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2021 Vol. 41, No. 08 Published: 2021-08-01

	2325	Development and Application of an Automated Program for Photodissociation Spectroscopy Study Based on a FT ICR Mass Spectrometer
		ZHANG Kai-lin^{1, 2}, ZHOU Min³, SHI Ying-ying², LI Shu-qi², MA Li-fu¹, ZHANG Xian-yi^3, WANG Yan¹, KONG Xiang-lei^{2, 4}
		DOI: 10.3964/j.issn.1000-0593(2021)08-2325-07
		Photodissociation spectroscopy plays a significant role in studying the structure and kinetics of species in the gas phase. This method is very flexible and can be realized by combining different kinds of lasers and mass spectrometers in the laboratory. However, the method also brings some problems, such as time-consuming, mainly relying on manual operation, low degree of automation and prone to artificial errors. To solve the problem, we design a program named AutoMS, which can collect and analyze data automatically. The program consists of two parts. The first part AutoSpecMS integrates multiple commercial lasers and one commercial high-resolution FT ICR mass spectrometer. It can realize automatic scanning of the action spectrum through user setting parameters, reducing labor intensity and avoiding human error. The second part AutoDataMS is used for the analysis of obtained experimental data. It can be applied for displaying photodissociation mass spectra and action spectra in the forms of one-dimensional, two-dimensional or three-dimensional graphics. The feasibility of this program has been experimentally verified by the selected examples of tetraphenylpyrrin (TPP), tetra (4-carboxypyryl) porphyrin (TCPP) and tetra (4-aminophenyl) porphyrin (TAPP). The UV-Vis action spectra of TPP, TCPP and TAPP in the 210~700 nm band were collected automatically using the program. Yield spectra of some photofragment ions have also been obtained, whichare helpful for users to analyze the dissociation mechanism and dynamics of the system. More valuable information can be obtained by considering the corresponding photodissociation mass spectra and photodissociation spectrum simultaneously. 2D and 3D spectra can also be obtained by the program of AutoDataMS, enhancing the visualization of the experimental data. Further data analysis about the three samples studied here showed that the UV-Vis action spectra of the molecules have obvious substituent effects. In addition, the correlation analysis of ions was fulfilled through the program, providing more information relative to the dissociation process. It is believed that the method and procedure described in this paper have good expansibility and applicability and can be applied as a good reference for many related works.
		2021 Vol. 41 (08): 2325-2331 [Abstract] ( 173 ) RICH HTML PDF (4467 KB) ( 164 )

	2332	End-Point Prediction of BOF Steelmaking Based on Flame Spectral Feature Selection Using WCARS-ISPA
		ZHU Wen-qiong, ZHOU Mu-chun^*, ZHAO Qi, LIAO Jun
		DOI: 10.3964/j.issn.1000-0593(2021)08-2332-05
		Real-time precise control of the BOF steelmaking end-point can effectively improve the quality of steel output. The flame spectra change obviously in different stages of steelmaking. It can be used to control the end-point of steelmaking effectively with the machine learning method. Due to a large amount of spectral data and the lack of reliability and real-time performance of the existing methods for spectral feature extraction, a characteristic spectral wavelength selection method based on window competitive adaptive reweighted sampling (WCARS) combined with iterative successive projection algorithm (ISPA) was proposed in this paper. This method can effectively solve the problem of over-fitting and reduce the complexity of high-dimensional data calculation. After dividing the spectral data along the wavelength direction in the window, CARS was used to select the feature window band. The iterative selection was combined with a traditional successive projection algorithm, and the characteristic wavelengths were selected through repeated iteration. On this basis, support vector machine regression (SVR) was used to establish the carbon content prediction model of steelmaking end-point. 363 sets of spectral data of the later stage of steelmaking were collected as an experimental sample and preprocessed by Savitzky-Golay smoothing. The input of the SVR model was 10 characteristic wavelength data selected by WCARS-ISPA, and the output was carbon content. The training set and test set were divided by the Kennard-Stone algorithm. The average prediction error of carbon content, the hit ratio of prediction error within ±2% and the average running time of 30 times were selected as the evaluation indexes. The results indicated that the average prediction error is 1.413 2%, the hit ratio is 90.63%, and the running time is 0.019 679 s. Compared with the model of full spectra and characteristic wavelengths selected by four different feature selection methods of WCARs-ISPA, CARS-SPA, WCARS and SPA, the WCARS-ISPA model has the lowest error and the highest hit ratio. In this paper, a new flame spectral characteristic wavelength extraction method was proposed. Window competitive adaptive reweighted sampling was combined with an iterative successive projection algorithm to select the wavelength, and a prediction model of end-point carbon content is established on this basis. The experimental results showed that this method could effectively extract the spectral characteristics of flame. This model can accurately predict the endpoint of BOF steelmaking and meet the requirements of real-time control of industrial production.
		2021 Vol. 41 (08): 2332-2336 [Abstract] ( 227 ) RICH HTML PDF (2849 KB) ( 74 )

	2337	Research on the Electron Temperature in Nanosecond Pulsed Argon Discharges Based on the Continuum Emission
		CHEN Chuan-jie^{1, 2}, FAN Yong-sheng³, FANG Zhong-qing^{1, 2}, WANG Yuan-yuan^{1, 2}, KONG Wei-bin^{1, 2}, ZHOU Feng^{1, 2*}, WANG Ru-gang^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2021)08-2337-06
		In this paper, atmospheric pressure nanosecond pulsed discharges in pin-to-pin geometry are very easily reproducible by applying a positive overvoltage, and such discharge system is placed in a sealed chamber filled with high purity argon gas. A continuum radiation model for the atmospheric pressure discharges is proposed to diagnose the electron temperature of the nanosecond pulsed argon discharges. The high voltage and current probes monitor the voltage and current waveforms during the discharge, and the discharge pulse width is about 20 ns. The time-resolved emission spectra of the discharge column at different times (0<t<20 ns) are measured by the combination of optical systems, such as achromatic lens, monochromator and ICCD. The results indicate that the continuum emission intensity of the discharge increases with time during the period of 0<t<10 ns, and then decreases during 10 ns<t<20 ns. However, the intensity of argon lines always increases with time. As the intensity of continuum emission is positively correlated to the electron density, the electron density also increases firstly and then decreases, which has the same tendency as the discharge current. According to the continuum radiation model, the electron temperature during the discharge (0<t<10 ns) is measured to be (1.4±0.2) eV. As the driven voltage drops (10 ns<t<20 ns), the electron temperature decreases gradually to 0.9 eV. Our research suggests that the excited argon atoms are mainly populated by electron impact excitation during 0<t<10 ns, and thus their emission intensities increase with the electron density. Afterwards, due to the decreasing of electron temperature, the rate of Ar⁺₂ ions recombination reaction increases dramatically. The production of excited atoms is governed by the electronion recombination processes, leading to increase their emission intensities further. The virotational spectrum of OH species is detected by adding 0.5% water vapor into the working gas. It is found that the production mechanisms of OH(A) make it deviated from Boltzmann distribution. In this work, a two-rotational temperatures OH(A-X) spectral model is employed to examine the gas temperature. During the discharge pulse, the gas temperature remains invariant around the value of 400 K. Moreover, the addition of water vapor causes the increase of the intensity of the continuum in the short wavelength range. It is analyzed that H₂ could be produced by the dissociation of H₂O in the discharge and then excited to the excited state H₂(a³Σ⁺_g) by means of the energy transfer reaction from argon atoms in a metastable state. Finally, H₂(a³Σ⁺_g) decays by spontaneous radiation to the repulsion state H₂(b³Σ⁺_u) and emits the short-wavelength continuum emission. The electron temperature (T_e>1 eV) is very sensitive to the short wavelength response of the continuum spectrum. So even if the working gas contains a small amount of water vapor, it will greatly influence the electron temperature diagnosed by the continuum radiation.
		2021 Vol. 41 (08): 2337-2342 [Abstract] ( 199 ) RICH HTML PDF (3514 KB) ( 65 )

	2343	Research Progress of Spectral Measurement on the On-Line Monitoring of Laser Processing
		HU Guo-qing^{1, 2}, GUAN Ying-chun^{1, 2, 3*}
		DOI: 10.3964/j.issn.1000-0593(2021)08-2343-14
		With the development of modern industrial applications, laser processing requirements with complex processing environments and objects, large dynamic range, high efficiency, and high precision are becoming more and more urgent. And the on-line monitoring and real-time optimization of laser processing parameters is an important solution. At the same time, a variety of optical signals and changes in surface optical properties can be generated during the interaction between laser and material. They are closely related to processing parameters, processes, and target properties. Therefore, spectral measurements of corresponding optical signals could reveal the machining process and status, indicating an important on-line monitoring means of laser processing. Spectral measurements with the characteristics of high resolution and rich spectral information have been used for almost all laser processing processes, including laser welding, laser cutting and drilling, laser cleaning and polishing, micro-nano structure preparation, and additive manufacturing. This paper analyzes and summarizes the spectral measurement techniques, including plasma spectroscopy, reflection spectroscopy, and nonlinear optical spectroscopy, applied in on-line monitoring of laser machining. Based on the spectral measurement of plasma signals excited during single and multiple-pulse processing, the qualitative and quantitative monitoring of chemical composition during laser processing can be achieved. In addition, laser focus can be adjusted in real-time according to the relative intensity variances of characteristic peaks. The laser processing processes related to thermal effect can also be monitored and regulated based upon the plasma temperature. As a non-destructive monitoring method over a relatively long distance, reflection spectroscopy can effectively monitor the cleanliness, damages, chroma, and compositional changes of the material surface by measuring the integral spectral power of the reflected light signal a specific band, position and intensity of characteristic spectral peaks and bands. The nonlinear optical signals excited under certain conditions, including the harmonic signals, the fluorescence signals, and the Raman signals, can also provide additional methods of spectral measurements. Although their application scenarios are limited, they provide a new monitoring method for component analysis, focus, and material damage. Furthermore, the future development trend of spectral measurement, including the collaborative monitoring of multiple optical signals, the combined monitoring of spectral, acoustical, temperature and image signals in on-line monitoring of laser processing, has prospected. Meanwhile, the combination of artificial intelligence technology, on-line monitoring and laser processing will further promote the intelligent development of laser processing technology.
		2021 Vol. 41 (08): 2343-2356 [Abstract] ( 267 ) RICH HTML PDF (12286 KB) ( 121 )

	2357	Research Progress of Microspectral Analysis Technologies in Protecting Pigments of Cultural Relics
		ZHENG Li-ping^{1, 2}, WANG Li-qin^1*, ZHAO Xing¹
		DOI: 10.3964/j.issn.1000-0593(2021)08-2357-07
		Pigments are important material composition and artistic expression of polychrome cultural relics. The protection of cultural relics pigments has always been a hot and difficult issue in the field of cultural heritage protection. Cultural relics have non-regenerative characteristics, so the in-situ, non-invasive and accurate analysis of micro samples of cultural relics pigments plays an important role in protection of cultural relics. With the progress of various micro-beam technologies, micro spectral analysis technologies have unique advantages in the study of cultural relic the protection with the working mode of precise micro-area positioning and rapid spectral scanning, so the application has been developed rapidly. This paper presented the application, characteristics, and technical difficulties of the micro spectral analysis technologies, such as micro X-ray fluorescence(μ-XRF), micro-laser induced breakdown spectroscopy(μ-LIBS), micro-Raman spectroscopy(μ-Raman), micro-Fourier transform infrared spectroscopy(μ-FTIR), micro X-ray absorption near-edge spectroscopy(μ-XANES), micro time-resolved photoluminescence microscopy(μ-TRPL) and micro-fade tester(μ-FT) in order to get the information about composition analysis, depigmentation and degradation analysis, and protective effect evaluation. Also, the development tendency of microspectral technologies was prospected from eliminating measurement interference, improving measurement devices, and developing hybrid setup. Among these micro spectral technologies, μ-XRF, μ-LIBS, μ-Raman and μ-FTIR are conventional technologies for pigment composition analysis. Moreover, μ-Raman and μ-FTIR are widely applied to assess protection effect and μ-FTIR and μ-XRF can also be used to analyze degradation products. Combined with PCA and other relevant analyses, conventional micro spectral technologies can be used to identify the pigments of cultural relics and to provide valuable information for the origin, dating and authenticity identification of cultural relics. Especially, μ-XANES, μ-TRPL and μ-FT belong to the advanced international technologies which play a key role in the analysis of cultural relics pigments, the identification and visualization of distributions of the degradation products, the origin of the pigment and its history, degradation phenomena associating with the migration of ions from pigments and specific photochemical fading behavior. However, at present, these advanced technologies are rarely applied in the field of cultural relics protection in China. Therefore, this study has great significance for promoting the development of analysis and protection of cultural relics and brings a new insight into the identification, protection and restoration of cultural relics pigments in China.
		2021 Vol. 41 (08): 2357-2363 [Abstract] ( 189 ) RICH HTML PDF (2189 KB) ( 101 )

	2364	Research Progress of Pesticide Residue Detection Based on Fluorescence Spectrum Analysis
		ZHANG Ya-li^{1, 2}, YAN Kang-ting^{1, 2}, WANG Lin-lin^{2, 3}, CHEN Peng-chao^{2, 3}, HAN Yi-fang^{2, 3}, LAN Yu-bin^{2, 3*}
		DOI: 10.3964/j.issn.1000-0593(2021)08-2364-08
		The application of many pesticides in agricultural production has increased the output of agricultural products. However, the excessive use of pesticides also threatens the food safety of agricultural products in China. Therefore, rapid and effective detection of pesticide residues in agricultural products has become an urgent requirement in the environment of agricultural production. Fluorescence spectrum analysis technology has presented outstanding high sensitivity and favorable time scale, and good resolving power for multi-component pesticide residue detection. Compared with pesticide residue detection methods such as gas chromatography, liquid chromatography and gas-mass spectrometry, fluorescence spectrum analysis technology has advantages of simple pretreatment and fast detection speed. Therefore, fluorescence spectroscopy detection technology has been well utilized in the complex pesticide residue detection environment. This article mainly introduces the rapid detection method of pesticide residues based on fluorescence spectrum analysis technology and summarizes the application of traditional fluorescence spectrum analysis methods in pesticide residue detection, as well as the combination of synchronization, derivative method, three-dimensional fluorescence spectroscopy, neural network, biosensor, metal nanomaterials. Finally, the limitations and challenges of pesticide residue detection based on fluorescence spectroscopy were analyzed. The wider application of fluorescence spectrum analysis technology in pesticide residue detection needs to be realized through the continuous development of fluorescence detection instruments towards integration and modularization, so that the detection is faster and more efficient.
		2021 Vol. 41 (08): 2364-2371 [Abstract] ( 372 ) RICH HTML PDF (1851 KB) ( 154 )

	2372	Research Advances and Trends of Rapid Detection Technologies for Pathogenic Bacteria Based on Fingerprint Spectroscopy
		LIAO Wen-long¹, LIU Kun-ping², HU Jian-ping¹, GAN Ya¹, LIN Qing-yu³, DUAN Yi-xiang^3*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2372-06
		Pathogen detection is essential to ensure the safety of drinking water and food, and handle public health emergencies. However, the current testing standards or methods have the defects of labor-intensive, time-consuming operation and high cost, which makes it difficult to meet the requirements of high timeliness in modern society. Therefore, developing rapid detection technology for pathogenic bacteria with simple operation and low-cost is extremely urgent. In recent years, with the rapid development of laser and photoelectric detection technologies, laser-based spectral technologies, which can quickly obtain fingerprint information of microorganism, have attracted wide attention from researchers. Among them, surface enhanced Raman spectroscopy (SERS) and laser induced breakdown spectroscopy (LIBS) with the advantages of rapid, non-destructive or micro-destructive detection in situ have been widely investigated in rapid detection of pathogens. As a molecular vibrational spectroscopy technique, SERS introduces noble metal nanostructures with optical signal amplification capability into conventional Raman spectroscopy, which can enhance the Raman signal order of magnitude while quenching fluorescence, so that the fingerprint spectrum information of the whole bacterial cells can be quickly obtained. However, due to the material, morphology, and size of noble metal nanoparticles and the distance between nanoparticles and the target, reproducibility is still a major bottleneck for SERS in bacterial detection. As an emerging atomic emission spectroscopy technique, LIBS has the capability of real-time detection of multiple elements, and can quickly obtain all element information of samples including micro and trace elements. When using LIBS to classify and identify bacteria, in order to reduce the elemental interference of the substrate and the coexisting matrix, it is necessary to collect a large number of spectral data of pure cultured bacteria, which not only increases the detection period but also lost the quantitative capability at the same time. In view of the research status of SERS and LIBS technology in the rapid detection of pathogenic bacteria, this review summarized the advantages and limitations of the two methods and forecasted their research trends in the fields of bacterial detection, thus providing references for the development of rapid detection techniques for pathogens based on laser spectroscopy.
		2021 Vol. 41 (08): 2372-2377 [Abstract] ( 213 ) RICH HTML PDF (1275 KB) ( 72 )

	2378	Determination of New Non-Invasive Blood Glucose Detection Method Based on Spectral Decomposition
		CHEN Jian-hong, LIN Zhi-qiang, SUN Chao-yue
		DOI: 10.3964/j.issn.1000-0593(2021)08-2378-06
		Diabetes is a disease of abnormal glucose metabolism that manifests as hyperglycemia. If the glucose level in the blood remains very low or very high for long periods, it could cause serious diseases including tissue damage, stroke, heart disease, blindness and kidney failure. According to the World Health Organization (WHO), currently there are around 450 million cases of diabetes in the world. With the increase in the number of diabetic patients, the demand for glucose measuring equipment has become increasingly urgent. As the currently popular invasive blood glucose measuring equipment will cause inconvenience and pain to patients and may even cause infections, it will inevitably bring psychological and physiological pressure to patients in the long term. Therefore, the realization of non-invasive blood glucose measurement has important clinical application value. Photoplethysmography(PPG) pulse wave contains abundant information about human cardiovascular physiology and pathology. This paper proposes a new method for non-invasive blood glucose detection based on spectral decomposition, aiming at the spectral information related to blood glucose concentration changes in the PPG signal that is difficult to observe in the time domain Continuous Wavelet Transform(CWT) is used to decompose the PPG signal from the corresponding scale and details in order to obtain the spectral component amplitude information related to the change of blood glucose concentration. Studies have found that there is a higher correlation between the change inthe amplitude of the PPG signal spectral components and the changes in the blood glucose concentration. Through the Oral Glucose Tolerance Test (OGTT), the detected blood glucose concentration and the obtained relevant PPG signal spectral components amplitude is modeled by partial least square regression, and the established model is evaluated. The Root Mean Square of Calibration (RMSEC) of the calibration set is 12.47 mg·dL^-1, which is 0.69 mmol·L^-1, and the Root Mean Square Error of Prediction (RMSEP) of the prediction set is 6.21 mg·dL^-1, which is 0.35 mmol·L^-1. The agreement between the predicted value of model’s blood glucose concentration and the reference value is 96.00%. The results of the OGTT experiments show that the spectral decomposition method can effectively separate the vibration characteristic absorption spectra of blood glucose molecular groups, and the blood glucose spectral component modeling can minimize the impact of physiological variability and various environmental conditions. The prediction results of the model meet the national testing standards (＞95%). Clark grid error analysis show that the results predicted by this method can be used for daily blood glucose monitoring of patients.
		2021 Vol. 41 (08): 2378-2383 [Abstract] ( 233 ) RICH HTML PDF (4175 KB) ( 84 )

	2384	The Study of Turbulent Calibration System of HO_x Radical Detection
		WANG Yi-hui^{1, 2}, HU Ren-zhi^2, XIE Pin-hua^{2, 3, 4}, WANG Feng-yang^{1, 2}, ZHANG Guo-xian^{1, 2}, LIN Chuan^{1, 2}, LIU Xiao-yan⁵, WANG Yue²
		DOI: 10.3964/j.issn.1000-0593(2021)08-2384-07
		HO_x radicals are important oxidants in the atmosphere. Accurate measurement of atmospheric HO_x radicals plays an important role to study the mechanisms of atmospheric photochemical reactions. Gas expansion laser-induced fluorescence technology (FAGE) has been widely used in the field measurement of HO_x radicals. Accurate calibration has always been an important prerequisite for the FAGE system to accurately detect atmospheric Hox radicals. A turbulent calibration system producing an accurate concentration of OH and HO₂ radicals is developed in this work. It is based on the photolysis of H₂O and O₂ radiated by 185 nm UV light produced by a low-pressure mercury lamp. HO_x radicals generated in the calibration system are uniformly distributed and suitable for system calibration on multiple platforms. The measurement of oxygen and water vapor absorption cross-sections were carried out to accurately calculate the concentration of HO_x radicals in the turbulent calibration device. The high-precision cavity ring-down spectroscopy (CRDS) system was used to measure the ozone concentration, and a chilled mirror dew point meter was used to correct the concentration of water vapor measured by humidity & temperature probe to improve the calculation of HO_x radicals concentration. In order to simplify the field application of the turbulent calibration system and quickly obtain the concentration of HO_x radicals, the sensitivity factor of the phototube used to detect the intensity of mercury lamp was detected, and the relationship between mercury light intensity and ozone concentration was measured. There will be a certain loss during the transmission process of the turbulent calibration system. By changing the distance between the mercury lamp and the gas outlet of the calibration device, the loss of HO_x radicals during the transmission process is a quantitative measurement in the turbulent calibration system. And then, the built-up turbulent calibration system is applied to the system, which is based on gas expansion laser-induced fluorescence technology (FAGE). The fluorescence signal of OH radical detected in the FAGE system is corrected according to the transmission loss of OH radical in the calibration system. The experimental result shows a good correlation between the corrected OH fluorescence signal and the concentration of OH radicals, which intimates that the turbulent calibration system has good accuracy. And the high accuracy and small size of the turbulent calibration system is more suitable for the field measurement of HO_x radicals.
		2021 Vol. 41 (08): 2384-2390 [Abstract] ( 174 ) RICH HTML PDF (2835 KB) ( 39 )

	2391	Terahertz Spectroscopy Characteristics of Sugar Compounds
		WANG Wen-ai, LIU Wei^*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2391-06
		Three sugar compounds were selected as the research objects because of their importance to the human body. Their absorption spectra were measured in a wide frequency range by high resolution terahertz time domain spectroscopy and Fourier transformation infrared spectroscopy systems. It has been found that glucose has the characteristic absorption frequencies of 1.10, 1.30, 1.45, 1.79, 1.88, 1.97, 2.08, 2.40, 2.55, 2.70, 2.84, 2.96, 3.24, 3.64 and 4.23 THz, fructose has the characteristic absorption frequencies of 1.09, 1.33, 1.65, 2.14, 2.62, 2.97, 3.24, 4.75, 6.97, 7.35, 7.98, 8.36, 9.16, 9.32, 9.53 and 9.73 THz, as well as galactose has the characteristic absorption frequencies of 2.21, 2.33, 2.70, 2.82, 3.17, 3.42, 3.93, 4.51, 5.07, 5.96, 6.60, 6.91, 8.03, 8.71 and 9.01 THz. By analyzing the experimental results of samples mixed from glucose, fructose, galactose and polyethylene quantitatively, it has been known that at the measured characteristic absorption frequencies, absorption increases linearly along with increasing the mass fraction of glucose, fructose and galactose. Furthermore, both the glucose and fructose have a common fingerprint frequency in 2.96 THz, glucose and galactose have a common fingerprint frequencies in 2.33, 2.70 and 2.82 THz, fructose and galactose have common fingerprint frequency in 8.00 THz, and all three kinds of compounds have common fingerprint frequency in 3.20 THz. Because the three samples have the same molecular formula, the 3.20 THz characteristic absorption mainly comes from intramolecular interaction, which represents the same chemical bonds or groups of isomers. The difference in characteristic absorption frequency is due to the molecular structure and inter-molecular interaction, which represents the difference between isomer structure and inter-molecular vibration mode. It can be predicted that glucose fingerprint frequencies would be tested in 4.70, 5.30, 5.60, 5.98, 7.03, 7.85, 8.26, 8.71 and 9.01 THz in development. Based on Density Functional Theory, CASTEP software was adopted to optimize the structures and calculate the characteristic absorption frequencies of samples. The theoretical simulation results are in agreement with the experimental ones. This result shows that CASTEP is feasible to compound molecules research in the THz range.
		2021 Vol. 41 (08): 2391-2396 [Abstract] ( 193 ) RICH HTML PDF (5606 KB) ( 66 )

	2397	Study on Arc Characteristic of Flux-Cored Wire Pulse TIG Arc Additive Manufacturing
		ZHAO Xiao-yan¹, YANG Li-jun^2, HUANG Yi-ming^1,2, HUANG Shi-cheng¹, LI Wang¹
		DOI: 10.3964/j.issn.1000-0593(2021)08-2397-07
		The arc characteristic of flux-cored wire pulsed TIG arc additive manufacturing was studied. The images of arc and droplet transition under different pulsed current were taken using high speed camera. High-speed camera images were analyzed. The results showed that the lagging melt phenomena in the wire melting process resulted in two contacting transition modes: slag bridge transition and liquid bridge transition, in addition, under the current parameters of 50/100 A, the frequency of slag bridge transition with intermittent droplets is the highest. Droplet transfer modes affected the arc temperature field and the distribution of flux composition in the arc. The characteristics of flux-cored wire pulsed TIG arc additive manufacturing were studied by spectral diagnosis, and the distribution of the arc temperature field under the conditions of different pulsed peak current and pulsed base current during additive manufacturing was analyzed. The spectral data of each point was measured by the lattice method, the temperature of each point was calculated according to the Boltzmann diagram method, finally the temperature of each point was fitted to obtain a complete arc temperature field. The result showed that the arc was disturbed and arc heat was absorbed by wire when the wire was fed from the front (left) side of the tungsten electrode axis. The temperature on the front side of the arc is lower than the back (right) side of the arc, and the size of the front side of the arc is slightly smaller than the back side. As the number of additive layers increased, the peak current was reduced, the arc shrunk. Also the proportion of the high- temperature region was relatively reduced, the proportion of low-temperature region is relatively enlarged. The highest temperature region of the arc appeared in the range of 1~2 mm below the tungsten electrode, which is about 13 000~15 000 K. The larger the pulse peak current, the larger the proportion of the highest temperature region. Due to the small current, the arc size was much smaller than the peak period in the pulse base current period, the interaction between the wire and the arc weakened, and the arc temperature field was basically symmetrical about the tungsten axis. The Na Ⅰ 589.5 nm spectrum line of the unique Na element in the basic flux-cored wire was selected to mark its distribution points, and the distribution of flux composition in the arc under different pulse peak currents and base currents was drawn by fitting. The results showed that the smaller the current, the lower the movement height of the powder. The flux composition was not contaminated on the tungsten electrode under different pulse peak currents, and the Na element was distributed in the back of the arc under different pulse peak currents and pulse base current. It showed that after the wire was fed into the molten pool from the front side of the arc, there was no strong spraying phenomenon of flux composition in the arc but it entered the molten pool for metallurgical reaction. The contact transition solves the problem of poor manufacturability of the flux-cored wire, the arc was relatively stable, and the tungsten electrode was prevented from being damaged by the spraying flux composition, the deposition process was stable.
		2021 Vol. 41 (08): 2397-2403 [Abstract] ( 203 ) RICH HTML PDF (5083 KB) ( 40 )

	2404	Study on the Space and Anisotropy of Phonon Thermal Radiation in Metal/Dielectric Thin Films
		DONG Xin, ZHANG Xia, SUN Xue-bo, YUAN Shuang-xiu, XU Hui, SU Fu-fang^*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2404-05
		Based on the approach to combine theory, experiment and simulation, this paper highlights the space and anisotropy of phonons thermal radiation utilizing metal/dielectric (MD) structure. Phonons, the elementary excitation characterizing the vibrations of lattice, are the eigenstates of materials. Albeit phonons controlled difficultly, the couplings between phonon modes and other photonic excitations enable exotic optical phenomena. Notably, surface phonon polaritons (SPhP) emanate from the coupling between phonon modes of polar dielectrics and photons in the infrared to terahertz. SPhP is featuring tight electromagnetic field confinement, low optical loss, and complementary to those provided by plasmon polaritos, facilitates access to deep subdiffraction optics. Firstly, the paper theoretically analyzed phonons absorption based on the Huang-kun equation and superlattice continuous dielectric model to further understand the internal theoretical foundation of phonons absorption. Experimentally, the research object we took into account was SiO₂ phonons, and then, the 500 nm-thick SiO₂ thin films respectively were synthesized on Si/Al（150 nm）thin films and Si substrate utilizing plasma chemical vapor deposition( PECVD) approach. The thermal radiation spectra were obtained at normal angle, which fourier transform infrared (FTIR) implemented. Phonons thermal radiation spectra in MD structure and in the non-MD structure were compared by analysing thermal radiation spectra and simulation spectra calculated by finite-difference time-domain (FDTD), demonstrating that MD structure was more conducive to stimulate phonons and SPhP. Longitudinal optical (LO) phonons emerge merely at oblique-incident in accordance to Berreman effect. LO phonons was obviously non-radiation due to the thermal radiation spectra obtained at normal- incidence. However, it made a difference on the liner-shaped of transverse optical (TO) phonons. What’s more, from the metal（Si/Al）/dielectric（SiO₂ thin films）thermal radiation angle diagram of two kinds of polarizations, we could observe that the SiO₂ phonons in Si/Al/SiO₂ thin films abided by Lyddano-Sachs-Teller (LST) relation, LO phonons and TO phonons appeared in pairs, and the spatial radiation characteristic of the two phonons differed. In addition, the difference between the phonons modes appearing under S polarization and under P polarization existed, verifying the spatial anisotropy of phonons. Especially, the coupling of phonons and photons could stimulate SPhP, in turn, SPhP could enhance the absorption of phonons. Strikingly, the phonon modes and SPhP enable to be stimulated and tuned based on MD structure, which set the stage for the implementation of these appealing concepts in infrared optical devices.
		2021 Vol. 41 (08): 2404-2408 [Abstract] ( 163 ) RICH HTML PDF (2071 KB) ( 31 )

	2409	Coastal Soil Salinity Estimation Based Digital Images and Color Space Conversion
		XU Lu^*, WANG Hui, QIU Si-yi, LIAN Jing-wen, WANG Li-juan
		DOI: 10.3964/j.issn.1000-0593(2021)08-2409-06
		Soil salinization is one of the most important reasons for soil degradation. Rapid and accurate monitoring of soil salinity has positive effects on sustainable agricultural development and ecological environment protection. This study proposed a new method of surface soil salinity estimation in coastal areas based on digital photographs to obtain soil salinity information quickly and conveniently under complicated weather conditions. 52 bare surface soil samples and photographs were collected under sunny and cloudy weather in the coastal area of Yancheng, Jiangsu province. Parameters such as soil electrical conductivity (EC), pH value and soil water content were measured in the lab. Using RStudio software for photo processing, firstly, three color components were extracted from RGB color space, then five color spaces (HIS, CIEXYZ, CIELAB, CIELUV, and CIELCH) were obtained from color space conversion. Three parameters were extracted from each color space. Hence there were 16 parameters from 6 color spaces for CIELAB, CIELUV, and CIELCH having the same parameter L. The correlation analysis of soil EC and color parameters indicated that the color purity and brightness were significantly correlated with soil EC, while color hue was insignificantly correlated with soil EC. Random forest and leave one out cross validation methods were used to establish soil EC estimation model with randomly 70% dataset, and the rest 30% dataset was used for validating. Repeated 100 times to get the optimal model, and finally, the accuracy of the best model reached R²_val=0.75, RMSE_val=3.52, RPD_val=2.02. By analyzing the importance of color parameters, we found that color purity and color brightness contributed most to the model, and color hue contributed relatively little. To sum up, the color parameters obtained from digital images provided a new approach for soil salinity estimation effectively. Combined with the unmanned aerial vehicle, this study proposed a new perspective for quantitative assessment of surface parameters, which would provide technical support and effective means for the precise management of precision agriculture and coastal ecological environment in future.
		2021 Vol. 41 (08): 2409-2414 [Abstract] ( 208 ) RICH HTML PDF (3218 KB) ( 64 )

	2415	Performance Evaluation of a Portable Breath Isoprene Analyzer Based on Cavity Ringdown Spectroscopy
		LI Qing-yuan, LI Jing, WEI Xin, SUN Mei-xiu^*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2415-05
		Breath isoprene is an endogenous metabolite whose concentration is related to human blood cholesterol level. However, numerous factors are influencing human breath. It is necessary to conduct effective breath analysis in selected specific populations (access large breath data with real-time, online, high sensitivity, high selectivity, and high accuracy). Cavity ringdown spectroscopy (CRDS) is a highly sensitive, highly stable, and highly selective spectral technique. In this paper, a breath isoprene analyzer based on CRDS was constructed considering the single-wavelength integrated semiconductor UV laser currently on the market. The breath isoprene analyzer mainly comprised of laser source, vacuum cavity, photodetector, and data acquisition. The fitting result showed good linearity indicating that the ringdown signal obtained by this analyzer was close to the single exponential decay (R²=0.998 39), and obeyed Lambert-Beer’s law. Effects of different average times on ringdown signal stability were evaluated. Considering the stability of the ringdown signal and the response time of the analyzer comprehensively, 128 times was used as the average time during the experiment. Subsequently, the performance of the breath isoprene analyzer was investigated. Ringdown times of 16 min under vacuum were measured continuously. The repeatability and response of the breath isoprene analyzer were examined. We measured the ringdown times of standard isoprene gas with different density of particle (10×10^-9，30×10^-9，50×10^-9，100×10^-9，200×10^-9) to calculate the linearity of the analyzer. At last, the spectral interference (NO, N₂O and acetone) at 224 nm was discussed. The experiment shows that: the ringdown breath analyzer has high sensitivity (limit of detection is 0.49×10^-9), good repeatability, stability (0.48%), near real-time response (1 datum per second) and good linearity (R²=0.993 13). The improved LoD in this paper is about 1/1 000 of the current LoD. The portable breath isoprene analyzer based on CRDS could realize the effective analysis of isoprene in actual human breath.
		2021 Vol. 41 (08): 2415-2419 [Abstract] ( 182 ) RICH HTML PDF (2589 KB) ( 153 )

	2420	Identification of Different Brands Erasable Pens by Infrared Spectroscopy Combined With Chemometrics Methods
		ZHAO Yu-xuan¹, ZENG Le-yang-zi², LI Kai-kai^1*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2420-07
		As a new writing tool, an erasable pen has the characteristics of erasable ink. Therefore, in the current public security work, common criminals use an erasable pen to tamper with documents. In order to ensure the integrity of material evidence, it is urgent to establish a non-destructive and rapid ink test of the erasable pen to provide help for finding writing tools and identifying criminal suspects. Common erasable pen inks can be divided into film-forming ink and temperature change ink. In this study, the ink of 30 erasable pens of different brands, types and colors were analyzed with Fourier transform infrared spectroscopy (FTIR). Through the analysis of infrared spectra in the range of 4 000～650 cm^-1, the difference in their composition and the spectral difference of erasable pen with different fading mechanism were compared. Through the infrared spectrum information, it is found that the components of the same brand and the same model of erasable pen ink are similar, and the ink color has little influence on the infrared spectra. At the same time, comparing the infrared spectrum information of the erasable pen ink before and after erasing, it is found that there are still some special chemical components in the temperature change ink after erasing, which can be used as the identification standard. However, the residual components of film-forming ink are less after erasing, which is difficult to identify, which may be related to the particle structure of film-forming ink. In addition, the spectra in the range 650～1 500 cm^-1 of erasable pen ink were analyzed by principal component analysis (PCA) and Heatmap to classify the types of erasable pen. The relationship between infrared spectrum information and principal component loadings was established. According to the loading plot, the first two principal components summarize almost all the infrared spectrum information, and the cumulative contribution rate is more than 79%. Therefore, the first two principal components are selected to a scatter plot. In order to determine the source of the erasable pen in practical work, 5 samples of the unknown pen were randomly selected from 30 kinds of ink samples, and PCA analysis was carried out with known samples at the same time, and a scatter diagram was made to realize the prediction of the types of unknown erasable pen ink samples and work well. The results indicate that FTIR combined with PCA can be used to classify the erasable pen ink rapidly. It provides a method for examining the erasable pen ink in altered documents with advantages of fast, non-destructive and high sensitivity.
		2021 Vol. 41 (08): 2420-2426 [Abstract] ( 217 ) RICH HTML PDF (5014 KB) ( 77 )

	2427	A Sequential Classification Strategy Applied to the Detection of Terrestrial Animal Lipid in Fish Oil by MID-Infrared Spectroscopy
		GAO Bing, XU Shuai, HAN Lu-jia, LIU Xian^*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2427-05
		Compared with other animal fat, fish oil has the traits of the high demand of extraction technology, low oil yield and high nutritive value. Authenticity appraisal of fish oil is conducive to the normal operation of the feed market and the protection of consumer rights and interests. In the present study, a Sequential Classification Strategy (SCS) was proposed and applied to identify illegally adulterated terrestrial animal lipid in fish oil. A total of 50 animal fat samples (12 fish oil, 10 lard, 9 chicken oil, 10 tallow and 9 suet) were collected in this experiment, and 160 adulterated fish oil samples with terrestrial animal fat were prepared by homogeneous mixing method. Exploratory research based on the principal component analysis (PCA) method was used to identify the feasibility of identification analysis. The results showed that pure fish oil and adulterated fish oil were well differentiated. The species identification of terrestrial animal fat adulterants is potential. Based on partial least squares-discriminant analysis (PLS-DA) and one class-partial least squares (OC-PLS), the first step was to establish a one class screening model to detect the authenticity of fish oil. In the second step, the identification model of multi-class adulterations (two types of classification) of terrestrial animal lipid was established. Results show that the one-class screening model distinguished pure fish oil from adulterated fish oil, and the recognition rate and rejection rate of the one-class screening model were both 100%, the first multi-class model for the classification of adulterants (lard, chicken oil, suet, tallow) in pure fish oil performed well with the recognition rate and rejection rate higher than 80% and the mis-discrimination ratio lower than 15%, the second multi-class model for the classification of adulterants (ruminant animal lipid, non-ruminant animal lipid) performed better than the first multi-class model with the recognition rate and rejection rate higher than 90% and the mis-discrimination ratio lower than 7%. With the proposed SCS, infrared spectroscopy combined with chemometrics can be used to identify pure fish oil form adulterated fish oil. Furthermore, the species source of adulterants can be recognized effectively. Finally, we can suggest this type of application as a potential tool to assist the feed industry and regulatory organisms in food quality control, allowing detection in feeding fish oil through direct, fast and reliable screening analyses.
		2021 Vol. 41 (08): 2427-2431 [Abstract] ( 162 ) RICH HTML PDF (3345 KB) ( 54 )

	2432	*Construction and Verification of a Mathematical Model for Near-Infrared Spectroscopy Analysis of Gel Consistency in Southern Indica* Rice**
		LIU Hong-mei, SHEN Tao, ZHANG Wen-yi, SHI Xi-wen，DAI Tao, BAI Tao, XIAO Ying-hui^*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2432-05
		Cultivating high-quality and high-yielding rice varieties is one of the important tasks of current rice breeding, and gel consistency is one of the most important indicators of rice cooking and eating quality. The traditional chemical method for measuring the gel consistency of rice has complicated pretreatment, complicated process, and high reagent consumption. It is difficult to meet the needs of rapid non-destructive testing of the gel consistency for large batches of rice varieties (combinations). The near-infrared spectroscopy analysis technology can quickly, non-destructively, and non-pollutingly analyze. In this study, 137 indica rice varieties (combinations) mainly cultivated or newly bred in southern rice areas were used as the test materials, and their near-infrared spectra were measured by traditional chemical methods to collect their near-infrared spectra to establish near-infrared spectra of southern indica rice. Build an analysis model, and then correct and verify the model. The results showed that the partial least squares method (PLS) was used to establish their respective near infrared analysis models after 20 kinds of mathematical preprocessing and 6 kinds of wavelength bands (or combinations). By comparing the model evaluation indexes, it was determined that smooth pretreatment was the best pretreatment method, and the wavelength band of 1 100 to 1 650 nm was the best modeling wavelength band. Evaluation index of smoothing model: calibration correlation coefficient (R), test correlation coefficient (r), relative analysis error (RPD) were 0.970 0, 0.964 2, and 3.780 5 respectively; wavelength evaluation range: 1 100 to 1 650 nm Model evaluation indicators: R, r, RPD They were 0.969 4, 0.963 8, and 3.758 6 respectively; after smoothing, the best near-infrared analysis model of rice gel consistency was established in the wavelength range of 1 100 to 1 650 nm, and the model evaluation indicators: R, r, and RPD were 0.979 0, 0.974 1, and 4.419 4 respectively; Then used 30 samples to verify the obtained optimal model. It indicated that the absolute error between the near infrared predicted value and the chemical value was 0.198 6～6.502 4 mm, and paired t test showed that p=0.726>0.05, indicating no significant difference between the predicted value and the chemical value. The near-infrared model was feasible for rapid non-destructive testing of rice gel consistency. This study provides technical support for the rapid screening of high-quality rice varieties (combinations) in the early generation of materials and the rapid batch analysis of the gel consistency of rice.
		2021 Vol. 41 (08): 2432-2436 [Abstract] ( 158 ) RICH HTML PDF (1372 KB) ( 55 )

	2437	Study on Characteristic Wavelength Extraction Method for Near Infrared Spectroscopy Identification Based on Genetic Algorithm
		LI Hao-guang^{1, 2}, YU Yun-hua^{1, 2}, PANG Yan¹, SHEN Xue-feng^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2021)08-2437-06
		At present, although the near-infrared (NIR) spectroscopy analysis technology has been widely used in many fields, it is mainly used as laboratory instruments, and the spectrometer used in the laboratory has the problems of large volume, high power consumption and high price. The main units that can purchase and use the NIR spectrometer are universities, scientific research institutes, large and medium-sized enterprises, etc. The price of a spectrometer based on the Fourier or grating principle is usually as high as several hundred thousand Yuan, which is beyond the affordability of small and medium-sized enterprises and ordinary people. Therefore, the application of NIR spectrometer is far away from ordinary people’s daily life. The high price and large volume of near-infrared spectrometers restrict the large-scale application of near-infrared spectroscopy analysis technology. The reason is that the near-infrared spectrometer itself is expensive and the volume has not yet been portable and miniaturized. Reducing the cost of the NIR spectrometer and miniaturizing the spectrometer is an important direction to promote NIR spectroscopy technology. The efforts of miniaturization of NIR spectrometer include CT orthogonal grating technology and micro electro mechanical system technology. However, the volume reduction of the spectrometer by these two technical solutions is limited, and there are still some problems, such as high price, internal moving parts and real hard miniaturization. For a specific qualitative analysis task, a small number of characteristic wavelength points are selected from full spectra and used to build models which can recognize testes samples. The method mentioned above can reduce the cost of instrument manufacturing and difficulty of spectrometer miniaturization, and it is also conducive to the large-scale promotion and application of NIR analysis technology. Near infrared spectra of Haploid and diploid maize seeds are collected by diffuse transmission method in several days. The collected data are divided into five data sets in chronological order. For the first data set, 10 characteristic wavelength points are extracted by genetic algorithm, and then 10 characteristic wavelength points are extracted for the remaining four data sets In order to test the validity of the method, the haploid and diploid identification was carried out. The experimental results show that using 10 characteristic wavelength points can obtain the identification effect, which is consistent with the full spectrum, indicating that using a small number of characteristic wavelength points can also effectively identify haploids, which can provide a reference for the development of low-cost portable NIR spectrometer for a specific task in other fields.
		2021 Vol. 41 (08): 2437-2442 [Abstract] ( 387 ) RICH HTML PDF (2390 KB) ( 263 )

	2443	Application of Various Algorithms for Spectral Variable Selection in NIRS Modeling of Red Ginseng Extraction
		CHEN Bei¹, ZHENG En-rang^1*, GUO Tuo²
		DOI: 10.3964/j.issn.1000-0593(2021)08-2443-07
		As an effective active component in red ginseng extraction, ginsenoside content has an important impact on the quality of follow-up products. Traditional chemical detection quality control methods have high costs and time-delay. Existing studies have shown that the fast and non-destructive near-infrared detection method is feasible for red ginseng extraction. However, the existing methods heavily rely on the data processing software algorithm of the instrument, which cannot meet the actual production accuracy and speed requirements. In order to monitor the extraction process rapidly and accurately, a variety of intelligent spectral selection algorithms are applied in the near-infrared spectral(NIRS) modeling, and the performance and robustness of different spectral selection algorithms are compared in this study. In order to detect the high content of ginsenoside Rg1 and the low content Rc in the red ginseng extract, 128 samples of red ginseng extract in the first two times extracted were collected from three batches, 1 000～2 499 nm band NIRS data were obtained online, and the content of ginsenoside was determined by using the international standard high-performance liquid chromatography (HPLC). Firstly, the dimension of the input wavelength was reduced by using four wavelength selection algorithms, namely, competitive adaptive reweighting sampling (CARS), the uninformative variable elimination (UVE), random frog (RF) and successive projection algorithm (SPA). Then the selected wavelength was used for the linear partial least squares (PLS) quantitative model establishment. At last, the performance of the model was evaluated by the root mean square error (RMSE), coefficient of determination (R²) and relative analysis error (RPD), etc. According to the PLS modeling results of four wavelength optimization algorithms, after RF optimization, the characteristic wavelength variable of the modeling decreased to 0.67% of the original, R² of the ginsenoside Rg1 and Rc content in red ginseng extract reached above 0.94, the RMSE of the prediction was 0.024 6 and 0.013 5 respectively, and the RPD of prediction set reached above 4.84, which reduced the difficulty of the modeling and improved the accuracy of modeling. From the comparison of RF and CARS modeling in the original spectrum, full-spectrum and SNV pretreated full spectrum, the overall performance of the RF wavelength selection algorithm model is better. Different spectral ranges and pretreatment methods have little impact on the performance and good robustness. In conclusion, RF is a relatively ideal wavelength selection algorithm for the modeling of red ginseng extract. PLS based on RF realizes the one-time modeling of two red ginseng extracts, which can be used to rapidly detect ginsenoside content in the extract. The study provides theoretical support for the online extraction control of medicine.
		2021 Vol. 41 (08): 2443-2449 [Abstract] ( 159 ) RICH HTML PDF (3054 KB) ( 70 )

	2450	On-Line Spectral Analysis of Crotonaldehyde Content in Cigarette Mainstream Smoke
		QIN Yun-hua^1,2, GAO Lei³, LI Chao¹, LONG Yu-jiao⁴, ZHU Ming⁴, CHEN Da^2*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2450-05
		The cigarette mainstream smoke represents the main gas that is ingested by the human body when the cigarette is burned. The reduction of scorch and other hazardous components has become an issue of great concern to the whole society. Among various components in cigarette mainstream smoke, crotonaldehyde has become one of the seven main harmful indicators in cigarettes prescribed by the state due to its strong genotoxicity. Traditional analytical methods for crotonaldehyde usually rely on high-performance liquid chromatography and other laboratory methods, which requires complex sample pretreatment procedures. This makes it difficult to measure crotonaldehyde in real-time to evaluate its effects on health. In order to monitor the crotonaldehyde content in cigarette mainstream smoke efficiently, a Fourier Transform Infrared Spectrometer (FTIR) system was set up to a couple with a smoking machine. In this system, an innovative oversampling data driven spectral analysis (ODDSA) method was developed to accurately extract the spectral features of crotonaldehyde from the complex and fluctuating spectra of cigarette mainstream smoke. The ODDSA method started with experimental design and used the idea of random design to simulate the distribution range of actual cigarette samples, which constructed a good data structure to guide further data mining. Thereafter, the high-density wavelet transform (HDWT) was innovatively used to process the IR spectra, which enabled oversampling in time/frequency dual-domains to improve the spectral resolution. This would definitely suppress the effects of other matrix components on the analysis of crotonaldehyde. Finally, the strategy of modified competitive adaptive reweighted sampling was developed to accurately extract the interseting features from the multiple redundant HDWT coefficients, which was used to construct a qualified calibration model for the analysis of crotonaldehyde. In the experiment, 15 typical commercial cigarette brands were collected, in which 8 samples of each brand were prepared to collect their IR spectra of mainstream smoke. Thereafter, 25 samples were randomly selected to validate the performance of ODDSA. The calculation results showed that the regression coefficient of the test set was 0.971, and the relative root means square error is 5.5%. The satisfactory results indicate that the ODDSA is capable of on-line analysis of crotonaldehyde in cigarette mainstream smoke, which may well extend to on-line monitoring of other components in second-hand environmental smoke. This would provide a novel tool for the evaluation of cigarette effects on health.
		2021 Vol. 41 (08): 2450-2454 [Abstract] ( 198 ) RICH HTML PDF (1758 KB) ( 227 )

	2455	Syntheses and Spectral Study of the Polyoxosilicotungstate and Its Complex Reaction With RhB
		SUN Rui-qing, SHI Lin, CHEN Yi-ping^*, SUN Yan-qiong
		DOI: 10.3964/j.issn.1000-0593(2021)08-2455-07
		A novel triclinic polyoxosilicotungstate [Cu(en)₂(H₂O)]_n{[Cu(en)₂] [SiW₁₂O_39.5]}_n(OH)_n·n(en) was hydrothermally synthesized with P1 space group and a one-dimensional double chains structure. The hydrogen bonds between ligands and cluster anions formed a two-dimensional layered structure. The layers were connected to form a three-dimensional supramolecule by strong hydrogen bonds between free en molecules, hydroxyls and cluster anions. The compound was characterized by XRD, FTIR, two-dimensional(2D) correlation infrared spectroscopy under magnetic and thermal perturbation, UV-Vis DRS spectrum and TG etc. XRD showed that the spectrum was basically consistent with the simulation by single crystal structure data, and the main peaks were the same, indicating that the synthesized compound was relatively pure. The FT-IR spectrum indicated that there was four characteristic stretching vibration of Keggin cluster anion skeleton in the range of 1100 to 700 cm^-1, the ν_as(O—H) at 3 600～3 300 cm^-1 was broadened due to the formation of hydrogen bonds. Furthermore, the two-dimensional infrared correlation spectroscopy under 5~50 mT magnetic showed that the strong response peaks at 890，800 and 780 cm^-1 were ν_s(W═O_d)，ν(W—O_b—W) and ν(W—O_c—W) respectively. This might be caused by the coordination between magnetic Cu and O_d of cluster anion, which led to the variation of the dipole moment of W—O skeleton stretching vibration with magnetic. The 2D-IR COS under 50~120 ℃ illustrated that there was a strong ν_as(W═O_d) response peak at 920 cm^-1, while ν (W—O_b—W) at 762 cm^-1 and ν(W—O_c—W) at 748 cm^-1 was relatively weak, which verified that the hydrogen bonds formed by O_d were more than those of O_bin the structural analysis. The strong hydrogen bonding made the whole cluster anion skeleton more sensitive to the thermal response. UV-Vis DRS found the O_μ→W(LMCT) and d→d transition of Cu²⁺ happened at 309 and 558 nm respectively. TGA showed that the weight loss process could be divided into three stages. In the first stage, the free en and hydroxyl groups were lost, and in the second, the coordinated en and coordination water was lost. At last, in the third stage, the framework of the tungsten oxide cluster began to collapse from 540 ℃. The complex reaction of the compound and RhB under different pH conditions were performed and discussed. The results showed that strong acid condition was more favorable for the complex reaction and the formation of the purple complex. The standard concentration curve of RhB was drawn under pH 1, and the absorbance of residual RhB in the test solution after the complex reaction was detected by UV-Vis. Through further calculation, the best ratio of RhB to the compound was determined as 4∶1. This research provided a novel way to remove organic pollutant RhB from industrial wastewater and revealed the potential application prospects of the compound.
		2021 Vol. 41 (08): 2455-2461 [Abstract] ( 167 ) RICH HTML PDF (4956 KB) ( 43 )

	2462	Calculation and Study of Methane Absorption Coefficient at Variable Pressure and Temperature Under 3 016.49 cm^-1 Wave Number
		HUANG Han¹, CHEN Hong-yan^2*, LI Xiao-lu¹, LIU Jia-hao¹, ZHAO Yong-jia², CHEN Liang³
		DOI: 10.3964/j.issn.1000-0593(2021)08-2462-07
		The infrared methane sensor detects the concentration of methane according to Beer-Lambert Law. What’s more, the absorption coefficient is an important parameter in Beer-Lambert Law, which varies greatly under the influence of temperature and pressure. The change will lead to the error of concentration measurement. Therefore, it is of great significance to study the variation law of methane absorption coefficient under different temperatures and pressures for the design of high-precision infrared methane sensors. In the literature reports, the experimental data of measuring methane concentration affected by the environment are generally obtained and then processed mathematically to compensate and correct the measurement error. Based on the theory of molecular spectrum analysis, the methane with 3 016.49 cm^-1 wave number is taken as the research object, and the methane data in the HITRAN database are used to design a Python program to call the HAPI function to fit and calculate the variation law of methane absorption coefficient with temperature and air pressure, and the variation law of methane absorption coefficient is verified by Fourier infrared spectrometer. Results show that at 3 016.49 cm^-1, water molecules (the influence of humidity) have little influence on the methane absorption coefficient, which can be ignored. Temperature and air pressure have certain effects on the absorption coefficient. When the air pressure is 1 atm and the temperature increases from -10 ℃ to 50 ℃, the absorption coefficient of methane decreases, and the relationship between the absorption coefficient and temperature is linear. When the temperature is 273.15 K, and the air pressure increases from 0.6 atm to 1.2 atm, the methane recovery coefficient increases and the relationship between the absorption coefficient and the air pressure is linear. Finally, the formula of absorption coefficient with temperature and air pressure is fitted, k(T, p)=53.65(±3.24)-0.114 6(±0.010 7)T+21.07(±0.95)p. Methane standard gas concentration is 1.01%, 2.00%, 3.51%, 5.06%, respectively, which are introduced into a short optical path quartz gas cell with a diameter of 2.5 cm and a length of 8 cm. The absorbance of methane was obtained from Fourier infrared spectrometer by changing the gas pressure and temperature. Due to the influence of the instrument resolution in the laboratory, if the methane concentration is directly inverted by absorbance, the error is large. In this paper, the absorption coefficient ratio to absorbance is used to judge the correctness of absorption coefficient fitting. The results show that the ratio of absorption coefficient to absorbance is fixed when the concentration is fixed and the air pressure and temperature change, further confirming the correctness of the calculated fitting methane absorption coefficient changing with temperature and pressure.
		2021 Vol. 41 (08): 2462-2468 [Abstract] ( 273 ) RICH HTML PDF (3562 KB) ( 73 )

	2469	Study on Rapid Recognition of Marine Microplastics Based on Raman Spectroscopy
		YANG Si-jie^1,2, FENG Wei-wei^2,3,4*, CAI Zong-qi^2,3, WANG Qing^2,3
		DOI: 10.3964/j.issn.1000-0593(2021)08-2469-05
		Due to a large amount of use and discharge of plastics, these plastics are broken into microplastics by the environmental effect and gather in the ocean in large quantities, leading to the accumulation of a large number of microplastics in the ocean，inrecent year. Microplastics are small in shape and difficult to identify their source and type. Laser Raman detection technology has been widely used in recent years which have fast, nondestructive and easy identification. In this paper, based on Raman spectral detection technology, an intelligent classification method combining wavelet processing and random forest algorithm is proposed to realize the rapid recognition of microplastics in seawater. The spectral data were collected by using laser Raman detection technology from six typical seawater microplastics standard samples(ABS, PA, PET, PP, PS, PVC), and the obtained spectra were pretreated by wavelet base DB7 and decomposition times 3 and standard deviation normalization. In order to improve the recognition speed, the spectral data is compressed at the same time. The data are respectively compressed to 64, 128, 256, 512 and 1 024 points, and their decision tree algorithm identification accuracy was 91.51%, 91.67%, 92.35%, 93.17% and 93.21% respectively. The random forest algorithm identification accuracy was 93.12%, 93.92%, 94.83%, 96.81% and 96.81%, respectively. The experimental results show that the Raman spectral compression of microplastics is the best compression point for efficiency and precision when the Raman spectral compression is 512 points, which can provide a reference for the Raman data compression of microplastics in practical engineering applications. Two recognition algorithms, decision tree and random forest, were used to study the Raman spectrum recognition of microplastics. The results show that the cross-validation accuracy of the random forest is higher than that of the decision tree. In order to further improve the identification accuracy, the model parameter optimization was carried out, and the cross-validation accuracy of the random forest method for identifying microplastics could reach 97.24% by using the optimized model parameters. It can provide a technical reference for the rapid identification of microplastics in seawater.
		2021 Vol. 41 (08): 2469-2473 [Abstract] ( 372 ) RICH HTML PDF (2714 KB) ( 157 )

	2474	Comparison of Raman Spectroscopy and Color Difference in the Light-Induced Color Damage Evaluation of Cultural Heritages With Silk
		TAN Hui-jiao, DANG Rui^*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2474-06
		Silk is one of the important collections in the museum, with high cultural, artistic and historical value. As a kind of unstable protein organic material, silk is extremely susceptible to the color damage such as yellowing caused by optical radiation, particularly in the museum light environment where Light Emitting Diode (LED) is widely used. How to evaluate the light-induced color damage to silk scientifically is the main problem to be solved in this study. Although effectively analyzed in the color damage of museum lighting to silk, there is limitations for the color difference evaluation method that is impossible to evaluate the color damage in the induction period. Since the fundamental cause of the color damage to silk lies in the photochemical reaction of the molecular structure inside the material, theoretically, the color damage to silk can be evaluated more scientifically based on Raman spectroscopy, which is studied at the microscopic molecular level. In this study, Raman spectroscopy was introduced into the field of museum lighting to verify its feasibility and scientificity in the color damage evaluation by comparing the evaluation results of the color difference method. Four narrow-band lights at 450, 510, 583, and 650 nm peak wavelengths that constitute the four-primary LED were used to carry out the long-period illumination experiment on silk samples. The relative color damage coefficients of four narrow-band lights on silk samples based on two evaluation methods of color difference and Raman spectroscopy were calculated, which were 450 nm∶510 nm∶583 nm∶650 nm=1.00∶0.63∶0.48∶0.32, and 450 nm∶510 nm∶583 nm∶650 nm=1.00∶0.69∶0.47∶0.27, respectively. On the one hand, the results show that the color damage trend of four narrow-band lights obtained by two methods is consistent, that is, the shorter the peak wavelength, the higher the color damage to silk samples, indicating that Raman spectroscopy is a feasible method to evaluate the light-induced color damage to the silk. On the other hand, the ratio difference of the coefficient obtained based on Raman spectroscopy is greater. There is an induction period in the aging process of silk samples. It is difficult to analyze the change during the induction period by the method of color difference, while the change of molecular structure, including in the induction period, can be detected sensitively by Raman spectroscopy to evaluate the light-induced color damage to silk samples more scientifically. At the same time, the relative color damage coefficients provide a basis for the light-induced color damage evaluation and museum admission evaluation of the four-primary light-emitting diode in the illumination of silk.
		2021 Vol. 41 (08): 2474-2479 [Abstract] ( 200 ) RICH HTML PDF (2464 KB) ( 44 )

	2480	Study on Alumina/Lanthanum Oxide X-Ray Diffraction and Raman Spectroscopy
		WANG Yi^{1, 2}, LI Chang-rong^{1, 2*}, ZHUANG Chang-ling^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2021)08-2480-04
		When the size of aluminum oxide inclusions in steels is too large and the edges and corners are sharp, they can be regarded as the main source of cracks during the process of steel wire drawing, and these cracks substantially affect the performance of the steel. The refinement or removal of inclusions in steel is important. Since the amount of alloying elements added to steel is relatively small compared to that in the molten steel and there are errors during the experiments and analyses, the reaction of inclusions is magnified and studied by varying the proportions of rare earth lanthanum oxide powder and alumina at a high temperature of 1 600 ℃. The amount of powder that is added affects the phase change and size of the inclusions. A high-temperature box furnace is set to increase the temperature, keep warm and cool, and X-ray diffraction and Raman spectrometry are used to analyze the specific changes of lanthanum aluminum oxide. The results show that with increasing amounts of La₂O₃, the LaAl₁₁O₁₈ phase is formed first, followed by the LaAl₁₁O₁₈ and LaAlO₃ phases. As the peak intensity decreases, the full width at half maximum increases and the grain size decreases. Then, the characteristic peak intensity of LaAl₁₁O₁₈ disappears, leaving only a decreased amount of the LaAlO₃ phase, and no new phase is formed. Combined with the mathematical model for the average grain size of HW, R² for samples 1^#, 2^#, 3^# and 4^# is calculated to be 0.990 25, 0.962 59, 0.987 1, and 0.989 76, and the grain sizes are 6.08, 2.88, 7.67, and 4.75 μm, respectively. Sample 2^# has the smallest grain size herein, and sample 3^# has the largest grain size herein, indicating that an appropriate ratio of lanthanum oxide and aluminum oxide can promote nucleation and reduce the grain size. Through Raman spectrometry, it is observed that with a decrease in the Al₂O₃ ratio, the Raman characteristic peak at 4 385 cm^-1 disappears. When these results are combined with those from XRD, it is determined that the LaAl₁₁O₁₈ phase is present. Samples 3^# and 4^# have characteristic Raman peaks from 3 564～3642 and 4 461～5 554 cm^-1, respectively. Upon combining the Raman peaks and XRD pattern for sample 2^#, a new LaAlO₃ phase is generated. The different ratios of the samples have little effect on the Raman peak intensity, and no new characteristic peaks appear. By enlarging the materials in steels that need targeted research, the evolution process of the modification of alumina powder after the addition of lanthanum oxide powder is analyzed. The research results can reference solving the problem of alumina inclusion modification during the actual steelmaking process.
		2021 Vol. 41 (08): 2480-2483 [Abstract] ( 369 ) RICH HTML PDF (1595 KB) ( 147 )

	2484	Study on the Haze Process in Huainan City From October 2019 to March 2020 Observed by Raman-Mie Aerosol Lidar
		ZHANG Shuai¹, WANG Ming¹, SHI Qi-bing¹, YE Cong-lei¹, LIU Dong²
		DOI: 10.3964/j.issn.1000-0593(2021)08-2484-07
		The Raman-Mie Aerosol Lidar (RMAL) has advantages over traditional Mie scattering Lidar in accurately measuring aerosol extinction coefficient without assuming radar ratios. The results of the outfield sounding comparison experiment in Hefei indicated that the extinction coefficient retrieved by RMAL below 2.5 km is more accurate than the traditional Mie scattering Lidar with a difference of up to 0.04 km^-1, obtained water vapor mixing ratio profiles were consistent well with the sounding. This study presented the long-time observational results of aerosol extinction coefficient and height of atmospheric boundary layer (ABL) data over Huainan City during the autumn and winter from 2019 to 2020 using this technology for the first time. The pollution types (local pollution discharge, transmission pollution, transmission pollution and local pollution accumulation) and spatial-temporal changes of aerosol during the air quality pollution period were analyzed and discussed. The results showed that Huainan City is affected by 20 fine particle air pollution and 8 times dust air pollution during this period. The transportation of dust mainly came from the northwest, and it generally sunk from high altitude to the ground, with a thickness of more than 2 km. The average height of ABL was more than 1.23 km. In the typical fine particle transportation process, the height of the ABL was maintained at about 1.1~1.2 km, and the ground wind direction was mainly northwest, with a small amount of southeast. In the coincidence pollution process of fine particle transmission and local accumulation, the height of ABL was slightly lower (the average height is about 1.0 km), the near-surface wind direction is dominated by northerly winds. The lower edge height of the polluted air masses continued to decrease from low altitude and eventually coupled with near-ground pollution. In the process of heavy pollution caused by fine particles, the evolution trend of surface water vapor mixing ratio, relative humidity and PM_2.5 concentration were in good agreement. This showed that increasing moisture absorption of particulate matter and secondary transformation of gaseous pollutants might promote the second generation process of PM_2.5. In particular, the trend of atmospheric boundary layer height was closely related to the settlement of polluted air masses and the accumulation of surface pollution. During the attention period, most of the city’s hourly height of ABL was distributed below 1.6 km, with an average of around 1.0 km. When the hourly air quality reached severe pollution, the height of the boundary layer was generally less than 0.6 km. According to the simulation results of the backward trajectory of the air mass, the polluted air mass mainly came from the northerly direction, with a small amount came from the southeast, during the air pollution period of the city with moderate or above pollution. Therefore, it is necessary to strengthen the management and control of pollution sources in the north of the urban area to prevent superimposed effects.
		2021 Vol. 41 (08): 2484-2490 [Abstract] ( 179 ) RICH HTML PDF (4056 KB) ( 56 )

	2491	XRD and Raman Spectroscopy Characterization of Graphitization Trajectories of High-Rank Coal
		LI Huan-tong^{1, 2}, CAO Dai-yong^3*, ZHANG Wei-guo^{1, 2}, WANG Lu⁴
		DOI: 10.3964/j.issn.1000-0593(2021)08-2491-08
		In order to the interpretation of ordering and crystallinity of natural graphitized coal, nineteen kinds of different deformation-metamorphism degree high-rank coal from Hunan Province and Shaanxi Province were studied with proximate and ultimate analysis, X-ray diffraction (XRD), Raman spectrum and curve-fitting analysis. The graphitization, crystal size (L_a and L_c), interplanar spacing (d₀₀₂) were calculated with XRD. The parameters of P_G (G band position), P₁ (G and D1 band separation), R₁=I_D1/I_G, the peak height ratio, R₂=A_D1/(A_G+A_D1), peak area ratio were calculated with Raman. The results showed that the H/C decreases gradually with the increase of metamorphic degree during the coalification stage, but during the graphitization stage, the change was primarily physical, and the trend was slow or not significant. The parameters of d₀₀₂, L_a, L_c, N and L_a/L_c had shown that the crystalline structure of natural graphitized coal presented nonlinear continuous (step) change with metamorphism degree. The inflection point corresponds roughly to R_m=7.0% and d₀₀₂=0.338 nm. Before the inflection point, L_a, L_c and N changed little (or increase steadily), and the graphite crystal structure formed rapidly after the inflection point, the stacking effect begins and gradually increases, as the crystallite size increases. L_a/L_c variation reflected that the graphitization process changed from condensation to overlap. The graphitization trajectory of high-rank coal can be given in a three-stage model of orderly increase. During the stage from amorphous carbon (anthracite) to meta-anthracite, the parameters of P_G and P₁ changed significantly, and I_D1/I_G did not obey the TK relation when expressing the degree of disorder. During the stage from meta-anthracite to semi-graphitization showed different directions, R₁ presented an opposite trajectory with the increase of order, the evolution of some graphite components followed the TK relation, and R₂ showed a completely contradictory trajectory when the graphitization degree was 45%. The temperature and pressure in the graphite stage led to a sharp increase in crystal size (step evolution), and the decrease of I_D1/I_G obeying the TK relation. As neogenesis-associated components in different graphitized coals, d₀₀₂ cannot reflect the largest metamorphic degree of graphitized coal. However, it was still a superior choice to consider d₀₀₂ as an average scaling of the graphitized coals in the process of graphitization. Moreover, full width at half maximum of the (002) and (γ) band are reliable indicators for distinguishing and classifying of metamorphism type of nature graphitized coals. H/C, and I_D1/I_G also evolved over d₀₀₂ trajectory was altered, needed to use d₀₀₂＜0.344 nm, R₁＜2.0, H/C＜0.12 and other comprehensive indicators to identify the beginning of graphitization. From this, it could be seen that XRD and Raman spectral analysis techniques could be used to characterize the graphitization track stages and structural differences of high rank coal.
		2021 Vol. 41 (08): 2491-2498 [Abstract] ( 310 ) RICH HTML PDF (4251 KB) ( 293 )

	2499	A SERS Substrate for On-Site Detection of Trace Pesticide Molecules Based on Parahydrophobic Nanostructures
		GUI Bo^{1, 2}, YANG Yu-dong¹, ZHAO Qian^{1, 2}, SHI Meng¹, MAO Hai-yang^{1, 3*}, WANG Wei-bing¹, CHEN Da-peng^{1, 3}
		DOI: 10.3964/j.issn.1000-0593(2021)08-2499-06
		As banned veterinary drugs, many pesticides, including malachite green (MG), pose a risk of carcinogenesis. Due to its low price and strong antiseptic qualities, MG has been used illegally in fisheries. As a result, MG residues are usually detected in fresh fish. To evaluate MG residues, currently, approaches include high-performance liquid chromatography (HPLC), liquid chromatography-mass spectrometry (LC-MS) and other methods are used, and the detections are performed using a small volume of aquaculture water. However, such traditional detections rely on large and expensive equipment, which are cumbersome, and their processes are complicated, time-consuming and expensive. Consequently, these traditional methods cannot meet the needs of on-site detection of pesticides in markets, which are with features of large circulation, fast speed and low price. In recent years, with the emergence of surface-enhanced Raman scattering (SERS) and portable Raman spectrometers, a rapid on-site detection method for trace pesticide molecules becomes possible. Herein, the SERS technology uses surface plasmon of metallic nanostructures to sense molecules located nearby, thus obtaining information of molecular species and concentrations. In order to achieve an extremely low limit of detection(LOD), generally, the coffee ring effect or other means are used on SERS substrates to enrich molecules into a certain region sufficiently. When a droplet contact the substrate for a hydrophilic substrate, the liquid spreads on the surface, leading to a long perimeter of its coffee ring and a decrease in molecular distribution concentration. While when a superhydrophobic substrate is used for molecule enrichment, due to its small surface adhesion, droplets are unable to be fixed and would roll on the surface, thus shall significantly increase the difficulty of operation. Taking detection of trace residues of MG molecule as an example, due to the noisy environment caused by people in the market, collisions occur from time to time, and due to the lack of professional experiment platforms in the market, it is not desirable to use a superhydrophobic SERS substrate to detect pesticide molecules under this condition. A SERS substrate based on parahydrophobic nanostructures is proposed for rapid on-site trace detection of MG molecules in this work. Compared with previous superhydrophobic substrates, parahydrophobic substrates presented herein is able to firmly grasp droplets to be measured, which perfectly solves the problem that in on-site detections, droplets roll on conventional supehydrophobic substrates. In addition, compared with the hydrophilic substrates, due to a large contact angle of the parahydrophobic substrate, the area of the coffee ring can be reduced by 5.73 times, thus enriching concentration of the molecules can be largely increased, which as a result, can ultimately reduce LOD by at least two orders of magnitude. In short, the parahydrophobic SERS substrate proposed in this work is expected to be applied in rapid on-site detections of trace pesticide molecules.
		2021 Vol. 41 (08): 2499-2504 [Abstract] ( 163 ) RICH HTML PDF (4119 KB) ( 41 )

	2505	Study on Oil Identification Method Based on Three-Dimensional Fluorescence Spectrum Combined With Two-Dimensional Linear Discriminant Analysis
		KONG De-ming¹, DONG Rui¹, CUI Yao-yao^2*, WANG Shu-tao¹, SHI Hui-chao³
		DOI: 10.3964/j.issn.1000-0593(2021)08-2505-06
		Oil pollution seriously threatens the natural environment and human health. Therefore, it is very important to identify and deal with oil pollution. Therefore, three-dimensional fluorescence spectroscopy is generally used to detect the presence of oil contaminants in a certain solution. However, the three-dimensional fluorescence spectrum data of oils have high dimensions, and direct analysis is difficult. Therefore, the data dimensionality reduction method can be used to extract the spectral characteristics of the original oil samples. And the obtained spectral characteristics is used to identify and classify the samples. Based on this, the two-dimensional linear discriminant analysis (2D-LDA) is used to extract the characteristics of the oil samples. The differences in the spectral characteristics of the different samples extracted are studied. The obtained spectral characteristics are used as the input of the K nearest neighbor (KNN) classification to obtain the corresponding. Firstly, four different oils samples (diesel, gasoline, aviation kerosene, lubricating oil) was prepared, and each of the oils has 20 samples. So, 80 oils samples were prepared totally. Secondly, three-dimensional (3D) fluorescence spectrum data of all oil samples are collected by an FS920 spectrometer. Then, the spectral data is pre-processed to remove the scattering and to standardize it. Finally, the 2D-LDA algorithm is used to extract the characteristics of the samples, and the KNN algorithm is used to classify. The results were compared between principal component analysis (PCA) and 2D-LDA. 2D-LDA extracted the emission and excitation characteristics. Both accuracy is 95%. However, the accuracy of combining the classification distances of the emission and excitation spectrum characteristics and re-classifying is 100%. It shows that the two types of spectra are complementary to the three-dimensional fluorescence spectrum, and the combination of emission and excitation spectrum characteristics can better classify the sample. The results show that the classification effect of 2D-LDA characteristics extraction is superior to PCA. It shows that 2D-LDA is better for characteristics extraction of 3D-fluorescence spectrum data. Compared with PCA, 2D-LDA uses the intra-class matrix and the inter-class matrix to maximize the projection vector to extract the characteristics of samples. So, the same type of samples are closer, and the different type of samples are separated as much as possible. Therefore, the 2D-LDA can make it easier to identify data after reducing data dimensionality. Its robustness is good. This study provides a reference to identify oils.
		2021 Vol. 41 (08): 2505-2510 [Abstract] ( 235 ) RICH HTML PDF (2911 KB) ( 54 )

	2511	Determination of Thiabendazole and Bisphenol A in Environmental Water Samples Using Excitation-Emission Matrix Fluorescence Coupled With Chemical Multi-Way Calibration Method
		SUN Hai-bo, WU Hai-long^*, CHEN An-qi, SUN Xiao-dong
		DOI: 10.3964/j.issn.1000-0593(2021)08-2511-07
		As the economy is making high-speed progress, and environmental issues have raised people’s attention. Long-term abuse of pesticides and plasticizers in the actual production makes them the most pervasive environmental pollution source. Moreover, this issue does severe harm to ecotope, food stuff and human and animal, etc. In this paper, to solve the residual pesticides and plasticizers issue, a fast, sensitive and effective analysis strategy that the three-dimensional fluorescence spectroscopy coupled with the chemometrics-based method was developed for simultaneous determination of thiabendazole (TBZ) and bisphenol A (BPA) in environmental water samples. This analysis strategy gives consider both high sensitivity and abundant information of three-dimensional fluorescence spectroscopy and the significant advantage of “mathematical separation” of the chemical multi-way calibration method. It can achieve the trace analysis for TBZ and BPA only need simple pretreatment. Although the fluorescence spectra of TBZ and BPA overlapped each other and unknown interferences coexisted in the matrices, reliable qualitative and quantitative results were obtained by the proposed method with the help of a significant “second-order advantage”.TBZ had a good linear relationship (r=0.999 9) in range of 20~200 ng·mL^-1, while BPA had good linear relationship (r=0.999 1) in 40~280 ng·mL^-1. In two kinds of environmental water samples, the obtained average recoveries of TBA and BPA were 96.3%～99.1% and 90.0%～90.8%, respectively. Meanwhile, the standard deviations were less than 7.2%. In order to evaluate the performances of the proposed method, the figures of merit such as sensitivity (SEN), selectivity (SEL), the limit of detection (LOD) and limit of quantification (LOQ) were investigated. The satisfactory results indicated that it might be promising as an effective strategy for rapidly and accurately quantifying TBZ and BPA in complex environmental water samples. So this work provides an effective and scientific monitoring tool for pesticides and plasticizers residues.
		2021 Vol. 41 (08): 2511-2517 [Abstract] ( 157 ) RICH HTML PDF (2753 KB) ( 42 )

	2518	Three-Dimensional Fluorescence Characteristics Analysis of DOM in the Process of Treatment of Brackish Water by Ultrafiltration-Nanofiltration Double Membrane Process
		XIAO You-gan¹, CHEN Hong-jing¹, WEI Zhong-qing¹, CHEN Shou-bin¹, SHANGGUAN Hai-dong¹, LIN Hui², LI Zhong-sheng², LIN Ze-ying³, FAN Gong-duan^2*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2518-06
		In this paper, three-dimensional fluorescence spectroscopy was used in order to find out the three-dimensional fluorescence characteristics of DOM components during the treatment of brackish water by the “ultrafiltration-nanofiltration” dual-membrane water treatment process. Raw water mainly contains two high-intensity spikes and two low-intensity spikes. With the progress of the water treatment process, the fluorescence peaks in water samples gradually weaken. Quantitative analysis was performed on the water samples in the process of water purification by parallel factor analysis. It was found that the water sample mainly contains protein-like and fulvic-like factors. The variation of DOM components was analyzed by the maximum fluorescence peak intensity of each factor in the water sample. The fluorescence peak intensities of protein-like factors and fulvic-like factors in raw water were 0.351 08 and 0.175 55, respectively. The fluorescence intensity of the protein-like fluorescence peak is greater than that of the fulvic acid-like fluorescence, which indicates that the raw water has been contaminated by external organic matter. After the conventional process, the removal of the protein-like factors and the fulvic acid-like factors was 22.27% and 47.57%, respectively. The DOM that is not completely removed in the conventional process will enter the “ultrafiltration-nanofiltration” dual-membrane water treatment process. The ultrafiltration unit does not have a good removal effect on the DOM, which is a pretreatment to ensure that the water quality could meet the requirements of the nanofiltration unit. The removal of DOM is mainly contributed by nanofiltration unit. After the nanofiltration treatment, the DOM in the water is greatly reduced. The fluorescence peak intensities of the two factors were 0.013 67 and 0.002 56, respectively. Compared with the raw water, the protein-like substances have decreased 96.11%, fulvic-like substances decreased by 98.54%. Therefore, in treating brackish water by dual-membrane process, the proper pre-oxidation treatment should be designed to enhance the removal of DOM to reduce the impact on membrane fouling. This paper will provide a further theoretical basis for the promotion of the dual-membrane process and the control of membrane fouling.
		2021 Vol. 41 (08): 2518-2523 [Abstract] ( 149 ) RICH HTML PDF (4358 KB) ( 33 )

	2524	Spectroscopic Characteristics and Coloring Mechanism of Brown Tourmaline Under Heating Treatment
		YUE Su-wei^{1, 2}, YAN Xiao-xu^{1, 2*}, LIN Jia-qi¹, WANG Pei-lian^{1, 2}, LIU Jun-feng³
		DOI: 10.3964/j.issn.1000-0593(2021)08-2524-06
		Tourmaline group belongs to the trigonal system and contains a series of Boro-Aluminosilicate minerals. It can be subdivided into lithium tourmaline, magnesium tourmaline, and sodium-manganese tourmaline. Gem grade tourmalines show various colors, due to the occurrence of different trace elements and color centers. Brown tourmalines are selected to be modified into attractive colors by 3～4 hours(h) heating treatment under oxidizing or reducing environment. We obtained such results of 250～600 ℃ step heating-treatment experiments in brown tourmalines: (1) the color of samples changed successively from brown, greenish-brown to brownish-green in 250～350 ℃; (2) the brown hue continuous faded as the transparency improved in 450～500 ℃ which indicated the optimum heating temperature; (3) the fracture in all samples enlarged when heated above 600 ℃; (4) after heating treatment, the dichroism of samples showed green and brown on the direction parallel to c-section, while brown perpendicular to c-section. The color modification mechanism of brown tourmalines before and after heating treatment were investigated in this study by mid-near infrared absorption spectroscopy (IR), X-ray fluorescence spectroscopy (XRF), and ultraviolet-visible spectrophotometry (UV-Vis). The result of XRF indicated that all tourmaline samples belonged to the lithium tourmaline group which were rich in Mn and Fe. The mid-IR absorption peaks in natural brown samples were located at 3 800～3 400, 1 350～1 250, 1 200～800 cm^-1 and below 800 cm^-1, while the near-IR located at 4 720, 4 597, 4 537, 4 441, 4 343, 4 203, and 4 170 cm^-1. The absorption peaks between 3 800～3 400 cm^-1 attributed to bending and stretching vibration of M—OH (M can be replaced by Al, Mg, Fe, Mn etc.), which decreased after heating treatment and vanished at 600 ℃. The water loss in heating treatment caused the weakening of bending vibration of structural water. The UV-Vis-spectra in natural brown samples showed 715, 540, and 417 nm absorption bend on the direction parallel to c-section, caused by Fe²⁺ d—d (⁵T_2g→⁵E_g), Fe²⁺→Fe³⁺ inter valence charge transfer (IVCT), and Fe²⁺→Ti⁴⁺ (IVCT) respectively. In this contribution, all samples contain high Mn content. The presence around 417 nm absorption is possibly influenced by the superposition of 413/414 nm absorption, which attributed to spin-allowed transitions of Mn²⁺in d—d orbits (⁶A_1g→⁴A_1g, ⁴T_Eg). After heating treatment, Mn³⁺ was reduced into Mn²⁺, which led to an augment in 414 nm absorption. Simultaneously, the absorption of 520 nm vanished as the content of Mn³⁺ decreased. The presence of 520 nm absorption might be a reason to form asymmetrical absorption in 540 nm band. After heating treatment above 450 ℃, the absorption band of 715 and 417 nm remained unchanged, while 540 nm vanished. The vanishment of 540 nm absorption band could be caused by partial Fe³⁺→Fe²⁺ charge transference in heating treatment, which led to the reduction of Fe²⁺→Fe³⁺ (IVCT) in the direction parallel to the c-section. The vanishment of 540 nm absorption band induced transmittance increase for the green-light region, which could be the reason of green color existence after heating treatment.
		2021 Vol. 41 (08): 2524-2529 [Abstract] ( 144 ) RICH HTML PDF (3911 KB) ( 77 )

	2530	A Multi-Derivation-Spline Wavelet Analysis Method for Low Atomic Number Element EDXRF
		WU Lian-hui^{1, 2, 3}, HE Jian-feng^{1, 2, 3*}, ZHOU Shi-rong^{2, 3}, WANG Xue-yuan^{1, 2}, YE Zhi-xiang^{2, 3}
		DOI: 10.3964/j.issn.1000-0593(2021)08-2530-06
		The information of elements to be measured in the energy dispersion X-ray fluorescence(EDXRF) spectrum is included in the characteristic peak position and the characteristic peak net peak area. Accurate detection of characteristic peaks is the key to energy dispersive X-ray fluorescence spectroscopy. The energy difference between the characteristic X-rays of many low sequence elements is very small, there are many kinds of interference in the process of fluorescence spectrum generation，resulting in serious overlapping peaks of measured X-ray fluorescence data, in this paper, overlapping peaks are taken as the research object，this paper presents a method to deal with overlapping peaks by combining the fourth derivative with the three-spline wavelet transform. The effectiveness of the method was tested by simulating overlapping peaks. The data of X-ray fluorescence spectrum and measured data are verified and analyzed. Firstly, the principle of the derivative method and three-spline wavelet method to decompose overlap is introduced in detail. The higher the derivative order, the more distorted the signal, but it can effectively improve the separation degree of the overlapping peak. The three-spline wavelet transform is weak for the to deal with peak with low separation degree, but it can effectively maintain the peak shape. By simulating the data. Among the three overlapping peaks, the separation degree of peak 1 and peak 2 is R=0.33. The separation degree of peak two and peak three R=0.67, after the fourth derivative there is some overlap in the signal, but the fourth derivative not only retains the peak position of the signal, and the degree of separation increases. Combined with the characteristics of the three-spline wavelet transform, by adjusting the value of the decomposition hierarchy, and reconstructed by scaling up the high frequency signal by a factor greater than 1, the simulated overlapping peaks are decomposed. The number of decomposition layers of the three-spline wavelet is four, and the amplification factor of high frequency is six times. Then, the overlapping spectrum of element K is simulated. The decomposition of overlapping peaks is realized. The simulation results show that the new method can accurately identify the peak position, and the error is within 1%. The applicability of the new method to X -ray fluorescence spectrum overlap peak decomposition is proved. It is verified that this method is feasible to decompose overlapping peaks. The last, is the Ca element X-ray fluorescence spectrum data and Mixed light element X-ray fluorescence spectrum data detected by the CIT-3000SY X-ray fluorescence element logging instrument were processed. Now the decomposition of the overlapping peaks and the peak position error after decomposition are controlled within 1%, with high accuracy. The experimental results show that: The fourth derivative combined with three-spline wavelet transform can effectively separate overlapping peaks. And it is practical to deal with the overlapping peak decomposition of X-ray fluorescence spectrum.
		2021 Vol. 41 (08): 2530-2535 [Abstract] ( 147 ) RICH HTML PDF (2920 KB) ( 44 )

	2536	Spectral and Index Analysis for Burned Areas Identification Using GF-6 WFV Data
		LIU Qian，QIN Xian-lin^*，HU Xin-yu，LI Zeng-yuan
		DOI: 10.3964/j.issn.1000-0593(2021)08-2536-07
		This study aims to explore the appropriate spectral bands and indices of GF-6 WFV data in identifying burned areas. The study area is located in three burned areas in the Greater Khingan Mountains forest region of Inner Mongolia of China. 11 indexes, including Normalized Difference Vegetation Index (NDVI), Global Environment Monitoring Index (GEMI), Enhanced Vegetation Index (EVI), Burned Area Index (BAI), Soil-Adjusted Vegetation Index (SAVI), Modified Soil-Adjusted Vegetation Index (MSAVI), Normalized Difference Water Index (NDWI), MERIS Terrestrial Chlorophyll Index (MTCI), Normalized Difference Red Edge Index 1 (NDRE1), Modified Chlorophyll Absorption Ratio Index 2 (MCARI2) and Modified Normalized Difference Soil Index (MNDSI) were selected according to the channels of GF-6 WFV data. To quantitatively evaluate the ability of selected spectral indexes and modified indexes to identify burned areas, the separability M was calculated between burned areas and other typical categories based on single-temporal and bi-temporal images. Then these 11 indexes and their differenced indexes were used to identify the burned areas. The results show that (1) the near-infrared band of GF-6 WFV and the two newly added red-edge bands provided better spectral separation, indicating an ability to reflect the characteristics of burned areas. (2) In terms of distinguishing between the same area before and after burned, NDVI, GEMI, EVI, BAI, SAVI, MSAVI and NDWI improved performance. Among four modified indexes, NDRE1 and MCARI2 performed better than MNDSI and MTCI. (3) As for distinguishing burned areas from other typical categories, BAI, NDVI, MCARI2 and NDWI performed better, followed by NDRE1, GEMI, EVI, SAVI and MSAVI, while MNDSI and MTCI performing poorly. (4) In extracting burned areas using indexes and differenced indexes, GEMI, EVI, BAI, SAVI and MSAVI performed better, followed by MCARI2, NDVI and NDWI with medium performance, while MTCI, MNDSI and NDRE1 performing poorly. In summary, BAI and GEMI had the best performance in identifying burned areas, followed by NDVI, EVI, SAVI, MSAVI, NDWI and MCARI2 with medium identification ability, while three modified indices MNDSI, NDRE1 and MTCI performing poorly.
		2021 Vol. 41 (08): 2536-2542 [Abstract] ( 218 ) RICH HTML PDF (2290 KB) ( 51 )

	2543	Early Detection of Cauliflower Gray Mold Based on Near-Infrared Spectrum Feature Extraction
		MU Bing-yu¹, ZHANG Shu-juan¹, LI Ze-zhen², WANG Kai¹, LI Zi-hui¹, XUE Jian-xin^1*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2543-06
		Gray mold easily occurs during cauliflower growth, thereby leading to reduced output. Cauliflower infected with gray mold at an early stage is difficult to detect with existing methods. In this study, near-infrared spectroscopy was used to distinguish and detect cauliflower with gray mold, which is highly significant for the disease control of cauliflower. Taking cauliflower with Botrytis cinema spore inoculation as the research object, this study obtained the near-infrared spectra of cauliflower in control and treatment groups and performed de-noising. The spectra of 608 samples in four batches (76 healthy and infected cauliflowers at 0.5, 1, 2 and 3 d old each) were acquired within the waveband range of 500～2 400 nm. After measuring the activity of polyphenol oxidase, peroxidase and malondialdehyde in the cauliflower samples, and one-way ANOVA was used to statistically analyze the quality indices of a single batch of healthy and infected cauliflowers. The Kennard-Stone algorithm was used to divide each day’s samples into a calibration (114 samples) and a prediction (38 samples)set. Competitive adaptive reweighted sampling (CARS) was then used to extract the feature waveband of the spectroscopic data of the four batches of cauliflower samples, and the discrimination models of single and combination batches were established based on of partial least square regression (PLSR). Results indicated that the naked eye could not identify infected cauliflower samples at the early stage of inoculation and could identify them only 3 d after infection when some infected samples showed evident disease characteristics. The measurement of quality indices of the cauliflower in the control and treatment groups showed significant differences in all quality indices between these groups 2 d after infection (p＜0.05); however no significant differences existed in all quality indices at 0.5 d, and a significant difference in MDA value existed only at 1d. These findings suggested that the quality indices of infected cauliflower cannot be discriminated at an early stage. The PLSR discrimination model of a single batch was established, and it showed the following: the discrimination accuracy of the model established for the first batch (0.5 d) reached 94.74%, the root-mean-square error of the prediction set was 0.835, and the discrimination accuracy of the models established for the second to fourth batch (1～3 d) reached 100%. These findings indicated that the PLSR model could detect infected cauliflower samples under a single batch at an early stage. The discrimination accuracy of the PLSR combination discrimination model reached 92.11% and 97.37% at 0.5 and 1 d, respectively, to discriminate a large proportion of infected cauliflower. However, the effect of PLSR combination-batch modeling was inferior to that of PLSR single-batch modeling. Therefore, using near-infrared spectroscopy, extracting the feature waveband through CARS, and establishing a PLSR model can detect cauliflower infected with gray mold at an early stage, thereby providing a reference for the early detection cauliflower with gray mold and has some practical value.
		2021 Vol. 41 (08): 2543-2548 [Abstract] ( 191 ) RICH HTML PDF (1667 KB) ( 198 )

	2549	Estimation of Potato Above Ground Biomass Based on UAV Multispectral Images
		LIU Yang^{1, 2, 4}, SUN Qian^{1, 4}, HUANG Jue², FENG Hai-kuan^{1, 3, 4*}, WANG Jiao-jiao^{1, 4}, YANG Gui-jun^{1, 4}
		DOI: 10.3964/j.issn.1000-0593(2021)08-2549-07
		Above ground biomass (AGB) is an important indicator of evaluating crop growth and guiding agricultural production and management. Therefore, AGB information was obtained timely, accurately and efficiently to provide a strong basis for predicting yields and securing grain trade. The conventional way to obtain AGB is to use destructive sampling methods that require manual harvesting of crops, weighing, and recording, making large-area and long-term measurements difficult. However, UAV remote sensing technology is considered the most effective way to estimate AGB of large area crops with the rapid development of precision agriculture. In this study, the multispectral images of the tuber formation period, tuber growth period and starch accumulation period were obtained by the UAV platform equipped with multispectral sensors. The measured plant height, AGB and latitude, longitude and altitude of ground control point (GCP) were measured on the ground. Firstly, using UAV multispectral images combined GCP location information basing structure from motion (SFM) algorithm to generate the digital surface model (DSM) of the potato experimental field, and DSM extracted the plant height (Hdsm) of each growth period. Then, four original single band vegetation indices, 9 multiband vegetation indices，high-frequency information (HFI) in the red edge band and Hdsm were selected with AGB for correlation analysis. Finally, based on single-band vegetation indices (x₁), multiband vegetation indices (x₂), vegetation indicescombined Hdsm (x₃)，vegetation indices combined HFI (x₄) and their integration (x₅) as input parameters were used to estimate AGB of each growth period by partial least squares regression (PLSR) and ridge regression (RR). The results showed that: (1) The R² of extracted Hdsm and measured plant height was 0.87 and NRMSE was 14.34%. (2) All model parameters reached highly significant levels with the AGB, and correlations increased and then decreased from the tuber formation period to the starch accumulation period. (3) Using the same method to estimate potato AGB with five variables at different growth periods, it starts to get better and then it gets worse for the effect of potato AGB from tuber formation period to starch accumulation period with the estimation accuracy from high to low was x₅>x₄>x₃>x₂>x₁. (4) The results showed that PLSR was better than RR in estimating AGB for different growth stages and basing x₅ combined PLSR method was the best in estimating AGB at tuber growth period with R² of 0.73 and NRMSE of 15.22%. Therefore, this study combined the selected multispectral vegetation indices combined HFI and Hdsm with the PLSR method can significantly improve the estimation accuracy of AGB, which provides new technical support for the monitoring of AGB in large areas of potato crops.
		2021 Vol. 41 (08): 2549-2555 [Abstract] ( 198 ) RICH HTML PDF (1044 KB) ( 79 )

	2556	Chlorophyll Content Estimation of Northeast Japonica Rice Based on Improved Feature Band Selection and Hybrid Integrated Modeling
		LIU Tan^{1, 2}, XU Tong-yu^{1, 2*}, YU Feng-hua^{1, 2}, YUAN Qing-yun^{1, 2}, GUO Zhong-hui¹, XU Bo¹
		DOI: 10.3964/j.issn.1000-0593(2021)08-2556-09
		Using spectral information to detect chlorophyll content in rice canopy leaves quickly, non-destructively and accurately has a great practical significance for rice growth evaluation, precise fertilization and scientific management. In this paper, japonica rice in northeast China is taken as the research object, and rice canopy hyperspectral data of key growth stages are obtained through plot experiments. Firstly, the standard normal variate (SNV) is used to preprocess the spectral data, based on the processed spectral data and the random frog (RF) algorithm, by combining a correlation coefficient analysis method (CC) and the successive projections algorithm (SPA), an improved random frog algorithm (fpb-RF) is proposed, which combines two primary bands to select the feature bands of chlorophyll content, It is compared with the standard RF, CC and SPA methods, respectively. A hybrid prediction model (GPR-P) with gaussian process regression (GPR) compensation partial least squares regression (PLSR) is proposed: PLSR method is used to preliminarily predict the chlorophyll content in rice to obtain the linear trend of chlorophyll content, and then the GPR with good nonlinear approximation ability is used to predict the deviation of PLSR model, then the final prediction value is obtained by superposition of two outputs. To verify the superiority of the proposed method, with the feature bands by different extraction methods as inputs, PLSR, Least Square Support Vector Machine (LSSVM) and BP neural network prediction models are respectively established. The results show that under the same prediction model conditions, the improved fpb-RF algorithm can better reduce the complexity and improve the model’s prediction performance by extracting feature bands as input. Both the determination coefficient (R²_P) of the test set and the determination coefficient (R²_C) of each model’s training set are higher than 0.704 7. In addition, the R²_C and R²_P of the proposed GPR-P model are both higher than 0.755 3 when each algorithm extracts feature bands. Among them, the GPR-P model with the input of the feature band extracted by the fpb-RF method has the highest prediction accuracy, R²_C and R²_P are 0.781 5 and 0.779 6 respectively, RMSE-C and RMSE-P are 0.904 1 and 0.928 3 mg·L^-1 respectively, which provides a valuable reference for the detection and evaluation of chlorophyll content in northeast japonica rice.
		2021 Vol. 41 (08): 2556-2564 [Abstract] ( 157 ) RICH HTML PDF (5222 KB) ( 70 )

	2565	Combining Textures and Spatial Features to Extract Tea Plantations Based on Object-Oriented Method by Using Multispectral Image
		HUANG Shao-dong¹, XU Wei-heng^{1, 2, 3*}, XIONG Yuan¹, WU Chao¹, DAI Fei^{1, 2, 3}, XU Hai-feng¹, WANG Lei-guang^{2, 3}, KOU Wei-li¹
		DOI: 10.3964/j.issn.1000-0593(2021)08-2565-07
		The tea plantations of Yunnan province are mainly fragmentally distributed in mountainous areas and often mixed with other ground objects, making it difficult to extract tea plantations with high precision based on remote sensing. Combining textures and spatial features based on Object-Oriented method is rarely applied to extract tea plantations in previous crop classification research using multi-spectral imagery. Therefore, it is necessary to explore further the recognition ability for tea plantations by using high spatial resolution and multi-spectral images under the fragmental and mountainous region. In this research, a typical mountainous area located between the northern Xishuangbanna autonomous prefecture and the southern of Pu’er city was used as our study area. A scene image with a 2 m resolution pan-chromatic and 8 m resolution multi-spectral derived from the GF-1 PMS sensor was used as the source data for our research. The eCognition Developer9.0 software was employed to segment the image by multi-resolution segmentation, and the ED3_Modified method was used to evaluate the optimal segmentation scale. Firstly，we constructed 23 dimensions of original features including 14 spectral features, 6 textures and 3 spatial features. Secondly, 16 optimal features were selected to classify by calculating the separation distance of five land-cover types. Thirdly, based on 16 optimal features space, three object-oriented supervised classification methods (Bayes, Decision Tree 5.0 (DT) and Random Forest (RF) were applied to extract the tea plantations of the study area. Finally, filed survey samples and random samples were used to validate the accuracy of tea plantations extraction results, and we compared the classification accuracies of different classification methods. The results showed that for the multi-classification (including tea plantations, forest, cropland, impervious and water body) the overall accuracy (OA)/ Kappa coefficient (Kappa) are Bayes (87.73%/0.70), DT5.0 (91.23%/0.78) and RF (88.52%/0.72) respectively, but for tea plantations, the producer accuracy (PA)/user accuracy (UA) are Bayes (67.23%/75.33%), DT (68.84%/83.83%) and RF (70.54%/87.13%). Compared with the object-oriented RF multi-classification, the OA and Kappa of the object-oriented RF binary classification (tea plantations and others) increased by 3.24% and 0.07, the PA/UA of tea plantations increased by 5.99%/5.61%. Similarly, compared with the pixel-based multi-classification, the OA and Kappa of the object-oriented RF binary classification increased by 23.32% and 0.27, the PA/UA of tea plantations increased by 21.10%/29.03%, respectively. The results indicated that the object-oriented supervised classification methods have the potential for tea plantations extraction, especially the object-oriented RF classification got a higher accuracy. Moreover, the binary classification method has higher accuracy than that of multi-classification for tea plantation extraction. Our object-oriented method that combined textures and spatial features with spectral features is effective for tea plantations extraction, especially when applied to the complex and fragmental mountainous landscape. Our method can meet the application requirements in fine tea plantations identification based on high-spatial resolution and multi-spectral imagery too.
		2021 Vol. 41 (08): 2565-2571 [Abstract] ( 260 ) RICH HTML PDF (7753 KB) ( 89 )

	2572	On-Line Fast Detection Technology of Chilled Fresh Meat Quality Based on Hyperspectral and Multi-Parameter
		FANG yao¹, XIE Tian-hua², GUO Wei¹, BAI Xue-bing¹, LI Xin-xing^1*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2572-06
		In order to solve the problems of complicated operation and irreversible damage of traditional chilled beef quality detection technology, this paper proposed a method of chilled beef quality detection based on hyperspectral fusion and multi-parameter fusion. The Region of Interest (ROI) spectra of chilled beef were extracted, and the texture parameters of chilled beef were measured: hardness, elasticity, adhesion, adhesion, chewing degree and resilience. After the parameter precision comparison, the cohesiveness and resilience are selected as the modeling parameters. Kennard-stone and the SPXY algorithms were used to divide the original spectral data respectively, and the optimal sample division method was determined by the prediction effect of the model built after sample division. Finally, 35 training sets and 7 test sets were obtained by dividing the samples by the SPXY algorithm. Based on the sample division of the SPXY algorithm, preprocessing of hyperspectral data was conducted by using first derivative (D1st), multiple scattering correction (MSC), second derivative (D2st) and standard normal transformation (SNV), which effectively eliminated the noise in the spectrum and improved the signal-to-noise ratio. The continuous projection method (SPA) is used to extract the spectral characteristic wavelength, which effectively reduces the shortcoming of the large amount of noise information contained in the full-band modeling, ensures the accuracy of the model and improves the running speed of the model. Finally, the partial least square method (PLSR) and principal component regression method (PCR) were used to construct the quality prediction model of chilled beef. When the cohesion was taken as the parameter, the SNV-SPA-PLSR model had the best performance, and the predicted correlation coefficient was 0.879 8. The D2st-SPA-PLSR model has the highest accuracy when regression is taken as the parameter, and the predicted correlation coefficient is 0.880 6. The experimental results show that the chilled meat quality detection method based on hyperspectral fusion and multi-parameter fusion can realize the fast quality detection of chilled beef.
		2021 Vol. 41 (08): 2572-2577 [Abstract] ( 178 ) RICH HTML PDF (2407 KB) ( 63 )

	2578	Analysis of Influencing Factors in Wheat/Maize Canopy RVI and NDVI Acquisition Using Ground-Based Remote Sensing System
		ZHENG Yu-dong¹, XU Yun-cheng¹, YAN Hai-jun^1*, ZHENG Yong-jun²
		DOI: 10.3964/j.issn.1000-0593(2021)08-2578-08
		Implement ground-based remote sensing technology in a large-scale sprinkler irrigation system can monitor crop growth status and has played an important role in detecting of crop water and nutrient demands and field management of crop production. Crop canopy has bidirectional reflectance characteristics, so different observation methods used in ground-based remote sensing will affect the accuracy of canopy spectral reflectance measurement. This study used a self-built ground-based remote sensing system to simulate the field observation conditions of large sprinkler irrigation machinery, obtained spectral reflectance information of wheat and maize canopy through multi-spectral optical sensors, and quantified the variation of the crop canopy information data caused by the canopy bidirectional reflection characteristics by the coefficient of variation CV, and analyzed the effect of the observation conditions on the crop canopy spectral reflectance measurements through influence factor weight W. Reflectance in the red band (650 nm) and reflectance in the near-infrared band (810 nm) of winter wheat at regreening to filling growth stages and summer maize at V7 to V14 growth stages were measured and recorded in 2019 season. Effect of various observation factors on the ratio of vegetation index (RVI) and the normalized index of vegetation (NDVI) was analyzed. Results showed that the correlation of observation height in 0.5~2.5 m, observation frequency in 2~60 min^-1 and moving speed in 0~4 m·min^-1 with the measurements of the canopy spectral reflectance characteristics were not significant (p>0.05); observation time in 8:00—18:00, observation zenith angle at -60°~60°, and observation azimuth angle from 0° to 180° had an extremely significant correlation with the measurements (p＜0.01). Results of canopy spectral reflectance measurement for wheat and maize depended mainly on the degree of the canopy coverage. Under the same leaf area index (LAI), the canopy spectral reflectance would also be affected by the observation time, observation azimuth and observation zenith angle: canopy spectral reflectance had significant bidirectional reflection characteristics. In wheat crop, the coefficients of RVI and NDVI variation were 15%~50% and 2%~50%，respectively, while in maize, they were 10%~33% and 18%~39%, respectively. When measuring RVI and NDVI with wheat and maize crops, the desired time for the measurement could be 12:00—14:00 because the solar zenith angle is relatively stable. The observation angle should be in a fixed angle, and also the influence of shadow effect and hot spot effect should be noticed. When measuring RVI and NDVI of wheat during regreening to jointing stage and heading to the flowering stage, close attention should be paid to the effects of observation zenith angle and observation time, respectively. This study performed a quantitative analysis of measuring canopy spectral reflectance with wheat and maize crops. The results obtained in the study could provide technical support for accurate and effective measurement of the crop canopy spectral reflectance.
		2021 Vol. 41 (08): 2578-2585 [Abstract] ( 239 ) RICH HTML PDF (4427 KB) ( 82 )

	2586	Application of Hyperspectral Image to Detect the Content of Total Nitrogen in Fish Meat Volatile Base
		ZOU Jin-ping¹, ZHANG Shuai², DONG Wen-tao², ZHANG Hai-liang^2*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2586-05
		For fish products, the study of freshness has always been an important topic. Among them, the total volatile base nitrogen (TVB-N) is an important indicator. This indicator has been listed in China food hygiene standards. Generally, under low temperature conditions, when the amount of volatile base nitrogen in fish reaches 30 mg/100 g, it is considered a sign of meat deterioration. Traditional physical detection methods cannot achieve quantitative detection, andchemical testing methods are time-consuming and require professionals to perform destructive testing. In order to overcome the shortcomings of traditional spectral detection techniques that can not detect and analyze external space properties, this paper uses a wavelength range of 900～1 700 nm. Hyperspectral imaging technology combined with stoichiometry that has achieved the detection of TVB-N content in salmon. First, the fresh salmon bought from the market is divided into back and abdomen, and the back and abdomen are divided into 10 equal parts, each salmon is made into 20 samples, a total of 100 samples, 75 of which are used for calibration set, and 25 samples are used for prediction set, then use the hyperspectral imaging system to collect the spectral data of the salmon fish sample, next determine the content of salmon TVB-N by distillation, and establish its physical and chemical value samples, after that use the least square support vector machine (LS-SVM) and partial least squares (PLS) model performs salmon TVB-N modeling analysis on 100 sample spectral full wavelength data. The prediction coefficient of determination (R²) of the LS-SVM model and the PLS model are 0.918 and 0.907, respectively, and the root mean square error (RMSEP) of the prediction is 2.312% and 2.751%, respectively. In order to further improve the computational efficiency and optimize the model, 8 characteristic wavelengths (956, 1 013, 1 152, 1 210, 1 286, 1 301, 1 397, 1 464 nm) are extracted from the full spectrum data using the successive projections algorithm (SPA). For the LS-SVM and SPA-PLS models, the model prediction coefficient of determination (R²) is 0.903 and 0.901, and the RMSEP is 2.761% and 2.801%, respectively. The results of the SPA-LS-SVM model are better than those of the SPA-PL. Finally, the SPA-LS-SVM model was selected as the most suitable TVB-N prediction model due to its reliability and effectiveness. Based on image processing programming technology, each pixel in the hyperspectral image was converted into a corresponding TVB-N value and used different colors to indicate the visual distribution of the TVB-N content of salmon meat, which can vividly express the distribution of TVB-N content of salmon. Experiments show that hyperspectral imaging technology can be used to predict the content of salmon TVB-N, which lays the foundation for the automatic processing and classification of aquatic products. Fisheries can benefit from hyperspectral technology.
		2021 Vol. 41 (08): 2586-2590 [Abstract] ( 172 ) RICH HTML PDF (1865 KB) ( 51 )

	2591	Prediction and Distribution Visualization of Salmon Quality Based on Hyperspectral Imaging Technology
		SUN Zong-bao, LI Jun-kui, LIANG Li-ming, ZOU Xiao-bo^*, LIU Xiao-yu, NIU Zeng, GAO Yun-long
		DOI: 10.3964/j.issn.1000-0593(2021)08-2591-07
		In this study, color, shear force and K value was used to evaluate the quality of salmon with different freeze-thaw times, and then predicted by hyperspectral imaging technology combined with chemometric methods. Besides, the prediction performance of the PLS model developed with characteristic variables was compared and discussed to select the optimal variable selection method for color, shear force and K value. The prepared salmon samples with different freeze-thaw times were scanned and analyzed to obtain hyperspectral data and the true values of quality indicators (color, shear force, K value). Afterwards, six different pretreatment methods were used to reduce dark current and noise interference in the spectral data. The competitive adaptive reweighting algorithm (CARS), interval variable iterative space shrinkage approach (iVISSA), and iVISSA-CARS algorithms were applied to screen out variables related to the indicators to improve the prediction performance of the model. The optimal variable selection method was determined according to the prediction performance of the PLS model built by the characteristic variables screened by the three-wavelength selection algorithms. The result exhibited that the 1^st Der-CARS-PLS model developed by 51 characteristic variables related to a^* possessed the best prediction with R_c of 0.931 6, R_p of 0.929 7, RMSECV and RMSEP of 0.72 and 0.74, respectively. Similarly, in shear force prediction, 2^nd Der proved to be the best pretreatment method and 2nd Der -CARS -PLS model developed by 61 characteristic variables displayed the best prediction with R_c of 0.885 3, R_p of 0.860 9, RMSECV and RMSEP of 0.69 N and 0.90 N respectively. Besides, the N-CARS-PLS model built by 51 characteristic variables achieved the best predictive effect on K value and obtained R_c of 0.951 3, R_p of 0.946 0, RMSECV and RMSEP of 1.33 and 1.53, respectively. It indicates that CARS can effectively extract variables related to feature indicators and improve the prediction performance of the PLS model. Besides, the combined algorithm iVISSA-CARS-PLS also achieved a significant results in the prediction of the three indicators. The R_p of the test set was 97.48%, 97.02% and 98.98% of the CARS-PLS prediction model. In comparison, the number of variables used was only 60.78%, 62.29% and 60.78% of CARS-PLS, indicating that the variable selection combined algorithm greatly reduces the amount of data. The CARS-PLS and iVISSA-CARS-PLS models of the three indicators show higher prediction performance than iVISSA, which indicates that the feature variable selection strategy of CARS is more advantages than iVISSA in predicting of the above three quality indicators of salmon. Using the optimized PLS model, the visual distribution map of salmon quality indexes with different freezing and thawing time was constructed in the form of a pseudo color images, which provided more detailed and intuitive information for understanding the quality of salmon. In general, the combination of hyperspectral imaging combined with chemometrics, can accurately and non-destructively determine the quality indicators in salmon. This study can provide the same theoretical reference for the simultaneous rapid detection of multiple quality indicators of salmon.
		2021 Vol. 41 (08): 2591-2597 [Abstract] ( 160 ) RICH HTML PDF (3326 KB) ( 53 )

	2598	Hyperspectral Image Features Combined With Spectral Features Used to Classify the Bruising Time of Peach
		OUYANG Ai-guo, LIU Hao-chen, CHENG Long, JIANG Xiao-gang, LI Xiong, HU Xuan
		DOI: 10.3964/j.issn.1000-0593(2021)08-2598-06
		From the ripening of the fruit tree to reaching the consumers, the peaches need to go through a series of processes such as picking, packaging, and transportation. In each process, bruised fruit may occur. Therefore, it is particularly important to check which process produces the most bruises and to improve the processing process in a targeted manner. Throughout the application of hyperspectral technology in detecting fruit bumps at home and abroad, most of them ignore image features and only use spectral features. Modeling based on image features combined with spectral features is rare. Secondly, the interval is usually the number of days in terms of the qualitative judgment of fruit bump time. The larger time interval, the longer fruit bump time, and the more obvious change, the higher detection accuracy. There is no effective method of classifying the bump time for the fruits which were bruised in a very short time. In this paper, 90 simulated surface bruises were taken as experimental samples, and hyperspectral images of the bruises 12, 24, 36 and 48 h were collected respectively. The spectral feature extraction of the peach sample uses the average spectrum of 100 pixels in the region of interest to prevent the spectral information of a single-pixel from being significantly different from the overall spectral information; The PC1 image that can best reflect the bruise of the peach is selected after dimensionality reduction by principal component analysis (PCA). In the weight coefficient curve of the PC1 image, 4 characteristic wavelength points (512, 571, 693, 853 nm) at the peak and valley points are selected as the characteristic image. The average gray value which calculates as the characteristic image after graying is used as the feature of the bruised peach image. Finally, based on the least squares support vector machine (LS-SVM) algorithm, three discriminant models, namely the spectral feature model, image feature model and image feature combined with the spectral feature model of the peach bruise time were established, and the performance of models was judged according to their classification accuracy. The research results show that the classification accuracy of the three peach bruise models increases with the increase of bruise time; the model based on the radial basis kernel function (RBF_kernel) combined with the spectral features has the best predictive effect, and it has the best prediction effect on bruises. The recognition accuracy rates of the peach samples at 12, 24, 36 and 48 h were 83.33%, 96.67%, 100% and 100%, respectively. This may be due to the model established by the radial basis kernel function with nonlinear characteristics is more suitable for peach Classification of bump time. The model combining image features with spectral features can better estimate the fruit bump time, and it can provide a certain reference and basis for fruit external quality sorting, which has certain reference significance for fruit sales and deep processing enterprises.
		2021 Vol. 41 (08): 2598-2603 [Abstract] ( 180 ) RICH HTML PDF (2564 KB) ( 59 )

	2604	A New Copper Stress Vegetation Index NCSVI Explores the Sensitive Range of Corn Leaves Spectral Under Copper Pollution
		XIA Tian^1*, YANG Ke-ming², FENG Fei-sheng³, GUO Hui⁴, ZHANG Chao²
		DOI: 10.3964/j.issn.1000-0593(2021)08-2604-07
		At present, heavy metal pollution in the soil is becoming more and more serious in China. Hyperspectral remote sensing has become a hot spot in the research of heavy metal pollution in crops by reason of its characteristics such as high spectral resolution and integrated maps with spectral. The spectral of crops will change slightly after being contaminated by heavy metals, how to explore the sensitive bands in the leaves spectral stresses by heavy metal pollution is a current research direction. In this study, a new copper stress vegetation index (NCSVI) was proposed to explore the sensitive range of corn leaves spectral under copper stress. By designing corn stress experiments with different gradients, the spectral and the contents of Cu²⁺ in corn leaves under each copper stress concentration were determined. First, the spectral of corn leaves were divided into 11 sub-band intervals, NCSVI were constructed by spectral reflectance corresponded to the middle wavelength of each sub-band interval. Then, the Pearson correlation coefficient and RMSE (Root Mean Square Error) between NCSVI and the contents of Cu²⁺ in each corn leaves was calculated, combined with three conventional vegetation indexes of water band index (WBI), modified chlorophyll absorption ratio index (MCARI) and normalized water index (NDWI). Finally, the corn leaves spectral which obtained under the same experimental conditions in other year were selected for verification to confirm the stability and effectiveness of NCSVI. The results show that among the 11 sub-band intervals, only the four sub-band intervals of a green peak, red edge, near the valley, and near peak A, the absolute value of the correlation coefficient between NCSVI and Cu²⁺ contents of corn leaves were higher than 0.9, respectively to -0.94, -0.97, -0.94，-0.96, as for RMSE, the root mean square error were less than 15, reached to 12.57, 8.71, 12.71 and 10.06. However, the highest correlation coefficient of WBI, MCARI and NDWI only reached to 0.75. The smallest RMSE was 24.21. Indicating that NCSVI corresponded to the four subintervals had a better indicator of copper pollution in corn leaves. The above results were verified by corn experiments under the same conditions in a different year, and it was found that among the 11 subintervals, only four subintervals of a green peak, red edge, near the valley, and near peak A had its absolute value of the coefficient R between NCSVI and the contents of Cu²⁺ in corn leaves were greater than 0.9, respectively to -0.9, -0.97, -0.97 and -0.93, as for RMSE, the root mean square error were less than 1.55, reached to 1.50, 0.85, 0.78 and 1.29, which were higher than WBI, MCARI and NDWI, and with the same sensitive sub-band intervals in the experiment of 2016, indicating that NCSVI could detect the sensitive range of corn leaves spectral stressed by Cu²⁺, with the characteristics of high efficiency and good stability. The NCSVI index proposed in this paper can be used as a method to monitor copper pollution in corn leaves, and provide some theoretical supports for the research of heavy metal pollution in other crops.
		2021 Vol. 41 (08): 2604-2610 [Abstract] ( 172 ) RICH HTML PDF (3501 KB) ( 53 )

	2611	Spectral Characteristics and Color Origin of Unstable Yellow Sapphire
		WANG Yu-yan¹, YANG Ling-yue¹, LI Ming², YANG Peng-tao³, Andy Hsitien Shen¹, WANG Chao-wen^1*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2611-07
		Yellow sapphires with unstable color are widely available in the market. How to effectively identify the characteristics of color unstable yellow sapphires is a hot topic in gemological research. In this paper, color-changing experiment, Ultraviolet-visible spectroscopy and 3D fluorescence spectroscopy were employed to study spectral characteristics of color-stable yellow sapphires. The color-changing experiment revealed that a part of yellow sapphires from Sri Lanka have unstable color, showing a photochromic phenomenon. Short-wave ultraviolet light dyed the original color, while sunlight faded the original color. The color of yellow sapphire after ultraviolet light is composed of stable part and unstable part. Color-unstable sapphire in the “colored state” and the “faded state” both showed blue-violet region absorption in the UV-Vis spectrum, which was likely related to the charge transfer of O^2--Fe³⁺, causing the stable yellow coloration of sapphire. The UV-Vis spectrum of sapphire with obvious color changes showed a significant absorption enhancement in the blue-violet region in the “colored state” compared to the “faded state”, which might attribute to ultraviolet irradiation enhancing the charge transfer between O^2--Fe³⁺. The UV-Vis spectroscopy result showed that samples had a weak Fe-related absorption peak, consistent with low Fe content. The low Fe concentration in the yellow sapphire is not enough to produce a stable yellow in color. 3D fluorescence spectra results revealed that the samples in “colored state” and “faded state” had the same fluorescence center (excitation wavelength=325～335 nm and emission wavelength=560～570 nm). The fluorescence intensity in the “colored state” is much higher than that in the “faded state”. Iron-containing yellow sapphire has a fluorescent effect, and the characteristic fluorescent center can be used as a potential identification characteristic to identify color-unstable yellow sapphire. This paper comprehensively reports the spectral characteristics and possible color causes of unstable yellow sapphires, providing potential identification characteristic to identify color-unstable yellow sapphire and a theoretical basis for the subsequent color modification process.
		2021 Vol. 41 (08): 2611-2617 [Abstract] ( 267 ) RICH HTML PDF (5178 KB) ( 119 )

	2618	Gemological and Spectral Characteristics of Mexican Red Blue Amber
		ZHAO Tong¹, WANG Ya-mei^1,2, LIU Ling¹, LI Yan^1,3*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2618-08
		In recent years, Mexican blue amber has become popular and has an increasing market share. Red blue amber is one of the varieties of blue amber, it usually has a maroon oxide surface layer, and the inner amber has blue-green fluorescence under ultraviolet light, so it’s also called “red skin blue amber”. However, the red blue materials in Mexican amber are very scarce due to the limitation of the formation conditions. In this research, gemological characteristics and spectral characteristics of Mexican red blue amber were studied using gemological routine methods, microscopic observation, infrared spectroscopy and photoluminescence spectroscopy Mexican black skin amber was investigated as a comparison with red blue amber. The red skin of Mexican red and blue amber is often slightly transparent, and its interior is translucent to slightly transparent. The thickness of red skin is uneven, and it is composed of black dots wrapped and flowing. The red part shows weak to no fluorescence under long-wave ultraviolet, and the inside shows strong blue fluorescence. The FTIR absorption peaks at 1 723 and 1 233～1 046 cm^-1 in the red part of the red blue amber are respectively caused by oxygen-containing groups C═O and C—O. The absorption peak caused by —CH₃ is located at 2 928 cm^-1. The oxygen-containing group C═O is the chromophore that makes red blue amber appears red. The absorption intensity ratio of the C═O peak and —CH₃ peak of the red blue amber red part is about 4/5, and the inner part is about 2/5~1/2. The oxidation degree of the red part of red blue amber is stronger than the inner part, while the oxidation degree of red blue amber’s inside is higher than that of the black skin amber’s inside. Photoluminescence spectroscopy results show that the red part of red blue amber has different luminescence centers with the inner part. The luminescence centers of red part are located at 562 and 506 nm, while the inner part mostly emits 467 and 472 nm center. As the degree of oxidation increases, the luminescent center gradually shifts to red spectra region, and the fluorescence intensity is significantly decreases. C═O quenches the fluorescence of Mexican red blue amber. The inner part of the black skin amber has two wide luminescence centers of 489 and 466 nm. The fluorescence intensity of black skin amber inside is higher than that of red blue amber inside. This research provides a basis for the identification of Mexican red blue amber and is beneficial for readers to distinguish Mexican red blue amber from other origins and other varieties. It has important theoretical significance and market application value.
		2021 Vol. 41 (08): 2618-2625 [Abstract] ( 188 ) RICH HTML PDF (7746 KB) ( 75 )

	2626	The Spectral Characteristics of “Edison” Pearls and Nucleated Pearls With Dyeing Treatment
		YU Lei, WANG Ya-mei^*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2626-07
		Fresh water nucleated cultured pearls with large grain size, high roundness and rich color (the commercial name is “Edison” Pearl) provide higher quality and value for the pearl market. However, due to the trend of interests, dyed nucleated cultured pearls gradually flow into the market, which disturbs the healthy consumption of consumers and hinders the sound development of “Edison” pearl industry to a certain extent. In this paper, infrared spectrometer, ultraviolet-visible spectrophotometer and photoluminescence spectrometer were used to systematically study the spectra of cultured and dyed “Edison” pearls and compared with seawater pearls and dyed seawater pearls. The results showed that: (1) the dyed and cultured “Edison” pearls showed aragonite vibration peaks at 1 445, 882 and 725 cm^-1 in the infrared spectrum, and the dyed “Edison” pearls showed a broad and weak absorption peak at 3 800 cm^-1; (2) The absorption peak at 280 nm of dyed “Edison” pearls is obviously weaker than that of cultured “Edison” pearls, which may be related to the damage of protein molecules in pearls caused by dyes. After dyeing, the overall reflectivity of “Edison” pearls decreased. Dyed yellow “Edison” pearl lacks the absorption peak at 360~380 nm of cultured orange-yellow “Edison” pearl, which is similar to the strong absorption peak at 430 nm of dyed seawater gold beads. Dyed black “Edison” pearls have absorption peaks at 425 nm, dyed sea water black pearls have absorption peaks at 480 and 645 nm, and cultured sea water black pearls have absorption peaks at 702 nm. The difference between the three patterns may be due to their different dyes; (3) A group of absorption peaks can be seen in the range of 450~550 nm in the photoluminescence spectrum of cultured “Edison” pearls. The luminous center of dyed “Edison” pearls shifts to the red zone, and absorption peaks related to dyes appear around 650 nm with different intensities. Dyed seawater gold beads also have absorption peaks related to dyes at 600 nm.
		2021 Vol. 41 (08): 2626-2632 [Abstract] ( 173 ) RICH HTML PDF (4064 KB) ( 126 )

	2633	Multiple Discharges-Enhanced Laser-Induced Breakdown Spectroscopy
		ZHU Zhi-feng, LI Bo, GAO Qiang^*, LI Zhong-shan
		DOI: 10.3964/j.issn.1000-0593(2021)08-2633-05
		Laser-induced breakdown spectroscopy (LIBS) is an elemental analysis technique widely used throughout science and engineering. A limitation of LIBS is the low analytical sensitivity for trace elements. Therefore, it is of great significance to enhance the signal intensity and reduce the detection limit of LIBS. To enhance LIBS signals, here we propose a method, multiple discharges-enhanced LIBS. The measurements were performed on a solid aluminum alloy. A nanosecond laser was focused on the alloy to generate plasma. The plasma was sputtered into the air between the two discharge electrodes, which triggered the discharge. Multiple discharges were generated by using a high-frequency discharge power source. The multiple discharges excite, heat the plasma and extend the plasma duration, thereby enhancing the signal intensity. Here, a direct current pulse power source with a frequency of 100 kHz was used, and five discharges occurred after each laser-induced breakdown. We show that compared with LIBS, the plasma duration is extended by approximately 50 μs. Multiple discharges-enhanced LIBS increases the signal intensity of Mg Ⅱ (at ~279 nm) by about 48 times; Al Ⅱ (at ~358 nm), 72 times; trace element Mn Ⅰ (at ~403 nm), 6.3 times; trace element Cu Ⅰ (at ~403 nm), 8.3 times. The detection limit of Mn Ⅰ (at ~403 nm) is reduced by a factor of 6; Cu, 8. Multiple discharges-enhanced LIBS dramatically enhances the signal intensity and improves the detection limit of LIBS, and it expands the applications of LIBS. This method has the potential to be applied to the identifications of valuables, rare materials and cultural relics.
		2021 Vol. 41 (08): 2633-2637 [Abstract] ( 158 ) RICH HTML PDF (2694 KB) ( 50 )

	2638	Rapid Classification of Steel by a Mobile Laser-Induced Breakdown Spectroscopy Based on Optical Fiber Delivering Laser Energy
		LI Wen-xin¹, CHEN Guang-hui^{1, 3}, ZENG Qing-dong^{1, 2*}, YUAN Meng-tian^{1, 3}, HE Wu-guang¹, JIANG Ze-fang¹, LIU Yang¹, NIE Chang-jiang¹, YU Hua-qing¹, GUO Lian-bo²
		DOI: 10.3964/j.issn.1000-0593(2021)08-2638-06
		In order to realize the industrial on-site rapid detection and identification for special steel, a mobile laser-induced breakdown spectroscopy prototype based on optical fiber delivering laser energy is adopted in this experiment to collect the spectral data of 14 special sheets of steel. The spectra of special steels were rapidly classified via dimensionality reduction in which pre-selected spectral lines were traversed, combined with a support vector machine (SVM).In the experiment, original spectral data, normalized spectral data and normalized spectral data after traversed were used as the input vectors of the SVM classification model, and the recognition accuracy of the model for special steels under different input vectors was compared. The results show that on the basis that more than 51 spectral lines were selected as input variables, the recognition accuracy of normalized spectral data as input variables for steels reaches 95.71%. It is significantly higher than 11.43%, whose accuracy was used raw spectral data as the input vector. Further, the MATLAB program was used to traverse the spectral line combination to choose the optimal input features. When 6 specific spectral lines were selected, the accuracy of special steels recognition reached 100%, and the modeling speed was also improved accordingly. It can be seen that when a large number of common feature data are pre-selected, automatic feature selection by machine has obvious advantages over the spectral line of manual selection. The SVM algorithm based on this dimension reduction method has a good industrial application prospect in LIBS rapid classification technology.
		2021 Vol. 41 (08): 2638-2643 [Abstract] ( 172 ) RICH HTML PDF (2133 KB) ( 179 )

	2644	Study on Spectral Characteristics of Large Diameter Plasma Jet
		ZHAO Na^{1, 2}, WU Kai-yue¹, CHEN Jun-yu¹, JIA Peng-ying¹, LI Xue-chen^1*
		DOI: 10.3964/j.issn.1000-0593(2021)08-2644-05
		Atmospheric pressure plasma jet which can generate a plasma plume has good application prospects in wastewater purification, element detection, material treatment and so on, because the plasma plume is rich in abundant active species. In addition, the diameter of the plasma plume is usually small, which limits its work efficiency. In view of this, in this work, a large scale uniform plasma plume with a diameter of about 14 mm is produced in a plasma jet excited by an AC voltage in Ar at atmospheric pressure. The electron density and the concentration of oxygen atom as a function of different experimental parameters are studied by means of emission spectroscopy. Photoelectric measurement results show that the luminance of plasma plume increases when applied peak voltage or argon flow increases. There are two optical emission pulses per voltage cycle both in upstream and downstream regions of the plasma plume when the peak voltage is low, and the intensity of optical emission signal in the upstream is higher than that in the downstream. Both optical signal intensities of plasma plumes in the upstream and downstream increase with the increasing of peak voltage. There are three optical emission pulses at each voltage period in the upstream and downstream when the peak voltage is high. Regardless of the number of discharge pulses per voltage cycle, the optical emission signals for the upstream and downstream of the plasma plume are synchronous. OH, N₂, Ar, and O Ⅰ spectral lines can be observed from emission spectrum in the range of 300~800 nm both in the upstream and downstream discharge collected by a spectrometer. The emission intensity of Ar upstream is higher than that downstream, while the emission intensity of OH and N₂ is lower than that in the downstream. The electron densities for the upstream and downstream of the plasma plume are measured by spectral line intensity ratio. The results show that the electron density in the upstream discharge is on the order of 10¹⁴ cm^-3, which is higher than that in the downstream plume (10¹³～10¹⁴ cm^-3). In addition, the electron densities of the plasma plume increase with the increase of peak voltage and argon flow both upstream and downstream. In addition, The variations of concentration of oxygen atom with different experimental parameters are studied by using optical actinometry. It is shown that the concentration of oxygen atom decreases along the flow direction. For the plasma plume, the oxygen concentration increases with the peak voltage and the argon flow, averagely. The experimental phenomena mentioned above are explained qualitatively based on the theories of gas discharge.
		2021 Vol. 41 (08): 2644-2648 [Abstract] ( 180 ) RICH HTML PDF (2613 KB) ( 67 )

	2649	Identifying Gas-Washing and Water-Washing of Oil Reservoirs by Fluorescence and Infrared Spectra of Single Oil Inclusion
		SU Ao¹, LI Pei-jun^2*, LEI Ming-zhu³, LIU Qiang⁴, ZHANG Xin⁵
		DOI: 10.3964/j.issn.1000-0593(2021)08-2649-08
		Samples in the two oil fields with reported gas-washing and water-washing were collected for fluid inclusion analysis. Micro-fluorescence and Fourier infrared spectra of single oil inclusions were measured to study the different effects of gas-washing and water-washing on oil compositions. The results show that spectral parameter QF₅₃₅ values of the oils altered by gas-washing were expanded toward decreasing and increasing, respectively. The CH₂/CH₃ distribution range ratio does not expand significantly, but the peak values are averaged. And the distribution of H₂O/Alkanes has no change. The QF₅₃₅ values of the oils affected by water-washing increased towards the increase direction, and the distribution ranges of both CH₂/CH₃ and H₂O/Alkanes increase significantly. The changes of QF₅₃₅ in light oil reservoirs altered by gas-washing and CH₂/CH₃ in heavy oil reservoirs by water-washing are not obvious. Therefore, two spectral parameter distribution trend charts of light and heavy oil reservoirs are summarized to discriminate the gas-washing and water-washing processes. This study is of great practical significance to utilize fluid inclusion analysis to restructure stages and processes of petroleum accumulation.
		2021 Vol. 41 (08): 2649-2656 [Abstract] ( 159 ) RICH HTML PDF (2431 KB) ( 52 )

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