the width of light pulse TFWHM), the structure parameters of optical fiber (the pitch Λ, the hole-to-pitch ratio d/Λ, the length of fiber), the transmission characteristics (the dispersion properties, the nonlinear coefficient) is obtained. The spectral characteristics produced by nonlinear effects of the Raman soliton, dispersive wave, self-phase modulation are analyzed. The nonlinear optical spectrum of cladding note in photonic crystal fiber is studied in experiments, the broadband spectrum of soliton wave and dispersive wave is obtained. There are blue-shift dispersive wave near the wavelength of 0.5 μm, residual pump light near the wavelength of 0.82 μm, soliton wave near the wavelength of 1.1 μm, red-shift broadband dispersion wave near the wavelength of 2 μm in the spectrum obtained both in theory and experiment. The numerical simulation is confirmed through experimental observation. The physics principle of the nonlinear spectrum in photonic crystal fiber is revealed. These are useful and practical to realize the controllable output of broadband spectrum. These provide guidance for the structure design, fabrication, applied research of high nonlinear photonic crystal fiber.

Ag nanowires (Ag NWs) are synthesized by polyol method under the conditions of different temperature of reaction solution, different addition amount and injection rate of polyvinylpyrrolidone (PVP). The structure and the process of lateral growth of Ag NWs were observed and analyzed by X-ray diffraction (XRD), ultraviolet-visible absorption spectrum (UV-VIS), scanning electron microscopy (SEM) and transmission electron microscope (TEM). It showed that the lateral growth of Ag NWs and longitudinal growth of Ag NWs occurrs at the same time by UV-VIS. And in the later stage of synthesis of Ag NWs, the peak in UV-VIS, which indicated the lateral growth of Ag NWs, red-shifted obviously from 384 nm to 388 nm. This rapid redshift implied that the diameters of Ag NWs increased quickly. In other words, rapid lateral growth of Ag NWs occurred in the later stage of synthesis of Ag NWs. According to the SEM of Ag NWs, in the early stage of the reaction (15~23 min), the diameter of Ag NWs increased by only 20 nm, but in the later stage of reaction (23~30 min), the diameter of Ag NWs increased by nearly 150 nm. The result of SEM observation is consistent with the analysis of UV-VIS. It was also found that the lateral growth of Ag NWs is related not only to the sizes of seeds but also to the thicknesses of the outer Ag layers. Tiny Ag particles with diameters of several nanometers adsorbed onto the side facets of Ag NWs and acted as adsorption points for Ag source. The lateral growth of Ag NWs was caused by the continuous multipoint adsorption of Ag source on the side of Ag NWs. Decreasing the temperature of the reaction solution (from 165 to 155 degree), reducing the injection rate (from 67 to 49 mL·h-1) and the addition amount of PVP in the later stage could inhibit the lateral growth of Ag NWs and increase the aspect ratios of Ag NWs remarkably. The diameters of Ag NWs decreased from 200 nm to 100 nm, but their lengths still maintained above 100 μm.

The isothermal surface equation of tri-band radiation thermometry with linear emissivity model has been deduced, based on tri-band radiation measurement equations. The isothermal surface equation is the point multiplication of measurement signal vector and measurement signal coefficient vector. The solution algorithm for tri-band radiation thermometry defined as dichotomy with coefficients stored in this paper has been developed because of the characteristics of measurement signal vector which is only the function of temperature and the advantage of dichotomy in solving non-linear equation. And the solution algorithm has been achieved by C++ program. The curves of isothermal surface equations at specific measurement signal vectors have been investigated and the results show that the curves are monotone at a greater range of temperature and the tail of curves tend to be positive from minus with the increase of V3. The analyses of error and time complexity have been carried out and the results show that the maximum error is (Tmax-Tmin)/2num+1 when the number for the solution algorithm is Num, and there are about 3Num+1 multiplication and 2Num+1 addition in every dichotomy process without division and logarithm, which can crease the solving rate dramatically.

Quantitative analysis of mixture samples’ components based on terahertz absorption spectra is one of the most important applications of THz technology. As is known to all, when the THz wave irradiates into samples, it will be scattered by the sample particles in the microscale, which is known as scattering. So THz absorption spectra of the experimental obtained samples are basically composed of two parts, samples’ intrinsic absorption of THz wave and the scattering. Especially when particles’grain size of the samples is near or comparable to the THz wavelength, the scattering is so significant that it cannot be ignored. However, the scattering was always not taken into account while only the Lambert-Beer law was used in THz quantitative analysis, in which the absorption of light was described as linearly related with the material’s concentration. As a result, the accuracy was restricted. In this paper, the scattering in THz band was analyzed and absorption spectrum model of mixed sample’s THz was proposed. A series of quantitative analysis experiments proved the validity of this model. Through the comparision with the traditional method, the accuracy of the quantitative analysis was improved and the errors were basically below 3%. This research proved that scattering is important to improve the accuracy of THz quantitative analysis.

Scanning Electron Microscope-Energy Dispersive X-ray spectroscopy (SEM-EDX) was applied to analyze the chemical and structural properties of biochars produced under different temperatures. Results showed that average carbon content (SEM C aver.) and maximum carbon content (SEM C max.) of miscanthus (MS) biochar increased as temperature increasing. There were significant and positive relationships between SEM C max., SEM C aver. and highest treatment temperature (HTT) (r were 0.76 and 0.86). SEM C max., SEM C aver. and dry combustion total carbon content had significant and positive relationships (r were 0.83 and 0.91), SEM C max. which was better than SEM C aver. So the carbon content of MS biochar which had good correlationship with temperature analyzed by SEM-EDX, SEM C max. could be used for composition analysis of biochar, scanning results could analyze structural properties of biochar effectively. This method is rapid, simple and stable. It also could analyze structure and composition of biochar simultaneously. It is a promising method that would be useful to study the structure and composition of biochar and other materials.

This paper presents a photoacoustic noninvasive setup of detecting blood glucose based on the tunable pulsed laser coupled with the confocal ultrasonic transducer and the forward detection model. To validate the reliability of the setup, in the experiments, the different concentrations of glucose aqueous solution are excitated by the Q-switched 532 nm pumped Nd∶YAG pulsed laser to generate the time-resolved photoacoustic signals. And the glucose aqueous solutions are scanned by the tunable pulsed laser in the infrared waveband from 1 300 to 2 300 nm with the interval of 10nm and the photoacoustic peak-to-peak values are gotten. The difference spectral method is used to get the characteristic wavelengths of glucose, and the principle component regression algorithm is used to determine three optimal wavelengths and establish the correction mathematical model between the photoacoustic peak-to-peak values and the concentrations. The experimental results demonstrate that the mechanism of the photoacoustic signal is agreement with the cylindrical model, and the predicted results of the correction and prediction samples based on the established correction model demonstrate that the root-mean-square error of correction and prediction are all less than 10 mg·dl-1, the correlation coefficient reaches 0.993 6.

Montmorillonite (MMT) is a natural mineral that has great potential as reinforcing filler in wood adhesives. In order to study the reinforcing mechanism more clearly, organic MMT-reinforced urea-formaldehyde adhesive (UF-OMMT) was prepared to analyze its chemical properties and crystal structure with Fourier Transform Infrared Spectroscopy (FTIR) and X-Ray Diffraction (XRD). The nanomechanical properties of UF, UF-MMT and PF-OMMT adhesives in the interphase of wood-based composite were analyzed by nanoindentation (NI) and the macro-bonding strength of composite were also tested. The results of FTIR and XRD indicated that in the spectra of MMT modified by cetyltrimethyl ammonium bromide (CTAB), the new peaks appeared at 2 929 and 2 853 cm-1corresponding to C—H stretching vibrations of the organic intercalation agent (CTAB). The (001) diffraction peak of MMT was shifted to a lower angle and the lamellar repeat distance increases from 1.51 nm to 2.71 nm after organic modification. The ion exchange of the cations in montmorillonite with organic ammonium ions and the separating and disorder crystalline improved the compatibility of the modified clay with the polymers and the dispersion of the layers into the matrix. The good physical filling of MMT particles and the elastomer formed during the reaction could transfer and distribute loads between components more homogenously, therebycontributing to the improved mechanical properties of adhesives. As compared to the untreated UF, the reduced elastic modulus and hardness of UF-OMMT in the interphase increased by about 66.9% and 24.2%, respectively. At the macroscale, the bonding strength of plywood bonded with UF-OMMT increased by about 97% as compared to that of unmodified UF resin. The positive effects of montmorillonite on water and heat resistance can be attributed to the better barrier properties of the interphase.

Near-infrared reflectance spectroscopy (NIRS) is a simple, convenient and safe technology which is widely used in many industries. NIRS was employed to the rapid classification of coal in this study. The new method can be a replacement of the chemical analysis which is laborious and time consuming. Confidence machine was firstly applied to NIRS in this study which was used to evaluate the risk of the analysis. The near infrared reflectance spectrum of 199 coal samples including four types of coal (50 fat coal samples, 50 coking coal samples, 49 lean coal samples and 50 meager lean coal samples) from different mines in China were collected and classifiers based on the near infrared spectra of coal samples which were established by using machine learning methods to realize the rapid classification of coal samples. Confidence machine was introduced into the analysis technology based on NIRS in this paper. Confidence machine based on support vector machine (CM-SVM) was built and applied to the classification of coal samples via NIRS. Confidence machine is a probabilistic algorithm and instead of using hyper plane (SVM) to carry out the classification, using probability (CM-SVM) turned to be more effective which had 95.45% of the samples correctly grouped. Besides that, CM-SVM also estimated the confidence and credibility for each predicted sample. By setting different confidence levels, CM-SVM can perform region prediction whose error rate was predefined by the different confidence levels, which was very important for the control of product quality when NIRS was applied to the analysis of productions. Confidence machine is designed as an on-line learning method; new samples can be added to the training set one by one to improve the efficiency of the model and is very appropriate for industry on-line analysis. On-line CM-SVM models showed that the confidence of prediction would be raised as the samples increased, which was valuable for industry on-line analysis.

According to the research achievements of phase change and humidity storage composite materials preparation in early stage, SiO2-based phase change and humidity storage composite materials were made by sol-gel method with SiO2 as the carrier and decanoic acid-palmitic acid as a phase change material in this paper. Synthetic materials in every stage of preparation process of decanoic acid-palmitic acid/SiO2 phase change and humidity storage composite materials were measured by Fourier transform infrared spectrum, such as phase change material preparation stage, SiO2 carrier material preparation stage and decanoic acid-palmitic acid/SiO2 phase change and humidity storage composite materials preparation stage. In the process of decanoic acid-palmitic acid/SiO2 phase change and humidity storage composite materials preparation, SiO2 network structure forming mechanism, decanoic acid-palmitic acid embed mode, chimeric mechanism of SiO2 and decanoic acid-palmitic acid were researched, respectively, in order to explain the mechanism of how to prepare decanoic acid-palmitic acid/SiO2 phase change and humidity storage composite materials by sol-gel method. Meanwhile, material composition and micro topography of decanoic acid-palmitic acid/SiO2 phase change and humidity storage composite materials were tested by X-ray diffracmeter and scanning electron microscope, so as to provide evidence about preparation mechanism of decanoic acid-palmitic acid/SiO2 phase change and humidity storage composite materials. The results showed that decanoic acid-palmitic acid is packed in a large number of closed pores or cages which were formed through breaking and restructuring of Si—O—Si groups; then, decanoic acid-palmitic acid/SiO2 phase change and humidity storage composite materials can be prepared based on those mentioned above. Decanoic acid-palmitic acid and SiO2 are only physical chimeric to each other, without any chemical reaction in the preparation process of decanoic acid-palmitic acid/SiO2 phase change and humidity storage composite materials. A large number of closed pores or cages are formed by SiO2 in acid-palmitic acid/SiO2 phase change and humidity storage composite materials, of which one part is used for coating decanoic acid-palmitic acid with phase change thermal control performance, and the other part is used for network space structure with humidity storage humidity control performance, in order to achieve the purpose of adjusting indoor temperature and humidity at the same time.

Potassium (K) deficiency affects cotton growth. The substitution effects of sodium (Na) and potassium research have been the focus of attention at home and abroad. The aim of this paper was to study the substitution effects of Na and K on material composition in leaf of two kinds of K-efficiency cotton genotypes (HG103 and LG122) using Fourier to transform infrared (FTIR) spectroscopy. The results showed that: (1) the increment of the relative absorbance of HG103 at peaks 2 960, 2 855 and 2 926 cm-1 were the same with LG122 with addition of Na in deficient K, while at peaks 1 078 and 1 103 cm-1, the increment of HG103 was higher than LG122, indicating that in deficient K, Na could promote the synthesis of carbohydrate, protein and esters, wherein the promoting effect on carbohydrate of HG103 was greater than LG122, while for protein and esters, there has no difference. However, the decrement of the relative absorbance at these five peaks of HG103 was higher than LG122 with addition of Na in adequate K, suggesting that in adequate K, the inhibitory effect of Na on carbohydrate, protein and esters of HG103 was less LG122. (2) the peaks at 1 734 and 1 437 cm-1 disappeared due to K dificiency, when added Na, these peaks did not appear, implying that the structure of amideⅠband and cellulose was broken when lack of K when added Na has no changes.

Non-destructive detection for soluble solids content (SSC) is important to improve watermelon’s internal quality, which attracts more and more attention from consumers. In order to realize the precise detection for SSC of mini watermelon’s whole surface by using Near-infrared (NIR) spectroscopy and reduce the influence of detective position variability on the accuracy of NIR prediction model for SSC, the diffused transmission spectra and soluble solids content were collected from three different detective positions of ‘jingxiu’ watermelon, including the equator, calyx and stem. The prediction models of single detective position and mixed three detective positions for SSC were established with Partial least square (PLS). Successive projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS) were adopted to select effective variables of NIR spectroscopy for SSC of watermelon as well. The results showed that the prediction model of mixed three detective positions was better than the model of single detective position. Meanwhile, 42 characteristic variables of NIR spectroscopy selected with CARS were used to establish PLS prediction model for SSC. The prediction model was simplified significantly and the prediction accuracy for SSC was improved greatly. The correlation coefficient of prediction (RP) and root mean square error of prediction (RMSEP) by CARS-PLS were 0.892, 0.684 °Brix for the equator, 0.905, 0.621 °Brix for the calyx, 0.899, 0.721 °Brix for the stem, respectively. However, the prediction result of SPA-PLS established by 19 characteristic wavelength variables of NIR spectroscopy was bad for the equator, calyx and stem detective positions. The correlation coefficient of prediction (RP) is less than 0.752 and root mean square error of prediction (RMSEP) is relatively high. It was proposed that the PLS prediction model established by mixed three different detective positions with effective characteristic wavelength variables selected by CARS can improve the prediction accuracy for SSC. And the CARS-PLS prediction model can achieve fast and precise detection for SSC of mini watermelon’s whole surface. The influence of detective position variability on the accuracy of NIR prediction model could be reduced simultaneously. Thispaper could provide theoretical basis for calibrating NIR prediction model for SSC of mini watermelon. It also could provide reference for developing the portable and non-destructive detection equipment for soluble solids content of mini watermelon’s whole surface.

The sodium chloride (NaCl) salt has been reported to be associated with glucose metabolism. However, the effect of it on non-invasive detection of blood glucose using near-infrared spectroscopy is still an open question. The aim of this study was to investigate this affection through transform background correction analysis two-dimensional (2D) correlation synchronous spectrum and the partial least-squares (PLS) regression. First, the transmittances of glucose aqueous solutions with different NaCl content are collected and the pure water and NaCl aqueous solution are measured as the background. Results show that, the dissolving of NaCl in water changes the amplitude and position of the absorption peak of water. There are two negative peaks in 1 400 and 1 500~1 700 nm corrected spectra of NaCl aqueous obviously and the amplitude of peaks associated with NaCl concentration. That’s because NaCl affect the molecular binding and vibration of water. Then the glucose aqueous solutions without NaCl and with NaCl are corrected by the spectra of pure water and NaCl aqueous solution, respectively. So we get the conclusion that NaCl also affect the combination of glucose and water molecules. And the two-dimensional correlation spectroscopy analysis is performed under the perturbation of glucose concentration. The slice spectra of synchronous correlation spectra show that, the adding of NaCl weakens the spectral variation due to glucose concentration change in the wavelength of 1 400 and 1 520~1 700 nm. Finally, the partial least square (PLS) regression models were built to quantitatively conduct the influence of NaCl on glucose prediction accuracy. Comparison results showed that, NaCl molecule in aqueous solution will deteriorate the model accuracy, where root mean square error of prediction increases with the NaCl content; the mean difference of predicted glucose concentration between models based on glucose aqueous solutions with NaCl and without NaCl, is linear with NaCl concentration in samples.

Soil organic matter (SOM) is an essential indicator for the fertility assessment of farmland. and An efficient and stable prediction model is in need to rapidly estimate SOM in larger scale. Spectroscopic technology has been proved as a powerful tool to access SOM in the last decade. The aims of this paper were: to compare different selection method of calibration set for modeling SOM in paddy soil by using visible-near infrared (VNIR), mid-infrared (MIR) and VNIR-MIR spectra and to assess the prediction ability of the results. All spectra were transformed from reflectance to absorbance, and preprocessed by Savitzky-Golay smoothing algorithm. The prediction models of SOM were built by using partial least squares regression (PLSR) coupled with three selection methods of calibration set in VNIR, MIR and VNIR-MIR regions. The selection method of calibration Rank-KS performed better than Rank method and KS method, meanwhile the models in MIR region showed stronger prediction ability than VNIR and VNIR-MIR regions. The best prediction model was obtained with the MIR model combined with Rank-KS, and the root mean square error of prediction (RMSEP) and ratio of performance to deviation (RPD) were 3.25 g·kg-1 and 4.24. According to variable in the projection (VIP) score, important bands for SOM prediction in paddy soil were identified in VNIR and MIR region. Our results show that MIR spectroscopy could make quantitative prediction of SOM in paddy soil and Rank-KS is an effective method for selection of calibration sets, so as to provide some scientific basis for fertility assessment of farmland and rational fertilization.

Botanical origins of propolis are significant factors affecting biological and pharmacological activities because of different components in propolis. Until now, the determination of propolis botanical origins is mainly based on different varieties and the content of the compositions with great limitations. Therefore, it is important to discriminate different botanical origins of propolis quickly and accurately. In this study, Near-infrared (NIR) spectra of propolis varieties based on principal component analysis mahalanobis distance (PCA-mahalanobis distance) model and canonical discriminant analysis model were built for the classification of three botanical origins (poplar propolis, brich propolis and rubber propolis). The models were built based on the optimal pretreatment method and bands of first derivative + Savitzky-Golay (7) filter and 4500~12 000-1, which were selected in advance. After the principal component analysis, the correct classification rates of calibration sets and validation sets in analysis mahalanobis distance models were 93.62% and 82.61%, respectively. The discrimination rate and the cross-validation rate of canonical discrimination models were 91.4% and 88.6%, respectively. Therefore, NIR spectroscopy with chemometric methods is not only feasible but also practical for rapid and accurate identification of varieties of propolis.

Lettuce storage time is an important factor affecting the lettuce freshness. To realize the non-destructive, rapid and effective discrimination of lettuce storage time, generalized fuzzy K-harmonic means (GFKHM) clustering was proposed by introducing the pth power of Euclidean distance into fuzzy K-harmonic means (FKHM) clustering to replace the square of Euclidean distance in FKHM, and furthermore GFKHM was applied in the discrimination of lettuce storage time. Sixty fresh lettuce samples were prepared as the research object, and the near infrared reflectance (NIR) spectra of lettuces were collected by Antaris Ⅱ near infrared spectrometer with a spectral range of 10 000～4 000 cm-1 for three 12-hour detections. Firstly, the 1 557-dimensional NIR spectra were reduced by principal component analysis (PCA) to decrease redundant information. After the first 20 principal components were selected, PCA translated the 1 557-dimensional NIR spectra into the 20-dimensional data. Secondly, linear discriminant analysis (LDA) was used to extract the discriminant information from the 20-dimensional data to improve the clustering accuracy. With the first two discriminant vectors, LDA translated the 20-dimensional data into the two-dimensional data. Finally, the cluster centers from fuzzy C-means clustering (FCM) were set as the initial cluster centers for FKHM and GFKHM and fuzzy membership values of FKHM and GFKHM were calculated to identify lettuce storage time. The experimental results showed that the discrimination accuracy of GFKHM has achieved 92.5% which was higher than that of FKHM. The cluster centers of GFKHM were much closer to the true cluster centers in comparison with FKHM. Furthermore, the convergence of the GFKHM was significantly faster than FKHM. Near infrared spectroscopy coupled with GFKHM, PCA and LDA could cluster NIR spectra of lettuce quickly and correctly, and this provided a fast and nondestructive method for identifying lettuce storage time.

With the aim of establishing a rapid method to discriminate Boletus tomentipes samples from different regions, FTIR spectroscopy with the aid of principal component analysis and clustering analysis were used in the present study. The information of infrared spectra of B. tomentipes samples originated from 15 regions has been collected. The original infrared spectra was pretreated by multiplicative signal correction (MSC) in combination with second derivative and Norris smooth. The spectral data were analyzed by principal component analysis and cluster analysis after the optimal pretreatment of MSC+SD+ND (15, 5), and the reasons for the differences of B. tomentipes samples from different regions could be explained through the principal component loading plot. The results showed that, the RSDs of repeatability, accuracy and stability of the method were 0.17%, 0.08% and 0.27%, respectively, which indicated the method was stable and reliable. The cumulative contribution of first three principal components of PCA was 87.24% which could reflect the most information of the samples. Principal component scores scatter plot displaying the samples from same origin could clustered together and samples from different areas distributed in a relatively independent space. Which can distinguish samples collected from different origins, effectively. The loading plot of principal component showed that with the principal component contribution rate decreasing, the captured sample information of principal component was also reducing. In the wave number of 3 571, 2 958, 1 625, 1 456, 1 405, 1 340, 1 191, 1 143, 1 084, 935, 840, 727 cm-1, the first principal component captured a large amount of sample information which attributed to carbohydrates, proteins, amino acids, fat, fiber and other chemical substances. Which showed that the different contents of these chemical substances may be the basis of discrimination of B. tomentipes samples from different origins. Cluster analysis based on ward method and Euclidean distance has shown the classification and correlation among samples. Samples originated from 15 regions could be clustered correctly in accordance with the basic origins and the correct rate was 93.33%. Which can be used to identify and analyze B. tomentipes collected from different sites. Fourier transform infrared spectroscopy combined with principal component analysis and cluster analysis can be effectively used to discriminate origins of B. tomentipes mushrooms and the reasons for the differences of B. tomentipes samples from different regions could be explained. This method could provide a reliable basis for discrimination and application of wild edible mushrooms.

In the study, rubber accelerator tetraisobutylthiuram monosulfide (TiBTM) was synthesized by two-step method with hydrogen peroxide as oxidant firstly. TiBTM was detected and characterized by FTIR, XRD, TG-DSC. Its micro-structure and intrinsic regularity were revealed. Chemical bond types into TiBTM molecule were revealed by FTIR. TiBTM phase composition and structure were given by crystallographic data from XRD detecting such as cell parameters, crystal face index. The phase composition and qualitative identification of TiBTM structure were completed. Two kinds of information were detected by TG-DSC as quality change and thermal effect. TiBTM phase transition and decomposition temperature were 75.1 and 287.0 ℃ respectively. Uhe decomposition temperature of TiBTM was very high, samples possessing with high purity, without other impurities. It could provided reference with research on rubber vulcanizing and multiple functional properties by TiBTM on rubber vulcanizing machine. This study can provide the basis experimental data on the enterprises to designate the working standard tracing detection of TiBTM industrialized production. The best technological conditions and parameters could be provided for the enterprises to adopt cleaner production process of TiBTM. Performance index of TiBTM was judged. The project of TiBTM industry standard can be declared by the enterprises, written a draft standard.

As the skeleton substances of lignocellulosic biomass cell wall and the precursor of biofuels production, the research on cellulose structure, an important natural biomarcromolecules, attracts great attention. Considering its in situ features and higher resolution, Raman spectroscopy has been used to investigate the structure of cellulose molecular chain and cellulose aggregation structure at multi-scale. In this paper, the configurations and corresponding parameters of two types of Raman spectroscopy (Dispersive Raman and FT-Raman) were compared. Subsequently, the utilization of Raman spectroscopy in cellulose micro-distribution, cellulose enzyme hydrolysis, cellulose chain orientation and deformation, cellulose crystallinity and polymorphic transformation was discussed in detail. Given the existing deficiencies of the Raman spectroscopy when used to investigate the natural cellulose, some suggestions were proposed in order to promote the application of Raman spectroscopy to the research of natural macromolecular.

Surface-enhanced Raman scattering (SERS) is spectroscopic technique with ultra-sensitivity and high selectivity and has attracted great attention because of the potential applications in various fields. P-aminothiophenol (PATP) is often used as SERS probe molecule because it is easy to adsorb on SERS substrates and produce high-quality SERS signals. TiO2 is extensively used as photocatalyst although its photocatalytic efficiency is still needed to be improved. Noble metal-modified TiO2 is one of current important techniques for maximizing the efficiency of photocatalytic efficiency. In this article, a kind of bifunctional SERS substrates, Ag/TiO2 nanotubes, with photocatalysis property were prepared, the TiO2 NTs were prepared by anodic oxidation and noble metal Ag nanoparticles were deposited on the surface of TiO2 NTs by photoreduction method. The photocatalysis of PATP on Ag/TiO2 NTs and on Ag mirror substrates were studied. The SERS signals of PATP were decreased with the ultraviolet irradiation time, however, on Ag mirror substrates, SERS intensity of PATP was slightly changed, which indicated the photocatalysis reaction of PATP on Ag/TiO2 NTs substrates. The kinetics analysis results indicate that the kinetics of the photocatalysis follows the first order of the dynamical reaction.

Grating coupled semiconductor lasers (GCSLs) has a wide application prospect in many fields, such as optical free space communication, intersatellite communication, ranging for laser radar, atmospheric environmental testing and medical imaging. In order to verify the reliability of GCSLs, the chips in different preparation stages and products of GCSLs are tested based on Raman spectroscopy. It concluded that for unprocessed semiconductor laser chip, the longitudinal optical (LO) photons mode vibration of GaAs chip is strong but the transverse (TO) optical photons mode vibration of GaAs chip is weak. when the is unprocessed. When the surface of GaAs chip is covered by a layer of SiO2 membrane, the LO mode will movetowards long wavelength direction, but its intensity wouldn’t change. When a 100 m mesa is etched on GaAs chip which is covered by SiO2 membrane, LO mode vibration of GaAs chip weakens and TO mode vibration of GaAs chip enhances, and the peak width of LO mode and TO mode increase. After gratings are etched on the 100 m mesa, LO mode vibration of GaAs chip continues to weaken, but TO mode vibration of GaAs chip becomes stronger. It shows that lattice defects exist in the fabrication process of GCSLs. By contrast testson the semiconductor lasers without gratings, it shows that defect peaks present in the Raman spectrum of GCSLs regardless of the defects on light emitting surface. This further proved that the strains or defects were introduced into the fabrication process of grating structure, which affects its reliability, resulting in a decrease of the reliability of GCSLs.

In this paper, a novel paper-based Surface enhanced Raman spectroscopy (SERS) substrate with high sensitivity, good uniformity and popular price is developed via liquid/liquid interface self-assembly technique. Three pigment, rhodamine B, sunset yellow and chrysoidine were detected through paper-based SERS substrates using a portable Raman spectrometer. The structures of the three pigments were investigated and vibrational modes of characteristic peaks of three pigments were assigned. SERS spectra of rhodamine B, sunset yellow and chrysoidine in aqueous solution with different concentrations were detected respectively. Rhodamine B, sunset yellow and chrysoidine in drinks were also detected in drinks without any pretreatment. Within a certain range of concentrations, it meets certain function. For rhodamine B and sunset yellow, the relationship between concentration and Raman peak intensity is on an index curve, while for chrysoidine, the relationship is linear. In addition, high recoveries are achieved for detecting rhodamine B, sunset yellow and chrysoidine in drinks, which indicated our method is suited for semi-quantitative analysis for the concentration of rhodamine B, sunset yellow and chrysoidine in drinks. Surface-enhanced Raman spectroscopy provides an easy approach to fast and efficient detection for multiple pigments in drinks and can be used for quality control and market monitoring of drinks.

A fast and efficient way to synthesize a large number of silver nanowires was developed in this paper, in which the reaction conditions were optimized. Under the protection of Cu(NO3)2 silver nitrate was reduced by polyol with polyvinyl pyrrolidone (PVP) in existence. The silver nanowires with uniform structure and good dispersion were obtained. Surface enhancement activity of the silver nanowires was detected by using RhB as a probe molecule, its surface enhancement factor can reach 6.4×105. The results showed that the nanowires significantly enhance the Raman spectroscopy of RhB. The normal Raman spectroscopy (NRS), Raman spectroscopy of D-carnitine solution and Surface enhanced Raman Spectroscopy of D-carnitine by means of the new base were obtained. There are obvious Raman peaks at 3 100～2 800 and 1 700～200 cm-1, and the peak of 1 700～200 cm-1 in the surface enhanced Raman spectra of the D-carnitine can be obviously enhanced. The analysis showed that the angle between the molecular and silver nanoparticles were 180°. The vibrational peaks were assigned comprehensively. Compared with the NRS and SERS of D-carnitine, the detailed structural information of D-carnitine was obtained. In this paper, the surface enhanced Raman spectra of the D-carnitine absorbed on the synthesized silver nanoparticles were obtained, and the minimum detection concentration was 10-6 mol·L-1. The new method can be a rapid and characteristic way to detect D-carnitine, and it will also provide an important guidance for the studies on pharmacology of D-carnitine.

This experiment adopts Surface Enhanced Raman Spectroscopy (SERS) to quickly detect auramine Ⅱ, basic orange Ⅱ and metanil yellow in bean products. It uses High Performance Liquid Chromatography (HPLC)-tandem mass spectrometry to verify. The best extraction solvent is methanol-water (Seven plus three) solution. Before classification, extracting the bean products withAccelerated Solvent Extaction (ASE) and purifying it with Gel Permeation Chromatography(GPC), which improves the extraction efficiency, improves the detection sensitivity, reduces the dosage of extraction solvent and effective in the matrix of macromolecular distractors.ASE and GPC conditions are optimized. This study of three types of pigment surface enhanced Raman spectra characteristic peak of the ownership certification. The characteristic peak of auramine Ⅱ, basic orange Ⅱ and metanil yellow is respectively 652, 995 and 983 cm-1; he method detection limit is 3.0, 1.0 and 4.0 mg·kg-1. Three quantitative characteristic peak of pigment had a good linear relationship with pigment concentration, Recovery of this experiment was 83.48%～92.59% range, relative standard deviation less than 7.2%. The method is characterized by simple pretreatment, short analysis period and high sensitivity, etc. The method provides a reliable reference for food pigment detection.

According to actual market demand for nondestructive detection of vegetables quality and safety, combined with the heterogeneity of quality and safety parameters such as pesticide residues on leaf vegetables surface and to realize the automatic point scanning for the whole leaf vegetables samples, a suction device based on laboratory (self-designed) Raman spectroscopy hardware and a GUI application software based on the LabVIEW development platform were developed. This system can test the Raman spectroscopy of the whole spinach including the automatic collection, display and storage of the Raman signal of all the scanned points by set up different scan step. A new method to remove the Raman spectrum background was proposed based on data replacement with linear equation at the range of threshold spectrum on both sides of the effective peaks according to the characteristics of spinach original spectra. Its principle is to determine the starting position of linear fitting by judging whether there is trough on both sides of the crest, and then to generate and replace the original spectra data in peak position through the linear fitting equation. Spinach samples were used for the experiment showed that the chlorophyll content and distribution of chlorpyrifos pesticide residue on each scanning point can be obtained after scanning. Therefore, the point scanning Raman system could improve detection accuracy of the quality and safety parameters for the non-uniform samples effectively.

Ethanol concentration quantitative analysis of ethanol-water solution can be realized by measuring the ratio of Raman characteristic peak heights. The content of ethanol can be determined by linear relation between relative intensity ratio and ethanol concentration. However, this analytical method only applies to the ethanol solution at low concentration. Concerning this issue, relative intensity of characteristic peak of ethanol (asymmetric stretching vibration of CH2 2 924.0 cm-1) and peak background of water (3 350 cm-1) at different ethanol concentration is experimentally measured by using a self-developed laser Raman ethanol content detection system. According to the relationship between relative ratio of characteristic peak heights and ethanol concentration, the nonlinear regression analysis methods are proposed to apply in the measurement of ethanol concentration in a wide range. Adjacent region average method is utilized to remove mutational random noise in Raman spectra of ethanol solution. Combined with multi-point interpolation processing, the baseline of Raman spectra can be calibrated. The influences of mutational random noise and the strong fluorescence background can be effectively eliminated with baseline correction and normalization methods. Polynomial and exponential mathematical models are adopted for nonlinear regression analyses by the relation between ratio of characteristic peak heights and concentration of ethanol solution. The analysis results show that the correlation coefficient of linear fitting and nonlinear fitting is about 0.991 and higher than 0.997 respectively. The linear analytical method can be effectively applied when ethanol concentration range is 15%～60%. The nonlinear analytical method has higher measurement accuracy in a wider ethanol concentration range of 3%～97%. Nonlinear mathematical model will provide theoretical basis for analysis of ethanol concentration, which can be applied in laser Raman ethanol content detection system to calculate the relatively accurate ethanol concentration of ethanol-water solution. Rapid, real-time and accurate quantitative analysis of wide concentration range ethanol solution, which has mutational random noise and strong fluorescence background interference, can be achieved by these analytical methods.

Extensive use of pesticides has a significant impact on the environment. Carbaryl, whose residues stay in the surface water, is one of the most widely used broad spectrum insecticides in agriculture. It is important to understand carbaryl spectral characteristics and detection methods. The characteristic of excitation-emission three-dimensional spectra of carbaryl is studied. By changing the concentration of methanol in methanol-water binary solvent, the impact of methanol-water mixture on three-dimensional fluorescence spectra of carbaryl is discussed. The results show that the characteristic excitation-emission spectra of carbaryl is single peak, the range of the excitation wavelength and emission wavelength are: 244~304 and 300~350 nm respectively, the maximum excitation/emission peak located at 280 and 335 nm. With increasing the content of methanol in methanol-water binary solvent mixture, there is no obviously spectra shift of three dimensional fluorescence spectra of carbaryl. However, the intensity of fluorescence is nonlinear dependent on the content of methanol, mainly due to the specific properties of binary mixed solvent.

The occurrence of greenhouse vegetable diseases and its epidemic seriously affect the production and management of facility agriculture, which greatly reduce the economic benefits of facility agriculture. In order to achieve nondestructive and accurate prediction of greenhouse vegetable diseases, this paper taking cucumber downy mildew disease as the research object, constructed spectrum characteristic index by using chlorophyll fluorescence induced by laser and established the prediction model of greenhouse vegetable diseases. In this paper, the experiment used comparative analysis method. The healthy leaves of the crops were inoculated with the pathogen spores, the spectrum curves of four groups of test samples: healthy, 2 d inoculated, 6 d inoculated and the ones with obvious symptoms were collected; then qualitative analysis was given to the variation regulation of the fluorescence intensity with the leaf samples infected with the pathogen spores. The chlorophyll fluorescence spectrum index k1=F685/F512 and k2=F734/F512 were created by using the peak and valley values of different bands. According to the range of values, set k1=20 and k2=10 as the characteristic value to judge the sample with obvious symptoms or with no obvious symptoms, and the accuracy rate of the judgment was 96% and 94% respectively. Based on spectrum index created and the classification results of sample health status, we selected the spectrum index F685/F512, F685－F734, F715/F612 to determine the health status of the sample and selected spectrum index F685/F512, F734/F512, F685－F734, F715/F612 as the inputs of quantitative analysis model. Regarding classification accuracy of prediction set as the evaluation criteria, we compared three data modeling methods: discriminant analysis, BP neural network and support vector machine. The results showed that the forecasting ability can reach 91.38% when the support vector machine was used as the modeling method for predicting the downy mildew disease. Use the method with chlorophyll fluorescence induced by laser to construct spectrum index to study the prediction of plant diseases, which has a good classification and identification effect.

Since ultraviolet radiation is one of the major environmental factors that cause photoageing/photodamage, human hair, including both dyed and undyed hair, are subject to color change following extended exposure to sunlight. In the work described in this paper, six samples of human hair from Chinese volunteers that included untreated, bleached and dyed were subjected to accelerated ageing by exposure to UVA (320～400 nm) radiation. Changes to their chemical compositions during photoageing were non-destructively characterized by reflectance, 3D-fluorescence and attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopies. These techniques, together with a quantitative analysis of the photosensitized generation of hydrogen peroxide, were used to assess the effects of different hair color and bleaching/dyeing treatments on the light stability of hair fibers. The results suggest that UVA irradiation can induce the production of hydrogen peroxide via a type Ⅱ mechanism (electron transfer interaction between photosensitive protein groups in their excited states) and subsequent reaction with oxygen, resulting in photo-oxidative degradation of surface protein and pigments of the hair fiber. Hair fibers of natural or artificial color respond differently in terms of color change during photoageing. Natural white and gray hair fibers exhibited the usual photoyellowing; and chemically black-dyed and bleached hairs showed photofading and additional photobleaching, respectively. Irradiation of hair in the wet state was found to accelerate photodegradation. Chemical bleaching and oxidative dyeing processes were shown to promote the photoinduced production of hydrogen peroxide, which contribute to a higher level of oxidative stress and thereby affects the photostability of human hair. Pigment molecules in hair, including both the natural pigmentation of melanin and that produced by artificial dyes, are suggested to play a dual role, both in the production and in the scavenging of oxygen free radicals. The work is designed to contribute to the establishment of spectroscopic methods for assessing the extent of hair photodamage as well as providing a sound experimental data basis for the research and development of improved hair dyes and after-dye products for the Chinese cosmetic market.

The Panax notoginseng is an important Chinese herbal medicine (CHM) and the quality is affected by growing environment. UV spectra approach was used to study the relationships between UV spectra of P. notoginseng and locations, rapidly. The UV spectra of fifty P. notoginseng samples which collected from ten regions were obtained and processed by using mean value, smoothing and derivative. The numbers of common peaks of chloroform, ethanol and water extractions were compared, respectively and the best extraction solvent was confirmed. The differences and relationships of P. notoginseng samples from different locations were investigated by comparing the characteristics of UV spectra combined with partial least square discriminant analysis (PLS-DA). The results showed that the extract ratio was the best in chloroform and the RSD% of precision, repeatability and stability in 30 h were 0.00～0.42, 0.00～0.54 and 0.00～0.60, respectively. The spectra of samples collected from different areas were similar except the absorbance. It could display the fingerprint characteristics. The common peaks of UV spectra were 194, 200, 204, 210 and 218 nm and the peaks absorption value ranged from 0.00 to 4.00. It showed that the main constituent had low correlation with collection regions while the content may be affected by the collection areas. The PLS-DA score plots could show the relationships among the P. notoginseng from different locations. In conclusion, this qualitative method could evaluate P. notoginseng samples from different locations rapidly and exactly. Moreover, it could provide the reference for source discrimination of CHM.

To obtain the weaker second harmonic signal of low concentration, reduce the minimum measurable limit and improve the sensitivity and accuracy of absorption measurement, a serious of data processing methods are proposed based on tunable diode laser wavelength modulation spectroscopy. The experiment on lower NH3 concentration at 2.25 μm was carried out in a 10.13 m absorption cell with different concentration. The peak height of the second harmonic signal is maximum at m=2.2, which optimizes the signal-to-noise ratio. In order to guarantee the optimal signal-to-noise ratio, the experiment was carried out by loading the optimal high frequency modulation signal. WMS-2f was performed at a repetitive scan rate of 200 Hz and a current-modulation rate of 15 kHz, wavelength modulation spectroscopy with the optimal signal-to-noise ratio was adopted for its better noise immunity to measure different lower NH3 concentration in the Herriott cell. This survey is focused on the ν２＋ν３ bands of absorption spectra near 2.25 μm in near-infrared region at ambient temperature and pressure, the line strengths of 2.25 μm are much larger than the absorption lines in the telecommunication bands, using stronger NH3 absorption lines can offer the potential of lower detection limits. During the data processing, the background signal of the original harmonic should be deducted at first, the second harmonic signal of 0.6×10-6 was obtained in a 10 m long-path Herriott cell after data processing, these signal processing mainly consist of cross-correlation analysis, multiple averages and wavelet transform analysis, the cross-correlation analysis was used to control the shift of center wavelength, the multiple averages and wavelet transform analysis were used to reduce influences of the environment noise, after that we get the revised second harmonic signal and improve the accuracy of the measurement results. The experimental results show that these data processing methods can obviously improve the signal quality and reduce the minimum measurable limit about 100 times lower than before. The experiment doesn’t need to add any laboratory equipment and can well restrain the influence of the environmental noise and other disturbance, so these signal process combined with wavelength modulation technique will be more useful for on-line gas detection technology.

In the study, zinc O,O,O’,O’-tetrabutyl bis(phosphorodithioate) (ZBPD) was synthesized with two-step method firstly. ZBPD was detected and characterized with UV-vis, FT-IR andTG-DSC. Its micro-structure and intrinsic regularity were revealed. Two absorption peaks were detected with UV-Vis at 212.0 and 227.0 nm respectively caused by n→σ*, π→π* electron transition. The intensity of peaks was changed with the regularity with different ZBPD concentration. It could provide the basic data with the enterprise of ZBPD product quality inspection. Chemical bond types into ZBPD molecule were revealed by FT-IR. Two kinds of information were detected by TG-DSC as quality change and thermal effect. The DSC curve of ZBPD was very complex. There were a wide absorption peak of 84.3 ℃, four exothermic peaks of 245.0, 344.3, 476.1, 344.3 ℃, due to the molecular structure of ZBPD and small amounts of impurities. The decomposition temperature of ZBPD was very high. It could provided reference with research on rubber vulcanizing properties by ZBPD on rubber vulcanizing machine. This study could provide the basis experimental data on the enterprises to designate the working standard tracing detection of ZBPD industrialized production. Performance index of ZBPD was judged. The project of ZBPD industry standard could be declared by the enterprises, written a draft standard.

In this paper, the critical micelle concentration (cmc) values of sodium dodecyl benzene sulfonate (SDBS) in aqueous solution at different concentrations of hydroxypropyl-β-cyclodextrin (HP-β-CD) are determined by synchronous fluorescence spectrometry. The results indicated that, when the scanning wavelength difference of the synchronous fluorescence spectrum is 25 nm, both the critical micelle concentration value and the fluorescence intensity of SDBS will greatly increase in the presence of HP-β-CD. The standard molar Gibbs free energy for SDBS from aqueous HP-β-CD solution to the micelle, ΔγGΘm, increases with increasing HP-β-CD concentration in aqueous solution, which showed that SDBS molecules are more likely to form inclusion complexes with HP-β-CD rather than micelles. The results of Job’s plot for inclusion complexation of SDBS with HP-β-CD indicated that “β-CD/SDBS” inclusion should be formed with the molar ratio of 1∶1 in aqueous solution. The effect of the formation of SDBS micelle on the quantitative determination of SDBS could be greatly reduced by adding HP-β-CD with the molar ratio of 1∶1. Thus, whether higher or lower than the critical micelle concentration value, the concentration of SDBS in water samples from T5-X15 and T9-X4 sites in LinPan oilfield could be calculated by establishing the quantitative standard curve of SDBS in aqueous HP-β-CD solution, and the recovery rate of SDBS was 100.5%~101.2%. The results of 1H-NMR and FT-IR showed that the phenyl group of SDBS molecule is likely located within the broad mouth of HP-β-CD molecule.

In this paper, the interaction of cucurbit ［8］uril(Q［8］) with thionine (TH) and carbendazim (CBZ) were investigated with fluorescence and UV-Vis spectroscopy. The experimental results showed that the inclusion complex between Q［8］ and TH informed was at molar ratios of 1∶2 in 0.01 mol·L-1 hydrochloric acid solution. The fluorescence intensity of the Q［8］/TH complexes quenched when Q［8］ was added to TH solution, but fluorescence increasing of the Q［8］/TH complex with the addition of CBZ was observed. The fluorescence increasing values show a good linear relationship with the CBZ concentration within 0~3.5 μmol·L-1. The linear regression equation relating fluorescence intensity (If) to CBZ concentration (c) is If=0.45c+32.24 (r=0.999). The detection limit was 9.39×10-8 mol·L-1. Forthemore, the influence of foreign species on the analytical signal of the Q［8］/TH complex in the presence of carbendazim was established. No interference was observed from commonly used foreign species such as metal ions (Fe3+, Mg2+, Ca2+). In particular, benzimidazole compounds thiabendazole and fuberidazole do not interfere with CBZ determination at a specific concentration. The results revealed that complexation of Q［8］ and TH with CBZ offers a fluorescent switching “on-off” effect which will supply a potential application in pesticide residues test.

As an important content of the nature, soil has great influence on the formation of ecological system and human life. Therefore, the study of soil’s polarized thermal radiation characteristics has great practical significance. There have been few reports about the study of the polarized radiation characteristics of the soil in 2π space. The results showed that the polarized brightness temperature performed nonlinearly as the change of detection angles between 0° to 80°. However, polarized brightness temperature increased greatly when the detection angle changed from 60° to 80°. It also changed under different azimuth angles. The polarized brightness temperature increased as the growth of the azimuth angles in the range of 0° to 240°, but its tendency was opposite in the range between 240° and 320°. The channels and polarized angles both influenced the polarized brightness temperature. Their amplitudes of fluctuation of their own curves were gentle and the temperatures of different agrotype were various. The order was Meadow Soil>Leached Chernozem>Chernozem>Aeolian Soil. These results provide significant foundation to the study about the basic theory of thermal infrared polarization remote sensing.

The aim was to find a nondestructive way to improve the accuracy of detecting the winter wheat aboveground fresh biomass(AGFB). In this study, data fusion technology of the spectroscopy technology and the machine vision technology were used to analyze the AGFB and solve the problem that the accuracy of the prediction model of a single technology is not high. In this experiment, canopy spectra and canopy pictures of 93 samples at seeding stage were collected. Canopy spectra and side images of 200 samples at medium and later growth stage were collected. Spectral reflectance as the spectral absorption parameter was used to construct the AGFB prediction models based on the spectra technology at different stages; The wheat coverage were extracted from canopy pictures and side images by using image processing technology to build the AGFB prediction models. Multivariate regression analysis (MRA) and Partial least-squares regression analysis(PLS) were implemented on the feature variables from the spectral information and image information. The results showed that, compared with the individual image model and spectral model, the AGFB prediction models of PLS based on multi-information at different stages shows better performance. At the seeding stage, the determination coefficient (R2) of PLS models based on multi-information was 0.881, and the RMSE was 0.015 kg. The R2 of PLS models based on multi-information was 0.791, the RMSE was 0.059 kg at middle and final stages. It demonstrated that the precision of model based on multi-information fusion technology, which increased utilization of image and spectral information, was improved for AGFB detecting, which is than the individual image model and spectral model.

Discriminating the maturity levels of tobacco leaf with in-situ measurement can effectively reduce loss rate and quality decline due to misjudgment of the maturity levels of tobacco leaf. In the meantime, the regular way we use to determine the maturity levels of tobacco, which is depend on tobacco leaf age and judgment of tobacco grower, lacks of objectivity. So this paper proposed a method to identify maturity levels of tobacco leaf by using spectral feature parameters combined with the method of support vector machine (SVM). In this paper, a total of 351 tobacco leaf samples collected in 5 maturity levels including immature (M1), unripe (M2), mature (M3), ripe (M4), and mellow (M5) determined by experts were scanned by field spectroscope(ASD FieldSpec3) with in-situ measurement for getting their reflectance spectrum. Through spectral analysis we found that the spectrum of tobacco leaf with different levels of maturity can be distinguished in visible band but not easily be distinguished in near-infrared band, so we use the tobacco leaf spectrum in visible band as the sensitive bands to analyze and model. To find the most suitable input variables for modeling, we use continuous spectrum (350~780 nm), feature band (496~719 nm) and spectral feature parameters (the reflectance of green peak, location of green peak, first order differential value of red-edge and blue-edge, red-edge and blue-edge area, location of red-edge and blue-edge) in visible region as the input variables, and using these three kinds of input variables in the method of SVM to establish a discriminant model for identifying maturity levels of tobacco leaf. The result shows that, the model using spectral feature parameters gains the accuracy rate of 98.85%. While the accuracy rates of other two models were 90.80% and 93.10%, respectively. The conclusion was drawn that using spectral feature parameters in visible spectrum as the input variables in SVM can improve the model performance. It is feasible to use this method to identify maturity level of tobacco leaf with in-situ measurement.

The paper uses MSR-16 portable multispectral radiometer made in the USA and computes the numbers of the test units by pulling the formula on the radiometer effective observation area, which solves the problem on the uncertain numbers of computing the times on region visible light band spectral radiation ratio M_D. The paper uses CI-310 portable photosynthesis measurement system made by American CID Company and measures the net photosynthetic rate of a group of soybean plant. M_D and C_D are normalized by the normalization method ［0,1］. Then, the normalization data M_D1 and C_D1 are gained . Based on the different test time, M_D1 is divided of M_D11 and M_D12. C_D1 is divided of C_D11 and C_D12. The paper uses polynomial kernel function, gauss kernel function, sigmoid kernel function and bio-selfadaption kernel function constructed by us with Support Vector Machine. Penalty parameter c and parameter g separately are optimized with optimization algorithms such as grid-search, genetic algorithm and particle swarm optimization. Based on the formula epsilon-SVR and the formula nu-SVR with Support Vector Machine, the paper constructs the prediction model on the net photosynthetic rate of a group of soybean plant by using of the cross combination with four kernel functions, three optimization methods and two formulas. The test results are as follows: in the condition of S=17 m2 which is the test plan area of soybean plant and the H=2 m which is the high on MSR-16 portable multispectral radiometer above the canopy of soybean plant, the prediction accuracy is up to 85% on the No.1 prediction set C_D12 and the prediction accuracy is up to 82% on the No.2 prediction set C_D12 based on the model epsilon-SVR-bio-selfadaption-grid-search. In the condition of other combinations with S and H, the prediction accuracy is up to 81% on the No.2 prediction set C_D12 based on the model epsilon-SVR-bio-selfadaption-grid-search. The model epsilon-SVR-bio-selfadaption-grid-search indicates the validity of bio-selfadaption kernel functions which is constructed by our previous research with support vector machine. The model epsilon-SVR-bio-selfadaption-grid-search indicates the rationality of the measure method on visible spectral data in the test area. The model epsilon-SVR-bio-selfadaption-grid-search indicates the feasibility of the prediction method on net photosynthetic rate of soybean plant groups by using of visible spectrum.

In order to study the feasibility of using digital image analysis and machine learning algorithm to estimate leaf nitrogen accumulation (LNA) of winter wheat at canopy level, digital images of winter wheat canopies grown under six levels of nitrogen application rate were taken for four times during the elongation stage. Meanwhile, wheat plants were sampled to measure LNA. The random forest method using CIEL*a*b* components was used to segment wheat plant from soil background and then extract canopy cover, RGB components of sRGB color space and compute five color indices derived from RGB components. Correlation analysis was carried out to identify the relationship between LNA and canopy cover (CC), RGB components, and five color indices. Two kinds of nonlinear least squares regression models (NLS) with different independent variables of color components and color indices, and three machine learning algorithmic of artificial neural network (ANN), support vector regression (SVR), and random forests method (RF) were used to estimate winter wheat leaf nitrogen accumulation. All three machine learning algorithm had four input variables of CC, R, G, and B. The results showed that, CC, R and G component of sRGB color space, and five color indices derived from RGB components showed significant correlations with LNA during the elongation stage. CC revealed the highest correlation with LNA. The lowest accuracy in estimation LNA was achieved by using nonlinear least square model with CC and color indices, and RF had showed the problem of overfitting. The other three methods of LNA with CC and RGB components, ANN, and SVR had showed good performance with higher R2 (0.851, 0.845, and 0.862) and lower RMSE (19.440, 19.820, and 18.698) for model calibration and validation, revealing good generalization ability.

Near-infrared hyperspectral imaging technology combined with chemometrics was applied for rapid and non-invasive transgenic soybeans variety identification. Three different non-GMO parent soybeans(HC6, JACK, TL1)and their transgenic soybeans were chosen as the research object. The developed hyperspectral imaging system was used to acquire the hyperspectral images in the spectral range of 874~1 734 nm with 256 bands of soybeans, and the reflectance spectra were extracted from the region of interest (ROI) in the images. After eliminating the obvious noises, the moving average(MA)was applied as smooth pretreatment, and the wavelengths from 941~1 646 nm were used for later analysis. Partial least squares-discriminant analysis (PLS-DA)was employed as pattern recognition method to class the three different non-GMO parent soybeans. The classification accuracy of both the calibration set and the prediction set were 97.50% and 100% for the HC6, 100% and 100% for the JACK, 96.25% and 92.50% for the TL1, which indicated that hyperspectral imaging technology could identify the varieties of the non-GMO parent soybeans. Then PLS-DA was applied to classify non-GMO parent soybean and its transgenic soybean cultivars for building discriminant models. For the full spectra, the classification accuracy of both the calibration set and the prediction set were 99.17% and 99.17% for the HC6 and its transgenic soybean cultivars, 87.19% and 81.25% for the JACK and its transgenic soybean cultivars, 99.17% and 98.33% for the TL1 and its transgenic soybean cultivars, respectively. The sensitive wavelengths were selected by x-loading weights, and the classification accuracy of the calibration set and prediction set of PLS-DA models based on sensitive wavelengths were 72.50% and 80% for the HC6 and its transgenic soybean cultivars, 80.63% and 79.38% for the JACK and its transgenic soybean cultivars, 85% and 85% for the TL1 and its transgenic soybean cultivars, respectively. These results showed that the pattern recognition for non-GMO parent soybean and their transgenic soybeans was feasible, and the selected sensitive wavelengths could be used for the pattern recognition of non-GMO parent soybeans and transgenic soybeans. The overall results indicated that it was feasible to use near-infrared hyperspectral imaging technology for the pattern recognition of the non-GMO parent soybeans varieties, non-GMO parent soybean and its transgenic soybeans. This study also provided a new alternative for rapid and non-destructive accurate identification of transgenic soybean.

Only using soil spectrum to model soil salinity is not enough to meet the actual demands because of the complicated soil context. As a remotely sensed indicator, the vegetation type and its growing condition can provide a spatial overview of salinity distribution. Based on the synergistic relationship between soil salinity and vegetation in arid land, this paper tries to combine the spectrum of soil and vegetation to quantitatively estimate the salt content with the help of the concept of two-dimensional feature space. After the analysis of scatter diagram, the soil salinity detecting model was constructed to improve reasoning precision. However, because the impact of soil reflectance on the quantification of vegetation parameters under the individual pixel, the Normalized Difference Vegetation Index (NDVI) was difficult to accurately obtain sparse vegetation cover in arid areas. Therefore, in order to avoid the limitations of NDVI, the Combined Vegetation Indicative Factor(CVIF)was created and supported by Linear Spectral Unmixing Model (LSUM). Then, the study constructed the feature space based on the CVIF and salinity index (SI) and analyzed the response relationship between soil salinity and the trend of scattered points. Finally, a new and operational model termed Salinity Inference Model (SID) was developed. The results showed that the CVIF (R2>0.84, RMSE=3.92) performed better than NDVI(R2>0.66, RMSE=13.77), which means the CVIF was more appropriate for analyzing variations in vegetation cover (particularly halophytes) than NDVI in the study area. The SID was then compared to the Combined Cpectral Response Index (COSRI)(NDVI-based) from field measurements with respect to the soil salt content. The results indicated that the SID values are highly correlated with soil salinity, in contrast to the performance of COSRI. Strong exponential relationships were observed between soil salinity and SID (R2>0.86, RMSE<6.86) compared to COSRI (R2=0.71, RMSE=16.21). These results suggested that the feature space related to biophysical properties combined with CVIF and SI can effectively provide information on soil salinity.

Powdery mildew (Blumeria graminis) and stripe rust (Puccinia striiformis f. sp. Tritici) are two of the most prevalent and serious winter wheat diseases in the field, which caused heavy yield loss of winter wheat all over the world. It is necessary to quantitatively identify different diseases for spraying specific fungicides. This study examined the potential of quantitative distinction of powdery mildew and yellow rust by using hyperspectral data with continuous wavelet transform at canopy level. Spectral normalization was processing prior to other data analysis, given the differences of the groups in cultivars and soil environment. Then, continuous wavelet features were extracted from normalized spectral bands using continuous wavelet transform. Correlation analysis and independent t-test were used conjunctively to obtain sensitive spectral bands and continuous wavelet features of 350～1 300 nm, and then, principal component analysis was done to eliminate the redundancy of the spectral features. After that, Fisher linear discriminant models of powdery mildew, stripe rust and normal sample were built based on the principal components of SBs, WFs, and the combination of SBs & WFs, respectively. Finally, the methods of leave-one-out and 55 samples which have no share in model building were used to validate the models. The accuracies of classification were analyzed, it was indicated that the overall accuracies with 92.7% and 90.4% of the models based on WFs, were superior to those of SFs with 65.5% and 61.5%; However, the classification accuracies of Fisher 80-55 were higher but no different than leave-one-out cross validation model, which was possibly related to randomness of training samples selection. The overall accuracies with 94.6% and 91.1% of the models based on SBs & WFs were the highest; The producer’ accuracies of powdery mildew and healthy samples based on SBs & WFs were improved more than 10% than those of WFs in Fisher 80-55. Focusing on the discriminant accuracy of different disease, yellow rust can be discriminated in the model based on both WFs and SBs & WFs with higher accuracy; the user’ accuracy and producer’ accuracy were all up to 100%. The results show great potential of continuous wavelet features in discriminating different disease stresses, and provide theoretical basis for crop disease identification in wide range using remote sensing image.

The new hybrid flocculant polyaluminum chloride-poly (dimethyl diallyl ammonium chloride) (PAC-PDMDAAC) was used to treat disperse violet and reactive brilliant red dye wastewater. The experimental results indicated that the decolorization effect of hybrid PAC-PDMDAAC was better than that of PAC and composite PAC-PDMDAAC. The decolorization rates of disperse violet and reactive brilliant red dye wastewater were 99% and 86.8% respectively when the dosages of hybrid flocculant were 400 and 450 mg·L-1. When the pH of disperse violet wastewater was 7～12, the hybrid flocculant had the best decolorization effect. When the pH of reactive brilliant red wastewater was 7～9, the hybrid flocculant had the best decolorization effect. Each of the two dyes and their flocs were characterized with FTIR. Results showed that the hybrid flocculant had a complex reaction with the dye wastewater, and the main decolorization mechanism was charge neutralization and adsorption bridging capacity. The UV scanning results indicated an adsorption peaks shift and an absorbance decreases, which further explained the main mechanism above. At the same time, it also indicated the ether linkage and —NH2 of disperse violet were destroyed and replaced by hybrid flocculant, and the -SO3 , Cl－ of reactive brilliant red were also replaced. The study will provide a new method in decolorization effiency and decolorization mechanism for the new inorganic-organic hybrid polymer flocculant. And it has significant practical meaning and application value.

In the study, rubber accelerator 3-methylthiazolidine-2-thione (MTT) was synthesized by one-step method firstly. MTT was detected and characterized by XRD, FTIR, TG-DSC. The micro-structure and intrinsic regularity were revealed. Chemical bond types into MTT molecule were revealed by FTIR. MTT phase composition and structure were given by crystallographic data from XRD detecting such as cell parameters, crystal face index. The phase composition and qualitative identification of MTT structure were completed. Two kinds of information were detected by TG-DSC as quality change and thermal effect. MTT phase transition and decomposition temperature were 76.3 and 306.9 ℃ respectively. The decomposition temperature of MTT was very high. It could provided reference with research on rubber vulcanizing properties by MTT on rubber vulcanizing machine. This study can provide the basis experimental data on the enterprises to designate the working standard tracing detection of MTT industrialized production. Performance index of MTT was judged.

The pulsed plasma thruster(PPT) is suited for various applications, e. g., attitude control, station keeping and formation flying due to its significant advantage with regard to the related savings of wet system mass, small volume and high specific impulse. In order to elaborate the mechanism of PPT operation process, the optical emission spectrum was conducted on a breech-fed PPT with tongue electrodes. The results show that plasma plume mainly consists of C, F, C+, F+ and C2+, besides Cu+ and Cu2+ were detected in plasma which were produced by electrodes ablation. The plasma distribution is asymmetric in the discharge channel, the maximum of plasma density of plasma appears at the central axis of discharge channel and the plasma density nearby the anode is much higher than that nearby the cathode. The composition of plasma is not symmetric and not uniform. The distribution of F+ and neutral particle concentrate close to the anode. The electron temperature is about 6.67 eV derived from the optical emission spectra by Boltzmann linear fitting. Evolution of plasma emission spectrum was derived at the fourth measurement point, the results show that there is much difference between different discharge stages for the composition of plume and the proportion of each component.

As a novel technology in ultra-smooth surface machining, atmospheric pressure inductively coupled with plasma jet processing can produce plasma with high density and energy. This capability makes it a perfect medium in fully exciting the reactive gases to improve the material removal rate. This paper is directed towards using the emission spectrometer to monitor and measure the spectra of the plasma jet from 400~1 000 nm. Spectral lines with obvious peaks and large energy differences are selected from the measurement results to calculate the electron temperatures. The measured spectral data are the integrals of emission coefficients along the optical path, and the plasma has a circularly symmetry with respect to the torch axis. Abel inversion transform is employed to compute the emission coefficients of the measured spectrum. These coefficients are then applied to obtain the electron temperatures with Boltzmann plot method. The calculation results denote that the temperature profiles appear to be typically double-peak profiles as a result of the skin effect and swirling inlet flow. With the increasing of off distance, the double-peak effect decreases and the profiles become smooth. The results also indicate that the plasma fringe is somewhat deviate from the local thermodynamic equilibrium, and the applicability of Boltzmann plot method is reduced. Consequently the goodness-of-fit factors, R-Squared values, on the plasma fringe are reduced. The spectra and characteristics of the argon plasma with reactive gas CF4 are also analyzed. This mixed plasma shows bright blue-green color. The reason for the color is that some band spectra emerge between the range of 400~650 nm. These band spectra are the swan bands of diatomic C2 which is formed by the fully excitation of carbon source CF4.

The spot-halo hexagon pattern consisted of the center spot and hexagon halo in dielectric barrier discharge is researched, which filled with gas-mixture of argon and air. The pictures taken from the experiment shows that there is an obvious difference on brightness between the center spot and hexagon halo. All of these phenomena suggest that the center spot and hexagon halo are probably in different plasma state. The plasma parameters of the center spot and hexagon halo in the spot-halo hexagon pattern as a function of gas pressure are studied in details by using optical emission spectra. The emission spectra of the N2 second positive band(C3Πu→B3Πg)are measured, from which the molecule vibrational temperature of the center spot and hexagon halo are calculated. Based on the relative intensity of the line at 391.4 nm and the N2 line at 394.1 nm, the change of the electron average energy of the center spot and hexagon halo as a function of gas pressure is investigated. The electron density is studied by using the broadening of the spectral line 696.5 nm. It is found that the main chart of the spot-halo hexagon pattern is the argon content from 60% to 75% and the pressure from 30 to 46 kPa. The molecule vibrational temperature and electron average energy of the hexagon halo are higher than those of the center spot at the same pressure. As the pressure gradually increased from 30 to 46 kPa, the molecule vibrational temperature and electron average energy of the center spot and hexagon halo are increased, too. The broadening of the spectral line of the hexagon halo is bigger than the center spot at the same pressure, which increases with the gas pressure increasing. It indicates that the electron density increases with gas pressure increasing. The different plasma state of the center spot and hexagon halo show that the different formations mechanism of them. It is found that there are volume discharges firstly and then comes surface discharges with e high speed camera.

In order to promote the research on erbium-doped fiber’s anti-radiation properties and fully grasp variation laws of erbium-doped fiber’s properties under radiation, theoretical analysis on how irradiation effect erbium-doped Fiber based on model of color centers was conducted. The performance changes of erbium-doped fiber that may occur during irradiation were predicted. According to working principle and application characteristics, online real-time monitoring of 980 nm wave band loss spectra, 1 550 nm wave band loss spectra, luminescence spectra of two different types(EDF-L-980 and MP980) of erbium-doped fiber as well as recovery measuring after radiation were carried out,. Studies showed that spectral characteristics of both types have similar variation trends during radiation. Losses at 980 and 1 530 nm wave band increase monotonically with dose, and the relationship is approximately linear at absorption peak of 980 and 1 530 nm; luminescence spectra intensity decreases monotonically with dose, and energy of luminescence spectra is shifting to long wavelengths, while its mean wavelength and bandwidth increasing substantially. The relationship between luminescence intensity and dose is also approximately linear at luminescence peak of 1 530 nm. Erbium-doped fiber’s spectral characteristics recovered modestly after radiation, but to a limited extent of less than 40% for all parameters. The experiment result is in good agreement with theoretical analysis and prediction, so rationality of theoretical explanation of erbium-doped fiber’s performance changes during radiation has been proven.

With the rapid development of economy and industrialization, global warming is becoming the most serious sensitive global climate issues, which causes the rising of sea level and many other negative effects. The cause of global warming is the emission of greenhouse gases and carbon dioxide is the main component of greenhouse gases. The control of CO2 emssion is beneficial to addressing gobal climate change and environmental degradation. Therefore, it’s important to develop a rapid detection of CO2 for accurate control. There are amounts of methods to detect CO2 at present, including titration, electrochemical method, gas chromatography, infrared absorption spectroscopy and so on, however, t they still have the deficiency for online monitoring in industrial field. laser induced breakdown spectroscopy (LIBS), which is developing rapidly in recent few decades, is a detecting technology with characteristics of time-saving and synchronous measuring of multicomponent. What’s more, there is no need for sample pretreating. To develop the online monitoring technique of CO2 emission in the industrial field, LIBS was employed to measure CO2 in this study. The mass flow controller was used to adjust the flow of high purity CO2 and N2 to obtain mixed gas with different CO2 concentrations. The mixed gas was firstly mixed in an air mixing chamber for thorough mixing and then sent to the sample cell for LIBS measurement. The evolution of C atomic spectral line and CN molecular band with different delay times were being studied, which demonstrated parts of CO2 react with air ambient to form CN molecular during the plasma generation, the CN molecular band should be taken into consideration for quantitative analysis, and the parameters were optimized for synchronous measurement of C line and CN band: 800 ns was the optimal delay time. During the plasma generation, many factors in the plasma may interact with others, the analysis index had close relationship wih serval measuring parameters. With the consideration of the effect of C, CN and the self-absorption in high concentration, multivariate calibration method was employed to establish calibration models of CO2. The results showed that the correlation coefficients R2 and the slope were 0.978 and 0.981, respectively. Compared with calibrated with single factor, the multivariate method improved the reliability of the model. What’s more, the feasibility of the application of LIBS to measure CO2 rapidly was proved.

Laser-induced breakdown spectroscopy (LIBS) was used to calibrate the concentration of Cr in soils combined with Support Vector Machine. The Nd:YAG pulse laser with the wavelength of 1 064 nm was used as the excitation source. The grating spectrometer and the charge couple device were used as spectral separation device and the spectral detection device. The multiple linear regression and support vector machine were adopted to make quantitative analysis on Cr in soils respectively. The result indicate that the multiple linear regression can get more accurate informination of the spectral lines: the correlation coefficient is increased from 0.689 to 0.980 compared with conventional quantitative method. Thereofre, the the accuracy of quantitative analysis is increased. The slope about calibration curve with support vector machine of test set is nearly about 1 and the correlation coefficient is 0.998, the relative errors for the test set all are lower than 2.57%, the quantitative analysis results about support vector machine are better than the results combined with the conventional quantitative method and the multiple linear regression. The support vector machine can correct the matrix effect and improve the accuracy of prediction on the concentration of Cr in soil.

Density, which is closely relate with many physical and mechanical properties of bamboo, is one of the important indicators of bamboo material properties. Moreover, because of existing different moisture gradients in bamboo, the measured results of the density are different. Based on X-ray computed tomography (X-CT) technology, the divergent degree of the CT values of 7 different aged Moso bamboo was compared under oven-dried, air-dried and water-saturated conditions. Except for the 4-year-old and 10-year-old Moso bamboo, the CT values of other aged bamboos have minor differences with each other; the models for the measured CT values and the corresponding densities of Moso bamboo were respectively fitted under oven-dried, air-dried and water-saturated conditions. Meanwhile, the model was also fitted under different moisture gradients, which was composed by the measured CT values and the corresponding densities of Moso bamboo. Then the relations between the CT values andthe densitiesof 7 different aged Moso bamboo were systematically analyzed under single moisture content and three moisture gradients;the CT values were fitted under oven-dried condition, of which the radial positions are relative to the outer of Moso bamboo. According to the relation between the CT value and the density, the fitting curves explain the reasons for the radial density variations of 7 different aged Moso bamboo. Results show that the relations, which are fitted by the measured densities and the corresponding CT values of 7 different aged Moso bamboo under oven-dried, air-dried and water-saturated conditions, are good linear and the slopes of those models are approximate; the relation of the densities with the CT values for Moso bamboo is linear under different moisture gradients, moreover, which is rarely affected by moisture. The regression equation is: D=0.001 H+1.003 2, R2=0.968 3(D is the density, H is the CT value) and the determination coefficient of the validation model is: R2=0.974 3; there is no obvious variation between the densities of the inner and the outer, but not in middle part to 7 different aged Moso bamboo under oven-dried condition. To realize rapid detection on the densities of Moso bamboo under different moisture content, these results provide technical support and data reference. At the same time, X-ray computed tomography (X-CT) technology also puts forward a new feasible way for the further studies of bamboo material properties and structure.

Currently, X-ray fluorescence spectrometer (XRF) is not widely used in the determination of geological samples, and it’s much less used in the study of sedimentary facies. XRF was firstly used to identify sedimentary environment of the T3x2 formation in central Sichuan region. In order to investigate the controversy of sedimentary facies and sedimentary environment of T3x2 formation of the Upper Triassic in the Central Part of Sichuan Basin, particularly whether the T3x2 formation is continental deposit or marine deposit, samples were collected in four representative zones from Xujiahe formation in Sichuan Basin. The method of X-ray fluorescence spectrometry were used to analyze the element contents and its’ changing characteristics of the deposition from target formation. The sedimentary facies and sedimentary environment of target formation could be quantificationally analyzed by the symbol of corresponding element content. The results of the study show that the ratio of Sr/Ba, Mn/Fe and Sr/Ca of T3x2 formation belong to continental deposits, and it has no significant difference with characteristics of element contents from T3x3 or T3x4. The analysis results about the ratio of Sr/Cu show that the climatic environment of target formation was warm and humid, and T3x2 formation was belong to continental deposits in warm and humid environment, which is similar to the sedimentary environment of T3x3 or T3x4 formation. The relative errors between this method and conventional chemical analysis are less than 3%. The method of X ray fluorescence spectrometry is simple and feasible, which provides a quantitative analysis method for identification of sedimentary facies and sedimentary environment. The paper provides a new feasible method to solve the controversial sedimentary facies, which will promote the using of X-ray fluorescence spectrometric analysis method in geology.

In order to investigate the effect of long-term (1991—2013) K fertilizer deficiency and surplus on potassium-bearing mineral and K nutrition of purple soil -soil primary, clay mineral composition and potassium (K) nutrition were determined on the long-term experiment of fertility and fertilizer efficiency in neutral purple soil by using X-ray diffraction (XRD) analysis technique. Five soil samples were selected from soil samples library for soil mineral analysis, including original soil, which preserved in 1991 before the experiment carrying out; K deficient treatment for 12 years and 22 years, which means no K fertilizer was applied during 1991—2003 and 1991—2013, respectively; and K surplus treatment for 12 years and 22 years, which means excess K fertilizer was applied during 1991—2003 and 1991—2013, separately. The result showed that, soil potassium-bearing primary mineral, such as mica, potassium feldspar, had apparently weathered and slaked for the K deficient treatment and the weathered extent gradually aggravated following fertilization ages, demonstrating fertilization for 22 years<12years<original soil. However, for K surplus treatment, the content of mica and potassium feldspar only had a little decline. As similar with primary mineral, for soil clay potassium mineral, the content of illite and mica was also seriously reduced for K deficient treatment and a slightly declined for K surplus treatment, representing the disintegration of soil potassium mineral under rice-wheat rotation system, and the deficient input of K fertilizer would obviously accelerate this weathering process. The two treatments all represented raising of vermiculite with the increasing of fertilization ages, and it’s much higher on K surplus treatment than K deficient treatment. In addition, we found that the silica-sequioxide ration of soil clay, which indicated the degree of soil weathering, decreased as the fertilization ages increasing, and after 22 years K deficient input soil clay had the lowest silica-sequioxide ration, showing the greatest weathering extent of soil clay silicate minerals. To further research the changing of soil K nutrition, we analyzed the content of soil available K, slowly available K and total K. The result indicated that, for K deficient treatment, soil available K and slowly available K content all gradually declined with the increasing of fertilization ages, about 62.0% and 37.4% down from 1991 to 2013, respectively. While there had a gain trend of soil available K content after long-term K surplus input, versus slightly dropping of slowly available K content. However, we found that long-term fertilization had no obvious effect on soil total K content. Therefore, long-term K deficiency could have negative effect on soil K, exhausting soil K resource and accelerating soil mineral weathering. It seems to be difficult maintaining soil slowly available K and potassium-bearing mineral content, even excess applied K fertilizer.

As the polarization characteristics are the physical property determined by the material itself, its corresponding polarization image contains abundant target’s information. Using polarization information to identify the target is always a hot research topic in the field of the target detection. Active polarization imaging has more advantages compared with passive polarization imaging because of its high signal-to-noise ratio and good controllability. In this paper, based on the detailed analysis of the theory of the distribution of polarization Fresnel reflectance ratio, a kind of active polarization imaging method is proposed with detecting the polarization Fresnel ratio of the surface of the object. The proposed method adopts two kind of polarization light with orthogonal polarization direction at the light emission part to exposure to the target scenario alternately. Then two cameras side-by-side at the detecting part respectively equipped with two orthogonal polarization direction filters to capture the polarization images. Meanwhile, the detectors are placed in different detecting direction to acquire the polarization imaging with active polarization light source illuminating. Finally, with transmitting the data to the calculating center, optical constants can be recovered from the polarization data by the optimization fitting technique. Because the materials of target’s surface are different, the corresponding optical constants are different. Then the purpose of discriminating the targets with different materials is achieved. The simulated and actual measured experiments are explored to verify the effectiveness of the proposed method. Simulation experiment shows it is not only scientific but also more convenient and effective in that the proposed method can distinguish the different materials using the calculated optical constants. The actual measured data further shows that the method is able to do better in recover optical constants of targets, especially in the distinction between metal and dielectric materials. Furthermore, the system has great application prospect in the field of target detection and camouflage recognition with its simple structure and practicability.

The finite bandwidth of spectroradiometers always causes significant errors when the measured light source has a narrow bandwidth compared to that of spectroradiometers. In order to solve this problem, an improved correction approach which is called seven-point correction approach is proposed. Firstly, the seven-point correction formula is obtained with Taylor’s series and related derivative formula. Secondly, the effect of seven-point formula is validated through a simulated spectrum with a sine function shape. Considering the sine function as true spectrum, we calculate the measured spectrum with the bandpass function of spectroradiometers. We also correct the measured spectrum with the seven-point formula. At last, we validate the seven-point formula experimentally with a LED lamp whose center wavelength is 365 nm. Using a double grating monochromator, we measure the irradiance of LED lamp when the bandwidth of spectroradiometer is 5 and 0.5 nm. We also obtain the corrected spectrum by applying seven-point formula to measured spectrum. The simulated results show that, the corrected value at the center wavelength could be above 99% of the true value. The experimental results show that, the corrected value at the center wavelength could reach above 95% of the true value. Above all, the proposed seven-point approach has an improved correction effect compared with three-point and five point approach. This correction approach could be widely applied in the field of spectrum measurement.

Echelle spectrometer gets full spectrum by transient direct reading because of the characteristic of cross-dispersion. The two-dimension spectra received by flat-plane detector needs to be reduced to one-dimension spectra so that the effective wavelength can be detected. Because of huge original data and few effective data, background removal plays an important role of decreasing the amount of data and improving data processing speed. The two-dimension spectrum of echelle spectrometer is analyzed and a suitable background removal algorithms is came up. The edge detection method is applied to diffuse spot detection. Selecting appropriate operator to convolute original image to get edge image and calculating global threshold to segment edge image which can be used to map original image to get the background removed image. Two-dimensional spectral images based on different elements at different integration time are used to judge the effect of different background removal algorithm and different operator are analyzed to figure out their effect of speed and accuracy for algorithm. Experimental result shows that the algorithm came up by this letter is better for image background removal than the others. The background removed image can be used in spectrum reductionand the speed of data processing is notable promoted.

In order to calibrate the corresponding center wavelength and bandwidth to the prism’s rotating angle of a scanning prism-dispersive solar spectrometer, a prism-rotating method to measure the spectral response function (SRF) of the solar spectrometer is suggested. The measuring process is as follows. With the wavelength of monochromatic light invariant, the prism is rotated for scanning the monochromatic image at the location of detector. Then the spectral response function is obtained by mapping the coordinate in position to the coordinate in wavelength. At first in this paper, by analyzing the definition of SRF, the conclusion is deduced that the prism-rotating method is equivalent to the wavelength-scanning method in practice. Then the 532 nm solid-state laser and 632.8 nm He-Ne laser are used as light source. The measurement of SRF of the solar spectrometer based on prism-rotating method is performed. A measurement of SRF with wavelength-scanning method is also performed to be used as a comparison. Experimental results indicate that the center wavelength of the scanning prism-dispersive solar spectrometer measured with prism-rotating method is 531.86 and 632.67 nm respectively. On the other hand, the result is 53139 and 631.97 nm with wavelength-scanning method, which is less precise than the result of prism-rotating method. The values of bandwidth measured with prism-rotating method are also more precise than the latter owing to avoiding the performance deficiency of monochromator. At last, using mercury vapor lamp as light source, an experiment for spectral calibration of the solar spectrometer with prism-rotating method is performed. The values of center wavelength and bandwidth are both achieved with the method combining the prism-rotating method and chracteristic spectrum. This method can also be used to calibrate the monochromator and the grating-dispersive spectrometer whose grating is rotatable.

The self-developed portable DOAS instrument based on differential optical absorption spectroscopy(DOAS) and composed of optical fiber spectrograph and multiple-pass cell was introduced. The standard gases of SO2 and NO2 were employed to test the accuracy and stability of the system, and then cruise observation of SO2, NO2 and benzene was carried out using the system in Tongling industrial park. During the entire period, the polluted gases showed high concentrations near the contaminated areas and the maximum concentrations of SO2, NO2 and benzene were 5 023.2, 2 195.2 and 162.5 μg·m-3, respectively. With 12.6 m optical path, the detection limits of SO2, NO2 and benzene were 67.0, 169.9, 30.6 μg·m-3, respectively. The portable DOAS system provides a convenient and effective technique for industrial park about emergency and supervisory monitoring and evaluation of gas leakage and fugitive emissions of gaseous pollutants.

The satellite thermal infrared image has been an important data source for the acquisition of the earth’s surface temperature. The thermal infrared sensor (TIRS) Landsat 8 satellite newly launched onboard has added valuable data for this mission. However, the calibration parameters for the two bands of the TIRS, i.e., TIRS Bands 10 and 11, had been modified several times since its launch. This finally led the United States Geological Survey (USGS) to reprocess all achieved Landsat 8 data starting from February 2014. In order to examine the calibration accuracy of the reprocessed TIRS data, this paper crossly compares Landsat 8 TIRS data with synchronized, well-calibrated Landsat 7 ETM+thermal infrared data. A total of three date-coincident image pairs of western United States, downloaded from USGS Earth Explorer website, were used for the cross comparison. Three test sites were selected respectively from the three image pairs for the comparison, which representing moderate vegetation-cover area (test site 1), low vegetation-cover area (test site 2), and bare soil area (test site 3). The thermal infrared data of the three image pairs of both sensors had been firstly converted to at-sensor temperature. A band-by-band comparison and a regression analysis were then carried out to investigate the relationship and difference between the two sensor thermal data. The results show a very high degree of agreement between the three compared Landsat 8 TIRS and Landsat 7 ETM+thermal infrared image pairs because the correlation coefficients between the retrieved at-sensor temperature of the two sensors are generally greater than 0.95. Nevertheless, the cross comparison also reveals differences between the thermal infrared data of the two sensors. Compared with retrieved at-sensor temperature of Landsat 7 ETM+Band 6, TIRS Band 10 shows an overestimation, which can be up to 1.37 K, whereas TIRS Band 11 underestimates the temperature, with a difference reaching to -3 K. This suggests that in spite of the reprocessing of Landsat 8 thermal infrared data, the calibration parameters for the satellite’s TIRS data are still unstable, especially for TIRS Band 11. It was found that the at-sensor temperature difference between ETM+Band 6 and TIRS Band 10 was enhanced with the decrease in vegetation coverage from test site 1 to test site 3. The at-sensor temperature difference of test site 1 is 0.07 K and increased to 1.37 K in test site 3, a net increase by 1.3 K. While the at-sensor temperature difference between ETM+Band 6 and TIRS Band 11 had an inverse performance. With the decrease in vegetation coverage from test site 1 to test site 3, the at-sensor temperature difference was reduced from ~-3.0 to -0.4 K. Therefore, in bare soil dominated test site 3, the temperature difference was 1.37 K for TIRS Band 10 and -0.4 K for TIRS Band 11. The RMSE of TIRS Band 11 is also much lower than that of TIRS Band 10. This suggests that TIRS Band 11 can perform batter in bare soil area than TIRS Band 10 though the latter shows an overall batter performance than TIRS Band 11. The study also found that in low vegetation cover areas like in test sites 2 and 3, taking an averaged at-sensor temperature of TIRS Bands 10 and 11, the difference between the two sensors’ at-sensor temperature can be reduced to less than -0.5 K.

The spectrum of optical fiber surface plasmon resonance (SPR) shows the characteristics of wider full width at half-maximum (FWHM) and smaller peak value. The traditional peak detection algorithm cannot calculate the resonance wavelength of this kind of spectrum accurately. Therefore, efficient methods to calculate the resonance wavelength are required. This paper presents a method to process the SPR signal based on the Gaussian fitting. Combined with the trust region algorithm to determine the Gaussian fitting function, and then the resonance wavelength be calculated by line search method. Data processing of standard spectrum of glycerin with different concentration proves that this algorithm can adapt to optical fiber SPR spectrum characteristics, and calculate resonance wavelength accurately. The experiment measures the SPR signals of sucrose under different concentrations through the self-building SPR measure system. By using the proposed method, the weighted centroid method and the tracking centroid method to calculate the resonance wavelength, the result shows that the Gaussian fitting method can effectively improve resolution and have a short operation time which is conducive to engineering application.

The in situ biological process relays on a high performance attenuated total reflection (ATR) probe while ATR technique is a powerful tool for inline analysis. The basic principle and characteristic of the ATR technique was analyzed in this paper. A low cost and high throughout ATR probe was designed which can be inserted into the biological reactor directly with nondestructive and zero delay monitoring. It shows that the online ATR probe has a wide spectrum range, and the collected spectra has a high signal-to-noise ratio, which can be used in in-line quantitative analysis for biological process.

Effect of pulsed electric field on the drought resistance of crops is an important topic in biological effect of electric field. The changes in the photosynthetic system of leaf cells can be sensitively reflected by the kinetics parameters of delayed fluorescence. In order to reveal the effect of pulsed electric field and its mechanism on drought resistance of crop seedling, the germinating maize seeds were treated by pulsed electric field with electric field strength 200 kV·m-1, frequency 1Hz and pulse width 80ms. Then, PEG-6000 solution with -0.1 MPa osmotic potential to was used to form physiological drought of maize seedlings, the changes of dry leaf mass and the kinetics parameters, induced by LED were studied in this paper. The result showed that the dry leaf mass gradually increased under drought stress after applied with the electric field, which was significantly higher than that without external field, the relative growth rate was 45.6% (p<0.01). Besides, during the processes, the relative growth rate was between 5.8%～18.7%, the difference was significant (p<0.05) when there was no electric field, which indicated that the pulsed electric field promoted the leaf growth of maize seedling. The analysis of delayed fluorescence kinetic about leaf of maize seedling showed that the value of delayed fluorescence kinetics parameters, initial photon number I0, coherence time τ, decay factor β and integral intensity I(T), under drought stress, showed fluctuation, These changes were response to drought stress made by leaf cells. The study also found that pulsed electric field increased delayed fluorescence kinetics parameters and the integrated intensity of leaf cells, which indicated that the pulsed electric field could improve the photosynthesis potential and the organize sequence of photosynthetic electron transport system in leaf cells, as the interaction between functional molecules was strengthened, the leaf photosynthetic capacity was enhanced under drought stress. The result of this study provides a reference to explain clearly the effect of the pulsed electric field on drought resistance of plants seedlings.

Catalpa sawdust was respectively pretreated by NaOH, Ca(OH)2, H2SO4 and HCl solution, and the enzymatic hydrolysis of catalpa sawdust was significantly enhanced by alkaline pretreatments. In order to investigate the mechanisms of pretreatment of catalpa sawdust, the characteristics of catalpa sawdust before and after pretreatments were analyzed by scanning electron microscopy (SEM), X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy. It was found that the surface of catalpa sawdust was disrupted by four kinds of chemical pretreatment, and the pretreatment with Ca(OH)2 solution resulted in the most serious damage. The XRD results showed that part of amorphous regions was damaged by alkaline pretreatments, which led to a relative increase of crystallinity Index (CrI) of catalpa sawdust; while the CrI of catalpa sawdust was insignificantly influenced by acid pretreatments. The FTIR analysis displayed that the molecular structures of hemicellulose and lignin of catalpa sawdust were damaged in different degrees by four types of pretreatment. The significant improvement of enzymatic hydrolysis of catalpa sawdust after alkaline pretreatment might be attributed to the effective delignification of alkaline.

Remote sensing technique can be used to examine the effects of agrichemical application on the performance of field crops at a large scale in an effort to develop precision agricultural aerial spraying technology. In this study, an airplane M-18B at the 4-m flight height was used to spray a mix of agrichemicals (a fungicide and a plant growth regulator) to control rice leaf blast disease and improve the growth vigor of rice plants in the field. After the aerial spraying, satellite imagery of tested area was acquired and processed to calculate vegetation indices (VIs). Ground agrichemical concentration data were also collected. The relationships between droplets deposition and VIs were analyzed. The results indicated that the highest correlation coefficient between single phase spectral feature (NDVI) and droplets deposition points density (DDPD, points·cm-2) was 0.315 with P-value of 0.035 while the highest correlation coefficient between temporal change characteristic (MSAVI) and droplets deposition volume density (DDVD, μL·cm-2) was 0.312 with P-value of 0.038). Rice plants with the greatest growth vigor were all detected within the spraying swath, with a gradual decrease in the vigor of rice plants with the increase of droplets drift distance. There were similar trend patterns in the changes of the spraying effects based on the spatial interpolation maps of droplets deposition data and spectral characteristics. Therefore, vegetation indexes, NDVI and MSAVI calculated from satellite imagery can be used to determine the aerial spraying effects in the field on a large scale.

Due to the existence of the aerosol, the traditional method of measuring atmospheric temperature by using Rayleigh scattering technique has limitations in the low altitude. A pure rotational Raman lidar to get tropospheric temperature profiles is built. We carried out the atmospheric temperature observation in Beijing for two months. The atmospheric temperature profile was retrieved using the observed rotational Raman scattering signals. The effect of smooth window, calibration range and calibration constant on the retrieval precision of the atmospheric temperature was evaluated and analyzed. The results show that with the increase of smooth window, the mean absolute deviation between the lidar and radiosonde firstly decreases and then increases; in order to remove effectively the effect of random error in the return signals, while maintaining the fine vertical structure of temperature profile, it is better to choose the range between 600 and 1 200 m for smooth window. When calibration range is different, the mean absolute deviation between the lidar and radiosonde is varied, the relative variation of the deviation is about 0.07 K. When both calibration constant a and b increase or decrease, the mean deviation between the lidar and radiosonde increases; when one increases and another decreases, the mean deviation has a tendency to cancel each other out. The variance probability of a or b is not equal, and the variance of a and b is always contrary in the sign; the mean deviation is not sensitive to variance of a or b, and it is sensitive to the whole variance of a and b, about 91.7% of the mean deviation is in the range between -3 and 3 K. These results provide the theoretical basis for the selection of smooth window and calibration range in pure rotational Raman lidar data retrieval, and the reference for the error of actual temperature inversion result caused by lidar calibration constant.

In this work, we have mainly studied SERS spectra of fresh human urine by using Au nanoparticles excited by 785 and 1 030 nm lasers, respectively. And the UV/Vis adsorption experiment of the Au nanoparticles mixed with different ratio of urine has been performed, and the obvious shifting of corresponding absorption band is observed. The result showed that the Au nanoparticles which have been synthesized by classical Fren’s method can interact with urine, and the Au nanoparticles aggregations caused by the urine have strong SERS effect. Intense and repeatable spectra of the urine samples can be quickly obtained using Au colloids, which characterized by the scanning electron microscope (SEM) and the high-resolution transmission electron microscope (HRTEM) images, and it can be confirmed that the size of the Au nanoparticles is about 55 nm with a finite variation. When different spectra can be detected under different exciting lasers, the various biofluid to Au substrate ratios can generate different intense spectra. From the spectra of 785 nm laser, we can conclude that it has lower background and higher resolution with more detail information of this system contained human urine. For the 1 030 nm laser, a portable Raman instrument is helpful for on-site clinic treatment detection. It also gets well defined information and will be a good and convenient choice for urine analysis. It should note that this peak band located at 1 006 cm-1 may be the dominant nitrogen-containing component in urine. On the other hand, uric acid, urea, hypoxanthine as well as creatinine can be assigned; the other bands are still unknown, which might be attributed to biomarkers important for disease differentiation. Another result shows that different sample preparation can influence the SERS spectra with different ratio. We also have made a comparison of Raman spectra between 785 and 1 030 nm lasers to learn the difference between each other just like background and high-resolution. The current study indicates the SERS of urine might be a good choice and tool for urinalysis with potential diagnostic application, especially with the portable Raman instrument which would be an accurate and convenient approach for urine analysis. It is possible for SERS detection to be applied in not only the health diagnosis but also biological tissue in the future.

There is need to determination of uranium concentration at ppb level in environmental matrices. Due to low sensitivity of FAAS, UV-Visible Spectroscopy is generally used as measurement technique. In this study, ion-imprinted polymers (IIP) were prepared for uranyl ion (imprint ion) by formation of ternary (salicylaldoxime and 4-vinylpyridine) complex in 2-methoxy ethanol (porogen) following copolymerization with methacrylic acid (MAA) as a functional monomer and ethylene glycol dimethacrylate (EGDMA) as crosslinking monomer using 2,2-azobisisobutyronitrile as initiator. The synthesized polymers were characterized by FT-IR and TGA analysis. Arsenazo Ⅲ in 3 M HClO4 was used as complexing agent in the measurement step. The optimal pH for preconcentration was found to be between 3.5～6.5 values. The developed method was applied to uranium (Ⅵ) determination in natural water samples.

In this Study, Cadmium Oxide (CdO) nanostructures were synthesized by using Chemical Bath Deposition Technique. The synthesized process was carried out at room temperature. The structural and optical properties of nanostructures was characterized by XRD, SEM and UV-Vis techniques. As a result, the CdO nanostructures are oriented along (111) plane of cubic crystal structure. The morphology of CdO nanostructures showed interconnected prism-like and cauliflower-type cluster nanostructure. The UV results of this structures with high absorbtion coefficient are observed to be in accordance with the CdO nanoparticles.