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2019 Vol. 39, No. 12 Published: 2019-12-01

	3653	Research on the Identification of Chemical Weapon Based on PGNAA Technology
		TANG Ya-jun¹, JIA Wen-bao^{1, 2}, HEI Da-qian^{1, 2*}, LI Jia-tong¹, CHENG Can¹, CAI Ping-kun¹, SUN Ai-yun¹, ZHAO Dong¹, HU Qiang¹
		DOI: 10.3964/j.issn.1000-0593(2019)12-3653-06
		Identifying the unknown chemical weapons is an important work for maintaining social security, and it can guide the chemical weapons destruction. Prompt gamma-ray neutron activation analysis (PGNAA) technology has the advantages of being non-destructive and rapid. In this research, the device was designed for identifying the chemical weapons based on PGNAA technology, and logic-tree-based discrimination method was employed to conduct qualitative analysis on samples.Firstly, with the high purity germanium (HPGe) detector and Cf-252 neutron source as the core instruments, the structures of device were optimized using the Monte Carlo MCNP code, including neutron source moderator, the thickness of the shielding body, and the relative position of the detector. To maximize the characteristic gamma ray generated by sample activation, it is necessary to increase the thermal neutron flux in the sample. In this research, polyethylene is used as moderator to increase the scattering of neutrons before the sample, so that more neutrons are thermalized. The simulation results showed that the thermal neutron flux in the sample reaches a high level when the polyethylene has a thickness of 6 cm and a width of 12 cm. In order to reduce the interference of the surrounding material activation noise, lead is selected as the shielding structure. And the simulation showed that it can meet the shielding requirement when the lead shielding thickness reaches 5 cm. At the same time, the distance between the detector and the sample also affects the detection of gamma rays. The final simulation determines that the distance between the detector and the sample is 28 cm, and the characteristic signal count is the highest.According to the optimization results, the experimental device was set up. And the simulated samples of chemical weapon were prepared according to the actual elements by using the analytical pure reagent, and the gamma spectrum was obtained by measuring the five samples. In the process of analyzing the characteristic peaks in the spectrum, the elements were analyzed based on the characteristic peaks of the elements. The elements with well statistic were analyzed by using gauss and polynomial fitting (such as H, Cl, S). The high-energy Compton platform at the characteristic peak was deducted to obtain the full peak information. For the element characteristic peak with poor statistic (such as 10.829 MeV of the N element), the energy interval summation method was used to sum the counts between the full peaks and the single escape energy peaks, so we can get the information of the elements in the sample. Finally, the logic-tree-based discrimination method was used for sample identification. The analysis results showed that the information of H, Cl, S, N and other elements in the simulated samples of chemical weapons can be obtained by using the spectrum fitting method. And the type of simulated samples of chemical weapon can be identified by combining logic-tree-based discrimination method.
		2019 Vol. 39 (12): 3653-3658 [Abstract] ( 211 ) RICH HTML PDF (3270 KB) ( 106 )

	3659	Progress on Terahertz Spectroscopic Detection and Analysis on Antibiotics
		LI Bin, ZHAO Xu-ting, ZHANG Yong-zhen, CHEN Yi-mei
		DOI: 10.3964/j.issn.1000-0593(2019)12-3659-08
		Antibiotics have the property of treating various bacterial infections and pathogenic microorganisms. The absorption spectrum of antibiotics for detection can effectively monitor and control its addition, which is of important significance and value in the fields of medicine, animal husbandry and aquaculture et al. Terahertz time-domain spectroscopy ( THz-TDS) is a brand-new spectrum detection tool featuring being non-destructive, high-efficient and convenient, which owns great application potentials and bright prospects in many fields such as national defense security, information communication, materials, environment, biomedicine, agriculture and food safety. This paper introduced the structure and working principle of the terahertz time-domain spectroscopy detection system, and summarized the research progress of terahertz time-domain spectroscopy on antibiotics detection. The identification and quantitative analysis methods on main antibiotics such as β-indoleamines, aminoglycosides and tetracycline, quinolones, macrolides, sulfonamides, etc. were induced. The development trend and unsolved problems of terahertz time-domain spectroscopy on antibiotics detection were then presented, which provides a reference for future development of qualitative and quantitative rapid detection instruments.
		2019 Vol. 39 (12): 3659-3666 [Abstract] ( 245 ) RICH HTML PDF (1889 KB) ( 124 )

	3667	Synthesis of Carboxyl Functionalized Photoluminescent Nano-SiO₂ Fingermark Reagent
		CHEN Yu-tai¹, HUANG Wei², JIANG Hong^1, WANG Yuan-feng^{3, 4}
		DOI: 10.3964/j.issn.1000-0593(2019)12-3667-06
		Fingermark detecting is very important for individual identification over the past decades. However, the health of forensic technicians and our environment had been damaged seriously by these methods. The new method of Nano Particles Reagent for fingermark detection can effectively reduce the nano-dust suspending in the air, andrecover the technicians’ health and environment as well. It also resolved the problem of the disposal of dispersant and organic dye. The research focuses on the synthesis of fluorescent nanosilica functionalized by carboxyl and the migrating of latent fingermarks. In this study, nanoscale silicon dioxide doped with fluorescent dyes was prepared by reverse microemulsion method, and the Tris(2,2’-bipyridine)ruthenium(Ⅱ) chloride hexahydrate was used to make the nano silica luminescent. Amino modification was accomplished by aminosyl-silane coupling agent. Carboxyl modified fluorescent fingermark developing reagent based on silica nanoparticles was prepared by ammonolysis of butyl two anhydride. The surface chemical groups, fluorescence properties, dispersibility in aqueous phase, surface electrical properties and particle size of the target objectives were characterized by infrared spectroscopy, ultraviolet-visible absorption spectroscopy, Zeta potential-DLS tester and micro-spectrophotometer, respectively. The influence of dye concentration on the fluorescence intensity of products was studied. It was found that the electrical ionization efficiency, the concentration of nano-particles and the migrating time can directly impact the development. As a result, the three-factor orthogonal experiment was designed to explore the effects of pH value, dilution multiple and display time on the display effect in this study. The developing conditions of the fingermarks deposited on aluminum foil surface were preliminarily explored. Some conclusion was presented that the molecular structure of fluorescent dye remained comparing to the maximum absorption before reacting with silica, and 15 mmol·L^-1 was the best concentration. The surface modifications of amino and carboxyl were accomplished, and the 375 nm was the exciting wavelength. The nanostructure of the objective in suspension was confirmed. According to the charge characteristic in the suspension, it was proved that the modified silica was positively and negatively charged by amino and carboxyl groups respectively. The product could migrate the fresh and aged fingermarks on non-porous surface in the condition: pH 2.8, double dilution, and 5 minutes. The carboxylic nano-SiO₂ suspension is an effective method of fingermarks detecting, and according to the smoothness degree, the more detailed features could be obtained.
		2019 Vol. 39 (12): 3667-3672 [Abstract] ( 177 ) RICH HTML PDF (3212 KB) ( 76 )

	3673	Research Progress on On-Orbit Calibration Technology for Far Ultraviolet Payload
		FU Li-ping^1，2, JIA Nan^{1, 2，3}, HU Xiu-qing^4*, MAO Tian⁴, JIANG Fang^1，2, WANG Yun-gang⁴, PENG Ru-yi^1，2, WANG Tian-fang^1，2,3, WANG Da-xin³, DOU Shuang-tuan³
		DOI: 10.3964/j.issn.1000-0593(2019)12-3673-08
		Far Ultraviolet wavelengths (FUV 115 to 200 nm) optical remote sensing detection on satellite is one of the most promising technologies on space weather. This technology can be effectively used to obtain some important space environment parameters, such as O, N₂, O₂ column density and profile distribution, total electron content (TEC) of ionosphere and electron density profile. It also yields valuable information on content of plasma, temperature profile of the atmosphere, solar EUV flux and energy particle. In the processes of obtaining these physical parameters quantitatively there is one key step—the radiation calibration, including pre-launch laboratory calibration and on-orbit calibration: the former gives original calibration coefficient of the load before launch; the latter checks the change of the calibration coefficient of the instrument’s on-orbit performance after a set period. In the West, FUV technology application to upper atmosphere, ionosphere, magnetosphere and solar activity started in the 1970s, and has been applied to the long-term Space Weather Program Strategic Plan by U. S. federal government. In China, this technology was carried out at the beginning of the 21^st century, and the in-flight calibration is still a research gap now. This paper introduces on-orbit calibration technologies for some representative far ultraviolet payload based on the external standard radiation source, internal radiation standard source and vicarious calibration, and then analyses the data processing method and the results on three kinds of FUV remote sensing: Imager, Spectrometer Imager and Photometer. The results suggest that the best on-orbit calibration method for imager or spectrometer imager is using UV stellar as an external radiation standard; the instrument can catch the known radiation from the stellar; using the radiation from the stellar and the spectral responsibility from the lab, the sensitivity of the instrument will be known as in-flight. The internal standard radiation source, like deuterium lamp, is not a good choice for in-flight calibration becauseradiation itself from lamp attenuates. On single-point detection instrument, like a photometer with limited visual field, the vicarious calibration is a good way to realize on-orbit calibration. During the process of calibration, data selecting and spatio-temporal matching should be cautiously conducted in order to enhance the calibration accuracy.
		2019 Vol. 39 (12): 3673-3680 [Abstract] ( 206 ) RICH HTML PDF (6020 KB) ( 86 )

	3681	Study of the Influence of Common Gas Pollutants on the Silk Fabric Structures Based on Infrared Spectroscopy
		WANG Li-qin, YOU Rui, ZHAO Xing
		DOI: 10.3964/j.issn.1000-0593(2019)12-3681-05
		As silk is made up of proteins, their structures are easy to be changed by high temperature, high humidity, pollutants and other factors. In order to scientifically evaluate the influence of pollutant gases on silk fabrics structures, artificial simulated experiments were conducted to prepare common pollutant gas environments in museums, including nitrogen dioxide, sulfur dioxide, acetic acid and ammonia. The effects of the four kinds of pollutant gases on protein peptides, secondary structures and other aspects were investigated using Fourier transform infrared spectroscopy (FTIR). The experimental results showed that for silk fabrics aging with nitrogen dioxide for 30 h, there arose the peak of the methyl symmetric deformation vibration, near 1 382 cm^-1, which did not appear on the samples aging with other gases for 50 days. It was shown that nitrogen dioxide had the most serious damage to silk fabrics. After aging with all pollutant gases, the absorption peaks of -Gly-Ala- and -Gly-Gly-peptide chains (primary structure) at 975 and 999 cm^-1 were all reduced in varying degrees, but the effect of the alkaline gas ammonia on the peptide chains was more obvious than that of other acidic gases. The deconvolution of the amide Ⅲ band (1 330～1 200 cm^-1) and Gaussian fitting results showed that the samples aging with ammonia for 50 days had only slight changes in the amorphous region with slight content changes of α-helix, random coil and β-sheet, and the secondary structures of silk protein did not change much. In comparison with ammonia, acid gases had a significant influence on the secondary structures of silk protein. The relative content of β-sheet was greatly reduced with that of random coils increasing significantly, and the crystalline region was damaged seriously. Among the four gases, nitrogen dioxide has the most significant effect on secondary structures of silk fabrics. The relative content of β-sheets decreased from 30.36% to 18.12% after 30 hours’ aging, which reduced about 40%. The nitrogen dioxide had the most serious damage to the strength of silk fabrics. With the declining of the β-sheet, the mechanical strength of the material decreased. The ratios of infrared absorption peaks at different wavenumbers A_{1 700/1 640} and A_{1 620/1 514} were used to judge the aging modes. Oxidation reaction occurred mainly to the samples aging with nitrogen dioxide, sulfur dioxide, and ammonia. Both oxidation and hydrolysis reaction happened to the samples aging with acetic acid. With the increase of aging time, the ratio of A_{1 620/1 514} of the samples aged with nitrogen dioxide increased most among the four gases and the oxidation was the most severe. It was inferred that it was related to the strong oxidizing property of nitrogen dioxide, also associated with the significant methyl symmetry vibration occurring of the silk fabric aging with nitrogen dioxide. It is suggested that the concentration of nitrogen dioxide gas should be strictly monitored and controlled in museums. This study provides a scientific basis for formulating a reasonable storage environment for silk cultural relics, and is of great significance to the protection of silk cultural relics.
		2019 Vol. 39 (12): 3681-3685 [Abstract] ( 248 ) RICH HTML PDF (1440 KB) ( 79 )

	3692	Dynamic Diagnostic of Physical Property in P-TIG Argon-Nitrogen Shielded Arc Plasma with Optical Emission Spectrometry
		XIAO Xiao^1,2, LI Fang^2*, HUA Xue-ming², ZHANG Ke-ke¹
		DOI: 10.3964/j.issn.1000-0593(2019)12-3692-06
		The welding property was decided by the physical characteristic of the arc plasma, and the dynamic property of two-element arc plama which was produced by pulse tungsten inert gas welding(P-TIG) with hybrid shielding gas was analyzed, which provides a theoretical basis for further research on the physical process of weld in hybrid gas shielded welding. Argon-nitrogen arc plasma was used to improve penetration since it has high thermal property, but demixing during welding complicated its physical characteristic. Spectral diagnosis is the most important means to measure the physical characteristics of arc plasma, but the further research on the arc characteristics of P-TIG welding with hybrid sheilding gas is still needed, especially during the arc ignition time. In this paper, an argon-nitrogen arc plasma produced by P-TIG welding during arc ignition is studied, the high-speed camera experiment system is proposed to collect the dynamic spectrum information of arc plasma, and the dynamic intensity of Ar Ⅰ 794.8 nm and N Ⅰ 904.6 nm under P-TIG welding arc was obtained; temperature and concentration of 1, 2, 3 and 4 mm under tungsten during arc ignition were calculated by Fowler-Milne method; and the physical characteristics of 80%Ar+20%N₂ shielded P-TIG welding arc plasma were quantitatively analyzed. The results show that the change of arc intensity, temperature and concentration is synchronized with the current. The welding current reaches a stable state within 3 ms, while the intensity, temperature and concentration of the arc plasma take longer time to reach equilibrium state. From arc ignition to steady burning, the arc intensity presented a trend of increasing first and then decreasing during the base and peak period. As a result of changes in heat conduction and current density of the cathode, the peak temperature and base temperature in the axial position of arc plasma increase rapidly and then decrease slowly. Due to the impact of particles collision and friction, the concentration of argon decreases rapidly and increases slowly during both the peak and the base period of arc plasma, and is lower than the original value.
		2019 Vol. 39 (12): 3692-3697 [Abstract] ( 207 ) RICH HTML PDF (4038 KB) ( 55 )

	3698	Research on Dissolution Crystallization Kinetics of Na₂SO₄-H₂O System Study Using Hydrothermal Diamond Anvil Cell and Raman Spectra
		WANG Shi-xia¹, YANG Meng¹, WU Jia², ZHENG Hai-fei³
		DOI: 10.3964/j.issn.1000-0593(2019)12-3698-07
		During the mineralization process, the dissolution of primary mineral and the formation of secondary mineral could happen on the conditions of changing temperature and pressure. The dissolution and recrystallization of the minerals would cause the changing concentration of the solute, and the crystal which is from recrystallization depends on the reaction process. The process of dissolution and recrystallization is a complex dynamic process. At present, high-pressure autoclave and piston-cylinder are mainly used for the study of the kinetics on the dissolution and recrystallization of the minerals, whereas the cooling quenching reaction will affect the true composition of the sample. In this experiment, the process of the crystal recrystallization of thenardite saturated Na₂SO₄ solution with the change of temperature and pressure was traced by using the in-situ observation of diamond anvil cell with Raman spectroscopy. The dissolution and recrystallization kinetics of sodium sulfate crystals during different temperature and pressure conditions were investigated by in situ observation and spectrometry. The results showed that the Raman spectroscopy of thenardite at room temperature were 449.9, 620.5, 632.9, 647.4, 993.3, 1 101.8, 1 132.2 and 1 153.1 cm^-1 respectively. The crystal shape of solid thenardite changed continuously with the slow increase of temperature, and thenardite was dissolved completely when system temperature reached to 193 ℃. The recrystallized crystal appeared with decreasing temperature rapidly, and the new 1 196.5 cm^-1 Raman characteristic peak of recrystallized crystal showed the appeared crystal was mirabilite (Na₂SO₄·10H₂O). In-situ observation of diamond showed that thenardite partially dissolveed and recrystallized during the rapid heating process, and the Raman characteristic peak of the recrystallized region was still thenardite. The process of dissolution and crystallization was controlled by diffusion. The Raman spectroscopy improved can be used for quantitative analysis. Compared with the parameter of peak intensity, area and SO^2-₄/H₂O intensity ratio in the system solution, the area ratio of SO^2-₄/H₂O in the solution reflected the change of SO^2-₄ concentration precisely in the solution during the reaction. The SO^2-₄/H₂O peak area ratio (AR) is (0.016 6±0.000 4), and the error is 2.4% when solution reaches the dissolved recrystallization equilibrium state. Based on Johnson-Mehl-Avrami-Kolmogorov (JMAK) model and the SO^2-₄/H₂O peak area ratio in the solution, the kinetics fitting of dissolution and recrystallization can be simulated. The results showed that the reaction order of dissolution and crystallization of anhydrous sodium sulfate is 1.266 7 and the equilibrium constant of the reaction is 0.001 26 at the temperature of 109 ℃. In summary, the device of hydrothermal diamond anvil cell is simple to operate, and can also avoid errors caused by degeneration and exchange in the quenching process. The advantage of in-situ observation of hydrothermal diamond anvil cell combined with Raman spectroscopy quantitative analysis can be applied to the kinetics of dissolution and crystallization of minerals in aqueous solution under high temperature and high pressure conditions. It is an efficient kinetic research method and is of great significance for studying rapid phase transition.
		2019 Vol. 39 (12): 3698-3704 [Abstract] ( 155 ) RICH HTML PDF (4464 KB) ( 42 )

	3705	Ultraviolet Multi-Channel Imaging of Sweat Latent Fingerprints and Analysis of Its Characteristics Over Time
		YU Jin-tao^{1, 2, 3}, LI Qing-ling^{1, 2, 3} , LI Lei^{1, 2, 3}, YIN Da-yi^{1, 2, 3*}
		DOI: 10.3964/j.issn.1000-0593(2019)12-3705-06
		The uniqueness and lifetime invariance of fingerprints enable fingerprints to verify a person’s identity information, which has a wide range of applications in the field of biometrics. The sweat latent fingerprint has special reflection, scattering and fluorescence characteristics for ultraviolet light, so the sweat latent fingerprint can be extracted by the ultraviolet band, and the scene and target samples are not polluted. At present, there are extensive researches on fingerprint extraction in the ultraviolet band, but there are few studies on the change of fingerprint with time. Generally, the changes of the content of sweat latent fingerprint components are generally measured by chemical methods. The study found that the UV spectral characteristics of each component of the fingerprint are different, and the volatilization degree of these components is also inconsistent with time. The multi-channel UV imaging system is used to perform gaze imaging on the sweat latent fingerprint, and the DN value of each channel is found to change with time. The degree is not the same, and the fingerprint can be timely analyzed by studying the change of the DN value of each channel. First, the reflectance spectra of substances that are easily contacted by fingers such as sweat, alcohol, and edible oil were studied by ultraviolet spectrometer and xenon lamp, and the reflection spectrum characteristics of these materials were obtained. Then, for these types of fingerprints, a multi-channel UV imaging device was developed, which has three UV channel pairs at 240～280 nm (channel 1), 280～315 nm (channel 2) and 315～340 nm (channel 3). The gaze imaging was performed to obtain a clear fingerprint image, and the average values of the 10 points with the highest code value on the fingerprint image were compared, and the relationship between the DN value and the time change of different channels was obtained. The experimental results show that the sweat latent fingerprint has good imaging characteristics in the ultraviolet band, and its imaging DN value gradually decreases with time. The imaging DN values of the three fingerprints in channel 1 of 240～280 nm were reduced to the first day. The imaged DN values of the three fingerprints in channel 2 of 320～340 nm on day 7 decreased to 0.57, 0.61, and 0.60 on the first day, respectively; the three fingerprints in channel 3 of 340～420 nm were respectively reduced by 0.62, 0.60, and 0.59. The imaging DN values on the seventh day were reduced to 0.56, 0.63, and 0.58 on the first day, respectively. The experimental results show that the spectral characteristics of different types of fingerprints in the ultraviolet band are not consistent, the imaging DN is not the same, and the law of change with time is different, but the volatilization of fingerprint components has a certain law, imaging DN value from the first day By the seventh day, it will be reduced to about 60%, which can reflect the volatile nature of the fingerprint to some extent. Combined with the ultraviolet multi-channel imaging system, the variation law of fingerprints can be well studied, which provides an important means for fingerprint research in criminal investigation.
		2019 Vol. 39 (12): 3705-3710 [Abstract] ( 199 ) RICH HTML PDF (3032 KB) ( 86 )

	3711	Extracting Linear Attenuance of Analyte in Turbid Scattering Media and Prediction Model Transfer Based Thereon
		CAO Hai-qing, HAN Tong-shuai, LIU Xue-yu, LIU Jin^*
		DOI: 10.3964/j.issn.1000-0593(2019)12-3711-07
		In near-infrared spectroscopy (NIRS) is widely applied for the qualitative or quantitative component detection in foods, medicines, pollution and biological tissues as it can provide real-time, non-invasive and continuous measurement. In the quantitative analysis of components in scattering media based on NIRS, the attenuance of the media doesn’t exhibit linearity with the source-detector separation (SDS) due to light scattering. Then measurement models at different SDSs are difficult to be applied to each other. In this paper, we propose a signal processing method based on Diffusion Equation (DE) to acquire the linear attenuance and get a SDS-independent optical parameter, i. e. effective attenuation coefficient (EAC). The EAC spectrum can be used to detect the component since the spectrum shows a comprehensive absorption of it. We apply a differential measurement on the spectra from two arbitrary SDSs to get the EAC spectrum, which will be independent to the used SDSs as long as the SDSs are in a limited linear range. The SDSs also can be flexibly selected according the different wavebands. More over, the differential can greatly reduce the influence from light diffusing in medium, and then benefit the measurement model transferring for different scattering media. We tested the method on the turbid water solutions with high scattering property by using theoretical calculation, Monte Carlo (MC) simulation and experiment. The tested solutions’ scattering coefficients were in the range of 28.53～87.47 cm^-1 and the waveband was 1 000～1 360 nm. The linear range of SDS for the attenuance was acquired. Taking the glucose measurement as an example, the EAC spectra of glucose in these media were tested. Using the SDSs from the linear range, we measured glucose’s EAC spectra. The experiment system was equipped with a SDS adjustable probe to get the diffuse light from different SDSs. The spectra of three typical media, which are 3%，5%，10% Intralipid solutions, were compared. These glucose spectra presented high similarity and could be linearly transferred to each other. Intralipid solutions are often used as biological tissue phantoms since their optical property covers most water rich materials. And the solutions can also be used to mimic water rich food like milk, juice etc. Therefore, our study would be widely beneficial to many cases. In summary, we proposed an effective method to extract linear attenuance for diffuse spectra in turbid scattering media. This method can well improve the real use of NIRS, since it not only helps flexibly select SDSs, but also presents a convenient and linear measurement model transferring for easy varying media, such as tissues, milk, and other foods.
		2019 Vol. 39 (12): 3711-3717 [Abstract] ( 186 ) RICH HTML PDF (3385 KB) ( 58 )

	3718	Study on the Resistance and Thermal Effects of Current in Lightning Return Stroke Channel by Spectroscopy
		WANG Xue-juan¹, YUAN Ping^2*, ZHANG Qi-lin¹
		DOI: 10.3964/j.issn.1000-0593(2019)12-3718-06
		The resistance and the thermal effects of current in lightning discharge channel are important to the lightning disaster research and prevention design, and the thermal characteristics of lightning channel are closely related to the spectra of the plasma. In this work, using the spectra of two cloud-to-ground lightning with multiple return strokes obtained by a slit-less spectrograph, and combining with the synchronous electrical information, the electrical conductivity, the peak values of current, the arc channel radius has been calculated, then the resistance per unit length, the thermal power per unit length at the instant of peak current, and the heat energy per unit length during the first 5 μs in the channel are firstly obtained. Meanwhile, compared to the common metal conductors, the relationships between the thermal power and the resistance and the square of the peak current in lightning plasma channel are analyzed. The results shown that the resistances per unit length are estimated by spectra to be 0.04～8.41 Ω·m^-1. The thermal peak powers per unit length are in the range of 0.88×10⁸～2.20×10⁸ W·m^-1 and the heat energies over the initial 5 μs are in the range of 1.47×10²～3.66×10² J·m^-1. The values of these parameters are consistent with the values reported in other works; The thermal power at time of peak current increases linearly with the resistance but reduces exponentially with the square of the peak current; Because the resistance in lightning channel is inverse ratio to 2/3 power of the temperature, the stronger peak currents are generally corresponding to the higher temperatures, but the resistance and the thermal power will decrease rapidly with the temperature, which further proves why the plasma cannot be heated by the ohmic heating method.
		2019 Vol. 39 (12): 3718-3723 [Abstract] ( 159 ) RICH HTML PDF (2858 KB) ( 44 )

	3724	Terahertz Time-Domain Spectroscopy for Identification of Hazardous Substances in Mail
		LI Tao¹, ZHANG Liang¹, HE Jian-an^{2, 3}, ZHANG Si-xiang^1, GU Da-yong^{2, 3}
		DOI: 10.3964/j.issn.1000-0593(2019)12-3724-07
		With the rapid development of e-commerce, the number of mails has increased dramatically, and the hazardous substances in the mail have become an important criminal means for criminals, which threatens public safety and social stability. The security check of emails becomes especially important, but the conventional detection techniques can not accurately identify hazardous substances. Terahertz waves occupy the region between microwaves and the infrared. The explosives, illicit drugs and harmful biological factors concealed in the mail have a characteristic absorption spectrum in the terahertz band, and THz waves can penetrate the non-polar packaging materials commonly used in mail. Terahertz radiation also has characteristics of low energy, coherence and so on, making it possible to achieve high-sensitivity and non-destructive detection of hazardous substances by using terahertz technology. The present paper introduces the characteristics of terahertz technologies, the composition of the terahertz time-domain spectroscopy system and the Fresnel formula analytic method for obtaining optical constants. The method obtains material parameters including absorption spectra by sample transmission or reflection signals and reference signals. The terahertz characteristic absorption spectra of samples were compared with the established spectral characteristic databases of various dangerous substances to determine whether the samples were dangerous and the types of hazardous substances. The research achievements of the characteristic absorption spectra of explosives and drugs in the terahertz band and the research progress of the absorption spectra under various non-polar materials were summarized. The analytical method for obtaining the absorption spectrum is suitable for thicker samples. For the thin sample article, a P-spectrum method is also introduced, which can accurately obtain the absorption spectrum of the sample under the cover without the reference signal. In addition to directly using absorption spectroscopy for detection, in recent years, many methods for terahertz spectroscopy have been proposed, such as the spectral dynamics analysis method which can distinguish the substances with overlapping absorption frequencies well, chemometrics method which can achieve qualitative and quantitative analyses of terahertz spectra, and imaging analysis based on terahertz time domain spectroscopy which can complete the identification of hidden dangers of large areas. The feasibility of terahertz time-domain spectroscopy to identify harmful biological factors,and the characteristics of for small carrying amount of harmful biological factors were also analyzed. Meanwhile, the progress of terahertz time domain spectroscopy in improving the detection sensitivity of biological factors was summarized. Finally, the existing technique difficulties, such as limited power of terahertz, large influence by environmental factors, lack of unified standards, were discussed and the future development trend was analyzed.
		2019 Vol. 39 (12): 3724-3730 [Abstract] ( 189 ) RICH HTML PDF (3125 KB) ( 71 )

	3731	Quantitative Analysis of MixedInorganic Salt Solution Based on Terahertz Spectroscopy
		HE Ming-xia^1,2,3, SUN Long-ling^1,2,3, CHEN Da³, HUANG Zhi-xuan³, LIU Li-yuan^2,4, ZHAO Jin-wu^1,2,3, ZHANG Hong-zhen^1,2,3
		DOI: 10.3964/j.issn.1000-0593(2019)12-3731-06
		Terahertz biomedicine is getting more and more concentration, especially in the field of spectroscopic research. Its main difficulty lies in how to achieve accurate component analysis of complex biological system as well as effectively avoid water interference . Terahertz spectrum contains the information of molecular vibration. However, its absorption spectrum is weak and overlaps seriously. Therefore, it is difficult to use traditional calibration techniques for quantitative calculation, such as the peak height and peak area. Adopting multivariate correction method makes terahertz spectrum a fast, simple and widely applicable way to carry out quantitative analysis. In this paper, the mixed aqueous salt solution of KCl and NaCl is taken as a typical system to be studied. The concentration of each component varies from 0.1 to 2 mol·L^-1, with an interval of 0.1 mol·L^-1. Due to the hydrated hydrogen bond of inorganic metal ions, terahertz time-domain spectrum data can be collected to analyze each component quantitatively. Based on theorthogonal experiment principle, we constructed the data set with outstanding structure characteristics to accuratelyextract the hydrogen bond information by spectral analysis. Here, the adaptive algorithm is developed to find the relationship between the spectral data and the concentration, and the variable screening technology is adopted to extract the characteristic information of different components from the original spectral data. Finally, we build the data-driven model between the concentration and the characteristic information. The calculation results show that the prediction errors of KCl and NaCl components are 8.0% and 9.1% respectively, which can effectively meet the requirements of detection accuracy for most applications. Therefore, the new method of data-driven modeling terahertz spectrum analysis can provide a new way for terahertz biomedical research.
		2019 Vol. 39 (12): 3731-3736 [Abstract] ( 172 ) RICH HTML PDF (3569 KB) ( 56 )

	3737	Terahertz Spectral Recognition Based on Bidirectional Long Short-Term Memory Recurrent Neural Network
		YU Hao-yue, SHEN Tao^*, ZHU Yan, LIU Ying-li, YU Zheng-tao
		DOI: 10.3964/j.issn.1000-0593(2019)12-3737-06
		Feature extraction, the key process of the terahertz spectral recognition, typically uses the dimensionality reduction techniques. However, when the overall difference of terahertz spectra of some compounds is small, dimensionality reduction methods often lack important feature information of sample differences, which leads to classification errors. If the dimensionality reduction process is not performed, the traditional machine learning algorithm cannot be well classified because the original spectral data have a high dimensionality. Therefore, this paper proposes a terahertz recognition method based on bidirectional long short-term memory recurrent neural network (BLSTM-RNN), which performs automatic feature extraction with containing full spectrum information of terahertz spectrum. BLSTM-RNN is a special recurrent neural network, whose LSTM unit can be used effectively to solve the problem that the original terahertz spectral data dimension is high. Then, it becomes easier to train the model. What’s more, the architectural model combined with bi-directional spectral information can enhance the ability of the model to extract valid feature information from complex spectral data automatically. In this paper, three types and 15 compounds terahertz transmission spectra are used as test objects. The terahertz transmission spectrum samples data of 15 organic compounds such as Anthraquinone, Benomyl and Carbazole were firstly normalized in 0.9～6 THz by S-G filtering and cubic spline interpolation. Then a recurrent neural network with bidirectional Long short-term memory unit (LSTM) is constructed to automatically extract the full spectrum information of the terahertz spectrum and classify it by Softmax classifier. Through experimentation of optimizing the network structure and various parameters, the prediction model of the complex terahertz transmission spectrum data is obtained, and the comparative experiment is done by contrasting with the traditional machine learning algorithm SVM, KNN and neural network algorithm MLP, CNN. The results show that compared with other methods，the recognition accuracy of both dataset-1 and dataset-2 is improved. Dataset-1 and dataset-2 are two terahertz transmission spectral data sets of five compounds with large difference and no obvious peak characteristics, and the average recognition accuracy of the former is 100% and the latter 98.51%. Most importantly, dataset-3 is a dataset of terahertz transmission spectra with five similar spectral lines. The average recognition accuracy is 96.56%. Compared with other methods, the recognition accuracy is significantly improved. Dataset-4 as a collection of transmission spectral data sets for dataset-1, dataset-2, and dataset-3 has an average recognition accuracy of 98.87%. It is verified that the BLSTM-RNN model can automatically extract effective terahertz spectral characteristics and meanwhile ensure the prediction accuracy of complex terahertz spectra. In the selection of model training optimization algorithm, the Adam optimization algorithm is better than the RMSProp, SGD and AdaGrad optimization algorithms, and the target function loss value of the model has the fastest convergence rate. At the same time, as the number of training iterations increases, the prediction accuracy of similar terahertz transmission spectral datasets also increases. The proposed method can provide a new identification method for spectral recognition retrieval of complex terahertz spectral databases.
		2019 Vol. 39 (12): 3737-3742 [Abstract] ( 200 ) RICH HTML PDF (2113 KB) ( 65 )

	3743	Model of Micro-Leakage Point Recognition of Underground Gas Based on Continuous Wavelet Transform
		LI Hui¹, JIANG Jin-bao^1*, CHEN Xu-hui¹, PENG Jin-ying¹, QIAO Xiao-jun¹, WANG Si-jia²
		DOI: 10.3964/j.issn.1000-0593(2019)12-3743-06
		As a clean, efficient low-carbon energy source, natural gas accounts for an increasing proportion of consumption. For underground gas pipelines, gas storage, and the like, natural gas leakage will occur due to factors such as pipeline corrosion, aging, natural disasters, underground faults, and the bad sealing of injection-wells. In terms of security, economic, environmental and other considerations, micro-leak detection of underground natural gas pipeline and gas storage is essential. In this paper, we use hyperspectral remote sensing to monitor surface vegetation changes, thus indirectly detecting natural gas micro-leakage points. The field controllable system is used to simulate the underground micro-leakage experiment. Winter wheat is used in this study, and a time series of 9 experiments of canopy spectral collecting were conducted. Spectral analysis was used to identify and exploit the spectral characteristics of stress wheat and thereby constructing an index recognition model. Firstly, the wheat canopy spectrum is subjected to the processing of singular value culling and smoothing, and then the continuous spectrum wavelet transform is performed on the canopy spectrum after continuum removal. Specifically, mother wavelet of Mexihat is selected. When the scale parameter is 32, the wavelet coefficients have fewer peaks and valleys, which can fit well with the original spectrum, and the peak and valley positions of wheat multi-phase data are relatively stable. The original spectrum of stress and healthy wheat was poorly separable, but separability of proposed model using the wavelet coefficients at 487, 550 and 770 nm was better among wheat samples, and had obvious diagnostic characteristics: (1) The wavelet coefficient of stress and healthy wheat having “absorption valley” at 487 nm, the wavelet coefficient value being negative, and the wavelet coefficient of healthy wheat being larger than that of stressed wheat; (2) the wavelet coefficient of stress and healthy wheat is 550 nm at 770 nm, where clear “reflection peak” can be observed, and the wavelet coefficient of stressed wheat is larger. In order to better highlight the differences of wavelet coefficients of stressed and healthy wheat, the index CWT_mexh（CWT_mexh=CW²₇₇₀/(1-CW₄₈₇)·CW₅₅₀） was constructed for the identification of stress and healthy wheat. Compared with the index NDVI₇₀₅，mNDVI₇₀₅，ARI1，R₄₄₀/R₇₄₀，D₇₂₅/D₇₀₂ and J-M distance quantitative test, the results show that the CWT_mexh has a better recognition performance on winter wheat under natural gas micro-leakage stress. The CWT_mexh can stably distinguish between stress and health after 20 days of natural gas stress, and maintain the same performance in the whole growth period, while the indexes of NDVI₇₀₅，mNDVI₇₀₅，ARI1 and so on, can not accurately identify throughout the growth period. The CWT_mexh index is superior to the other five indexes in terms of stability, universality and the ability to recognition. Therefore, it is feasible to indirectly identify natural gas micro-leakage points by monitoring surface vegetation using hyperspectral remote sensing. The results can provide theoretical basis and technical support for monitoring underground gas leakage points by satellite-borne hyperspectral remote sensing.
		2019 Vol. 39 (12): 3743-3748 [Abstract] ( 191 ) RICH HTML PDF (3110 KB) ( 61 )

	3749	The Reversible Ammonium Detection Based on the Coupled Microfluidic Chipand the Investigation of the Impact Factors
		ZHOU Hao, YANG Zheng
		DOI: 10.3964/j.issn.1000-0593(2019)12-3749-06
		The spectroscopic detection of ammonium (NH⁺₄) has great significance. With the development of microfluidics, microfluidic spectroscopic analysis aiming at rapid, portable and multi-component detection has realized tremendous achievements. However, the excessive consumption of the indicating material which exists all the time has not been settled yet. Zinc porphyrin, being a natural chromophore, can reversibly detect NH⁺₄ and settle the problem. But it suffers from the lack of selectivity. In allusion to these issues, a coupled microfluidic chip which consists of a reaction chip, a gas-diffusion chip and a detection chip is fabricated in our experiments. The reaction chip made of polydimethylsiloxane can convert NH⁺₄ into NH₃. The gas-diffusion chip which is made of two glass chips and a piece of polydimethylsiloxane gas-diffusion membrane allows NH₃ diffuses into the detection solution. The detection chip immobilizes the indicating material tightly through the multi-layer structure. The indicating material fabricated by dying zinc porphyrin on the surface of the cation exchange resin permanently will turn from green to purple when it meets NH₃ and will turn reversely into green when pure water is around. Using the coupled chip as the analytical platform, we set up a miniaturized spectroscopic detection system. With a portable spectrometer being the analytical instrument, we detect NH⁺₄ by the transmission spectrum intensity change at the wavelength of 450 nm and study three factors that could affect the detection performance: the thickness of the gas-diffusion membrane, the flow rate and the dosage of the indicating material. First, we confirm the reversibility of the indicating process and settle the issue of indicating material consumption by the spectrum change intensity. The time responses show the rapidity of the indicating process. Then through the comparison to the contrast experiment, the high selectivity of the indicating process is demonstrated because the interference has no influence and the spectrum change is attributed merely to NH₃. The relationship between the membrane thickness and the spectrum intensity change is obtained by changing the thickness of the gas-diffusion membrane in the gas-diffusion chip. Results show that the increase of the membrane thickness leads to a worse detection performance, but the outcome remains stable when the thickness is less than 10 μm. So 10 μm is selected as the optimal thickness in consideration of the mechanical strength. The impact of the flow rate is investigated afterwards. The results exhibit that the increase of the flow rate will decrease the spectrum intensity change, but the performance becomes unchanged when flow rate is less than 5 μL·min^-1. Last, how the dosage of the indicating material impacts the results is studied. It is demonstrated that both excessive and inadequate indicating material will deteriorate the performance. So 5 mg is selected as the optimal amount. The spectroscopic detection system which uses the coupled chip as the analytical platform has the advantages of small volume, high economy, rapid response and realizes highly selective and reversible NH⁺₄ detection.
		2019 Vol. 39 (12): 3749-3754 [Abstract] ( 132 ) RICH HTML PDF (3531 KB) ( 47 )

	3755	Qualitative Analysis Method for Raman Spectroscopy of Estrogen Based on One-Dimensional Convolutional Neural Network
		ZHAO Yong¹, RONG Kang¹, TAN Ai-ling²
		DOI: 10.3964/j.issn.1000-0593(2019)12-3755-06
		The qualitative identification of Raman spectroscopy has been widely used in many industries and research fields, but the preprocessing in traditional Raman spectroscopy analysis mainly relies on human experience. Although spectral feature extraction can reduce the signal dimension, it also causes partial spectral information loss. Materials with similar characteristics have high spectral similarity. In addition, due to the interference of measurement environment and the various errors in the analysis process, the final classification accuracy is not ideal enough. Aiming at these problems, this paper proposes a novel Raman spectral qualitative classification method based on one-dimensional convolution neural network. The Raman spectra of three different estrogen powders, estrone, estradiol and estriol, were collected, and three Raman spectral data augmentation methods were designed to construct Raman spectral database; a one-dimensional convolution neural network classification model for Raman spectral data was proposed, which integrated the whole process of spectral preprocessing, feature extraction and qualitative classification. The hyper-parameters and training process of the proposed classification model were optimized and the accuracy was tested by simulation experiments. Experimental results indicated that the 1D-CNN model can classify three similar estrogen powders Raman spectroscopy with the highest classification accuracy of 98.26%. No spectral preprocessing and feature extraction steps were required in the analysis process, which simplifies the spectral signal analysis process and can retain more vital information. In addition, when the noise intensity of the simulated measurement reached 60 dBW, the classification accuracy of the traditional methods decreased obviously in varying degrees, but the 1D-CNN model could still achieve 96.81% accuracy. Compared with traditional Raman spectral classification methods, the proposed method was less affected by the noise of measurement process and had stronger robustness, which was suitable for Raman spectral signals with strong noise measured in more complex environments. The results of this study show that deep learning method has great application potential in the field of analysis of Raman spectroscopy.
		2019 Vol. 39 (12): 3755-3760 [Abstract] ( 281 ) RICH HTML PDF (2516 KB) ( 154 )

	3761	Retrieval of Water Quality Parameters of Urban River Network Using Hyperspectral Date Based on Inherent Optical Parameters
		LIN Jian-yuan¹, ZHANG Chang-xing^2*, YOU Hong-jian³
		DOI: 10.3964/j.issn.1000-0593(2019)12-3761-08
		The water radiative transfer mechanism is the theoretical basis of water spectral characteristic analysis. The inherent optical parameters of water due to the composition of the water is independent of the surface light field of water. The semi-empirical algorithm based on statistics can be used to retrieve water quality parameters in some specified areas. However, that is lacking in physical meaning. It was of great significance for the study of the spectral characteristics of turbid water in inland cities to study the model to retrieve the water quality parameters of urban river network based on inherent optical parameters using hyperspectral data. The study was based on the analysis algorithm of bio-optical model. Taking the consideration of the characteristics of inland type II water of urban river network such as complexity of optical characteristics, strong heterogeneity of spatial distribution, small water and large fluidity. The paper came up with an improved QAA algorithm suitable for water of inland urban river network to obtain the inherent optical parameters of water. The improvements included the following two aspects: adjustment of the backscattering estimation model and optimization of the reference band. By calculating inherent optical parameters, such as the coefficient of total absorption of the reference band, the coefficient of backscattering particles, etc., coefficient of phytoplankton absorption was obtained and coefficient of pure water absorption was eliminated in this paper. A linear regression analysis was carried out on the optimal ratio of coefficient of phytoplankton absorption and concentration of chlorophyll-a to build a model to retrieve water quality of chlorophyll-a concentration. A linear regression analysis was also carried out to eliminate the optimal band ratio of coefficient of pure water absorption and concentration of suspended solids. And a model to retrieve suspended solids concentration for water quality was built. Aiming at type II water bodies of inland river network and taking the typical river network of Jiaxing City as the research area, regional aeronautical hyperspectral data, ground quasi-synchronous measurement data of water sampling data and spectral data above the water surface were collected; the QAA algorithm and IIMIW algorithm were used to retrieve the inherent optical parameters of the measured water spectral data. With the two algorithms compared and the characteristics of urban river network was taken into consideration, the improved QAA algorithm was put forward. The retrieval of the inherent optical parameters of the water in the study area was achieved by using improved QAA algorithm. Based on the inherent optical parameters of water obtained by the inversion, quantitative inversion model of chlorophyll-a concentration and suspended solids concentration were established. The determining coefficients R² of the inversion model were 0.64 and 0.71, respectively. The retrieved results were validated and analyzed using the actual measured sample data of four ground samples acquired at the same time in the area by the aircrafts which obtained aviation hyperspectral data. Comparing the retrieved values of water quality parameters of concentration with the measured values, the average relative errors of retrieved values for chlorophyll-a and suspended solids were 9.2% and 9.4% respectively. The table of distribution of chlorophyll-a and suspended solids obtained from the retrieval was also consistent with the characteristics and actual conditions of the urban river network. That provided methods and model references for urban river network water quality monitoring.
		2019 Vol. 39 (12): 3761-3768 [Abstract] ( 161 ) RICH HTML PDF (6089 KB) ( 72 )

	3769	Preparation of 9,10-Diphenylanthracene Derivative and Its Detection for Cu²⁺ by Up/Down-Conversion
		CHEN Shuo-ran, HUANG Su-qin, HAN Peng-ju^, YE Chang-qing, SONG Sa-sa, WANG Xiao-mei^
		DOI: 10.3964/j.issn.1000-0593(2019)12-3769-07
		Cu²⁺ is one of the essential trace elements for human metabolism, while excess ingestion will cause metabolic disorders even diseases. However, Cu²⁺ has been elevated levels in living environment due to overuse and inappropriate reprocessing measures of copper, which makes Cu²⁺ one of the toxic heavy metal pollutions. Therefore, the continuous concern over Cu²⁺ pollution has been a hot issue and attracted interest in the detection methods for Cu²⁺. Fluorescent spectrometry based on fluorescence probe has been widely used in ion detection field owing to good selectivity and high sensitivity. So far, researchers have developed fluorescence probes for Cu²⁺ detection based on selectional weak interaction between probe molecules and ions to be measured. However, these strategies all involve selectivity or sensitivity drawbacks, making the probes difficult for practical applications. Here, we designed and synthesized a new molecule 9,10-bis (3’-hydroxy-4’-thiosemicarbazide) phenylanthracene (b-HTPA) as a fluorescence probe for Cu²⁺ detection. The electron configuration of b-HTPA would change through coordinating with Cu²⁺, which would cause the remarkable change of fluorescence property of the b-HTPA as responsiveness for Cu²⁺. Characterizations of the detection of b-HTPA for Cu²⁺ were mainly carried out by down/up conversion fluorescence spectral. Results of selectivity research showed that Cu²⁺ has the strongest fluorescence quenching effect compared with the other thirteen kinds of metal cations. Besides, upon addition of Cu²⁺about 150-fold decreasement of fluorescence intensity was observed compared to other metal cations. The results indicated the good selectivity of b-HTPA to Cu²⁺. Results of sensitivity research showed that the detection limit of b-HTPA to Cu²⁺ was 2.78×10^-7 mol·L^-1 which was much lower than the hygienic standard for drinking water (GB5749—2006), which indicated high fluorescent response sensitivity and ideal detection limit. The results of response time test revealed that interaction rate between b-HTPA and Cu²⁺ was very high in the first two minutes and completely reacted within ten minutes, which showed that b-HTPA could be capable of reacting intensively with Cu²⁺ in short time which may save detection period. Moreover, up-conversion fluorescence spectra were also used for the sensitivity evaluation of b-HTPA to Cu²⁺ with palladium(Ⅱ) octaetylporphyrin (PdOEP)as the sensitizer. The research results showed that intensity of up-conversion fluorescence obviously declined upon the addition of Cu²⁺ and the detection limit was 3.78×10^-6 mol·L^-1 which is also lower than the hygienic standard. This work designed and synthesized the 9,10-bis (3’-hydroxy-4’-thiosemicarbazide) phenylanthracene as a fluorescence probe for Cu²⁺ detection, and the probe was proved to have highly selective and sensitive. Moreover, the probe b-HTPA had ideal detection limit and short detection period, which gave it great potential in the field of Cu²⁺ detection.
		2019 Vol. 39 (12): 3769-3775 [Abstract] ( 231 ) RICH HTML PDF (2242 KB) ( 50 )

	3776	Wood Species Recognition with Microscopic Hyper-Spectral Imaging and Composite Kernel SVM
		ZHAO Peng^*, TANG Yan-hui, LI Zhen-yu
		DOI: 10.3964/j.issn.1000-0593(2019)12-3776-07
		In this paper, a stereomicroscopic hyper-spectral imaging scheme is used for wood species recognition. The SOC710VP hyper-spectral imaging system is used to pick up the wood images in visible and near-infrared spectral band (i. e., 372.53～1 038.57 nm). First, the ENVI software is used to pick up the mean spectra of wood sample’s Region of Interest (ROI). The Successive Projection Algorithm (SPA) and Competitive Adaptive Reweighted Sampling algorithm (CARS) are used for spectral dimension reduction. Second, a Support Vector Machine (SVM) is used to classify the wood samples in full spectral band and in feature wavelengths. Third, in the spatial dimension the 1^st principal component image (PC1) is used to compute the wood texture features based on Gray Level Co-occurrence Matrix (GLCM). In the 4 directions of 0°, 45°, 90°, 135° the 16 feature parameters such as energy, entropy, inertia moment and so on are calculated and are put into SVM for wood species recognition. Lastly, the 4 composite kernels SVM are used to fuse the spatial-spectral features for wood species recognition. Experiments on 20 wood species classification indicate that CARS is a better choice in view of the feature wavelength selection and running speed and the classification accuracy for testing set reaches to 92.166 7% if the ordinary SVM is used for wood spectral classification. If the wood texture features based on GLCM are used, the classification accuracy for testing set reaches to 60.333 0% if the ordinary SVM is used. When the wood spectral and texture features are fused for classifications, the composite kernel SVM has the best classification accuracy. Especially, the classification accuracy of the 2^nd composite kernel SVM is the highest with 94.1667% for testing set and a processing speed of 0.254 7 s. Moreover, the classification accuracy of the 1^st or 3^rd composite kernel SVM reaches to 93.333 3% or 92.610 0% with a running speed of 0.180 0 or 0.260 2 s. Therefore, wood species classification accuracy can be improved by use of hyper-spectral imaging and composite kernel SVM, which may be applied in the practical wood species classification system.
		2019 Vol. 39 (12): 3776-3782 [Abstract] ( 199 ) RICH HTML PDF (2622 KB) ( 70 )

	3783	Research on NIR Spectra Quality Detection Method Based on Support Vector Data Description
		LI Hao-guang^1,2, YU Yun-hua^1,2, SHEN Xue-feng^1,2, PANG Yan¹
		DOI: 10.3964/j.issn.1000-0593(2019)12-3783-05
		Near infrared spectroscopy (NIR) is a weak signal, and its spectral quality is easily disturbed by the state of the measured object and various external factors. Specifically, the spectral quality in the qualitative analysis of NIR is mainly affected by the state change of measuring instrument, wrong operation, and the interference of singular samples. The robustness and applicability of the model are easily affected by the incorporation of poor quality spectra, so spectral quality determination is of vital importance to ensure the model prediction ability. At present, there are many studies on the determination of spectral quality for quantitative analysis, but few studies on the determination of spectral quality for qualitative analysis. In this paper, a method for the determination of spectral quality for near-infrared qualitative analysis based on data description of support vector is proposed. A self-made diffuse reflectance NIR acquisition device is used to collect the spectra of single-grain maize as an experimental object, and under normal conditions, the diffuse transmission spectra of a maize single grain were collected as normal samples, while the collected spectra were used as abnormal spectra under the conditions of artificial light leakage, near infrared detector window covering maize epidermis debris, intensity change of light source, distance change between light source and tested maize grain, and mixture of similar maize seeds. On this basis, the determination based on support vector data description (SVDD) was studied. The principle and method of establishing spectral quality judgment model were analyzed. Because the parameters of kernel function and regularization have important influence on the performance of spectral quality judgment model based on SVDD, the combination of grid search and cross validation was used to optimize the parameters of kernel function and regularization, and the optimal parameters of Gauss kernel were determined through experiments. Then, the SVDD method was compared with other spectral quality determination methods such as Mahalanobis distance and local anomaly factor. The average of correct recognition rate of normal samples and correct rejection rate of abnormal samples were used as evaluation criteria. The experimental results show that the spectral quality determination method based on support vector data description has the best performance. In near infrared qualitative analysis, this method can be used as a means of eliminating abnormal spectra before feature extraction and pattern classification, and the spectra quality determination step based on SVDD can effectively improve the reliability of the qualitative analysis.
		2019 Vol. 39 (12): 3783-3787 [Abstract] ( 196 ) RICH HTML PDF (2213 KB) ( 66 )

	3788	A Method of Extracting Mining Disturbance in Arid Grassland Based on Time Series Multispectral Images
		LI Jing, DENG Xiao-juan, YANG Zhen, LIU Qian-long, WANG Yuan, CUI Lü-yuan
		DOI: 10.3964/j.issn.1000-0593(2019)12-3788-06
		Surface mining will completely change the original landscape pattern of land use, directly destroy the local ecological environment, and even affect the production and life of the nearby residents; therefore, more and more scholars have begun to pay attention to mining disturbance. Previous studies on extracting mining disturbances from temporal multispectral images focused on forest areas with single disturbance form. However, most surface mines in China are concentrated in grassland areas, and in the grassland mining areas in northeastern China, mining disturbances are more difficult to be identified because of their fragile ecological environment and the existence of various other forms of disturbance. In order to clarify the mining disturbance of grassland open stope in ecologically fragile areas in northeastern China, the authors taking Shengli mining area as an example, firstly employs 27 Landsat multi-spectral remote sensing images from 1986 to 2017, and bases the study on the long time series trajectory change characteristics of NDVI (normalized difference vegetation index). (In order to remove the effects of phenology, cloud and shadow on time series multispectral images, BISE-WT filter is used to filter the original NDVI time series to effectively remove the noise in the time series NDVI data and retain the effective information at the same time). After sample point training, CV threshold (Coefficient of Variation) and Max vegetation threshold are obtained. The Max vegetation threshold (vegetation threshold) is then used to construct the CV-Max disturbance recognition model and extract the disturbance distribution in the study area. Furthermore, using vegetation threshold, NDVI time series trajectory is analyzed to obtain disturbance interannual information and reconstruct disturbance history map. Then, by analyzing the spectral characteristics of typical terrain in the study area, bare coal extraction rules are constructed to extract the distribution of bare coal in the study area. Finally, the topological relationship between bare coal and disturbance area is constructed and a spatial topological overlay analysis is conducted to obtain mining disturbance information. The accuracy verification reveals the extraction accuracy of mining disturbance is 93.17% (Kappa coefficient=0.85) and the extraction accuracy of disturbance interannual information is 83.35% (Kappa coefficient=0.81) respectively. The results show that during the study period, the mining disturbance area accounts for 8.90% of the total area of the study area in space; in terms of time, the occurrence of mining disturbance concentrated in 2000—2009, during which the mining disturbance pixels accounted for 76.70% of the total mining disturbance pixels; the years from 1988 to 1998 witness the initial period of land destruction, and in 2000—2005, land destruction increased in the mining area, and in 2006—2009, the land destruction the mining area reached the peak. The proportion trend of mining disturbance pixels in 2010—2017 is relatively flat and continues to be at a low level, and the scope of land damage in mining area is basically stable. In view of the ecologically fragile grassland mining area in northeastern China, the method of extracting mining disturbance information by using NDVI and bare coal spectral features based on time series multispectral images is feasible. The research results can provide data and theoretical method support for the sustainable development of arid and semi-arid grassland surface mining area.
		2019 Vol. 39 (12): 3788-3793 [Abstract] ( 192 ) RICH HTML PDF (3202 KB) ( 74 )

	3794	Classifying Forest Dominant Trees Species Based on High Dimensional Time-Series NDVI Data and Differential Transform Methods
		XU Kai-jian^{1, 2}, TIAN Qing-jiu^{1, 2*}, XU Nian-xu^{1, 2}, YUE Ji-bo^{1, 2}, TANG Shao-fei^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2019)12-3794-07
		Ensuring the accuracy of forest trees species recognition based on remote sensing spectral detail information has strong practical significance and value in forestry resources monitoring and management, which is also an important scientific issue to be settled. The time-series remotely sensed data with high resolution can distinguish small canopy spectrum variation caused by different phenological growth characteristics of different forest tree species effectively, which is expected to solve the common problem of the isomorphism in multispectral recognition of tree species. To clarify this situation, we study the Wangyedian forest farm in Chifeng of Inner Mongolia, northeast China, by using a total of 36 scenes covering the whole year medium-high resolution satellite observations (at 16 m spatial resolution) which were supported with GF-1 WFV (wide field view) to extract various time series of NDVI reflectance data. The data contain all the seasonal phases and phenological growth stages of different tree species and are propitious for the fine recognition of forest types. Five dominant forest types of Pinus tabulaeformis, Larix gmelinii, Populus davidiana, Betula platyphylla, and Quercus mongolica forest were classified and recognized using Support Vector Machine (SVM) classifier at different time scales (single season, every quarter, month-to-month and every ten-days). We also explore the effects of different time scales of NDVI reflectance data and differential transformation methods on the recognition of regional forest dominant tree species, based on the original sequence spectrum and the first, second and third order differential transformation, respectively. The results showed that Autumn is the best single season to identify the dominant tree species in the study area (p<0.05), and the largely improved recognition accuracy of forest tree species can be obtained from different time series data than single season data across all different seasons (p<0.05). Compared with the single data of spring, summer and autumn, the overall accuracy (OA) based on the every quarter data improved, which increased by 7.67%, 6.64% and 3.6% respectively, indicating the importance of phenological information contained in time series data images for discriminating different forest types. Besides, the results of spectral recognition based on month-to-month and every quarter data were significantly lower than those based on every ten-days and every quarter (p<0.05), and the spectrum recognition results based on the whole seasonal phase were the lowest in these time series data (p<0.05), which showed that the denser time series spectral information is more beneficial to the improvement of the accuracy of regional tree species identification (p<0.05). In addition, combined appropriately with spectrum differential transformation increased classification accuracy using time series multispectral imagery (p<0.05), for the overall accuracy of tree species created with the combined data was higher than that from results of time series NDVI spectral alone in the study area. After combined with the optimal spectrum differential transformation method, the best overall accuracies occurred in every ten-days and month-to-month data were 82.1% and 78.74%, and the corresponding rates of increase reached 3.38% and 2.95%, respectively. The results indicated that adding spectral derivative analysis was more effective in improving the tree species recognition accuracy from every ten-days to month-to-month time series NDVI data (p<0.05), which provided an effective reference and foundation for related researches focusing on fine recognition of forest types with multispectral remote sensing.
		2019 Vol. 39 (12): 3794-3800 [Abstract] ( 231 ) RICH HTML PDF (4740 KB) ( 141 )

	3801	Reflectance Spectroscopy Applied in Sandstone Weathering and Nitrogen Excretion: a Case Study in Longhushan Mountain, Jiangxi Province
		XU Chao-bin^1，2, QIU Jun-ting³, ZHONG Quan-lin^{1, 2, 4 *}, LI Bao-yin^{2, 4}, CHENG Dong-liang^{1, 2, 4}, ZENG Han-zhao², CHANG Yun-ni², YU Hua², ZHENG Wen-ting², ZOU Yu-xing², ZHANG Chuan³
		DOI: 10.3964/j.issn.1000-0593(2019)12-3801-08
		Nature and Science have revealed the interaction between surface rocks and the global nitrogen cycle, considering that rock is an important reservoir of nitrogen. Nitrogen excretion during rock weathering is one of the main sources of nitrogen in soil ecosystems, and has a major impact on the local and even global nitrogen cycle. Sedimentary rock, one of the important rock types, occupies 75% of the land surface. Danxia landform is one of the important geomorphologic types formed by the weathering and erosion of sedimentary rocks. Studies on Danxia landform sedimentary rock weathering and nitrogen excretion contribute to better understanding of the global nitrogen cycle. In this paper, we systematically collected red sandstone samples from Danxia landform in Longhushan Mountain of Jiangxi Province, and studied the mineral composition, spectral characteristics and nitrogen content of the rock samples using polarizing microscope, ASD spectrometer and carbon-nitrogen analyzer. The experimental results showed that the sandstones in the Longhushan Mountain area are dominated by feldspar sandstones. The granular minerals include feldspar and quartz, and the cement is mainly composed of iron and calcium with minor muddy. The chemical weathering of sandstone in Longhushan Mountain area includes cement dissolution and hydration. The dissolution of cement is mainly caused by iron dissolution, and the hydration of granular mineral is mainly represented by feldspar altering to clay mineral. The absorption index at 902 nm (the characteristic absorption band of Fe³⁺)decreased when iron dissolved, while that at 2 210 nm (the characteristic absorption band of clay Al—OH) increased after feldspar altered to clay minerals. For the same sample, the nitrogen content in the chemically weathered part is lower than that in the unweathered part, and the nitrogen content has a negative relationship with the absorption index at 2 210 nm (R²=0.802 6), indicating that rock weathering contributes to nitrogen excretion. For different samples, the correlation between nitrogen content and the absorption index at 2 210 nm is very poor (R²=0.025 6), indicating that the different mineral compositions and structures of rocks will decrease the correlation between absorption index and nitrogen content. The above studies showed that the reflectance spectroscopy provides a potential approach to study sandstone weathering and nitrogen excretion, but samples used in the study should have same lithology property.
		2019 Vol. 39 (12): 3801-3808 [Abstract] ( 174 ) RICH HTML PDF (7462 KB) ( 98 )

	3809	NIR Spectral Feature Selection Using Lasso Method and Its Application in the Classification Analysis
		LI Yu-qiang¹, PAN Tian-hong^{1, 2*}, LI Hao-ran¹, ZOU Xiao-bo³
		DOI: 10.3964/j.issn.1000-0593(2019)12-3809-07
		Near-infrared spectroscopy (NIRS) is a non-destructive detection method for qualitative or quantitative analysis by using spectral feature data. The integrity and representativeness of feature data determine the performance of the analytical model. However, existing analytical methods can only extract the feature data from the spectral subinterval. Then the developed models using these feature extracting methods have poor stability. In order to extract the feature from the high-dimensional NIR spectral data and improve the accuracy and stability of NIR spectral model, a spectral screening method using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm is proposed in this paper. Furthermore, the Tricholoma Matsutake, one of the high-value foreign trade products in China is taken as example to validate the developed classified model using LASSO algorithm. The effectiveness of the feature screening algorithm for the high-dimensional spectral data is discussed, and predictive accuracy and stability of the Tricholoma Matsutake distinguished and edible fungus classified model using LASSO and PCA are also analyzed. It is well known that the fresh Tricholoma Matsutake has the unique shape and it is easy to distinguish its counterfeit. However, it is difficult to distinguish the dry Tricholoma Matsutake from other mushrooms because all of dry mushrooms have the similar flake shape. As a result, dry Tricholoma Matsutake adulteration incidents have occurred frequently. 166 dry samples of Yunnan Tricholoma Matsutake, Pleurotuseryngii, Jujube hilt nipple mushroom and Agaricusblazei were selected in this experiment, and 166×512-dimensional raw spectral data were obtained by NIRQuest 512 NIR spectrometer with a spectral range of 900～1 700 nm. The standard normal transformation (SNV) was taken to pre-process the spectral data after the anomalous data eliminating. The LASSO was used to extract feature variables from the high-dimensional NIR spectral data based on the spectral pretreatment. Then the typical linear (k-Nearest Neighbor, KNN) and the nonlinear modeling (Back-Propagation neural network, BP) algorithms combined with the Kennard-Stone method were used to construct the Tricholoma Matsutake distinguished and edible fungus classified model. The effectiveness of models using LASSO and PCA were also analyzed. Furthermore, the predictive accuracy and the stability of the developed KNN model and BP model were analyzed by using the Monte Carlo method. The experimental results demonstrated that the prediction accuracy and stability of model using LASSO were better than those of the model using PCA. The prediction accuracy of the distinguished and edible fungus classified models using the original spectral data were 69.57% (BP), 60.87%(KNN) and 67.39% (BP), 65.22% (KNN) respectively. And the prediction accuracy of the distinguished and edible fungus classified models using LASSO algorithm were up to 100% (BP), 67.39% (KNN) and 89.13% (BP), 80.43% (KNN) respectively. The two models were performed by 10 times Monte Carlo method and the average results were 99.93% and 97.22%, respectively. Compared with the conventional feature selection methods (such as PCA), the LASSO algorithm can extract the feature from the high-dimensional NIR spectral data. And the accuracy and stability of the models using NIR spectral data can be improved. Furthermore, the developed algorithm is alternative to be a new feature extraction method for NIR spectral data analysis.
		2019 Vol. 39 (12): 3809-3815 [Abstract] ( 164 ) RICH HTML PDF (4495 KB) ( 77 )

	3816	*Impact Analysis of Infrared Spectra in Pterocarpus santalinus* and Confused Species Coated with Wood Wax Oil**
		LIU Jing¹, HUANG An-min², ZHANG Qiu-hui^1*
		DOI: 10.3964/j.issn.1000-0593(2019)12-3816-05
		The wood characteristics of P. tinctoricus Welw and Dalbergia louuelii are similar to Pterocarpus santalinu. Especially，after the two species have been painted with colored wood wax oil, it is difficult to distinguish from P. tinctoricus Welw, Dalbergia louuelii and Pterocarpus santalinu. As many rosewood furniture sold on the market are mostly surface-finished in order to achieve anti-corrosion, dust-proof, anti-cracking properties, as well as to improve the surface gloss and the texture of precious wood, the identification of wood itself is far from meeting market demand. Pterocarpus santalinus, P. tinctoricus Welw and Dalbergia louuelii finished with Wood wax oil were analyzed by the Tri-step Infrared identification（FTIR, SDIR and 2D-IR）. The three species were surface finished by Polishing-Carrier oil-Polishing-Coating oil-Drying. The wood powder of three species themselves and three surface-coated samples were analyzed by means of three IR spectroscopic methods, and the FTIR spectrum of wood wax oil was also determined. The results show that: (1) The FTIR spectrum of wood wax oil has strong peak at 2 925, 1 733, 1 465 and 1378 cm^-1, which coincide with the peak positions of three species themselves. C—H methylene symmetric stretching around 2 854 cm^-1, C—O stretching of aliphatic aldehydes at 1 233 cm^-1 and long-chain C—H methylene bending at 729 cm^-1 have the same embodiment between wood wax oil and three surface-coated species. The above results indicate that the characteristic peaks of infrared spectra of three species are not affected by wood wax oil. Correlation coefficient between three species themselves and three surface-coated samples can also confirm it. (2) The FTIR spectrum can distinguish P. tinctoricus Welw from Pterocarpus santalinus and Dalbergia louuelii at 1 595, 1 060 and 836 cm^-1; The SDIR spectrum can distinguish Dalbergia louuelii from 1 551 cm^-1 and can further verify the characteristic peak of P. tinctoricus Welw; For the 2D-IR spectrum, in the range of 1 425~1 800 and 850~1 300 cm^-1, the automatic front of Pterocarpus santalinus is obviously different from the other two species, and the absorption peak attributed to the ether compound at 1 250 cm^-1 can separate Pterocarpus santalinus. Redwood identification mainly uses wood anatomy and Surface finishing is mostly concentrated on the study of wood color change. This article makes the best of infrared spectroscopy. Finally, Functional group differences with characteristic peaks of tree species and wood wax oil can directly speculate different content of characteristic components and the specific substances of characteristic components are not required to determine. It is possible to accurately and quickly distinguish the Pterocarpus santalinus painted with wood wax oil and P. tinctoricus Welw and Dalbergia louuelii with which people are confused.
		2019 Vol. 39 (12): 3816-3820 [Abstract] ( 196 ) RICH HTML PDF (2927 KB) ( 48 )

	3821	Determination of Trans Fatty Acids in Edible Vegetable Oil by Laser Raman Spectroscopy
		JIANG Xue-song¹, MO Xin-xin³, SUN Tong^{2, 3*}, HU Dong²
		DOI: 10.3964/j.issn.1000-0593(2019)12-3821-05
		Trans fatty acids (TFA) in oils and fats are harmful to people’s health, so it is necessary to monitor their content. In this research, 79 samples of edible vegetable oils were collected, involving 9 varieties and 27 brands. The number of samples that were allocated to calibration and prediction sets was 53 and 26, respectively. Raman spectra of 79 edible vegetable oil samples were collected by a QE65000 Raman spectrometer, and adaptive iteratively reweighted penalized least squares was used to remove fluorescence background of Raman spectra. Then, various normalization methods were used to process Raman spectra, and preliminary selection of modeling wavenumber range of Raman spectra was carried out. After that, competitive adaptive reweighted sampling (CARS) method was used to select TFA-related variables, and partial least squares regression was used to correlate the spectral intensity of TFA characteristic variables with the real content determined by gas chromatography to establish quantitative prediction model of TFA content in edible vegetable oils. The results indicate that among various normalization methods, four normalization methods can improve the performance of PLS quantitative prediction model, and area normalization method has the best effect. After primary selection of wavenumber range, the range of wavenumber is reduced from 686 to 2 301 cm^-1 to 737 to 1 787 cm^-1, and the optimum range of wavenumber is determined to be 737 to 1 787 cm^-1. Thirty-one spectral variables are selected by CARS method. The selected spectral variables are mainly distributed near the Raman vibration peaks of 1 265, 1 303, 1 442 and 1 658 cm^-1, and the variables in the both sides of the Raman vibration peaks of 974 cm^-1 are also selected. In addition, the PLS modeling results of CARS method were better than those of the commonly used methods such as uninformative variable elimination and successive projections algorithm. Therefore, it is feasible to detect TFA content in edible vegetable oil by laser Raman spectroscopy combined with chemometrics. Normalization method, wavenumber range selection and CARS method can effectively improve the prediction accuracy and stability of TFA quantitative prediction model. The correlation coefficients and root mean square errors of optimized TFA quantitative prediction model in calibration and prediction sets are 0.949, 0.953 and 0.188%, 0.191%, respectively. Compared with the unoptimized prediction model, the root mean square error of prediction decreases from 0.361% to 0.191%, with a decrease of 47.1%. The number of variables used in modeling decreases from 683 to 31, accounting for only 4.54% of the original variables.
		2019 Vol. 39 (12): 3821-3825 [Abstract] ( 198 ) RICH HTML PDF (1974 KB) ( 193 )

	3826	Using Landsat-8 to Remotely Estimate and Observe Spatio-Temporal Variations of Total Suspended Matter in Zhoushan Coastal Regions
		PANG Shu-na¹, ZHU Wei-ning^1*, CHEN Jiang², SUN Nan³, HUANG Li-tong¹, ZHANG Yu-sen¹, ZHANG Ze-liang¹
		DOI: 10.3964/j.issn.1000-0593(2019)12-3826-07
		Total suspended matter (TSM) is one of the important parameters for ocean water quality and aquatic environment assessment. Zhoushan Islands is located on the edge of Hangzhou Bay, where sediments present very high concentration and TSM shows suspended status for long-term. The distribution and variation of TSM in Zhoushan Islands have great impacts on its coastal water quality, ferry, fishery and tourism. Because of its high spatial resolution and open access, Landsat-8 imagery has been widely used for ocean color studies and hence providing good spectral information for observing variations of TSM in Zhoushan coastal regions. This study used in-situ measured TSM absorption coefficient (a_p(440), m^-1) and water surface spectra to develop the TSM remote sensing model based on Landsat-8 imagery, and results show that the S-function using blue and near-infrared bands of Landsat-8 performed better than the other functions. The S-function is with the form a_p=3.72/(0.009+e^-5.249B5/B2). This function overcomes the shortcomings of previous inversion functions (e. g., linear, logarithmic, and exponential functions) which performed well for modeling datasets, but often failed when they were applied to real satellite images since spectral values in images are often much larger than those in the modeling dataset. Another problem of coastal and inland water color remote sensing is the atmospheric correction. The previous studies usually used a specific atmospheric correction method, but it might not return the best results. In this study, we tested and compared three types of atmospheric corrections models, FLAASH, 6S, and ACOLITE, and found that ACOLITE was better than the other two methods for ocean color remote sensing using Landsat-8, especially in blue band, where ACOLITE performed better than the FLAASH and 6S methods. The S-model was used to a series of Landsat-8 images covering the Zhoushan Islands from 2013 to 2018. The field measured and image-derived results show that TSM absorption coefficients in Zhoushan Islands were extremely high, ranging from 1.64 to 417.04 m^-1, with mean 118.47 m^-1, which account for more than 90% of total water absorption coefficients. The measured above-surface spectra demonstrated typical spectral signatures of complex turbid coastal water, with two peaks within green and red bands and relatively high reflectance within red and near-infrared bands. Due to the high concentrations of the riverine discharged TSM, remote sensing reflectance in estuarine and coastal regions were much higher than those in open sea. TSM concentrations illustrated a clear downward gradient from Hangzhou Bay to open sea, and TSM in coastal areas such as Qushan, Yangshan and Ningbo were much higher than those in open sea area such as Dongji and Shengsi. TSM distribution pattern in coastal regions were usually more complex than those in offshore regions. TSM concentrations in winter were usually much higher than those in summer, where the highest was found in December with value of 413.32 m^-1, and the lowest was found in August with value of 3.69 m^-1. There are also local peaks of TSM during May and October. Our results indicate that the TSM spatio-temporal variations in Zhoushan Islands are not only controlled by many natural environmental factors, such as currents, tides, typhoons, monsoons, but also aresignificantly influenced by many human activities, such as ferry, ocean shipping, harbor projects and island tourism.
		2019 Vol. 39 (12): 3826-3832 [Abstract] ( 211 ) RICH HTML PDF (3109 KB) ( 81 )

	3833	FTIR Spectrometry Characteristics of Diamonds from the Modern River Placer in Hunan and Their Origin Implication
		DENG Xiao-qin¹, QIU Zhi-li^1*, MA Ying^{1, 2}, BO Hao-nan¹
		DOI: 10.3964/j.issn.1000-0593(2019)12-3833-06
		FTIR spectrometry provides a crucial means to explore the types of diamonds and their impurities, which would to some extent reflect the physical-chemical conditions of the diamonds and also their origin characteristics, revealing the source information and genesis of the diamonds. In this paper, a set of samples of diamonds from the modern river placer in Hunan are analysed by in-situ measurement of FTIR spectrometry. The results show that the diamonds are mainly IaAB type (93%), with minor IaA type (5%), IaB type (<1%) and IIa type (2%). Most diamonds have medium to low nitrogen contents (35.0~436 μg·g^-1) and medium to low nitrogen aggregation (3%~57%, ave. 37%), while the others are relatively high (517~2 848 μg·g^-1, even up to 6 829 μg·g^-1). The probable range of storage temperatures of the diamonds are between 1 100 and 1 230 ℃, similar to the formation temperature of mineral inclusion in diamonds reported by previous literature. In addition, their residence time in the mantle are generally short (most <0.2 Ga), indicating that the diamonds from the modern river placer in Hunan are probably mainly generated in the upper mantle, and their source rocks are related to both ultramafic and eclogitic parageneses. Few diamonds with high nitrogen contents and low nitrogen aggregation features may be more closely related to eclogitic parageneses. By further comparing with another place where we have found primary diamonds, Guizhou, Yangtze Craton, it shows that Guizhou diamonds have characteristics of high proportion of IIa type (75%), high degree of fragmentation, poor integrity, low quality and strong corrosion, indicating that the diamonds from Guizhou are derived from the deeper mantle than Hunan’s. The different types and features of the diamonds from Hunan and Guizhou may show the diversity of their sources. Furthermore, the placer diamonds from Hunan and primary diamonds from Guizhou may constitute a complete mineralization sequence in Yangtze Craton, which may correspond to different environment stages of diamond mineralization, respectively. The haul distance of the diamonds from Hunan placer is relatively short, indicating a near-field source. Therefore, FTIR spectrometry provides an approach to explore the origin features and formation condition of the diamonds in Yangtze Craton.
		2019 Vol. 39 (12): 3833-3838 [Abstract] ( 159 ) RICH HTML PDF (2904 KB) ( 82 )

	3839	Technological Analyses and Research of the Green Glazed Tile Fragments in Liao Dynasty
		SUN Feng^{1, 2}, WANG Ruo-su¹, XU Hui-pan¹, LIU Cheng^{1, 2}, HUANG Feng-sheng¹
		DOI: 10.3964/j.issn.1000-0593(2019)12-3839-05
		As an ancient high-class building material, glazed tiles have been used in palaces and royal temples since the Northern Wei dynasty. In the Liao and Song dynasties, glazed tiles were not only used in royal buildings, but also used in cemetery buildings. The existing glazed tile in Ming and Qing dynasties is characterized by a large numbes of glaze layers falling off. However, on this remnant of green glazed tile in liao dynasty studied in this paper, although the glaze layer is extremely thin, ice cracks are all over the surface and the surface is white, the glaze layer is completely well preserved, almost no obvious warping and falling off, and has a good strength. In this paper, the super depth of field microscopy, scanning electron microscopy and energy spectrum(SEM-EDS) and X-ray diffraction(XRD) were used to study the technology and preservation of green glazed tile fragments unearthed from Xinli site of Liao dynasty emperial mausoleum site in Yiwulu Mountain of Beizhen Town in Liaoning province. Combining with literature materials, the results show that the raw material of green glazed tile in Liao dynasty is high quality porcelain clay with a few small grains of sand. Its phases include quartz (SiO₂), cristobalite low (SiO₂), sillimanite (Al₂[SiO₄]O) and corundum (Al₂O₃), which is an early example of ceramic clay as body. The green glaze layer belongs to the basic PbO-SiO₂-Al₂O₃ glaze system, which takes Cu as the color element, and the Pb content is lower than that of the glazed tiles of Ming and Ding dynasties. The lack of ZnO in the composition may be the reason why the glaze is of different shades of turquoise and low gloss. Green glaze has almost no peeling, and the bond strength of the glaze is very good, which is because the low lead thin glaze reduces the thermal expansion coefficient, eases the stress, the glaze thermal expansion coefficient matches, and shallow surface cracks are not easy to connect the internal and external environment. In addition, its use and storage environment are relatively dry, reducing the impact of water, almost no hygroscopic expansion and freezing expansion. This paper provides a reference for the study of similar cultural relic samples, the research on the construction technology of colored glaze in Liao dynasty and the preservation of colored glaze cultural relic, and promotes the related research work.
		2019 Vol. 39 (12): 3839-3843 [Abstract] ( 144 ) RICH HTML PDF (2133 KB) ( 58 )

	3844	Gemological and Spectral Characterization of Brownish Yellow Tourmaline from Mozambique
		LIAO Qin-jing, HUANG Wei-zhi, ZHANG Qian, PEI Jing-cheng^*
		DOI: 10.3964/j.issn.1000-0593(2019)12-3844-05
		Tourmaline is a borosilicate with complex crystal structure and chemical composition. The most common species of tourmaline on jewelry markets are elbaite and some dravite. There are numerous textbooks and articles in related fields focusing on elbaite rather than dravite. In this study, six light-yellow to brownish yellow tourmaline gemstones from Mozambique were examined. Standardgemological testing was followed by LA-ICP-MS, infrared spectroscopy, ultraviolet-visible spectroscopy, fluorescence spectroscopy and Raman spectroscopy testing. Standard gemological testing revealed that the physical and optical properties of the samples are basically in agreement with those of general tourmaline, but all samples have medium to strong green fluorescence under short-wave (254 nm) UV light, while general tourmaline is inert. In addition, the samples contain a lot of dark or grey granular mineral inclusions, but no tubular inclusions, gas-liquid two-phase inclusions, which are common in tourmaline. LA-ICP-MS testing shows that the samples belong to dravite and their average crystal structure formula is (Ca_0.15Na_0.85)_1.00(Mg_2.89Fe_0.02Al_0.09)_3.00Al₆(Si₆O₁₈)(B_0.95□_0.05O₃)₃(OH)₄. The samples with fewer inclusions were selected for infrared spectroscopy testing. The vibration peaks of hydroxyl group and Si—O are found in the 2 000～6 000 cm^-1 region, indicating that the samples contain water. There is a broad absorption peak between 400～500 nm in the Ultraviolet-visible spectra. The peak position is about 445 nm, which may be related to the charge transfer of Fe²⁺-Ti⁴⁺ and exchange-coupled Fe²⁺-Fe³⁺. The samples emit medium-strong green fluorescence under 254 nm UV light. There are 534 nm strong peak and 475 nm shoulder peak in fluorescence spectra. The fluorescence may be related to the Ti and Fe in the samples. Laser Raman spectra of the tourmaline samples are performed. The result is in accordance with the Raman spectra of dravite (species of tourmaline). The innovation of this paper is mainly embodied in the following two aspects: (1) the samples turn out to be dravite, whose spectral characteristics have not been studied in detail. (2) These dravites have a unique fluorescence under short-wave UV light, which has not been documented, and the reason for the origin of the fluorescence has been deduced by the author.
		2019 Vol. 39 (12): 3844-3848 [Abstract] ( 242 ) RICH HTML PDF (1929 KB) ( 106 )

	3849	Chemical Constituents and Spectra Characterization of Demantoid from Russia
		PEI Jing-cheng, HUANG Wei-zhi, ZHANG Qian, ZHAI Shao-hua
		DOI: 10.3964/j.issn.1000-0593(2019)12-3849-06
		Garnet is the most valuable subspecies in garnet family, and is popular for its beautiful appearance and rarity. In particular, demantoid from Russia is the most sought after object of domestic and foreign collectors. Previous studies were more on garnet minerals from different perspectives, but there are few studies on the demantoid. To study the chemical composition and spectroscopic characteristics of the Russian demantoid, the systematic research is conducted by using LA-ICP-MS, IR spectrum, Raman spectrum, UV-Vis absorption spectrum, so as to obtain the chemical components, especially rare earth elements and spectroscopic characteristics, and to analyze the causes of colour, and provide important data for its variety identification and traceability of origin. Chemical research shows that the demantoid is almost pure Andradite (Andradite>96.39 Mol.%). Among the secondary components, Cr₂O₃ content is relatively high, with an average of 0.502 Wt%. Cr and V are chromophore which causes the green color in garnet. Content of rare earth elements generally is low, ∑REE with an average of 4.85 μg·g^-1; And the light rare earth elements are significantly enriched, ∑LREE with an average of 4.56 μg·g^-1; Heavy rare earth elements relative loss, ∑HREE with an average of 0.29 μg·g^-1, ∑LREE/∑HREE=5.35~100.48. Most samples show Eu positive anomaly. The main Raman shifts are 995, 874, 841, 815, 576, 552, 515, 492, 451, 369, 351, 323, 311, 295, 263, 235, and 172 cm^-1. Raman spectra can only be used as one of the methods for the identification of variety, and have little effect on determination of its origin. The infrared spectroscopy studies show that the infrared spectra of the fingerprint region can be used to identify the demantoid, and the functional region shows the absorption peak of the structure water, which indicates that the Russian garnet contains a small amount of structural water, which is relate to its formation with hydrothermal process. Studies on UV-Vis absorption spectra show that Russian demantoid has an obvious absorption peak at 384 and 440 nm, a weak absorption peak at 436 nm, a wide absorption band near 620 nm, and a strong absorption from 500 nm to the ultraviolet region. The 440 nm absorption band was attributed to the ⁶A₁ to ⁴A_1g+⁴E_g(G) d—d transition of Fe³⁺ in octahedral site. The 620 nm absorption band was attributed to the ⁴A_2g(F) to ⁴T_2g(F) d—d inhibiting transition of Cr³⁺ in octahedral site. Fe and Cr are both chromogenic elements, and the O-Fe Charge transfer band and the 440 nm strong absorption band produce yellow and yellow-green garnet. The addition of Cr³⁺ produce a 620 nm wide absorption band, which absorbs orange light and makes the gem color shift to the green, producing the pure green demantoid. The fingerprint characteristics of Raman spectrum and infrared spectrum can be used for the accurate identification of demantoid. The characteristics of rare earth elements and the structural water features of functional groups in the middle infrared spectrum can provide important information for its origin determination.
		2019 Vol. 39 (12): 3849-3854 [Abstract] ( 193 ) RICH HTML PDF (2562 KB) ( 80 )

	3855	Chemical Composition and Colorimetric Characteristics of Bluish White Porcelain of Jingdezhen Hutian Kiln
		WU Jun-ming^{1, 2}, MA Hong-jiao¹, QIAN Wei^1*, ZHENG Nai-zhang², HAI Jin-xia²
		DOI: 10.3964/j.issn.1000-0593(2019)12-3855-06
		Jingdezhen is famous for producing bluish white porcelain in the Song Dynasty, and Hutian kiln is one of the main production sites of the time. The bluish white porcelain produced by Hutian kiln is exquisite and beautiful, and it is known as “false jade ware” and “Rao jade (Jingdezhen belonged to Raozhou government in ancient times)”. Chemical composition and colorimetric characteristics of glaze and body of Southern Song and Northern Song Jingdezhen Hutian kiln’s bluish white porcelain were analyzed by EDXRF and colorimeter in this study. The result shows that the body chemical compositions of Hutian kiln’s bluish white porcelain are basically the same in the Northern and Southern Song Dynasties, which are similar to local porcelain stones, such as the kind from Sanbo near Hutian kiln. The composition of glaze shows that it contains high CaO and a certain amount of MnO and P₂O₅, indicating that the glaze of Hutian kiln is “calcium glaze”, and a certain amount of plant ash is included in the glaze recipe. The result of colorimetric analysis shows that the main wavelengths reflected by Northern Song and Southern Song bluish white glaze are 500 and 496 nm respectively, and they belong to the green band of visible light. The glaze chemical composition and colorimetric data of Northern Song bluish white are more dispersed, and the Southern Song glaze has a smaller b value and bluer color. The study concluded that the glaze formulation of Hutian kiln bluish white porcelain went through a process from exploration to maturity and stability from the Northern Song Dynasty to the Southern Song Dynasty. The research results not only provide data support for the dating of bluish white porcelain in Hutian Kiln of Jingdezhen, but also provide scientific materials for the inheritance and dissemination of the techniques of making it.
		2019 Vol. 39 (12): 3855-3860 [Abstract] ( 181 ) RICH HTML PDF (2168 KB) ( 60 )

	3861	Research on Olivine Component Analysis Using LIBS Combined with Back-Propagation Algorithm
		YUAN Ru-jun^{1, 2, 3}, WAN Xiong^{1, 2*}, HE Qiang^{1, 2, 3}, WANG Hong-peng^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2019)12-3861-07
		Laser-induced breakdown spectroscopy analysis technology is a powerful method for analyzing material composition, but the use of it for quantitative analysis has the disadvantages of inaccurate analysis results and low reproducibility. In order to predict the composition information of olivine in nature accurately, this paper made 15 samples according to the composition information of olivine in nature, and 11 of them were used as standard samples, and the other 4 samples were used as test samples for LIBS quantitative analysis. Lastly, the laser-induced breakdown spectroscopy database of olivine was established with 50 spectra per sample. Then, the multiple linear regression algorithm and the back-propagation algorithm were used to analyze the 50 sets of data of this series of samples, which effectively reduced the inaccuracy of the test results caused by random errors. In the study of the content of forsterite and fayalite in olivine using back-propagation algorithm with data of laser-induced breakdown spectroscopy, the final results showed that the coefficient of determination of the prediction result was 0.901, close to the 0.911 which was yielded with conventional multiple linear regression algorithm. This indicated that the backward propagation algorithm’s prediction accuracy for olivine content was close to the multiple linear regression algorithm. Furthermore, the root mean square error of the result obtained with back-propagation algorithm was 28.64, which was better than the latter’s 29.23, which indicated that the result distribution obtained by the back-propagation algorithm was more concentrated. In addition, by analyzing the correspondence between the size of each numerical value in the correlation matrix and the position of each element’s spectral line, the results showed that the correlation matrix F inverted with back-propagation algorithm had a higher correlation with the physical meaning represented by it. This showed that the performance of the back-propagation operation was comparable to that of the traditional multiple linear regression algorithm, and it performed better in predicting the consistency of the data. In addition, the back-propagation algorithm could directly analyze the data of the olivine full spectrum data obtained by laser induced breakdown spectroscopy without the step of spectral peak finding, simplifying the process of data analysis and making up the shortcomings of the multiple linear regression algorithm in analyzing full-spectrum data.
		2019 Vol. 39 (12): 3861-3867 [Abstract] ( 213 ) RICH HTML PDF (4135 KB) ( 68 )

	3868	Analysis and Research of Residues from Iron Lamp Unearthed in Yihenaoer, Inner Mongolia by THM-Py-GC/MS
		HAN Hua-rui¹, WEI Shu-ya^1*, JING Yong-jie², WANG Xiao-kun³, LI Yan-xiang¹
		DOI: 10.3964/j.issn.1000-0593(2019)12-3868-05
		In the unearthed relics, most of the organic residues are attached to the objects or the surface of archaeological sites. Organic residues are often neglected in previous studies, because they have no definite shape, sometimes the amount of them is small and difficult to be found and preserved. However, as materials for ancient human life, this kind of organic residues contain important historical information and have cherished value. Even through the organic residues found in objects or sites, it can determine the use of objects and even sites. Ancient illuminating fuel belongs to such kind of organic residues. Animal tallow, vegetable oil and wax were used in ancient China. Vegetable oil and wax have been studied in the past, but the research of animal tallow only stays in distinguishing ruminants from non-ruminants. In this paper, pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) was introduced to study organic residues. Triglyceride and production in aging process could be completely decomposed into glycerol and fatty acid due to the loss of acyl group by pyrolysis temperature of 600 ℃ and pyrolysis time of 12 s. By calculating the relative content of fatty acid, the characteristics of different animal oils could be analyzed. At the same time, high temperature pyrolysis replaces the traditional pretreatment method of acidizing and purifying samples, which can retain the components of samples to the greatest extent. With the addition of excessive tetramethylammonium hydroxide, the fatty acids and alcohols in the sample can be converted into corresponding esters and ethers. The methylated sample can be separated at the initial 50 ℃ of gas chromatography for 5 minutes, then elevated to 280 ℃ for 10 minutes. The methylated sample components can be determined by mass spectrometry at a split ratio of 1∶100. The residual illuminating fuel from an iron lamp, which was excavated in a tomb from Yihenaoer, Inner Mongolia, were analyzed. According to the results, the main components of residues were fatty acids with continuous number of carbon atoms ranging from 7 to 22, in which relative content of tetradecanoic acid, pentadecanoic acid, hexadecenoic acid, heptadecanoic acid and octadecanoic acid were higher. Compared with the compounds of lard, beef tallow, and mutton tallow (three main kinds of animal tallows used as illuminating fuels), the contents of odd number of carbon atoms of fatty acids in mutton tallow were significantly more than the other two kinds of animal tallous. And this feature was also verified in archaeological sample. By combination with the other researchers’ results, the exact type of animal tallow contained in residues should be mutton tallow. Moreover, the hydrocarbons and alcohols contained in the archaeological sample were identified as beeswax according to the relative contents of fatty acids and alcohols. Thermally assisted hydrolysis-methylation pyrolysis-gas chromatography-mass spectrometry (THM-Py-GC/MS) provides a new method for the analysis of organic residues, especially animal tallous. In addition, a useful attempt has been made to identify the species of mixed organic residues.
		2019 Vol. 39 (12): 3868-3872 [Abstract] ( 175 ) RICH HTML PDF (1234 KB) ( 82 )

	3873	Prediction Soil Heavy Metal Zinc Based on Spectral Reflectance in Karst Area
		WANG Jin-feng^{1, 2, 5}, WANG Shi-jie^{2, 3}, BAI Xiao-yong^{2, 3*}, LIU Fang¹, LU Qian^{1, 2}, TIAN Shi-qi^{2, 4}, WANG Ming-ming²
		DOI: 10.3964/j.issn.1000-0593(2019)12-3873-07
		In order to solve the problem of inefficiency in measuring heavy metal zinc contentand soil samples collection difficultly with traditional way in karst area, it is greatly essential to get zinc content in soil by effective measures. The institutional area is a typical Karst region, soil zinc content as well as reflectance spectral of soil data were collected by inductively coupled plasma mass and Spectrophotometer. The reflectance spectra of measurement were handed by these steps. Firstly, 7 kinds of mathematical transformations were used including continuum removed, first differential, second differential, reciprocal transformation, absorbance transformation, first differential of absorbance, and second differential of absorbance. Secondly, spectral characteristic variables were determined based on the characteristic absorption band of spectral absorption of heavy metals. And then, further spectral characteristic variables were selected by correlation analysis. Finally, stepwise regression was used to determine the effective modeling spectral bands. Mapping relationships between Spectral bands and heavy metal zinc content were revealed by linear and nonlinear estimation algorithm, and the results aim to measure the heavy metal zinc in soil. It shows that the characteristic bands of zinc are associated with iron oxide, organic matter and clay mineral absorption band. It’s focused on 580，810，1 410，1 910，2 160，2 260，2 270，2 350，2 430 nm, and these results reveal that the absorption characteristics of heavy metal zinc possible were captured in karst area. The models were funded by Random Forests, Support Vector Machines, Partial Least Squares Regression to precision evaluation by coefficient of determination and the root mean square error of prediction. The best estimation model was obtained from spectrum transformation and model performance. The algorithm of Random forests for second differential transformation has the highest accuracy and is chosen as the best model. The content of heavy metal zinc was estimated by spectral reflectance. It is a rapid, efficient method for indirect evaluation of zinc. It provides a technical support for the dynamic monitoring of heavy metal content in karst areas.
		2019 Vol. 39 (12): 3873-3879 [Abstract] ( 165 ) RICH HTML PDF (6108 KB) ( 124 )

	3880	Inversion of Heavy Metals Content in Soil Using Multispectral Remote Sensing Imagery in Daxigou Mining Area of Shaanxi
		WANG Teng-jun^{1, 2}, ZHAO Ming-hai³, YANG Yun^1*, ZHANG Yang^{2, 4}, CUI Qin-fang¹, LI Long-tong¹
		DOI: 10.3964/j.issn.1000-0593(2019)12-3880-08
		The problem of low efficiency and higher cost exists in the traditional method mainly on “field-work point sampling then indoor experimental analysis”. Also the problem that how to choose the optimal factors indicating the content of heavy metals in soils is difficult to solve for the quantitative inversion of high precision using multispectral remote sensing technology. Using Landsat8/OLI satellite imagery, DEM data and soil samples data, the paper performed the analysis indicators of heavy metals in soil and the quantitative inversion of the content of heavy metals in soil in order to achieve an improved accuracy, taking a study case of a mountainous and forestry mining area called Daxigou mineral of Shaanxi in China. The work was as follows: A soil sampling scheme considering terrain and geomorphology characteristics was designed and evenly sampled in both sides along main topographic feature lines in the study area and 45 soil samples were acquired. Furthermore, a mixed samples from 45 samples were analyzed in laboratory so as to choose the most interested metals (i.e. Cu, Zn, As) as our focus according to both the degree of metals content bigger than that of national authoritative statistics and the type of mineral. Secondly, the paper suggested three types of factors including six spectral reflectivity from band two to seven of Landsat8/OLI imagery, and several spectral indices such as CMR, MNDWI, DVI, EVI etc., derived from Landsat8 image and also slope and aspect factors derived from DEM data were adopted to indicate the characteristics of the spatial distribution of the content of the three metals candidates considering land use and terrain circumstances in the study area. Subsequently, a correlation analysis of the content of three interested metals individually with six spectral reflectivity data, eight spectral indices and three terrain indicators was done using Least Squares principle. According to the consequence of the correlation analysis, the paper introduced the rule-based M5 model tree in the form of piecewise linear model which was used to estimate the content of Cu, Zn, As three metals in the principle of minimizing error rate. And an inversion model for the content of the three metals was constructed through the simulation, smoothing and pruning of the model tree with an input of all three types and 17 indicators mentioned above and 80% training samples. Also, a set of optimal indicators focusing on spectrum for the inversion were determined according to the principle of minimizing RMSE. Finally, the inversion results using 20% random samples were verified, showing that our suggested method achieved a decrease of RMSE value by 27.3%, 24.6%, 20.9%, and an improvement in confidence level for Cu and As, compared to that of the three interested metals using ordinary linear regression model. Also the thematic images showing the spatial distribution were mapped using the model. Then, the comparisons between the estimated value of the content of three metals and the background value published by Chinese government in 1990 were made. Furthermore, the statistical distribution rules of the three metals were concluded and verified using field survey results.
		2019 Vol. 39 (12): 3880-3887 [Abstract] ( 214 ) RICH HTML PDF (4247 KB) ( 127 )

	3888	Fluorescence Characteristics of DOM in Overlying Water of Erhai Lake and Its Indication of Eutrophication
		ZHAO Hai-chao^2,3, LI Yan-ping³, WANG Sheng-rui^1,3*, JIAO Li-xin³, ZHANG Li³
		DOI: 10.3964/j.issn.1000-0593(2019)12-3888-09
		The composition characteristics of dissolved organic matter (DOM) have an important effect on water quality. The study on the composition characteristics of DOM in overlying water is the great significance to the indication of the lake eutrophication status. The temporal and spatial changes of DOM components in overlying water of Erhai Lake, and the relationship between DOM components and water quality factors were quantitatively analyzed by fluorescence spectroscopy regional volume integral analysis (FRI). The fluorescence characteristics of DOM components in the different source water bodies and different eutrophication levels of plateau lakes were compared and analyzed. The results showed that humic acid was the main type of DOM in overlying water of Erhai Lake, followed by fulvic acid. The contents of DOM and humic acid were higher in the middle of Erhai Lake. Tryptophan and tyrosine and other protein-like DOM were higher in the south, and a higher level of the fulvic acid DOM was in the north. During the Algal Bloom (in October), the protein DOM and the fulvic acid DOM were lower and the humic acid DOM significantly increased, and biological source DOM and biological activity of DOM decreased. The endogenous release of sediments in the Erhai Lake and its inflow rivers mainly affected the humic acid DOM in overlying water, and then the wet deposition mainly increased the protein-like DOM. During the poor nutrition stage, the fulvic acid DOM had greater impact on water quality，and in the eutrophic stage, the humic acid DOM had a great influence on water quality. Following the increase of the lake eutrophication, the proportion of the protein-like DOM and fulvic acid DOM decreased in overlying water, and then the proportion of microbial degradation products and the humic acid DOM showed an increasing trend. The proportion change of fluorescent components in DOM had an indication of the lake.
		2019 Vol. 39 (12): 3888-3896 [Abstract] ( 264 ) RICH HTML PDF (7174 KB) ( 64 )

	3897	Spectral Imaging Detection of Crop Chlorophyll Distribution Based on Optical Saturation Effect Correction
		SUN Hong¹, XING Zi-zheng¹, QIAO Lang¹, LONG Yao-wei¹, GAO De-hua¹, LI Min-zan^1*, Qin Zhang²
		DOI: 10.3964/j.issn.1000-0593(2019)12-3897-07
		Chlorophyll content is an important indicator of photosynthesis capability and nutrient content in crops. Measuring chlorophyll content of crops is considered to be the most effective method for detecting crop growth status. In this paper, a multi-spectral camera was built to capture images of maize plant in RGB(Red, Green, Blue) and NIR(Near Infrared) band, which was the fundamentalfor the distribution analysisof nutritional status with rapidand non-destructive method. The RGB and NIR images were acquired by image acquisition platform. Light saturation correction of RGB images based on light saturation correction algorithm was studied. The crop SPAD distribution map was established following the image matching and segmentation, image information extraction and correction. In the experiment, images of 15 maize plants were acquired by RGB-NIR camera, and 68 SPAD values were measured at different positions of the plants. Firstly, the RGB images were corrected by light saturation correction algorithm. At the same time, the NIR images were filtered and enhanced. Secondly, the RGB and NIR images were matched with SURF (Speeded-Up Robust Features) and RANSAC (Random Sample Consensus) algorithm. Used RGB images color feature, the mask was generated with ExG (Extra Green) and OTSU algorithm, and applied in the RGB -NIR images segmentation. The R, G, B and NIR components of the image were extracted and the reflectance were corrected by the fourth-order gray-scale plate. The Intensity(I) component histogram and crop SPAD value distribution were compared to verify the effect of the optical saturation correction algorithm. The results show that I component of RGB image concentrates between [140～180] before optical saturation correction, and between [85～130] after optical saturation correction because of correction in image blurring and RGB image saturation. The correlation coefficients between the image components (R, G, B, NIR) and gray scale reflectance were 0.829, 0.828, 0.745 and 0.994, respectively. Then the pseudo-color images of R, G, B and NIR bands were generated. The reflectance results (R_NIR＞R_G＞R_R＞R_B) indicated the spectral characteristics of crops which absorbed light in blue and red regions, reflected light in green and near infrared regions. Thirdly, the SPAD values at pixel level were calculated. The accuracy of chlorophyll content fitted in SPAD formula with R and NIR component reflectance before and after correction were compared. The R² was 0.332 6 before correction and the R² after correction was 0.619 3. Finally, the SPAD distribution map of crops was drawn, which could provide technical support for analyzing and monitoring the nutritional distribution of crops.
		2019 Vol. 39 (12): 3897-3903 [Abstract] ( 173 ) RICH HTML PDF (2951 KB) ( 63 )

	3904	Screening of DON Contamination in Wheat Based on Visible/Near Infrared Spectroscopy
		JIANG Xue-song¹, ZHANG Bin², ZHAO Tian-xia², XIONG Chao-ping², SHEN Fei^2, HE Xue-ming², LIU Qin², ZHOU Hong-ping^1, LIU Xing-quan³
		DOI: 10.3964/j.issn.1000-0593(2019)12-3904-06
		Wheat is not only the main grain in China, but also is an important feed and industrial raw material. Wheat is susceptible to scab, which can produce vomitoxin whose scientific name is Deoxynivalenol (DON). Vomitoxin is carcinogenic and pose a serious threat to human and animal health. In recent years, due to the frequent occurrence of extreme and abnormal weather, the risk of DON infection is on the rise, which has become the main factor affecting the quality and safety of wheat products. However, traditional methods for detecting DON content have obvious problems such as cumbersome and time-consuming detection process. Therefore, developing a fast, low-cost and online detection method is of great significance for the safe production and processing of wheat. Firstly, 200 wheat samples with different degrees of scab infection were collected from all parts of Jiangsu. After milling, the content of DON in wheat was determined by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), and then the visible/near-infrared spectral of wheat were collected online. The data processing steps are: pre-processing the spectrum by multi-scattering correction and second derivative, and extracting the characteristic wavelength according to the competitive adaptive reweighted sampling algorithm, then using linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA) was used to establish a qualitative analysis model of wheat flour samples (with a national standard of 1 000 μg·kg^-1), and a quantitative analysis model of DON content in wheat flour samples was established according to partial least squares regression (PLSR). UPLC-MS/MS results showed that the risk of wheat DON contamination was higher, and the over-standard rate of the tested samples was 50%. Visible/near-infrared spectroscopy analysis showed that the spectral characteristics of different DON content wheat samples had some differences. The original spectrum and the second derivative spectrum showed that the higher the DON content, the lower the absorbance at 1 420 nm. Due to the low absolute content of DON and the limited detection limit of spectroscopy, the obvious clustering trend could not be found by principal component analysis. However, the LDA and PLS-DA discriminant models constructed according to the full spectrum and the characteristic spectrum can quickly identify and screen sound and infection samples, and the best recognition rate was 87.69%. According to the quantitative analysis results, the PLSR model of DON content in wheat samples was not ideal. The optimal model results: the correlation coefficient (r_p) of the prediction set was 0.688, the root mean square error (RMSEP) was 727 μg·kg^-1, and the relative analysis deviation (RPD) was 1.38. The accuracy and robustness of the model needed to be further improved. It is feasible to use visible/near-infrared spectroscopy and chemometrics methods to achieve on-line discrimination and screening of wheat DON content exceeding the standard, which provides a technical reference for the rapid and quality detection of wheat products in China. However, the quantitative analysis of DON content needs further research to explore the influence of external factors on the model, and it is planned to expand the sample size, collect wheat samples from different regions and different varieties, and improve the accuracy and universality of the model.
		2019 Vol. 39 (12): 3904-3909 [Abstract] ( 166 ) RICH HTML PDF (2254 KB) ( 65 )

	3910	The Online Detection Model Research of Tomatoes’ Bruise and SSD
		LIU Yan-de, RAO Yu, SUN Xu-dong, XIAO Huai-chun, JIANG Xiao-gang, ZHU Ke, XU Hai
		DOI: 10.3964/j.issn.1000-0593(2019)12-3910-06
		Soluble solids and bruise are the two main factors affecting tomato quality. The purpose of the study was to explore the feasibility of simultaneous on-line detection of bruises and soluble solids in tomatoes by near-infrared diffuse transmission spectroscopy. The near-infrared diffuse transmission spectra of tomato were collected under the condition of a single-channel fruit delivery speed of 5/s. The near-infrared diffuse transmission spectrum characteristics of the bruised and normal tomato samples were compared and analyzed. The results showed that there was a significant difference in the light intensity between the bruises and the normal tomato samples. The light intensity of the bruises was stronger than that of the normal fruits. The reason may be that the meat becomes soft and the light transmission becomes stronger after the bruising. The two absorption peaks are more than the normal fruit at 650 and 675 nm. The reason may be that the color of the tomato skin changes before and after theinjury. The first three main scores with the highest contribution rate were selected. After qualitative analysis of principal components of near-infrared diffuse transmission spectra of normal fruits and bruises, normal fruits and bruises could not be effectively clustered. Therefore, high-dimensional near-infrared diffuse transmission spectral qualitative discriminant model was selected. By establishing the near-infrared diffuse transmission spectrum partial least squares qualitative discriminant model of the injured tomato sample, the false positive rate of the partial least squares qualitative discriminant model is 0%, which can correctly discriminate the fruit, so the near-infrared diffuse transmission spectroscopy partial least squares qualitative discriminant model of the touched tomato sample was selected as the online knockout sorting model for tomato touch injury. Validation of samples that have not been involved in modeling can correctly identify bruises. After the injurious fruit was removed by the near-infrared diffuse transmission spectroscopic partial least-squares qualitative discriminant model, the classification was based on the soluble solids index. The model is preprocessed using all the bands and the 606～850 nm band, and the second-order derivative preprocessing is performed on all the bands and the 606～850 nm band spectrum, and the front-back smoothing is set to 9, and the continuous projection algorithm and genetic algorithm are used to optimize the soluble solids. The spectral modeling variables, through comparison found that the use of non-algorithm screening 606～850 nm band spectral variables modeling, the best effect, established a soluble solids online detection model, the prediction set root mean square error of 0.43 Brix°. Simultaneous on-line detection of bruising and soluble solids using samples not involved in modeling demonstrated that the accuracy of sorting of bumped specimens was 96%, and the accuracy of sorting of soluble solids samples was 91%. The experimental results show that the simultaneous on-line detection of tomato bruising and soluble solids near-infrared diffuse transmission spectroscopy is feasible.
		2019 Vol. 39 (12): 3910-3915 [Abstract] ( 208 ) RICH HTML PDF (3673 KB) ( 67 )

	3916	Determination of Fat in Walnut Beverage Based on Least Squares Support Vector Machine
		LI Zi-wen¹, LI Zong-peng¹, MAI Shu-kui¹, SHENG Xiao-hui¹, YIN Jian-jun¹, LIU Guo-rong², WANG Cheng-tao²,ZHANG Hai-hong³, XIN Li-bin⁴, WANG Jian^1*
		DOI: 10.3964/j.issn.1000-0593(2019)12-3916-05
		Near-infrared spectroscopy was used to quantitatively analyze the fat content of walnut beverage. At the same time, modeling variables were optimized and modeling methods were compared to optimize the best model. In order to eliminate the influence of scattering on the spectrum, the data are preprocessed by the standard normal transformation (SNV) method. The preferred characteristic wavelengths of genetic algorithms (GA) combined with backward interval partial least squares (BiPLS) were used as input variables of partial least squares (PLS) and least squares support vector machine (LS-SVM) respectively to establish model of fat content in walnut beverage. The R², RMSEP and RPD were used to evaluate the effect of spectral band selection method on the construction of fat index model in walnut beverage and determine the best modeling method. The results showed that the variable selection could optimize the model. 150 and 30 variable points corresponding to the characteristic absorption peaks of the fat components in walnut beverage samples were selected by BiPLS and GA-BiPLS methods, respectively, accounting for 10% and 2% of the full spectrum. The RMSEP value of the PLS model decreased from 0.049 to 0.043 and 0.040, respectively, and the R² increased from 0.964 to 0.973 and 0.974. The range error ratio RPD increased from 4.88 to 5.62 and 6.00, and the principal component number also decreased to varying degrees. The method of variable selection could reduce model dimensions and improve model accuracy. Compared with the PLS model, the R², RMSEP and RPD values of the LS-SVM model showed better results, reaching 0.986, 0.036 and 6.52, respectively. The LS-SVM model has higher accuracy and stability than the PLS model. Since PLS is a classic linear modeling method, the nonlinear factors in the sample data set are ignored in the process of building the model. However, there was a complex nonlinear relationship between fat content and near-infrared spectral information, which is due to the interference of noise, background and other factors in the spectral measurement process of walnut beverage samples and the interaction between various indicators. The LS-SVM method could enhance the correlation between spectral variables and index concentration, so that the established model has better accuracy and universality. It shows that in the actual production, the LS-SVM method has excellent feasibility, which reflects its great potential in the analysis of the quality of walnut beverage. Based on the LS-SVM method, the quantitative analysis model of walnut fat content has accurate and stable characteristics, which can provide technical reference for the quality monitoring of walnut beverage production, and provide a new idea for the analysis of beverage quality.
		2019 Vol. 39 (12): 3916-3920 [Abstract] ( 181 ) RICH HTML PDF (1490 KB) ( 73 )

	3921	Analysis of Mineral Elements in Different Germplasm of Cistanche deserticola
		ZHENG Lei^{1, 2}, GUO Yu-hai^2*
		DOI: 10.3964/j.issn.1000-0593(2019)12-3921-04
		The content of mineral elements in Chinese herbal medicines is an important indicator for the quality evaluation of Chinese herbal medicines and is closely related to the growth and development, the formation of functional substances and the efficacy. The content and proportion of mineral elements vary with origin, harvest time, and harvesting parts, but the germplasm is the stablest and most important factor influencing the content and proportion of mineral elements in Chinese herbal medicines. Inductively coupled plasma atomic emission spectrometry (ICP-AES) can rapidly and simultaneously determine a variety of mineral elements. It has been widely used in the determination of mineral elements in Chinese herbal medicines. Cistanche deserticola is a famous tonic herbal and its mineral element content and proportion have attracted more and more attention. In this study, using C. deserticola germplasm of different flower colors as materials, the mineral element K, P, Ca, Mg, Na, Fe, Mn, Zn, Cu and Mo in C. deserticola germplasm of different flower colors were determined by ICP-AES method after the materials digestion with nitric acid and perchloric acid. The results show that: (1) The germplasm affected the content of mineral elements in C. deserticola. C. deserticola germplasm of different flower colors were rich in K, P, Ca, Mg, Na, Fe, Mn, Zn, Cu, Mo, but with significant differences. (2) The content and accumulation of K in C. deserticola germplasm of different flower colors were the highest among macroelements. Especially, the content and accumulation of K in C. deserticola germplasm of the white color flower reached 15.91 mg·g^-1 and 727.76 mg·plant^-1. The content and accumulation of P in C. deserticola germplasm of different flower colors were the lowest among macroelements. The content and accumulation of P in C. deserticola germplasm of the lavender color flower were 0.45 mg·g^-1 and 21.8 mg·plant^-1. (3) The content and accumulation of Fe in C. deserticola germplasm of different flower colors were the highest among microelements. Especially, the content and accumulation of Fe in C. deserticola germplasm of the yellow color flower reached 722.33 μg·g^-1 and 30 251.29 μg·plant^-1. The content and accumulation of Mo in C. deserticola germplasm of different flower colors were the lowest among microelements. The content and accumulation of Mo in C. deserticola germplasm of the lavender color flower were 0.11 mg·g^-1 and 5.12 mg·plant^-1. (4) The content and accumulation of K, Ca, Mg, Mn, Zn were with higher values in C. deserticola germplasm of the white color flower, while the content and accumulation of K, Ca, Mg, Na, Mn were with lower values in C. deserticola germplasm of the lavender color flower. (5) The germplasm affected the proportion of mineral elements in C. deserticola. The proportion of mineral elements in C. deserticola germplasm of different flower colors were different. The proportion of K∶P and Fe∶Mn were with significant differences, while Ca∶Mg and Zn∶Cu were with little differences. Conclusion: C. deserticola was rich in mineral elements, and the germplasm affected the content, accumulation and proportion of mineral elements in C. deserticola and there are significant differences among different flower colors. The results should be concerned about and paid attention to. Mineral elements are important indicators for the quality evaluation of Chinese herbal medicines and affect the growth and development. Therefore, the results of this study could provide the basis for quality evaluation, nutrition evaluation and scientific fertilization of C. deserticola germplasm of different flower colors.
		2019 Vol. 39 (12): 3921-3924 [Abstract] ( 136 ) RICH HTML PDF (767 KB) ( 42 )

	3925	A New Ratiometric Fluorescence Probe Based on CuNCs and CQDs and Its Application in the Detection of Hg²⁺
		SHI Ji-yong, LI Wen-ting, HU Xue-tao, SHI Yong-qiang, ZOU Xiao-bo^*
		DOI: 10.3964/j.issn.1000-0593(2019)12-3925-07
		Mercury is a typical low-dose and high-toxic substance, which widely exists in the environment and water. It is transmitted and accumulated through the food chain, which is easy to cause harm to human body. Therefore, accurate and rapid monitoring of Hg²⁺ content is of great significance for ensuring food safety. At present, there are many techniques to detect mercury ions such as high performance liquid chromatography atomic fluorescence spectrometry (LC-AFS), inductive coupled plasmamass spectroscopy (ICP-MS), electrochemical methods and fluorescence analysis methods. Ratio fluorescence probe has dual emission fluorescence characteristics. The built-in calibration function can reduce the detection errors caused by probe concentration and various environmental factors, and effectively overcome the shortcomings of single emission fluorescence probe. A novel ratio fluorescent probe based on carbon quantum dots (CQDs) and copper nanoclusters (CuNCs) was proposed for the rapid detection of Hg²⁺ in crabs. The main research contents and results are as follows: (1) The preparation of CQDs-CuNCs composite system, CQDs were synthesized by microwave-mediated method with sucrose as carbon source and polyethylene glycol as passivator; CuNCs were synthesized by hydrothermal method using ascorbic acid as reductant and stabilizer, and then self-assembled into CQDs-CuNCs composite system. (2) Characterization of CQDs-CuNCs composite system. The CQDs-CuNCs composite system was characterized by high power transmission electron microscopy (HRTEM), ultraviolet-visible absorption spectroscopy (UV-Vis), fluorescence spectroscopy (FL) and Fourier transform infrared spectroscopy (FTIR). The results show that the CQDs-CuNCs ratio fluorescent probe with dual emission characteristics has been successfully synthesized. (3) The stability of CQDs-CuNCs composite system was tested. The stability of CQDs-CuNCs ratio probe was compared with that of traditional single-channel CuNCs probe. The results show that the migration of CQDs-CuNCs ratio probes is stronger and stabler than that of single-emitted CuNCs when the probe concentration drift and temperature fluctuation are measured. (4) The CQDs-CuNCs composite system detects Hg²⁺. When Hg²⁺ exists, the CuNCs in the composite system will agglomerate, but CQDs will not be affected, resulting in the fluorescence quenching of CuNCs at 443 nm and the fluorescence intensity of CQDs at 545 nm almost unchanged. Quantitative detection of Hg²⁺ was realized based on the relationship between the ratio of fluorescence intensity (I_{443 nm}/I_{545 nm}) and the concentration of Hg²⁺. In the standard sample detection, the quenching rate of CQDs-CuNCs composite system at I_{443 nm}/I_{545 nm} and single-emission CuNCs has a good linear relationship with Hg²⁺ (0.1～12 μmol·L^-1), the correlation coefficients are 0.994 7 and 0.991 6, and the detection limits (3σ/S) are 2.83 and 3.62 nmol·L^-1, respectively. In crab sample detection, the recoveries of CQDs-CuNCs ratio probe and single-emission CuNCs were 102.5%~105.4% and 104.2%~112.5%, respectively. The results show that the CQDs-CuNCs composite system has higher sensitivity and recovery to Hg²⁺ than single-emission CuNCs. The CQDs-CuNCs ratio fluorescent probe constructed in this study can be used for rapid and accurate detection of Hg²⁺ in food.
		2019 Vol. 39 (12): 3925-3931 [Abstract] ( 165 ) RICH HTML PDF (4486 KB) ( 54 )

	3932	Quantum Chemical Vibrational Study, FTIR and FT-Raman Spectra of 1,3-Diphenyl Propenone
		Revathi Haldorai¹, M. Thirumalaikumar², S. Sampathkrishnan³, C. Charanya⁴, N. Balamurugan^5*
		DOI: 10.3964/j.issn.1000-0593(2019)12-3932-08
		The Fourier Transform Infrared (FTIR) and Fourier transform Raman (FT-Raman) spectra of 1,3-Diphenyl Propenone were recorded in the regions 4 000～400 and 4 000～100 cm^-1, respectively, in the solid phase. Molecular electronic energy, geometrical structure, harmonic vibrational spectra was computed at the DFT/ 6-31G(d,p) and three parameter hybrid functional Lee-Yang-Parr/6-31G(d,p) levels of theory. The vibrational studies were interpreted in terms of potential energy distribution (PED). The results were compared with experimental values with the help of scaling procedures. Most of the modes have wave numbers in the expected range and are in good agreement with computed values and also the molecular properties of Mulliken population analysis have been calculated. Besides, thermodynamic properties were performed.
		2019 Vol. 39 (12): 3932-3939 [Abstract] ( 150 ) RICH HTML PDF (1955 KB) ( 77 )

	3940	Quantum Chemical and Corrosion Inhibition Studies of (4-Chlorophenyl)-N-(4-Methylphenyl) Nitrone
		Rubarani. P. Gangadharan^1*, S. Sampath Krishnan², M. Thirumalaikumar³
		DOI: 10.3964/j.issn.1000-0593(2019)12-3940-06
		The compound (4-chlorophenyl)-N-(4-methylphenyl) nitrone (4CPNMPN) has been selected as one of the new nitrone derivative for our study. The molecular structure of the compound was investigated based on frontier orbital analysis and natural bond orbital (NBO) theory. The present work also focuses on the inhibition efficiency of the compound. It is an attempt to find the correlation between the molecular structure of the compound and possible behaviour like corrosion inhibitors. The NBO analysis and the values of electric dipole moment (μ) of the investigated molecule were computed using DFT calculations. The molecule orbital contributions were studied by using the total (TDOS) density of states. The strong evidences that the compound can be used as an efficient nonlinear optical (NLO) of 4CPNMPN were demonstrated by considerable polarizability and hyperpolarizability values obtained at DFT levels.
		2019 Vol. 39 (12): 3940-3945 [Abstract] ( 179 ) RICH HTML PDF (1548 KB) ( 56 )

	3946	Deflagration Characteristics of Forest Trees from the Perspective of UAV
		LÜ Zhen-yi¹, HE Cheng^2, SHU Li-fu^3, JI Ren-xin⁴, ZHANG Si-yu², WANG Yue², GAO Jian-qi¹, ZHAO Feng-jun³
		DOI: 10.3964/j.issn.1000-0593(2019)12-3946-07
		The phenomenon of “deflagration” in forest fires is characterized by a sudden occurrence of high-intensity combustion with high spreading speed. Consensus hasn’t been reached about the causes of “detonation fire” so far. In this study, forest fire videos, real-time pose data, and wind speed estimation derived from KWT (Keweitai) drone, together with field research data were analyzed to characterize the spatial and temporal feature of forest fire spreading within a valley topography in Liangshan Prefecture, which killed 27 firefighters on 31 March 2019. We found that: the microclimate played a dominant role in complex terrain, and the special period of the high mountain terrain was 4:00—12:00 every day for the quiet wind period, which was the best period for the canyon forest fire fighting. The wind speed of the valley topography was active from 15:00—17:00 in the afternoon and from 20:00—22:00 in the evening, the model of relationship between inclination angle of the drone and wind speed was established y=-1.043 5+1.150 1x(y is the wind speed m·s^-1, and x is the uav inclination °) . The wind speed and direction of the mountain, valley and mountainside were not uniform, and there was no positive correlation between wind speed and altitude. The peak state of the airflow velocity occurred in the middle of the valley to the depth of the valley, and there would be turbulent flow at the bottom of the valley, which provides objective and necessary conditions for the occurrence of deflagration fire. The short duration of drones was the bottleneck of forest fire monitoring.
		2019 Vol. 39 (12): 3946-3952 [Abstract] ( 402 ) RICH HTML PDF (2733 KB) ( 80 )

	3953	On-Orbit Analysis and Correction of the Inconsistency in the Response Characteristics of TG-2/MAI CCD Pixels
		GUO Jun-jie^1,2,3,4, YAO Zhi-gang^1,4,5*, HAN Zhi-gang^1,4, ZHAO Zeng-liang^1,4, YAN Wei³, JIANG Jun^1,4
		DOI: 10.3964/j.issn.1000-0593(2019)12-3953-10
		The difference in the response characteristics of charge-coupled device (CCD) pixels is one of the main factors restricting the quality of the Multi-angle Polarization Imager (MAI) and its quantitative application. In order to improve the quality of CCD imaging, this paper used a total of 104,403 frames of observational data from September 2016 to March 2018, based on the full-range multi-section analysis and correction method, to realize the analysis and correction for the inconsistency in the pixel response characteristics of MAI polarized and non-polarized channels. And the results were verified using the Global Ozone Monitoring Experiment 2 (GOME-2) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data. Firstly, assuming there are sufficient observational samples, that is, the objects observed by each pixel have the same ergodicity, and the average Digital Number (DN) value of all samples corresponding to each CCD pixel could represent the response characteristics of each pixel of the CCD. Secondly, constructing reference images for each channel by using 104 403 frames observation data, and the 5×5 pixels in the CCD center are used as standard DN values corresponding to each reference image. Next, the response characteristics of the MAI polarized and non-polarized channels are analyzed respectively. The results show that there is significant inconsistency in the response characteristics in each MAI pixel and each channel. The inconsistency in each channel falls roughly between 4% and 10%. And for polarized channels, the inconsistencies in the pixel response characteristics between the three polarized channels in the same polarization band have some similarities, but there are certain differences, and the difference in pixel response inconsistency is basically within 1%. Then, the observational data for two years are divided into two periods for comparative analysis. The result shows that the CCD pixel response characteristics do not decay over time. This also shows that the amount of reference image data is sufficient, which further rerifies the rationality of the above assumptions. Therefore, the full-range multi-section correction method can be used to correct the inconsistency of each pixel’s response characteristics on a channel-by-channel basis. After correction was performed based on this method, the image quality of MAI is significantly improved. The dependence on the observational zenith angle of the CCD pixel response is significant. The image is smoother, and the graininess is basically eliminated. Also, the scenes of some areas have changed-especially targets with a reflectivity between low and medium reflectivity, such as broken cloud and so on. Compared with GOME-2, the average absolute deviations between the reflectance of the MAI 565, 670, and 763 nm bands and the GOME-2 reference reflectance are reduced from 1.6%, 4.2%, and 2.2% to 0.5%, 2.6%, and 0.4% after correction, respectively. In addition, the cloud detection result based on the multi-band cloud identification method shows that, compared with the MODIS cloud detection product at a similar time, the corrected MAI cloud detection result looks more accurate. Therefore, the full-range multi-section analysis and correction method can realize the monitoring and correction of the inconsistency in the response characteristics of the MAI CCD pixels, which significantly improves the quality of the on-orbit observations of this instrument. And this method can also be applied to the on-orbit calibration of other CCD instruments.
		2019 Vol. 39 (12): 3953-3962 [Abstract] ( 172 ) RICH HTML PDF (5088 KB) ( 45 )

	3964	《光谱学与光谱分析》2019年(第39卷)总目次(第1～12期)
		《光谱学与光谱分析》编辑部

		2019 Vol. 39 (12): 3964-3984 [Abstract] ( 147 ) PDF (1088 KB) ( 99 )

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