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2022 Vol. 42, No. 07 Published: 2022-07-01

	1993	Hyperspectral Non-Destructive Analysis of Red Meat Quality: A Review
		BAI Xue-bing, MA Dian-kun, ZHANG Meng-jie, MA Rui-qin^*
		DOI: 10.3964/j.issn.1000-0593(2022)07-1993-06
		With the complete construction of the All-Roundly Well-off Society in China, residents have higher and higher requirements for the quality of life, especially for food safety. However, food quality and safety accidents such as “deteriorated meat”, “adulterated meat”, “added meat” and “water-injected meat” frequently occurring to threaten the life safety of Chinese residents seriously and hinder healthy development of the market. The quality test method of red meat is a physical and chemical experiment that seriously damages the samples and is only applicable to the spot check of the market supervision department. Hyperspectral technology is a kind of in-situ non-destructive, high-throughput and, fast intelligent detection technology which provides effective technology for solving the low operational feasibility of traditional detection methods. It greatly promotes the development and improvement of the quality and safety supervision system of red meat in China. This paper aims to review the research progress of hyperspectral technology in non-destructive detection of red meat quality. Firstly, the advantages and disadvantages of the red meat quality model based on the Hyperspectral technique are summarized. Its advantage is high resolution and a combination of image and spectrum, which will provide better data for the model. Then, the key algorithms in the model are analyzed: (1) Due to regions of interest obtained manually, automatic separation of regions of interest will be one of the focus of research; (2) The spectral preprocessing algorithm is mainly selected by observing the spectral signal or extrapolating by model, so there is no standard general preprocessing algorithm; (3) The combination of spectrum and image features can more comprehensively describe the quality of red meat and provide a batter basis for modeling; (4) The linear model is more mature and stable, but the research potential of nonlinear model is better for the complex environmental factors in red meat quality detection. Finally, the future development direction and research focus of hyperspectral technology in red meat quality prospect. Finally, the key research direction of hyperspectral non-destructive detection for red meat quality is concluded as improving algorithm automation, making full use of spectrum information and strengthening the application of the nonlinear model based on the summary of the research results in recent years.
		2022 Vol. 42 (07): 1993-1998 [Abstract] ( 185 ) RICH HTML PDF (1434 KB) ( 188 )

	1999	Application Progress of Spectral Detection Technology of Melamine in Food
		LÜ Ru-lin¹, HE Hong-yuan^1*, JIA Zhen¹, WANG Shu-yue¹, CAI Neng-bin², WANG Xiao-bin¹
		DOI: 10.3964/j.issn.1000-0593(2022)07-1999-08
		Melamine is an illegal food additive in beans and dairy products. As a cheap substitute for protein, melamine was illegally added into milk powder and other foods, causing serious social harm and greatly threatening the safety of people’s lives and property. At present, spectral technology has become an effective means to identify and quantitatively detect illegal food additives, which provides a reliable research method and identification basis for the quality supervision department. The timeliness, non-destructive and accuracy of spectral detection technology improve the detection efficiency of melamine in food and promote the development of accurate and automated food quality detection. In recent years, a large number of studies have focused on the spectral detection of melamine, such as the development of new enhanced substrates or sensors to reduce the detection limit of melamine and improve the detection accuracy; Develop more portable automatic spectrum rapid detection equipment, reduce the detection cost and improve the detection efficiency. These spectral technologies have their advantages, but it is difficult to form a standardized and unified detection specification, making all kinds of spectral detection technologies only stay in the experimental stage and can not be applied to actual combat. On the other hand, with artificial intelligence and pattern recognition technology, spectral data analysis methods have made great progress in recent years. Various spectral preprocessing and data modeling methods have been proposed, which greatly improves the sensitivity and stability of spectral detection technology. The application status of spectral techniques (Raman spectroscopy, near-infrared spectroscopy, fluorescence spectroscopy, spectral imaging, etc.) in the detection of melamine in recent ten years was reviewed. The detection limits, quantitative ranges and sample pretreatment methods of different instruments were summarized; The applicability of various spectral preprocessing and spectral data modeling methods in different spectral data is analyzed, the advantages and disadvantages of these methods and the suitable instruments are summarized, and their application prospects and research trends have prospected.
		2022 Vol. 42 (07): 1999-2006 [Abstract] ( 176 ) RICH HTML PDF (1706 KB) ( 120 )

	2007	Flame Spectrum and Active Particles Analysis of the Effect of Dielectric Barrier Discharge Induced on Gliding Arc Discharge With the Mixture of Methane-Air-Ar Within A Dual Mode Discharge
		PEI Huan¹, CHEN Lei^1*, WANG Si-yuan², YANG Kun¹, SONG Peng²
		DOI: 10.3964/j.issn.1000-0593(2022)07-2007-06
		The discharge of DBD in unburned gaseous fuel or the combustible mixture will produce a lot of active free radicals, which can promote combustion and improve the combustion characteristics of fuel. In this paper, the effect of DBD excited methane on gliding arc flame is studied by using the key active particles (CH and OH) produced by DBD to enhance combustion. Therefore, a self-designed DBD-Gliding arc dual-mode plasma exciter is used to excite argon, methane and air mixture by using a coaxial Dielectric barrier discharge structure. The argon, methane and air mixture after excitation is fed into the gliding arc end for ignition. The volume flow ratio of argon to Air-methane in the inlet passage can reach Ar∶(CH₄+Air)=1∶30 by adjusting the Airflow rate to 4.76 L·min^-1 and adding methane to 0.5 L·min^-1, the mixture of argon, methane and methane can be discharged and burned uniformly and stably when the equivalent ratio of chemical combustion isΦ=1. The discharge voltage in the DBD segment varies from 15 to 20 kV, and the discharge frequency varies from 6 to 10 kHz. The voltage and frequency in the gliding arc discharge segment remain constant at 4 kV and 10 kHz, respectively, the type and spectrum intensity of free radicals in gliding arc flame were measured by a high-speed optical fiber spectrometer, and the effect of methane excited by discharge parameters on free radicals (CH and OH) in-flame was analyzed. The results show that the increase of DBD voltage and frequency can promote the coupling reaction in the flame and can effectively increase the content of active particles in the methane gliding arc flame. The OH group and CH group play an important role in the combustion chain reaction. The OH and CH groups in the flame increase with the increase of DBD discharge voltage and frequency. After DBD discharge, the spectrum intensity of the active particles increases, and the characteristic spectrum is more obvious than that of a single-mode. After the methane is excited by DBD, the flame composition changes, and the methane combustion reaction at the exit of the gliding arc is sufficient. The higher the flame temperature, the more likely it to produce an OH group. Compared with the single-mode GAD, the Double mode discharge can promote the chain chemical reaction process and fuel combustion.
		2022 Vol. 42 (07): 2007-2012 [Abstract] ( 130 ) RICH HTML PDF (2785 KB) ( 70 )

	2013	Fast Spectral Calibration Method of Spectral Imager
		WANG Jian-wei^{1, 2}, LI Wei-yan¹, SUN Jian-ying¹, LI Bing¹, CHEN Xin-wen¹, TAN Zheng¹, ZHAO Na¹, LIU Yang-yang^{1, 3}, LÜ Qun-bo^{1, 3*}
		DOI: 10.3964/j.issn.1000-0593(2022)07-2013-05
		Spectral calibration is determining the central wavelength of each channel of a spectrometer. To obtain the spectral radiance, it is usually necessary to calibrate the spectrometer and map the output value of the spectrometer to a physical quantity radiance. Different spectrometers, The spectral response is different, so it is necessary to determine the spectral response of each channel during the spectral calibration process. The spectral imager can be regarded as a composition of multiple spectrometers, and the center wavelength and spectral response of all points need to be calibrated. Since the birth of the first imaging spectrometer, its calibration method has been gradually fixed. A monochromator with the higher spectral resolution is required, and its spectral bandwidth is much smaller than the spectral response bandwidth of the spectral imager so that quasi-monochromatic light can be considered a pulse function. According to the characteristics of the pulse function, changing the wavelength of the quasi-monochromatic light and scanning the response wavelength range of the spectral imager is a process of sampling the spectral response function at intervals.. Therefore, the spectral imager’s central wavelength and spectral response function can be directly obtained from the spectral calibration data. With the development of technology, the sensitivity of the detector is getting higher and higher, and the resolution of the spectral imager is getting higher and higher. Higher requirements are put forward for the quasi-monochromatic light required for the spectrum calibration. However, the narrower the bandwidth of the quasi-monochromatic light, the lower its energy, and it takes longer to obtain data that meets the signal-to-noise ratio, which reduces the efficiency of calibration. In this paper, we combined the characteristics of quasi-monochromatic light’s spectral line type and spectral response function approximating to Gaussian function. Through theoretical analysis, a method of spectral calibration using wide-band quasi-monochromatic light is proposed, which can effectively reduce the calibration step of spectral calibration improves the efficiency of calibration and is suitable for the rapid calibration of spectral imagers. This method is used for the spectral calibration of a space-borne hyperspectral imager. The spectral imager uses a prism to split light and has the characteristics of non-linear dispersion. The spectral resolution varies from 2 to 18 nm, and there is a large curve of spectral lines. As a result, the center wavelength of each pixel is different, and spectral calibration is required for each pixel. To avoid the discontinuity of the central wavelength of the adjacent field of view caused by the calibration of the separate field of view, the quasi-monochromatic light spot emitted by the monochromator illuminates the entire slit, and a cylindrical lens and ground glass are placed between the slit and the monochromator. The cylindrical lens is used to converge the light perpendicular to the slit direction to improve the energy utilization; the ground glass is used to homogenize the light, and the presence of ground glass greatly reduces the energy entering the spectral imager. Combining the method proposed in this paper increases of the accuracy the bandwidth of monochromatic light, and the increase of energy have finally completed the rapid calibration of the spectral imager. The mercury lamp verifies that the spectral calibration accuracy is 0.23 nm.
		2022 Vol. 42 (07): 2013-2017 [Abstract] ( 136 ) RICH HTML PDF (5690 KB) ( 127 )

	2018	Research on Oil Spill Status Recognition Based on LIF
		YUAN Li¹, XIE Bei-bei², CUI Yong-qiang², ZHANG Xiao-dan², JIAO Hui-hui²
		DOI: 10.3964/j.issn.1000-0593(2022)07-2018-07
		With the rapid development of the marine transportation industry and the offshore oil exploitation industry, oil spill pollution is becoming increasingly serious, posing a great threat to the marine environment and ecological balance. Therefore, the treatment and improvement of oil spill pollution have become an urgent and important work in marine environmental protection engineering. The identification of oil spills in different states is the basis and key to solving the problem of oil spill pollution. The oil spill on the sea mainly includes two different stages: non-emulsification and emulsification. The former is in the form of oil film with different thicknesses, while the latter is in oil spill emulsion with different oil-water ratios. The oil spill in different states has different element compositions: the oil film is a pure oil molecule, the emulsified oil spill is an oil-water mixed structure, and the fluorescent group is formed. Under the action of the laser, it has its own characteristic fluorescence spectrum information, and different states show obvious fluorescence spectrum differences. The shape feature of the spectral curve is an external manifestation of fluorescent substances’ physical and chemical properties, so analyzing and comparing certain spectral parameters from the shape feature of the spectrum can achieve the purpose and effect of substance classification and species identification. In order to realize the rapid classification and identification of different states of oil spills on the sea, the LIF detection system was built to collect the fluorescence spectra of common oil products in different states. The comparison of the spectral curves shows that the spectrum in the emulsification stage will show a series of characteristics, such as the increase in the number of fluorescence peaks, the change of fluorescence intensity, the shift of fluorescence peak position and so on. According to the principle of apparent statistics, the mean value, standard deviation, kurtosis coefficient, spectral linewidth, curve slope and other characteristic parameters of the spectrum are extracted, and these characteristic values are used for cluster analysis. The results show that the cluster analysis results of oil spills based on laser-induced fluorescence spectrum are consistent with the actual oil spill status. Based on the premise of known oil species, the classification method can better identify different oil spill states on the sea. Therefore, this method can provide a new idea for identifying oil spills on the sea and lay a foundation for the improvement of LIF technology detection quality and application level.
		2022 Vol. 42 (07): 2018-2024 [Abstract] ( 120 ) RICH HTML PDF (4190 KB) ( 80 )

	2025	Quantitative Analysis Method of Key Nutrients in Lanzhou Lily Based on NIR and SOM-RBF
		LIAN Xiao-qin^{1, 2}, CHEN Qun^{1, 2}, TANG Shen-miao^{1, 2}, WU Jing-zhu^{1, 2}, WU Ye-lan^{1, 2}, GAO Chao^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2022)07-2025-08
		In order to realize the rapid and nondestructive detection of key nutrients protein and polysaccharide of Lanzhou lily, near infrared spectroscopy (NIRS) of 59 Lanzhou lily powder samples were collected in the range of 12 000~4 000 cm^-1. Firstly, ten pretreatment methods of SG, Normalize, SNV, MSC, Detrend, OSC, SG+1D, SG+Normalize, SG+SNV and SG+Detrend were used to process the original spectral data, and the optimal pretreatment method was SG+Detrend, Detrend was the best pretreatment method for polysaccharide. Then, CARS, SPA and PCA were used to screen the characteristic wavelength of the preprocessed spectral data. Finally, the SPA algorithm was used to determine the best extraction method for protein and polysaccharide’s characteristic wavelength. The results showed that the correlation coefficient R_p of the prediction set was 0.810 6, and the root mean square error of the prediction set RMSEP was 1.195 3 in the protein PLSR model established by SG+Detrend_SPA treatment. In the polysaccharide PLSR model established by the Detrend SPA treatment, the correlation coefficient R_p of the prediction set was 0.810 9, and the root means square error RMSEP of the prediction set was 2.094 6. Considering the limitation of precision of the classical PLSR nondestructive prediction model, SOM-RBF neural network nondestructive prediction model is proposed in this paper. Firstly, the SOM network is used to cluster the data samples, and then the number of clustering categories and clustering center obtained is used as the number of hidden layer nodes and the data center of hidden layer nodes of the RBF network to optimize the structural parameters of RBF. In the established protein SOM-RBF neural network model, the correlation coefficient R_p of the prediction set is 0.866 6, and the root means square error of the prediction set RMSEP is 1.038 5. In the SOM-RBF neural network model established for polysaccharides, the correlation coefficient R_p of the prediction set was 0.868 1, and the root means square error RMSEP of the prediction set was 1.799 4. Comparing-PLSR and SOM-RBF prediction results, the SOM-RBF neural network model was determined as the optimal modeling method. Finally, the optimal model was established based on SG+Detrend_SPA_SOM-RBF in protein detection. The correlation coefficient of the prediction set of the model was 5.6% higher than that of PLSR, and the root means square error of the prediction set was 0.156 8 lower than that of PLSR. In the detection of polysaccharides, the optimal model was established based on Detrend_SPA_SOM-RBF, and the correlation coefficient of the model was 5.72% higher than that of PLSR, and the root means square error of the model was 0.295 2 lower than that of PLSR. The results showed that NIR and SOM-RBF techniques could be used for the rapid and non-destructive detection of key nutrients, proteins and polysaccharides, and the results could provide a theoretical basis for the future rapid and non-destructive detection of nutrients in Lily of Lanzhou.
		2022 Vol. 42 (07): 2025-2032 [Abstract] ( 136 ) RICH HTML PDF (4232 KB) ( 59 )

	2033	Micro Confocal Raman Spectroscopy Combined With Chemometrical Method for Forensic Differentiation of Electrostatic Copy Paper
		CHEN Wei-na¹, GUO Zhong-zheng¹, LI Kai-kai¹, YANG Yu-zhu¹, YANG Xu^2*
		DOI: 10.3964/j.issn.1000-0593(2022)07-2033-06
		The identification of electrostatic copy paper is an important work in forensic science physical examination. Establish the analysis method of microscopic confocal Raman spectroscopy combined with Chemometrics to examine different brands and models of copying paper, to achieve the non-destructive inspection and accurate identification of copy paper. The online shopping platform was used to collect 20 kinds of electrostatic copy paper of different brands and models. The Raman Spectra data of different paper samples were collected by using the laser wavelength of 785 nm semiconductor laser. The main characteristic peaks in each paper sample and their corresponding components were analyzed. The spectral data were classified by Wohlde hierarchical clustering analysis, and the discrimination results were evaluated by principal component analysis (PCA). It was found that the main characteristic peaks of different paper samples were concentrated in the range of 900~1 700 cm^-1, respectively around 714，892，1 092，1 119，1 143，1 343，1 385，1 470，1 510 and 1 600 cm^-1, and the main components were cellulose, lignin and calcium carbonate. Although the spectral curves of each paper sample overlap each other, there are some differences in peak intensity and peak area. The spectral data of paper samples can be classified and identified by cluster analysis and principal component analysis in Chemometrics. According to the tree diagram of the system cluster analysis and the scatter diagram drawn in light of the schedule Table, 20 kinds of copy paper samples in different brands and models can be divided into four categories. Among the four categories, 10 samples are included in ClassⅠ and 3 samples are included in ClassⅡ, ClassⅢ contains six samples and ClassⅣ contains only one sample. Then PCA of spectral data of paper samples in the range of 900~1 700 cm^-1, the contribution of the first two principal components in 17 principal components reached 84%, which contained most of the spectral information. Based on the first two principal components, the principal component scores of the Raman Spectrum data of paper samples were drawn. It was found that the results of cluster analysis were well verified in the principal component scores. All the subclasses contained in Class Ⅰ-Class Ⅳ can be grouped and distinguished clearly. The results of classification and identification are accurate and reasonable. This method can not damage the paper samples when used, the operation process is simple, and the effect of identification is ideal. It can be applied to the examination and analysis of documents material evidence in forensic science, and it can provide clues and a basis for tracing the source of material evidence.
		2022 Vol. 42 (07): 2033-2038 [Abstract] ( 134 ) RICH HTML PDF (3148 KB) ( 69 )

	2039	Study on Vertical Distribution of Atmospheric HONO in Winter Based on Multi-Axis Differential Absorption Spectroscopy
		TIAN Xin^{1, 3}, REN Bo^{3, 5}, XIE Pin-hua^{1, 3, 4, 5}, MOU Fu-sheng^2*, XU Jin³, LI Ang³, LI Su-wen², ZHENG Jiang-yi³LI Xiao-mei³, REN Hong-mei³, HUANG Xiao-hui¹, PAN Yi-feng¹, TIAN Wei¹
		DOI: 10.3964/j.issn.1000-0593(2022)07-2039-08
		Nitrite (HONO), as one of the sources of OH free radical in the atmosphere, plays an important role in the oxidative capacity of the atmosphere. Moreover, previous studies have shown that HONO plays an important role in generating atmospheric haze in winter. The conversion of NO₂ is considered one of the important sources of HONO. Therefore, researching the vertical distribution characteristics of HONO in the atmosphere has an important role in studying the formation and control of atmospheric pollution. Because of the important role of HONO in the atmosphere, currently, the methods of chemiluminescence and spectroscopy, as well as indirect methods, are mainly used to measure HONO in the atmosphere. MAX-DOAS method is a passive remote sensing technology that can quickly and effectively obtain the three-dimensional distribution of pollutants in the atmosphere. In this paper, the MAX-DOAS instrument was used for stereo detection of HONO and NO₂ in the winter atmosphere of the Science Island of Hefei in December 2017. The vertical distribution characteristics of those are obtained through the PriAM algorithm. The research results show that during the observation period, the NO₂ vertical mixed concentration (VMR) and vertical column concentration (VCD) in the range of 10m near the ground were in the range of 0.51×10¹¹～20.5×10¹¹ molecules·cm^-3 and 6.0×10¹⁵～5.5×10¹⁶ molecules·cm^-2, respectively.The concentration was mainly concentrated within 1 km, and evenly mixed near the ground. However, the VMR and VCD of HONO were between 0.03×10¹⁰～5.1×10¹⁰ molecules·cm^-3 and 3.5×10¹⁴～7.0×10¹⁵ molecules·cm^-2, respectively. The upper level of concentration was within 100m, and its concentration decreased significantly with the increase in height. The HONO/NO₂ ratio was between 0.17%～16.0% (VMR) and 1.0%～25.0% (VCD), indicating that HONO was mainly derived from NO₂ conversion during the study period. Under a typical polluted episode (2017.12.26—2017.12.31), HONO/NO₂ was greater than 5%, and the concentration of HONO increased (greater than 0.26×10¹¹ molecules·cm^-3), indicating that the conversion of NO₂ to HONO became strong. By combining the wind field changes to study the source of NO₂ during the pollution period, it was found that the transmission in the urban area of Hefei, northern and northwestern Anhui has a significant effect on NO₂ and HONO.
		2022 Vol. 42 (07): 2039-2046 [Abstract] ( 120 ) RICH HTML PDF (6220 KB) ( 65 )

	2047	IR Characterizations of Ribavirin, Chloroquine Diphosphate and Abidol Hydrochloride
		CHEN Jing-yi¹, ZHU Nan², ZAN Jia-nan³, XIAO Zi-kang¹, ZHENG Jing¹, LIU Chang¹, SHEN Rui¹, WANG Fang^{1, 3*}, LIU Yun-fei³, JIANG Ling³
		DOI: 10.3964/j.issn.1000-0593(2022)07-2047-09
		Since the outbreak of novel coronavirus pneumonia (COVID-19), many research institutes and enterprises at home and abroad have been accelerating the research of COVID-19 (SARS-CoV-2) antibody drugs. However, the research on effective drugs was limited by the drug polymorphisms. The environment of drug production, storage and use also affected the stability of the drug. As a fast, non-destructive testing method, infrared spectroscopy can reflect the differences in drug structure, crystal form and even manufacturing technique to the vibration spectrum, which greatly improves the efficiency of R&D (research and development). In this paper, three clinical trials were considered effective drugs for the treatment of COVID-19: Chloroquine diphosphate, Ribavirin and Abidol hydrochloride. Their far-infrared spectrum (1~10 THz) and mid-infrared spectrum (400～4 000 cm^-1) were measured by Fourier transform infrared spectrometer (FTIR). In the far-infrared spectrum, the characteristic peaks of Ribavirin were around 2.01, 2.68, 3.37, 4.05, 4.83, 5.45, 5.92, 6.42 and 7.14 THz; the characteristic peaks of Chloroquine phosphate were near 1.26, 1.87, 2.37, 3.06, 3.78, 5.09 and 6.06 THz; the characteristic peaks of Abidol hydrochloride were located near 2.24, 3.14, 3.72, 4.25 and 5.38 THz. Based on density functional theory, the B3LYP hybrid functional and 6-311++G (d, p) basis sets were selected to analyze the vibrational modes corresponding to all characteristic peaks in the spectrum using Crystal14 and Gaussian 16 software, and the accurate identification of the vibration spectrum was realized. The vibrational modes originated from the molecules’ collective vibration in the far infrared region. In the mid-infrared band, below 2 800 cm^-1, the vibrational modes mainly came from the in-plane and out-of-plane bending and rocking of the group; Above 2 800 cm^-1, the vibrational modes transited to the in-plane stretching of C-H, O-H and N-H bonds. Taking the crystal structure with periodic boundary conditions as the initial configuration of the theoretical calculation would make the calculated spectrum more consistent with the experimental one, especially in the far-infrared band and the low-frequency band of mid-infrared (400～1 000 cm^-1). This study was of great significance to deeply understand the pharmaceutical characteristics, drug interactions, control of drug production process, and guide the storage and use of antiviral drugs such as Chloroquine phosphate, Ribavirin and Abidol hydrochloride.
		2022 Vol. 42 (07): 2047-2055 [Abstract] ( 228 ) RICH HTML PDF (5274 KB) ( 61 )

	2056	Characteristics of Extreme Ultraviolet and Debris Emission From Laser Produced Bi Plasma
		XIE Zhuo^{1, 3}, WANG Hai-jian¹, DOU Yin-ping^1, SONG Xiao-wei^1, LIN Jing-quan^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2022)07-2056-07
		Laser produce plasma extreme ultraviolet (EUV) source, which has the advantages of small size, high stability and adjustable output wavelength, plays a significant role in applying EUV lithography. Laser produces plasma Bi EUV source has a wide spectrum in the wavelength range of 9~17 nm, which can be used to apply extreme ultraviolet metrology in the development of extreme ultraviolet lithography. Therefore, EUV emission and debris characteristics from laser-produced Bi plasma were carried out. When the 1 064 nm pulse laser irradiated the Bi target, a natural dip displays at 12.3 nm in the EUV spectrum, corresponding to the L-edge absorption in silicon. Meanwhile, two strong peak emissions are located at 11.8 and 12.5 nm, respectively. Firstly, we studied the emission characteristics and intensity of the spectrum near the 11.8 and 12.5 nm dependence on laser power density. When the laser power density is adjusted by changing the focus spot size by fixing the laser energy, the emission intensity of two peaks increases first and then decreases with an increase in the laser power density. The maximum emission intensity of two peaks was formed when the laser power density of 2.0×10¹⁰ W·cm^-2. This is attributed to the final output EUV emission is determined by the balance of the laser energy loss used to support plasma expansion and reabsorption of the EUV emission by the plasma. When the laser power density is adjusted by changing laser energy by fixing the focus spot size, the emission increases with an increase of laser power density due to the ablation material and high stage ions increases. Secondly, we studied the effect of dual pulse on the emission intensity of the 11.8 and 12.5 nm peaks. The experiment results show that the emission intensity of two peaks increases gradually when the laser energy increases from 20~140 mJ. Moreover, the intensity decreases when the laser energy larger than 140 mJ due to the EUV emission being absorbed by the thick plasma at a larger plasma density. In addition, it is found that the dip generated in the spectrum at a 13~14 nm wavelength with a single pulse laser disappeared when using the dual pulse method. Finally, we measured the angular distributions of ions emission from a 1 064 nm laser-produced plasma. The results indicated that the kinetic energy of Bi ions decreases when the detection direction moves from the normal direction of the target surface to the direction along the target surface due to the plasma preferential expansion perpendicular to the target surface. Moreover, the kinetic energy of Bi ions decreases linearly with the decrease of laser pulse energy. This research is expected to provide technical support and lay a solid foundation for the metrology field needed in the development of EUV lithography.
		2022 Vol. 42 (07): 2056-2062 [Abstract] ( 115 ) RICH HTML PDF (3588 KB) ( 50 )

	2063	Eu³⁺/Dy³⁺ Co-Doped Sr₃Y₂(BO₃)₄ Phosphor Luminous Properties Research
		HU Xin-yan¹, CAO Long-fei¹, LI Jin-hua^{1, 2, 3}, LI Shuang^1*
		DOI: 10.3964/j.issn.1000-0593(2022)07-2063-06
		Rare earth-doped luminescent materials have always been a hot spot in the field of scientific research and are widely used in the fields of white light LEDs, temperature sensing, display imaging, new energy and lasers. The matrix structure has a significant influence on the photoluminescence properties of rare-earth ions. Among many luminescent matrix materials, borate has the advantages of a wide range of light transmission, high optical damage threshold, better thermal stability and chemical stability. Alkaline-earth and rare-earth metal borates Sr₃Y₂(BO₃)₄ have excellent optical properties, and the study of its luminescence properties is of great significance. The rare-earth ion Eu³⁺ ions have a 4f⁶ electron layer, which is a typical down-conversion luminescence center ion, and is often selected as an activator of red luminescent materials. Dy³⁺ ions have a 4f⁹ electron layer, a typical down-conversion luminescence center ion. Under the excitation of ultraviolet light, there is a strong fluorescence emission in the blue and orange light areas. This paper synthesised, Sr₃Y₂(BO₃)₄∶Eu³⁺/Dy³⁺ phosphors by high-temperature solid-phase method. XRD and SEM characterized the structure and morphology of the samples. XRD results showed that when sintered at 1 000 ℃ for 5 hours, 20% excess of H₃BO₃ is the best preparation conditions, and doping with a small amount of Eu³⁺ ions and Dy³⁺ ions did not change the lattice structure of Sr₃Y₂(BO₃)₄. The SEM image shows that the average grain size of the Sr₃Y₂(BO₃)₄ matrix is 2~4 μm, compared with the SEM image of the 10% Eu³⁺ single-doped sample and 5% Eu³⁺/5% Dy³⁺ double-doped sample, the morphology and size of the matrix Sr₃Y₂(BO₃)₄ did not change significantly. The luminescence results of Sr₃Y₂(BO₃)₄∶Eu³⁺ samples show that the main luminescence of Eu³⁺ mono-doped Sr₃Y₂(BO₃)₄ phosphors at concentrations of 5%, 10% and 15% under excitation at 395nm and 466 nm is located at 593 and 613 nm. For red light emission, the peak intensity increases first and then decreases with the increase of Eu³⁺ concentration. When the doping concentration is 10%, the luminescence intensity is the highest, indicating a concentration quenching phenomenon. The CIE chromaticity coordinates results show that the excitation wavelength changes from 395 to 466 nm, and the emission color of Sr₃Y₂(BO₃)₄∶Eu³⁺ phosphor changes from orange-red to red. After the introduction of Dy³⁺, the emission spectrum of Sr₃Y₂(BO₃)₄∶Eu³⁺/Dy³⁺ samples showed the 486 nm blue emission (⁴F_9/2→⁶H_15/2) and 576 nm orange emission (⁴F_9/2→⁶H_13/2) of Dy³⁺, And with the increase of Dy³⁺ ions concentration, it has an inhibitory effect on the ⁵D₀→⁷F_{1, 2, 3, 4} transition of Eu³⁺. The CIE coordinates results show that by adjusting the ratio of doped ions Eu³⁺ and Dy³⁺, the color of Sr₃Y₂(BO₃)₄∶Eu³⁺/Dy³⁺ phosphor can be changed from the red area to the orange area, indicating that it has a good application prospect in the display.
		2022 Vol. 42 (07): 2063-2068 [Abstract] ( 105 ) RICH HTML PDF (3795 KB) ( 55 )

	2069	Spectral Analysis and Study on the Channel Temperature of Lightning Continuing Current Process
		WANG Xue-juan^{1, 2}, XU Wei-qun^{1, 2}, HUA Le-yan¹, WANG Hai-tong¹, LÜ Wei-tao², YANG Jing³, YUAN Ping⁴, ZHANG Qi-lin¹, ZHANG Yuan-kan¹
		DOI: 10.3964/j.issn.1000-0593(2022)07-2069-07
		Continuing current is an important sub-physical process of lightning discharge. It refers to the process in which the local charge center in the thunder cloud discharges to the ground through the original channel after the return stroke. It is also usually overlapped by the M-component, which is the phenomenon that the brightness of the glowing channel increases suddenly. Since the continuing current was discovered in the 20th century. Many kinds of research were made by domestic and foreign researchers. The present studies mainly reveal the macroscopic characteristics of the discharge and luminescence using electromagnetic and optical observations. There is a lack of studies on the microcosmic luminescence information and the physical characteristics used by spectral observation. There are few studies about the temperature in the discharge channel of the continuing current. However, the temperature is not only a basic parameter to analyze the physical properties of the continuing current discharge channel but also a concerned parameter to prevent lightning disasters caused by the continuing current. Based on the spectra of a first return stroke and the following continuing current process overlapped with three M-components for cloud-to-ground lightning recorded by a slit-less high-speed spectroscope, the spectral evolution properties during the entire discharge process have been analyzed. The temperatures in the channel core and the corona sheath have been calculated, and the variations of both along the channel height have been studied. The results show that in the stage of the return stroke, the channel optical radiations are mainly the NⅡ lines with higher excitation energy. In the continuing current process, the channel optical radiations are mainly the NⅠ and OⅠ lines with lower excitation energy. The intensity of the ionic lines is strongest at the initial stage of the return stroke, while the intensities of the Hα and the neutral atomic lines are strongest at M1, and the continuum spectrum is strongest at M2. Four lines of OⅠ 777.4, NⅠ 746.8, 821.6 and 868.3 nm in the near-infrared band were observed throughout the discharge process. During the continuing current, the temperatures in the channel core are 42 060～43 940 K, which are 6 020~7 900 K higher than the temperature in the channel core of the corresponding return stroke. The temperatures in the outside corona sheath are 16 170～20 500 K. The temperatures of the channel core, and the corona sheath both remain unchanged with time. The temperature of the channel core decreases with the increase of the channel height, while the temperature of the peripheral corona sheath increases with the increase of the channel height.
		2022 Vol. 42 (07): 2069-2075 [Abstract] ( 112 ) RICH HTML PDF (5054 KB) ( 35 )

	2076	Surface-Enhanced Raman Spectroscopic Investigation on the Effect of Solution pH on Dehydroxylation of Hydroxythiophenol Isomers
		GE Deng-yun, XU Min-min, YUAN Ya-xian^, YAO Jian-lin^
		DOI: 10.3964/j.issn.1000-0593(2022)07-2076-06
		The optical enhancement effect and catalytic activities produced by surface plasmon resonance (SPR) of metallic nanostructures have become one of the hot fields in surface scientific research. The SPR and electrochemical control combine to induce and catalyze the unconventional reactions, and electrolyte solutions with different pH values affect the SPR photocatalytic reaction by changing the adsorption form of surface adsorbed molecules. In this study, the adsorption and reaction behaviors of the isomers of hydroxythiophenol were served as probes modified on the Ag electrode and were investigated by the combination of electrochemistry and surface-enhanced Raman spectroscopy (SERS). The results revealed that the SPR-catalyzed dehydroxylation reaction of hydroxythiophenol with different hydroxyl substituent positions exhibited different sensitivity to the pH value of the solution. The C—O bond peak intensity of o-hydroxythiophenol (OHTP) was related to the pH value of the solution. The O end was easier to interact with metal and adsorb on the surface, and it improved with increased pH. Under alkaline conditions, the dehydroxylation reaction of p-hydroxythiophenol (PHTP) was completely inhibited, and it could occur in both meta-hydroxythiophenol (MHTP) and OHTP. MHTP held the highest SPR catalytic dehydroxylation reaction efficiency in neutral (pH 7) solution, which was about 1.36 times that of acidic (pH 2) and 2.70 times that of alkaline (pH 12). OHTP exhibits the highest reaction efficiency in alkaline (pH 12) solution, which was about 13.71 times that of acidic (pH 2) and 4.95 times that of neutral (pH 7). SPR-catalyzed dehydroxylation was mainly contributed by two approaches non-deprotonation conditions and Ag—O formation. The dehydroxylation reaction of MHTP and OHTP under acidic conditions was mainly due to the undeprotonated hydroxyl reaction, and the formation of Ag—O mainly caused the alkaline conditions after deprotonation. Under neutral conditions, both contributions occurred simultaneously. For MHTP, due to the steric hindrance, only part of the molecules was deprotonated to form Ag—O, which promoted the catalytic dehydroxylation of SPR. Therefore, the simultaneous action of the two effects in the pH 7 solution led to the highest catalytic efficiency. For OHTP molecules, the O terminal in the deprotonated state was more likely to interact with the electrode surface, and the degree of deprotonation of the hydroxyl group as the pH increases was more thorough, more conducive to the dehydroxylation reaction. The dehydroxylation reaction in the pH 12 solution mainly occurred in Ag—O, where the efficiency was the highest. The study of the isomer structure and the pH of the medium on the SPR-catalyzed dehydroxylation reaction was of great significance for broadening the types of SPR catalytic reactions and analyzing the mechanism at the molecular level.
		2022 Vol. 42 (07): 2076-2081 [Abstract] ( 124 ) RICH HTML PDF (3050 KB) ( 154 )

	2082	The Technological Characteristics of Housi’ao Sagger and Its Influence on Influence on the Color of Celadon Glaze
		WU Jun-ming¹, SANG Yue-xia^1*, ZHENG Nai-zhang¹, ZHENG Jian-ming², WU Lin¹, SHAN Ri-qin¹
		DOI: 10.3964/j.issn.1000-0593(2022)07-2082-10
		Yue kiln celadon is the earliest celadon manufactured with a precise fire system in China, and the use of porcelain saggers to firing Mi’se celadon is the unique firing technique of the Yue kiln. In order to reveal the processing feature of porcelain sagger and its influence on celadon of Tang and Five Dynasties, saggers, which were unearthed at the Housi’ao kiln site in the Shanglin Lake of the Yue Kiln, were characterized via a variety of testing methods. In this paper, energy dispersive X-ray fluorescence spectrometer (ED-XRF), super depth of field microscope, scanning electron microscope (SEM) and other mondern test methods, were applied on the porcelain sagger, common sagger, common celadon and Mi’se celadon which unearthed from Housi’ao kiln site of Shanglin Lake, to realize the understand of element composition, microstructure, water absorption, etc. Meanwhile, a spectrophotometer has also conducted the tests of surface chroma on the common celadon and Mi’se celadon of Tang and Five Dynasties. The results of the analysis showed that the base of the common sagger was similar in composition to that of the porcelain sagger in the Tang and Five Dynasties, using local alluvial clay-like raw materials with a SiO₂ content of approximately 75% and an Al₂O₃ content of approximately 16%, similar to that of the celadon body. In contrast, the TiO₂ and Fe₂O₃ contents of the porcelain sagger in Tang and Five Dynasties were higher than those of the celadon body and fluctuated slightly, indicating a more rigorous process of washing the celadon body. The presence of a large number of inclusions of coarse particles with an average size of around 530 μm and a regular particle gradation in the common sagger was a type of high-silica material that was deliberately selected and added to increase the service life of the common sagger, increasing the permeability, mechanical strength and thermal stability of the sagger and thus extending the service life of the sagger; the porosity of the porcelain sagger in Tang and Five Dynasties was 1.61% and the water absorption rate was 0.73%, lower than the common sagger 8.18%, 4.28%, while the bulk density of 2.22 g·cm^-3 higher than the common sagger 1.99 g·cm^-3, and thermal conductivity than the common sagger, conducive to reducing the temperature difference between the inside and outside of the sagger, to alleviate the temperature lag phenomenon. In addition, the use of a porcelain sagger with a lower porosity and the sealing of the mouth rim at the Housi’ao site in Shanglin Lake effectively reduced the degree of secondary oxidation of the fired celadon glaze during the cooling process, improved the stability of the atmosphere within the sagger and the Fe²⁺ content of the celadon glaze layer, and improved its colour stability and appearance. At the same time, the slightly thicker glaze layer on the Mi’se celadon reduced the influence of the body on the appearance of the product and increased the refractive index and brightness of the glaze, placing it in a more bluish-green area in the CIE chromaticity space than common celadon.
		2022 Vol. 42 (07): 2082-2091 [Abstract] ( 144 ) RICH HTML PDF (7153 KB) ( 60 )

	2092	Research on Spectral Image Reconstruction Based on Nonlinear Spectral Dictionary Learning From Single RGB Image
		ZUO Chu¹, XIE De-hong^2*, WAN Xiao-xia³
		DOI: 10.3964/j.issn.1000-0593(2022)07-2092-09
		A nonlinear reconstruction method based on nonlinear spectral dictionary learning was proposed to solve the ill-posed problem of spectral image reconstruction from a single RGB image. In order to adapt to the linear and nonlinear data, the method firstly improves the nonlinear principal component analysis algorithm based on a modified self-association neural network model. It uses to learn the low-dimensional spectral dictionary from the training spectrum set, which is used in the inverse equation of spectral reconstruction to alleviate the ill condition. In addition, based on the spectral dictionary, the damped Gaussian Newton method combined with the truncated singular value decomposition regularization method is used further to alleviate the ill-posed problem of the nonlinear inversion, and the spectral image can be reconstructed from a single RGB image. In the experiment, two different spectral training sets, Munsell and Munsell+Pantone, were used to learn the spectral dictionary. Meanwhile, CAVE and UEA spectral image libraries were used for the spectral reconstruction tests. Compared with the existing methods, it is found that the average root means square error of CAVE and UEA spectral images reconstructed by this method under different spectral training sets were the lowest, which were 0.212 4, 0.255 4, 0.229 4 and 0.294 9 respectively. The standard deviations of root mean square error was close to the effect of the best method, which was 0.068 5, 0.084 7, 0.066 8 and 0.087 0 respectively. The results show that the method for reconstructing the spectral image from a single RGB image has advantages in accuracy and stability.
		2022 Vol. 42 (07): 2092-2100 [Abstract] ( 175 ) RICH HTML PDF (5697 KB) ( 49 )

	2101	Uncertainty Evaluation and Method Improvement of Determination of Copper, Lead, and Zinc in Rocks by Atomic Absorption Spectrometry
		HOU Ya-ru, LU Ji-long^*, FAN Yu-chao, Abudusalamu·KADIER, TANG Xiao-dan, WEI Qiao-qiao, GUO Jin-ke, ZHAO Wei
		DOI: 10.3964/j.issn.1000-0593(2022)07-2101-06
		The determination of trace elements in Geological Samples by Atomic Absorption Spectrometry is simple, rapid, accurate and economical, which has been widely used in geological laboratories. However, the complex pre-processing process and testing process will inevitably introduce uncertainty. According to the general requirements for the competence of inspection and calibration laboratories, the uncertainty of measurement results should be properly evaluated. In this study, the concentration of Cu, Pb, and Zn in the national standard rock sample and a core sample from the Qujia gold mine in Jiaodong were determined by Atomic Absorption Spectrometry after electric heating plate digestion. Three times the standard deviation of the blank samples test results was calculated as the detection limits. The results of the standard samples and core samples are by the requirements of DZ/T 0130.3—2006 on the accuracy and precision of the test. The bottom-up method was used to evaluate the uncertainty of results in the laboratory. The sources of measurement uncertainty were determined, including sample weighing, constant sample volume, sample digestion, preparation of standard series, least-square fitting and repeated measurement. The value and expanded uncertainty of six uncertainty components were accurately calculated. Among them, the last four components are the main sources of uncertainty. The results show that the uncertainty of the measurement results ofcopper, lead, and zinc in the standard samplesaresmaller than the uncertainty given in the standard certificate, the concentration of Cu, Pb, and Zn in the core sample is (4.965±0.383), (36.415±2.449), (30.818 0±0.736) μg·g^-1, respectively. The uncertainty of six sources is compared, and some improvements are put forward when the content of Cu, Pb, and Zn in rock samples is measured by this method: adjusting the sampling mass or constant volume to improve the concentration and absorbance of elements in the solution to be measured, adjusting the concentration of standard series to make it close to the concentration of elements in the solution to be measured, increase the measurement times of standard point and the solution to be measured, the pipette with small relative standard uncertainty should be used as much as possible if necessary in order to reduce the measurement uncertainty. Evaluating measurement uncertainty as an effective tool to guide the improvement of analytical methods and test process is of great significance in the accurate determination of trace elements in rock samples.
		2022 Vol. 42 (07): 2101-2106 [Abstract] ( 158 ) RICH HTML PDF (1335 KB) ( 56 )

	2107	Study on the Inhibition Mechanism of Angiotensin Conversion Enzyme Inhibitor Peptide Leu-Lys-Pro (LKP)
		XU Xiao-qing¹, ZHOU Qian¹, SUN Jian-hua¹, SUN Li-xia¹, FENG Xue-zhen^{1, 2}, XU Yong-fang¹, TONG Zhang-fa¹, LIAO Dan-kui^1*
		DOI: 10.3964/j.issn.1000-0593(2022)07-2107-06
		Angiotensin-Ⅰ Converting Enzyme (ACE) is a zinc-containing carboxydipeptidase that regulates blood pressure through renin-angiotensin and kallikrein-kinin systems. The ACE inhibitory peptide (ACEIP) derived from food protein could inhibit the activity of ACE, which is beneficial to antihypertension. In this paper, the inhibition mechanism of the inhibitory peptide LKP from bonito fish on ACE was studied by using fluorescence spectra, ultraviolet absorption spectra, circular dichroism (CD), and isothermal titration calorimetry (ITC) and molecular docking. The fluorescence spectra showed that LKP could effectively quench the endogenous fluorescence of ACE, and the quenching mechanism was static quenching by the formation of a relatively stable complex LKP-ACE. The microenvironment around the tryptophan and tyrosine residues in ACE was localized, decreased the hydrophobicity, and enhanced the polarity. The results of UV and CD showed that the combination of LKP and ACE would lead to the conformation change of ACE. After the addition of LKP, the secondary structure of ACE became looser, and the structural changes of a tightness, loosening and slightly tighter have taken place during the interaction process. The thermodynamic parameters such as enthalpy change (ΔH), entropy change (ΔS), stoichiometric ratio (n) and binding constant (K_a) of the interaction between LKP and ACE were obtained by the ITC method. The results showed that the binding reaction of LKP and ACE was a spontaneous endothermic process driven by entropy, and the binding force was mainly hydrophobic. The stoichiometric ratio (n) value was determined to be about 1, which was enhanced with increasing temperature. At 288, 293 and 299 K, the binding constants Ka of LKP and ACE were 2.2×10³, 0.9×10³ and 5.3×10³, respectively, indicating the affinity of LKP and ACE was relatively low. The results of molecular docking showed that the amino acid residues Gln281 and Lys511 in the S₁ pocket of the ACE active center could form two hydrogen bonds with LKP, and hydrophobic interaction could have occurred between His353 and His513 and LKP, LKP bond to ACE mainly through hydrophobicity, and hydrogen bonds stabilized the spatial structure of the protein. This study provides certain help for exploring the interaction between ACE inhibitory peptide and ACE and offers some theoretical basis for the development of new hypertension drugs.
		2022 Vol. 42 (07): 2107-2112 [Abstract] ( 119 ) RICH HTML PDF (3383 KB) ( 36 )

	2113	The “Cluster-Regression” COD Prediction Model of Distributed Rural Sewage Based on Three-Dimensional Fluorescence Spectrum and Ultraviolet-Visible Absorption Spectrum
		ZHOU Ming-rui^{1, 2}, QU Jiang-bei², LI Peng^{1, 2*}, HE Yi-liang^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2022)07-2113-07
		Based on the relationship between the three-dimensional fluorescence spectrum and the characteristic fluorescence peaks of organic matter, this study proposed to use the three-dimensional fluorescence spectrum for clustering and then for different kinds of water samples, using UV-Vis full-band absorption spectrum data to establish the COD prediction model technical route. The parallel factor analysis (PARAFAC) algorithm and fluorescence volume integration (FRI) algorithm were compared and analyzed, and then the fuzzy c-means(FCM) algorithm was used for clustering, and the COD prediction model of different water samples was established. The water samples in this study were collected from the rural areas around Changshu City, Jiangsu Province, and 100 experimental water samples were collected from the effluent of different distributed rural domestic sewage treatment plants. The measured three-dimensional fluorescence spectrum of water samples was pretreated by de-scattering, and then the fluorescence characteristic data were extracted by the PARAFAC algorithm and FRI algorithm, respectively. Then, the FCM clustering algorithm was used for similarity clustering. Finally, the partial least squares (PLS) algorithm was used to establish the regression and prediction model between the UV-Vis full-band absorption spectrum and COD of water samples, and the prediction accuracy was evaluated by the coefficient of determination and the root mean square error(RMSE). The results showed that the prediction models’ mean determination coefficients(R²) were 0.632, 0.819 and 0.906, respectively, after the fluorescence feature information was extracted using FRI and PARAFAC algorithms. RMSE were 27.857, 23.621 and 13.071, respectively. The regression and prediction accuracy was significantly improved after clustering, and the modeling established after the extraction of fluorescence feature information using the PARAFAC algorithm had the highest prediction accuracy, which was 0.274 higher than theR² of the unclassified prediction model. The proposed COD prediction model based on a three-dimensional fluorescence spectrum combined with UV-Vis full-band absorption spectrum and using the combined algorithm of “PARAFAC-FCM-PLS” can effectively improve the prediction accuracy of COD and provide a new idea for high precision online monitoring of water quality.
		2022 Vol. 42 (07): 2113-2119 [Abstract] ( 110 ) RICH HTML PDF (4485 KB) ( 56 )

	2120	Study on Spectral Characteristics of Dissolved Organic Matter in Composting With Different Conditioners and Leached Dewatered Sludge
		LU Ze^{1, 2}, XI Bei-dou³, TAI De-zhi^{1, 2}, LU Liang-quan^{1, 2}, SUN Xiao-jie^{1, 2}, ZHANG Jun^{1, 2}, ZHANG Hua^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2022)07-2120-10
		Bioleach deep dehydrated sludge was used as the main material, four kinds of agricultural and forestry organic wastes were used as conditioners for mixed composting. Four treatment groups (T1: sludge+bagasse, T2: sludge+straw, T3: sludge+rice bran, T4: sludge+sawdust) were set for mixed composting. UV-vis spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), and three-dimensional fluorescence spectrum (3D-EEM) were used to study the structural characteristics and component content evolution of dissolved organic matter (DOM) in co-composting. The UV-vis results showed that the aromaticity and unsaturation of DOM increased in all treatment groups, and the T3 treatment group showed the largest increase. SUVA₂₅₄ and SUVA₂₈₀ of four composting treatment groups showed an increasing trend. The change range of the T3 treatment group was higher than the other three treatment groups, indicating that the degree of aromatization deepened, the molecular weight of DOM gradually increased. E₂₅₃/E₂₀₃ and E₂₅₃/E₂₂₀ increased significantly at the end of composting, indicating that the aliphatic chain on the benzene ring in DOM was oxidized, decomposed, and transformed into functional groups such as carboxyl group and carbonyl group. A_226～400 increased with composting, whileE₂₅₀/E₃₆₅ decreased, indicating that the conjugation degree increased. FTIR results show that the content of polysaccharides and aliphatic substances decreased during composting, and unsaturated organic substances such as aromatic compounds increased. The transformation degree of the T4 treatment group was better than the other three treatment groups. Emission fluorescence spectra showed that the fluorescence peak position shifted from 334nm to around 422nm with composting, which indicated that the substances with low conjugation degree were continuously degraded, and aromatic groups were continuously condensed to form humic-like matters. In the synchronous fluorescence spectrum, with composting time, the fluorescence peak of protein-like substances changed from strong to weak, the fluorescence peak of humic-like matters changed from weak to strong, A_250～308 decreased, A_308～360 and A_363～500 increased, which also indicated that protein-like substances were degrading, while humic acid-like substances and fulvic acid-like substances increased. Combined with the parallel factor (PARAFAC) model to analyze the three-dimensional fluorescence spectrum, DOM was divided into three components. According to the analysis and judgment of the excitation and emission wavelength positions, the three components are fulvic acid-like substances, humic acid-like substances and tryptophan-like substances. The percentage of C1 (fulvic acid-like substances) and C2 (humic acid-like substances) components showed an increasing trend, while the percentage of C3 (tryptophan-like substances) components showed a decreasing trend, indicating that protein-like substances decreased. At the same time, humic-like matters increased, and the humification degree of T3 and T4 treatment groups were good. Comprehensive analysis showed that rice bran and sawdust as conditioners had better compost maturity.
		2022 Vol. 42 (07): 2120-2129 [Abstract] ( 185 ) RICH HTML PDF (7413 KB) ( 46 )

	2130	Research on Spectral Characteristics and Coloration of Natural Cobalt Spinel
		TAO Long-feng^{1, 2}, SHI Miao², XU Li-juan², HAN Xiu-li^1*, LIU Zhuo-jun²
		DOI: 10.3964/j.issn.1000-0593(2022)07-2130-05
		Spinel[(Mg,Fe,Zn,Mn)(Al,Cr,Fe)₂O₄] is a magnesium aluminum oxide mineral used for gemstones and glass-ceramics. In recent years, a natural spinel has been found as a gemstone with the color of cornflower blue.It has been loved by collectors and designers and has an increasing price. The cobalt spinels are often cornflower blue and transparent. It shows weak to medium green fluorescence under long-wave ultraviolet and no fluorescence at short-wave. The cobalt spinel with alexandrite effect displayed cornflower blue color in sunlight and purplish-red color in incandescent light. Three natural cobalt spinel samples with spectral characteristics and coloration were investigated with EPMA, FTIR, Raman spectrometer, UV-VIS-NIR spectrometer, and cathodoluminescence spectrometer, and these testing results were compared with those of ordinary spinel without alexandrite effect. The results show that the alexandrite effect and cobalt spinel belong to magnesium spinel. The cobalt spinel was composed of MgO and Al2O3, with an average content of 71.37% and 25.77%, respectively; The contents of transition metals such as Zn, Fe, Co and V were relatively high, and with an average content of 1 333.85, 831.53, 99.52 and 58.26 μg·g^-1, respectively. It was found that their infrared spectra and Raman spectra are the same as those of ordinary spinel: the infrared spectrum at 517, 589, and 704 cm^-1 are red-shifted, and the red shift range is 5~33 cm^-1, and the Raman peaks are concentrated at 300~800 cm^-1. Compared the UV-Vis-NIR-spectra with the results of chemical analysis and cathodoluminescence test, it is suggested that the color of natural cobalt spinel is due to the combined action of electronic transitions in Co²⁺, Fe³⁺ and V³⁺ contained in the lattice. The spin-forbidden transition ⁴T_1g(⁴F)→⁴T_1g(⁴P) of Co²⁺ makes the orange-yellow region (550~630 nm) produce absorption bands, while the transition ³T_1g→³T_1g(³P) of V³⁺ and the transition ⁴A₂→E₂ of Cr³⁺ makes the blue-purple region (400~490 nm) absorption lines are generated to uniformly transmit the red and blue light so that it produces alexandrite effect. Discolored cobalt spinels are often cornflower blue in sunlight and purplish-red in incandescent lamps. This research confirmed the spectral characteristics and coloration mechanism of natural cobalt spinels and the alexandrite effect of cobalt spinels. This study provided a basis for their scientific identification of natural cobalt blue spinels and is beneficial for readers to distinguish natural cobalt blue spinels from ordinary blue spinels and synthetic cobalt blue spinels. It has important theoretical research and commercial application value.
		2022 Vol. 42 (07): 2130-2134 [Abstract] ( 147 ) RICH HTML PDF (1994 KB) ( 110 )

	2135	Experimental Research on Coal-Rock Identification Method Based on Visible-Near Infrared Spectroscopy
		XU Liang-ji^{1, 2}, MENG Xue-ying², WEI Ren², ZHANG Kun²
		DOI: 10.3964/j.issn.1000-0593(2022)07-2135-08
		Taking the coal and rock samples retrieved from the Huainan Xieqiao Mine and the Paner II Mine as the research object, the sample reflectance spectrum curve was collected by a ground spectrometer, and the sample’s oxide content, moisture, ash and volatile content were simultaneously detected to reflect the sample’s reflection. The rate spectral curve and the sample component content are used as independent variables, and the sample type is used as the dependent variable to establish a coal and rock identification model to classify coal and rock. This paper mainly adopts three models, which are principal component analysis combined with support vector machine (PCA-SVM), principal component analysis combined with BP neural network (PCA-BP) model and kernel principal component analysis combined with support vector machine (KPCA-SVM) model. The results show that among the three models based on visible light near-infrared spectroscopy, nuclear principal component analysis combined with support vector machine model has the highest recognition accuracy, the average accuracy of modeling is 95.5%, and the average accuracy of verification is about 90.56%; three based on sample components. In the model, the kernel principal component analysis combined with the support vector machine model has the highest recognition accuracy, the average accuracy of modeling is 98.5%, and the average accuracy of verification is about 95%.
		2022 Vol. 42 (07): 2135-2142 [Abstract] ( 122 ) RICH HTML PDF (2573 KB) ( 64 )

	2143	A Simple Measuring Method for Infrared Spectroscopy of Liquid Matters
		YANG Shan, CAI Xiu-qin, LIU Yu-han, WANG Wei
		DOI: 10.3964/j.issn.1000-0593(2022)07-2143-05
		Infrared (IR) spectroscopy is an important tool for the qualitative analysis of liquid matters. IR spectroscopy of liquid samples is commonly prepared by liquid film method and tested by transmission (TR) method, while the salt window required is expensive, prone to force or moisture cracking. The incomplete surface cleaning or scratches can easily cause test interference; moreover, installing the demountable liquid cells is troublesome, and mixing the trapped air into the sample will also cause test interference. In this paper, a simple method for measuring IR spectra of liquid substances is studied. The differences between the improved TR method, samples prepared by smearing method of directly coating liquid onto a single-use compressed potassium bromide (KBr) disc, and the attenuated total reflection (ATR) method in IR spectra of liquid substances are compared. 6 kinds of liquid reagents with different volatility, hygroscopicity and corrosivity were selected as the research objects, and their IR spectra were tested by both the improved TR method and ATR method. The IR spectra measured by the two methods were compared with those in the SDBS spectral database. The influence of scanning times and resolution on ATR spectra was also studied. The results show that the two methods are accurate in the IR qualitative analysis of liquid samples. The improved TR method simplifies the sample preparation process, avoids the problem of cleaning salt window, and reduces the cost, but water interference is still difficult to avoid. In contrast, the ATR method requires no sample preparation, is more simple, convenient and faster, and the interference of water is negligible. Although the overall intensity and fineness of the spectra tested by the ATR method are not as good as tested the TR method, the high-quality spectra can be obtained by improving the resolution and increasing the scanning times. The amount of liquid should be increased when using the improved TR method and ATR method for volatile liquids. The improved TR method is recommended for strongly acidic and/or corrosive liquids. For hygroscopic liquids, the spectra measured by the ATR method are easier to analyze. In contrast, except for strongly acidic and/or corrosive liquids, the other liquid substances can be rapidly and accurately tested by the ATR method.
		2022 Vol. 42 (07): 2143-2147 [Abstract] ( 149 ) RICH HTML PDF (2804 KB) ( 73 )

	2148	Drugs Identification Using Near-Infrared Spectroscopy Based on Random Forest and CatBoost
		JIANG Ping¹, LU Hao-xiang², LIU Zhen-bing^2*
		DOI: 10.3964/j.issn.1000-0593(2022)07-2148-08
		Drug quality is related to people’s health and national lifeblood. The rapid development of the economy and society plays an extremely important role in the rapid and effective identification of drug quality. Spectral analysis technology has high accuracy, fast analysis speed and no pollution to samples, and is widely used in the chemical industry, petroleum, medicine and other important areas of people’s livelihood. In order to solve the problems of low accuracy, low identification speed and poor stability of the traditional drug identification model, the spectrometer was used to collect near-infrared spectroscopy data of drugs to achieve the purpose of pollution-free drugs. Then, random forest and CatBoost were combined to classify and identify drugs quickly and accurately. The proposed method firstly uses Random Forest (RF) to screen the effective characteristic wavelength of the spectrometer’s spectral data to eliminate the irrelevant wavelength in the drug spectral data and screen out the characteristic wavelength that can best characterize the sample properties. Then Extreme Learning Machine (ELM) was used as CatBoost weak classifier to analyze the feature wavelengths of the screening for drug attribute identification. Since ELM only contains one hidden layer and no iterative optimization is required to ensure the faster running of the identification model, CatBoost can improve the model’s identification accuracy by integrating a weak classifier. In order to effectively evaluate the performance of the drug identification model proposed in this paper, the spectral data of drugs of different sizes were constructed by randomly selected training sets, and experiments were carried out independently. The mean value of 10 running results was taken as the final result. In addition, Back Propagation with CatBoost, Support Vector Machine (SVM), BP, ELM, Summation Wavelet Extreme Learning Machine (SWELM) and Boosting were compared to evaluate the performance of the proposed model further. As can be seen from the classification results of training sets of different sizes, with the increase of training sets, the highest classification accuracy is 100%, and the prediction standard deviation tends to be 0. The experimental results show that the RF-CATBoost identification model proposed in this paper has higher classification accuracy, faster speed and stronger robustness than the comparison method on drug data sets of different sizes and can be widely used in the accurate identification of drug categories, to achieve effective supervision of drug quality.
		2022 Vol. 42 (07): 2148-2155 [Abstract] ( 182 ) RICH HTML PDF (3302 KB) ( 58 )

	2156	Visualization of Thiourea in Bulk Milk Powder Based on Portable Raman Hyperspectral Imaging Technology On-Site Rapid Detection Method Research
		YANG Qiao-ling^{1, 2}, CHEN Qin², NIU Bing², DENG Xiao-jun^3*, MA Jin-ge³, GU Shu-qing³, YU Yong-ai⁴, GUO De-hua³, ZHANG Feng⁵
		DOI: 10.3964/j.issn.1000-0593(2022)07-2156-07
		Thiourea is a potential protein adulteration compound with high nitrogen content and high toxicity. Conventional laboratory testing methods are complicated in-process and low inefficiency and cannot meet the port’s demand for rapid quality screening of large batches of bulk milk powder samples. In order to solve the problem of the lack of rapid real-time evaluation methods for port sampling supervision, this research uses a self-built portable point scanning Raman hyperspectral imaging system to develop a simple and efficient on-site visualized rapid detection method of thiourea in milk powder to ensure accurate supervision of bulk milk powder in the import and export process. In the study, thiourea milk powder mixtures with different additive concentrations (0.005%~2.000%) were used as samples. Whittaker smoothing method and adaptive iteratively reweighted penalized least squares (airPLS) were used to eliminate random background noise signal and fluorescent background interference of spectral data.. After peak identification, the single-band data at the characteristic displacement of thiourea is binarized to obtain a binary heat map of the region of interest of the mixed sample. The qualitative identification and positioning analysis of thiourea in milk powder can be carried out through the presence or absence and coordinates of the thiourea pixel in the binary map. Further analysis of the relationship between the number of thiourea pixels in the region of interest and the concentration of addition showed that with the increase of the concentration of addition, the number of thiourea pixels increased linearly, and the coefficient of determination (R²) of linear fitting was 0.991 3, the lowest detectable concentration of thiourea is 0.05%. Under the addition levels of 0.25%, 0.60%, 1.20%, and 1.50%, the number of pixels and the linear fitting relationship is used to predict the concentration of thiourea in milk powder. The results show that the relative error range of the predicted concentration is -9.41%~4.01%, the relative standard deviation is less than 7%. The point scanning Raman hyperspectral imaging system can complete the detection of a single sample within 10 minutes, combined with the software control system, real-time qualitative, quantitative and pollution distribution analysis of thiourea particles in milk powder. The method has the advantages of being simple and efficient, high sensitivity and stability, and good accuracy. It provides a technical supervision method for the real-time and rapid detection of adulterated thiourea in bulk milk powder at the port site and can significantly improve the quality evaluation of the supervision link of the bulk sample at the port, provide technical support for the rapid customs clearance of imported milk powder.
		2022 Vol. 42 (07): 2156-2162 [Abstract] ( 101 ) RICH HTML PDF (3151 KB) ( 194 )

	2163	Determinations of Zr, Hf and Nb Contents in Soil Samples by Laser-Induced Breakdown Spectroscopy (LIBS)
		ZHANG Peng-peng^{1, 2}, XU Jin-li^{1, 2}, HU Meng-ying^{1, 2}, ZHANG Ling-huo^{1, 2}, BAI Jin-feng^{1, 2}, ZHANG Qin^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2022)07-2163-06
		Zirconium, hafnium and niobium are important elements in analysing multi-objective geochemical samples. It is difficult to completely remove these high field strength elements in traditional wet pretreatment, resulting in low results. Moreover, traditional wet digestion has many disadvantages, such as high acid and alkali, long pretreatment process and environmental pollution. LIBS has a unique advantage in analysing geochemical samples, especially for those elements that are not completely digested under conventional conditions. In this study, the zirconium, hafnium and niobium elements in soil samples were quantitatively analyzed by laser-induced breakdown spectroscopy. Firstly, the output energy of the laser, the longer time of acquisition by the spectrometer and the diameter of the laser spot were optimized. Comparing the accuracy of the laser output energy from 0.0 to 4.4 mJ in determining zirconium, hafnium and niobium in soil samples, when 1.6mj is selected, the best experimental results can be obtained. Secondly, the influence of the extended collection time of the spectrometer on the determination of zirconium, hafnium and niobium in soil samples is analyzed, and the results show that 0.5 μs is the best acquisition delay time condition. Finally, the measurement results are obtained by comparing different laser spot diameters, and 50 μm is selected, the stability of the measurement is the best. At the same time, this experiment also carried out a comparative experimental study from the measurement mode and sample preparation pressure. The results show that the stability of the LIBS signal and the accuracy of quantitative analysis is the best when using laser-induced breakdown spectroscopy to measure Zr, Hf and Nb in soil samples under the sample preparation pressure of 2 000 kN and dynamic mode. Under the optimal experimental conditions (laser output energy 1.6 mJ, spectrometer acquisition time 0.5 ms and laser spot diameter 50 μ m). The dynamic model was used to detect Zr, Hf and Nb in 9 national first-class reference materials. The measured values are consistent with the recommended values. The precision of 3 national first-class reference materials is less than 11%, which can meet the analysis requirements of geochemical samples. Based on the above conditions, this paper established a laser-induced breakdown spectroscopy (LIBS) method to analyze the content of Zr, Hf and Nb in soil samples, which solved the problems of incomplete digestion and low determination results of Zr, Hf and Nb in wet digestion. It has high analysis efficiency, simple operation and no pollution. It also provides a choice for the development of solid sampling technology.
		2022 Vol. 42 (07): 2163-2168 [Abstract] ( 118 ) RICH HTML PDF (3525 KB) ( 80 )

	2169	Determination of Nb and Re in High Purity Tungsten by Precipitation Separation-Inductively Coupled Plasma Mass Spectrometry
		ZHANG Xuan^{1, 2, 3}, WANG Chang-hua^{1, 2}, HU Fang-fei^{1, 2}, MO Shu-min^{1, 2}, LI Ji-dong^{1, 2, 3*}
		DOI: 10.3964/j.issn.1000-0593(2022)07-2169-06
		High purity tungsten is an indispensable material in military defense, nuclear industry, semiconductors and other fields for its high melting point, high density and corrosion resistance. Its physical and chemical properties are greatly affected by the content of impurity elements. With the rapid development of new material research, the manufacturing of some key components puts forward higher requirements on the purity of tungsten, and this demand corresponds to strict detection of types and contents of trace impurity elements in high purity tungsten. Inductively coupled plasma mass spectrometry (ICP-MS) is an inorganic mass spectrometry technique with a low detection limit and rapid determination of multiple elements. However, some elements encounter serious mass spectrometry interference problems. Nb and Re in high purity tungsten determined by ICP-MS are interfered with by the doubly charged ions and hydride ions respectively, which are difficult to be eliminated by reaction cells and other techniques. In this paper, the tungsten matrix was separated from the solution by precipitation method using lead acetate as a precipitator to eliminate mass spectral interference. The interference intensity of tungsten matrix on Nb and Re, and the correction effect of standard internal elements on residual matrix and signal drift were mainly investigated. The experimental conditions, including sample dissolution solvents, the dosage of precipitator, acidity, temperature and aging time, were also discussed. The results showed that tungsten matrix solution with a concentration of 1 mg·mL^-1 had a significant positive interference effect on the determination of Nb and Re, and interference intensity enhanced with the increase of tungsten mass concentration. When tungsten concentration in solution was less than 2 μg·mL^-1 the mass spectral interferences produced by tungsten could be ignored (considering the requirement for a determination limit of 0. 10 μg·g^-1). Through various condition tests, the final conditions were as follows: sample was dissolved by mixed acid of nitric acid and hydrochloric acid, 600 μL ammonia (1+1) and 1.0 mL acetic acid-ammonium acetate buffer solution were added, 2.7 mL lead acetate solution with a concentration of 10 g·L^-1 was dripped at 250 ℃, and then the solution was heated for 5 min, and entire separation process was about 10 min; Cs was chosen as the standard internal element. The detection limit of Nb and Re was 0.007 and 0.036 μg·g^-1, the relative standard deviation was 12% and 4.8%, and the spiked recovery rate was 108% and 105%, respectively. This method is simple and fast, and the precision and accuracy of results meet actual requirements for the analysis of high purity tungsten.
		2022 Vol. 42 (07): 2169-2174 [Abstract] ( 113 ) RICH HTML PDF (1544 KB) ( 162 )

	2175	UV Aging Characterization of Paraloid Acrylic Polymers for Art Conservation by Infrared Spectroscopy
		GONG Xin^{1, 2}, HAN Xiang-na^1*, CHEN Kun-long¹
		DOI: 10.3964/j.issn.1000-0593(2022)07-2175-06
		Paraloid is the trade name of a series of acrylic resins. Paraloid products are one of the most useful materials in cultural relics conservation, which is usually applicable to a wide range of artifacts for consolidation, sealing and bonding. Among these products, Paraloid B-72 is the most representative one, widely used in art conservation at home and abroad. There are many reports on application cases, performance evaluation and aging mechanism research of Paraloid B-72. However, the other Paraloid products are obtained less attention due to limited domestic applications, and the aging performance research has not yet been conducted. This paper systematically evaluated the UV aging performance of Paraloid B-72, Paraloid B-44, Paraloid B-48N and Paraloid B-67. By using infrared spectroscopy to track the molecular structure changes during the 3864 h UV test, the aging mechanisms of these Paraloid products were further discussed and semi-quantitatively characterized. The results show that among the four Paraloid acrylic resins, the color and gloss of B-72 do not change significantly before and after aging test, while B-48N and B-67 color change greatly, and the gloss of B-44 decreased the most. During the aging process, the chain scission reaction and a certain degree of cross-linking reaction occur inside the acrylic resins, which is manifested in the weakening of the absorption of main functional groups and the increase of the carbonyl index (CI). According to the semi-quantitative results of the relative intensity of the main functional group absorption peakC═O, it can be reflected that B-72 has the best photostability. B-48N and B-44 perform slightly better than B-67. B-67 may be due to the low tertiary hydrogen bond energy on the isobutyl group, which is easy to absorb UV spectral energy and produce free radical oxidation reactions. Therefore, B-67 has the worst light aging resistance. In the comprehensive evaluation of the light aging performance of four Paraloid acrylic resins, B-72 has the best light stability, followed by B-44 and B-48N, and B-67 is the least suitable conservation material for outdoor cultural relics. The conclusions of this study are expected to provide some scientific suggestions for the first-line cultural relics conservators when choosing Paraloid acrylic resins as the conservation material.
		2022 Vol. 42 (07): 2175-2180 [Abstract] ( 141 ) RICH HTML PDF (3229 KB) ( 42 )

	2181	Simulated Estimation of Nitrite Content in Water Based on Transmission Spectrum
		WANG Cai-ling¹, WANG Bo², JI Tong³, XU Jun⁴, JU Feng⁵, WANG Hong-wei^6*
		DOI: 10.3964/j.issn.1000-0593(2022)07-2181-06
		NO₂-N is an important parameter in water bodies and can quickly detect organic pollution parameters. It is of great significance to the assessment of water quality. However, traditional methods are complicated in operation, subject to many interference factors, long measurement time, cannot reflect water quality changes in time, and cannot provide timely and effective early warning. For sudden water pollution incidents, because of the shortcomings of traditional methods, it is of great significance to explore accurate, real-time, and environmentally friendly detection methods for the NO₂-N content in environmental water bodies and drinking water. This experiment is to study the use of superior grade pure reagents to prepare 10 concentrations of NO₂-N nitrogen standard solutions (0.02, 0.04, 0.06, 0.08, 0.1, 0.12, 0.14, 0.16, 0.18 and 0.2 mg·L^-1), using the OCEAN-HDX-XR micro-fiber spectrometer to scan 10 times the transmission spectrum of the NO₂-N solution of each concentration in the range of 181.1~1 023.1 nm. Take the average value as the original transmission spectrum of the NO₂-N solution of each concentration, and then take the NO₂-N content of the solution as the dependent variable and the original transmission spectrum as the independent variable. Use the method of variable feature importance in random forest regression to screen the feature variables. Based on the cross-validation method, the number of the most stable model variables is selected, and the NO₂-N optimization random forest inversion model is established. The results of the study are as follows: (1) The variable explained rate (Var Explained) of the random forest model established by the whole band (Var Explained)=76.49%, and the mean squared residuals (Mean of squared residuals)=0.000 688; In the sensitive band of salt inversion, 195.1 nm has the highest importance value, and the leave-one-out crossover method is used to find that the random forest model has the lowest root mean square error when 19 spectral characteristic variables are used to screen the optimized random forest established by spectral characteristic variables Variable Explained rate (Var Explained)=83.45%, Mean of squared residuals (Mean of squared residuals)=0.000 552. Variable screening effectively reduces the amount of spectral data and provides a basis for the establishment of the optimization model; (3) Model verification of the established model, including the full-band random forest model test set R²=0.820 3, RMSE=0.03, test set R²=0.979 3, RMSE=0.01, optimized random forest model test set R²=0.873 4, RMSE=0.022, test set R²=0.979 8, RMSE=0.008, after comparing the full-band random forest model with the optimized random forest model, it is found that the optimized random forest model test set and test The interpretation and accuracy of the set model are higher than the full-band random forest model, indicating that the optimization method can not only effectively reduce the spectral dimension, but also has positive significance for finding the sensitive band of NO₂-N spectrum and establishing a high-precision NO₂-N inversion model. . Based on the above test results, an inversion method for optimizing the hyperspectral water quality NO₂-N parameters of the random forest model is proposed, which provides a new method for the dynamic detection of water quality NO₂-N parameters.
		2022 Vol. 42 (07): 2181-2186 [Abstract] ( 115 ) RICH HTML PDF (2457 KB) ( 41 )

	2187	Design of Measurement and Observation System Based on Digital Camera
		LEI Ming¹, SUN Mei-ling^3, NIE Kai², LIU Xu-lin^2
		DOI: 10.3964/j.issn.1000-0593(2022)07-2187-07
		In the atmospheric visibility observation, most of the related research focus on daytime observation, while the researches on nighttime observation are rare, and the research on the continuous observation of day and night are rarely reported. At present, there is no automatic atmospheric visibility observation instrument developed by the definition of visibility at home and abroad. In order to solve this problem, based on CCD digital camera technology, the principle of artificial observation optics is simulated, and a method of continuous observation of atmospheric visibility is proposed. This method is based on the visibility calculation formula of the target. It modifies the system parameters in the day and night mode, which can effectively eliminate the observation error caused by the external environmental factors and the internal factors of the camera system. In order to verify the effectiveness of the algorithm, three sets of principle prototypes based on the method are built for different situations such as sky occlusion, semi occlusion and open space (different situations will affect the brightness of the observation environment, to test the system’s resistance to stray light and adaptability to different environments). They are using the built digital photography visibility system (DPVS) to observe the actual atmospheric visibility at a minute level in the Beijing area. Observation experiments show that the observation system based on this method has a wide observation range and can effectively adapt to all kinds of complex weather conditions. It has a good observation effect in different weather conditions such as rain, snow and haze, and the DPVS system can respond quickly and correctly no matter the visibility changes rapidly or slowly. Through the comparative analysis of the observation results of DPVS, scatterometer and transmission instrument, it is found that there is a high correlation between DPVS and the observation results of the former two instruments: 0.973 1, and the observation performance is similar, with the average relative error of -1.54% and the root mean relative square error of 8.82%. The maximum relative error of this algorithm is -14.11%. According to the World Meteorological Organization (WMO) MOR, if the maximum relative error of the visibility meter is less than 20% within the full range, it is considered a standard visibility meter and can be used in actual observation. The DPVS system based on this algorithm meets the observation standard and can be practical. Moreover, the observation cost of the DPVS system is much lower than that of the scatterometer and transmission instrument, so it has a good prospect and application value.
		2022 Vol. 42 (07): 2187-2193 [Abstract] ( 108 ) RICH HTML PDF (5227 KB) ( 39 )

	2194	Study on the Spectral Characteristics of Scapolite From Madagascar
		DING Wei¹, CHEN Quan-li^{1, 2*}, AI Su-jie¹, YIN Zuo-wei¹
		DOI: 10.3964/j.issn.1000-0593(2022)07-2194-06
		The gemological and spectroscopic properties of the Madagascar scapolite is studied based on analyses of fifteen samples using EMPA, FTIR, Raman spectroscopy, UV-Vis Spectroscopy, fluorescence spectroscopy and some gemological instruments. The gemological characteristics of Madagascar scapolite are consistent with the theoretical values of scapolite; The samples are uniform in color and have a glassy luster. The raw stone crystal is relatively intact. Longitudinal stripes and maroon impurities are commonly seen on the surface of them. Iridescence can be seen on the surface of some samples, and a variety of inclusions can be seen inside the samples, such as biotite and colorless crystal inclusions. The infrared spectrum analysis shows that absorption peaks of 1 039, 1 105, 1 196 cm^-1 in the fingerprint area are attributed to the Si(Al)—O group. 752 cm^-1 peak is due to Si—Si(Al) stretching, 551, 687, 624 cm^-1 peaks are due to O—Si (Al)—O bending vibration. Bending vibration of Si—O—Si associated with Na(Ca) —O stretching jointly results in a 459 cm^-1 peak. 416 cm^-1 is due to the bending vibration of Si—O—Si. Absorption peaks related to functional group area are mainly due to different vibrational modes and frequencies of CO^2-₃ (2 499, 2 629, 2 964 cm^-1) and O—H(3 530 and 3 592 cm^-1), which are diagnostic for the identification of scapolite. The Raman Spectroscopic analysis indicates that the bending vibration of bridge oxygen produces 459 and 538 cm^-1 peaks; Al—O vibration leads to a 775 cm^-1 peak. The vibration of SiO₄ tetrahedron unit generates 1 114 cm^-1. UV-Vis spectrum shows 379 and 420 nm, which are caused by electron transfer between Fe²⁺ and Fe³⁺ in tetrahedron position. The yellow color of Madagascar scapolite is due to transition metal elements. The intensity of the 420 nm peak directly affects the color depth of scapolite. Analysis of 3D luminescence shows a relatively uniform luminescence phenomenon, which shows two fluorescence peaks, one strong and one weak, mostly centered at 302 nm(λ_ex)/343 nm(λ_em). The EMPA analysis result indicates that the sample belongs to Dipyre in the scapolite series. The Ma value is around 66%~69%, and the average value is 68.1%, and with the increase of the Ma value, the refractive index decreases. As a nondestructive testing technique, spectrum testing is suitable for identifying gem varieties. It is of great significance for the identification of Madagascar scapolite. It provides data support for the traceability of origin and the differentiation of scapolite varieties.
		2022 Vol. 42 (07): 2194-2199 [Abstract] ( 105 ) RICH HTML PDF (3764 KB) ( 150 )

	2200	Application of Micro X-Ray Fluorescence Imaging Technology in Core Analysis
		ZHANG Qi-yan¹ , LIU Xiao¹, YANG Jie^{2, 3*}, SHI Wei-xin¹, GAO Qing-nan¹, ZHANG Hong¹, DENG Huang¹
		DOI: 10.3964/j.issn.1000-0593(2022)07-2200-07
		Micro-XRF analysis technology is one of the non-destructive analysis methods that use tiny X-Ray beams to irradiate samples and then analyze fluorescence spectra and observe the components of the samples. It has the characteristics of high sensitivity, high efficiency and high accuracy. In this experiment, The Micro-XRF spectrometer (M6 JETSTREAM) was used to scan the core samples of the ZK3801 drilling in Dongguashan copper mine, Anhui province. It can analyze the distribution characteristics and combination relationships of 17 elements in different parts. The results show that (1)The high-value spatial distribution regions of Cu and Fe do not overlap basically, and the distribution ranges of S and Fe are highly overlapped, Ni, Bi, Pb, Zn, Si and Na are closely related to Cu, while Ti, Al and K have a weak correlation with Fe; (2)In the vertical direction, as increasing depth, the content of Fe increases gradually, while the content of Cu and other elements shows a decreasing trend; (3) The element distribution is modified by the middle Carboniferous submarine jet sedimentation and mineralization and magmatic-hydrothermal mineralization;(4) The ore minerals of the drill hole are mainly pyrrhotite, chalcopyrite and pyrite, with a certain combination law in the vertical direction. The gangue minerals are mainly quartz, garnet and diopside; Analyzing the spatial distribution of elements, correlations, and mineral combinations and distribution relationships can provide new understanding and new evidence for the enrichment and migration of elements, mineralization mechanisms, genetic models, and environmental, geological processes. Moreover, combined with the distribution pattern of the geochemical halo of the deposit, trace elements can be used as indicator elements to find the main mineral species and provide a basis for deep prospecting. Additionally, it can filter out the information and location that we are interested in quickly. It can provide powerful technical support for different scales and different levels of requirements for screening various fine parameters in the later stage.
		2022 Vol. 42 (07): 2200-2206 [Abstract] ( 140 ) RICH HTML PDF (7540 KB) ( 81 )

	2207	*Application of Rapid Fluorescence Analysis Technology on Study on Glycine Soja* Response to PAHs（Phenanthrene）**
		DING Jun-nan, WANG Hui, YU Shao-peng^*
		DOI: 10.3964/j.issn.1000-0593(2022)07-2207-06
		In this study, the chlorophyll fluorescence analysis was used as a technical means to study the effects of PAHs (Phe) stress in soil on chlorophyll fluorescence characteristics and light energy distribution parameters of Glycine soja. The results showed that Phe stresses can decrease PSⅡ activity center and the electron transfer ability, resulting in the decrease of the light energy utilization ability, especially for the use of the strong specular ability. Under 200 mg·kg^-1 Phe stress conditions, F_v/F_m, q_P, ENR and NPQ were changed, and slow light inhibition occurred in G. soja leaves, which reduced the electron transport capacity and photosynthetic reactivity of the photosynthetic electron transport chain. Under the control of different light intensity and the increase of concentration of Phe stresses that G. soja leaves chlorophyll fluorescence response curve Ф_PSⅡ and q_P parameters showed a trend of decrease, increase of NPQ launched the PSⅡ cycles way excitation energy dissipation of excess radiation, in order to maintain the normal physiological function of photosynthetic institutions. Those parameters such as F_m，F_v/F_m，F_v/F_o and PI_ABS decreased with the increasing concentration of Phe, which means that the soils Phe stressing subdued the photochemical activity of PSⅡ of those G. soja. Based on the study of electronic supply and transmission capacity at electronic donor side and receptor side of the PSⅡ found that on 0.3 ms (K point) of the OJIP curve of Phe stressed G. soja leaf, the fluorescence intensity increased the activity of OEC decreased. Phe stressing also caused the increase of the fluorescence intensityat the J point and I point on the OJIP curve of Phe stressedG. soja leaf. It showed that the Phe stressing reduced the electronically acceptability at the electronic receptor side of PSⅡon the leaves of G. soja, and made the electronic from Q_A to Q_B transfer blocked. The optical energy absorption and distribution parameters of seedling leaves of G. soja were influenced by Phe stressing. With the increase of soil Phe concentration, theratio of optical energy absorbed by PSⅡ reaction center and used for electron transfer after Q^-_A and the energy absorbed by each unit reaction center and used for electron transfer was reduced in the leaves of treated G. soja. It means that the proportion of optical energy captured by the reaction center and used for the photochemical reaction was reduced, and the proportion used through the invalid heat dissipation was increased. It could be concluded that there were three important reasons that generated the reduction of activity of PSⅡ reactive center of G. soja leaves under the soil Phe stress, which was the damage of OEC at electron donor side of PSⅡ, the electron transfer ability reducing at the electron acceptor side of PSⅡ and the change of the distribution and utilization of optical energy. This studise on the chlorophyll fluorescence analysis technique could provide guidance for the effect mechanism of plant photosynthesis to PAHs (Phe) stress.
		2022 Vol. 42 (07): 2207-2212 [Abstract] ( 126 ) RICH HTML PDF (3009 KB) ( 41 )

	2213	The Proceedings of Raman Spectroscopy in Cervical Cancer in Recent Five Years
		SHEN Zhuo-wei, LI Rui, WANG Yang, XU Xiao-guang, XIAO Zhen^*
		DOI: 10.3964/j.issn.1000-0593(2022)07-2213-05
		Cervical cancer is the fourth incidence rate of cancer in women. If we can diagnose cervical cancer and cervical intraepithelial neoplasia early, we can greatly improve survival. The existing diagnostic techniques have the problems of high false-positive rate, low specificity, low sensitivity, time-consuming and high price. Raman spectroscopy is a new and reliable technology which can analyze the molecular structure of substances and the chemical composition of human tissues. In medical research, Raman imaging has been successfully applied to nasopharyngeal carcinoma, gastric cancer, lung cancer, esophageal cancer, renal tumor, cerebral cancer, etc. This review summarizes the key research of Raman spectroscopy in cervical cancer in the recent five years. Raman technology has been used in the study of cervical cancer for decades. In the past five years, we have studied the influence of inflammatory factors on the diagnosis, the differentiation of cervical squamous cell carcinoma and adenocarcinoma. This review summarizes the literature in recent five years from histology in vivo, histology in vitro, cytology and blood. It also summarizes the data processing methods, excitation wavelength, Raman wave number, and representative substances. The existing literature has proved that the specificity and accuracy of Raman spectroscopy in the diagnosis of cervical cancer can reach more than 90%, which is no less than the traditional hematoxylin-eosin (HE) staining. Compared with HE staining, Raman technology has the advantages of no staining, no fixation, less demand for professionals, faster and so on, which provides another feasibility for the diagnosis of cervical cancer. However, more research and evidence are needed to fully demonstrate the role of Raman spectroscopy in the diagnosis of cervical cancer before it is used in the clinic. We are also looking forward to more samples and more research.
		2022 Vol. 42 (07): 2213-2217 [Abstract] ( 129 ) RICH HTML PDF (1000 KB) ( 180 )

	2218	Early Classification and Detection of Melon Graft Healing State Based on Hyperspectral Imaging
		YANG Jie-kai¹, GUO Zhi-qiang¹, HUANG Yuan^{2, 3*}, GAO Hong-sheng¹, JIN Ke¹, WU Xiang-shuai², YANG Jie¹
		DOI: 10.3964/j.issn.1000-0593(2022)07-2218-07
		The purpose of grafting is to improve the ability of plants to resist soil-borne diseases and abiotic stresses. The early detection of the grafting healing state of melon is an important demand for the current industrial development of nursery plants. Based on the standard normal variable transformation savitzky Golay smoothing second derivative (SNV-SG-SD) preprocessing, this paper proposes a competitive adaptive reweighting (DIS-CARS-SPA) feature extraction algorithm fusing grafting difference information. Establishes a radial basis function support vector machine (GS-RBF-SVM) classification model based on grid optimization, The early classification detection of melon grafting healing state based on hyperspectral imaging was realized. Firstly, hyperspectral images of grafted survival seedlings and non-survival seedlings with pumpkin as rootstock and melon as scion were collected within 1~7 days of the healing period. Nine spectral preprocessing methods, two feature extraction algorithms and five optimization algorithms, and four kernel function support vector machine (SVM) classification models were used for analysis. The results show that the best is SNV-SG-SD spectral preprocessing, DIS-CARS-SPA feature extraction and GS-RBF-SVM classification model. Further analysis using the model shows that the classification accuracy of different types of binary classification on the same day can reach more than 99% on any day within 1~7 days of the healing period. More than 90.17% of the grafted seedlings survived on different days; More than 97.03% of the grafted non-survival seedlings could be classified on different days. On different days and types of 14 classifications, it can reach 96.85%, which is 0.59% higher than the cars-spa feature extraction method without fusion of grafting difference information and 3.37% higher than the method without only preprocessing feature extraction. The results show that the proposed method can not only realize the two classifications of grafted survival seedlings and non-survival seedlings on the same day but also the two classifications of the same type on different days and the multi-classification of different types on different days. In practical application, it can advance the classification time to the first day after grafting (3~4 days for naked-eye observation and 1~2 days for machine vision technology). At the same time, the third day is the difference between mutation days of grafted survival seedlings and non-survival seedlings. The state of grafted survival seedlings can be divided into three stages: weak, medium strong, and the state of non-survival seedlings can be divided into two stages: weak weaker. This conclusion can provide effective guidance for the production of grafted melon seedlings and has a certain theoretical and practical value.
		2022 Vol. 42 (07): 2218-2224 [Abstract] ( 148 ) RICH HTML PDF (3489 KB) ( 74 )

	2225	Predicting Yield Reduction Rates of Frost-Damaged Winter Wheat After Jointing Using Sentinel-2 Broad-Waveband Spectral Indices
		ZHAO Ai-ping¹, MA Jun-cheng¹, WU Yong-feng^1*, HU Xin², REN De-chao², LI Chong-rui¹
		DOI: 10.3964/j.issn.1000-0593(2022)07-2225-08
		On the regional scale, the late frost damage to winter wheat after jointing showed a spatial difference which determines that the sub-regional measures against the frost damage should be implemented. Broad-waveband spectral indices based on the Sentinel-2 satellite were proposed in this study to predict yield reduction rates of winter wheat. It is of great significance to disaster assessment and production management decision-making. Based on the artificial frost simulation experiments, the canopy reflectance data measured by ASD FieldSpec^® 3 spectroradiometer were simulated to the Sentinel-2 wavebands using spectral resampling. And then, the nineteen published spectral indices and three new forms of wavelength random combinations (simple ratio, simple difference, and normalized difference) were used to construct the linear regression models with winter wheat yield reduction rates. In every form, broad-waveband spectral indices with the top three coefficients of determination were selected as the candidate indices. Aiming at the frost event in the Shangqiu area, all candidate indices were calculated using the Sentinel-2 reflectance data and used to predict winter wheat yield reduction rates, which were validated by the measured yields of the ground sampling points. The results indicated that: (1) With the decrease of the treatment temperatures, canopy reflectance shows a decreasing trend in the near-infrared region, but increased in the visible and short-waveband infrared regions. (2) Most of the nineteen published spectral indices were significantly (p<0.001) correlated with yield reduction rates, regardless of whether the canopy reflectance data were before or after resampling. The twelve candidate spectral indices screened out have good linear regression accuracy for predicting the yield reduction rates of winter wheat and the coefficient of determination above 0.631 in the calibration and the validation datasets. (3) The accuracy of candidate spectral indices calculated from sentinel-2 satellite data showed that the three spectral indices, including the band B9 failed to pass the significance test, and the other nine spectral indices all passed the extremely significant test. The two spectral indices (B8a-B12 and B8-B12) based on the combinations of the B8, B8a, and B12 had good accuracy. The coefficient of determination was 0.543 and 0.492, the root means square error was 8.510% and 8.971%, respectively. Further, B8a-B12 and B8-B12 were found to conform to the simple difference form, which was considered the optimal combination of the broad-waveband spectral indices predicting yield reduction rates of winter wheat. The research results revealed that the response mechanism of canopy reflectance at early spike development stage of winter wheat under different low-temperature stress, indicating that Sentinel-2 broad-waveband spectral indices have good accuracy in predicting the yield reduction rate of winter wheat. It is feasible to predict yield reduction rate at a regional scale after frost and has a guiding role in formulating frost disaster measures in different regions.
		2022 Vol. 42 (07): 2225-2232 [Abstract] ( 110 ) RICH HTML PDF (3327 KB) ( 46 )

	2233	Fertilization Management Zoning Based on Crop Canopy Spectral Information
		CHEN Hao¹, WANG Xi^1*, ZHANG Wei¹, WANG Xin-zhong¹, DI Xiao-dong¹, WANG Chang²
		DOI: 10.3964/j.issn.1000-0593(2022)07-2233-08
		With the continuous development of ground remote sensing technology, more and more crop canopy spectral sensors are applied to agricultural production, among which the Greenseeker plant spectral detector is widely used. Greenseeker can obtain crop canopy spectral information, normalized vegetation index (NDVI) data and divide fertilization management zoning. Targeted variable rate fertilization can be realized according to fertilization management zoning. The fuzzy c-means (FCM) algorithm is common for dividing fertilization management zoning, but the FCM algorithm has certain limitations. In the calculation process, the iterative calculation will be carried out continuously with the increase of data, which will affect the speed of fertilization management zoning. Based on the FCM algorithm, a model-based fuzzy c-means (MFCM) algorithm is proposed. In dividing the fertilization management partition, this algorithm does not have to iteratively calculate all the data every time a group of data is obtained, which can improve the speed of dividing the fertilization management partition. The NDVI data of soybean and maize were obtained through the established crop canopy spectral information collection platform. The fertilization management zoning was divided by the MFCM algorithm, and the division effect was evaluated by evaluation index contour coefficient (SC) and adjusted rand index (ARI). The results show that with the increased NDVI data, the MFCM algorithm can partition fertilization management partition faster than the FCM algorithm. The MFCM algorithm is 0.02～0.15 seconds faster; the MFCM algorithm is 0.07～0.51 seconds faster in dividing maize fertilization management zoning. By calculating the indexes SC and ARI to evaluate the effect of dividing fertilization management zoning, it is found that when dividing different NDVI data, the maximum difference of SC value is 0.022, indicating that the effect of dividing fertilization management zoning by the two algorithms is not different; The ARI value is sensitive to data changes. It can be maintained above 0.7 after the NDVI data volume reaches 6 000, but it will decrease significantly when the NDVI data changes.
		2022 Vol. 42 (07): 2233-2240 [Abstract] ( 231 ) RICH HTML PDF (5734 KB) ( 66 )

	2241	Using Fiber Grating Cascade Structure to Realize Fiber Delay Line
		WANG Chong, DU Huan, WANG Jing, WANG Jing, WANG Jing-hua
		DOI: 10.3964/j.issn.1000-0593(2022)07-2241-06
		Based on fiber grating to achieve picosecond-level delay, a microsecond-level cascade structure combining fiber grating and single-mode fiber is proposed. This structure can achieve a narrow wavelength with a center wavelength of 1 550~1 553 nm and a spacing of 1 nm. The reflective delay line has four different delays: 1, 1.5, 2 and 2.5 μs. The single-wavelength-reflected chirped Bragg fiber grating is connected with a 103 m single-mode fiber to form a delay unit, and then an optical circulator cascades the four delay units and uses a fiber reel with an inner radius of 3 cm to integrate the transmission fibers of the four delay units. With the help of the mirror function of the fiber grating, the optical signals of different wavelengths are controlled to pass through different transmission distances to achieve the purpose of corresponding time delay. In this article, through the simulation analysis of the reflection spectrum of the chirped fiber Bragg grating, it can be found that the side lobes of the adjacent reflection spectrum will overlap. Therefore, six apodization functions are used to filter the side lobes. The results show that: the apodization function has different filtering effects on the side lobes of the reflection spectrum. The Cauchy apodization function can filter the side lobes and has the least impact on the reflection spectrum envelope. After Cauchy apodization, the reflectance of optical signals of different wavelengths can reach 1 in the range of the corresponding center wavelength of 1 nm, and the reflectance in other ranges is 0. Because the use of fiber reel to integrate the delay unit transmission fiber will produce a certain loss, the bending loss is simulated and analyzed. The results show that when the bending radius is the same, the loss is proportional to the working wavelength; when the working wavelength is the same, the bending loss is inversely proportional to the bending radius. When the bending radius is greater than 2.9 cm, the bending loss curve changes smoothly and tends to zero. Therefore, when the inner radius of the optical fiber winding reel is 3 cm, it is ensured that the volume is reduced without excessive loss. The waveforms of signals with a frequency of 2 000 Hz after different transmission distances are tested by a TDS784D oscilloscope. The results show that the signal parameters remain unchanged after 3 m and 5 km transmission lines. After long-distance transmission, the original signal characteristics can still be maintained. Therefore, the use of a 103 m transmission line can achieve the delay. The W-GGL optical power meter measured the output power at different frequencies. Compared with the output power of straight fiber, when the bending radius is 2~3 cm, the deviation is large, when the bending radius is equal to 3 cm, the deviation is 0.18 dBm, and when the bending radius is greater than 3 cm, it will approach infinitely. Therefore, the inner radius of the winding reel is set to 3 cm conforming to the loss range of the optical fiber delay line.
		2022 Vol. 42 (07): 2241-2246 [Abstract] ( 116 ) RICH HTML PDF (4144 KB) ( 34 )

	2247	*Similar Wood Species Classification Within Pterocarpus* Genus Using Feature Fusion**
		WANG Cheng-kun^{2, 3}, ZHAO Peng^{1, 2*}, LI Xiang-hua²
		DOI: 10.3964/j.issn.1000-0593(2022)07-2247-08
		There are much rare wood in the Pterocarpus genus. Rosewood is very similar to different tree species. Traditional wood identification methods are mainly based on wood anatomy, and the wood species are judged by observing the structural characteristics of wood slices. Although this method has a high identification accuracy, its identification process is relatively complex, and the technical difficulty is relatively high. Corresponding to wood anatomy is the identification method of wood tree species using image or spectral information. Although this kind of method has a relatively simple identification technology, it often fails to achieve a good identification effect in identifying similar wood species belonging to the same genus. This paper proposes a wood species identification method based on the fusion of spectral features and texture features of wood section. This method has a simple identification process, a high degree of automation, and a high identification accuracy. First collected by digital camera and a spectrometer wood, slice image information and spectral information, and then respectively using texture feature extraction method and spectrum feature extraction method to extract the characteristics of two kinds of the feature vector, then using the feature level fusion method based on canonical correlation analysis to these two characteristics vector fusion, finally using support vector machine (SVM) for the fusion of feature vector classification recognition. In order to verify the effectiveness of the method, three sections of 5 species of Rosewood species commonly found in the market were taken as research objects to identify these wood species. The experimental results show that the highest recognition accuracy is 80.00% when texture features are used alone, 94.40% when spectral features are used alone, and 99.20% when fused features are used. In this paper, these 5 wood species were mixed with 30 other wood species, and the number of mixed wood samples could reach 1 750. The experimental results show that the method can identify 35 wood species, including Rosewood, and the accuracy rate is 98.29%. To sum up, the texture features and spectral features of wood can effectively complement each other to further improve the recognition accuracy. At the end of this paper, the proposed method is compared with the current mainstream method, and the results show that the wood species identification method described in this paper is higher than the current mainstream method.
		2022 Vol. 42 (07): 2247-2254 [Abstract] ( 110 ) RICH HTML PDF (5324 KB) ( 52 )

	2255	*Study on Nondestructive Identification of Panax Notoginseng* Powder Quality Grade Based on Hyperspectral Imaging Technology**
		ZHANG Fu-jie, SHI Lei, LI Li-xia^*, ZHAO Hao-ran, ZHU Yin-long
		DOI: 10.3964/j.issn.1000-0593(2022)07-2255-07
		Panax notoginseng powder is the main consumption and commodity form of panax notoginseng. There are shoddy or even adulterated phenomena in the market. As panax notoginseng powder is a powdery material, it is not easy to distinguish with the naked eye. In order to identify the quality grade of panax notoginseng powder, visible near-infrared hyperspectral imaging technology was used to identify the panax notoginseng powder with different quality grades. The taproots of panax notoginseng of 30 heads, 40 heads, 60 heads and 80 heads were ground into powder to prepare samples. The hyperspectral image of 384 samples of four quality grades was acquired by using a visible near-infrared hyperspectral imaging system(400.68～1 001.612 nm). Region of interest (ROI) was extracted from the hyperspectral image, and the average spectral value of samples was calculated. 384 samples of panax notoginseng powder were divided into training sets and test sets in a ratio of 2∶1. The original spectra of panax notoginseng powder were preprocessed using multiplication scatter correction (MSC), Savitzky-Golay (SG) and standard normal variable (SNV), and the support vector machine (SVM) was employed to form the classification models based on MSC, SG and SNV. By comparing the classification accuracy of SVM models based on MSC, SG and SNV, it was found that SNV had the best effect on preprocessing. Iterative reserved information variable (IRIV), variable combined cluster analysis (VCPA) and variable combined cluster analysis and iterative reserved information variable (VCPA-IRIV) were adopted to extract feature wavelengths from the spectra after SNV pretreatment, and the SVM was employed to form the classification models based on feature spectra and original spectra. By comparing the range of feature wavelengths and the classification accuracy of SVM models based on IRIV, VCPA and VCPA-IRIV, it was found that VCPA-IRIV, which combines VCPA and IRIV, had the best effect on feature selection. VCPA-IRIV extracted 18 feature wavelengths to participate in the modeling instead of the full spectra, and the algorithm can reduce the complexity of the model while maintaining the model’s classification accuracy. In order to improve the classification accuracy of the model, the gravitational search algorithm (GSA) was introduced to search the optimal parameters(c,g) in the SVM model and compared with Grid Search (GS). The results indicated that the VCPA-IRIV-GSA-SVM model has the best classification effect, and the classification accuracy of the test set reached 100%. Thus, it is feasible to use visible near-infrared hyperspectral imaging technology to identify the quality grade of panax notoginseng powder. This method references the quality grade identification of panax notoginseng powder in the market.
		2022 Vol. 42 (07): 2255-2261 [Abstract] ( 129 ) RICH HTML PDF (3671 KB) ( 87 )

	2262	Spectral Selection Method Based on Ant Colony-Genetic Algorithm
		HUANG Qing¹, XUE He-ru^1, LIU Jiang-ping^1, LIU Mei-chen¹, HU Peng-wei¹, SUN De-gang²
		DOI: 10.3964/j.issn.1000-0593(2022)07-2262-07
		As an important nutritional component in milk, fat is an important index to evaluate milk quality. Hyperspectral image technology can provide tens to thousands of bands of data and can reflect the subtle spectral differences of different components in milk. On the other hand, there is often a strong correlation between adjacent bands, which increases the amount of calculation and easily causes problems such as dimension disaster. Therefore, it is very important to select bands for hyperspectral data. This paper proposes a PLS-ACO feature band selection method combined with a genetic algorithm to form a new feature band selection method of PLS-ACO-GA. The two methods proposed in this paper are based on ant colony optimization. The absolute value of the regression coefficient of the PLS regression model is the main basis for evaluating the importance of wavelength, which is used as the heuristic information of ant colony optimization. Ant colony optimization is used for intelligent search, combined with genetic algorithm to produce more excellent characteristic band combinations. To avoid that pls-aco algorithm only obtains the optimal local solution. The optimal band combination can better reflect the information of fat composition in milk. By calculating the wavelength contribution rate, the optimal band combination is selected and compared with the spectral feature selection methods of genetic algorithm, cars algorithm and basic ant colony optimization. Finally, the prediction effects of the PLS regression model under different feature selection methods are compared. PLS-ACO, PLS-ACO-GA, CARS, GA and ACO screened 18, 16, 40, 43 and 42 characteristic bands in the spectrum of milk samples, respectively. The PLS prediction model after the PLS-GA-ACO screening band has the best effect. The prediction sets R²_P and RMSEP are 0.997 6 and 0.062 2 respectively, followed by PLS-ACO, and the prediction sets R²_P and RMSEP are 0.997 0 and 0.077 8 respectively. PLS-ACO and PLS-ACO-GA reduce the number of characteristic bands and improve the accuracy of the model. MLR, RFR and PLS regression prediction models are established based on PLS-ACO-GA data after characteristic band selection. The R²_P and RMSEP of the MLR prediction model are 0.997 6 and 0.062 3 respectively. R²_P and RMSEP of the RFR regression model were 0.999 9 and 0.003 0 respectively, and R²_P and RMSEP of the PLS regression model were 0.997 6 and 0.062 2 respectively. RFR model performs best among the three regression prediction models. The results show that hyperspectral technology can detect the fat content in milk, which provides a new, rapid and non-destructive method for the detection of fat content in milk.
		2022 Vol. 42 (07): 2262-2268 [Abstract] ( 132 ) RICH HTML PDF (2837 KB) ( 65 )

	2269	Rocky Desertification Information Extraction in Karst Terrain Complex Area Based on Endmember Variable
		RUAN Ou^{1, 2}, LIU Sui-hua^{1, 2*}, LUO Jie^{1, 2}, HU Hai-tao^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2022)07-2269-09
		Shadows, mixed pixels and spectral variations are common in remote sensing images in mountainous karst areas due to complex terrain and broken surface. Dimidiate pixel model (DPM) based on multispectral remote sensing is difficult to accurately extract rocky karst desertification (KRD) information in areas with significant spectral variations and shadows. The mixed pixel decomposition technology of hyperspectral remote sensing can decompose complex mixed pixels into the mixed ratio corresponding to the pure landmark spectrum and each landmark spectrum, which provides the possibility for obtaining higher precision rocky desertification information in complex mountainous areas. However, due to the changes in many factors such as illumination, environment and atmosphere, the end members will vary to varying degrees, which will result in significant errors in the process of mixed pixel decomposition. Secondly, it is difficult to directly obtain the pure landmark spectrum from mountain images with complex terrain and strong surface heterogeneity and establish a spectrum library to deal with spectral variation. Therefore, the focus of current studies is how to deal with spectral variation and terrain effect in this case and obtain effective and accurate information extraction of rocky desertification. In order to solve the above problems, the generalized linear mixed model (GLMM), which simulates the reflectivity change of ground objects caused by illumination conditions and considers the spectral variation at each wavelength interval, was adopted to reduce the influence of spectral variation and terrain effect in the process of information extraction of rocky desertification in karst areas. First of all, the typical representative spectra of main ground objects (vegetation, bare rock and bare soil) in the karst area were extracted from GF-5 hyperspectral images. Then the spectral variation of each pixel under different illumination was simulated based on the extracted landmark spectrum, and the most suitable spectral combination was selected to decompose the pixels to get the best unmixing effect. In order to verify the reliability of the method, the visual interpretation results of high-resolution images were used as a reference to verify the prediction results of the method, and the fully constrained least squares linear spectral unmixing (FCLSU) DPM without considering end-member variation were selected for comparison. The results showed that it was necessary to consider shadows, mixed pixels and spectral variation in karst mountainous areas with highly complex terrain. The total accuracy of GLMM in rocky desertification information extraction reached 84.89%, significantly higher than that of the other two methods (59.68% and 67.34%). The accuracy of GLMM in the illumination area and shadow area was similar to that of GLMM in the illumination area and shadow area. However, the other two were quite different, and the shadow area was lower than the illumination area, which reflects that GLMM can effectively reduce the influence of terrain effect and improve the accuracy of information extraction of rocky karst desertification.
		2022 Vol. 42 (07): 2269-2277 [Abstract] ( 114 ) RICH HTML PDF (3945 KB) ( 36 )

	2278	Inversion of Leaf Area Index Based on GF-6 WFV Spectral Vegetation Index Model
		WANG Xiao-xuan¹, LU Xiao-ping^1*, MENG Qing-yan^{2, 3}, LI Guo-qing⁴, WANG Jun⁴, ZHANG Lin-lin^{2, 3}, YANG Ze-nan¹
		DOI: 10.3964/j.issn.1000-0593(2022)07-2278-06
		Agriculture is not only the basic pillar of national economic development but also the basic social development industry. With the progress and development of agricultural remote sensing technology in China, many remote sensing satellites, such as Gaofen-1, 2 and 6, have been launched, providing important technical support for agricultural situation monitoring, crop growth and agricultural industrial structure adjustment in China. Agricultural remote sensing has become an important means of agricultural science and technology innovation and precision agriculture. LAI is an important key index that can be used to measure vegetation canopy’s physiological and biochemical characteristics. LAI can not only be used to evaluate the initial energy exchange on the surface of the vegetation canopy but also provide corresponding quantitative structural data and reflect the spectral energy information of the vegetation canopy. At the same time, the leaf area index is a key input to the production model of the terrestrial ecosystem and land use process in the context of terrestrial climate change. In addition, when it is found that the vegetation canopy is directly or indirectly affected by human activities and climate change, LAI is also a very important measurement standard for terrestrial ecosystems to cope with climate change. There are few kinds of researches on leaf area index inversion of GF-6 WFV remote sensing image, and the traditional spectral vegetation index model has a weak mechanism and stability. This article is based on GF-6 WFV remote sensing image in the Luancheng county as the experimental zone. Through spectral vegetation index and the measured leaf area index structure of 5 kinds of traditional spectral vegetation index model and 15 kinds of red edge of ratooning buds to participate in the spectrum of the vegetation index model inversion leaf area index, evaluating model using R2 and RMSE. At the same time, using the actual leaf area index was not involved in the modeling, model and using the MODIS LAI product authentication model. The experimental results showed that: (1) Correlation analysis showed that, on the whole, 20 spectral vegetation indexes were significantly correlated with LAI, with the correlation coefficient above 0.4, and the spectral index correlation of red-edge participating structures was higher than that of non-red-edge participating structures, among which NDSI had the best correlation. (2) Fitting analysis showed that, on the whole, 20 spectral vegetation indexes had a better fitting effect with LAI, among which NDS13 had the highest fitting accuracy, R² was 0.803, and RMSE were 0.301 2. R² and RMSE was 0.803 and 0.301 2, respectively. (3) As seen from the spatial distribution of inversion maps, the inversion results were in line with the actual local situation. (4) The verified model of measured LAI showed that the overall LAI fitting of measured LAI and NDSI3 model inversion is good, with R² and RMSE of 0.804 and 0.312 5 respectively, indicating that this model can effectively invert the growth status of maize at the milk stage. (5) The verification model of MODIS LAI products indicated that the LAI of MODIS mean it is higher than the LAI of GF-6, mainly due to the serious mixing of MODIS image pixels and the low spatial resolution. In summary, GF-6 WFV has a strong ability to invert LAI, and the spectral vegetation index model with red edges in its image can effectively invert LAI at the milk stage, providing a basis for maize growth potential monitoring.
		2022 Vol. 42 (07): 2278-2283 [Abstract] ( 154 ) RICH HTML PDF (4007 KB) ( 47 )

	2284	Combining the Red Edge-Near Infrared Vegetation Indexes of DEM to Extract Urban Vegetation Information
		WANG Xiao-xuan¹, LU Xiao-ping^1*, LI Guo-qing², WANG Jun², YANG Zen-an¹, ZHOU Yu-shi¹, FENG Zhi-li¹
		DOI: 10.3964/j.issn.1000-0593(2022)07-2284-06
		With the continuous improvement of living standards, residents’ requirements for urban vegetation are also increasing. Urban vegetation has become one of the important criteria to measure the livability of cities and plays a very important role in assessing and protecting urban biodiversity. Therefore, rational planning of urban vegetation is an important means of solving environmental problems and improve the quality of life. To sum up, monitoring urban vegetation becomes the main task, and the extraction of urban vegetation becomes the top priority. At present, the problems of urban vegetation extraction mainly focus on two aspects. Vegetation extraction is affected by region and species. On the other hand, Vegetation extraction is affected by topography and the shadow of buildings. In order to solve the above problems, this paper proposes a red edge-near infrared vegetation index model based on DEM. In this experiment, worldView-3 remote sensing images with red-edge bands and high spectral and spatial resolution after radiation calibration and atmospheric correction were first selected. Then, according to the high sensitivity of the Red Edge band to vegetation and the good correlation between the spectral data within the red edge and the parameters reflecting vegetation growth, the DEM model and the spectral difference between the red edge were adopted to remove the shadow of terrain and buildings effectively. Finally, the red-border spectrum-near-infrared spectrum is constructed based on the feature space within the visible band, and the red-border near-infrared vegetation Index model is constructed. At the same time, the urban vegetation extraction is compared and analyzed with NDVI and EVI. The analysis methods are qualitative and quantitative. The former is to extract vegetation images for visual analysis by using a real vegetation image reference map and model. The latter is a quantitative analysis using user accuracy, producer accuracy, overall accuracy and Kappa coefficient. The result of the qualitative experiment shows that the DEM model can effectively remove the shadow of buildings and terrain by combining with the different information of the red edge band between shadow and vegetation. After removing the shadows, NDVI and EVI were used to extract urban vegetation from the images, which made the buildings and road pixels confused in the vegetation, resulting in the problem of misclassification and omission. However, RENVI can effectively eliminate the confusion between shadow pixels and vegetation pixels, accurately extract urban vegetation, reduce redundancy, and increase vegetation index information. The quantitative experimental results show that the RENVI model can accurately extract urban vegetation compared with NDVI and RVI. The overall accuracy of the 3 images is 89%, 81.4% and 91.8% respectively, and the Kappa coefficient is 0.852 8, 0.791 3 and 0.905 2 respectively. In summer, this method can effectively improve the extraction precision of urban vegetation and obtain a better visual effect of extraction.
		2022 Vol. 42 (07): 2284-2289 [Abstract] ( 122 ) RICH HTML PDF (3791 KB) ( 145 )

	2290	Early Warning Method of Apple Spoilage Based on 2D Hyperspectral Information Representation With Pixel Mean and Variance
		WANG Zhi-hao, YIN Yong^*, YU Hui-chun, YUAN Yun-xia, XUE Shu-ning
		DOI: 10.3964/j.issn.1000-0593(2022)07-2290-07
		To effectively realize the early warning of apple spoilage during storage, a 2D hyperspectral information representation method based on the mean fusion variance of the hyperspectral image pixel grey value is proposed, and the early warning model of apple samples based on Bhattacharyya distance (BD) is constructed. Firstly, to obtain effective spectral information, the hyperspectral image’s region of interest (ROI) was selected. At the same time, through the comparative analysis of 6 kinds of original spectrum preprocessing methods, and the full-band (371.05～1 023.82 nm) spectral curves represented by the pixel mean and variance were smoothed Savitzky-Golary (SG) for noise reduction, respectively. Secondly, the successive projection algorithm (SPA) combined with the two physical and chemical indexes of sample hue angle and water loss rate was used to extract the feature wavelengths spectrum information, and 7 (pixel mean representation) and 8 (pixel variance representation) common feature wavelengths in the two representation methods were extracted. Then, by analyzing the change of the sample hue angle with the storage time, the storage data corresponding to the data point with a significant turning point was determined and combined with the actual observation during the storage period of the sample, the 21st storage day was preliminarily defined as the spoilage benchmark of apple samples. In addition, according to the characteristic absorption wavelength of the chlorophyll of the apple samples (675 nm or so), the average spectral reflectance change trend graph was drawn, and it was found that the changing trend rose to the highest point on the 21st day, which was consistent with the hue angle analysis result. It shows that the apple samples were indeed spoilt from the 21st day. Thus the spectral information of the 21st storage day corresponding to feature wavelengths can be used as the spectral feature vector of the spoilage benchmark day. Finally, the early warning models of Bhattacharyya distance spoilage based on the mean pixel representation, variance representation and the fusion of the two representation variables were established, respectively. The results show that the early warning models based on the spectral representation information of the pixel mean fusion variance have further reduced volatility compared with their respective early warning models and can better reflect the degree of spoilage of the apple samples during storage. Therefore, the spectral feature information fused with the mean and variance of pixel grey value can more comprehensively characterize the quality changes of apples during storage, and the robustness and generalization ability of the early warning model is strong. The research results provide a new idea for using hyperspectral image information to early warning apple storage spoilage.
		2022 Vol. 42 (07): 2290-2296 [Abstract] ( 105 ) RICH HTML PDF (3484 KB) ( 59 )

	2297	Multispectral Analysis of Interaction Between Catechins and Egg Yolk Immunoglobulin and the Change of Bacteriostasis
		ZHANG Meng-jun¹, LIU Li-li^1*, YANG Xie-li², GUO Jing-fang¹, WANG Hao-yang¹
		DOI: 10.3964/j.issn.1000-0593(2022)07-2297-07
		As a Cenozoic antibody, chicken egg yolk immunoglobulin (IgY) has the characteristics of safety, stability and no drug residue. It has an inhibitory effect on a variety of pathogenic microorganisms. IgY is one of the ideal substitutes for antibiotics. However, it cannot be used on an extensive scale application to a certain extent because of its high production cost and low antibacterial activity caused by protease decomposition. Therefore, it is of great significance to improve its economic benefit and bioavailability using modification. In this study, catechin interacted with IgY to prepare its complex. It provides support for improving the antibacterial properties of IgY and preparing safer and more efficient antibacterial agents. The interaction mechanism between catechin and IgY was studied via UV-Vis, FS and FT-IR. The antibacterial properties of the IgY-catechin complex were studied by using IgY and a mixture of IgY and catechin as control. With the increase of catechin concentration, the UV-Vis absorption peak value of IgY gradually increased and showed a blue shift. The quenching type of IgY by catechins is mainly static quenching. The IgY and catechin combine to form a complex with a number of binding sites close to 1. The interaction types were van der Waals force and hydrogen bond. Compared with IgY, the content of β-folded and β-corner in the secondary structure of the IgY-catechin complex had no significant change, while the content of α-helix was increased and irregular convolution was decreased. It indicated that the conformation of protein was changed due to the introduction of catechin. Compared with IgY and a mixture of IgY and catechin, the antibacterial rate of IgY-catechin complex against Staphylococcus aureus was increased by 135.8% and 9.95% on average, respectively. When the concentration was greater than 0.05 mg·mL^-1, the antibacterial rate against Escherichia coli was increased by 15.74% and 13.27%, respectively. Catechins and IgY could form a complex, which showed better antibacterial properties than IgY and mixture of IgY and catechin. This study is helpful in understanding the effects of catechins on the structure and function of IgY. It can also provide theoretical support for preparing safer and more efficient antibiotic substitutes. In addition, this study can supply theoretical guidance for the property changes of IgY during food processing.
		2022 Vol. 42 (07): 2297-2303 [Abstract] ( 137 ) RICH HTML PDF (2277 KB) ( 151 )

	2304	Molecular Characterization of Phosphorus in Typical Crop Residues
		XIN Hong-juan¹, YANG Dong-ling¹, HAN Chao-qun¹, GU Xue-qi¹, YANG Jian-jun², LIU Jin^1*, CHEN Yuan-quan¹, SUI Peng¹
		DOI: 10.3964/j.issn.1000-0593(2022)07-2304-05
		The returning of crop residues to agricultural soils are of great significance to the development of Green Agriculture and soil fertility improvement. In China, there are various types of crop residues with high abundance. It is essential to characterize phosphorus (P) speciation in typical crop residues to predict the crop availability after returning them to the agricultural fields. To date, liquid-phase phosphorus-31 nuclear magnetic resonance (³¹P-NMR) spectroscopy is a state-of-the-art technique for characterizing P species at the molecular level. However, there were limited investigations on the characterization of P speciation in crop residuals by ³¹P-NMR spectroscopy. Moreover, spectral peaks of different P forms, generally assigned based on the published literature, were significantly affected by sample properties (i.e pH), which resulted in large uncertainty and limited P forms to be identified. Therefore, with spiking experiments, this study used ³¹P-NMR spectroscopy to characterize molecular P species in different parts (straw, chaff and seed) of the typical crops, including corn, wheat, rice, cotton, soybean and peanut. The results showed that the total P content in all investigated crop residues was seed > chaff > straw. NaOH-EDTA extractable P ranged from 73% to 139% of total P, with an average value of 105%. Based on the spiking experiments, inorganic P forms (orthophosphate, pyrophosphate, tripolyphosphate) and organic P forms (phytate, α and β-glycerophosphate, adenosine monophosphate) were detected in the investigated samples. Additionally, as one type of orthophosphate diesters, deoxyribonucleic acid was first detected in this study. In all investigated straw and chaff samples, the major P species were orthophosphates, comprising 49.3%~71.6% of the NaOH-EDTA extracted P, while P in the seeds was mainly phytate (48.5%~82.9%). With correction for diester degradation, orthophosphate diester (17.1%~33.5%) was more than orthophosphate monoester (9%~13.5%) in crop straw samples. In contrast, the orthophosphate monoester and orthophosphate diester percentages in chaff samples were 8.8%~23.2% and 8.8%~24.6% respectively, and orthophosphate monoester was the main component in seed samples (57.6%~82.9%). It showed that the investigated crop residues, especially straw, probably release orthophosphate and orthophosphate diesters as labile P forms for subsequent crop uptake after returning to the soil. These results provide a significant scientific basis for crop residue returning and P fertilization management in agricultural lands.
		2022 Vol. 42 (07): 2304-2308 [Abstract] ( 101 ) RICH HTML PDF (1323 KB) ( 33 )

	2309	Study on Heavy Metal in Soil by Portable X-Ray Fluorescence Spectrometry Based on Matrix Effect Correction and Correspondence Analysis
		GUO Jin-ke, LU Ji-long, SI Jun-shi, ZHAO Wei, LIU Yang, WANG Tian-xin, LAI Ya-wen^*
		DOI: 10.3964/j.issn.1000-0593(2022)07-2309-06
		With the deepening of industrialization and urbanization, urban soil heavy metal pollution is becoming more and more serious. At the same time, traditional laboratory chemical analysis methods such as inductively coupled plasma mass spectroscopy have long analysis cycles and are prone to secondary pollution of the environment by experimental waste reagents. Portable X-ray fluorescence spectrometry is a testing method that can be used for rapid and non-destructive analysis directly in the field, and matrix effect is the most important factor affecting the testing accuracy and precision. The more commonly used calibration method is the traditional linear regression method, which is influenced by outlying values and still has large deviations in the processed data. The study attenuated the matrix effects during testing by adding the data of the major elements to the correction equation of the elements to be tested. In this study, heavy metals of Cr, Ni, Cu, Zn and Pb in soil samples from each campus of Jilin University was rapidly tested by portable X-ray fluorescence spectrometry under in situ to investigate the major elements that had the greatest influence on the matrix effect of each heavy metal element. The original Sherman equation was adjusted by combining the partial least-square method and the multiple linear regression method, and the new equation was used to correct for the matrix effect of each heavy metal element under the data of inductively coupled plasma mass spectrometry a reference. The differences between the data processed by this method and the traditional linear regression method were compared by statistical parameters, and the correlation between elements and samples was also analyzed by correspondence analysis. The results show that the major elements are the important factor affected by the matrix effect, and the matrix effect correction equation based on different major elements is effective, with applicability Cr>Pb>Zn>Ni>Cu. The quality of the corrected data was significantly improved, the coefficient of determination increased, the regression images were concentrated, the mean absolute error and root mean square error was further reduced. The correction effect was better than the traditional linear regression method. The matrix effect correction method mainly reduces the overall average error and discrete degree of the data by reducing the deviation of outlying values. The processed data meet the quantitative analysis requirements and can be extended to portable X-ray fluorescence spectrometry for rapid large area testing of heavy metals to detect environmental quality. At the same time, correspondence analysis is an analysis method between multi-dimensional data dimensions and multi-dimensional data dimensions. It has excellent results for classification and correlation analysis between multiple variables.
		2022 Vol. 42 (07): 2309-2314 [Abstract] ( 120 ) RICH HTML PDF (1945 KB) ( 79 )

	2315	Spatio-Temporal Analysis of Land Subsidence in Beijing Plain Based on InSAR and PCA
		HE Xu^{1, 2, 3}, HE Yi^{1, 2, 3*}, ZHANG Li-feng^{1, 2, 3}, CHEN Yi^{1, 2, 3}, PU Hong-yu^{1, 2, 3}, CHEN Bao-shan^{1, 2, 3}
		DOI: 10.3964/j.issn.1000-0593(2022)07-2315-10
		Since the 1970s, uneven ground subsidence caused by groundwater overdraft and uneven thickness of compressible layers has gradually developed into one of the most serious geological hazards in Beijing Plain. There are few research reports on the temporal and spatial analysis of land subsidence in the latest period in Beijing Plain. Therefore, this paper used SBAS-InSAR technology to obtain the ground deformation data of the Beijing Plain from May 2017 to May 2020 based on 39 Sentinel-1A spectral images acquired by active microwaves. The principal component analysis method was used to analyse land subsidence’s temporal and spatial characteristics in the Beijing Plain. In the SBAS-InSAR technology processing, the time baseline was set to 120 days, and the threshold of the space baseline was set to 45% of the maximum normal baseline, and 154 interference pairs were generated, and then all interference pairs were registered and interfered. After the interference, the results were flattened, Goldstein flattening for filtering, generated coherence coefficient and used minimum cost flow algorithm for phase unwrapping. The 73 high-quality interference pairs were screened for orbit refinement and re-leveling to estimate and remove the residual phase. The atmospheric phase was removed through temporal high-pass filtering and spatial low-pass filtering. Finally, the least-squares method and singular value decomposition were used to obtain land subsidence data of the Beijing Plain from May 2017 to May 2020. During the monitoring period, the maximum average deformation rate was -114.9 mm·yr^-1, and the maximum cumulative subsidence was 345.9 mm. which was located in Chaoyang Jinzhan. Compared with 2018, the ranges where the settlement rate of the central plain decreased by exceeding 50 mm·yr^-1 in 2019 in the Haidian District, Changping district, but the settlement rate range of Daxing District was gradually increasing. It analysed the land subsidence of the Beijing Plain by using the principal component analysis method. It was concluded that the first three principal components explained 99.11% of the data characteristics. The first principal component explained 96.48% of the characteristics, reflecting the long-term and unrecoverable process of groundwater subsidence caused by long-term groundwater extraction. However, the replenishment of groundwater by the South Water entering Beijing slowed down the settlement rate in the central plain. The second principal component explained the 2.11% feature, highlighting the interannual settlement process, which was related to factors such as the thickness of the compressible layer and the type of land use; The third principal component explained 0.52% of the characteristics of the data set and emphasized the seasonal elastic deformation regulated by rainfall. The research results of this paper can provide a certain scientific basis for the comprehensive management of land subsidence in the Beijing Plain.
		2022 Vol. 42 (07): 2315-2324 [Abstract] ( 146 ) RICH HTML PDF (13513 KB) ( 94 )

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