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2019 Vol. 39, No. 09 Published: 2019-09-01

	2657	An Adaptive Hierarchical Savitzky-Golay Spectral Filtering Algorithm and Its Application
		LU Yi-bing^{1, 2}, LIU Wen-qing^{1, 2}, ZHANG Yu-jun^{1, 2*}, ZHANG Kai^{1, 2}, HE Ying^{1, 2}, YOU Kun^{1, 2}, LI Xiao-yi¹, LIU Guo-hua^{1, 2}, TANG Qi-xing^{1, 2}, FAN Bo-qiang^{1, 2}, YU Dong-qi^{1, 2}, LI Meng-qi^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2019)09-2657-07
		The tunable diode laser absorption spectroscopy (TDLAS) has the narrow linewidth characteristic of tunable diode lasers, so the gas concentration measurement of high precision and selectivity can be achieved by selecting the single absorption line of the specific gas to eliminate the interference of other gases, which has wide applications in the gas concentration detection. However, under different application conditions and environments, the people need to solve corresponding technical problems in hardware and data processing. In this paper, the TDLAS spectral data processing problem in the telemetry system for the vehicle exhaust CO concentration has been mainly studied. The system telemetered the exhaust CO concentration of the driving vehicle with the echo signals from the road diffuse reflection. Because the echo signal of laser scanning spectral is affected by factors such as the variation of the diffuse reflection surface, the change of the air environment, and the influence of exhaust turbulence, the signal collected by the detector is not only weak but also mixed with various noises, which means the SNR of the measured optical path is comparatively weak, so an adaptive hierarchical Savitzky-Golay (S-G) smoothing filter algorithm has been proposed in this paper, which can realize the spectral filtering processing to inversion the CO concentration more accurately. The S-G filtering algorithm has been widely used in spectral processing due to its advantages of such as simple principles, powerful functions and only two parameters setting (the window size and the fitting order). But how to set the parameters of the S-G algorithm correctly to balance the filtering effect between insufficient denoising and excessive filtering is a big problem for its application. In the designed detection system, the spectral signal of the measured optical path is non-stationary signal, and the amplitudes of the noises and effective signals are time-varying. So the optimal window size and polynomial order are changing with the signal dynamics of large range. As a result, it’s difficult to achieve the optimal filtering effect through S-G filters with fixed parameters. With the adaptive hierarchical S-G smoothing filter algorithm proposed in this paper, the sum of the signal correlation coefficient and the first derivative of the signal from measured light path spectrum signal after S-G filtering layer by layer and the reference section set by the spectrum signal of the reference light path have been compared, and then the optimal parameters of each layer can be obtained adaptively. With the analysis on 10 groups of band noise spectrum of which the signal to noise ratios(SNR) are from 9.81 to 29.77, the algorithm could effectively restore the concentration information carried by the band noise signals of the gas to be measured. Compared with the band noise spectrum, the maximum error of the absorption spectrum peak has dropped from 25.152% to 5.917%, and the maximum error of the integral absorbance has decreased from 18.1% to 3.9%. In the realized system, the adaptive algorithm has been used for the filtering processing of the measured optical path. The CO concentration emitted by motor vehicles of different models, displacement and oil product use has been monitored online in real time when they passed the system at idle and low speed(5 km·h^-1).
		2019 Vol. 39 (09): 2657-2663 [Abstract] ( 417 ) RICH HTML PDF (3882 KB) ( 169 )

	2664	Mapping for Horizontal Aerosol Density Field by a Portable Dual-FOV Lidar
		WANG Jie^{1, 2, 3}, LIU Wen-qing^{1, 2}, ZHANG Tian-shu^1*, WAN Xue-ping³, GAO Jie³, LI Ling³, MA Na³
		DOI: 10.3964/j.issn.1000-0593(2019)09-2664-06
		The three-dimensional (3D) distribution of aerosol was realized based on a home-made dual field of views (DFOV) Mie lidar system. The effective combination method of backscattering signals from the two telescopes was explored to retrieval the aerosol mapping. To implement the lidar mapping of the near-surface aerosol density distribution, a combination of the widely adopted and well-elaborated method of Fernald and the slope method was used. In this combination, the slope method was applied to determine the aerosol extinction and backscattering coefficients in appropriate parts of the lidar beam path. Subsequently, the values of backscattering coefficients of aerosol obtained here were used in retrieving the whole range profiles of extinction coefficients by means of forward- and backward-integrations in the Fernald solutions. As a result, the lidar range profiles of the aerosol extinction coefficients were retrieved with relatively high precision and reliability. In this manner, the advantages of these two approaches are synergistically combined with avoiding priori assumption of atmospheric condition and the reference point, respectively. Then an ideal quantity relationship between the particulate matter mass concentration (ρ(PM₁₀)) and aerosol extinction coefficients was given through a nonlinear fitting with ρ(PM₁₀) monitored by an air quality station (AQS) and the overhead extinction coefficient scanning by DFOV lidar. The fitting Pearson Coefficient was 0.91. The mass concentration density field of aerosol was mapped continuously and online through applying the fitting formula. This quantity study established a foundation for the city-cluster’s air pollution evaluation and the regional 3D air quality model assimilation.
		2019 Vol. 39 (09): 2664-2669 [Abstract] ( 195 ) RICH HTML PDF (3288 KB) ( 75 )

	2670	Study on Concentration Distribution Reconstruction Method of Pollution Gas Column
		HU Zhao-kun^1，2, LI Ang^1*, XIE Pin-hua^1，2，3, WU Feng-cheng¹, XU Jin¹, YANG Lei^1，2, HUANG Ye-yuan^1，2
		DOI: 10.3964/j.issn.1000-0593(2019)09-2670-07
		The comprehensive prevention and control of atmospheric pollution need to proceed from different scale areas. It is necessary to fully study the environmental characteristics of the area and conduct a comprehensive and systematic analysis of various factors that have an effect on the air quality. Obtaining the spatio-temporal distribution of atmospheric pollutant concentrations is important for understanding the characteristics of regional pollution way. Getting high spatial resolution of atmospheric pollutant concentration distribution is an important prerequisite for grasping the degree of regional pollution. From the atmospheric diffusion model, the column concentration of atmospheric pollutants around the emission source obeys the Gaussian distribution. In this paper, the spatial distribution of the vertical column concentration of the contaminated gas in the troposphere obtained by the mobile passive differential optical absorption spectroscopy (DOAS) is combined with the sequential Gaussian simulation method to reconstruct the spatial distribution of the pollutant column concentration and its error distribution in high spatial resolution. The typical blocks such as industrial parks (steel companies) and urban areas (Huairou, Beijing and Tongzhou, Beijing) were selected to conduct the navigation and observation to obtain the concentration of NO₂ and HCHO on the observation path respectively. Combined with the geographic information gridded on-board observation Data, the concentration distribution of NO₂ and HCHO columns in the observation area and the error distribution of the concentration of pollutant column were obtained by using sequential Gaussian simulation. The feasibility and reconstruction results of the simulation of column concentration distribution in the area with different emission characteristics were analyzed emphatically. The pollution sources in a steel enterprise, Huairou and Tongzhou area decreased in turn, and the structural complexity of distribution of gaseous pollutants decreased in turn. According to the results of semi-variance analysis, due to the large amount of NO₂ emission sources, the space dependence of pollutant column concentration is slightly weak in an iron and steel enterprise. The concentration of pollutant column in urban area shows a strong spatial correlation, and it shows as a whole that the more complex pollutant source in the area, the smaller the scope of the spatial correlation. Based on the three-dimensional monitoring data, the spatial distribution of the vertical column concentration and the error distribution of the pollutants in the hundred meters of the observation area were obtained. Based on the measured data and without dependency on the underlying surface data, source inventory data or population distribution data, the distribution of gaseous pollutants in key industrial areas or urban areas is improved by 2~3 orders of magnitude compared with the existing methods such as satellite remote sensing to obtain the vertical column concentration distribution of polluting gases. Meanwhile, through the column concentration error distribution, we quantitatively assessed the accuracy of simulation reconstruction. Based on the situation of air pollution in key areas with different emission characteristics, a new measurable measure of accuracy is provided. This method plays an important role in understanding regional pollution status, pollution control strategies and assessment of control effect.
		2019 Vol. 39 (09): 2670-2676 [Abstract] ( 164 ) RICH HTML PDF (3926 KB) ( 64 )

	2677	A Geological Application Oriented Comparison Research on Different Atmospheric Correction Methods for Airborne CASI-SASI Hyperspectral Data
		YE Fa-wang, WANG Jian-gang^*, QIU Jun-ting, ZHANG Chuan
		DOI: 10.3964/j.issn.1000-0593(2019)09-2677-09
		Alteration information extraction is one of the most important aspects of hypersepctral remote sensing application, and alteration mineral identification based on special absorption peaks is an important means of alteration information extraction. Due to the absorption and scattering of the atmosphere, atmospheric correction must be performed in order to obtain a more realistic reflection spectrum of the ground object. At present, comparison researches on atmospheric correction mainly focus on the improvement of image quality before and after atmospheric correction, the improvement of the classification effect of different features, and the correlation between the corrected image pixel spectrum and the actual spectrum. In contrast, the correspondence between absorption peaks of pixel spectrum obtained using different atmospheric correction and actual spectrum is rarely discussed, which is extremely unfavorable for geological application of hyperspectral remote sensing that is based on identification of mineral absorption peaks. In this study, the CASI-SASI aeronautical hyperspectral imaging system was used to collect the airborne hyperspectral data of the Longshoushan area of Gansu Province. Additionally, spectra of terrain objects were obtained using ground based ASD spectrometer. Based on these datasets, a geological application oriented comparison research on FLAASH, QUAC, and EMPL atmospheric correction methods was conducted. The results suggest that FLAASH, QUAC, and EMPL can eliminate the effects of the atmosphere and improve the image quality of aerial hyperspectral remote sensing, and EMPL shows the best effect. Besides, the absorption peaks of terrain objects’ reflection spectra and corresponded pixel reflection spectra obtained with different atmospheric correction were compared using visual interpretation. It is found that the absorption peaks of pixel spectra have different degrees of differences from those of the real terrain object spectra. Although EMPL has the best retention, some absorption peaks are still error corresponded, suggesting that multiple atmospheric correction methods should be used and a comprehensive research should be carried to improve the alteration extraction accuracy.
		2019 Vol. 39 (09): 2677-2685 [Abstract] ( 186 ) RICH HTML PDF (6785 KB) ( 75 )

	2686	Satellite Bands Based Estimation of Nitrogen Concentration in Potato Plants
		YANG Hai-bo^1,2, GAO Xing^1,2, HUANG Shao-fu^1,2, ZHANG Jia-kang^1,2, YANG Liu^1,2, LI Fei^1,2*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2686-07
		Plant nitrogen concentration (PNC) is one of the most important nutrient elements that directly affectscrop growth and yield. High-throughput ground-based remote sensing, passive or active re?ectance sensors, has the potential to provide more information for making better-informed management decisions for nitrogen fertilizer inputs at the canopy scale in real time but it is difficult to obtain data at the regional scale. For that multi-channel satellites with high spatial resolution (WorldView-2 and VENμS satellites with red edge bands) were tested in this study to estimating PNC on large scale at different growth stages of potato varieties. Experiments were conducted in 2014, 2015 and 2016 to remotely estimate the PNC of diverse potato varieties under different nitrogen levels in Wuchuan County of Northern Yin mountain, Inner Mongolia. The results showed that the combined spectral index NDRE/NDVI based on the red, red edge and near-infrared channels of the VENμS and WorldView-2 satellite is superior to other indices in estimating the PNC of potato varieties. The spectral index (NDRE/NDVI) of VENμS and WorldView-2 satellites had a high correlation with PNC at different growth stages, and the correlation coefficient ranged between 0.63 and 0.81. The spectral index (NDRE/NDVI) of VENμS had the highest correlation coefficient with PNC (r=0.81) at reproduction growth stage. The growth stages significantly affected the spectral index to estimate the PNC. The calibration models of spectral index (NDRE/NDVI) of two satellites based on the data of three years was validated to predict the PNC at reproduction growth stage. The predictive model of VENμS-NDRE/NDVI had the highest coefficient of determination (0.56), the lowest RMSE (0.38%) and RE (10.45%) with a slope of 0.82, as well as the predictive model of WorldView-2-NDRE/NDV had higher coefficient of determination (0.49), lower RMSE (0.41%) and RE (11.12%) with a slope of 0.78. In conclusion, the results of multi-channel satellite simulations showed that the combined spectral index based on the red edge width band can be used to monitor the PNC of potato varieties.
		2019 Vol. 39 (09): 2686-2692 [Abstract] ( 175 ) RICH HTML PDF (4259 KB) ( 87 )

	2693	Regression Prediction of Photometric Redshift Based on Particle Warm Optimization Neural Network Algorithm
		MU Yong-huan¹, QIU Bo^1, WEI Shi-ya¹, SONG Tao¹, ZHENG Zi-peng¹, GUO Ping^2
		DOI: 10.3964/j.issn.1000-0593(2019)09-2693-05
		In addition to the spectral redshift of galaxies, the prediction of galaxies redshift has important research significance for studying the large-scale structure and evolution of the universe. In this paper, we use the metering and spectral data of 150 000 galaxies of SDSS DR13 released by the Sloan Sky Survey project to analyze the galaxies according to the color characteristics and clustering methods. The classification results show that the early galaxies account for a large proportion. In this paper, three different machine learning algorithms are compared to measure the redshift regression prediction of early galaxies and find the optimal method. In the experiment, the photometric values of the galaxy samples u, g, r, i, z and the 10 color features obtained by the difference between the two bands are used as input data. First, the BP network is constructed, and the BP algorithm is used to measure the galaxies redshift. Then the Genetic Algorithm (GA) is used to optimize the parameters of the BP network, and the optimized GA-BP algorithm is applied to the regression prediction experiment of the early galaxies; considering the complex operation of the GA algorithm will affect the prediction efficiency. Moreover, the Particle Swarm Optimization algorithm not only has high stability and simple operation, so the Particle Swarm Optimization algorithm is used to optimize the BP network (PSO-BP) and Particle Swarm Optimization is used to optimize BP network (PSO-BP). By adjusting the weight method to improve the prediction efficiency and increase the stability, the particle swarm optimization algorithm is used to predict the redshift of the early galaxies in the galaxy samples. In the experiment, the spectral redshift is taken as the expected value, and the mean square error (MSE) is used as the error analysis index to judge the accuracy of the three algorithms. The PSO-BP regression prediction results are compared with the BP network model and the GA-BP network model. The experimental results show that the MSE value of the BP network is 0.001 92, the MSE value of the GA-BP network is 0.001 728, and the MSE value of the PSO-BP network is 0.001 708. The experimental results show that the PSO-BP optimization model used in this paper is superior to the BP neural network model and the GA-BP neural network model in terms of accuracy, which is respectively improved by 11.1% and 1.2%. It is superior to the traditional K-nearest neighbor test in efficiency, which overcomes the shortcomings of traversing all data samples in KNN algorithm and its generalization performance is better than that of other BP network optimization models.
		2019 Vol. 39 (09): 2693-2697 [Abstract] ( 217 ) RICH HTML PDF (1735 KB) ( 73 )

	2698	The IR Radiation Characteristics of Nanosecond Pulsed Laser Induced Air Plasma
		WANG Xing-sheng, YUAN Li-xin, LI Xin, WANG Ming, GAO Xun^, LIN Jing-quan^
		DOI: 10.3964/j.issn.1000-0593(2019)09-2698-04
		Nanosecond laser-induced air plasma has a wide spectrum of radiation from ultraviolet, visible, near-infrared, and even radio frequency microwaves, but most people are currently concerned about spectral radiation from the ultraviolet to visible wavelength range. Laser plasma has many advantages as a new type of infrared radiation source. Compared with infrared bombs and infrared interference means, air plasma infrared radiation sources can be flexibly arranged and have low cost. Therefore, the study of the infrared radiation characteristics of air plasma is necessary. In view of the current research on the infrared interference of pulsed laser-induced air plasma, the infrared radiation characteristics of nanosecond pulsed laser-induced air plasma with a laser wavelength of 532 nm are experimentally studied. The influences of laser energy on the infrared radiation intensity of the air plasma are discussed, the angle distribution characteristics of the infrared radiation are presented, the possible mechanisms of plasma infrared radiation are analyzed. The experimental results show that the infrared spectrum of the laser-induced air plasma in the range of 950～1 700 nm is a superposition of the line spectrum and the continuous spectrum. The main spectrum is the neutral atomic lines of nitrogen and oxygen, and the infrared radiation of nitrogen atom dominates at the whole radiation. As the laser pulse energy increases, which induces the amount of oxygen and nitrogen atoms increasing produced by the air breakdown, the intensity of the infrared spectrum of the air plasma gradually increases. With the change of infrared radiation detection angle, the spectral intensity of OⅠ 1 128.63 nm and NⅠ 1 246.96 nm and 1 362.42 nm reaches the maximum at the detection angle of 75 degrees. When the detection angle is 120 degrees, the spectral intensity of NⅠ 1 011.46 nm and 1 053.96 nm reaches peak. The biggest reason is that the intensity of infrared radiation in the air plasma shows a spatial asymmetry with the change of the detection angle, indicating that the spatial distribution of different particles in the air plasma is asymmetric.
		2019 Vol. 39 (09): 2698-2701 [Abstract] ( 165 ) RICH HTML PDF (2050 KB) ( 64 )

	2702	Modulation Characteristics of Laser Based on Wavelength Modulation Technology
		ZHANG Bu-qiang^{1, 2}, XU Zhen-yu¹, LIU Jian-guo¹, XIA Hui-hui¹, FAN Xue-li¹, NIE Wei^{1, 2}, YUAN Feng^{1, 2}, KAN Rui-feng¹
		DOI: 10.3964/j.issn.1000-0593(2019)09-2702-06
		Tunable Diode Laser Absorption Spectroscopy (TDLAS) has become one of the main diagnostic techniques in flow field diagnostics，and it can be used for non-intrusive and in-situ detection. Wavelength modulation spectroscopy (WMS) and direct absorption (DA) are the two main methods for TDLAS sensing, the WMS method is advantageous for applications with small absorbance, high pressure or hostile flow field, and detection sensitivity is 1～2 orders of magnitude higher than direct absorption. In the field of near-infrared wavelength modulation technology, distributed feedback (DFB) semiconductor lasers have become one of the choices for flow field diagnosis, and whether using fitting of harmonic signals (or normalized harmonic signals) or selecting peaks of harmonic signals to invert flow field parameters, the accurate establishment of the absorption model is very important. The precise representation of the laser frequency-time response and intensity-time response is especially important when modeling, In order to solve the problem of establishing the accurate absorption model, this paper presents a complete method for accurately measuring the modulation parameters of lasers. The modulation characteristics of the 1 392 and 1 469 nm lasers used to detect water vapor absorption are measured. The modulation parameters of the distributed feedback laser with modulation amplitude, modulation frequency and operating temperature are studied. According to the modulation parameters obtained by the method, the absorption model was established. The concentration of water vapor in the air was 1.97% at room temperature, and the concentration measured by the direct absorption method was 1.99%. The accuracy of the measurement method of the modulation parameters was verified. The research shows that the modulation depth increases linearly with the increase of the modulation amplitude, decreases monotonously with the increase of the modulation frequency, and increases linearly with the increase of the operating temperature. The intensity and frequency of the laser are modulated simultaneously. Phase difference between the intensity and the frequency is not obvious with the change of modulation amplitude. It increases with the increase of the modulation frequency and decreases with the increase of the operating temperature. The normalized first and second harmonic amplitude increase with the increase of the modulation amplitude, decrease with the increase of the modulation frequency, and are not significant differences with the change of the operating temperature. In the field of absorption spectroscopy, wavelength modulation spectroscopy play an important role, the modulation index is closely related to the peak value of the harmonic signal. When applying the wavelength modulation technique, selecting the appropriate modulation parameters is beneficial to obtain a suitable harmonic signal. The optimal modulation index can be obtained by changing the modulation amplitude, modulation frequency and operating temperature. In this paper, the modulation characteristics of near-infrared distributed feedback semiconductor lasers are studied. The method is also applicable to other types of lasers, which is beneficial to the application of absorption spectroscopy in various fields.
		2019 Vol. 39 (09): 2702-2707 [Abstract] ( 239 ) RICH HTML PDF (3798 KB) ( 120 )

	2708	Study on the Large-Scale Distance Measurement Method for Femtosecond Laser Based on Frequency Scanning and Optical Sampling
		ZHANG Tian-yu, QU Xing-hua, ZHANG Fu-min^*, PENG Bo
		DOI: 10.3964/j.issn.1000-0593(2019)09-2708-05
		As a high-precision measurement tool, femtosecond laser is superior to traditional laser technology and has been widely used in industrial production, aerospace, scientific research and other fields. The method of frequency sweeping and optical sampling has greatly improved mechanical vibration and slow scanning speed, which has great significance for improving the absolute ranging performance of femtosecond laser. A large-scale distance measurement method using femtosecond laser is proposed based on the principle of frequency sweeping and optical sampling, and research is performed on the measurement principle, interference spectrums and demodulation algorithm of this technology. Firstly, according to the generation principle of mode-locked femtosecond laser and the piezoelectric effect of piezoelectric ceramics, the method of continuous scanning repetition frequency of femtosecond laser was introduced. On this basis, the traditional optical sampling principle was used to explain the range measurement principle of optical sampling method, and the influence of the fiber delay line length on the scanning range was deduced and discussed. Then, a distance measurement system using femtosecond laser was set up, long distance measurement experiments were carried out on a linear guide, and the He-Ne reference light path based on Michelson interference principle was designed. The group refractive index of air was modified according to the experimental environment, the influence of measured distance on the spectrum of interference fringes was analyzed, and the scanning ranges at different target positions were measured. In the range of 50.4 m, the scanning range increased from 0.56 to 1.12 mm, and it fully proved the importance of fiber delay line for improving large-scale ranging capabilities. Periodic scanning frequency could generate cross-correlation fringes, the real time frequency variations and sampling multiplication factors were calculated by performing Hilbert transform processing on the interference spectrums, and the distance information was obtained. In addition, in order to reduce the time delay error of the system and improve the accuracy of the measurement, the difference principle was used to improve the algorithm. The experimental results show that, by contrast, the improved algorithm based on distance difference is used to process dataand the performance results are better. After the algorithm is improved, the measurement accuracy of the system is improved from 11 to 4 μm in the range of 50 m, and the relative accuracy is improved from 2.2×10^-9 to 8×10^-8, which indicates that the accuracy is significantly improved. The repeatability measurement data is analyzed and compared with the results of incremental laser interferometers, the standard deviation of measurement error is improved from 10 to 2 μm, and the maximum relative stability is improved from 2×10^-9 to 4×10^-8, which indicates that the stability is significantly improved. Therefore, the method has excellent capability of large-scale distance measurement, the potential of achieving high-accuracy, large-scale and fast absolute range measurement simultaneously, and great prospects in the field of precision spectrum measurement in the future.
		2019 Vol. 39 (09): 2708-2712 [Abstract] ( 172 ) RICH HTML PDF (2914 KB) ( 54 )

	2713	Study on the Effect of He-N₂ Ratio in Mixed Carrier Gas on Separation of VOC Aliasing Peaks in FAIMS
		SHI Hai-xia¹, XU Qing^{1, 2}, WANG Han^{2, 3}, LIU You-jiang², LI Shan², HU Jun^{2, 3}, LI Yue^{1, 2}, CHEN Chi-lai^2
		DOI: 10.3964/j.issn.1000-0593(2019)09-2713-06
		Carrier gas mixing as one of the most important methods to improve the separation ability of high Field Asymmetric waveform Ion Mobility Spectrometry (FAIMS) has been widely used in the field of bio macromolecule mass spectrometry, while there is a lack of some research in environmental small molecules. In this paper, five typical volatile organic compounds (VOCs), including o-xylene, isobutanol, n-hexane, acetic acid and acetone, were chosen to study the effect of N₂-He mixing ratio on the peak position, resolution and ion pass rate of monomers and dimer ion. The results showed that with the increase of the proportion of He in the carrier gas of FAIMS, the peak position of the monomer and dimer ion in five VOCs shifts, and the peak of the monomer and the dimer were different, and the monomer peak shift increased first and then decreased, while the dimer peak position shift increased gradually. With the increase of the percentage of He, the resolution of FAIMS for aliasing peaks of five VOCs gradually increased and tended to saturate at last, where the saturated helium ratio was: 20%, 30%, 10%, 40% and 20%, respectively. In addition, with the increase of the percentage of helium, the signal intensity of o-xylene, isobutanol, n-hexane and acetone had no obvious change, while that of acetic acid decreased significantly. This study provided a feasible method for improving the separation ability of FAIMS and validating the effectiveness of Blanc’s law under high electric field applied in the field of small molecules.
		2019 Vol. 39 (09): 2713-2718 [Abstract] ( 209 ) RICH HTML PDF (3139 KB) ( 46 )

	2719	Classification of Terahertz Rosewood Based on Continuous Projection Algorithm and Random Forest
		WANG Yuan^{1, 2}, SHE Shuai^{1, 2}, ZHOU Nan³, JIA Pei-xing^1,2, ZHANG Jun-guo^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2019)09-2719-06
		This paper proposes a method to classify and recognize redwood using Terahertz time-domain spectroscopy (THz-TDS). Redwood is expensive and difficult to identify which leads to a shoddy market. The phenomenon disrupts the market order and causes huge economic losses to producers and consumers. The traditional methods of identifying redwood are difficult to give consideration to both accuracy and rapidity, therefore it is necessary to put forward a new method to supplement the traditional classification methods. Compared with the traditional methods, terahertz wave has good penetrability and fingerprint characteristics for redwood, and has great application potential in classification and identification of redwood. In this paper, five kinds of redwood (Dalbergia bariensis, Dalbergia oliveri, Bois de rose, Pterocarpus santalinus, Dalbergia cochinchinensis) are selected as test samples. The THz-TDS system is used to obtain the terahertz time-domain spectrum of wood; the terahertz frequency domain spectrum is obtained by fast Fourier transform of the terahertz time-domain spectrum of five woods, the optical parameters of the terahertz time-domain spectrum are extracted. The results show that different types of wood have time delay line and amplitude difference in time domain spectrum, the attenuation trend and amplitude are different in frequency domain spectrum, the bands of various types of redwood absorption peaks appear differently in the absorption coefficient spectrum, which all can show the differences between various types of wood, indicating that THz-TDS has feasibility for classification of redwood. The successive projections algorithm (SPA) is used to extract the characteristic frequency of the absorption coefficient spectrum and the refractive index spectrum. 28 characteristic frequency points are selected from the 260 frequency points of the absorption coefficient spectrum and the frequency band accounts for 10.77%; 12 characteristic frequency points are selected from 260 frequencies of the refractive index spectrum, and the frequency band accounts for 4.62%. A random forest classification model and a support vector classification model based on the absorption coefficient spectrum and the refractive index spectrum are established and compared. The results show that THz-TDS has great quality to recognize wood. A random forest classification model based on absorption coefficient spectrum and refractive index spectrum shows good classification performance for redwood species and the accuracy rate of classification is 94% and 96% which can show that they can classify and identify redwood species correctly. THz-TDS technique is used to classify and identify mahogany, which provides a new idea and technical scheme for the classification and identification of mahogany therefore it can be used as a supplement to the near-infrared spectrum wood detection method. This method also provides a theoretical basis to apply terahertz technology in the field of wood classification and identification.
		2019 Vol. 39 (09): 2719-2724 [Abstract] ( 235 ) RICH HTML PDF (1925 KB) ( 67 )

	2725	Application of Zernike Moment in Terahertz Spectrum Quantitative Analysis of Rubber Additives
		YIN Xian-hua^{1, 2}, GUO Chao^{1, 2}, LI An³, MO Wei^1*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2725-07
		In recent years, the development of “green tire” has attracted much attention. Many kinds of rubber additives are needed in the manufacturing process of green tires, and the content of rubber additives is closely related to whether green tires can meet the standards. Therefore, it is important to quantitatively detect the rubber additives in tire rubber. THz-TDS technology has been successfully applied in the field of quantitative analysis of substances. However, when the quantitative analysis object is a multi-component mixture, the results of quantitative analysis will not be satisfactory due to the overlap and distortion of the mixture spectrum. In order to solve this problem, Zernike moment is introduced as a spectral pretreatment technology into terahertz spectral quantitative analysis of multi-component mixtures of rubber additives. A quantitative analysis method of terahertz spectrum based on Zernike moment and support vector regression (ZM-SVR) is proposed. Firstly, three rubber additives, zinc oxide, silica and 2-Mercaptobenzothiazole (MBT), which affect the quality of green tires, were used as quantitative detection objects. Three rubber additives and nitrile-butadiene rubber were prepared as multi-mixture experimental samples, and the terahertz spectra of samples were measured by terahertz time-domain spectroscopy system. Then, terahertz spectroscopy was analyzed and processed. After obtaining the three optical parameters of absorption coefficient, extinction coefficient and refractive index, the three optical parameters were constructed into the THz three-dimensional spectrum of the sample, and the characteristic information of the THz three-dimensional spectral gray-scale image was extracted by Zernike moment. Finally, the quantitative model between the characteristic information of the THz three-dimensional spectral gray-scale image of the sample and the content of the target component was established by using support vector regression. The target component content in the mixture sample was analyzed. The correlation coefficients of the forecasting set of the quantitative model obtained by this method were greater than or equal to 0.952 2, and the root mean square error was less than or equal to 2.267 2%. To further verify the validity of this method, the results of quantitative analysis were compared with those of PLS and SVR. Compared with the quantitative analysis results obtained by conventional methods, the accuracy and stability of the results obtained by Zernike moment combined with support vector regression method have been significantly improved. Therefore, Zernike moment combined with support vector regression provides a new method for terahertz spectroscopy quantitative detection of multi-component mixture of rubber additives, and has broad application prospects in the field of quality detection of green tires and rubber.
		2019 Vol. 39 (09): 2725-2731 [Abstract] ( 184 ) RICH HTML PDF (4844 KB) ( 43 )

	2732	*Estimation of Leaf Loss Rate in Larch Infested with Erannis Jacobsoni* Djak Based on Differential Spectral Continuous Wavelet Coefficient**
		HUANG Xiao-jun^{1, 2, 3, 4}, XIE Yao-wen^1*, BAO Yu-hai^{2, 3}, BAO Gang^{2, 3}, QING Song^{2, 3}, BAO Yu-long^{2, 3, 4}
		DOI: 10.3964/j.issn.1000-0593(2019)09-2732-07
		Defoliation caused by insect pests severely threatens the health and safety of forests; the rapid and accurate acquisition of information regarding leaf loss is of considerable significance to the remote sensing monitoring and estimation of forest pests. Based on this, we conducted spectral measurements of infested trees and tested leaf loss rate estimation owing to larch defoliation caused by Erannis jacobsoni Djak in Mongolia. Differential spectral reflectance (DSR, first derivative of spectral reflectance) and continuous wavelet coefficient of differential spectral reflectance (DSR-CWC, continuous wavelet transform of DSR carried out using 36 mother wavelet basis functions of four wavelet families: biorthogonal, coiflets, daubechies and symlets) were obtained based on the processing of spectral measurement data. The sensitivity of DSR and DSR-CWC with respect to the estimation of leaf loss rate was analyzed, following which the sensitive bands of DSR and DSR-CWC were automatically identified using the Findpeaks (Fp) function of MATLAB and the sensitive features identified. Dimension reduction of the sensitive features was processed using a successive projections algorithm (SPA). Partial least squares regression (PLSR) and support vector machine regression (SVMR) models for estimating leaf loss rate were established based on these sensitive features and their effectiveness was compared with that of stepwise multiple linear regression (SMLR) models. The results showed that: ①DSR-CWC was determined to be more sensitive than DSR to changes in leaf loss rate in infested larch, with more sensitive bands, mainly distributed in three absorption valleys (440～515, 630～760 and 1 420～1 470 nm) and three reflection peaks (516～620, 761～1 000 and 1 548～1 610 nm). This finding reflects the fact that DSR-CWC can enhance spectral reflection and absorption characteristics. ②The use of the combination pattern of Fp and SPA (Fp-SPA) was an effective method for the selection of sensitive spectral features that could not only select these features quickly and objectively but also effectively reduce dimensions. ③The optimal mother wavelet bases for the four wavelet families respectivelywere bior2.4, coif2, db1, and sym6; db1 had the most stable performance and accuracy for leaf loss rate estimation. ④The continuous wavelet transform of DSR could improve the accuracy of leaf loss estimation; db1-PLSR (R²_M=0.934 0, RMSE_M=0.089 0) exhibited the most obvious improvement, achieving an R²_M that was 0.047 5 higher than that of DSR-PLSR and an RMSE_M that was 0.024 9 lower than that of DSR-PLSR. ⑤The estimation accuracy of the PLSR and SVMR modelsestablished based on DSR-CWC was either similar to or better than that of the SMLR models. DSR-CWC thus estimated leaf loss rate more effectively than DSR did. It can be seen that DSR-CWC has more potential than DSR in estimating leaf loss rate, and it can provide important reference for remote sensing monitoring of forest pests.
		2019 Vol. 39 (09): 2732-2738 [Abstract] ( 189 ) RICH HTML PDF (4676 KB) ( 66 )

	2739	Comparison of Sun-Induced Chlorophyll Fluorescence and Reflectance Data on Estimating Severity of Wheat Stripe Rust
		ZHAO Ye^1，3, JING Xia^1*, HUANG Wen-jiang², DONG Ying-ying², LI Cun-jun³
		DOI: 10.3964/j.issn.1000-0593(2019)09-2739-07
		Stripe rust of wheat is one of the hazardous diseases which affects the wheat yield in China. It is more significant to early detect wheat stripe rust infection information for the prevention of wheat stripe rust and the improvement of yield and quality. Considering that reflectance spectra are sensitive to variations in the concentration of plant biochemical components, and the sun-induced chlorophyll fluorescence is sensitive to variations in plant photosynthetic physiology. In order to preferably detect the severity of wheat stripe rust disease by remote sensing, especially the earlier detection of wheat stripe rust disease, this study made a comparative analysis of the sensitivity of sun-induced chlorophyll fluorescence and reflectance spectrum data to monitor the severity of wheat stripe rust disease. First used the ASD Field Spec Pro NIR spectrometer to determine the wheat canopy spectral data of different illness severity, on the basis of the principle of fraunhofer line to extracted sun-induced chlorophyll fluorescence data by the method of 3FLD under different illness severity, then respectively induced by reflectance spectra data and sun-induced chlorophyll fluorescence data to construct at different conditions of wheat stripe rust of remote sensing detection model, and through the retained sample cross terms of inspection on the forecast model accuracy is evaluated. The result shows that: (1) when the severity of wheat stripe rust disease was less than 20%, the sun-induced chlorophyll fluorescence response of wheat stripe rust disease information was more sensitive than reflectance spectra data, and the sun-induced chlorophyll fluorescence as the independent variable to build the forecasting model of wheat stripe rust disease severity reached the extremely significant level. It can earlier diagnose the crop diseases by detecting the stress state of plants before the change of chlorophyll content or leaf area index, while it is hard to use the reflectivity spectrum data to detect wheat stripe rust damage information. (2) when the severity of wheat stripe rust disease is in the state of moderate incidence (20%45%), the prediction model of severity of wheat stripe rust disease constructed by using reflectance spectral data and sun-induced chlorophyll fluorescence data has reached the extremely significant level, both of which can preferably detect the severity of wheat stripe rust by remote sensing. The results of this study have great significance for improving the remote sensing detection accuracy of wheat stripe rust, and it provides reference basis for the earlier detection of stripe rust in wheat by using TanSat or other satellite fluorescence data.
		2019 Vol. 39 (09): 2739-2745 [Abstract] ( 249 ) RICH HTML PDF (1969 KB) ( 122 )

	2746	Preliminary Study on Origin Identification of White-Light Gray Gaoshan Stone and Changhua Stone
		CHEN Tao, CHEN Meng-yao, DENG Yu-qing
		DOI: 10.3964/j.issn.1000-0593(2019)09-2746-05
		China has a long history enjoying in the Seal Stones. Both Shoushan Stone and Changhua Stone are famous Seal Stones in China. But their prices are different. Gaoshan Stone is a main variety of Shoushan Stones, which has high market share. In order to preliminarily study the origin identification of Seal Stone, this paper chooses white-light gray Gaoshan Stone and Changhua Stone as study objects that can avoid disturbance of color minerals and color elements to the identification of origin. Infrared spectrum (FTIR), Raman spectrum (LRM) and laser ablation-plasma mass spectrum (LA-ICP-MS) were used to study mineral compositions and trace chemical compositions of white-light gray Gaoshan Stone and Changhua Stone. Combined with physical properties of them, differences and identification methods have been discussed in the two origins. The color of white-light gray Gaoshan Stone is more uniform than that of Changhua Stone. The transparency of Gaoshan Stone is better. They have similar density and refractive index. According to the absorbance peaks of IR in the fingerprint area, the main mineral compositions of white-light gray Gaoshan Stone and Changhua Stone are kaolin-group minerals. Because the different occupied site of hydroxyl in kaolin-group minerals, the forms and amounts of absorbance peaks of stretching vibration of hydroxyl are different. According to the results of the forms and amounts of absorbance peaks of functional area in IR spectrum, the main mineral composition of Gaoshan Stone is ordered dickite, but Changhua Stone has disordered dickite. However, both of them can contain a minor amount of kaolinite. Raman spectrum was used to study impurity minerals on the site of pricker- and soft-spot areas. It is found that Gaoshan Stone has simple impurity minerals. The dark pricker-spot is pyrite, and the soft-spot is quartz. However, Changhua stone has relative complex impurity minerals, such as hematite, rutile, anatase, quartz and barite. Comparing the LA-ICP-MS data of dickite, we found that Gaoshan Stone contains relative high Ge element, while Changhua Stone contains relative higher V and Zn. According to the value of Ge/Zn, which is larger than 0.2 for Gaoshan Stone, but is smaller than 0.2 for Changhua Stone. And according to the value of Ge/V, which is smaller than 0.1 for most of Changhua stone, but which is between 0~1.0 for Gaoshan Stone. The distributions of splashes of Ge/V-Ge/Zn values of the two origins are different. The distinction degree can be larger than 90%. Color, density and refractive index are similar for white-light gray Gaoshan Stone and Changhua Stone. It is difficult to distinguish them only by the appearance characters and physical properties. However, their varieties and contents are different. The test and analysis can be used to identify their origins. On the other hand, they are different in the amount of trace elements, which also can be used to identify the origin by Ge/V-Ge/Zn scatter diagram.
		2019 Vol. 39 (09): 2746-2750 [Abstract] ( 190 ) RICH HTML PDF (1867 KB) ( 76 )

	2751	Progress of Measurement of Infrared Absorption Spectroscopy Based on QCL
		ZHANG Huai-lin, WU Tao^*, HE Xing-dao
		DOI: 10.3964/j.issn.1000-0593(2019)09-2751-07
		As a new type of unipolar semiconductor laser, the quantum cascade laser (QCL) has a peak emission wavelength in the mid-infrared band (2.5~25 μm), and has the unique advantages that traditional semiconductor lasers do not have, such as high power, narrow linewidth and fast response rate. The infrared absorption spectroscopy of QCLs has high detection sensitivity and is very suitable for the detection of gas molecules with the characteristic spectrum in the mid-infrared band and can be widely used in the detection of low-concentration gas such as trace gas, respiratory gas, combustion gas, biochemical gas, automobile exhaust, industrial waste gas and pesticide residue gas. Therefore, the use of QCL to detect gas molecules is of great significance in non-invasive medical diagnosis, environmental monitoring, and industrial and agricultural production. Since the invention of QCL at the end of 20th century, the performance of room temperature laser has been greatly improved, and a variety of QCLs have appeared, which also makes the infrared absorption spectroscopy of QCLs greatly developed. In fact, many laser spectroscopies have been developed and applied before the invention of QCL. These include direct absorption spectroscopy (DAS), wavelength modulation spectroscopy (WMS), cavity ring-down spectroscopy (CRDS), cavity enhanced absorption spectroscopy (CEAS) and photoacoustic spectroscopy (PAS) and other related technologies. While the use of QCL as the light source extends the detectable band to a large extent, and also increases the detection limit to some extent. This paper reviews the research status and development trends of infrared absorption spectroscopy of QCLs at home and abroad, and analyzes the bottlenecks encountered in the development process and the solutions obtained in the later stage. The principle and application of various methods are introduced in detail, and the advantages and disadvantages in the measurement are pointed out. At the same time, the field trace gas detection is briefly summarized. Finally, the application and development of infrared absorption spectroscopy of QCLs in the detection of trace gases in the future are prospected. It is pointed out that with the rapid development of infrared absorption spectroscopy, these methods can be more effectively improved and developed with high sensitivity, high integration and high timeliness.
		2019 Vol. 39 (09): 2751-2757 [Abstract] ( 232 ) RICH HTML PDF (2050 KB) ( 100 )

	2758	*Study on Microfibrils Orientation in Daemonorops jenkinsiana* Cell Wall by Polarized Laser Raman Spectroscopy**
		FENG Long, JIN Ke-xia, LIU Xing-e, TIAN Gen-lin, YANG Shu-min, JIANG Ze-hui, MA Jian-feng^*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2758-05
		The variation in the microfibrils orientation of the Daemonorops jenkinsiana multilayered fiber and vessel was in-situ studied by polarized laser Raman spectroscopy with 532 nm exciting laser and a high-NA objective lens (1.25). Raman imaging obtained by integrating over the band range from 2 771 to 3 000 cm^-1 displayed the morphologically distinct cell wall regions, including cell corner middle lamella, compound middle lamella and secondary wall. Furthermore, the fiber secondary wall displayed a concentric structure with alternating broad and narrow layers, while vessels had no obvious layering structure. Higher Raman C—O—C band (1 097 cm^-1) intensity was visualized within the narrow layer of fiber wall from polarized laser Raman images, indicating the microfibrilsin these regions were more parallel to the incident laser electric vector and more perpendicular to the cell axis. The microfibrils orientation in vessel was uniform with in its secondary wall. Raman spectral analysis of different morphological areas of cell wall evidenced the band intensities of the C—O—C, CH and CH₂ modes had a significant correlation with the polarization direction of incident light. When the orientation of cellulose microfibrils changed from parallel in respect to the fiber axis to with a high angle, the C—O—C signal reduced obviously. By comparison, the signal of CH and CH₂ displayed slight decrease when changing the direction of incident laser, indicating the more sensitive nature of C—O—C vibration modes to polarization direction of incident light. Comparing the Raman spectra extracted from the narrow (Nl-R), broad layer (Bl-R) of fiber radial wall, as well as narrow (Nl-T), broad layer (Bl-T) of fiber tangential wall, it was found that the Nl-R had higher 1 097 cm^-1 band intensity, while Bl-T displayed higher 2 897 cm^-1 band intensity. Raman band ratio (I_{1 095}/I_{2 897}) can be used to predict microfibrils angle (MFA) in different cell wall types, qualitatively. The results showed that the ratio was highest in vessel secondary wall (1.32~1.10), followed by narrow layer of fiber secondary wall (0.92~0.55), and lowest in the broad layer of fiber secondary wall (0.42~0.33), indicating the highest MFA in the vessel secondary wall. This study provided a novel method and important theoretical guidance for the investigation on cell wall architecture, chemical composition distribution and micromechanics.
		2019 Vol. 39 (09): 2758-2762 [Abstract] ( 171 ) RICH HTML PDF (3560 KB) ( 60 )

	2763	Blind Separation of Multi-Voltage Projection Sequence Based on Fundamental Effect Decomposition
		ZHAO Yao-xia, HAN Yan, CHEN Ping^*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2763-06
		In X-ray CT imaging system, the polychromatic X-ray results in beam hardening artifacts，which influence the material composition distinction. It can’t realize quantitative characterization. The multi-spectrum CT can reach the higher correspondence between the composition and image gray by narrow-energy-width or monoenergetic CT. Compared with traditional CT, spectral CT can distinguish the different component. The implement method based on the photon counting detector is limited in temporal resolution and spatial resolution. The implement method based on filter doesn’t have enough discrimination. And the implement method based on blind separation of multi-voltage projection sequences has better practicability. It guarantees the correspondence between the materials and the gray of reconstructed image. However, the attenuation coefficients are unknown and energy spectrum division is uncertain, the analytic energy value of reconstructed images is ambiguous. The error between the analytic energy and referenced energy is higher. Then it will influence the precision of the multi-component quantitative analysis. For this problem, an improved method is proposed. It utilizes the attenuation coefficient decomposition of compton effect and photoelectric effect as an energy constraint to eliminate the uncertainty energy partition. The error between the energy value of reconstructed images with decomposed projection and the reference energy value is reduced. In the decomposition model, the optimum object function is local variance sum of residual error minimum. The attenuation coefficient is decomposed as energy dependency term and material dependency term according to compton effect and photoelectric effect. The energy dependency term can be known in advance. It can be as energy constraint and used to fix the energy value of narrow-energy-width. Then the energy of decomposed projection is known and the energy of corresponding reconstructed images also is known. A cylinder composed of aluminum and silicon is used in the verification experiment since aluminium and silicon have approximate attenuation coefficients. The error between the attenuation coefficients of reconstructed images with the energy constraint is less than the result of reconstructed images without the energy constraint. The contrast tendency of silicon and aluminium with energy is close to the theoretical value. Also the difference with reference energy is reduced. The result shows that the proposed method solves the energy directivity problem of multi-spectrum CT based on the blind separation of multi-voltage projection sequences. The energy spectrum resolution ratio is higher. The composition representation is more accurate.
		2019 Vol. 39 (09): 2763-2768 [Abstract] ( 157 ) RICH HTML PDF (3915 KB) ( 57 )

	2769	A New Label-Free Fluorometric Assay for ATP Based on Split Aptamer
		LI Fei-fei^1,3, LU Yi-song², YANG Sheng-yuan^1,3*, LIN Xi^1,3, CHEN Wei¹, LIU Can^1,3, XIAO Fu-bing^1,3, LIANG Hao^1,3
		DOI: 10.3964/j.issn.1000-0593(2019)09-2769-05
		A novel Label-Free Fluorometric Assay based on the recombination of split aptamer chip was developed for thedetection of adenosine triphosphate (ATP). In this strategy, the split aptamer was selected as a specific capture probe for the split two fragments aptamers could specifically form a ternary assembly in the presence of ligand and the two separate oligonucleotides lack secondary structures, thus not yielding false-positive or nonspecific signals, while the Thiazole orange(TO), an almost non-fluorescence dye in buffer solution, was used as signal probe, and the single-walled carbon nanotubes (SWCNTs) was applied to reduce the background signals. In the pH 8.0 Tris-HCl buffer solution, those two split aptamer fragments will be combined with each other to form a stable “aptamer-ATP-aptamer” composite structure upon interacting with its target ATP. The “sandwich” structure can’t wrap the sidewalls of the SWCNTs and is freed in solution, and TO shows agreat fluorescence enhancement when binding to the “aptamer-ATP-aptamer” composite structure. In the absence of ATP, the split aptamers, existing in a single-stranded state, bind to the surface of the SWCNTs via a π—π-conjugate interaction, and TO shows weak fluorescence because “sandwich”structure is not formed. In the system, the higher the ATP concentration is, the more the “aptamer-ATP-aptamer” sandwich recognition structure complex obtained, sois the fluorescence. Under the optimized experimental conditions, the ATP concentration in the range from 9.0×10^-9 mol·L^-1 to 1.0×10^-7 mol·L^-1 was linear with the ΔF/F₀ value at the maximum fluorescence emission wavelength of 550 nm, r=0.996 4, with a low detection limit of 2.67×10^-9 mol·L^-1. The recoveries of the method were 95.2%~104%, and the relative standard deviation (RSD) was 1.02%~4.54%, respectively. Based on the specific molecular recognition and high affinity of twosplit aptamers, the reaction product was shown that a “turn-on” fluorescence response to ATP with good selectivity, only a slight fluorescence change could be observed by GTP, CTP, and UTP (at a 200-fold higher concentration than that of ATP), indicating that UTP, CTP, and GTP could not interact with P1 and P1 to initiate the reaction. The method is simple, rapid, free-label, sensitive and accurate, and can be used for the determination of ATP in serum samples. Therefore, the present strategy has a great potential application prospect in the field of rapid detection of small molecular substances.
		2019 Vol. 39 (09): 2769-2773 [Abstract] ( 184 ) RICH HTML PDF (1513 KB) ( 44 )

	2774	Simulation and Experiment Study on Three-Dimensional Coordinate Outlier Detetion Method
		WANG Lin, MA Xue-jie, MENG Dan-rui, LIU Rong^*, XU Ke-xin
		DOI: 10.3964/j.issn.1000-0593(2019)09-2774-06
		Near-infrared diffuse reflectance spectroscopy has many advantages, such as being non-invasive, continuous, non-infectious, fast, in the non-invasive detection of body components. It has a great prospect in the application of blood glucose measurement in vivo. However, outliers often occur in the process of measurement due to the random noise, the change in interference components or the measurement conditions. Therefore, it is of great significance to eliminate the outliers in the near-infrared spectroscopy and thus improve the reliability of non-invasive blood components measurement. In this paper, the types of outliers that may occur in the blood glucose sensing by near-infrared diffuse reflectance were analyzed, and a three-dimensional coordinate outlier determination method based on the three-dimensional space constructed by the residual of chemical value, the Mahalanobis distance and the spectral residuals was proposed firstly. Then, it was used to discriminate the outliers in the simulated spectra of three-layer skin model by Monte Carlo program, where the abnormal data was obtained by adding the artificial errors, abnormal chemical values and abnormal temperature changes in the parameters setting in Monte Carlo simulation. All the outliers could be found successfully by the three-dimensional coordinate outlier determination method, and the root-mean-square error of cross-validation (RMSECV) of the Partial Least Square (PLS) model was reduced from 21.2 to 1.1 mmol·L^-1 after the removal of outliers. Further, the oral glucose tolerance tests (OGTTs) of three volunteers were carried out, where three groups of experimental data were obtained by measuring the reference blood glucose concentrations and collecting the diffuse reflectance of finger synchronously, and Monte Carlo Cross-Validation outlier detection method and three-dimensional coordinate method were used to detect the outliers, respectively. Results showed that, after the removal of outlier by the three-dimensional coordinate method, the coefficient of determination of calibration model increased significantly, and the average RMSECV value of calibration model for three sets of samples was reduced from 2.1 to 0.8 mmol·L^-1, which was better than that of MCCV method. All these results indicated that, three-dimensional coordinate method can effectively determine the outlier in the near-infrared diffuse reflectance and it’s more suitable for the non-invasive blood glucose measurement in vivo by near-infrared diffuse reflectance spectroscopy.
		2019 Vol. 39 (09): 2774-2779 [Abstract] ( 174 ) RICH HTML PDF (2880 KB) ( 41 )

	2780	Early Identification of Male and Female Embryos Based on UV/Vis Transmission Spectroscopy and Extreme Learning Machine
		ZHU Zhi-hui^{1, 2}, HONG Qi^{1, 2}, WU Lin-feng^{1, 2}, WANG Qiao-hua^{1, 2}, MA Mei-hu^3*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2780-08
		In order to identify male and female embryos of chicken eggs, the feasibility of using UV/Vis/NIR transmission spectrum to identify the male and female embryos is explored. The transmission spectrum detection system of chicken eggs is established with blunt end vertically placed upwards and horizontally placed separately to obtain the 0~15 d spectrum (ranging from 360 to 1 000 nm) of 210 hatched eggs. The identification model of the embryo learning male and female of the extreme learning machine (ELM) is constructed. By comparing the identification accuracy of different placement and the number of hatching days, it is found that the recognition effect of the vertical placement hatching on the 7^th day is the best. The spectrum of the 7^th day of vertical incubation is initially divided into ultraviolet (360～380 nm), visible light (380～780 nm), near-infrared (780～1 000 nm), ultraviolet/visible (360～780 nm) and full-band (360～1 000 nm). Five different band ranges are analyzed, and the prediction set accuracy rates are 82.86%, 77.14%, 75.71%, 84.29%, and 81.43%, respectively. The ultraviolet/visible bands of 360～780 nm are selected as effective bands; In the ultraviolet/visible (360～780 nm) band, Multiplicative scatter correction (MSC) is used to denoise, and the characteristic wavelength reduction is selected by Competitive adaptive reweighted sampling (CARS) and Successive projection algorithm (SPA). Three kinds of wavelengths without screening, CARS screening characteristic wavelength and SPA screening characteristic wavelength are established ELM model. Among them, the ELM model without screening characteristic wavelengths has the best recognition effect, but the input variables are the most. When the hidden layer neuron is 680 and the activation function is sig, the prediction set accuracy is 84.29%. The ELM model of the SPA screening characteristic wavelength has the second recognition effect, and there are 9 input variables. When the hidden layer neurons are 840 and the activation function is hardlim, the prediction set accuracy is 81.43%. The ELM model with the CARS screening characteristic wavelength has the worst recognition effect, and there are 27 input variables. When the hidden layer neurons are 100 and the activation function is sig, the prediction set accuracy is 78.57%. Using Genetic algorithm (GA) to optimize the weight variable and hidden layer threshold of ELM model, the prediction set accuracy rate is 87.14%, 87.14% and 81.43% separately under the condition of the GA-ELM model established without screening the characteristic wavelength, the GA-ELM model established by SPA screening characteristic wavelength, and the GA-ELM model established by the CARS screening characteristic wavelength. The recognition effect of GA-ELM model in the ultraviolet/visible band without screening characteristic wavelength is the same as that in the GA-ELM model with SPA screening characteristic wavelength, which indicates that the characteristic wavelength variable of SPA screening can effectively reflect the information of 360～780 nm band. The number of variables used by the SPA is only 2.14% of the ultraviolet/visible range. Therefore, the best model for male and female identification is the GA-ELM model for screening characteristic wavelengths with SPA in the ultraviolet/visible range. The accuracy of the prediction set is 87.14%, of which the female recognition rate is 88.57%, the male recognition rate is 85.71%, and the average discrimination time of a single sample is 0.080 ms. The results show that UV/Vis transmission spectroscopy and ELM model provide a feasible method for the identification of chicken embryo eggs in early hatching.
		2019 Vol. 39 (09): 2780-2787 [Abstract] ( 189 ) RICH HTML PDF (5186 KB) ( 72 )

	2788	Quantitative Analysis for Adsorption of Polycarboxylate Superplasticizer with Different Side-Chain Length on Tuff Powder Using Second Derivative Spectrometry
		FENG Lei¹, CHEN Xi-qin¹, CHENG Zu-shun¹, WEN Xiao-dong^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2019)09-2788-06
		The tuff powder has certain adsorption to the polycarboxylic acid water reducing agent（PCs）, which makes the number of “effective water reducing agent” decrease, resulting in greatly reduced performance of PCs. The anti-adsorption characteristics of PCs have important design reference significance, and it is closely related to the composition and structure of PCs. The UV spectrophotometry is a common method for the detection of adsorption quantity, but there are still many uncertainties in the PCs test. So，UV spectrophotometry and derivative spectrometry were used to quantitatively analyze the adsorption capacity of tuff powder on PCs with different side chain lengths, and the experimental parameters were analyzed and optimized. The results show that there is no obvious ultraviolet characteristic peak in the absorption spectrum of PCs. When test solution concentration is increased and its pH value is lowered, the pseudo peak can be seen in the wavelength range of 190~200 nm, which is confirmed by the spectral test of acetic acid analysis reagent. After the derivative treatmentof the PCs spectral data, the characteristic peak of PCs can be obtained. There is a good linear relationship between the test solution absorbance and its concentration under this characteristic peak, and the correlation coefficient r is greater than 0.99. Further，the accuracy of UV absorption spectroscopy is demonstrated, compared with the TOC method. There is a good linear relationship between the above two methods, and the correlation coefficient r is 0.997, which indicates that second derivative UV spectrum can provide a simple, fast, accurate, inexpensive and non-developing agent quantitative test method for PCs adsorption analysis; The adsorption of the PCs by the tuff rock powder decreases as the length of its side chain decreases. The research results will help to provide a new way for UV detection of organic matter with weak ultraviolet absorption.
		2019 Vol. 39 (09): 2788-2793 [Abstract] ( 205 ) RICH HTML PDF (3016 KB) ( 57 )

	2794	Control and Data Acquisition System for Hard X-Ray Micro-Beam Grazing Incident Experiment and Its Application
		LAN Xu-ying^{1, 2, 3}, HE Shang-ming^{1, 3*}, ZHENG Yi^{1, 3}, LI Ai-guo^{1, 3}, WANG Jie^{1, 3}
		DOI: 10.3964/j.issn.1000-0593(2019)09-2794-06
		The hard X-ray micro-beam grazing incidence experimental method has been first developed in China. This method with micro-spatial resolution is applied to analyze nano-thickness films in micro-regions. It is greatly significant for analyzing the uneven component, structure, thickness, roughness and chemical valence of surface elements in micro-regions. In this work, according to the principle of X-ray total reflection technology, and based on the high-flux, energy-adjustable monochromatic micro-beam X-rays, a control and data acquisition system of the grazing incidence experimental method is designed, which integrates motion control, light intensity detection, diffraction and fluorescence detection. This system adopts the distributed control system structure, and designs the SPEC control software based on the Experimental Physics and Industrial Control System (EPICS) environment. By establishing the access channels of SPEC and EPICS, it realizes using SPEC software to control the equipment on the EPICS platform. Regarding the designed control and data acquisition system, the motion control system controls multi-dimensional sample stage motors, and it can position the sample and adjust the grazing incidence angle. The light intensity detection system detects the intensity of the emitted light of the sample. Motion control and light intensity detection system are combined to realize sample stage scanning positioning. Diffraction and fluorescence detection system can obtain diffraction peak intensity and fluorescence counts of the sample at different incident depths. Additionally, in order to locate an accurate zero-angle position where the sample plane is parallel to the X-ray, a method of automatic controlling zero-angle is given, its control algorithm is programmed and it realizes automatic and accurate zero-angle positioning. Revealed by zero-angle scanning positioning results, the spatial resolution of the experimental system is 2.8 μm, and the zero-angle positioning accuracy is below ±0.01°. Finally, micro-beam grazing incidence X-ray diffraction and fluorescence experiments with automatic and accurate control of zero-angle have been first performed by using this experimental system at the micro-focusing beamline of Shanghai Synchrotron Radiation Facility. The sample was a 10 nm Au/Cr/Si thin film, the uppermost layer of the Si substrate was a 10 nm thickness Au thin film, and there was a very thin layer of Cr adhesion between them. Diffraction signals of the sample were measured at different grazing incidence angles and diffraction peak intensity could be obtained. Fluorescence counts were also collected at the same grazing incidence angles. Thereby the phase structure information and the relationship of fluorescence counts and incidence angles were obtained. This experimental system realizes the analysis of phase structure and composition of nano-thickness films in micro-regions. Additionally, according to the maximum value of fluorescence counts, an incident angle can be selected at which grazing incidence X-ray absorption near-edge structure experiments can be developed for low-concentration samples, and it is helpful to improve the signal-to-noise ratio of this experimental method.
		2019 Vol. 39 (09): 2794-2799 [Abstract] ( 181 ) RICH HTML PDF (1887 KB) ( 44 )

	2800	Study on the Selection of Spectral Preprocessing Methods
		DIWU Peng-yao, BIAN Xi-hui^*, WANG Zi-fang, LIU Wei
		DOI: 10.3964/j.issn.1000-0593(2019)09-2800-07
		Spectral signals of complex samples are usually disturbed by stray light, noise, baseline drift and other undesirable factors, which can affect the final qualitative and quantitative analysis results. Therefore, it is necessary to pretreat the raw spectra before modeling. How to find a proper preprocessing method from the existing spectral preprocessing methods is a difficult problem. One strategy is to choose the optimal preprocessing by observing the characteristics of the spectral signal directly, which does not require modeling and is more explanatory. However, it may be difficult and subjective for subtle or multiple interferences and lead to misleading results. Another strategy is based on the modeling performance, which does not need observe the spectral characteristics, but numerous processing methods need to investigate which is time-consuming for large datasets. In summary, it is necessary to explore which selection method is more scientific and reasonable. In this study, nine datasets were used to investigate the necessity of preprocessing and the choice of preprocessing methods by arranging and combining of 10 preprocessing methods. Firstly, the latent variables of partial least squares (PLS), the window size of first derivative (1st Der), second derivative (2nd Der) and SG smoothing, the wavelet function and decomposition scale of continuous wavelet transform (CWT) were optimized, respectively. Then, non-preprocessing and 10 preprocessing methods including 1st Der, 2nd Der, CWT, multiplicative scatter correction (MSC), standard normal variate (SNV), SG smoothing, mean centering, normalization, Pareto scaling, auto scaling were combined in order of baseline correction, scattering correction, smoothing and scaling. A total of 120 preprocessing and their combinations were obtained. Finally, the characteristics of spectral signals and the root mean squared error of prediction (RMSEP) with PLS for 120 preprocessing methods were analyzed for the nine datasets and the same dataset with different components. Results show that compared with observing the characteristics of spectral signals, the optimal preprocessing method can be selected more accurately according to the modeling performance of the spectra and predictive components. For most datasets, appropriate preprocessing method can improve the modeling performance. For different datasets, the optimal preprocessing method is different because of the different information and complexity of the datasets. For the same dataset, the optimal preprocessing methods for different components are also different even if the spectra are the same. Thus, it can be concluded that no universal preprocessing method exists. The optimal preprocessing method is related to the spectra and the predictive components. Furthermore, it is an effective way to select the optimal pretreatment method by sorting and combining the existing preprocessing methods according to the preprocessing purpose.
		2019 Vol. 39 (09): 2800-2806 [Abstract] ( 406 ) RICH HTML PDF (3917 KB) ( 334 )

	2807	Qualitative and Quantitative Analysis of Two Types of Wood Plastic Composites
		LAO Wan-li, LI Gai-yun^*, CHEN Yi, XIANG Qin, WANG Chao, HUANG An-min
		DOI: 10.3964/j.issn.1000-0593(2019)09-2807-05
		Qualitative and quantitative analysis of different types of wood plastic composites (WPC) made of different plastics is important for waste WPC products classifying, recycling and quality controlin the production process, standardizing market order, protecting the legitimate rights and interests of the consumers during sales and use. Establishing a mixed model used for quantitative analysis of WPCmade of different plastics can reduce the costs and improve model applicability. However, the current studies on qualitative analysis of WPC made of different plastics do not address the quantitative analysis of WPC. Therefore, the complete technical systemcan not be established. There have been no studies concerning the quantitative analysis of WPC made of different plastics. For this purpose, in this study, Polyethylene (PE)and polypropylene (PP) were used as matrix materials, respectively. Chinese fir powders were used as filler, and some chemical regents were added. Then 20 Chinese fir/PE and 20 Chinese fir/PP composites were manufactured by extrusion moulding. FTIR spectral data of 40 WPC samples were obtained by potassium bromide pressed-disk technique. First derivatives and Standard Normal Variate（SNV）were used to preprocess the spectral data by The Unscrambler version 9.2. And the FTIR spectral data were analyzed by principal component analysis (PCA). Results showed that the WPC samples could be grouped according to their plastic matrixes, and the correct rate was 100% due to the differences between PE and PP. Partial least square regression (PLSR) models were developed to predict both wood flour and plastic contents in two types of WPC based the above FTIR spectra. Results indicated that for wood and plastic calibration, the coefficients of determination (R²) were 0.984 and 0.985, respectively; the standard errors of calibration (SEC) were 1.034% and 1.026%, respectively. For both wood and plastic validation, the R² values were 0.956; the standard errors of cross validation (SECV) were 1.779% and 1.792%, respectively; the ratios of performance to deviation (RPD) were 4.83 and 4.85, respectively; The current model was used to predict the contents of wood and plastic in ten WPCs samples that were randomly selected for external validation. Results show that theaccuracy of the model is high, the relative prediction deviations for wood flour contents were lower than ±8%, and plastic contents were lower than ±7%. A rapid and accurate identification and determination method applied for PE-based WPC and PP-based WPC was established, whichlays the foundation for FTIR’s use in the manufacturing, quality control and recycling.
		2019 Vol. 39 (09): 2807-2811 [Abstract] ( 178 ) RICH HTML PDF (1726 KB) ( 57 )

	2812	Identification of Walnut Origins and Varieties with Mid-Infrared Spectroscopy Analysis Technique
		HE Yong, ZHENG Qi-shuai, ZHANG Chu, CEN Hai-yan^*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2812-06
		To explore the feasibility of rapid detection of the origin and quality of walnut by using mid-infrared spectroscopy, mid-infrared spectroscopy and chemometrics algorithms were used to classify walnuts of ten varieties from four major origins and finally good results were achieved. After extracting the transmittance spectra of walnut powder, the apparent noise was removed in the head and the tail of the original spectrum, and the remaining spectrum of 700~3 450 cm^-1 was denoised by wavelet transform (WT) algorithm. The spectral characteristic wavenumber was extracted by uninformative variable elimination combined withsuccessive projections algorithm (UVE-SPA). Qualitative analysis of the spectrum was performed by principal component analysis (PCA). Back propagation neural network (BPNN), extreme learning machine (ELM), random forests (RF), radial basis function neural network (RBFNN) and partial least squares discrimination analysis (PLS-DA) were used for modeling based on the full spectrum and characteristic wavenumbers. For the discrimination of four different origins, 12 characteristic wavenumbers were selected: 803, 1 355, 1 418, 1 541, 1 580, 1 727, 1 747，1 868, 2 338, 2 462, 2 824, and 3 166 cm^-1, the discrimination accuracy of characteristic wavenumbers was much higher than that of full spectrum, and the accuracy of BPNN algorithm combined with characteristic wavenumbers reached 97%. The result of RF algorithm was the worst, and the accuracy was only 69.70%. For the discrimination of ten varieties, 10 characteristic wavenumbers were selected: 903, 1 275, 1 507, 1 541, 1 563, 1 671, 1 868, 2 311, 2 845, 3 437 cm^-1, the discrimination accuracy of characteristic wavenumbers was still much higher than that of full spectrum. The accuracy of BPNN algorithm combined with characteristic wavenumbersreached 83.3%. In terms of the versatility of characteristic wavenumbers, there were two same characteristic wavenumbers in the two sets of characteristic wavenumbers: 1 541 and 1 868 cm^-1, and most of the other characteristic wavenumbers were similar. The spectra based on characteristic wavenumbers of 10 varieties were used as input variables to discriminate walnuts’ origins, and the result was poor. Therefore, the characteristic wavenumbers selected under the supervisory value of 10 varieties could not be applied to discriminate 4 types of producing origins. Even with the same original data, characteristic wavenumbers selected based on different discriminant problems were less versatile in modeling. After extracting the characteristic wavenumbers by UVE-SPA algorithm, the discrimination results showed that the number of variables can be reduced by more than 99%, which effectively simplified the model, reduced the amount of calculation, and improved the stability of prediction. In general, the performance of each classifier is: BPNN>RBFNN>ELM>PLS-DA>RF. The experimental results showed that the identification of walnut origins and varieties can be realized effectively based on wavelet transform, characteristic wavenumber selection and back propagation neural network algorithm.
		2019 Vol. 39 (09): 2812-2817 [Abstract] ( 240 ) RICH HTML PDF (2413 KB) ( 131 )

	2818	Determination of Korla Pear Hardness Based on Near-Infrared Spectroscopy
		SHENG Xiao-hui¹, LI Zi-wen¹, LI Zong-peng¹, ZHANG Fu-yan², ZHU Ting-ting³, WANG Jian^1*, YIN Jian-jun¹, SONG Quan-hou¹
		DOI: 10.3964/j.issn.1000-0593(2019)09-2818-05
		Near-infrared diffuse reflectance spectroscopy was used to determine the hardness of five different fruits (including green head, rough skin, dislocated, scorpion, and apex) of Xinjiang pear fruit Korla pear. Due to the large amount of data in the near-infrared spectrum, the original spectral noise is obvious, and the scattering of fruits is serious, the key wavelength variables are difficult to extract during spectral modeling. Based on this, in order to effectively eliminate the influence of solid surface scattering and optical path variation on the NIR diffuse reflectance spectrum, it is proposed to use standard normal variable transformation (SNV) and multiple scattering correction (MSC). The original spectrum of Korla pear was pretreated. In order to find the best characteristic wavelength screening method suitable for the detection of Korla pear hardness by near-infrared spectroscopy, the comparison and research on the characteristic wavelength variable selection methods of Pear near infrared spectrum were carried out. The effects of two characteristic wavelength screening methods on the modeling accuracy of Korla pear hardness partial least squares (PLS) were compared. Simultaneously using the reverse partial least squares (BiPLS) and genetic algorithm combined with reverse partial least squares (BiPLS-GA) to screen the characteristic wavelength variable of the pear hardness in the whole spectral range, the corrected root mean square error (RESMC), The prediction root mean square error (RESMP) and the decision coefficient (R²) were used as the evaluation criteria of the model, and the optimal band selection method and the optimal prediction model were finally determined. The PLS model based on the selected characteristic wavelength variable (BiPLS-GA) was compared with the PLS model established by the full spectral variable. It was found that the BiPLS-GA model obtains better information than the full-variable PLS model by using only 6.6% of the information in the original variable. The prediction results of Korla pear hardness, where R², RMSEC and RMSEP are 0.91, 1.03 and 1.01, respectively. Furthermore, compared with the PLS model established by the feature variables obtained by the reverse partial least squares algorithm (BiPLS), BiPLS-GA can not only remove the non-information variables in the original spectral data, but also compress and remove the collinear variables, reducing the number of modeling variables from 301 to 20. The model is greatly simplified while the prediction accuracy and stability of the model are effectively improved. Therefore, the method can be effectively used for the selection of near-infrared spectral data variables. It is proved that the near-infrared spectroscopy analysis technology combined with the BiPLS-GA model can efficiently select the modeling variables, remove the near-infrared spectral information unrelated to the hardness of Korla pear, and significantly improve the prediction accuracy of the Korla pear hardness quantitative model. This not only provides a certain technical support for the rapid, precise and non-destructive optimization of the characteristic pear fruit Korla pear in Xinjiang, but also provides a reference for the research of predicting the internal quality of fruit based on near-infrared spectroscopy.
		2019 Vol. 39 (09): 2818-2822 [Abstract] ( 210 ) RICH HTML PDF (963 KB) ( 358 )

	2823	Spectral Characteristics and Identification Research of Corn under Copper Stress
		LI Yan, YANG Ke-ming^*, RONG Kun-peng, ZHANG Chao, GAO Peng, CHENG Feng
		DOI: 10.3964/j.issn.1000-0593(2019)09-2823-06
		The monitoring of heavy metal pollution in crops is one important application of hyperspectral remote sensing study. The objective of this work was to develop a new narrow-band vegetation index to characterize the Cu (copper) stress degree in two corn species at two growing years. The experiment on the copper pollution was designed based on its different concentrations, meanwhile, the hyperspectral reflectance of corn leaves stressed by different Cu²⁺ concentrations were measured using hand-held spectrometer(SVC, USA) and leaf Cu²⁺ contents were also measured. The first difference reflectance and biochemical data of corn were analyzed using Pearson correlation coefficient (r) to select wavelengths sensitive to Cu stress. The calculated Pearson correlation coefficients suggested that the first difference reflectance near 489~497, 632 and 677 nm wavelengths was significantly correlated with Cu²⁺ contents in leaves. The selected wavelengths of 489~497, 632 and 677 nm were used to establish the Cu stress vegetation index based on the first difference reflectance (dVI). To select index with the highest possible correlation to Cu stress, all possible dVIs were related through simple regression models with Cu²⁺ contents andthe predictive abilities of those models were evaluated through the R² values and the root mean square error (RMSE). The stability of the sensitive bands and the applicability of dVI were assessed using corn data from different growth years. Meanwhile, the performance of dVI was compared with that of existing popular vegetation index (VIs) related to heavy metal stress, such asnormalized difference vegetation index (NDVI), red-edge chlorophyll index (CI_red-edge), red-edge position (REP), photochemical reflectance index (PRI). The results suggest that the corn spectral characteristics in response to copper stress are enhanced with the first-order difference treatment. Compared with the original reflectance, the correlation coefficient between first difference reflectance at wavelengths of 450~500, 630~680 and 677 nm and Cu²⁺ content increases. The wavelength position of copper stress sensitive band based on the first-order differential reflectance is stable for the data sets of different growth years. The index that combined the first difference reflectance in 497, 632 and 677 nm wavelengths is found to be a potential useful index to predict leave Cu concentration for different data sets. And the correlation of dVI was much stronger than that of other VIs for all the tested data sets from two corn species at two growing years. The proposed dVI characterizes the Cu stress degree on vegetation with advantages of better effectiveness and robustness. This study focuses on the spectral reflectance at the leaf scale, so it is expected that future work will extend it to canopy scale.
		2019 Vol. 39 (09): 2823-2828 [Abstract] ( 183 ) RICH HTML PDF (3162 KB) ( 123 )

	2829	Nitrogen Nutrition Diagnostic Based on Hyperspectral Analysis about Different Layers Leaves in Maize
		ZHANG Yin-jie, WANG Lei^*，BAI You-lu, YANG Li-ping, LU Yan-li, ZHANG Jing-jing, LI Ge
		DOI: 10.3964/j.issn.1000-0593(2019)09-2829-07
		In order to clarify the location of nitrogen nutrient diagnosis of maize leaves at different growth stages, and to establish an accurate and robust model to diagnose maize’s nitrogen nutrition, which aims to guide rational fertilization and improve recovery rate, in this experiment, a single factor pot experiment was designed, and maize (Zhengdan 958) was used as the research object to study the distribution and variation of nitrogen content in different layers of leaf under different nitrogen nutrition levels. The distribution and variation of N content and the spectral response characteristics of maize leaves were analyzed. And the correlation relationship between nitrogen content and spectral reflectance of different layers leaves at different growth stages was investigated. Moreover, the regression relationship between the leaf nitrogen content and the ratio spectral index (RSI) which was composed of any two bands between 400～2 000 nm was explored. According to these analyses, leaf layer, optimal RSI and estimation models were initially determined at different stages for nitrogen nutrition diagnosis by spectral technique. The main results are as follows: The results indicate that the maize’s nitrogen content in different layers is as follows: the upper layer>the middle layer>the lower layer; and that as the stages of growth forward, leaves’ nitrogen content in upper layer, under the condition of low-nitrogen, appears to first decrease and then increase (after manuring) and decrease again while keeping the tendency of decrease under the condition of high-nitrogen, with the leaves’ nitrogen content in the levels of middle and low appearing to decrease. At the Six-leaf stage, the lower layer of leaves has a larger sensitivity range and a stronger correlation coefficient. At Nine-leaf and Filling stage, spectral reflectance of the upper layer maize leaves was more sensitive and correlated. At the flowering and silking stage, spectral reflectance of the middle layer leaves was more sensitive and relevant. SO the lower leaves were selected as the diagnosis target at the Six-leaf stage, and the optimal ratio spectral index RSI (1 811, 1 842) was selected to establish the linear estimation model. The upper leaves were selected as the diagnostic target at the Nine-leaf stage and the Filling stage, and the optimal ratio spectral indices were RSI (720, 557), RSI (600, 511) to establish the linear estimation model, respectively. The middle leaves were selected as the diagnostic target during the anthesis-silking stage, and the RSI (688, 644) spectral index was selected to establish the estimation model. The research results could provide a theoretical basis for rapid and accurate nitrogen nutrition spectrum diagnosis method in maize or other crop.
		2019 Vol. 39 (09): 2829-2835 [Abstract] ( 192 ) RICH HTML PDF (4778 KB) ( 133 )

	2836	Study of the Accuracy of Apple Internal Lesion Detection Based on Frequency Domain Diffuse Optical Tomography
		LI Jiang-tao¹, HU Wen-yan¹, ZHAO Long-lian^{1, 2*}, LI Jun-hui^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2019)09-2836-06
		Lesions inside the apple tissue cause changes in their optical parameters. Frequency domain diffuse optical tomography（FD-DOT） is used to detect the absorption coefficient and the reduced scattering coefficient of apple tissue, and the reconstructed image obtained by combining the 3D reconstruction technology can intuitively understand the internal condition of the apple. In this way, non-destructive detection of internal lesions in apple was realized. According to the visible near-infrared transmission spectrum of normal and rotten apple samples, the wavelength of 740nm can be chosen as the laser light source to distinguish normal and diseased apple tissues furthest. The imaging precision will vary with the frequency of incident light modulation, the degree, location, and size of lesions within the apple. In this paper, a series of simulation experiments are designed to study the effect of the above factors on the detection accuracy: to study the influence of modulation frequency on the accuracy of reconstructed images, setting different laser modulation frequencies; to study the influence of the size of lesion on the accuracy of the reconstructed image, adding spherical heteroplasmon of different sizes at a certain position in the apple model ; A heteroplasmon of a certain size was added at different positions to study the influence of different lesion positions on the accuracy of the reconstructed image. Firstly, finite element mesh model of apple was established by Abaqus. Twelve 740nm near-infrared laser sources and six detectors were designed to be evenly arranged on the surface of the apple model. Then according to the experimental needs, a spherical heteroplasmon representing lesion was added to the tissue model. After that irradiation into interior of the apple with a high-frequency modulated light source, and detect the AC amplitude and phase delay of the emitted light. The software NIRFAST is used to calculate and inversely derive the absorption coefficient and the reduced scattering coefficient distribution of the apple to be tested. Finally, the reconstructed image is obtained by using 3D reconstruction method, reconstruction results can be evaluated using the absorption coefficient contrast-to-noise ratio (CNR) and absorption coefficient distribution of the reconstructed image. The experimental results show that in order to detect deep lesions of larger apples, a higher incident light modulation frequency is required; this method can detect most spherical lesions with a radius greater than 5 mm in suitable apples, and as the size of lesions is enlarged within a certain range, the accuracy of the reconstructed image is gradually increased. However, when lesion area is too large, the image accuracy begins to decrease. When lesion is closer and closer to the detector, the accuracy of the reconstructed image gradually increases, but when distance between lesion and detector is too small, the accuracy of the reconstructed image has a tendency to decrease; the closer the vertical distance of lesion region to the detector plane is, the higher the accuracy of the reconstructed image is. The above experimental results will lay a good foundation for the application of FD-DOT in non-destructive testing of apples.
		2019 Vol. 39 (09): 2836-2841 [Abstract] ( 184 ) RICH HTML PDF (3287 KB) ( 62 )

	2842	Quantitative Conversion of Soil Color from CIELAB to Munsell System
		YUE Zhi-hui¹, HUANG Qiang², XIAO Li¹, LI Jun¹, HUANG Cheng-min^1*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2842-05
		Color is one of the critical morphological features of soils, which can be used as a basic index or proxy to reveal numerous soil physical and chemical properties, processes and functions. Soil color is universally expressed by the Munsell color system, and detected by the visual sense through the match of soil samples with the soil standard charts. However, the errors and bias in soil color readily occur using the current method due to the constrain of the difference in individual vision and variation in optical environment. An objective, quantitative and rapid method to determine the soil Munsell color is urgent to be invented.Here, with the combination of color measurement using the colorimeter, automatic calculation and linear interpolation between the adjacent Value (V) isoplanes, a procedure for the conversion of CIE color to Munsell color was proposed to obtain the soil color conveniently, rapidly and precisely. This protocol includes: (1) CIELAB color values of the samples are measured by the colorimeter; and (2) the color coordinates and the Munsell V values are computed automatically with the program in Python language on a base of the knowledge of the conversion between CIE and Munsell color systems; and (3) the linear interpolation between the adjacent V isoplanes and color conversion chart are employed to assign the Munsell Hue (H) and Chroma (C). 419 color chips from Munsell Soil Color Chart of China and 22 soil and paleosol samples were used to validate the protocol. The Munsell H values of 12 chips using our procedure were different from those in Munsell Soil Color Chart of China, and the measured accuracy reached 97%. Meanwhile, the correlation coefficients in Munsell V and C between the measured values and standard values were 0.987 (p<0.001) and 0.976 (p<0.001), respectively, exhibiting a robust significance. For the soil and paleosol samples, the difference in Munsell H between the measured values using our protocol and judged by visual sense is least while a discrepancy in Munsell V and C occurs possibly because of the visual values affected by the visual sense and optical environment. Based on the previous literatures on transformation in soil color between CIE to Munsell color systems, we established a procedure, particularly in making a Python program in order to complete the automatic calculation from CIELAB to the color coordinates and the Munsell V values, and providing a new interpolation method to acquire the Munsell V and C values, to facilitate the rapid and applicable conversion of CIE color system to Munsell color system for soils.
		2019 Vol. 39 (09): 2842-2846 [Abstract] ( 242 ) RICH HTML PDF (1151 KB) ( 84 )

	2847	Inversion and Mapping of the Moisture Content in Soil Profiles Based on Hyperspectral Imaging Technology
		WU Shi-wen^{1, 2}, WANG Chang-kun¹, LIU Ya³, LI Yan-li⁴, LIU Jie^{1, 2}, XU Ai-ai^{1, 2}, PAN Kai^{1, 2}, LI Yi-chun^{1, 2}, ZHANG Fang-fang^{1, 2}, PAN Xian-zhang^1*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2847-08
		Traditional methods for acquiring soil moisture can only provide discrete point data, which arenot so appropriate for finely and continuously mapping soil moisture distribution in soil profile. In this paper, the feasibility of predicting and mapping ofsoil moisture content (SMC) in soil profile was studied using near-infrared hyperspectral imaging in the spectral range of 882～1 709 nm. Two soil profiles, located in Dongtai City of Jiangsu Province, were continuously observed in situ for 5 days by the near-infrared hyperspectral imaging system. A total of 280 soil samples were obtained for later SMC measurement by oven-drying method. After a series of preproces on the acquired raw hyperspectral images, including digital number(DN) correction, reflectance correction, mosaicking, geometric correction, image clipping and masking, the average spectral reflectance of each sampling point in the corrected hyperspectral images was extracted for further analysis. Then the extracted spectra (Raw) were preprocessed by LOG₁₀(1/R), Savitzky-Golay (SG), first derivative (FD), second derivative (SD), multiplicative scatter correction (MSC) and standard normal variate (SNV), and partial least squares regression (PLSR) and least squares support vector machine (LS-SVM) models were developed and comparedfor a selection of optimum prediction model. Results showed that the soil spectral reflectance gradually decreased with the increase of SMC, and different spectral preprocessing methods had different prediction accuracy. Except for the MSC preprocessing method, the prediction accuracy of the LS-SVM model was higher than the PLSR model with the same spectral preprocessing method. The prediction accuracy of the LS-SVM model with LOG₁₀(1/R) preprocessed spectra was highest with R²_c of 0.96 and RMSE_c of 0.65% for calibration, and R²_p of 0.88, RMSE_p of 1.05% and RPD_p of 2.88 for prediction. The optimum model was then applied to produce high spatial resolution maps of SMC in profiles. The prediction accuracy was high (R²: 0.85～0.95, RMSE: 0.94%～1.02%) by comparing the extracted SMC values from prediction maps with the measured values, and both SMC had the samedistribution tendency in profiles, demonstrating that the SMC prediction mapscould well displaynot only the SMC distribution in profiles in the millimeter scale, but also the changes of SMC at different locations in the profile between different days. Thus, the near-infrared hyperspectral imaging technology combined with optimized prediction model could provide a new approach to quantitatively predict and map high spatial resolution images of SMC in soil profiles in situ, which could help to rapidlyand effectively monitorsoil moisture in profiles in the field.
		2019 Vol. 39 (09): 2847-2854 [Abstract] ( 216 ) RICH HTML PDF (3817 KB) ( 76 )

	2855	Quantitative Inversion of Soil Organic Matter Content in Northern Alluvial Soil Based on Binary Wavelet Transform
		WANG Yan-cang^{1, 3}, YANG Xiu-feng^{1, 3}, ZHAO Qi-chao^{1, 3}, GU Xiao-he^{2, 4*}, GUO Chang^{1, 3}, LIU Yuan-ping^1,3
		DOI: 10.3964/j.issn.1000-0593(2019)09-2855-07
		In order to separate the information of the content of soil organic matter contained in soil spectra, to extract the spectral response information of the matter, to improve the diagnostic accuracy and reliability of soil organic matter content, this study takes the content of organic matter in tidal soil as the research object, and takes the soil parameters and hyperspectral data of 96 farmlands collected from Beijing area as the data source to research and analyze. First, the binary wavelet technique is used to separate the soil spectral data into 5 scales of high-frequency data and low-frequency data, and then these two kinds of data are respectively used for the correlation analysis with the measured soil organic matter data. Afterwards, the optimal band combination is extracted to build the diagnosis model of organic matter content. Finally, results of the study show that: (1) The binary wavelet technology can restrain the noise interference to high frequency information, and effectively enhance the spectral sensitivity to soil organic matter content so as to improve the diagnostic accuracy and reliability of organic matter content; (2) Under the binary wavelet technique, the diagnostic ability of high frequency information to organic matter content is obviously superior to that of low frequency information. The diagnostic ability of low frequency information to soil organic matter content decreases with the increase of scale, while high frequency information increases with the scale increasing and then decreases; (3) Compared with the mathematical method, the model based on the binary wavelet transform algorithm has higher accuracy and better stability. The prediction accuracy of the optimal model is improved by 31.5% and the reliability is increased by 10.5%.
		2019 Vol. 39 (09): 2855-2861 [Abstract] ( 176 ) RICH HTML PDF (3477 KB) ( 72 )

	2862	Extracting Characteristic Wavelength of Soil Nutrients Based on Multi-Classifier Fusion
		LI Xue-ying^{1, 2, 3}, FAN Ping-ping^{1, 2, 3}, LIU Yan^{1, 2, 3}, WANG Qian^{1, 2, 3}, Lü Mei-rong^{1, 2, 3}
		DOI: 10.3964/j.issn.1000-0593(2019)09-2862-06
		Although spectral technology has been applied to the rapid detection of soil nutrient, how to find the spectral characteristic bands of soil, to avoid useless information and to keep useful information, and to establish a model with high accuracy and good predictive effect is still an urgent problem to be solved. Taking soil samples from three different regions in Qingdao as an example, the ultraviolet-visible-near-infrared spectra and total carbon (TC), total nitrogen (TN) and total phosphorus (TP) content of soil samples were determined. Successive Projections Algorithm (SPA), Uninformative Variable Elimination (UVE), Genetic Algorithm (GA) and Correlation Coefficient Method (CC) four kinds of algorithms (four single classifiers) were used to extract the characteristic wavelength of the soil spectra. The multi-classifier fusion of the voting method and the weighted voting method were used to obtain the characteristic wavelength. The soil nutrient content models were established by the partial least squares regression (PLSR). Through theresult of these models (the determination coefficient of calibration set R²_c, the corrected root mean square error RMSEC, the determination coefficient of test set R²_p, the predicted root mean square error RMSEP and residual predictive deviation RPD), we evaluated the effect of extracting the characteristic wavelength of soil nutrient content among each single classifier algorithm and multiple-classifier fusion algorithm. In this paper, the multi-classifier fusion of four algorithms, three algorithms and optimal two algorithms were analyzed. The results showed that, after merging four kinds of single classifier by voting method, the model effect was mostly inferior to each single classifier, and there were many characteristic wavelengths in the relative good model. The model effect of four single classifier by weighted voting method had been improved compared with that by voting method. TC and TN could achieve better prediction effect in less wavelength, but only after TN fusion, the model effect was better than each single classifier. TC, TN and TP were fused by weighted voting method with SPA+UVE+GA, SPA+UVE+GA (or SPA+GA+CC) and SPA+UVE+GA three kinds of single classifier, and the optimal model effect was obtained, which was superior to each single classifier. The soil nutrient content was fused by weighted voting method with two optimal single classifier, the modeling effect was better than that of the optimal single classifier, the results of TC and TP modeling were slightly worse than those of three single classifiers, and TN modeling effect was the same as that of three single classifiers. So TC, TN and TP could obtain higher results than single classifier in case of selecting three kinds of algorithms and including the optimal two algorithms. It provides a new method for finding spectral characteristic bands of soil nutrients and other complex substances, and also provides a new idea for the comprehensive application of various algorithms.
		2019 Vol. 39 (09): 2862-2867 [Abstract] ( 199 ) RICH HTML PDF (2110 KB) ( 65 )

	2868	Sulfhydryl Modification and Spectral Measurement of Cytoglobin
		ZHOU Dan-lei^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2019)09-2868-05
		Cytoglobin (Cygb), a member of globin family, is a hemeprotein which was discovered 15 years ago. It contains a prosthetic group heme, which can reversibly bind an oxygen molecule between the iron ion of the porphyrin ring and a histidine of the polypeptide chain and play an important role in storing and delivering oxygen. There are two cysteines in C38 and C83 site of Cygb. Modification of the cysteine on Cygb can affect the oxygen-binding function of Cygb. In this article, chemical reagent 4, 4’- dithiodipyridine (4-PDS), N-ethylmaleimide (NEM), Oxidized Glutathione (GSSG) and Dithiothreitol (DTT) were used for modifying Cygb to intramolecular disulfide bond (Cygb-SS), thioether bonds (Cygb-SC), intermolecular disulfide bond (Cygb-SSG)and free sulfhydryls (Cygb-SH) respectively. The modified effect and product yield were detected by 4, 4’-dipyridine disulfide (4-PDS) spectroscopy method which can calculate modified rate by measuring the free sulfhydryl content in modified Cygb. The concentration of sulfhydryl in Cygb-SS and Cygb-SC samples is lower than one-tenth of the concentration of Cygb, indicating that the free sulfhydryl on the Cygb has been occupied by 4-PDS and NEM; The concentration of sulfhydryl in Cygb-SSG sample is comparable to that of the protein, indicating that one sulfhydryl in Cygb molecule participated in the reaction. Due to the steric hindrance of Cygb, the other sulfhydryl remained unchanged in the free sulfhydryl state; Double the concentration of sulfhydryl in the Cygb-SH sample as compared to the concentration of the Cygb indicates that one Cygb molecule contains two free sulfhydryl. We can know the modified yield by detecting the free sulfhydryl content of the four Cygbs respectively. The results showed that the four chemical reagents successfully modified cysteines on Cygb, and that the product yield reached more than 90%. This article measures the modified effect of Cygb by 4-PDS spectroscopy method and verifies the feasibility of this method by cysteine. In summary, the 4-PDS spectrometry method is accurate and reliable, which is complementary to the classical Ellman’s reagent method, and is more suitable for determining the content of sulfhydryl of compounds with absorption peak at 410~420 nm.
		2019 Vol. 39 (09): 2868-2872 [Abstract] ( 162 ) RICH HTML PDF (2401 KB) ( 67 )

	2873	Accumulative Fluorescence Emission Spectra Combing Multivariate Statistics to Study the Characteristics of DOM in Moguhu Lake
		ZHANG Guang-cai^{1, 2}, YU Hui-bin², XU Ze-hua¹, HAN Mei¹, SONG Yong-hui^2*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2873-06
		This study takes the DOM of the Moguhu Lake water as an example, based on accumulative emission spectra (AFEs), combined with multivariate statistics and second derivative, to characterize the various fluorescent components and content of DOM. Principal Component Analysis (PCA) was used to analyze the factor loading of AFEs and to determine the difference between the types of fluorescent peaks and their contents. The second derivative AFEs are obtained by AFEs through second derivative conversion. Analysis of the content and variation of each component in DOM by absolute area integration of the fluorescence peaks of the second derivative AFEs of all sampling points. Cluster analysis was used to analyze the difference or similarity of DOM components at different points. Studies have shown that five types of fluorescent peaks are obtained by AFEs, namely protein-like peaks, fulvic acid-like peaks, marine or terrestrial humic acid peaks, and humic acid peaks. Based on the analysis of the AFEs and sum of fluorescence intensity, it can be seen that the DOM in the water of the Moguhu Lake is mainly unstable, easily degraded, and the protein with less molecular weight and fulvic acid. The degree of humification of its DOM is reduced from the lakeside area to the deep lake area. According to the AFEs score map, five types of fluorescent peaks are obtained, and the protein-like and fulvic acid-like peaks in the fluorescent peak are the main ones. Based on the point-score matrix, it can be explained that there is a difference in the fluorescence components between the points. The second derivative AFEs are divided into five fluorescent bands. The DOM is mainly composed of organic matter with small molecular mass, and the degree of humification and aromaticity are small, and the spatial difference is not significant. By clustering the fluorescence peak area and sampling points, the fluorescence peaks are divided into three categories, of which fulvic acid content is relatively large, and there is a difference between the shore sampling point and the sampling point located in the lake center area. In summary, AFEs are relatively simple and rapid, and can be used to characterize DOM instead of 3DEEM. The DOM in the water of the Moguhu Lake is mainly composed of protein-like and fulvic acid-like substances with relatively low molecular weight, instability and easy degradation. In general, the degree of humification and relative molecular mass have a tendency to decrease from the lakeside area to the deep lake area, but the spatial difference is small.
		2019 Vol. 39 (09): 2873-2878 [Abstract] ( 177 ) RICH HTML PDF (3971 KB) ( 52 )

	2879	Synthesis and Spectral Properties of Phosphors Based on Schiff Base Complexes
		LI Zhao, CAO Jing, WANG Yong-feng
		DOI: 10.3964/j.issn.1000-0593(2019)09-2879-04
		Organic electroluminescent materials have significant features such as active illumination, wide viewing angle, and high contrast. Rare earth organic complex electroluminescent materials are currently attracting the attention of researchers. In this paper, salicylaldehyde and benzoic acid derivatives are used as raw materials to synthesize salicylaldehyde p-methoxybenzoyl hydrazide (1-H₂L) and salicylaldehyde p-methylbenzene by esterification, deuteration and Schiff base condensation. Synthesis of salicylaldoxime series lanthanum rare earth complexes with pyroglycol (2-H₂L), salicylaldehyde-bromobenzoylhydrazide (3-H₂L) ligands and Pr(NO₃)₃ as raw materials The structures of the complexes were characterized by infrared spectroscopy and ultraviolet spectroscopy. The ligand is a hydroxyl ν(OH) stretching vibration peak at 3 136～3 141 cm^-1, which disappears in the infrared spectrum of the complex. The absorption peak of the complex between 3 330～3 368 cm^-1 belongs to the crystallized H₂O. The (OH) hydroxyl bending vibration absorption peak, the complex does not have an absorption peak at the hydroxyl group of 3 140 cm^-1 corresponding to the ligand, and the absorption waveforms of the three ligands and complexes are similar, and the structure of the ligand and the complex are reacted basically consistent. However, the absorption peaks between the ligand and the complex have a large difference, and it can be inferred that the ligand has been coordinated. The fluorescence properties of the complexes were determined by fluorescence spectrophotometer. The effects of ligand substituents on the fluorescence intensity were discussed. The complexes can be excited by 470 nm blue light and have good red light emission at 608～617 nm. Such phosphors are expected to be applied on OLEDs.
		2019 Vol. 39 (09): 2879-2882 [Abstract] ( 195 ) RICH HTML PDF (2561 KB) ( 52 )

	2883	Quantitative Analysis of Multi-Component Gases in Underground by Improved PSO-SVM Algorithm
		DUAN Xiao-li^{1, 2}, WANG Ming-quan^1*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2883-06
		For quantitative analysis of multi-component gas mixtures, there are incomparable advantages for the quantitative analysis technology of characteristic spectrum. However, the efficiency and accuracy of quantitative detection depends on the capabilities of the spectral data processing algorithms. Optimizing the parameters of spectral analysis algorithms and improving the processing of spectral data are important means to improve the speed and accuracy of quantitative analysis. According to the problem in selecting parameter of support vector machine(SVM) when detecting quantitatively the concentration of multi-component gas in underground mine, an improved Particle Swarm Optimization-Support Vector Machine (PSO-SVM) algorithm was proposed. The algorithm is mainly used to research the problem that the multi-component gas mixed spectrum data is large and the spectral feature information overlaps. The algorithm constrains the convergence path of the PSO algorithm through particle variation, and it improves model optimization efficiency through particle information sharing, and it uses the setting of dynamic insensitive areas to improve model accuracy. A rapid quantitative detection system for multi-component gas was designed in underground mine. The infrared light source was drived by signal modulation module controlled by PC, and the signal light was irradiated on the detector by the air chamber with dust and steam filter. On the basis of the pressure and temperature sensor compensation, the detected optical signals were transmitted to the CPU by signal processing module. Finally, quantitative analysis of the gas concentrations for the various components was achieved by the improved PSO-SVM algorithm. On the basis of the actual sample gas collection and pretreatment in the underground, five kinds of gas components of CH₄, C₂H₆, C₃H₈, SO₂ and CO₂ were tested. The concentration range of CH₄ was 0～10%, and the concentration range of other gases was 0～10%. Infrared spectral data of these five gases were collected with Fourier infrared spectrometer. 800 groups of these gases were divided into 400 groups for calibration set and 400 groups for validation set. The quantitative analysis model of multi-component gas was established by SVM. The parameters of SVM were optimized by improved PSO, and the quantitative parameters were reconstructed by the obtained optimal parameters. The infrared spectral data collected by the algorithm and the traditional BP network algorithm were used to invert the gas concentration of each component. The experimental results show that the convergence range of the optimal value is reduced due to the constraint of the mutated particle, which improves the convergence speed. The modeling time of the algorithm is only 1/10 of that of the traditional method; Since the insensitive area is given by the spectral characteristics of the gas, the cross-sensitivity effect of the characteristic spectrum is reduced, which improves the prediction accuracy of the model. It improves the accuracy of model predictions, with an average error of about 1/5 of traditional methods. It is feasible to use improved PSO combined with SVM for quantitative analysis of multi-component gas in underground. The improved PSO-SVM algorithm has good applicability for the separation of multi-component gas mixed infrared spectral data, and it has certain practical application value.
		2019 Vol. 39 (09): 2883-2888 [Abstract] ( 180 ) RICH HTML PDF (1404 KB) ( 74 )

	2889	Microscopic Experimental Study on the Crystallization of TBAB-CO₂ Hydrate
		CHEN Yu-feng¹, ZHOU Xue-bing^{2, 3, 4}, LIANG De-qing^{2, 3, 4*}, WU Neng-you⁵
		DOI: 10.3964/j.issn.1000-0593(2019)09-2889-05
		TBAB semi-clathrate hydrate has a huge potential for effective application of carbon dioxide (CO₂) capture. Because of the complexity of the crystal structure, the kinetics of TBAB hydrate remains poorly understood. In this work, the spectral characteristics of nCO₂·TBAB·26H₂O and nCO₂·TBAB·38H₂O were analyzed by Raman and powder X-ray diffraction (PXRD). To understand the gas storage characteristics of TBAB hydrate, the processes of CO₂ molecules entering 2 kinds of crystal structures were measured using in situ Raman spectroscopy. Results showed that the Raman spectra of 2 crystal structures had high similarity. The Raman peaks at 1 309.5 and 1 326.9 cm^-1 were assigned to be the C—C deformation vibration mode of TBA⁺ cations in nCO₂·TBAB·26H₂O hydrate. They did not shift in nCO₂·TBAB·38H₂O hydrate, but became detached and narrow in half-peak width. Meanwhile, the peaks at 1 446.6 and 1 458 cm^-1 were assigned to be the C—H shear vibration mode of TBA⁺ cations in nCO₂·TBAB·26H₂O hydrate. They shifted away from each other and had lower less overlap region in nCO₂·TBAB·38H₂O hydrate. Those features in Raman spectra were helpful to distinguish the 2 kinds of structures. The PXRD patterns of the 2 TBAB hydrates showed large difference from each other. nCO₂·TBAB·26H₂O hydrate was tetragonal which had the space group of (P4/m), while nCO₂·TBAB·38H₂O hydrate was orthorhombic which had the space group of (Pmma). In the PXRD patterns, the peaks at 2θ=8.406° and 10.941° were (200) and (220) planes of nCO₂·TBAB·38H₂O hydrate respectively. The structure of nCO₂·TBAB·26H₂O hydrate was characterized by the (012) and (003) planes at 2θ=5.976° and 6.969° respectively. During the in situ Raman measurements, nCO₂·TBAB·26H₂O and nCO₂·TBAB·38H₂O hydrates grew directly from the prepared TBAB·26H₂O and TBAB·38H₂O hydrates at 276 K, 2 MPa. The CO₂ molecules were captured by the 5¹² hydrate cages in the 2 kinds of hydrates, formed the characteristic peaks of CO₂ at 1 275.4 and 1 379.3 cm^-1 and increased continuously. The Raman peaks at 1 110.3 cm^-1 were chosen as reference peak to compare the CO₂ concentration growth in the 2 kinds of hydrates. In the initial 75 minutes of in situ Raman measurements, the content of CO₂ in hydrate phase grew linearly with generally the same growth rates in 2 kinds of crystals. As the measuring spots were on the hydrate surface where the gas diffusion resistance in hydrate phase could be neglected and the cage structures used for gas storage were all 5¹² cage, the similar gas storage rates were obtained. The microcosmic experimental study provides a theoretical basis for CO₂ capture technology by forming TBAB semi-clathrate hydrate.
		2019 Vol. 39 (09): 2889-2893 [Abstract] ( 196 ) RICH HTML PDF (2791 KB) ( 47 )

	2894	Study of Photocatalytic Degradation of Antibiotics Based on UV-LED Array
		MA Li-zhe¹, JI Bang², YANG Zhou^2, HUANG Quan-feng¹, ZHAO Wen-feng^1
		DOI: 10.3964/j.issn.1000-0593(2019)09-2894-07
		The heavy use of antibiotics has caused great damage to the ecological environment. Photocatalytic technology is widely used in the degradation of pollutants because it is easy to operate and will not harm the environment again. In the process of photocatalytic degradation of antibiotics, the choice of light source is very important for the degradation efficiency of antibiotics. Compared with mercury lamps, which are usually used as photocatalytic light sources, UV-LED have higher energy efficiency and lower energy consumption. Therefore, the application of UV-LED technology has brought about huge changes in the photocatalytic process. First, this paper establishes a photocatalytic platform based on UV-LED array. The spectral characteristics of the LED array light source and the light field distribution in the device are measured and analyzed by a grating spectrometer and an UV illuminometer. The results show that the wavelength of the UV-LED source is between 265 and 295 nm, and its dominant wavelength is 275 nm. Due to the influence of the superposition of the light field, the radial intensity of the device increases significantly with the increase of the radial distance. The distribution of light intensity at the axial position is relatively uniform; Secondly, the particle structure of P25 photocatalyst is characterized by 3D microscope with super wide depth of field and UV-Vis technology. At the same time, the semiconductor derivative formula is used to analyze the band gap of P25. The results showed that the TiO₂ was spherical. Due to the excessive relative humidity in the air, the moisture on the surface of TiO₂ enhances the adhesion among particles. Therefore, the TiO₂ particles have agglomeration. And the band gap of TiO₂ is 3.1 eV. Finally, UV-LED and high pressure mercury lamp are used as the catalytic light source. Photocatalytic degradation of methyl orange (MO) and sulfonamides (SM₂) using P25 as a catalyst. Ultraviolet-visible spectrophotometer is used to measure the absorbance in the degradation process, and the degradation rate of antibiotics is further analyzed. The results showed that MO and SM₂ could be degraded under UV-LED array. After the catalytic degradation process of 160 and 240 min, the degradation rates reached 70% and 36%. It conformed to the first order kinetic equation. The degradation kinetics constants of MO by LED array light source and mercury lamp were -0.007 5 and -0.113 5 min^-1. The degradation kinetics constants of SM₂ were -0.001 9 and -0.019 4 min^-1. Therefore, the degradation rate of the mercury lamp is higher than that of UV-LED array in case of degradation analysis of MO and SM₂. In catalytic degradation of pollutants, UV-LED arrays and mercury lamp systems differ in power and in distance from the axis of the reactor, and an evaluation method for the degradation efficiency of antibiotics under two light sources was established. Distance degradation efficiency of UV-LED and mercury lamp at unit power standard was adopted in this paper. For MO, distance degradation efficiency of mercury lamp at unit power is larger than that of ultraviolet LED. For SM₂, distance degradation efficiency of the UV-LED array is larger than that of the mercury lamp. Based on the results of various spectral analysis and application above, UV-LED array is a competitive alternative to light source for photocatalytic. The widespread application of this technology provides a new way to degrade antibiotics.
		2019 Vol. 39 (09): 2894-2900 [Abstract] ( 174 ) RICH HTML PDF (4131 KB) ( 70 )

	2901	Sensitive Determination of Trypsin in Urine Using Carbon Nitride Quantum Dots and Gold Nanoclusters
		HU Xue-tao, SHI Ji-yong, LI Yan-xiao, SHI Yong-qiang, LI Wen-ting, ZOU Xiao-bo^*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2901-06
		Low level of trypsin has adverse impacts on digestion, and the obvious increase of trypsin may indicate the occurrence of pancreatitis or chronic renal failure. In addition, the secretory of trypsin outside of pancreatic tissue may involve a precursor to cancer. Trypsin concentration is closely related to life activities. Simple and timely monitoring of trypsin content can provide important reference value for disease diagnosis. Therefore, a sensitive and rapid fluorescent method was developed for determination of trypsin in urine based on carbon nitride quantum dots (CNQDs) and gold nanoclusters (AuNCs). CNQDs was synthesized via solvothermal treatment of bulk carbon nitride (C₃N₄) powder which was obtained by calcining melamine. The CNQDs displayed blue emission under radiation of UV light at 365 nm and the fluorescent band was at 440 nm. Albumin bovine serum (BSA) and CNQDs were used as reducing agents and stabilizers to prepare AuNCs which absorbed on the surface of CNQDs forming CNQD-AuNCs. CNQD-AuNCs with dual emission wavelengths at 440 and 650 nm displayed red fluorescence under radiation of UV light at 365 nm. BSA and AuNCs structure can be destroyed leading to aggregation of AuNCs in the presence of trypsin owing to the hydrolysis of BSA catalyzed by trypsin. Emission at 650 attributed to AuNCs is quenched and emission at 440 nm produced by CNQDs remain unchanged. The detection of trypsin can be performed by using fluorescent responses of CNQD-AuNCs. Fluorescent intensity at 650 nm gradually decreased with increasing trypsin concentration, while fluorescent intensity at 450 nm stayed unchanged. The ratio of fluorescent intensities at 650 and 440 nm had a perfect linear correlation with the concentrations of trypsin in the range of 10～400 ng·mL^-1 with a good coefficient (R²=0.997 6). The linear regression equation was y=2.471～0.004x, where x was the concentration of trypsin (ng·mL^-1), and y represented ratio of intensity at 650 and 440 nm. Limit of detection (LOD) for trypsin was calculated to be 1.5 ng·mL^-1 at a signal-to-noise ratio of 3. The concentration of trypsin in urine (the actual concentration was 50, 100 and 150 ng·mL^-1) detected by this ratiometric method was 52.41, 103.25 and 154.39 ng·mL^-1, respectively. The recoveries of trypsin were 102.93%～104.82% with relative standard deviations of 3.57%～4.16%. AuNC@CNQDs nanosensor provide build-in self-calibration for correction of a variety of unfavorable factors by using the ratiometric responses as signals to detect trypsin. The ratiometric method can overcome shortcomings of signal response which is susceptible to effects of external factors such as light bleaching, nanosensor concentration, excitation light intensity and optical path, and so on. In summary, the developed method has been applied for detection of trypsin in urine with high sensitivity and selectivity, providing scientific basis for detection of trypsin in real application.
		2019 Vol. 39 (09): 2901-2906 [Abstract] ( 183 ) RICH HTML PDF (3593 KB) ( 79 )

	2907	Study of the Rapid Measurement of COD by Laser-Induced Breakdown Spectroscopy
		ZHAO Xian-de^1,2, CHEN Xiao², DONG Da-ming^2*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2907-05
		Chemical Oxygen Demand (COD) is an important water quality parameter, which is generally used to reflect the degree of organic pollution. The detection of COD has long relied on laboratory chemical analysis methods after sampling. The most commonly used method is potassium dichromate oxidation and acid Potassium Permanganate oxidation. However, the chemical analysis methodsarecomplicated, time-consuming and labor-intensive. Moreover, the introduction of new chemicals by these methods causes secondary pollution. Therefore, there is an urgent need for a detection technique that enables rapid measurement of COD in water. Based on the previous research, the test method of COD by the laser-induced breakdown spectroscopy was explored in this paper. The focus was to optimize the model prediction speed in order to study therapid measurement of COD in waterbythe techniqueof laser-induced breakdown spectroscopy. We collected 99 water samples with different COD concentrations, and divided them into two groups: training set and testing set. The COD concentration of each water sample was measured by potassium dichromate oxidation method. And the spectral information of each water sample at the wavelengths of 200～1 000 nm was collected by the laser-induced breakdown spectroscopy acquisition system built by our laboratory. Partial least squares (PLS) algorithm was used to establish a quantitative measurement model for COD of training set samples and the spectral data of test set were predicted. The predicted results were compared with the real values measured by laboratory chemical methods to evaluate the predicted results. By analyzing the prediction model established by the original spectrum, it was found that a large number of laser-induced breakdown spectral data have poor correlation with COD concentration during the modeling process, and these useless data participated in the calculation, wasting computing resources, dragging the detection time, causing the system load to be too large, which was not conducive to the development of portable detection equipment. We focused on the first few principal components with the largest contribution. By analyzing the principle of COD measurement and the load of PLS model, we found the main characteristic peaks of LIBS spectrum which have the highest correlation with the concentration of COD in water. These characteristic peaks belong to C, H, O, N and some reductive ion elements in water. Most of C, H, O and N come from organic matter in water whose characteristic peaks have the greatest contribution to the prediction ability of COD model. The definition of COD reflects the amount of these elements in the water body, which is consistent with our analysis conclusion. In order to improve the detection speed, we extracted these characteristic peaks, and eliminated a large number of unrelated or low-correlation data. After many times of screening and dimensionality reduction, the original 13 622 data of each spectrum were reduced to 28, which greatly reduced the computational complexity of the system, but still retains good prediction ability. The 28 characteristic wavelengths selected are the best ones to reflect the concentration of COD in water, which lays a foundation for the development of portable multi-band detection equipment for COD in water and the rapid measurement of COD.
		2019 Vol. 39 (09): 2907-2911 [Abstract] ( 218 ) RICH HTML PDF (2132 KB) ( 51 )

	2912	Study on the Determination of Nitrate with UV First Derivative Spectrum under Turbidity Interference
		CHEN Xiao-wei^1,2,3, YIN Gao-fang^1,3, ZHAO Nan-jing^1,3*, GAN Ting-ting^1,2,3, YANG Rui-fang^1,3, ZHU Wei^1,2,3, LIU Jian-guo^1,3, LIU Wen-qing^1,3
		DOI: 10.3964/j.issn.1000-0593(2019)09-2912-05
		Nitrate is one of the “three nitrogen” (nitrate nitrogen, ammonia nitrogen, total nitrogen) in water, and it is an important indicator to reflect the degree of pollution for water quality. The traditional method for measuring nitrate has many shortcomings, such as operational complexity, time consuming, and it is difficult to meet the real-time online detection requirements of modern water environment. Nitrate has strong UV absorption characteristics in the ultraviolet region. And in recent years, the UV absorption spectroscopy has been widely used for nitrate measurements for its real-time, low cost and easy operation. However, when the ultraviolet absorption spectrum is used to detect the concentration of nitrate, it is easily affected by the turbidity in water, causing the nonlinear lifting of the spectrum and measurement error. At present, the research on turbidity compensation algorithm is mostly used for the detection of the concentration of COD in water, and there are few studies on turbidity interference removal in nitrate detection. In that case, a method for measuring concentration of nitrate based on first derivative ultraviolet absorption spectrum is proposed to reduce turbidity interference and improve the accuracy of rapid detection of the concentration of nitrate. Ultraviolet absorption spectrum of the formalin and sodium nitrate standard solution and their mixed solution are measured in the region from 190 to 300 nm. Its spectrum is processed by first derivative method. In the meantime, Savitzky-Golay filtering is used to smooth the processed spectrum. After comparing the characteristics of turbidity and nitrate ultraviolet absorption gained by first derivative spectrum, studying the effect of turbidity on the first derivative spectrum of nitrate of different region, the results show that the effect of turbidity is small in the region from 220 to 230 nm. So this region is selected as the spectral analysis interval, and 30 kinds of concentrations of mixed solution of formazin and sodium nitrate solution are used as training samples. The partial least squares algorithm is used to establish the nitrate quantitative analysis model. This model is used to predict the concentration of nitrate in the remaining six different concentrations of formalin and sodium nitrate mixed solution. The results show that the predicted coefficient of determination of nitrate measurement is 0.994 3 and RMSEP is 0.346 9 mg·L^-1 under the condition of formazin interference. In order to further verify the accuracy and stability of the method, the model was also used to predict the concentration of nitrate in mixed water samples prepared from kaolin and potassium nitrate. The results showed that the predicted coefficient of determination of nitrate measurement is 0.991 5 and RMSEP is 0.362 8 mg·L^-1 under the condition of kaolin interference. In summary, the method to detect the concentration of nitrate by UV first derivative spectrum is proposed in this paper. The data from the UV derivative spectrum in the region from 220 to 230nm data was adapted, and PLS algorithm was combined. So we can measure the concentration of nitrate in water under turbidity interference quickly and accurately. Moreover, this study laid the foundation for further implementation of online analysis of actual water and further development of equipment.
		2019 Vol. 39 (09): 2912-2916 [Abstract] ( 292 ) RICH HTML PDF (2220 KB) ( 83 )

	2917	Study on the Distribution of Ca Elements in Ammonite Stones Based on Micro LIBS
		HE Qiang^1,2, WAN Xiong^1,2*, WANG Hong-peng¹, YUAN Ru-jun^1,2
		DOI: 10.3964/j.issn.1000-0593(2019)09-2917-05
		The research on fossils can help scientists understand the biological evolution and judge the stratigraphic age. The change of geological elements in different ages is a popular topic in geological research. In order to study the changes of geological elements in different ages, we used Micro LIBS to study the element distribution in the ammonite stones. The asymmetric least squares method is used to remove the baseline of the spectral data, and we determine the optimal fitting parameters. The average normalization algorithm is used to reduce the relative standard deviation, and the multiple linear regression algorithm is used to calculate the regression equation of this model. First, the optimal experimental parameters were determined by preliminary experiments: the wavelength of laser is 1 064 nm, the frequency of laser pulse is 30 Hz, and the acquisition delay is 700 ns. Secondly, 12 pieces of rocks whose contents were already known were selected, 9 samples were randomly extracted for testing, and the remaining 3 samples were for predicting. Ca Ⅱ 393.186 nm，Ca Ⅰ 422.856 nm，Ca Ⅰ 445.572 nm，Ca Ⅱ 559.031 nm and Ca Ⅰ 616.61 nm were selected to establish the quantitative analysis model of Ca element with a prediction accuracy of 92.9%. Then, a 5×5 area was scanned to get a series of atomic spectrum data. According to the quantitative analysis model of Ca element, the lateral distribution map of Ca element can be got, and its horizontal resolution is better than 100 μm. Finally, the 6th, 11th, and 16th spectra data of each test point were selected for processing to get a lateral distribution map of Ca elements. The longitudinal distribution of Ca element in ammonite stones can be got by comparison. The Ammonite can not only be used as evidence to judge the age of the bottom layer, but also the elemental information of the bottom layer of the fossil can be inferred by studying the element distribution and content of Ammonite. This research has guiding significance for the evolution of the geology of shallow sea stratum and environmental changes.
		2019 Vol. 39 (09): 2917-2921 [Abstract] ( 194 ) RICH HTML PDF (2265 KB) ( 108 )

	2922	Quantitative Inversion of Water Quality Parameters in Industrial and Mining Cities from Hyperspectral Remote Sensing
		PENG Ling¹, MEI Jun-jun¹, WANG Na¹, XU Su-ning^1*, LIU Wen-bo¹, XING Gu-lian¹, CHEN Qi-hao²
		DOI: 10.3964/j.issn.1000-0593(2019)09-2922-07
		Industrial and mining cities are affected by activities of these industries that damage the water environment to various degrees and make water pollution a particular problem. At present, field sampling with a grid pattern and indoor laboratory analysis are mainly used for routine water quality monitoring. However, the environment is complex and variable, and spatial differences are considerable. Therefore, the survey sites render limited representativeness, low overall accuracy, and poor efficiency, making it difficult to realize dynamic monitoring regionally. In this study, we took Daye City under Huangshi City, Hubei Province, as the research area. Daye is an important mining city that thrives on mining. Unmanned aerial vehicle (UAV) hyperspectral imaging, ground spectral measurements, and water body sampling were carried out simultaneously. As a result, 49-band hyperspectral imaging data and water body spectra with a spectral resolution of 1 nm were obtained. The imaging data have a wavelength range of 505～890 nm, a spectral resolution of 7.78 nm, and a spatial resolution of 30 cm. After outlier removal, spectral calibration and radiometric correction were performed on the hyperspectral imaging data and spectral measurements and a comparative analysis was carried out between the spectral data of various water bodies located in the study area in terms of their absorption/reflectance spectra and the morphological features of their spectral curves. We subsequently extracted 25 spectral features from these hyperspectral images and measurement spectra, and these were classified under the following categories: morphological features of reflectance spectra, morphological features of continuum-removed spectra, morphological features of third-derivative spectra, and 4-value spectral encoding. The Pearson’s correlation coefficient was used to analyze the correlation between the water quality parameters and the spectral features of the water specimens and to select the water quality parameters and spectral features that were significantly correlated with each other. On this basis, a multivariate linear inversion model was constructed for the water quality parameters using the following model variables, which were selected via stepwise regression analysis: the maximum reflectance and its corresponding wavelength, symmetry, and spectral code Ⅲ, and the maximum and minimum third derivative values. F-tests and t-tests were then performed on this model. After the tests, our inversion model was used to obtain the water quality parameters of typical water bodies, such as tailings ponds, rivers, and lakes, from the hyperspectral imaging data from the study area. We have thus succeeded in achieving the rapid acquisition of water quality information in a “point-to-surface” manner. The results of this study indicate that our model has high inversion accuracies for water quality parameters such as pH, hardness (Ca²⁺+Mg²⁺), potassium-to-chloride ratio (K⁺/Cl^-), and magnesium-to-alkalinity ratio [Mg²⁺/(HCO^3-+CO^2-₃)]. Between these parameters, pH has the lowest coefficient of determination (R²) of 0.669, whereas the magnesium-to-alkalinity ratio has the highest R² of 0.895. The relative root mean square errors (RRMSE) were generally lower than 28%. In contrast, the inversion accuracy of our model for total dissolved solids (TDS) was relatively low, and its R² and RRMSE were 0.463 and 36.762%, respectively. This study proposes a hyperspectral remote-sensing quantitative inversion method of water quality parameters based on spectral curve patterns. The method achieves hyperspectral quantitative inversion of water quality parameters such as pH, hardness and magnesium-to-alkalinity ratio, and it provides a new technique for dynamic monitoring of the regional water environment.
		2019 Vol. 39 (09): 2922-2928 [Abstract] ( 314 ) RICH HTML PDF (5428 KB) ( 106 )

	2929	XRD and NIR Analysis of Oxidation Particles in Dabashan Polymetallic Deposit and Its Significance
		DENG Yong-kang^{1, 2}, CAO Jian-jin^{1, 2*}, DANG Wan-qiang^{1, 2}, WANG Guo-qiang^{1, 2}, LIU Xiang^{1, 2}, LI De-wei^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2019)09-2929-06
		XRD and NIR techniques were used to analyze the seven oxide sample particles in the lower sub-group oxidized ore of the Dabaoshan dong Gangling Formation. The first four samples were of the same elevation and the latter three samples were of different elevations. XRD and NIR results show that as the degree of oxidation deepens (04-2→04-3→04-4), the wavelength corresponding to the absorption peak of Al—OH mineral increases continuously (2 160.72→2 163.05→2 200.36 nm). It is indicated that the cationic Al in the mineral is substituted, resulting in an Al-poor phenomenon; and the corresponding peak intensity is from 7.08×10^-4, 7.83×10^-3 to 6.66×10^-2, which indicates that the content of Al—OH minerals is increasing; in addition, the intensity of the absorption peak corresponding to SO^2-₄ mineral (1 938.80→1 946.94→1 926.47 nm) is from 5.635×10^-2, 1.82×10^-2 to 1.668×10^-2. It is indicated that the content of SO^2-₄ minerals decreases with the progress of oxidation. Combined with previous studies, we can speculate that the early formation of copper polymetallic sulphide deposits will undergo strong oxidation in the later stage, causing the sulfide ore bodies to oxidize. Oxidation forms a strongly acidic sulfuric acid solution, and the surrounding rock is corroded by a sulfuric acid solution to convert it into loose clay; Sodiumalumite and potassium alumite were found in samples 04-2, 04-3, 13-1. A large number of strontium minerals indicate that the oxidative leaching of the ore is still ongoing; Minerals such as quartz, sericite, calcite, epidote, hornblende, tremolite, phlogopite, chlorite, kaolin, etc. have been discovered by XRD and NIR techniques, which reflect the type of alteration, and the geological features of the area are consistent. At present, near-infrared spectroscopy has been used for alteration mapping in mineral deposit exploration. In this paper, the relationship between the deep oxidation process of the deposit and the cation substitution was discovered by means of spectroscopy, and the interpretation of the genesis of the Dabaoshan deposit was verified by the spectroscopy. The results of this paper show that on the one hand, XRD and NIR can effectively analyze the mineral composition of soil and rock, and provide services for the ore deposit research in this area. On the other hand, NIR can reflect the ion transfer and the sharpness of the peak reflects the crystallization. The intensity of the peak reflects the mineral content, and these unique advantages make it possible to study the oxidation of minerals from a microscopic point of view. However, there is one point that needs to be pointed out. Compared with the research of NIR and X-ray diffraction in other fields, the application of these two technologies in geology needs to be further deepened, including the theoretical basis for the application to geology research and analysis and interpretation of the spectrum, in order to not only analyze the corresponding mineral types by spectroscopy, but also quickly analyze the content of different minerals and different configurations of the same mineral.
		2019 Vol. 39 (09): 2929-2934 [Abstract] ( 158 ) RICH HTML PDF (4244 KB) ( 59 )

	2935	Research on Parameter Measurement of Cataclysmic Variable Stars
		JIANG Bin, ZHAO Yong-jian, WANG Lu-yao, WEI Ji-yu, QU Mei-xia^*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2935-05
		Cataclysmic variable star is a kind of special and rare binary system, of which the primary star is a white dwarf and the companion is normally a G, K or M-type late star or dwarf. CVs usually have very large outbursts and have positive significance for the study of the evolution of close binary stars. According to the characteristics of explosion and light variation, CVs can be divided into many subtypes, such as nova, recurrent nova, nova-like stars, dwarf nova and magnetic CVs. As a periodic variable star, the spectra of CVs are very complex. At present, the parameter measurements of CVs focus on the distance and the orbital periodic etc. Since matter accumulates on the surface of a white dwarf during accretion, it is not possible to directly measure the physical parameters of the main star. What is more, CV is a kind of faint celestial body and the number of its spectra is limited. Therefore, the study of the physical parameters of the CVs is greatly restricted. The only software currently capable of generating the spectra of CVs is CLOUDY with a photoionization model. But the number of sampling points of CLOUDY is limited and there are too many parameters. The spectra produced by CLOUDY cannot be used as ideal theoretical template. The high resolution spectra of ELODIE in France can be used as a theoretical template for measuring the spectral parameters of M-type stars of CVs. In order to compensate the blank of the spectral parameter measurement of CVs, in this paper, spectra with parameters from ELODIE are used as template spectra and 407 SDSS CVs spectra detected by data mining method before are measured by template matching. Most of these spectra are in quiet state and the main characteristic of the spectra are emission lines of Barmer and Helium. In order to reduce the computation, the feature extraction and dimension reduction of high-dimensional spectra are carried out by principal component analysis and local linear embedding. The experimental result shows that the LLE method has a maximum contribution rate of 94.91% with the neighborhood size of 15 and the dimension number of 59. According to the intersection of PCA and LLE, the final dimension of the spectra was determined to be 59. In the experiment, it is found that the number of M2 type companion is limited, and more samples are needed to explain the specific resaons. Because only some of the experimental cataclysmic variable spectra have distinct molecular bands, the spectra in decline stage are ignored. The experiment in this thesis makes up the gap of measurement of physical parameters of the spectra of the CVs.
		2019 Vol. 39 (09): 2935-2939 [Abstract] ( 201 ) RICH HTML PDF (3241 KB) ( 52 )

	2940	Spectral Characterization of Electrodeposited Cu₂ZnSnS₄ Thin Films on Fluorine-Doped Tin Oxide
		SONG Si-yue, LIU Xu-wei, LIN Hong-xiao, WANG Xue-jin^*，HE Zhi-wei
		DOI: 10.3964/j.issn.1000-0593(2019)09-2940-06
		Low cost and environment friendly Cu₂ZnSnS₄ (CZTS) is the best candidate to replace CuIn_xGa_1-xSe₂ (CIGS) which owns noble and toxic metal for thin film solar cells. Electrodeposition technique is a low cost method where vacuum equipment and target materials are not required. A simpler fabrication method is co-electrodeposition of Cu-Zn-Sn (CZT) alloy on fluorine-doped tin oxide (FTO) in aqueous solution. In this paper, CZTS thin films were successfully prepared by sulfurization of electrodeposited CZT alloy precursors at 550^oC in protective argon gas. The CZT precursors were electrodeposited on FTO via a three-electrode system in which FTO is used as working electrode, platinum (Pt) mesh and Ag/AgCl as counter and reference electrodes. The electrolyte contains CuSO₄, ZnSO₄, SnSO₄, complexing agent-Triethanolamine (TEA) and sodium citrate. The precursors were sulfurized by sulfur vapor at 550 ℃ in protective argon gas and then CZTS films were obtained. The structural, morphological, compositionaland optical properties of CZTS films have been characterized by X-ray diffraction (XRD), Raman spectroscopy, scanning electron microscopy (SEM), UV-vis spectroscopy and photoelectrochemical measurement (PEC). XRD and Raman spectroscopy have confirmed the kesterite structure of CZTS films sulfurized at 550 ℃. One major peak at 342 cm^-1 and two second strong peaks at 289 and 370 cm^-1 are observed in the Raman spectra, which agree with those reported from kesterite CZTS. SEM shows chemical composition of optimum CZTS film is near that of stoichiometric CZTS. The ratios of Cu/(Zn+Sn) and S/(Zn+Sn+Cu) in CZTS film are 0.52 and 1.01, respectively, which indicates that the content of S in “copper poor” CZTS film is very suitable. The photocurrent of the “copper-poor” CZTS film was measured by PEC. PEC results confirm that light current is produced by FTO/CZTS under front/back irradiation, and the photocurrent flows in the same direction in both cases. The band gap of CZTS is 1.45 eV. It is shown that high-quality CZTS thin films have been prepared via above analysis.
		2019 Vol. 39 (09): 2940-2945 [Abstract] ( 157 ) RICH HTML PDF (2509 KB) ( 56 )

	2946	Vibrational Spectra and Isotope Effect of Dihydroxylammonium 5,5’-Bis(Tetrazole)-1,1’-Diolate under High Pressure
		ZHAO Sheng-xiang¹, SONG Xue-yan², XING Xiao-ling¹, LI Yan², JU Xue-hai^2*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2946-07
		Density functional theory calculations were performed on crystalline dihydroxylammonium 5,5’-bis(tetrazole)-1,1’-diolate (HATO) under high pressure up to 40 GPa. The GGA-PW91 method in combination with the ultrasoft pseudopotentials reproduced the experimental crystal structure of HATO and was thus employed for the optimizations of both molecular structure and cell parameters. The intermolecular O…H distances generally decrease with increasing pressures. However, the O—H and N—H bond lengths change irregularly upon pressure. Based on the optimized crystal structures at different pressures, the non-periodic calculations of frequencies with a scaling factor of 0.967 9 were used to predict both the IR and Raman spectra. The predicted strongest Raman peak at 1 580 cm^-1, involving C—C stretching and NH₂ symmetric deformation, is in agreement with the experiment. Although there is no hydrogen atom in the anion moiety of HATO, the deuteration in cation still affects the vibrational mode of anion. For O—H and O—D vibration modes, the Raman shifts decrease due to the strengthening intermolecular hydrogen bond as the pressure increases. Upon deuteration, the most characterized change of Raman shifts for ND₂ is that the ν₂ stretching mode increases dramatically with high pressure as compared to those of NH₂, which leads to a coupling of ND₂ ν₂/ν₃ modes at high pressure. The calculated isotopic ratios, ν(NH₂)/ν(ND₂) for ν₁ to ν₃ modes, are in the range of 1.36～1.38, which are in consistent with the value from the reduced masses of these atoms. The couplings of vibrational modes change with both deuteration and pressure.
		2019 Vol. 39 (09): 2946-2952 [Abstract] ( 198 ) RICH HTML PDF (2712 KB) ( 50 )

	2953	Research on Relationship between Spectral Characteristics, Physical Parameters and Metal Elements of Rocks in Xingcheng Area
		YANG Chang-bao¹, LIU Na^2*, KUAI Kai-fu³
		DOI: 10.3964/j.issn.1000-0593(2019)09-2953-13
		The relationship between physical parameters, elemental content and spectral characteristics is not independent, which lays a foundation for exploring quantitative inversion methods of mineral contents and physical parameters of rocks through remote sensing information.This paper studies the relationship between spectra, physical parameters (density, magnetic susceptibility, resistivity, permittivity)，metal contents (Fe, Ti, V, Mn, Zr, Co, Zn, Nb, Bi, Pb) of 590 rocks in Xingcheng Area. Correlates the physicochemical parameters with original spectra, spectral absorption depths, and high and low frequencies after spectral wavelet packet decomposition, finds out the characteristic bands of the physicochemical parameters affecting spectral absorption and reflection, and explores closely related parameters. This study lays the foundation for lithology classification of rocks, inversion of certain metal elements and physical properties, and prediction of closely related parameters with certain parameters. This article mainly achieved the following results. (1)The characteristic bands of Fe, Ti, Mn, V, Zn, Bi and Pb in igneous rocks are obtained. The Fe content of igneous rock is higher, and the correlation with spectra is more significant. Characteristic reflection bands of Fe exist near the 0.4 and 0.54 μm bands, and characteristic absorption bands exist in the range of 1.0～1.5 μm. In the range of 0.4～0.55 and 0.6～0.65 μm, correlations between Ti and the spectra are more significant. There is a characteristic absorption band of Ti near 2.28 μm band and a characteristic reflection band of Mn exists in 0.41 μm band. The correlation between spectra and V element of igneous rock is different from that of sedimentary rocks. Moreover, characteristic absorption bands of igneous rocks and characteristic reflection bands of sedimentary rocks may exist near 0.76, 0.81, 0.89 and 0.95 μm bands. The correlation between spectra and Zn content of sedimentary rocks is more significant than that of igneous rocks. There may be Zn characteristic reflection bands of igneous rocks near 0.41, 1.36 and 1.59 μm bands, and Zn characteristic bands of sedimentary rock near 2.34 μm band. In the vicinity of 2.14 μm band, Bi element has effects on spectra absorption of sedimentary rocks. The characteristic band of Pb may exist near 0.45, 0.54, 2.29 μm band. In the study of the relationship between physical properties and spectra of rocks, the density has significant spectral absorption and reflection characteristics in the range of 0.57～0.8 μm bands. Susceptibility makes spectra have strong reflection near the 0.53 μm band, and susceptibility gives spectra spectral absorption near the 1.08 μm band. Correlations between resistivities and spectra are similar to those between densities and spectra. In the correlation between various physical parameters of rocks, it is found that density is significantly positively correlated with resistivity. (3) In the relationship between various physical parameters of rock, it is found that density and resistivity are significantly positively correlated. (4) In the relationship between various physical parameters and metal elements of rocks, it is found that the correlation between density and metal elements is weak. The susceptibility is significantly positively correlated with Fe and Ti. The correlation between resistivity and metal elements is weak. The permittivity is positively correlated with metal elements. And correlations between V, Zn and Bi elements are the most significant. (5) There are significant positive correlations between Fe and Ti, positive correlations between Ti, Fe and V elements, and positive correlations between Zn and Pb.
		2019 Vol. 39 (09): 2953-2965 [Abstract] ( 166 ) RICH HTML PDF (5664 KB) ( 62 )

	2966	Stability and Structural Characterization of Chelated Fertilizers
		HE Jiang-long, HUANG Ming-li, LI Ling-yu, NIE Zhao-guang, GENG Cun-zhen, YAN Dong-yun^*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2966-08
		In recent years, agricultural intensification and the need for reduced fertilizer application have rendered soil remediation and agricultural non-point-source pollution control globally significant. Compared to inefficiently utilized inorganic salt fertilizers, chelated fertilizers are more efficient and environmentally friendly, and have thus attracted considerable attention. In the new international context, more attention is being paid to soil remediation and reductions in agricultural non-point-source pollution, as the demand for high-quality agricultural products increases. Chelating fertilizers may play important roles in these contexts; models of stability and structure are required to provide both the theoretical basis for further development and data supporting continuing research and development. The stability constant reflects the stability of a chelated material; the stability constants of chelates can be calculated mathematically using the generating, Leden, and/or Fronaeus function (s). Although no standard method is yet available for the determination of stability constants, a great deal of relevant work has been performed worldwide. However, most methods are not yet mature, and appropriate stability constant reference values remain controversial. Since most of the fertilizers analyzed used amino acids for chelation, other ligands hardly received attention, potential applications of other ligands should be fully exploited. The molecular structure of a compound determines its properties. Structural characterization contributes to the qualitative analysis of chelated fertilizers, improves the understanding of experimental phenomena, and affects the selection of detective methods. The first consideration is whether the chelate is pure. Even if the levels of impurities are low, reliable structural data can be difficult to obtain. Therefore, we systematically summarize progress in how chelated fertilizer stability is assessed and how such fertilizers are structurally characterized. We focus on the advantages and disadvantages of various processes, outlining the need for future research. And we provide a theoretical basis for the development and effective utilization of chelated fertilizers.
		2019 Vol. 39 (09): 2966-2973 [Abstract] ( 169 ) RICH HTML PDF (414 KB) ( 55 )

	2974	Overlapping Green Apple Recognition Based on Improved Spectral Clustering
		LI Da-hua¹, ZHAO Hui^2*, YU Xiao³
		DOI: 10.3964/j.issn.1000-0593(2019)09-2974-08
		Fruits target recognition is one of the most important steps to realize agricultural automation. In the process of fruit recognition, because of the influence of overlap and occlusion, the target recognition is difficult, and the rate of recognition is not high. The paper uses spectral clustering algorithm to solve the problem of overlapped fruit in natural environment. Then the identification and location of fruit are realized by randomized hough transform. In view of the large number of computation and the slow operation speed of the traditional algorithm, this paper proposes an improved spectral clustering algorithm based on Mean Shift and sparse matrix principle. Firstly, the image is pre-segmented using the mean shift algorithm. Mean shift is a non-parametric estimation method for density gradient. The algorithm is essentially an iteration. Calculate the offset, move the point according to the offset, and repeat the above steps until the offset is zero. Most of the background pixels are removed by mean shift algorithm, and the removing is prepared for reducing the computational complexity of the spectral clustering algorithm. And then the useful information is extracted, which is the description of the similarity between the pairs of pixels in the image, and the extracted image feature information is mapped into a sparse matrix. The K-means algorithm is used to classify it into classes, and the final classification result is obtained to realize the re-segmentation of the reprocessed image. Then the color of the image segmentation area is restored, the edge contour is extracted by using a color vector gradient and the randomized hough transform is used on the resulting contour image, and the radius parameter range during the detection process is set to further accelerate the speed of the algorithm. The center coordinates and radius of the target can be obtained through the detection. Thereby the overlapped green apples are recognized. Finally, the algorithm has the high coincidence degree of 95.41%, the low error rate of 4.59% and the false detection rate of 3.05% through experimental analysis and algorithm comparison, and the algorithm meets the practical application requirements.
		2019 Vol. 39 (09): 2974-2981 [Abstract] ( 183 ) RICH HTML PDF (2151 KB) ( 74 )

	2982	Synthesis and Spectroscopic Investigations of Four New Y(Ⅲ), Ge(Ⅳ), W(Ⅵ) and Si(Ⅳ) Penicillin Antibiotic Drug Complexes
		Abeer A. El-Habeeb¹, Moamen S. Refat^2,3*
		DOI: 10.3964/j.issn.1000-0593(2019)09-2982-07
		A four new penicillinate complexes were prepared through the chemical interactions of penicillin potassium salt (Pin) with YCl₃, GeCl₄, WCl₆ and SiCl₄ metal ions. These metal complexes were characterized using spectroscopic techniques (e.g. ¹H-NMR, infrared, electronic UV-Vis) as well as elemental, conductivity, and magnetic measurements. The molar conductance values were highly, showing their electrolytic nature. The magnetic and electronic study strongly recommends the octahedral geometry of all penicillinate complexes. A monomeric structures of Pin complexes are proposed with octahedral coordinated metals ions. The metal ions are coordinated toward Pin as tridentate ligand through the amide and β-lactam carbonyls and a carboxylate group from penicillin. The in vitro antimicrobial activity of all the complexes, at concentrations in μg·mL^-1, was screened against four bacterial pathogens, namely, Bacillus subtilis, Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus, and two kinds of fungi Aspergillus flavus and Candida albicans showed better activity compared to parent drug and control drug. The anti-cancer inhibition of the tungsten(Ⅵ) complex was assessed against the human hepato cellular carcinoma (HepG-2) tumor cell line with IC50 value is 646 μg·mL^-1.
		2019 Vol. 39 (09): 2982-2988 [Abstract] ( 144 ) RICH HTML PDF (1357 KB) ( 56 )

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