SPECTROSCOPY AND SPECTRAL ANALYSIS

News

Forgot your password?

Enter your e-mail address to receive an e-mail with your account information.

Journal Online

Archive

Links

	CAST

	CNCOS

	CNKI

	WanfangDATA

	CHEMSOC

	sinospectroscopy

	CPS

Quick Search

Adv Search

2020 Vol. 40, No. 02 Published: 2020-02-12

	333	Research Progress of On-Chip Spectrometer Based on the Silicon Photonics Platform
		WANG Wei-ping^1*, JIN Li²
		DOI: 10.3964/j.issn.1000-0593(2020)02-0333-10
		Optical spectrometers have become an indispensable tool in various fields that involve optical spectrum analysis. Its application ranges in many areas, such as biochemical sensing, food and drug testing, medical treatment and environmental monitoring. The application of traditional spectrometers is greatly limited due to the size, high power consumption and price, difficult secondary development. With the development of micro processing, miniaturized spectrometers have been developed. Compared to the traditional spectrometers, miniaturized spectrometers have the advantages of low cost, small volume, low power consumption and easy secondary development, which expands the application. However, miniaturized spectrometer, which is usually based on discrete optical components, doesn’t have high integration and flexibility. As the requirement of portability becomes higher and higher, further miniaturization and integration has become a trend of spectrometer. On-chip spectrometers, with apparent Size, Weight, and Power (SWaP) advantages, have unprecedented impact on applications ranging from unmanned devices to intelligent platform. Among the methods to realize on-chip spectrometers, silicon photonics offers an approach to realize an integrated and cheap spectroscopic system because of its mature processing and integration. During the last few years, on-chip spectrometers have become an enormously active area, resulting in significant progress. In this review, it summarizes the principle of the silicon based on-chip spectrometer, and introduces the developments of the dispersive spectrometers including spectrometers based on the etch diffraction grating, arrayed waveguide grating and multimode waveguides, and Fourier transform spectrometers including spatial heterodyne, stationary wave, thermos-optic, digital and MEMS Fourier transform spectrometers. We analyze the characteristics and applications of these spectrometers. Our research has also been demonstrated. By combining the mach-zehnder interferometer spectrometer and the arrayed waveguide grating spectrometer, the large spectral range and high resolution have been simultaneously achieved. At the end, we also discuss the future challenges and prospects in this field, which can give some reference for the research of on-chip spectrometers.
		2020 Vol. 40 (02): 333-342 [Abstract] ( 471 ) RICH HTML PDF (5482 KB) ( 288 )

	343	Research Progress for In-Flight Calibration of the Large View Polarized Multispectral Camera
		CHEN Xing-feng^{1, 2}, LIU Li^3*, GE Shu-le³, LI Xin⁴, ZHANG Kai-nan², YANG Ben-yong⁴
		DOI: 10.3964/j.issn.1000-0593(2020)02-0343-07
		The large view, polarized and multispectral camera detects the angular and polarized two more dimensional information than a traditional optical multi-spectral camera, and has great advances especially in aerosol remote sensing. So, near the year of 2020, a number of satellites loading multi-angle and polarized camera would be launched in different countries. As a high quantitative sensor, its in-flight calibration has always been attractive. Due to the lack of onboard calibration instrument and the low spatial resolution, the natural scenery targets are selected to be vicarious optic references for the calibration. Multi-angel polarized camera has several parameters to be calibrated. The radiometric calibration of polarized camera includes intensity and polarization parameters. Different calibration parameters are calibrated using many natural targets by many methods which are developed in parallel. The Gaofen-5 launched in 2018 is the first satellite loading polarized sensor of China, also the only operational satellite in the world this time. In view of many new polarized camera aerospace plans in European and American countries and China, the vicarious calibration for polarized camera is necessary to overview. In this paper, the optical structure and the spectral settings of the large view, polarized and multispectral camera are presented. The optical transfer model of camera is introduced. The in-flight calibration theory and method of each camera parameter is classified into three categories including absolute radiometric intensity, relative radiometric intensity and polarization. For a specified calibration coefficient, the natural target and calibration flow are introduced for the in-flight calibration. The method system is formed for the in-flight radiometric calibration of the large view, polarized and multispectral camera. Also, the general validation methods of calibration are concluded. The in-flight calibration of the new large view, polarized and multispectral camera will inherit the original research and use special natural scenery to carry out calibration. In the same kind of future remote sensing camera, new style in-flight radiometric calibration will be based on the instruments and its calibrator onboard the same satellite platform, ground-based artificial optical source and others. China, Europe and America have planned some future polarized camera, jointly considering the research basis of authors, preliminary design and prospects for the future on-orbit calibration method are given. A polarized multispectral camera mainly serves the remote sensing monitoring of atmospheric particulate matter, which is very important for the atmospheric environment problems currently concerned in China. A continuous in-flight calibration can ensure the accuracy of satellite remote sensing retrieved products. This overview of in-flight calibration research and the preliminary design for the future calibration method will provide method and model references for the remote sensing application system of the planned satellite.
		2020 Vol. 40 (02): 343-349 [Abstract] ( 236 ) RICH HTML PDF (1602 KB) ( 108 )

	350	Application of Spectral Imaging Technology for Detecting Crop Disease Information: A Review
		BAI Xue-bing, YU Jian-shu, FU Ze-tian, ZHANG Ling-xian, LI Xin-xing^*
		DOI: 10.3964/j.issn.1000-0593(2020)02-0350-06
		As one of the major factors hindering crops growth, crop diseases make more than 12% loss of crop yield annually. Diseases not only directly reduce crop yields, but also seriously debase the quality of agricultural products, and even cause food safety accidents. Spectral imaging technique is aninformation foraging approach that fuses image processing and spectroscopy. It couldobtain image and spectral information of crop diseases simultaneously and describediseased spots feature intuitively. Spectral imaging technology improves the accuracy and efficiency of crop disease detection because of the advantage of union of imagery and spectrum and has been a hotspot at present research. This paper reviews the related literatures in recent six years, and analyses the advantages and limitations of spectral imaging technology in crop disease detection and focuses on the third key technology of spectral imaging in crop disease detection. The third key technology of spectral imaging in crop disease detection is emphasized: (1) Spectral image segmentation technology, focusing on the advantages and application scope analysis of four common segmentation algorithms; (2) spectral feature and spatial feature extraction technology, focusing on the accuracy comparison of spatial features, spectral features and their weighted combination of disease information expression; (3) detection model, focusing on the stability and prospects of spectral vegetation index and machine learning model in crop disease detection. Finally, this paper prospects the application prospect and research trend of spectral imaging technology in the field of crop disease detection, and provides a comprehensive and systematic reference for related research.
		2020 Vol. 40 (02): 350-355 [Abstract] ( 271 ) RICH HTML PDF (821 KB) ( 215 )

	356	In-Situ Non-Invasive FTIR Analysis of Conservation Materials on the Surface of Mural Paintings in Prince Shi’s Palace of the Taiping Heavenly Kingdom
		WANG Zhuo^{1, 2}, SU Bo-min^{1, 2*}, YU Zong-ren^{1, 2}, SHUI Bi-wen^{1, 2}, ZHAO Jin-li^{1, 2}, CUI Qiang^{1, 2}, SHAN Zhong-wei^{1, 2}, LI Qian³
		DOI: 10.3964/j.issn.1000-0593(2020)02-0356-06
		The murals in Prince Shi’s Palace of the Taiping Heavenly Kingdom are the typical examples of the murals in southern China, which have important historical, cultural and artistic values. In history, chemical conservation was carried out on many murals, and part of the murals formed a certain thickness of organic coating on the surface. It is of great theoretical and practical significance to analyze and study the compositions of mural conservation materials for the protection of cultural relics. Due to the rarity and non-renewability of cultural relics, the research and application of in-situ non-invasive analytical technique will be the trend in the future. Reflection infrared spectroscopy based on portable infrared spectrometer is an ideal method for non-invasive analysis of surface materials of cultural relics. In this paper, reflection Fourier transform infrared （FTIR） spectroscopy was used to analyze ground layer and conservation materials of murals in Prince Shi’s Palace, and it is the first time that this method was applied to the analysis of ancient Chinese murals and their conservation materials. In this study, the reflection FTIR spectrum of uncoated mural’s white background was measured at first, and the compositions of ground layer were identified as calcite and gypsum by comparison with standard inorganic minerals by reflection FTIR spectra. On this basis, the infrared reflection features of uncoated and coated mural surfaces and the influence of ground layer on surface coatings were analyzed. The feasibility and applied range of using Kramers-Kronig （K-K） transform as a data processing method were discussed. The differences between K-K-transformed reflection spectra and attenuated total reflection （ATR） spectra of mural coatings were analyzed. The reliability of in-situ reflection FTIR spectroscopy was verified by microscopic ATR FTIR spectroscopy and pyrolysis-gas chromatography/mass spectrometry（Py-GC/MS）. The thicknesses of coatings were measured by scanning electron microscopy（SEM）, demonstrating that high-quality reflection FTIR spectra can be obtained for different thicknesses. Finally, it was confirmed that the murals in Prince Shi’s Palace were strengthened with three kinds of polymers: polyvinyl acetate, polydimethylsiloxane and acrylic resin, and it was concluded that the current preservation situations of murals are closely related to conservation materials and coating thicknesses. The above research proves that the information of organic compounds and some inorganic substances on the surface of cultural relics can be effectively obtained by reflection FTIR spectroscopy. This method is particularly sensitive to organic coatings on the surface, making it an ideal non-invasive analytical method for cultural relics of mural paintings, and it has a very broad application prospect in the field of mural conservation research. Meanwhile, this study makes up for the deficiency of in-situ non-invasive analysis of organic compounds on the surface of Chinese murals, and provides a new idea for the research in this field.
		2020 Vol. 40 (02): 356-361 [Abstract] ( 218 ) RICH HTML PDF (2653 KB) ( 129 )

	362	Luminescence Enhancement of Erbium Doped Bismuth Glass by Silver Surface Plasmon
		CHEN Xiao-bo¹, LI Song¹, ZHAO Guo-ying², LONG Jiang-mi¹, GUO Jing-hua¹, MENG Shao-hua², ZHENG Dong¹, WANG Shui-feng¹, YOU Jia-jia¹, XU Ling-zhi², YU Chun-lei³, HU Li-li³
		DOI: 10.3964/j.issn.1000-0593(2020)02-0362-06
		The localized surface plasmon can be directly excited by light in free space. This is also the advantage of local surface plasmon. So, it is very meaningful for us to study enhancement effect of erbium ion luminescence by surface plasmon of silver nanoparticles in bismuth luminescent glass, to further improve the luminescent properties of erbium ions. First, this paper measured the absorption spectra of (A) Er³⁺(0.5%)Ag(0.5%): BiSiGa glass and (B) Er³⁺(0.5%): BiSiGa glass sample. It was discovered that there is a weak broad resonance absorption peak of silver surface plasmon in the position of about 600 nm for (A) Er³⁺(0.5%)Ag(0.5%): BiSiGa glass. It was also found that both have typical absorption peaks of erbium ions. Their absorptions were almost exactly the same. They were similar in peak shape, peak intensity and peak wavelength. Second, we measured the excitation spectra of (A) Er³⁺(0.5%)Ag(0.5%): BiSiGa glass and (B) Er³⁺(0.5%): BiSiGa glass sample. Five visible excitation peaks, in the positions of 379.0, 406.0, 451.0, 488.0 and 520.5 nm respectively, have been found when monitored in 550.0 nm visible light. Same, eight infrared excitation peaks, in the positions of 379.0, 406.5, 451.0, 488.5, 520.5, 544.0, 651.5 and 798.0 nm respectively, have also been found when monitored in 1 531.0 nm infrared light. It was easy to identify them as the absorption peaks of ⁴I_15/2→⁴G_11/2, ⁴I_15/2→²H_9/2, ⁴I_15/2→(⁴F_3/2, ⁴F_5/2), ⁴I_15/2→⁴F_7/2, ⁴I_15/2→²H_11/2, ⁴I_15/2→⁴S_3/2, ⁴I_15/2→⁴F_9/2, and ⁴I_15/2→⁴I_9/2 of Er³⁺ ions in turn. It is discovered by measurement that the maximum enhancement of visible and infrared excitation spectra was 238% and 133% respectively for (A) Er³⁺(0.5%)Ag(0.5%): BiSiGa glass relative to (B) Er³⁺(0.5%): BiSiGa glass. Finally we measured the luminescence spectra. Three sets of visible emission peaks at 534.0, 547.5 and 658.5 nm were found. It was easy to identify them as fluorescent transitions of ²H_11/2→⁴I_15/2, ⁴S_3/2→⁴I_15/2 and ⁴F_9/2→⁴I_15/2 of Er³⁺ ions in turn. It was also found that the infrared emission peaks were at 978.0 and 1 531.0 nm. They were fluorescence transitions of ⁴I_11/2→⁴I_15/2 and ⁴I_13/2→⁴I_15/2 of Er³⁺ ions in turn. It was discovered by measurement that the maximum enhancement of visible and infrared luminescence spectra was 215% and 138% respectively for (A) Er³⁺(0.5%)Ag(0.5%): BiSiGa glass relative to (B) Er³⁺(0.5%): BiSiGa glass. For the mechanism of erbium ion emission enhanced by silver surface plasmon, we think it is mainly that local surface plasmon resonance of silver nanoparticles causes the fact that the local electric field intensity generated near the metal nanostructure is much stronger than the electric field intensity of the incident light. This leads to metal nanostructures generating extremely strong absorption and scattering for incident light. This leads to enhance fluorescence. This is just the field enhancement effect of the local field of local surface plasmon resonance.
		2020 Vol. 40 (02): 362-367 [Abstract] ( 195 ) RICH HTML PDF (2382 KB) ( 69 )

	368	Effect of Current Blocking Layer on Photoelectric Properties and Thermal Characteristics of High Power LEDs
		YANG Xin, GUO Wei-ling^*, WANG Jia-lu, DENG Jie, TAI Jian-peng, SUN Jie
		DOI: 10.3964/j.issn.1000-0593(2020)02-0368-05
		As the core of LED light source, the quality of LED chip directly determines the performance, life and so on of the device. Therefore, the improvement of optical extraction efficiency is the key step to promote the development of LED chip technology when the internal quantum efficiency has reached a fairly high level. Due to the insulating property of sapphire, the N and P electrodes of normal LED are made on the same side of the light output surface of the chip. The P metal electrode on the light output surface absorbs most of the light emitted from the luminous region directly below it, and causes light loss. To improve this phenomenon and alleviate the current crowding around the P electrode, in this paper, we fabricated LED devices with SiO₂ current blocking layer（CBL）that was deposited between ITO transparent conductive layer and P-GaN,and another kind of LED without CBL. We tested voltage，light output power，main wavelength of the two kinds of chips without package under 350mA working current. The results showed that the forward voltage of the two kinds of chips are concentrated in 3~3.1V, while the light output power of the LED with CBL is obviously improved. CBL blocks the current from diffusing below the P electrode and reduces the current density flowing to the active region, thus reducing the absorption and shielding of light by the P electrode, and directing the current to the region far away from the P electrode through CBL, reducing current congestion around the electrode. Then the two kinds of chips were packaged in the same package structure and process conditions. The thermal characteristics and photoelectric properties of two samples were investigated under different current range from 10 to 600 mA, and the spectra and optical power of two kinds of devices were obtained. Results showed that main wavelength of the two samples blue shift with the increasing current, and the main wavelength blue-shifting of LED with CBL is 10nm less than the LED without CBL. It can be seen that the spectra of LED inserted CBL is less affected by the increasing current. Therefore, its color rendering properties is more stable. Under the low current, CBL structure has little effect on the optical power of the device. With the increase of current, the improvement effect of CBL on the optical power is improved gradually. Under the heavy current, the junction temperature of the LED without CBL is higher and the forward voltage is lower, and the voltage difference between the two kinds of devices increases with the increasing current. Under 25℃ ambient temperature, 350 mA working current, the voltage of LED with CBL increases 0.04 V, but it improves optical power, the highest increase is 9.96%, and the thermal resistance is obviously smaller than the device without CBL structure, which indicates that the heat production of LED with CBL is less than the device without CBL structure. Therefore, the optical extraction efficiency of the device is improved by CBL structure. And the spectrum drifting is smaller and the color rendering properties is more stable.
		2020 Vol. 40 (02): 368-372 [Abstract] ( 255 ) RICH HTML PDF (3409 KB) ( 61 )

	373	Preparation and Optical Properties of Near Infrared Persistentluminescent CaGdAlO₄∶Cr³⁺
		ZHANG Nan, LIU Chun-guang^*, ZHANG Meng, YANG Jian, LI Sheng-nan, ZHU Han-cheng, YAN Duan-ting, XU Chang-shan, LIU Yu-xue
		DOI: 10.3964/j.issn.1000-0593(2020)02-0373-06
		At present, for near infrared (NIR) long afterglow materials doped with Cr³⁺, the efforts have been focused on the dependence of luminescent centers in the cases of strong and medium crystal fields on the afterglow properties (emission wavelength, afterglow time and storage properties), but the research on the relationship between Cr³⁺ ions around weak crystal field environments and the afterglow properties is lacking. This studyis very essential for developing novel long afterglow luminescent materials and exploring their applications. In this paper, Cr³⁺ doped CaGdAlO₄ (CaGdAlO₄∶x%Cr³⁺) powders with different Cr³⁺ doping concentrations were prepared by a self-propagating combustion method. The influences of Cr³⁺ doping and heat-treatment conditions on the microstructure, morphology, particle size and luminescent properties of the samples were studied by means of X-ray diffraction, scanning electron microscopy, excitation and emission spectra. It was found that, in the concentration range of 0.1%～2.0%, Cr³⁺ions substitute for Al³⁺ions in CaGdAlO₄ because of their similar radii. From the excitation spectra, it could be found that the excitation peaks at 240, 373 and 592 nm are attributed to ⁴A₂→⁴T₁(4P), ⁴A₂→⁴T₁(4F) and ⁴A₂→⁴T₂(4F) transitions of Cr³⁺ ions, respectively, and the excitation peaks corresponding to 276 and 313 nm originate from the ⁸S_2/7→⁶I_j and ⁶P_2/7→⁸S_2/7 transitions of Gd³⁺ ionsin the matrix. Under 592 nm excitation, NIR broadband emission peak with a maximum value of 744 nm appears in the range of 650～850 nm and several narrowband peaks overlap with it. The NIR emission intensity exhibits an initialrise and a subsequent decrease with the increase of Cr³⁺ doping concentration and the optimum doping concentration is ~1%. After the heat-treatment at 800 ℃ in vacuum, the average grain size increases from 417 to 843 nm and the luminescent intensity increases by 2 times. It was found that Cr³⁺ replaces Al³⁺ site in the weak crystal field environment in CaGdAlO₄ host. The origin of NIR emission peaksof the samples was identified by the calculation of crystal field parameters and spectral analysis. It was found that the crystal field strength is ~1.54 and smaller than 2.3, i. e. Dq/B=1.54<2.3, indicating Cr³⁺ ions around a weak crystal field environment, which is consistent with the experimental result. The 670 nm broadband emission can be attributed to the zero phonon line (⁴T₂→⁴A₂) and 744 and 756 nm broadband emissions correspond to the phonon sideband transition ⁴T₂→⁴A₂. After the heat treatment, the afterglow time of the samples exceeds 60 seconds. In particular, compared with the case of Cr³⁺ ions around medium and strong crystal field environments (the maximum value of NIR emission peak at 697 nm), the maximum value of NIR emission peak of Cr³⁺ ions around the weak crystal field environment moves to 744 nm, which is closer to the center of the first biological window, suggesting that Cr³⁺ doped CaGdAlO₄ has potential application in bioimaging.
		2020 Vol. 40 (02): 373-378 [Abstract] ( 192 ) RICH HTML PDF (3867 KB) ( 188 )

	379	Research on the Spectral Analysis and Stability of Ultraviolet-Enhanced Thin Films with Stable and Tunable Graphene Oxide-Rare Earth Complexes
		LI Zhi-yuan¹, LIU Xue-lian^1,2, ZHENG An-dong¹, WANG Guo-dong¹, XIA Guo^1,3, LU Hong-bo^1,2*
		DOI: 10.3964/j.issn.1000-0593(2020)02-0379-06
		As a new two-dimensional sheet material, graphene oxide sheets (GOSs) offers many advantages, such as high specific surface area, abundant surface oxygen-containing functional groups and good photothermal stability. In particular, rare earth complexes formed with GOSs exhibit excellent fluorescent characteristics from the combination of the inorganic rare earth element and the organic ligand. In order to combine the physicochemical properties of the two types of materials for applications in the field of ultraviolet (UV) spectroscopy, GOSs was compounded with rare earth complexes through means of hydrogen bond self-assembly, with appropriate organic ligands, namely phenanthroline (phen) and 2’2-bipyrimidine (bpm), being used as bridging molecules. This method was used to prepare the highly stable and tunable GOSs-rare earth complex fluorescent materials GOSs-Eu(BA)₃phen and GOSs-Eu(TTA)₃bpm. A corresponding poly vinyl alcohol (PVA) mixed UV enhanced film was also prepared for each GOSs-rare earth complex, respectively. The properties of the materials were studied using infrared (IR) spectroscopy, scanning electron microscopy (SEM), and metallographic microscopy. The films were also characterized by their absorption and fluorescence spectra. In addition, the thermal stability of the UV-enhanced materials was tested using thermogravimetric analysis (TGA), and the photostability of the UV-enhanced film before and after reacting with the hydrogen bonds of the GOSs was tested using fluorescence intensity experiments. IR spectroscopy results showed that the characteristic absorption peaks of the organic ligands shifted after the complex formation, indicating that there is significant coordination between Eu³⁺ and the ligands in the rare earth complex. In addition, the characteristic chemical shift peaks of the bridging ligands also shifted, showing that the GOSs and the rare earth complexes were combined through hydrogen bonding of the bridging molecules. The absorption and fluorescence spectra results indicated that the absorption peak of the enhanced film was in the range of 200～400 nm, and that the main fluorescence peak was at about 612 nm, which is the characteristic red fluorescent peak of Eu³⁺. Different ligands achieved different absorption ranges, thus leading to differences in fluorescence behavior. The pictures from SEM and metallographic microscopy clearly showed that the rare earth complex particles adhered to the graphene sheet after the compositing process. The photostability test further showed that, following the compositing process, the photobleaching degree of Eu(BA)₃phen and Eu(TAA)₃bpm rare earth complex fluorescent materials decreased by 4.26% and 6.41% respectively, after 25 fluorescence intensity tests. The TGA results showed that the thermal stability of the rare earth complexes was greatly improved after the formation of hydrogen bonds with GOSs. In summary, the prepared UV-enhanced materials were shown to exhibit excellent fluorescent characteristics and stability, and will have broad applications in UV detection, especially in the field of narrow-band differential detection.
		2020 Vol. 40 (02): 379-384 [Abstract] ( 224 ) RICH HTML PDF (3713 KB) ( 53 )

	385	3D Model Feature Extraction Based on Light Propagation Simulation with Monte Carlo Method
		LIU Hong-hao¹, LIU Xian-xi¹, ZHANG Kai-xing^1,2*, LU Shan¹, Lee Heow Pueh³, SONG Zheng-he⁴
		DOI: 10.3964/j.issn.1000-0593(2020)02-0385-06
		Three-dimensional model has been showing extensive demand and vitality in modern industrial design, artificial intelligence and software design fields. Traditional feature extraction methods merely depend on model surface feature, which could not sufficiently satisfy complex model feature extraction needs. In order to improve the accuracy of model feature extraction, a 3D model feature extraction method with high discrimination was proposed based on spectral analysis and light propagation attributes. Firstly, the probability of light transmission, scattering and reflection when light propagation in different medium was quantitatively analyzed with scattering coefficient, absorption coefficient and anisotropy parameters. Secondly, the Monte-Carlo method was used to simulate light propagation in complex 3D model, where different feature statistics including angle, distance and energy were obtained to complete feature extraction. Then, the influence factors of photon beam number and constrained space shape were tested for optimal parameters determination. Finally, the feature extraction effectiveness was evaluated on retrieval precision, recall and E-measure. The results showed that the feature extraction accuracy sensitively varied with constrained space shape and the optimal constrained space for photon propagation was sphere; The feature extraction efficiency decreased with more photon beams, and within basic accuracy requirement, 10 000 to 25 000 photon beams were the optimal simulation number; The feature extraction accuracy of proposed method was higher than the wavelet transform, distance-angle and D2 distribution methods, which is more suitable for offline feature extraction of complex 3D models. The proposed simulation method of feature extraction broadens spectral analysis application, which could extract the integrated feature between model surface and internal structure, promoting model feature extraction research.
		2020 Vol. 40 (02): 385-390 [Abstract] ( 179 ) RICH HTML PDF (3264 KB) ( 55 )

	391	Edible Oil Terahertz Spectral Feature Extraction Method Combining Radial Basis Function and KPCA
		WANG Zhuo-wei¹, LUO Jian-peng¹, LI Xue-shi^2*, CHENG Liang-lun²
		DOI: 10.3964/j.issn.1000-0593(2020)02-0391-06
		In order to deal with the case where the terahertz spectrums are linearly inseparable, this paper proposes a method combining the radial basis function and the kernel principal component analysis (KPCA) to extract the terahertz spectral features of edible oils. By using this method, the extracted inner-class distance of features is small, meanwhile the extracted inter-class distance is large. An accurate classification model can be established in most support vector machine classifiers. Terahertz spectroscopy is an important method to detect the type and quality of edible oils. The research on the feature extraction technology of terahertz spectroscopy is of great significance for the rapid detection of edible oil types and quality. Although there have been a theoretical basis on how to use the terahertz spectroscopy to detect the type and quality of edible oils, it is still difficult to accurately extract the terahertz spectral features of edible oils and establish an accurate classification mode accordingly. Recently, researchers often use principal component analysis (PCA) in the field of chemometrics to extract features and use machine learning algorithms to establish a material classification model. However, the linear separability of the terahertz spectrum of edible oils has different characteristics in different frequency bands. When the terahertz spectrums of edible oils are linearly separable, it is feasible to extract features using PCA, and thus establish an accurate classification model. However, when the terahertz spectrums of edible oils are linearly inseparable, the features extracted using PCA are often not accurate enough, and an appropriate classifier is demanded to establish an accurate classification model. The method combining the radial basis function and KPCA feature extraction can be described as follows: the linear space-inseparable terahertz spectral data are mapped to the radial basis space by the radial basis function, then the features are extracted by KPCA which become linearly separable. As a result, a more accurate classification model can be established. For the experiment, firstly the sliding window average filtering algorithm is used to filter the terahertz spectral data of three edible oils. Then, the radial basis function is employed to nonlinearly map the terahertz spectrum. After that, KPCA is utilized for data dimensionality reduction. Finally, the support vector machine (SVM) is used to establish a classification model for edible oils and the feature extraction effect is verified. The calculated results of inter-class separability show that the inner-class distance of features extracted by the method is smaller, and the inter-class distance is larger. Thus, the overall feature extraction effect presented in this paper is better than those of PCA and KPCA. The experimental results of classification verification show that based on certain classification models the features extracted by PCA and KPCA cannot distinguish the type of edible oils very accurately. However, based on every classification model the feature extraction method proposed in this paper can distinguish the type of edible oils accurately. The method proposed in this paper has a better effect on the extraction of terahertz spectral features of edible oils, which makes it of great value in the detection and analysis of the quality of edible oils.
		2020 Vol. 40 (02): 391-396 [Abstract] ( 206 ) RICH HTML PDF (2089 KB) ( 59 )

	397	Study of Terahertz Vibration Modes of Amino Acid Functional Groups
		YAN Fang, LI Wei^*, WANG Zhi-chun
		DOI: 10.3964/j.issn.1000-0593(2020)02-0397-06
		Compared with the infrared analysis of amino acids, terahertz wave has lower electronic energy and can be used for nondestructive testing. The intramolecular atomic vibration, the intermolecular hydrogen bond and the low-frequency vibration of the crystal lattice of amino acids are all in terahertz band, which makes them have absorption peaks in terahertz band, and different amino acid molecules have different Terahertz Absorption peaks. Therefore, this fingerprint characteristic of amino acids in terahertz band can be used for qualitative analysis of amino acids. Quantum chemical analysis methods can apply the basic principles and methods of quantum mechanics to study the structure, properties and relationships of stable and unstable molecules. It can also study the interactions, collisions and reactions between molecules. The Terahertz Absorption Spectra of amino acids can be calculated by quantum chemical calculation method, which can match the molecular vibration mode of the terahertz absorption peaks of amino acids. It has certain reference and directivity for the qualitative analysis of amino acids, and provides theoretical support for the terahertz time domain spectra of samples obtained from experiments. Quantum chemical calculation is carried out on the basis of the terahertz absorption spectra obtained from experiments. It can also validate the experimental results. In this paper, Terahertz Absorption Spectra of glutamine, threonine and histidine were obtained by terahertz time-domain spectroscopy. The monomolecular configurations of these three amino acids in the form of amphoteric ions were constructed respectively. The Terahertz Absorption spectra were simulated by quantum chemical calculation method after the structural optimization was completed. The calculated results showed that the Terahertz Absorption Spectra of three amino acids are quite different from those obtained by experiments, but the peak positions at high frequencies are basically the same. GaussView was used to observe the vibration and rotation of the absorption peaks of the three amino acids at the corresponding frequencies in the terahertz band. It was found that the functional groups of the three amino acids only rotated without vibration in the high frequency band, and the rotation modes were basically the same. The Terahertz Absorption Spectra of amino acid functional groups were calculated quantum chemistry. The vibration and rotation patterns of functional groups at the corresponding frequencies of the absorption peaks in the high frequency band were compared with those of three amino acid molecules at the corresponding frequencies of the absorption peaks in the high frequency band. The results showed that in the terahertz absorption spectra calculated by quantum chemistry method under the single molecular configuration of amino acids, the simulated absorption peaks calculated in the high frequency band are basically consistent with the experimental Terahertz Absorption peaks. Vibration mode analysis showed that the vibrational modes of amino acid functional groups of glutamine, threonine and histidine were the same in the terahertz high frequency band. The absorption peaks of the three amino acid molecules in the high frequency band mainly came from amino acid functional groups. Therefore, the qualitative analysis of amino acids can be realized by combining quantum chemical calculation with Terahertz Absorption spectrum.
		2020 Vol. 40 (02): 397-402 [Abstract] ( 279 ) RICH HTML PDF (2321 KB) ( 63 )

	403	Terahertz Spectral Interval Combination Feature Extraction Algorithm in the Case of Aliasing Absorption Peak
		HE Wei-jian, CHENG Liang-lun^*, DENG Guang-shui
		DOI: 10.3964/j.issn.1000-0593(2020)02-0403-07
		Terahertz spectrum is an advanced method for material recognition. Due to the different molecular organizations and structures of different substances, the terahertz absorption spectrum of many substances will have many absorption peaks at certain frequency, which can be used as important features of the mixture for component detection. Effective and accurate extraction of the parameters of these absorption peaks is the key to improving the recognition rate. The multi-peak fitting algorithm fits the spectral curve into the sum of several standard peak functions, which can extract the frequency, wave height and wave width of the absorption peaks at the same time. However, based on the results of the peak finding algorithm, fitting algorithm determines the approximate position and number of the absorption peaks before fitting. The peak finding result is not necessarily the optimal fitting result, and it is difficult to accurately identify the aliasing absorption peaks. In order to improve the recognition and positioning accuracy of the absorption peaks in the aliasing spectrum, this thesis proposes to divide the pre-processed spectrum into several sub-intervals by the wave troughs of sharp smoothed curve. Then the sub-intervals are combined for multi-peak fitting, and the optimal fitting sub-interval combination and the approximate value of the absorption peak frequency are obtained by genetic algorithm. The number of absorption peaks is determined by the peak number increment optimization method in each subinterval during fitting. In order to realize the identification of matter, the density clustering algorithm is used to obtain the common absorption peaks of the same kind of pure substance in multiple measurements. Using those peak data as the standard data, the proposed spectral matching algorithm based on the absorption peak characteristics enables rapid identification of pure substances and mixtures of different contents. The actual spectral data of ten kinds of pure substance are fitted and clustered to obtain parameters of absorption peaks, which are basically consistent with the terahertz spectral database. The recognition rate for identifying the test set of pure substances by the recognition algorithm of this thesis is 100%, which proves the effectiveness of the feature extraction algorithm and material recognition algorithm. For the spectrum of mixtures with aliasing peaks, the recognition rate of the second derivative method for the masked absorption peak (1.280 THz) in the glucose-lactose mixture spectrum is only 70%, and the extracted frequency average value is 1.316 THz; The algorithm in this thesis improves the recognition rate to 95% and the average frequency is 1.281 THz，that is to say, this method improves the resolution of the aliasing peak and can accurately locate the aliasing peak. The Top-2 and Top-3 accuracy of the six types of binary mixtures which have different degrees of aliasing and consist of 10 pure materials are 90.8% and 98.3%, respectively. The extracted features can be effectively applied to the component detection of the mixture. The algorithm in this thesis can realize the component detection of mixture by using the data of pure substances as the standard data, which is of great significance to the component detection of mixture in terahertz spectroscopy.
		2020 Vol. 40 (02): 403-409 [Abstract] ( 260 ) RICH HTML PDF (2194 KB) ( 74 )

	410	A Novel Interpolation Method for Raman Imaging
		XI Yang, LI Yue-e^*
		DOI: 10.3964/j.issn.1000-0593(2020)02-0410-05
		Raman detection technology, with many advantages, has now become the preferred choice in the field of biochemical detection. Raman imaging is an important optionforRaman detection because it providesrich information of the concentration, distribution and changes of a certain substance component in the detection area. Raman spectrum for imaging construction obtained through experiments usually contains a limited number of pixels and the imaging effect is poor, so it is urgent to interpolate it. However, for most popular image interpolation methodscurrently available for conventional image processing, classical interpolation function is selected for interpolation based on the values and distribution of known pixel points. However, for Raman imaging, the existing interpolation method for conventional images is not enough for high quality imaging and the distribution of information at each pixel point (i. e., acquisition point) needs to betaken into account. Because the Raman signal collected at each pixel is from an objective lens and the light intensity is Gaussian distribution, the relationship ofthe collected Raman scattering signal at each pixel and the spatial distribution is also Gaussian dependent. That is, the signal center (i. e., the acquisition center point) has the highest signal ratio, and the signal around the collection point is Gaussian dependent. This rule tells us that the Raman scattering signal collected at the collection point actually contains the signal of the surrounding points. Based on the special significance of Gaussian beam in Raman imaging, this paper theoretically analyzes and proposes a new interpolation method suitable for Raman imaging. After setting a specific acquisition interval to make sure that the acquisition area at the adjacent collection point is tangent, we use our function based on the information contained at the collection point for interpolation, which meets the interpolation requirement. Unlike the conventional interpolation method, we establish an appropriate relationship between the Gaussian beam and the acquired Raman signal so that the interpolation can also indirectly reflect the biological information of the collected area. By comparing the imaging before and after interpolation, it is found that the new interpolation method has a good amplification effect, and the amplification by this interpolation method can greatly save the acquisition time for imaging construction with similar resolution ratio and information, there by saving experimental resources. We take the interpolation and amplification twice as an example, and explain the interpolation method in detail. In reality, the corresponding interpolation amplification can be performed according to the specific requirements.
		2020 Vol. 40 (02): 410-414 [Abstract] ( 181 ) RICH HTML PDF (2744 KB) ( 73 )

	415	Study on the Influence of Pb Doping on High Pressure Structural Properties of Tin Dioxide Using Diamond Anvil Cell and Raman Spectra
		WANG Shi-xia, GAO Jin-jin
		DOI: 10.3964/j.issn.1000-0593(2020)02-0415-05
		Based on the stable molecular structure and physicochemical property, SnO₂ has been more and more useful in the field of optical, electrical and magnetic materials in recent years. In order to broaden the application of SnO₂, the research focused on the phase transition behavior of pure SnO₂ and SnO₂ doped by lead ions under high pressure, and the changes of Raman spectrum active vibration modes were investigated at the same time. The pure SnO₂ and SnO₂ doped by lead ions with 10% content were prepared by hydrothermal method. And the Scanning Electron Microscopy (SEM) images and X-ray diffraction (XRD) patterns of samples were measured. SEM images showed that samples were arranged as divergent nanorods which from the center to form a whole flower-like shape. XRD patterns showed that the crystal structure of samples was rutile tin dioxide (space group is P₄₂) at room temperature and pressure. In this paper, the high pressure phase transition processes of materials rutile tin dioxide and SnO₂ doped by lead ions with 10% content were investigated by using Mao-Bell Diamond anvil cell and in situ Raman spectroscopy. The results showed the active Raman modes (B_1g, E_g, A_2g, B_2g) of pure SnO₂ and SnO₂ doped by lead ions all moved to high frequencies when the pressure was added to 26 GPa. The E_g peak of pure SnO₂ split and a new peak appeared in 563 cm^-1 when the pressure was added to 14GPa, which indicated that SnO₂ transformed from tetragonal rutile structure to CaCl₂ structure. The Raman peak of 577 cm^-1 happened in the sample SnO₂ doped by lead ions in room pressure, and the vibration mode of B_1g changed to Ag mode when the pressure was addeda to 13 GPa which indicated the first-order phase transition of SnO₂ doped by lead ions. Compared to pure SnO₂, SnO₂ doped by lead ions had a lower first-order phase transition pressure, which were attributed to the fact that lead ions replace tin ions in SnO₂ cells. The spacing between atoms decreased and surface defects of valence difference happened after doping, which caused the decrease of structural stability of SnO₂ and the decrease of phase transition pressure. In addition, the characteristic peaks at 577 and 639 cm^-1 of SnO₂ doped by lead ions began to coalesce into cladding peaks and its symmetry decreased when the pressure was added to 12 GPa, which indicated that the disorder degree of atoms on the surface of crystals increased and transition process from crystals to amorphous crystals occurred. The characteristic peaks of the two materials disappeared when the pressure reached to 26 GPa, and no other characteristic peaks were observed. Non-hydrostatic pressure in this research had a certain effect on the phase transformation pressure. The large stress at the grain boundary made nanocrystals form to nucleation point of high-pressure phases more easily, which might reduce the phase transformation pressure and cause some crystals tend to be amorphous more easily. In summary, the phase transition behavior of pure SnO₂ and SnO₂ doped by lead ions on different pressure conditions were studied, which enriched the diversity of physical and chemical properties of SnO₂ under extreme conditions.
		2020 Vol. 40 (02): 415-419 [Abstract] ( 203 ) RICH HTML PDF (2170 KB) ( 48 )

	420	Preparation and Surface Enhanced Raman Spectroscopy of Au/TiN Composite Films
		WU Zhen-gang¹, LIU Yan-mei¹, WU Ming-ming^2,4, CHEN Ying³, WEI Ying-na^2,4, XIAN Hao-han¹, WANG Xue-pei^2,4, WEI Heng-yong^2,4*
		DOI: 10.3964/j.issn.1000-0593(2020)02-0420-07
		Surface-enhanced Raman scattering spectroscopy (SERS) has been used in environmental monitoring, biomedicine, food hygiene, etc., and high-activity SERS substrates are the key to the application of surface-enhanced Raman scattering spectroscopy. As a novel plasma material, TiN has strong SERS performance, and also has good chemical stability and biocompatibility, but its SERS performance is not as strong as that of precious metal gold and silver. For this reason, the Au/TiN composite films were prepared by depositing noble metal Au nanoparticles on the surface of TiN films using ammonia reduction nitridation and electrochemical deposition method. There were metal Au and TiN in Au/TiN composite film. With the increase of electrochemical deposition time, the number of metal gold nanoparticles on the surface of TiN film increased gradually and the size increased. The absorption peak of Au/TiN composite films moved, which was due to the intrinsic surface plasmon resonance coupling of gold and TiN. The SERS performance of the Au/TiN composite film was analyzed by using Rhodamine 6G as Raman probe molecule. It was found that the Raman peak signal intensity of the R6G probe molecule on the Au/TiN composite film increased firstly and then decreased as different deposition times increased. When the electrochemical deposition time was 5 min, the R6G Raman signal peak was the highest, and the composite film showed the strongest SERS activity. The Au/TiN composite film and Au film were immersed in 10^-3, 10^-5, 10^-7, 10^-8 and 10^-9 mol·L^-1 of R6G solutions for 5 min, respectively. The Au/TiN composite film enhancement factor reached 8.82×10⁵, and the detection limit was 10^-8 mol·L^-1. Compared with the Au film and the TiN film, the Raman signal of the R6G probe molecule on the Au/TiN composite film was the highest. This was due to the coupling effect of surface plasma in Au/TiN composite film, which enhanced the intensity of local electromagnetic field and enhanced the Raman signal of R6G probe molecule. The 2D-FDTD simulated electric field distribution showed that the Au/TiN composite film, the Au film and the TiN film all had an electric field enhancement effect, and the Au/TiN composite film had a particularly strong reinforcing effect, which confirmd the coupling effect between titanium nitride and gold. It was also found that there may be charge transfer between TiN and Au, which promoted the oxidation of 4-aminobenzenethiophenol, which confirmed the synergistic effect of TiN and Au film. Furthermore, the Au/TiN composite film had good uniformity with a relative average deviation of 7.58%. It could be seen that the Au/TiN composite film as prepared has potential application for SERS substrate.
		2020 Vol. 40 (02): 420-426 [Abstract] ( 254 ) RICH HTML PDF (5672 KB) ( 77 )

	427	Raman Spectroscopy Study on the Interaction of Ciprofloxacin with Aminophylline
		CHEN Rong, ZHOU Guang-ming^*, LUO Dan, ZHOU Jia-yu
		DOI: 10.3964/j.issn.1000-0593(2020)02-0427-05
		The Raman peak of Ciprofloxacin (CIP) was calculated by the density functional theory (DFT) B3LYP/6-31G(d, p) basis set, compared with the experimental Raman peak. The degree of fit is high. And its Raman Peak has been fully vested. The surface enhanced Raman spectroscopy (SERS) and conventional Raman experiments of ciprofloxacin showed that the gold nanoparticles were used as the substrate to enhance the Raman peak of ciprofloxacin. The effect of binding time on the mixture of aminophylline and ciprofloxacin was explored. The results showed that the interaction between the two increased with time, and the partial Raman peak of ciprofloxacin disappeared. The addition of aminophylline affected the molecular structure of ciprofloxacin, which caused the haloxixine Raman signal to weaken and many Raman peaks to change, mainly pyrazine ring at 1 184 and 1 252 cm^-1. The vibration frequency of C—F at Raman, C═C at 1 627 cm^-1 and O—C—O at 1 458 cm^-1 changed; the increase of aminophylline content had a more serious effect on the structure of ciprofloxacin, of which the Raman peak at 800~1 200 cm^-1 disappeared. When the amount of aminophylline exceeded 22.5 mg·L^-1, almost no other peak appeared except for the weak signal at 1 384 cm^-1. As a commonly used analytical tool, surface-enhanced Raman spectroscopy has the advantages of short analysis time and high sensitivity. The experiment used SERS technology to investigate the interaction between aminophylline and ciprofloxacin, and provided a reference for its pharmacological research.
		2020 Vol. 40 (02): 427-431 [Abstract] ( 229 ) RICH HTML PDF (2501 KB) ( 69 )

	432	CO₂ in Air Detected by Right Angle Mirror Cell of Raman
		HUANG Bao-kun¹, WANG Jing-zhuo¹, SONG Yong-xian¹, ZHU Lin¹, ZHANG Ming-zhe², OUYANG Shun-li^2*, WU Nan-nan³
		DOI: 10.3964/j.issn.1000-0593(2020)02-0432-04
		As an excitation spectrum, Raman spectroscopy uses laser as an excitation source to excite Raman signals of all gas molecules. Due to the low molecular density, high transmittance of light and low Raman Scattering Cross Section, the utilization efficiency of the eycitation light energy is low, and the Raman signal scatters to space around focus, only fraction of signal can be collected by collecting system. As a result, the detection limit is poor and cannot be widely applied to the detection of gas. In this paper, a Raman right angle reflection cavity was proposed to improve the detection limit of Raman detection of transparent samples such as gases. The Raman right angle reflection cavity used a right angle mirror to reflect incident light back to the original direction but the optical path had a spatial offset. Two parallel to each other, oppositely placed right-angle mirrors were used, and the laser with a beam diameter of 0.7 mm had a working diameter of 25.4 mm. The exciting laser was reflected back and forth 10 times in the cavity, and two lenses were placed in opposite direction around focus which were used to focus the excitation light to the same focus, thereby improving the use efficiency of the exciting laser energy. The Raman scattering signal transmitted along with the direction of incident laser was reflected back by the right-angle mirror to the right about, after being focused by the lens to the focus, with the Raman scattering signal scattered to the laser incident direction all passes through the long-pass filter and collected by Raman spectrometer, thereby improving the collection efficiency of Raman scattering signals. The experiment was carried out with air as the test object. The Raman spectrum of clear carbon dioxide and the fine Raman spectrum of nitrogen and oxygen were obtained within 300 s and the intensity ratio was analyzed, including 2 332 cm^-1 of nitrogen and 1 557 cm^-1 of oxygen. The peak height ratio of the 1 388 cm^-1 Raman peak of carbon dioxide was 785∶257∶1. The Raman right angle reflection cavity added two right-angle mirrors and one focusing mirror compare to the conventional Raman scattering excitation collecting system, and had the characteristics of small volume, simple structure and easy adjustment. The signal intensity distribution of Raman scattering to the surrounding space was related to the incident direction of the incident light, and the maximum of Raman signal accorded with the direction of the incident light and the reverse direction. The Raman right angle reflection cavity was designed to match the Raman signal intensity distribution, and along with the advantages of optical depth of field was utilized to maximize the Raman scattering signal collection efficiency. The Raman right-angle mirror cavity can extend the application of Raman spectroscopy in gas detection, such as in-situ monitoring of gas phase chemical reactions, engine combustion processes and emissions detection, and unknown pollutant gas analysis.
		2020 Vol. 40 (02): 432-435 [Abstract] ( 233 ) RICH HTML PDF (2421 KB) ( 75 )

	436	Denoising Method for Raman Imaging Data Based on Singular Value Decomposition and Median Absolute Deviation
		FAN Xian-guang^{1, 2, 3}, WU Teng-da¹, ZHI Yu-liang¹, WANG Xin^{1, 2, 3*}
		DOI: 10.3964/j.issn.1000-0593(2020)02-0436-05
		Raman imaging is a noninvasive, marker-free spectral imaging technique that provides molecular fingerprinting and spatial distribution of different components of a sample, and is more important than other imaging techniques. However, the Raman scattering has a small cross-sectional area and low sensitivity. In addition, in many experiments, in order to observe the dynamic distribution of certain components, the scanning time is shortened, and the resulting imaging data are disturbed by noise, so it is often necessary to denoise the signal. Conventional algorithms generally process the spectrum based on a given mathematical model, which is likely to cause excessive filtering and distortion of the signal. In addition, when processing Raman imaging data, conventional algorithms tend to denoise the data one by one. This neglects the relationship between multiple spectra, resulting in the final Raman image still being disturbed by many noises. Therefore, a signal processing method based on singular value decomposition (SVD) and median absolute deviation (MAD) is proposed for denoising Raman imaging data. Firstly, the singular value decomposition is performed on the Raman imaging data to obtain a singular value matrix and two orthogonal matrices. Then, all singular values in the singular value matrix are detected by the median absolute deviation method. The consecutively labeled outliers are used as singular values to be preserved, and the remaining singular values are assigned to zero to obtain a new singular value matrix. Finally, the new singular value matrix and two orthogonal matrices are solved again to obtain a denoised Raman imaging data. In the experiment, we first verify the correctness of the median absolute deviation method in determining the k value, and then the proposed algorithm is compared with the conventional algorithm from the aspects of image quality and signal waveform. The results show that the median absolute deviation method can quickly determine a reasonable value, and the imaging data processed according to this value not only eliminate a lot of noise in the imaging quality, but also make the spatial distribution characteristics of the components clearly visible. The tiny peaks are also perfectly preserved on the signal waveform and the spectral signal is recovered. This algorithm is different from the conventional algorithm in that it can process the entire Raman imaging data at the same time and preserve the statistical features between the spectra. It is a more effective denoising method for Raman imaging data.
		2020 Vol. 40 (02): 436-440 [Abstract] ( 216 ) RICH HTML PDF (3207 KB) ( 78 )

	441	*Reflectance Analysis of Pocillopora verrucosa* in Luhuitou Sanya Bay**
		CHEN Yong-qiang^1,2, LEI Xin-ming¹, CHEN Biao³, HUANG Hui^1,2*
		DOI: 10.3964/j.issn.1000-0593(2020)02-0441-05
		Measurement and analysis of spectral features of ground objects is the theory basis of coral reefs remote sensing, and can be used as a basis for quantitative and qualitative research of coral reefs using remote sensing. In this paper, Pocillopora verrucosa, a common coral in Lu Huitou sea area in Sanya Bay in the northwestern South China Sea, was used to measure the reflectance spectrum using a fiber spectrometer. The spectral difference between healthy and bleached Pocillopora verrucosa was studied by reflectance spectrum and derivative spectroscopy. The results showed that the characteristic peak value appeared at around 580, 604.7, 647 nm, with significant trough being at 669 nm on the health Pocillopora verrucosa reflectance spectrum; bleached Pocillopora verrucosa reflectance spectrum was significantly higher than that of healthy coral reflectance spectrum, the reflectance spectrum waveform was gentle relatively, and there were relatively weak trough at the wavelength of 663 nm. Derivative spectroscopy was then used to conclude that the main distinguishable bands of healthy and bleached Pocillopora verrucosa. Reflectance spectral derivative analysis results showed that healthy bleached Pocillopora verrucosa has some distinguishing band, and the main distinguishing bands are as follows: first derivative regions, 404～425, 456～466, 513～532, 563～568 and 661～667 nm; second derivative regions, 408～420, 542～556, 563～573, 615～634 and 687～695 nm; fourth derivative regions, 402～418, 466～472, 478～481, 617～622 and 684～689 nm.
		2020 Vol. 40 (02): 441-445 [Abstract] ( 160 ) RICH HTML PDF (1784 KB) ( 52 )

	446	Simulation of Spectral Albedo Mixing of Snow and Aerosol Particles
		CHEN Wen-qian^{1, 2}, DING Jian-li^{1, 2*}, WANG Xin³, PU Wei³, ZHANG Zhe^{1, 2}, SHI Teng-long³
		DOI: 10.3964/j.issn.1000-0593(2020)02-0446-08
		Aerosol particles of Black carbon in the snow cause a significant decrease in the albedo spectrum of the snow, which results in climatic radiation changes seriously, and will delay or advance the snow melting time, badly affecting the characteristics of surface runoff and processes of water cycle in the arid region. This problem is receiving increasing attention in ecological hydrology issues in the arid region. The data of field measurement were obtained by ASD spectrometer, Snow Folk and HR-1024 external field spectrum radiometer. SNICAR model was used to simulate the snow spectrum spectral characteristics under different parameters. Discussed the sensitivity of BC and snow particle size in different spectral ranges. The results showed that: In the snow spectral curve, the zenith angle changes from 0° to 80°, the albedo at 600 nm in the visible spectrum increases by 0.045, and the albedo at 1 000, 1 200 and 1 300 nm in the near-infrared band increases by 0.16, 0.225 and 0.249, respectively. The zenith angle is at 60°, when snow particle size increases from 100 to 800 μm, the albedo reduction can reach 0.15, and snow particle size in the range of 100~300 μm is significantly higher than the albedo in the range of 400~800 μm. And the increase of the snow particle size can enhance the absorption effect of the light spectrum absorbing particles; Different BC concentrations have little effect on the spectral albedo in the near-infrared region, but are mainly concentrated in the visible light band. At 800 and 1 100 nm, the BC concentration of 5 μg·g^-1 reduces the spectral albedo by 0.13. The BC of 5 μg·g^-1 can reduce the spectral albedo at 350 and 550 nm by 0.25 and 0.23. Compared with the different snow sizes, the decrease of BC concentration on the broad-band albedo of snow spectrum can be found in BC. In the case of the increase in the particle size of the snow, the light absorption effect of BC is increased, and at the higher concentration, the more the absorption increases; from the spectral index, the BC is sensitive in the visible light range of 350~740 nm, and the correlation coefficient is higher; The snow size is sensitive in the near-infrared band 1 100~1 500 nm, especially around 1 000 and 1 300 nm. The correlation between BC and snow particle size in the sensitive band of the snow spectral curve is high. Finally, the snow albedo simulated by the model is compared with the measured data. The R² is 0.738, and the simulation effect is good. It can lay a data foundation for the study of the snow albedo in the arid region.
		2020 Vol. 40 (02): 446-453 [Abstract] ( 187 ) RICH HTML PDF (4375 KB) ( 60 )

	454	Classification of Color Matching Functions with the Method of Cluster Analysis
		HUANG Min, GUO Chun-li, HE Rui-li, XI Yong-hui
		DOI: 10.3964/j.issn.1000-0593(2020)02-0454-07
		Larger color discrimination difference exits among observers with normal color vision, especially those of different ages. In order to classify the cone fundamentals among normal color observers, the 108 color matching functions (CMFs) including 47 Stiles&Burch CMFs and 61 CMFs computed by CIE2006 model were respectively classified into 5 categories in $\bar{x}$ (λ), $\bar{y}$ (λ), $\bar{z}$ (λ) three channels by using the k-medoids algorithm of clustering analysis method as well as the square of Euclidean distance and a total of 5×5×5=125 categories were generated. Taking the 108 CMFs as 108 “individual observers”, the 17 color centers recommended by CIE were displayed on the center of iPad and 108 CMFs were compared with 125 categorical functions, then the average of 17 colors’ CIEDE2000 color differences were calculated. Finally 10 categorical CMFs were selected from those 125 categories to represent the spectral response of human cone cells. The results indicated that 77.8% from the 108 “real observers” were satisfied, which regarded the obtained minimum color difference as the objective function. As the target colors, CIE recommended 5 colors (gray, red, yellow, green, blue) were presented on the iPad and 30 young observers aged 20 to 25 and 17 old observers aged 61 to 74 were organized to match 5 color centers correspondingly on Quato display. Therefore, 158 groups, 790 color data (each group includes 5 color centers) were obtained and then categorized by computing CIEDE2000 color difference using 10 categorical CMFs. The CMFs possessing the minimum color difference value were assigned as the corresponding classification of 158 observers and finally 8 out of 10 categories were selected and named BIGC-1, BIGC-2, …, BIGC-8, which were used to test the results of paired comparison experiment based on metameric color samples in our previous study. The obtained results show that BIGC-3 CMFs worked well for young observers while BIGC-5 CMFs were suitable to old observers. Additionally, the calculated results of STRESS value were also lower than the results computed by other CMFs.
		2020 Vol. 40 (02): 454-460 [Abstract] ( 220 ) RICH HTML PDF (3155 KB) ( 56 )

	461	Measurement of Ozone Concentration in Atmospheric Pressure Air Barrier Discharge by Optical Absorption Spectroscopy
		GAO Kun^1,2, GONG Dan-dan¹, LIU Ren-jing¹, SU Ze-hua¹, JIA Peng-ying¹, LI Xue-chen^1*
		DOI: 10.3964/j.issn.1000-0593(2020)02-0461-04
		As a strong oxidant and bactericide, oxygen has great potentials in various applications，such as pollutant degradation, food processing, sterilization, and medical services. Atmospheric pressure dielectric barrier discharge (DBD) is an extremely efficient method of generating ozone. DBD is generated in atmospheric pressure air between two parallel-plate electrodes excited by alternating current voltage. Waveforms of applied voltage and light emission are measured by optical and electrical methods. It can be found that the light emission presents lots of narrow pulses, which distribute stochastically in every half cycle of applied voltage. These narrow pulses only sustain about several tens ns to several hundred ns, which indicates that barrier discharge in atmospheric pressure air belongs to a streamer regime. Based on 200 and 900 nm scanned optical spectrum emitted from the discharge, the emissions mainly include those from the second positive system of the nitrogen molecule (C³Π-B³Π), the first negative system of the nitrogen molecular ion (B²Σ-X²Σ), the first positive system of the nitrogen molecule (B³П-A³П), and oxygen atomic (OⅠ: 715.7 nm，799.5 nm). Moreover, no emission line is observed between 200 nm and 300 nm (ultraviolet (UV) region). Due to a strong absorption peak in this UV region, absorption spectrum in UV region between 230 and 300 nm can be used to obtain the ozone density. In doing so, UV lamp irradiates the plasma area from one side of the discharge region, and transmitted light is received by the spectrometer on the other side. Absorption spectra are measured when DBD is on and off. Absorption spectroscopy can effectively monitor the change of ozone concentration. Its advantages are simple operation, low requirements on the experimental environment, being able to be used under discharge conditions, and continuous monitoring of ozone concentration changes. Ozone concentration is calculated as a function of peak voltage and driving frequency based on Beer-Lambert’s law. It is found that ozone concentration increases with increasing peak voltage or driving frequency. These results are of great significance to industrial application of dielectric barrier discharge at atmospheric pressure.
		2020 Vol. 40 (02): 461-464 [Abstract] ( 255 ) RICH HTML PDF (1966 KB) ( 114 )

	465	Chemiluminescence Characteristics of Coal-Water Slurry Impinging Flames in Bench-Scale Entrained Flow Gasifier
		SONG Xu-dong¹, GUO Qing-hua², GONG Yan^2, SU Wei-guang¹, BAI Yong-hui¹, YU Guang-suo^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2020)02-0465-07
		The flame spectrum detection technology applied to the effective monitoring of gasifier can reflect the working condition of gasifier in real time and guarantee the stable operation of gasifier. Based on the bench-scale entrained flow gasifier, the different chemiluminescence characteristics at different axial positions of the impinging plane (L) of coal-water slurry (CWS) flame are studied by the spectrometer, and the reaction zones in gasifier are characterized by different radical intensity and distributions. The results show that: OH^(306.7 nm, 309.8 nm), H^₂ (382 nm), CH^(314.5 nm，387 nm), Na^(589 nm), Ar(671 nm)and K^(404 nm, 768 nm, 770 nm) characteristic peaks can be detected in the range of 300～800 nm. Different particle distributions can be used to characterize the macroscopic characteristics of flame. There is also a strong background radiation in CWS gasification flame. The background radiation mainly comes from the blackbody radiation generated by coal particles at high temperature and continuous rotational radiation of 350～600 nm generated by CO^₂. The strong background radiation will interfere with the determination of free radical intensity radiation, which will be deducted by the calculation. The distribution of OH^* can be used to characterize the flame reaction region, while CH^* only exists in a relatively narrow reaction region of -10 cm<L<10 cm. When 0.9≤O/C≤1.1，OH^* and CH^* peak intensity exist at the impinging plane. With the increase of O/C, the existence position of CH^* peak intensity turns to upstream. The intensity ratio of OH^/CH^ varies with the change of O/C at different positions. OH^/CH^ reflects the change of free radical excitation path. OH^/CH^ is the lowest at the impinging plane, because of chemical excitation dominates. Chemical excitation mainly occurs in the range of -10 cm＜L＜10 cm. The intensity of Na^* near the impinging plane is relatively high, but with the increase of \|L\|, the Na^* intensity will decrease. The Na^* intensity in the upstream is higher than that in the downstream. Different from Na^，the change of K^ intensity is disordered in the region of -20 cm<L<20 cm. Since the excitation mode of alkali particles (Na^* and K^) is thermal excitation, the distribution of alkali particles can be used to judge the high temperature region of the flame. However, due to the low content of Na and K particles in coal, the use of Na^ and K^* to characterize O/C will cause a large error. Because Na^* and K^* is less affected by background radiation, it can be used to characterize the flame frequency and reflect the gasification effect. Na^* intensity fluctuates with the impact of flames. With the increase of O/C, the frequency of Na^* intensity can indicate the change of flame fluctuation with the increase of oxygen gas velocity. And the Na^* strength gradually increase, indicating that the violent impact is conducive to the reactions. There is a high intensity of H^₂ in the impinging zone, and the H^₂ intensity can represent the reactions of volatile matter.
		2020 Vol. 40 (02): 465-471 [Abstract] ( 177 ) RICH HTML PDF (4248 KB) ( 53 )

	472	Study on Turbidity Compensation of Nitrate Nitrogen in Water Based on Ultraviolet Spectrum
		CHEN Ying¹, HE Lei¹, CUI Xing-ning¹, XIAO Chun-yan², ZHANG Jie¹, ZHANG Can¹, YANG Hui¹, ZHOU Xin-de¹, LI Shao-hua³
		DOI: 10.3964/j.issn.1000-0593(2020)02-0472-06
		Nitrate nitrogen is one of the most important pollution indicators in water environment monitoring and can be detected quicklywithout pollution by absorption spectroscopy. In view of the fact that the ultraviolet absorption spectrum is susceptible to turbidity interference, the influence of formaldehyde turbidity standard solution on the ultraviolet absorption spectrum of nitrate nitrogen standard solution is analyzed by experimental method. Based on this, a turbidity compensation method based on compensation curve method is proposed to compensate and correct the ultraviolet absorption spectrum. Then this method is validated by experiments, and the results are good. Firstly, the ultraviolet absorption spectra of 12 groups of nitrate nitrogen standard solution with concentration of 0.2～10 mg·L^-1, 10 groups of formaldehyde turbidity solution with concentration of 5～50 NTU and formaldehyde turbidity solution mixed with nitrate nitrogen solution were collected in the laboratory. Theoretically, according to Lambert’s law, the absorbance of the solution should be the superposition of the absorbance of different solutes, but through the experimental analysis, the absorbance of the mixed solution in the main absorption spectrum region of nitrate nitrogen was not equal to the sum of the absorbance of nitrate nitrogen and turbidity. This was because turbidity particles break the coplanarity of nitrate nitrogen molecules, resulting in steric hindrance, which destroys the conjugate system and leads to the decrease of nitrate nitrogen absorbance. Therefore, the compensation coefficient between 0 and 1 was introduced to characterize the effect of turbidity on the absorption spectrum of nitrate nitrogen. The closer to 0, the greater the influence of turbidity on the absorption spectrum of nitrate nitrogen at this wavelength. Based on the measured spectral data, the compensation coefficients of different turbidities in the main absorption spectral region of nitrate nitrogen can be obtained. According to the experimental analysis, the absorbance of nitrate nitrogen in 350～400 nm band is basically 0. The absorbance of mixed solution is only related to turbidity, and the absorbance of both is basically the same. Therefore, the spectral integral of this band can be selected to establish the turbidity regression model, and the turbidity value of mixed solution can be calculated. Compared with single wavelength regression, the spectral integral regression model has good stability and is not easily disturbed by other factors. The square of correlation coefficient R of turbidity calculation model is 0.998 5, and the calculation effect is good. Turbidity compensation can be carried out after the turbidity value is obtained. The compensation method is validated by experiments and compared with single wavelength turbidity compensation and uncompensated of turbidity. The validation results show that after turbidity compensation by compensation curve method, the nitrate nitrogen prediction model based on partial least squares (PLS) algorithm is established. The RMSEP is 0.124 and the average absolute error (MAE) between the predicted value and the real value is 5.3%. The compensation effect is pretty good, and the other two methods will deviate greatly. In contrast, the turbidity compensation method proposed in this paper is obviously better than the other two. This method can provide an effective technical reference for the turbidity compensation of nitrate nitrogen ultraviolet absorption spectrum.
		2020 Vol. 40 (02): 472-477 [Abstract] ( 219 ) RICH HTML PDF (2862 KB) ( 92 )

	478	Fluorescence Spectra and Fluorescence Saturation Intensity Analysis of Hepatic Cell，Hepatoma Carcinoma Cell and Hepatic Fibrosis Cell
		HU Yue, FU Yun^*, LI Xin-yang, LI Yong-liang
		DOI: 10.3964/j.issn.1000-0593(2020)02-0478-05
		Researched the fluorescence spectral characteristics of hepatic cell, hepatoma carcinoma cell and hepatic fibrosis cell to provide spectroscopy basis for early screening of liver cancer. The purpose of the experiment included the detection of cells by fluorescence spectrometer to acquire specific fluorescence spectra; eliminate background noise by de-Raman scattering to acquire fluorescence spectra of five cell concentrations；the cell diameter was detected by flow cytometry, analysis of the diameter characteristics of four cells based on two-parameter scatterplot; combined with Gauss multi-peak fitting parameter analysis results. The experimental process began as hepatic cell, hepatic fibrosis cell and two hepatoma carcinoma cell were detected by fluorescence spectroscopy and analyzed by flow cytometry as well. Then, Gauss multi-peak was used to fit the fluorescence spectrum differences, and the difference among the cells was analyzed. Finally, the fluorescence saturation intensity nonlinear fitting curve was compared to analyze the effect of cell size on it. The results showed that there were two specific fluorescence peaks in the hepatic cell between 550 and 750 nm. Combined with Gaussian multi-peak fitting, the peak height, peak center and peak width were analyzed. The results showed, the first peak was at 592 nm and the second peak was at 682 nm, and the former was significantly higher than the latter. In hepatoma carcinoma cell and hepatic fibrosis cell there was a third specific fluorescence peak at 726 nm except for two peaks at the same position as hepatic cell, and the maximum excitation intensity was obtained at 592 nm, and the fluorescence peak at 726 nm was higher than the second peak at 682 nm. The width of hepatoma carcinoma cell and hepatic fibrosis cell were basically the same. The maximum excitation peak width of hepatic cell was slightly smaller than that of the other two cells, but the small peak width at 682 nm was slightly larger than that of the diseased cells. The results of flow cytometry showed that the diameter of hepatoma carcinoma cell was the largest diameter, and hepatic fibrosis cell was larger than hepatic cell. Through fitting the curve of the fluorescence saturation intensity trend of the cell with the concentration curve by the nonlinear curve and analyzing the slope of the curve, the results showed that the fluorescence saturation intensity trend of the four cells increased with the increase of the cell concentration, but gradually showed the fluorescence saturation state. As the cell diameter increased, the trend of maximum fluorescence saturation intensity was more obvious, and auto fluorescence spectrum efficiency of single cells decreased. The results showed that the rational combination of cell morphology and spectroscopy, combined with two methods of analysis, improved the accuracy and effectiveness of cell judgment. By studying the fluorescence spectrum characteristics of hepatic cell, hepatoma carcinoma cell, hepatic fibrosis cell, and analyzing the fluorescence saturation intensity in combination with cell diameter, it can provide a certain spectral basis for the study of liver disease cells.
		2020 Vol. 40 (02): 478-482 [Abstract] ( 193 ) RICH HTML PDF (2307 KB) ( 60 )

	483	Application of Solid Surface EEM Fluorescence Spectroscopy for Analyzing Organic Matter Structural Composition of Lake Sediment
		HAN Xiu^{1, 2}, SONG Yong-hui^{1, 2*}, ZHANG Guang-cai², YAN Zong-cheng², JIN Fang-yuan², YU Hui-bin²
		DOI: 10.3964/j.issn.1000-0593(2020)02-0483-06
		Solid surface excitation-emission matrix (EEM) fluorescence spectroscopy, a leading technique, is used to characterize structural composition of solid organic matter. The EEM spectra were directly measured using solid samples, instead of extraction of dissolved organic matter. Hence the technique has feasibility, practicality and large amount of information. In this study, the solid surface EEM spectroscopy coupled with parallel factor analysis (PARAFAC), hierarchical cluster analysis (HCA), and classification and regression tree (CART) was applied to extract fluorescent components of the surface sediments in Wuliangsuhai Lake, to track potential factors of the organic matter, and to reveal spatial variations of the components. The ten samples were collected along a pollution gradient. The solid surface EEM fluorescence spectroscopy were measured using the untreated sample and the thermally treated samples, and the spectroscopy of the organic matter were obtained by the difference between the former and the latter. Four fluorescence components (C1 to C4) were extracted by the PARAFAC. The C1 was associated with the tryptophan-like material, which could be derived from in-situ source. The C2 was relative to the fulvic-like material, and the C3 and C4 were concerned with the Vis humic-like and UV humic-like materials respectively, which could be derived from ex-situ source. The total abundances of the four components were the highest in the northern region, followed by the southern and the central regions. The abundances of the C2 to C4 were higher than those of the C1, suggesting that the organic matter was mainly derived from the ex-situ source. The C1 in the southern region was relatively higher than that in northern and central, indicating that the C1 could be relative to the metabolism of many more aquatic plants. The decreasing order of the C2 was northern>southern>central. The C3 was higher in the northern region than those in the southern and central regions，so the C3 was the representative of the sediment in the north. The trend of the C4 was similar to the C2. Based on the fluorescence component HCA, the C2 and C4 might have the terrestrial source, while the C1 and C3 were the potential factors of the organic matter in the sediments. Based on the sample HCA, the sampling sites were grouped into three clusters, i. e. the high-pollution (the northern region), the medium-pollution (the southern region) and the low-pollution (the central region). With the CART model, the C3 and C1 were verified as the potential indicators, which provided clearer classification of the sediments, and offered technical support forsubsequent exploration of pollution characteristics and sources.
		2020 Vol. 40 (02): 483-488 [Abstract] ( 244 ) RICH HTML PDF (4285 KB) ( 67 )

	489	The Composition and Structure of Dissolved Organic Matter in Saline Soil Were Studied by Synchronous Fluorescence Spectroscopy Combined with Principal Components and Two-Dimensional Correlation
		CHEN Ying-ying^{1, 2}, ZHENG Zhao-pei^1*, YANG Fang², BAI Yang², YU Hui-bin²
		DOI: 10.3964/j.issn.1000-0593(2020)02-0489-05
		In order to solve the research limitations caused by overlapping fluorescence peaks of synchronous fluorescence spectroscopy, the overlapping peaks were analyzed by using synchronous fluorescence technology in combination with two-dimensional correlation and principal components and other methods to study the composition and structural characteristics of soil dissolved organic matter (SDOM). The typical and common reeds, poplar, corn, melon four planted soils in hetao irrigation area were selected as the research objects, and soil samples from the four sample points were collected, a total of 16 soil samples were collected under four layers of vegetation, namely 0~20, 20~40, 40~60 and 60~80 cm. Dissolved organic matter was extracted and Synchronous fluorescence spectroscopy (SFS) was detected. SFS showed that melon and corn SDOM fluorescence intensity was greater than the woodlands and reed, melon SDOM fluorescence intensity increased with the increase of soil depth, while for the other three plantings SDOM fluorescence intensity decreased with the increase of soil depth, indicating that for the melon soil,in the process of watering soil layer gave priority to eluviation, and other soil layers gave priority to filtration. Principal component analysis (PCA) was used to identify five fluorescence components, including tyrosine, tryptophan, microbial metabolites, fulvic acid and humic acid. Based on two-dimensional correlation spectrum analysis, tryptophan in reed soil was positively correlated with the change trend of microbial metabolites. The change order of spectral bands was 370 nm→337 nm→290 nm, indicating that the change order of components was fulvic acid→microbial metabolites→tryptophan. There was a positive correlation between fulvic acid and humic acid in maize soil, and the change order of the band was 318 nm→350 nm→420 nm→274 nm, indicating that the change order of components was microbial metabolites→fulvic acid→humic acid→tyrosine. There was a positive correlation between tyrosine, fulvic acid and humic acid in woodland soil, and the change order of band was 270 nm→392 nm→426 nm→305 nm→337 nm, indicating that the change order of components was tyrosine fulvic acid→humic acid→tryptophan→microbial metabolites. There was a positive correlation between humic acid and humic acid, but a negative correlation between humic acid and tyrosine in the soil of melons, and the change order of band was 410 nm→355 nm→334 nm→309 nm→275 nm, indicating that the change order of components was humic acid→fulvic acid→microbial metabolite→tryptophan→tyrosine. Therefore, it is very effective to analyze the fluorescence spectral characteristicsof SDOM and identification of fluorescence componentby using SFS combined with PCA and two-dimensional correlation spectroscopy, and to reveal the spatial variation law of fluorescence components.
		2020 Vol. 40 (02): 489-493 [Abstract] ( 193 ) RICH HTML PDF (3288 KB) ( 74 )

	494	Qualitative and Quantitative Analysis of PAHs Based on Three-Dimensional Fluorescence Spectroscopy and PARAFAC
		WANG Shu-tao^*, LI Ming-shan, WANG Yu-tian, WU Xing, CHENG Qi, CHE Xian-ge, ZHU Wen-hao
		DOI: 10.3964/j.issn.1000-0593(2020)02-0494-07
		Three-dimensional fluorescence spectroscopy plays an important role in studying the fluorescence information of polycyclic aromatic hydrocarbons (PAHs). PAHs are carcinogenic and refractory. They are mostly produced by exhaust emissions and waste incineration，which endanger human health and the environment. Therefore, people are constantly exploring the detection methods of PAHs. ANA and NAP in PAHs were selected as detection substances and FLS920 fluorescence spectrometer was used in the experiment. In order to avoid the influence of Rayleigh scattering produced by the fluorescence spectrometer itself, the initial emission wavelength was set at 40 nm, and the excitation wavelength was lagged behind, and the scanning excitation wavelength (lambda ex) was set at 200～370 nm, and the emission wavelength (lambda em) was set at 240～390 nm. Then we could gain the fluorescence data of PAHs obtained by fluorescence scanning, and we could analyze ANA and NAP qualitatively and quantitatively in mixed solution by the three-dimensional fluorescence spectroscopy and PARAFAC. The ANA and NAP used in the experiment were purchased from the Aladdin reagent official website, and we prepared a stock solution with a concentration of 10 mg·L^-1, and we should dilute the stock solution, and we canget 0.5, 1, 1.5, 2, 2.5, 3, 3.5，4, 4.5 mg·L^-1 of secondary stock solution, which obtain a concentration of ANA and NAP, Then we maxed the solution of ANA and NAP. Before spectral analysis, the spectra of ANA and NAP needed to be pretreated, and we should eliminate the effect of Raman scattering by blank subtraction method, and adopt the way of ensemble empirical mode decomposition (EEMD) to eliminate interference noise. In this experiment, there are two peaks in ANA, located at λ_ex=298 nm, λ_em=324/338 nm, and the peaks of NAP at λ_ex=280 nm and λ_em=322 nm. The PARAAFAC algorithm selected in this paper was very sensitive to the choice of component number, therefore, using the method of nuclear consistency diagnosis to estimate the number of components, and the nuclear consistency values of the estimated values 2 and 3 were all over 60%, then decomposed the mixed samples by PARAFAC of 2 and 3 factors respectively. After decomposition, the data of excitation emission spectra and concentration of each component were normalized, and we can draw the spectrogram, and compare with the real excitation emission spectrogram and concentration map of each component. At the same time, the predicted concentration of mixed samples obtained by PARAFAC was used to determine the accuracy of quantitative analysis by calculating the recovery rate (R) and root mean square error (RMSEP). When choosing two factors, the fitness of ANA and NAP was 95.7% and 96.7%, the average recovery was 101.8% and 98.9%, the root mean square error was 0.018 7 and 0.031 6, and choosing three factors, the fitness of ANA and NAP was 95.3% and 95.8%, the average recovery was 97% and 102.5%, the root mean square error was 0.033 and 0.116. Because of the three indicators, the effect of qualitative and quantitative analysis with two factors was better than that with three factors. The experimental results showed that the qualitative and quantitative analysis of mixed samples based on three-dimensional fluorescence spectrometry and PARAFAC algorithm can effectively determine the type of mixed samples, and its can successfully predict the concentration of mixed samples.
		2020 Vol. 40 (02): 494-500 [Abstract] ( 266 ) RICH HTML PDF (5183 KB) ( 89 )

	501	Three-Dimensional Fluorescence Combined with AWRCQLD to Measure Three Additives in Cosmetics
		WANG Yu-tian¹, ZHANG Yan^1*, SHANG Feng-kai¹, ZHANG Jing-zhuo², ZHANG Hui¹, SUN Yang-yang¹, WANG Xuan-rui¹, WANG Shu-tao¹
		DOI: 10.3964/j.issn.1000-0593(2020)02-0501-05
		Gallic acid (GAa), known as 3, 4, 5-trihydroxybenzoic acid (C7H605), usually in the form of hydrates, as an important organic raw material, is widely found in plants. Studies have shown that GAa has many effects such as anti-oxidation, anti-inflammatory, anti-tumor, anti-viral and anti-mutation. Therefore, GAa is often added to cosmetics as an antioxidant. P-Hydroxybenzoic acid (p-HA), whose molecular formula is C7H603, wherein the R group is methyl, ethyl, propyl, butyl or heptyl, respectively, referred to as ethyl p-hydroxybenzoate, Propyl p-hydroxybenzoate, butyl p-hydroxybenzoate and heptyl p-hydroxybenzoate. The p-HA ester has strong antibacterial property, low toxicity, and antibacterial action against pH, so it is often used as a preservative in cosmetics and medicines. Resorcinol (RE) is also known as 1,3 benzenediol or m-diphenol (formula C6H602). RE has a bactericidal action and can be added to cosmetics as a preservative. In this paper, three kinds of cosmetic additives such as gallic acid (GAa), p-hydroxybenzoic acid (p-HA) and resorcinol (RE) were used as target analytes, and four-dimensional fluorescence spectra were constructed by introducing a fourth dimension solvent. Three sets of experimental samples were obtained for methanol (spectral level), ethanol (spectral level), and ultrapure water, and the configuration of the three groups was the same as that of the added drug. Using the FS920 steady-state fluorescence spectrometer (spectral wavelength response range of 200~900 nm, liquid nitrogen refrigeration range of 77~320 K, excitation source power is 450 W, signal-to-noise ratio is 6 000∶1) to test the sample, and setting the excitation wavelength to 210～330 nm, a piece of data was recorded at intervals of 4 nm; the emission wavelength was 280～480 nm, and a piece of data was recorded at intervals of 2 nm. The initial emission wavelength always lagged the excitation wavelength by 10 nm, thereby eliminating the interference of the first-order Rayleigh scattering. The initial fluorescence data were then pretreated using a blank subtraction method to remove Raman scattering of the solvent. Finally, the nuclear consistent diagnosis method was used to determine the number of components of the sample to be tested to be 3, and the three-dimensional fluorescence spectrum data after pretreatment were decomposed using the alternating weighted residual constrained quadratic decomposition (AWRCQLD) algorithm. The results showed that the AWRCQLD algorithm decomposes the excitation and emission spectra of GAa, p-HA and RE almost overlapping with the target spectrum, and can achieve rapid qualitative and quantitative analysis of GAa, p-HA and RE with severe spectral overlap. Using the AWRCQLD algorithm to decompose the samples, the average recoveries of GAa, p-HA and RE were 98.3%, 98.4% and 98.1%, respectively, and the root mean square error (RMSEP) was 0.081, 0.111 and 0.001 μg·mL^-1. Three-dimensional fluorescence combined with the AWRCQLD algorithm enables rapid detection of GAa, p-HA and RE in cosmetics.
		2020 Vol. 40 (02): 501-505 [Abstract] ( 199 ) RICH HTML PDF (2512 KB) ( 54 )

	506	Determination of Phenolic Acids in Cosmetics by Three-Dimensional Fluorescence Spectroscopy Combined with Quadratic Decomposition Algorithm
		ZHANG Hui, WANG Shu-tao, ZHANG Li-juan, SHANG Feng-kai, ZHANG Yan, LI Ming-shan, WANG Yu-tian
		DOI: 10.3964/j.issn.1000-0593(2020)02-0506-06
		For phenolic acids in cosmetics, some are added as active ingredients, such as caffeic acid with skin-repairing effects, gallic acid capable of anti-inflammatory and anti-allergic, etc.; some are added as preservatives, such as p-hydroxybenzoic acid, sorbic acid, etc.; some are prohibited substances illegally added by bad businesses, such as hydroquinone, resorcinol and so on. In order to monitor the quality of cosmetics, the detection of phenolic substances in cosmetics is particularly important. Many researchers have done related work for this purpose. The method of separation and analysis based on chromatography has achieved certain success, but the disadvantages such as being time-consuming and costly and complicated operation are also obvious. Three-dimensional fluorescence spectroscopy has a high sensitivity, but fluorescence interference and spectral overlap have a large impact on detection, and complex cosmetic samples often fail to achieve the desired results. In order to realize simultaneous qualitative and quantitative detection of phenolic acids in cosmetics, the paper combines three-dimensional fluorescence spectroscopy with four-dimensional calibration of chemometrics (also called third-order correction) to overcome unknown interference and the effect of collinearity with the data while ensuring high sensitivity. First, select in the linear range of caffeic acid (CA), p-hydroxybenzoic acid (p-HA), hydroquinone (HQ). At the appropriate concentration, calibration samples, verification samples and cosmetic samples were prepared at the four pH values of 7.00, 7.30, 7.50, 7.80, respectively, so that the excitation-emission-pH-sample (EX-EM-pH-Sample) four-dimensional data were obtained. Secondly, in order to verify the effect of pH on the fluorescence intensity, 320 nm was chosen as the excitation wavelength to obtain the emission wavelength of caffeic acid at four pH values. It was found that the fluorescence intensity of caffeic acid increased with the increase of pH value, indicating the introduction of pH. The value was reasonable as the fourth dimension. Finally, the appropriate component number was selected to decompose and predict the four-dimensional data matrix by alternating penalty quadrilinear decomposition (APQLD). The decomposed spectrum was compared with the actual spectrum, and the predicted concentration was compared with the actual concentration. The experimental results showed that the decomposition spectrum can be consistent with the actual spectrum whether it is a validation sample or a cosmetic sample. The average recovery (AR) of the validation sample was 100.4% to 103.5%, and the predicted root mean square error (RMSEP) was less than 0.06. The average recovery (AR) of cosmetics sample was 100.0%~102.2%, and the predicted root mean square error (RMSEP) was less than 0.08. Compared with chromatographic studies, the recovery rate increased by about 4%, and the operation was simple, time-saving and labor-saving, and has high sensitivity. Compared with the second-order correction method, multiple components in the complex cosmetic system can be realized under unknown interference. Replacing “physical and chemical separation” with “mathematical separation” is fast, efficient, economical and environmentally friendly; and third-order correction can overcome certain data collinearity problems and improve sensitivity to some extent.
		2020 Vol. 40 (02): 506-511 [Abstract] ( 203 ) RICH HTML PDF (3600 KB) ( 47 )

	512	Classification of FTNIR Spectra of Tea via Possibilistic Fuzzy Discriminant C-Means Clustering
		WU Bin^1, FU Hai-jun², WU Xiao-hong^{2, 3}, CHEN Yong², JIA Hong-wen¹
		DOI: 10.3964/j.issn.1000-0593(2020)02-0512-05
		Fourier transform near-infrared spectroscopy (FTNIR) spectra contain valuable information about the chemical constituents of tea. Furthermore, the chemical constituents and their content of tea reveal differences concerning different kinds of tea and, therefore, it is feasible to classify tea varieties by FTNIR. FTNIR spectra have the characteristics of high dimension, crests and troughs, spectral overlapping and staggering, so it is difficult to classify spectra. In order to solve this problem, possibilistic fuzzy discriminant c-means clustering (PFDCM) was proposed by introducing fuzzy linear discriminant analysis (FLDA) into possibilistic fuzzy c-means clustering (PFCM) for purpose of discriminating FTNIR spectra correctly. Interestingly, during fuzzy clustering FLDA can not only extract discriminant information from FTNIR spectra but can transform the data space. PFDCM can achieve the accurate classification of FTNIR spectra according to its fuzzy membership and typicality values, and it has some advantages such as fast speed and high accuracy. PFDCM is superior to fuzzy c-means (FCM) clustering in clustering spectra containing noisy data because the typicality values of PFDCM are no constraint that the sum of the membership degrees is one. Four varieties of tea samples, called Yuexi Cuilan, Lu’an Guapian, Shiji Maofeng and Huangshan Maofeng, were collected in this study, and a total of 260 tea samples were scanned over the range of 10 000~4 000 cm^-1 by FTNIR spectrometer, and in the end the 1 557-dimensional data were acquired for further processing. For a start, spectral data were pretreated with multiplicative scatter correction (MSC) to reduce spectra scattering and noise effect and increase signal-to-noise ratio. Secondly, principal component analysis (PCA) was used to reduce the dimensionality of FTNIR spectra to seven. Thirdly, discriminant information was extracted from spectra and the dimensionality of data was transformed from seven to three by linear discriminant analysis (LDA). Finally, fuzzy c-means (FCM) clustering, PFCM and PFDCM were put into use, clustering data to classify tea variety correctly. The experimental results showed that under the condition of the weight index m=2.0 and η=2.0, the clustering accuracy rates of FCM, PFCM and PFDCM achieved 93.60%, 93.02% and 98.84%, respectively. After 25 iterations, FCM converged, but PFCM and PFDCM achieved 8 iterations and 23 iterations, respectively, and converged. As fuzzy clustering algorithms converged, FCM consumed the least time but the most time-consuming clustering was PFDCM. In conclusion, FTNIR coupled with MSC, PCA, LDA and PFDCM presented a classification model for the accurate identification of tea varieties.
		2020 Vol. 40 (02): 512-516 [Abstract] ( 225 ) RICH HTML PDF (1949 KB) ( 184 )

	517	*Effect of Leaf Dust Retention on Spectral Characteristics of Euonymus japonicus* and Its Dust Retention Prediction**
		ZHU Ji-you¹, YU Qiang^1*, LIU Xiao-xi², YU Yang³, YAO Jiang-ming⁴, SU Kai¹, NIU Teng¹, ZHU Hua⁵, ZHU Qiu-yu⁵
		DOI: 10.3964/j.issn.1000-0593(2020)02-0517-06
		Atmospheric particulate pollution has become one of the serious urban environmental problems on a global scale. In order to explore the influence of leaf surface dust on the spectral characteristics of the leaves, a prediction model of leaf surface dross based on high-spectrum data was established. In order to explore the influence of leaf surface dust on the spectral characteristics of the leaves, a prediction model of leaf surface dross based on high-spectrum data was established. Our study focused on the common greening tree species (Euonymus japonicus) in Beijing, and collected 720 leaf samples in high, medium and low dust pollution gradient environments, and then used the ASDF Fildsoec Handheld spectrometer to obtain hyperspectral data. The results showed that the spectral reflection peaks were at 560 and 900 nm, respectively, and the absorption valleys were in the range of 400~500, 600~700 and 1 000~1 050 nm. The leaf reflectivity with or without dust retention showed different rules in different bands. The spectral reflectances in the range of 400~760 and 760~1 100 nm were as follows: dust-retaining leaves>dust-removing leaves, dust-retaining leavesR²，which were y=-1.18x²+0.542 4x+0.991 7, y=-7.67x²+3.692 4x+0.371 4, respectively. The regression model was validated by using the predicted samples, and the R² reached 0.987 7 and 0.887 3, respectively. The fitting effect was good, indicating that the two prediction models can effectively estimate the dust retention of the leaf of Euonymus japonicus.
		2020 Vol. 40 (02): 517-522 [Abstract] ( 189 ) RICH HTML PDF (2657 KB) ( 47 )

	523	*Structural Properties and Composition of Paulownia：Effect of Acetic Acid and Sodium Sulfite Combined Pretreatment*
		MA Li¹, JIA Liang-liang¹, QI Xue-min¹, CHU Jie^1, ZHANG Jun-hua¹, CHANG De-long^2, XU Ya-ya²
		DOI: 10.3964/j.issn.1000-0593(2020)02-0523-06
		Pretreatment is one of the key steps in the efficient conversion of lignocellulose into fuel ethanol. During the pretreatment process, a large amount of barrier components such as lignin and hemicellulose can be removed, which can effectively increase the productive adsorption of the cellulase to cellulose, thereby effectively improving the subsequent enzymatic hydrolysis yield. Paulownia has a large annual output, short growth cycle and high processing waste. It is a potential material for the preparation of bio-energy and other chemicals. In order to achieve high-efficiency conversion of paulownia woody biomass material to bioethanol, and promote efficient enzymatic hydrolysis of paulownia material, the raw material was pretreated to break its original biological resistance, degrade and remove enzymatic hydrolysis barrier components, expose and retain more cellulose components. In this work, Paulownia was used as the experimental material, and the raw material was chemically pretreated with acetic acid and sodium sulfite, analyzing the effect of different treatment methods on the chemical compositions and structural characteristics of samples. The composition analysis showed that the relative content of glucan in the samples increased to different degrees after pretreatment, and the alkaline sodium sulfite synergistic treatment of paulownia increased most obviously. The data showed that the alkaline sodium sulfite synergistic treatment had a good delignification effect and could degrade some xylan component, so the relative content of glucan was significantly increased to 67.48% (the relative content of glucan in the raw material was 46.81%). In addition, the physicochemical structures of all paulownia samples were analyzed by FTIR, XRD and XPS to explore the effects of different pretreatments on the structure of samples. FTIR analysis showed that the characteristic absorption of lignin was significantly weakened by the alkaline sodium sulfite synergistic treatment, and the characteristic absorption of cellulose was enhanced, indicating that the lignin had a certain removal, and the relative content of cellulose had increased; XRD analysis showed that the fiber surface of pretreated Paulownia was destroyed, the amorphous substances such as lignin and hemicellulose were partially removed, and the crystallinity of cellulose increased to varying degrees. Among them, after alkaline sodium sulfite synergistic treatment, the cellulose crystallinity increased significantly to 58.98% (the cellulose crystallinity of the raw material was about 40.23%), the peak position of 002 shifted to the right, the diffraction intensity of diffraction peak increased obviously, the peak shape became higher and the sharpness increased; XPS analysis showed that the surface carbohydrate content increased and the surface lignin content decreased after the alkaline sodium sulfite synergistic treatment. All the structural characterization analysis showed that the alkaline sodium sulfite synergistic treatment had the greatest destructive effect on the structure of Paulownia, the most lignin degradation and the best cellulose retention, which could increase the accessibility of cellulase to cellulose and effectively improve the subsequent cellulase hydrolysis efficiency, and thereby promote the efficient conversion of paulownia raw material to fuel ethanol. The results of structural characterization analysis were consistent with the chemical composition rules.
		2020 Vol. 40 (02): 523-528 [Abstract] ( 189 ) RICH HTML PDF (2079 KB) ( 56 )

	529	Feature Band Extraction and Degree Monitoring of Corn Pollution under Copper Stress
		GAO Peng¹, YANG Ke-ming^1*, RONG Kun-peng¹, CHENG Feng¹, LI Yan¹, WANG Si-jia²
		DOI: 10.3964/j.issn.1000-0593(2020)02-0529-06
		The situation of heavy metal pollution in farmland isn’t optimistic. The heavy metals in soil can affect normal growth and development of crops after being absorbed by the roots, reduce quality of agricultural products, and then enter human body through food chain, endangering human health. Hyperspectral Remote Sensing provides possibility for a real-time, dynamic and efficient monitoring of heavy metal pollution in crops. The potted corn experiment with different Cu²⁺ stress gradients was set up, the spectral data of old, middle and new leaves in seedling, jointing and spike stages were collected, and the chlorophyll content and leaves Cu²⁺ content were determined in different growth periods. Based on the spectral data, chlorophyll content and leaves Cu²⁺ content, OIF-PLS method was constructed to extract feature bands containing Cu²⁺ pollution information by combining correlation analysis, optimal index factor (OIF) and partial least square (PLS). Firstly, the characteristic bands were preliminarily screened according to correlation coefficient between chlorophyll content in leaves at seedling stage, jointing stage and spike stage and Cu²⁺ content in leaves at spike stage and corresponding leaf spectra. Then, three bands were selected to calculate optimum index factor, and the three bands were taken as independent variables to carry out partial least squares regression analysis on Cu²⁺ content in corn leaves to calculate root mean square error. Finally, the best feature band was selected according to principle of maximum optimum index factor and minimum root mean square error. The vegetation index OIFPLSI was constructed based on the characteristic bands selected by OIF-PLS method to monitor heavy metal copper pollution, and compared with red edge normalized difference vegetation index (NDVI₇₀₅), modified red edge simple ratio vegetation index (mSR₇₀₅), red-edge vegetation stress index(RVSI) and photochemical reflectance index (PRI) monitoring results to verify the effectiveness and superiority of OIFPLSI. In addition, the applicability and stability of OIFPLSI were verified by using the data obtained from different years under same experimental method. The experimental results show that the feature bands (542, 701, 712 nm) extracted from OIF-PLS can better reflect Cu²⁺ pollution information than the feature bands (602, 711, 712 nm) based on OIF. OIFPLSI was significantly positively correlated with leaf Cu²⁺ content, and the correlation was better than NDVI₇₀₅, mSR₇₀₅, RVSI and PRI. OIFPLSI was significantly negatively correlated with leaf chlorophyll content and positively correlated with Cu²⁺ content in soil. The correlation between OIFPLSI and Cu²⁺ content in soil at different growth stages is successively higher in jointing stage, ear stage and seedling stage. Based on the data of different years, the results show that OIFPLSI is positively correlated with leaf Cu²⁺ content, and OIFPLSI has strong stability. OIFPLSI based on the characteristic bands extracted by OIF-PLS method can better diagnose and analyze copper pollution level of corn leaves, which can provide a certain technical reference for crop heavy metal pollution monitoring.
		2020 Vol. 40 (02): 529-534 [Abstract] ( 193 ) RICH HTML PDF (3028 KB) ( 73 )

	535	Effects of Different Fertilization Conditions on Canopy Spectral Characteristics of Winter Wheat Based on Hyperspectral Technique
		ZHANG Yue¹, TIAN Yuan-sheng¹, SUN Wen-yi^{1, 2*}, MU Xing-min^{1, 2}, GAO Peng^{1, 2}, ZHAO Guang-ju^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2020)02-0535-08
		Quantitative study of the relationship between soil nutrient content and canopy spectral characteristics of winter wheat based on hyperspectral techniques can provide theoretical basis and technical support for winter wheat nutrient abundance monitoring and scientific and rational guidance of fertilization programs. In a 35-year long-term positioning experiment, the effects of different fertilization treatments on the spectral characteristics of winter wheat canopy in different growth stages of Loess Plateau were studied. The results showed that under single fertilization conditions, compared with no fertilization (CK), from the jointing stage to the heading stage of the winter wheat, the CR₅₀₀, CR₆₇₀ and CR₅₅₀ values of single P application were higher, while the spectral reflectance of single N and M application was significantly lower. The CR₅₀₀ values of single P, N and M application in jointing stage were 1.2 times, 74.9% and 70.5% of CK; CR₆₇₀ values were 1.2 times, 66.8% and 62.6% of CK; CR₅₅₀ values were 1.2 times, 76.2% and 76.9% of CK, respectively. The peaks and valleys of the reflex characteristics of winter wheat were significantly enhanced at heading stage than those at jointing stage, at heading stage，the CR₅₀₀ values of P, N and M application were 1.2 times, 81.0% and 53.5% of CK; the CR₆₇₀ values were 1.3 times, 76.8% and 40.6% of CK; CR₅₅₀ values were 1.2 times, 78.5% and 63.4% of CK, respectively. At the filling stage, the peaks and valleys of the reflex characteristics of each treatment were obviously weakened; to the maturity stage, the difference between the peaks and valleys of the winter wheat spectrum under different fertilization treatments was no longer obvious. The spectral characteristics of the red band position absorption valley under single fertilization conditions after enveloping line removal showed that, except for the maturity period, the red band absorption valley area (A), the red band absorption valley left area (AL) and the absorption peak symmetry (S) of winter wheat with single P application were higherthan CK, both with N and Mapplication were lower than CK. Under the combined fertilization conditions, the NMP, NP and NM of all nitrogen application combinations showed similar patterns, and the red, blue absorption depth and green reflection peak and the near-infrared spectral reflectance in the visible light range were significantly lower than CK; the spectral reflectance eigenvalue of the PM combined treatment was slightly lower than CK. Compared with CK, the characteristic value of spectral reflectance of PM combined treatment was slightly lower from the jointing stage to the heading stage; the difference between the spectral reflectance values of NM, NPM and NP treatment was small but significantly lower than CK. The CR₅₀₀ values of NM, NPM and NP treatment were 25.85%, 27.99% and 26.07% of CK; CR₆₇₀ values were 12.56%, 13.27% and 13.98% of CK; CR₅₅₀ values were 33.39%, 35.38% and 37.04% of CK, respectively. The CR₅₀₀, CR₆₇₀ and CR₅₅₀ values of PM treatment were 67.52%, 55.69% and 79.40% of CK, respectively. At grain filling stage, the peaks and valleys of each treatment were significantly weaker than those at heading stage. At maturity stage, the spectral reflectance absorption characteristics of different fertilization treatments were not significantly different, but they were significantly lower than CK. The spectral characteristics of red band absorption valley under combined fertilization conditions after enveloping line removal showed that the area of red band absorption valley (A) of the winter wheat was the largest in CK, followed by PM treatment and NM treatment.
		2020 Vol. 40 (02): 535-542 [Abstract] ( 191 ) RICH HTML PDF (4757 KB) ( 116 )

	543	Study on the Moisture Content of Dried Hami Big Jujubes by Near-Infrared Spectroscopy Combined with Variable Preferred and GA-ELM Model
		WANG Wen-xia^1,2, MA Ben-xue^1*, LUO Xiu-zhi^1,2, LI Xiao-xia^1,2, LEI Sheng-yuan^1,2, LI Yu-jie^1,2, SUN Jing-tao³
		DOI: 10.3964/j.issn.1000-0593(2020)02-0543-07
		Moisture content is an important index in the drying process of Hami big jujubes which has an important influence on its appearance, taste, storage and transportation. Therefore, in order to realize the accurate prediction of the moisture content of Hami big jujubes, GA-ELM prediction model of the moisture content of dried Hami big jujubes was studied by using Near-Infrared spectroscopy combined with variable preferred method. In order to improve the stability and prediction accuracy of the model, the effects of kernel function and the number of neurons on the GA-ELM prediction model were discussed. Various pretreatment methods were used to deal with the spectrum of the whole band. The comparison analysis denoted that the standard normal variation (SNV) method was the best. The characteristic wavelengths were screened from the range of 927.77~2 501.14 nm by combining with successive projection algorithm (SPA), the synergy interval partial least squares (si-PLS, genetic algorithm (GA) and their combination algorithms after processing of SNV. Respectively, the corresponding GA-ELM prediction model was established. The GA-ELM model with 14 characteristic wavelengths screened by SNV and SPA had the best effect while compared with the full-band GA-ELM model. Furthermore, the predicted results could be given as follows: R_c and R_p are 0.984 2 and 0.967 5, RMSEC and RMSEP are 0.006 1 and 0.007 9 while RPD is 3.678 8. The results denoted that the SNA+SPA+GA-ELM method can realize the accurate prediction of moisture content of dried Hami big jujubes and provide a reference for the application of near-infrared spectroscopy in the on-line detection of dried Hami big jujubes.
		2020 Vol. 40 (02): 543-549 [Abstract] ( 209 ) RICH HTML PDF (3159 KB) ( 77 )

	550	Detection of Chlorpyrifos Residues in Green Tea Using SERS and Rapid Pretreatment Method
		ZHU Xiao-yu¹, AI Shi-rong², XIONG Ai-hua², DU Juan¹, HUANG Jun-shi², LIU Peng², HU Xiao³, WU Rui-mei^2*
		DOI: 10.3964/j.issn.1000-0593(2020)02-0550-06
		Tea is one of the main economic-crops in China. During tea planting, the unreasonable use and abuse of pesticides lead to serious pesticide residues in tea. At present, the classical chemical laboratory methods are adopted to detect the pesticide residues in tea, but there are some shortcomings such as complex pretreatment, time-consumption and high cost in the laboratory methods. Therefore, it is urgent to study the rapid detection method of pesticide residues in tea to supervise the quality and safety of tea market. In this study, Nano Bamboo Charcoal (NBC) purifier was used to reduce the matrix-induced enhancement of tea substrate. Surface-enhanced Raman spectroscopy (SERS) was employed to detect Chlorpyrifos residues in green tea, and a rapid detection method for analyzing Chlorpyrifos residues in green tea was developed. Different doses of NBC (0, 15, 20, 25, 30 mg) were used to remove the matrix effects. The optimal dosage of NBC was obtained by comparing the purification effect and SERS of different NBC dosage. The recovery experiment was carried to verify the reliability of the optimized pretreatment method. The results showed that NBC had obvious purification effect and the green tea substrates such as pigment and so on matrix-induced enhancement were reducing when the dosage of NBC was 20 mg. It was proved that this optimized pretreatment method was suitable for decreasing the matrix-induced enhancement of tea substrate by recovery tests. Density functional theory was used to simulate the theory Raman spectrum of chlorpyrifos. The theoretical and experimental Raman spectrums of chlorpyrifos were compared and spectral peaks of their functional groups were assigned. Five characteristic peaks of Chlorpyrifos in green tea such as 526, 560, 674, 760 and 1 096 cm^-1 were found. Within the scope of the concentration of 0.28~11.11 mg·kg^-1, a line relation was developed between the peak intensity of 1 096 cm^-1 and the concentration of Chlorpyrifos of tea extract, y=0.017 5x+0.909 2 and R² was 0.986 2, indicating a good linear relationship. The average recovery rates of the method were 96.71%~105.24%, and the relative standard deviations (RSD) were between 2.36%~3.65%. The minimum detection concentration of Chlorpyrifos residues detected by this method was about 0.56 mg·kg^-1 and the detection time of a single sample was performed within 15 minutes. The result demonstrated that SERS combined with rapid pretreatment method was feasible for rapidly detecting pesticide residue in tea.
		2020 Vol. 40 (02): 550-555 [Abstract] ( 248 ) RICH HTML PDF (2984 KB) ( 65 )

	556	Estimation of Soil Organic Matter in Coastal Wetlands by SVM and BP Based on Hyperspectral Remote Sensing
		ZHANG Sen¹, LU Xia^1*, NIE Ge-ge², LI Yu-rong¹, SHAO Ya-ting¹, TIAN Yan-qin¹, FAN Li-qiang¹, ZHANG Yu-juan¹
		DOI: 10.3964/j.issn.1000-0593(2020)02-0556-06
		In recent years, although the nutrient content in the soil can be quickly obtained with the emergence of hyperspectral technology, but different soil types have great differences in the accuracy of estimation. The soil type of coastal wetland is greatly affected by the marine environment, and its hyperspectral reflectance and inland soil type will be different. This will reduce the precision in the same estimation model when inverting the nutrient content of coastal wetland soil types. With the development of marine resources and the ecological restoration of coastal wetlands in recent years, it is urgent to explore a suitable estimation model to quickly and accurately obtain nutrient content in soil. This study aimed to verify the use of visible-near infrared hyperspectral reflectivity to construct a nonlinear model so as to invert the feasibility of organic matter (SOM) in coastal wetland soils. The topsoil in the third core area of Dafeng Elk National Nature Reserve in Yancheng, Jiangsu province was taken as the investigated object. The sensitive bands corresponding to Soil Organic Matter (SOM) content were retrieved based on correlation coefficient after 5 point S-G filtering and four differential transformations of R′, (1/R)′, (1/R)″, (lgR)′ by spectral reflectance of soil samples. The estimation models of SOM by Support Vector Machine (SVM) and BP neural network were determined, and the prediction accuracy of the model was verified by using the decision coefficient R2 and the root mean square error RMSE. The research results indicated that the effective bands can be identified by S-G filtering, differential transformation and correlation coefficient method based on the original spectra of soil samples. The characteristic bands of SOM based on transformations (1/R)′ were 498~501, 1 180~1 182, 1 946, 1 947, 2 323～2 326 nm. Estimation accuracy of SVM was better than that of BP neural network for SOM in Yancheng coastal wetland. The estimation model of SOM by SVM based on (1/R)′ spectra had the highest precision, with the determination coefficients (R²) and root mean square error (RMSE) of 0.93 and 0.23. Therefore, it is suitable to use hyperspectral remote sensing to quickly estimate the nutrient contents of topsoil in coastal wetland.
		2020 Vol. 40 (02): 556-561 [Abstract] ( 202 ) RICH HTML PDF (2724 KB) ( 319 )

	562	FT-NIR Spectroscopy Quasi-Qualitative Determination Applied to the Waveband Selection for Soil Nitrogen
		GU Jie¹, CHEN Hua-zhou^{1, 2*}, CHEN Wei-hao¹, MO Li-na¹, WEN Jiang-bei²
		DOI: 10.3964/j.issn.1000-0593(2020)02-0562-05
		Nitrogen is an important component to measure soil fertility. The traditional chemical method for detecting soil nitrogen content is complex and time-consuming. Fourier transform near infrared (FT-NIR) technology is utilized for direct and rapid quantitative determinationof soil nitrogen. Nevertheless, the calibration models always perform too ideally well to believe when established by the linear analytical methods, like partial least squares (PLS). That is not convinced for the practical application in on-line detection. In this paper, we proposed a fault-tolerant mechanism to be plug-into the quantitative analytical model, transforming the FT-NIR quantitative mode into a quasi-qualitative discriminant mode. In this way, the application ability of the calibration model can be enhanced. A new discriminant method was proposed for quasi-qualitative determination by combining the interval search principal component analysis algorithm with logistic regression (iPCA-LR). The nitrogen contents of soil samples were firstly predicted based on the common PLS regression. The fault-tolerant threshold was set as three different values of 0.05, 0.10 and 0.15, respectively. The samples were marked as accurately or non-accurately discriminated according to the priori predictive values and the thresholds, so that the original quantitative calibration method was transformed into a new quasi-qualitative discriminant method. The iPCA-LR method was applied for the FT-NIR quasi-qualitative discrimination of soil nitrogen. In the same process, we also discussed the latent variable extraction based on different wavebands that were generated by tuning the waveband division number as 5, 10, 15 and 20. Some informative FT-NIR wavebands were selected with optimal discriminant accuracy. And some combination of informative wavebands were also tested. Results showed that the FT-NIR quasi-qualitative discriminant predictive accuracy varied significantly for different thresholds, but fortunately the worst optimal accuracy climbed tothe level slightly above 75%. And the test of different informative wavebands or the combination of informative wavebands output optimal calibration models with the accuracy above 90%. These results were able to meet some practical cases of online detection. In the application of FT-NIR prediction of nitrogen content in soil samples, the proposed method of iPCA-LR manage to transform the common quantitative prediction problem into the quasi-qualitative discriminant problem when combined with the priori PLS prediction. The newly proposed method deals with the disadvantages of overfitting and overidealistic modeling that always appears in common PLS quantitative analysis. In comparison, the quasi-qualitative discriminant mode is more suitable for actual cases in field detection, more beneficial for real-time application of spectroscopy technology.
		2020 Vol. 40 (02): 562-566 [Abstract] ( 192 ) RICH HTML PDF (1566 KB) ( 70 )

	567	Hyperspectral Inversion and Analysis of Heavy Metal Arsenic Content in Farmland Soil Based on Optimizing CARS Combined with PSO-SVM Algorithm
		YUAN Zi-ran, WEI Li-fei^*, ZHANG Yang-xi, YU Ming, YAN Xin-ru
		DOI: 10.3964/j.issn.1000-0593(2020)02-0567-07
		Heavy metal pollution in soil is caused by human activity factors that bring heavy metals into the soil, resulting in deterioration of soil quality and ecological environment. Heavy metals in the soil tend to accumulate, are difficult to be degraded, are highly concealed for long periods of time, and can be enriched by atmospheric circulation and food chains, ultimately threatening human life and health. Hyperspectral remote sensing technology presents a combination of image and spectrum, and can effectively identify the abnormal conditions of different elements in the soil. At present, traditional soil monitoring techniques mainly rely on laboratory-based chemical detection methods such as photometry, chemical analysis, and atomic fluorescence spectroscopy. This kind of method can test the heavy metal content of farmland soil, but the precision depends on a large amount of manpower, material resources and equipment, and its detection efficiency and promotion are lacking. In order to achieve efficient and accurate monitoring of heavy metals in farmland soils. A method of hyperspectral estimation of heavy metal arsenic (As) content in farmland soils based on particle swarm optimization (PSO) and support vector machine (SVM), which use characteristic-enhanced competitive adaptive reweighted sampling (CARS) was proposed. In the characteristic rough selection stage, the measured spectral values from the darkroom are roughly selected by CARS. In the characteristic improvement stage, First Derivative (FD), Gaussian Filtering (GF), Normalization (N) are used to improve features. In the carefully chosen stage, Pearson Correlation Coefficient (PCC) is used to obtain the correlation coefficient between different pre-treated spectral indices and soil heavy metal As. The band whose correlation coefficient has an absolute value greater than 0.6 is selected as a feature band. Finally, PSO is used to optimize the kernel parameter sigma and the normalization parameter gamma used by the SVM. The root mean square error (RMSE) is used as the fitness function, and the optimal parameters of SVM are obtained by iterating the optimal fitness. The soil of Yanwo Town in Honghu City, a typical area of Jianghan plain, was selected as the research object in this paper. The prediction results showed that the decision coefficient (R²) of the verification sets based on PSO-SVM algorithm is 0.982 3, the root mean square error (RMSE) is 0.521 6, and the mean absolute error (MAE) is 0.416 4. The main conclusions are as follows: the PSO algorithm is used to optimize the SVM parameters, and the global optimal solution can be obtained quickly by iteratively updating the individual extremum and the group extremum. Compared with the support vector machine regression (SVMR) and random forests regression (RFR), the prediction accuracy has been greatly improved; The characteristic enhanced CARS algorithm can effectively eliminate irrelevant information and improve correlation. And it selects fewer bands, simplifies the model so that efficiency is greatly improved; It can realize early warning of soil pollution, meet the needs of precision agriculture and provide data basis for ecological restoration of heavy metal contaminated land in the later period.
		2020 Vol. 40 (02): 567-573 [Abstract] ( 292 ) RICH HTML PDF (3389 KB) ( 71 )

	574	Effects of Liquid Acid on the Spectral Characteristics During Peat Humic Acid Extracted by Alkali-Extraction Acid-Precipitation Method
		LU Ya-nan¹, WANG Xiao-xia^1,2, MA Li-tong^1,2*
		DOI: 10.3964/j.issn.1000-0593(2020)02-0574-05
		Effects of different liquid acid precipitation on the spectral characteristics of humic acid extracted by alkali solution acid precipitation method were studied to select the preferable liquid acid, and analyze the mechanism of new process of peat combined production by methane fermentation and humic acid extraction. Used the peat for methane fermentation, then adopted the alkali extraction acid precipitation method by different liquid acids to extract humic acid from fermented peat residue and unfermented peat. Finally, the humic acid was characterized by Fourier transform infrared spectroscopy analysis, fluorescence spectrum analysis and E₄/E₆ analysis. The results of extracting peat humic acid showed that the yield of humic acid the PHA1 was the highest, the PHA2 was somewhat lower. The yields of humic acid from PHA1, PHA2 precipitated by nitric acid were 45.30%, 35.00%. And the purity of humic acid precipitated by nitric acid was higher, which in PHA1 was 54.83 mg·L^-1, and in PHA2 was 61.03 mg·L^-1. Considering the yield and purity, nitric acid was the best liquid acid for extracting peat humic acid by alkali-extraction acid-precipitation method. Fourier transform infrared spectroscopy analysis showed that the humic acid by nitric acid precipitation contained the most O—H groups, and there were more fatty carbon chain structure, alkyl and alcohol hydroxyl groups. The infrared spectra of humic acids obtained from PHA1 and PHA2 were similar. There was little difference between the triple bond,the cumulative double bond and hydroxyl groups of PHA1 and PHA2. The fluorescence spectrum analysis showed that the humic acid from peat had a peak value of about 450 nm, the peak value of PHA1 humic acid was the highest, and that of the PHA2 was the lowest. The peak value of phosphate acid precipitation humic acid was the highest, followed by nitric acid, indicating that the number of humic acid functional groups obtained by different liquid acid precipitation was different. The results of E₄/E₆ analysis showed that the E₄/E₆ ratio of PHA1 humic acid was higher and the degree of aromatic condensation was lower. After fermentation, the E₄/E₆ of PHA2 decreased, the degree of aromatic condensation was higher. Therefore, methane fermentation could consume more humic acid with low aromatic condensation degree, but the complex aromatic structure could not be degraded, and the aromatic condensation degree of extracted humic acid was obviously increased. Study on the characteristics of the spectroscopic changes in the extraction of peat humic acid by alkali-extraction acid-precipitation method showed that different liquid acids and methane fermentation have obvious effects on the yield, purity and functional groups of peat humic acid by alkali-extraction acid-precipitation method. The process of co-production of methane and humic acid from peat is feasible.
		2020 Vol. 40 (02): 574-578 [Abstract] ( 225 ) RICH HTML PDF (1931 KB) ( 48 )

	579	Design and Application of Reflectance Measurement System for Sea Bottom in Optically Shallow Water
		ZENG Kai^{1, 2, 3}, XU Zhan-tang^{1, 2*}, YANG Yue-zhong^{1, 2}, ZHANG Yu^{1, 2, 3}, ZHOU Wen^{1, 2}, LI Cai¹, HUANG Hui⁴
		DOI: 10.3964/j.issn.1000-0593(2020)02-0579-07
		The spectral reflectance of the sea bottom plays an important role in radiative transfer signal of optically shallow water, affecting the spectral characteristics of water-leaving radiance in sea surface. Therefore, the precise information of the substrate is particularly significant in the study of the coastal remote sensing. In order to provide an accurate and convenient on-site information extraction of optically shallow water bottom, a set of sea bottom reflectance measurement system was designed, which is characterized by designing a reference whiteboard that can be freely stretched and rotated in order to eliminate the influence of the absorption attenuation of water between the probe and the target. And the design of the dual optical path for simultaneous measurement solved the interference of the spatial and temporal variability of water optical properties. Optical in-situ bottom reflectance of various substrates include corals, seagrass, sediment and beach collected in Sanya Coral Reefs Reserve during September 3—8, 2018 were used to study the feasibility of the system. As expected, the various types of substrate have distinct spectral separability. The spectral reflectance feature of the sand bottom and onshore beach are different over the range 580～700 nm, which suggests that the absorption and scattering of water and the presence of microalgae strongly affect the measurement of under water radiation. The difference between seagrass and coral is obvious that there is positive reflectance feature at 540～600 nm of seagrass, whereas the typical characteristic of coral is that there are three positive features around 575, 600 and 650 nm. In addition, the three carbonate substrates of coral, sand bottom and sandy beach have reflection peaks at 395, 430, 490 and 520 nm, and a small absorption peak at 485 and 585 nm, while seagrass has an absorption peak at 395, 430, 490 and 520 nm, a reflection peak at 485 and 585 nm. The above data results laid the foundation for the future extraction of benthic composition information, and also confirmed the reliability and real validity of the system design.
		2020 Vol. 40 (02): 579-585 [Abstract] ( 274 ) RICH HTML PDF (3559 KB) ( 73 )

	586	Ship Target Detection Based on Infrared Polarization Image
		GONG Jian, LÜ Jun-wei, LIU Liang, QIU Rong-chao
		DOI: 10.3964/j.issn.1000-0593(2020)02-0586-09
		As an important method detecting ship targets, infrared imaging system plays a vital role in military reconnaissance. In the face of complex background, bad weather environment, etc., the local contrast of target and background is low, which causes that the performance indicators of infrared system such as detection accuracy and recall rate are seriously affected. Considering the above problems, the research on ship target detection method based on infrared polarization image is carried out. Through the long-wave uncooled infrared polarization image acquisition system, 86 sets of infrared polarization images with 4 polarization directions (0°，45°，90°，135° ) were collected, and 309 ship targets were sampled. For the infrared polarization image with different polarization directions, the target and background local contrast of the infrared intensity/polarization image in the same scene, it was found that the difference between the sea surface and the ship target polarization characteristics can effectively improve the target and background local contrast. In the forward-looking infrared image, the ship target is usually located near or below the sea-sky line, but the complex background and weather and other factors have a great influence on the detection of the sea-sky line in the infrared image. For this reason, the infrared polarization image sea-sky line detection method is proposed. Gaussian filtering is used to eliminate the local extremum in the histogram of polarization image. According to the difference of the polarization characteristics between the sea and the background, the sea-sky line is detected by the bimodal method threshold segmentation. Finally, the sea-sky line is detected by the Hough transform, and the sea surface is segmented as the target candidate region. Aiming at the problem that the infrared polarization image is seriously interfered by sea clutter, the sea clutter background suppression algorithm is proposed. The background suppression and distance weighting method are used to suppress the complicated sea clutter background in the polarization image. Finally, the ship targets are detected according to the MSER algorithm, after they are constrained basing on the characteristics of the ship target. The ship target detection experiment is carried out on 86 sets of infrared polarization images. The proposed method can effectively overcome the interference of complex background, sea clutter and other factors to accurately detect the sea-sky line, and the detection precision ratio and the recall ratio are 93.2% and 95.7%, respectively, which is better than the infrared ship target detection method, especially in the scene with the low contrast of infrared image. Obviously, the detection precision ratio and the recall ratio increase by 46.5% and 16.4%, respectively. The research results show that considering the difference of polarization characteristics between the ship target and the background in the infrared polarization image can effectively improve the local contrast between the target and the background, which is conducive to accurately detecting the sea-sky line, improving the ship detection precision ratio and the recall ratio, and complex background. It has strong adaptability to complex background and bad weather, which has great application value in military applications. This study has great significance for the development of ship target detection technology in the infrared band.
		2020 Vol. 40 (02): 586-594 [Abstract] ( 264 ) RICH HTML PDF (5903 KB) ( 102 )

	595	Detection of Saturated Fatty Acid Content in Mutton by Using the Fusion of Hyperspectral Spectrum and Image Information
		WANG Cai-xia, WANG Song-lei^*, HE Xiao-guang, DONG Huan
		DOI: 10.3964/j.issn.1000-0593(2020)02-0595-07
		In order to explore the feasibility of detection of saturated fatty acids (SFA) in muttons by using hyperspectral imaging techniques (400-1000 nm), this paper proposed a prediction model based on the fusion of characteristic spectral information and image texture features, realizing the rapid detection and distribution visualization of SFA content in mutton. Firstly, the binary mask image was successfully determined by the segmentation of a certain threshold, and Region of Interest (ROI) in the sample of mutton was determined by binary mask image. SPXY methods were used for dividing the sample set, preprocessing of correlation spectral information. And continuous projection algorithm SPA,VCPA and β weight were used to select wavelength of the spectrum. The image textural information was described by taking the principal component image and the gray level co-occurrence matrix (GLCM) algorithm of the mutton samples. The partial least squares regression (PLSR) and the least squares support vector machine (LS-SVM) prediction model built based on the characteristic wavelength, textural information, textural combined with characteristic wavelength were compared and analyzed, respectively. Preprocessing of original spectral data using five methods without pretreatment. The correlation coefficients of calibration set and prediction set were 0.921 and 0.875, respectively. Compared with the original spectrum, the correlation coefficients of calibration set and prediction set were increased by 0.001 and 0.04, and the root mean square errors were 0.244 and 0.268, respectively. Compared with the original spectrum, the correlation coefficients of calibration set and prediction set were reduced by 0.003 and 0.06 respectively. This paper extracted characteristic wavelengths of the spectral from the pre-processed date using SNV, SPA, VCPA and β coefficient methods extracted 12, 10 and 9 characteristic wavelengths, respectively. Five principal component images were selected based on PCA, and four textural feature variables (energy, entropy, homogeneity and correlation) were extracted by the first principal component image, with which the most information in the 0, 45°, 90°, and 135° directions, respectively. The performance of PLSR and LS-SVM models based on characteristic wavelengths extracted by SPA method was better. The correlation coefficients of PLSR model correction set and prediction set were 0.8849 and 0.8807, and the root mean square errors were 0.300 1 and 0.260 6, respectively. The correlation coefficients of LS-SVM model correction set and prediction set were 0.898 7 and 0.892 6, and the root mean square errors were 0.276 7 and 0.247 6, respectively. In the atlas information fusion model, the correlation coefficients of correction set and prediction set of PLSR model were 0.907 1 and 0.907 8 respectively, which were 0.02 and 0.03 higher than that of characteristic spectral model, and the root mean square errors were 0.3269 and 0.2992, respectively, which were 0.03 and 0.04 higher than that of characteristic spectral model; The correlation coefficients of LS-SVM model calibration set and prediction set were 0.920 6 and 0.894 6, respectively, which were 0.02 and 0.002 higher than that of characteristic spectral model, and the root mean square errors were 0.251 9 and 0.245 8, respectively, which were 0.02 and 0.002 less than that of characteristic spectral model. Compared with other pretreatment methods, the performance of the model constructed by the SNV was better than others; The 12 characteristic wavelengths were extracted by SPA method to simplify the spectral dimension and improve the performance of the model. The optimal method of characteristic spectral modeling was SPA-LS-SVM. Compared with the characteristic spectral model, the correlation coefficient of the model increased less, which indicated that the image texture information carried less effective information, and the correlation between these information and saturated fatty acid content in Mutton needed to be further studied. The prediction performance based on the textural combined with characteristic wavelength information fusion model was the best, and the texture information model was the worst. Thus, the SFA content of could be calculated by SPA-PLSR model, and the visual distribution map of SFA content in mutton samples was plotted by using pseudo-color drawing.
		2020 Vol. 40 (02): 595-601 [Abstract] ( 198 ) RICH HTML PDF (3332 KB) ( 66 )

	602	A New Method for Predicting Soil Moisture Based on UAV Hyperspectral Image
		GE Xiang-yu^{1, 2, 3}, DING Jian-li^{1, 2, 3*}, WANG Jing-zhe⁴, SUN Hui-lan⁵, ZHU Zhi-qiang⁶
		DOI: 10.3964/j.issn.1000-0593(2020)02-0602-08
		Soil moisture content (SMC) is a key factor in biogeochemical and atmospheric coupling processes. It plays an important role in areas such as agriculture, ecology and environment in arid region. Compared to the spaceborne remote sensing system，UAV platform with hyperspectral sensors possess higher spatial resolution and maneuverability. With UAV (Unmanned Aerial Vehicle) being increasingly popular, it offers brand new platform of remote sensing. This platform realizes the goal that quickly and quantificationally monitor object in the area. Moreover, hyperspectral sensors contribute to remote sensing when they enrich high dimensional and nanoscale data source. However, there still lacks a standardized research scheme for estimation of UAV by hyperspectral Remote Sensing. In this study, we obtained UAV hyperspectral image from a typically dry-farming region lying in Xinjiang Uygur Autonomous Region. Hyperspectral image was pretreated using six methods of pretreatment, including first-derivative (FDR), second-derivative (SDR), continuum removal (CR), absorbance (A), first-derivative absorbance (FDA) and second-derivative absorbance (SDA). From pretreatment foundation, four types spectral indices were proposed containing the Difference Index (DI), the Ratio Index (RI), the Normalization Index (NDI) and the Perpendicular Index (PI). And the rationality of the spectral index was discussed from the spectral mechanism. Considering the superiority of ensemble learning algorithm rising in recent years, the SMC estimation model was constructed via Gradient Boosted Regression Tree (GBRT), Random Forest (RF) and eXtreme Gradient Boosting (XGBoost). In these models, 28 appropriate spectral indices were used as independent variables and 70 SMC measured values as response variables. Spectral indices were ranked via importance based on ensemble learning model analyzed and compared to make a more comprehensive evaluation. The result indicated that: (1) atmospheric disturbance and soil background were eliminated effectively throughvarious pretreatment schemes and spectral indices. Pretreatment scheme A highlighted more spectral information and PI correlation was significant. (2) Optimum spectral index was A_PI (\|r\|=0.773) that the ranking of importance ranks first, and the correlation coefficient \|r\| is the highest, and it had excellent performance in both linear and nonlinear relationships. (2) XGBoost prediction model was outstanding in three ensemble learning models, and it yielded the highest R²_val, the lowest RMSP and the best RPD (R²_val=0.926，RMSEP=1.943 and RPD=2.556). The ranking of the predictive performance was XGBoost>RF>GBRT. This proved that this scheme was effective in digital mapping in arid region. In conclusion, there is potential high accuracy for UAV imagery based on hyperspectral imagery. This study afforded an effective method for predicting SMC in arid regions, and it provided a new perspective for quickly and easily monitoring object attributes and it proposed an alternative solution for predicting soil moisture. Ultimately, our program is supporting better management and conservation strategies for precision agriculture and ecosystems in arid regions.
		2020 Vol. 40 (02): 602-609 [Abstract] ( 290 ) RICH HTML PDF (7615 KB) ( 170 )

	610	XRD and NIR Analysis on Minerals of Fault Sections from Dabaoshan Polymetallic Deposit, Guangdong
		WANG Guo-qiang^{1, 2, 3, 4}, CAO Jian-jin^{1, 2, 3, 4*}, DENG Yong-kang^{1, 2, 3, 4}, LIU Xiang^{1, 2, 3, 4}
		DOI: 10.3964/j.issn.1000-0593(2020)02-0610-06
		The Dabaoshan polymetallic deposit is a typical metal-sulfide deposit, and the metallogenic elements of economic value include copper, iron, lead, zinc, tungsten, molybdenum, etc. Mineralization of the deposit is closely related to magmatic and metamorphic hydrothermal alteration. Faults widely developed in the mining area provide the pathway of hydrothermal ore-forming solution migrating and the available ore-forming space. Moreover, faults can transform ore bodies after mineralization. In this study, 8 samples were collected from three fault sections in Dabaoshan Polymetallic Deposit, and the sample types include fault gouges, ore-bearing veins and altered wall-rocks. Then, all the samples were comprehensively analyzed by XRD analysis method and NIR analysis method. Varity of altered mineral assemblages were identified by spectral analysis, include beresitization (quartz, sericite, pyrite and chalcopyrite, etc), skarnization (Diorite, actinolite, garnet, etc) and propylitization (chlorite, carbonate, pyrite, etc). The altered mineral assemblages indicate that the rocks in mining area had undergone a variety of alteration types. In the fault gouges samples, we can identify minerals of altered wall rock and ore-bearing veins, as well as, the oxidation and weathering products such as metal oxides, sulfates (tenorite, antlerite, krausite and kalunite) and clay minerals (illite, montmorillonite, kaolinite and talc, etc). The oxidation and weathering minerals in the gouges indicate that the faulting provides favorable conditions for the physical and chemical weathering of rocks. In addition, the crystallinity parameters of dolomite minerals (IC=peak intensity of Al-OH (2 200 nm)/peak intensity of H₂O (900 nm)) were calculated based on Near infrared spectrum of altered surrounding rocks in three fault sections. In altered wall rock samples, 637 Platform: IC₁=0.078 71/0.037 76≈2.08; 793 Platform: IC₂=0.108 8/0.014 8≈7.35；817Platform: IC₃=0.098 6/0.039 1≈2.52. Obviously, the crystallinity of the altered surrounding rock of Platform 793 is significantly higher than the other two platforms. The higher crystallinity means the higher temperature of hydrothermal activity. Therefore, it can be speculated that the sampling location of altered rocks on the Platform 793 may be closer to the hydrothermal activity center. In conclusion, the combination of XRD and NIR spectroscopy analysis methods is helpful for the identification of alteration types and the analysis of mineral crystallinity, which will provide more abundant geological information for the study and the exploration of mineral deposits.
		2020 Vol. 40 (02): 610-615 [Abstract] ( 200 ) RICH HTML PDF (4743 KB) ( 69 )

	616	Study on Preparation Stage and Mechanism of Modified Desulfurization Ash-Based Eco Rubber by X-Ray Diffraction
		ZHANG Hao^1,2, ZHANG Lei¹, LIU Xiu-yu¹
		DOI: 10.3964/j.issn.1000-0593(2020)02-0616-06
		As main by-product of semi-dry desulfurization technology, desulfurization ash is very difficult to be utilized and there is a high -cost for its utilization. It cannot be disposed through direct stacking and landfill, otherwise it will cause environmental pollution and waste of potential resources. Rubber is a kind of widely used polymer material, of which the mechanical properties, machining properties and filling capacity can be improved by using large amounts of fillers during preparation. Carbon black and white carbon black, as the commonly used rubber packing, can only be prepared by complicated process, which always leads to large consumption of energy and resources, resulting in higher costs. Thus, the development of desulfurization ash into low-cost inorganic rubber fillers has become one of the main methods to achieve resource sustainable development and enhance economic performance by high value-added utilization of solid wastes and cost reduction of fillers in rubber industry to a great extent, respectively. The desulfurization ash is organic while rubber is inorganic. Therefore, chemical modification is necessary to be conducted for desulfurization ash to weaken incompatibility of interface(organic/inorganic) between them. Based on the research results obtained in the early stage of this research group, in this paper, modified desulfurization ash was innovatively used to replace part of carbon black to prepare modified desulfurization ash-based eco rubber. Production materials in every stage of preparation process of modified desulfurization ash-based eco rubber were measured by XRD, such as preparation stage of styrene butadiene rubber mixer glue, preparation stage of modified desulfurization ash-based eco rubber mixer glue and preparation stage of modified desulfurization ash-based eco rubber. The preparation process of styrene butadiene rubber mixer glue, preparation process of modified desulfurization ash-based eco rubber mixer glue and preparation process of modified desulfurization ash-based eco rubber were revealed at the microscopic level, respectively, in order to explain the bonding mechanism of styrene butadiene rubber mixer glue and modified desulfurization ash in vulcanization process. Meanwhile, microstructures of styrene butadiene rubber mixer glue and modified desulfurization ash-based eco rubber mixer glue were tested by SEM so as to further support the obtained mechanism. The results showed that after adding modified desulphurizing ash to styrene butadiene rubber, modified desulfurization ash-based eco rubber’ maximum torque F_max drops dramatically, minimum torque F_L remains stable, △F=F_max-F_L is significantly reduced, meanwhile scorch time and optimum cure time are shortened. Vulcanization induction stage is 0~387 s, vulcanization reaction stage is 387~1 586 s and vulcanization flat stage is 1 586~1 800 s. Form the non- crosslinking network structure in vulcanization induction stage, form the basic crosslinking network structure in early of vulcanization reaction stage, improve the crosslinking network structure in later of vulcanization reaction stage and maintain the crosslinking network structure in vulcanization flat stage. It aims to provide some theoretical basis and technical support for high value-added desulphurization ash resource utilization.
		2020 Vol. 40 (02): 616-621 [Abstract] ( 181 ) RICH HTML PDF (2347 KB) ( 47 )

	622	Standardized Cross-Validation and Its Optimization for Multi-Element LIBS Analysis
		ZHONG Qi-xiu^{1, 2, 3}, ZHAO Tian-zhuo^{1, 2, 3*}, LI Xin^{1, 2, 3}, LIAN Fu-qiang^{1, 3}, XIAO Hong^{1, 3}, NIE Shu-zhen^{1, 3}, SUN Si-ning^{3, 4}, FAN Zhong-wei^{1, 2, 3}
		DOI: 10.3964/j.issn.1000-0593(2020)02-0622-06
		Cross-validation is a statistical analysis method used to verify the performance of the model, which avoids the over-fitting caused by the coincidence of the training set and the test set. The average of the Root Mean Square Error of Cross-Validation (RMSECV) is often used for cross-validation to characterize the analytical accuracy of multiple elements. However, for the case of Laser-Induced Breakdown Spectroscopy (LIBS) applied to multi-element analysis, it is found that the RMSECV of each element can be approximately expressed in a linear relationship with its concentration rang in the sample set. Since the concentration ranges of different elements in the sample set vary greatly, the difference in RMSECV between different elements is large. In the experiment, the difference between the concentration range of C and Cr in the sample set is 28.11 times, and the RMSECV difference is 8.96 times. It is found that during the optimization process, the average RMSECV may not reflect the trend of analysis accuracy of most elements, when it is too sensitive for individual elements. In order to reduce the sensitivity difference of the average RMSECV to different elements and to more fully characterize the analysis accuracy of multi-element, this paper proposes a multi-element RMSECV standardized method that divides the RMSECV of each element by the concentration range of the element in the sample set. The concept of Standardized Root Mean Square Error of Cross-Validation (SRMSECV) is therefore introduced. LIBS detection is affected by uncertain factors such as fluctuations in measurement conditions (such as laser pulse energy, vibration, etc.), which will generate abnormal spectra and have a negative impact on analysis accuracy. The median area of all spectra of the same sample is selected as the center and a spectral area interval is selected. The spectra whose area is outside the interval are discarded and the remaining spectra are used for quantitative analysis. In order to improve the multi-element analysis accuracy by filtering out the abnormal spectra, the spectral data is pre-processed by spectral area screening. On this basis, the quantitative analysis of the multi-line internal standard method for 14 elemental components in 10 Ni-based alloys in a 0.5 Pa vacuum environment was carried out. After standardization, the relative standard deviation (RSD) of RMSECV of each element decreased from 68.7% to 48.9%, and the maximum difference of RMSECV between elements decreased from 8.96 times to 3.93 times. It showed that the average SRMSECV can comprehensively characterize the analysis accuracy of multi-element, which is beneficial to the automatic optimization of calibration curve. Under the optimized area screening span, the average value of the coefficient of determination (R²) and the average SRMSECV of the 14 elements were improved to some extent, which proved the value of spectral area screening for improving the accuracy of multi-element analysis.
		2020 Vol. 40 (02): 622-627 [Abstract] ( 199 ) RICH HTML PDF (1787 KB) ( 64 )

	628	Quick Classification of Pottery from Lingjiatan Site (3000BC) Based on Laser Induced Breakdown Spectroscopy and Principal Component Analysis
		WU Wei-hong¹, YAO Zheng-quan², WANG Jing³, ZHANG You-yin^4,5, ZHU Jian^3*
		DOI: 10.3964/j.issn.1000-0593(2020)02-0628-04
		For applying the Laser Induced Breakdown Spectroscopy technology to the ancient pottery(Lingjiatansite，3000BC, Anhui, China) research, the goal and aim is for quick identificationand classification of the different types of ancient ceramic wares. Lingjiatan Site, located in Hanshan County, Maanshan City, Anhui Province, China，is a large late Neolithic settlement in southern China. A large number of fine jade articles, stone ware and pottery have been unearthed from the site. It is an important site!for studying the origin of earlyChinese civilization. Therefore, the study of its pottery is of great cultural and historical significance. After LIBS analysis, using the principal component analysis to process the data and give the reference to the classification workof pottery. The results show that different temper in body of pottery will affect the characters of spectrum and the PCA could give the classification group based on those spectra discrepancies. In the other hand, due to the consideration of statistical analysis, the abnormal data interference such as background noise is purposefully reduced and classified, and the characteristic spectral lines are extracted based on the attribution of the element spectral lines, thus realizing the purpose of rapid classification by multivariate statistical analysis. The results show that compared with pure argillaceous pottery, the samples of temper of plant pottery and some fine sand temper have well discrimination in LIBS spectral characteristics and can be effectively distinguished. According to the actual situation, other types of processing and materials need to be judged comprehensively with other means. This work indicates that the LIBS and PCA will be suitable and useful tools for ancient ceramics research.
		2020 Vol. 40 (02): 628-631 [Abstract] ( 221 ) RICH HTML PDF (2009 KB) ( 77 )

	632	Determination of Cuprous in Biological Samples by Liquid-Liquid Extraction-GFAAS
		ZHANG Yuan, WU Peng, LI Hui, LUO Hong-jun, LUO Wen-hong, LIN Zhe-xuan^*
		DOI: 10.3964/j.issn.1000-0593(2020)02-0632-05
		A method for the determination of cuprous [Cu(Ⅰ)] in biological samples by liquid-liquid extraction-inductively coupled plasma mass spectrometry (ICP-MS) was developed. Serum and cell homogenate, cell membrane components were deproteinized with trichloroacetic acid, then the supernatant was mixed with a glycine- sodium hydroxide (NaOH) buffer (pH 12.5) to obtain a mixture with pH of 9. Then 1 000 μL of 0.05% 2,2’-biquinoline dissolved in N-pentanol was added and vortexed for 1 min. After static layering, 500 μL of the organic layer was collected in a 2 mL Teflon digestive tube, and the organic solvent was evaporated in an oven at 95 ℃. After digestion with nitric acid and hydrogen peroxide, the sample solution was subjected to inductively coupled plasma mass spectrometry and the data of cuprous content were obtained. The detection limit of this method was 0.04 μg·L^-1, with relative deviation being less than 5%. The recovery was 95% to 102%. Then the method was applied to determine Cu(Ⅰ) of serum from cervical cancer patients and several types of water. The results showed that serum Cu(Ⅰ) was higher in cervical cancer patients than that in normal controls. Cuprous ions could not be detected in tap water, Nongfu Spring water, and urine. While, Cuprous ions but not divalent copper ions could be detected in cytosol and cell membrane. This method could detect trace Cu(Ⅰ) ions in the presence of 10 times concentration of Cu(Ⅱ) ion without interference.
		2020 Vol. 40 (02): 632-636 [Abstract] ( 220 ) RICH HTML PDF (2321 KB) ( 50 )

	637	Analysis of Mortar Composition of Shanhe Weir and Yangtou Weir in Hanzhong City
		ZHANG Bao-xia¹, WEI Guo-feng^1*, HU Song-mei², GENG Qing-gang², YANG Wu-zhan², ZHENG Xiao-ping³
		DOI: 10.3964/j.issn.1000-0593(2020)02-0637-06
		Three weirs (Shanhe weir, Wumen weir and Yangtian weir) in Hanzhong city, Shaanxi province was successfully listed in the world irrigation engineering heritage list in October 2017. Among them, Shanhe weir is the earliest irrigation project in Hanzhong region. During the hydrological archeological surveyin the 1980s, it was found that the Shanheyan masonry was made of wooden stake masonry as a skeleton and tri-soil composed of yellow mud, sand, lime, Tung oil and glutinous rice pulpas the filler material. In this study, mortar samples from the east embankment and Yangtou weir of Shanhe weir were detected by X-ray diffraction analysis (XRD), fourier transform infrared spectrometry (FTIR), thermal analysis, scanning electron microscopy, petrographic analysisand ¹⁴C dating technology to determine the date, composition and scientific mechanism. The result of ¹⁴C dating of the stone strips of the East dike ofShanheweir was that they could date back to 1150 to 1226 AD, which indicated that the date of Shanhe weir could be be date back to the Southern Song Dynasty. Based on the results of XRD and FTIR, the inorganic components of the East dike and rammed earth and Yangtouweir were mainly calcite, quartz and a small amount of feldspar. Infrared analysis(FTIR) and thermal analysis showed that some organic matter appears to be added to the clay and rammed earth. Combined with the literature, the organic matter was likely to be glutinous rice pulp. The heat analysis results showed that the exothermic peak above 800 ℃ was the characteristic peak of calcium silicate hydrate, and it was assumed that lime reacts with water to produce calcium silicate. Calcium silicate can harden better in water or in moist environments. It is the main reason why water Conservancy projects can be preserved for thousands of years. The results of electron microscopy showed that the non-carbonized decalcitrate(Ca(OH)₂) in the sample was dehydrated to form a hydroxycalcite crystal. In addition, the organic matter added to the mortar and the slow carbonization of the mortar are helpful to enhance the self-repair ability and weathering ability of the mortar masonry and extend the service life of the water Conservancy project. This work uses various natural science means to carry out scientific research on the ash pulp ofShanhe Weir mortar, which is helpful to find out the composition and scientific mechanism of the mortar material of water Conservancy project, lay a scientific foundation for the protection and repair of water Conservancy project heritage such as Shanhe Weir, and provide useful enlightenment for the improvement and enhancement of modern water Conservancy materials.
		2020 Vol. 40 (02): 637-642 [Abstract] ( 209 ) RICH HTML PDF (3024 KB) ( 38 )

	643	Spectral Signal Denoising Algorithm Based on Improved LMS
		ZHENG Guo-liang, ZHU Hong-qiu^*, LI Yong-gang
		DOI: 10.3964/j.issn.1000-0593(2020)02-0643-07
		Under the high ratio of concentration, the spectral absorption signals detected by micro-spectrometer are easily disturbed by external environment and internal circuit noise. The spectral absorption signals of trace multi-metal ions are also weak and easily masked by noise, which seriously affects the accuracy and repeatability of the results of spectral quantitative analysis. Therefore, denoising of spectral absorption signal is required. However, the selection of some key detail parameters of most denoising algorithms not only needs to be tested and verified by repeated experiments, but also depends on the experience of the researchers’ experience and the characteristics of the signals. In view of the problem that these key parameters have great influence on filtering and are difficult to select, an improved LMS adaptive denoising algorithm based on sigmoid error constraints is proposed in this paper. Firstly, the principle of standard LMS algorithm is analyzed, and the standard LMS filter structure is optimized and improved in combination with the data interference of the micro spectrometer. Meanwhile, due to the characteristics with error constraints, the sigmoid function is used to optimize the error calculation module, reducing the algorithm sensitivity of noise. Then, for the improved least mean square error loss function is a nonconvex function, this paper proposes a kind of cross-entropy loss function, which transforms the nonconvex problem into a convex optimization problem. When using the gradient descent method to gradually minimize the loss function, it ensures that the local optimal solution is also the global optimal solution. The Adam algorithm is also used to adaptively adjust the learning rate factor, which ensures the fast convergence speed of the algorithm. Finally, in order to verify that the improved adaptive denoising algorithm has strong denoising performance, the proposed method is verified by cross-validation. The measured spectral absorption signals of four kinds of multi-metal ion mixed are used to test the performance of the proposed denoising method. The experimental results show thatwhen processing absorption spectrum signals with low signal-to-noise ratio (SNR), compared with the standard LMS algorithm, SG denoising algorithm, wavelet soft threshold algorithm and wavelet hard threshold algorithm, the SNR of the proposed method is increased by 9.225%, 19.678%, 7.591%, 12.042%, respectively, the mean square error of the proposed method is reduced by 59.647%, 63.070%, 53.600%, 57.793%. The proposed method can not only effectively remove the influence of irrelevant noise, but also retain some important detail features in the spectral signal, and avoid the subjective selection of parameters. In conclusion, it provides a new solution to analyze the spectral signal of low SNR.
		2020 Vol. 40 (02): 643-649 [Abstract] ( 247 ) RICH HTML PDF (4249 KB) ( 86 )

	650	Weak Coupling Properties of Optical Tamm State in Metal-DBR-Metal Structure
		LI Pei-li, GAO Hui, LUAN Kai-zhi, LU Yun-qing
		DOI: 10.3964/j.issn.1000-0593(2020)02-0650-06
		Weak couplingeffect between two optical Tamm states (OTS) in metal-DBR-metal (M1-DBR-M2) structure will occur when the periodicity of distributed Bragg (DBR) in theM1-DBR-M2 is relatively large. By studying the reflection spectrum and the distribution of the electric field of the intrinsic wavelength of OTS under the condition of weak coupling of OTS, the intrinsic wavelength, reflectivity and optical tunneling effect of OTS are revealed. The results show that the intrinsic wavelength of OTS is affected by the thickness of the metal film M1 under the weak coupling condition, while the thickness of the metal film M2 has no effect on the intrinsic wavelength of OTS. Although only the OTS1 at the M1-DBR interface can be excited, the local field phenomenon is not only localized at the M1-DBR interface. The light can go through the DBR and be localized to the DBR-M2 interface, which is optical tunneling effect. The optical tunneling effect is related to the intrinsic wavelength detuning between two OTS. The smaller the detuning of the intrinsic wavelength is, the stronger the tunneling effect is. The intrinsic wavelength detuning between two OTS also affects the local intensity of light in the M1-DBR-M2 structure. The smaller the detuning of the intrinsic wavelength is, the stronger the local phenomenon of light is, and the smaller the reflectivity at the concave peak in the reflection spectrum is.
		2020 Vol. 40 (02): 650-655 [Abstract] ( 203 ) RICH HTML PDF (6380 KB) ( 45 )

	656	Research on Classification of Dwarf Nova Based on Deep Architecture Network
		ZHAO Yong-jian, GUO Rui, WANG Lu-yao, JIANG Bin^*
		DOI: 10.3964/j.issn.1000-0593(2020)02-0656-05
		Dwarf nova (DN) is a special and rare class of semi-contiguous binary star. To discovery more DNs is significant for the further study of matter transfer theory. It also has been profound for understanding the evolution of close binary stars. It is a research hot spot to extract features of celestial spectra and then classify them by deep learning. Traditional auto-encoder is a classical neural network model with only one hidden layer. However, its coding ability is limited and data representation learning ability is insufficient. Broadening the depth of the neural network with modularity can make the network learn features of the celestial spectrum successively. High-level features can be obtained through gradual abstract learning of underlying features so as to improve the spectral classification accuracy. In this paper, a deep feedforward stack network is constructed consisting of an input layer, several hidden layers and an output layer on the basis of auto-encoder. This network with multi-layer perceptron architecture is utilized to process massive spectral data sets. It excavates the depth structure features hidden in the spectra and realizes the accurate classification of DN spectra. Parameters set for the network with deep architecture will seriously affect the performance of the constructed network. In this paper, the optimization of network parameters is divided into two processes: hierarchical training and inverse propagation. The preprocessed spectral data first enter the network from the input layer, and then the network parameters are trained layer by layer with the auto-encoder algorithm and weight sharing policy. In the reverse propagation stage, the initial sample data are input into the network again, and the network is initialized with the weights obtained from the hierarchical training process. Then the local optimization training results of each layer are fused and the network parameters are adjusted according to the set output error cost function. Hierarchical training and inverse propagation are operated repeatedly until the global optimal network parameters are obtained. Finally, the last hidden layer is adopted as the reconstruction layer to connect the support vector machine classifier, and the feature extraction and classification of DNs are realized. In the process of network parameter optimization, the idea of mean network is utilized to make the output of network hidden layer unit attenuate according to dropout coefficient. The reverse propagation algorithm is adopted to fine-tune the entire network to prevent depth overfitting in the network. Such operation can reduce to extract duplicate feature caused by mutual moderation of hidden layer neurons, and improve the generalization ability. The distributed multi-layer architecture of the network can provide effective data abstraction and representational learning. The feature detection layer can learn the depth structure features implicitly from the unlabeled data, and effectively characterize the nonlinearity and random fluctuation of spectral data, thus avoiding the explicit extraction of spectral features. The network shows strong data fitting and generalization ability. Weight sharing between different layers can reduce the interference of redundant information and effectively resolve the risk that the traditional multi-layer architecture network is prone to fall into the local minimization of weight. Experiments show that that of the accuracy of the deep architecture network in DNs classification is 95.81%, higher than the classical LM-BP network.
		2020 Vol. 40 (02): 656-660 [Abstract] ( 228 ) RICH HTML PDF (998 KB) ( 61 )

	661	Synthesis, Spectroscopic Characterization and Thermogravimetric Analysis of Cr(Ⅱ), Cu(Ⅱ), Zn(Ⅱ) and Mg(Ⅱ), Captopril Coordination Compounds
		Asma S. Al-Wasidi¹, Nawal M. Al-Jafshar¹, Amal M. Al-Anazi¹, Ahmed M. Naglah^{2, 3*}, Robson F. de Farias⁴, Claudio Airoldi⁵, Moamen S. Refat^6,7
		DOI: 10.3964/j.issn.1000-0593(2020)02-0661-04
		In this work, we have reported the synthesis and spectroscopic characterization of captopril (Cap) coordination compounds: Cu(Cap)·2H₂O, Cr(Cap)·H₂O, Zn(Cap)·3H₂O and Mg(Cap)₄. Herein, it is worthily mentioned that the FTIR spectroscopic technique was employed to recognized the nature of coordination between captopril ligand and copper, chromium, zinc and magnesium(Ⅱ) metal ions. In view of the infrared spectroscopic tool, the copper(Ⅱ) metal ion coordinated toward captopril drug ligand through sulfur atom of SH group dependent on the absent of stretching vibration band of —SH. Based on this result, the stretching motion of ν_a(COO) shifts clearly indicates that Cu²⁺, Cr²⁺, Zn²⁺ and Mg²⁺ the carboxylic group is employed as coordinative site for all compounds as a metal-ligand coordinative bond. As a general behavior, it is verified that the coordination compound thermal stability (considering the release of captopril molecules, not the release of water molecules) is affected by the metal cation radius: minor radius is associated with higher thermal stability, probably due to a higher metal-captopril bond dissociation enthalpy.
		2020 Vol. 40 (02): 661-664 [Abstract] ( 191 ) RICH HTML PDF (933 KB) ( 72 )

　CopyRight © OFFICE OF SPECTROSCOPY AND SPECTRAL ANALYSIS
　Address: NO.76 Collage South Road of Beijing 　Postalcode:100081
　Tel. (010)62181070　E-mail:chngpxygpfx@vip.sina.com
　Support by Beijing Magtech Co.ltd　E-mail:support@magtech.com.cn