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2020 Vol. 40, No. 01 Published: 2020-01-01

	1	Raman Spectral Characteristics of Human Embryonic Stem Cells and Acute Promyelocytic Leukemia Cells
		LIANG Hao-yue, CHENG Xue-lian, YANG Wan-zhu, YU Wen-ying, LI Chang-hong, DONG Shu-xu, ZHAO Shi-xuan, RU Yong-xin^*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0001-09
		Acute promyelocytic leukemia (APL) belongs to acute myeloid leukemia (AML) and is an M₃ subtype in FAB typing. Some APL patients develop a promyelocytic leukemia/retinoic acid receptor fusion gene, the PML-RARα fusion gene. Under the combined action of various factors inside and outside, promyelocytic leukemia is onset. Embryonic stem cells (ESCs) have the ability to multi-differentiate. Under certain induction conditions, ESCs can differentiate into hematopoietic system. Promyelocytes are located downstream of ESCs differentiation and are a cell in the granulocyte differentiation stage. Exploring a non-labeled technical method to identify hematopoietic cells at different stages of differentiation has important scientific and practical significance. Raman spectroscopy can be used for differential diagnosis of many types of diseases, and its application prospects have become more extensive in recent years. This experiment investigated the Raman spectral characteristics of human embryonic stem cells leukemia cell line (ES), acute promyelocytic leukemia cell line (NB4) and leukemia cells from 4 patients with acute promyelocytic leukemia (M₃), established a novel Raman label-free method to distinguish leukemia-related cells of distinct differentiation stages and provided basis for clinical research. Leukemia cells were collected from human embryonic stem cell line, acute promyelocytic leukemia cell line and bone marrow of patients. Raman spectra were acquired by Horiba Xplora Raman spectrometer and Raman spectra of 25~30 cells from each group or each patient were recorded. The diagnostic model was established according to principle component analysis (PCA), discriminant function analysis (DFA), cluster analysis and partial least squares discrimination analysis (PLS-DA), and the spectra of three kinds of cells were analyzed and classified. Characteristics of Raman spectra were discussed combined with ultrastructure of leukemia cells. There were significant differences among Raman spectra of three kinds of leukemia-related cells. Compared with ES cells, the spectra of acute promyelocytic leukemia cells showed stronger peaks which contributed to nucleic acids, proteins and lipids. Its biological mechanism involved the close relationship between APL and the PI3K/Akt/mTOR pathway. The PI3K/Akt/mTOR pathway was abnormally activated in acute promyelocytic leukemia cells, affecting the biomacromolecular metabolism of leukemia cells. The diagnostic models established by PCA-DFA, cluster analysis and PLS-DA could successfully classify these Raman spectra of different cells with a high accuracy of 100% (181/181). The model was evaluated by “Leave-one-out” cross-validation and reached a high accuracy of 98.9% (179/181). The proliferation and metabolism of M₃ cells and NB4 cells were higher than those of ES cells. The diagnostic models established by PCA-DFA, cluster analysis and PLS-DA can classify these Raman spectra of different cells with a high accuracy. Raman spectra show consistent result with ultrastructure by TEM.
		2020 Vol. 40 (01): 1-9 [Abstract] ( 332 ) RICH HTML PDF (5856 KB) ( 237 )

	10	Shape-Controlled Synthesis of NaMgF₃∶Gd³⁺ Nanocrystals and Its Upconversion Photoluminescence Properties
		YANG Yong-xin^1,2, XU Zheng^1,2*, ZHAO Su-ling^1,2, QIAO Bo^1,2，SONG Dan-dan^1,2, LIANG Zhi-qin^1,2, ZHU Wei^1,2, XU Xu-rong^1,2
		DOI: 10.3964/j.issn.1000-0593(2020)01-0010-05
		In this study, rare earth ions Yb³⁺ and Er³⁺ co-doped into NaMgF₃∶Gd³⁺ nanoparticles were successfully prepared by modified solvothermal method. The structure of the prepared sample was determined by X-Ray Diffraction, and the average particle size was calculated by using the Debye-Scherrer formula. The particle size of the sample was within the nanometer range. The results of further experiments show that with the change of the concentration of Gd³⁺ in the reactants, the morphology of the nanoparticles appears to change from nanosheets to nanowires, so as to realize the regulation of nanocrystals. At the same time, the photoluminescence properties of the prepared nanoparticles under 980 nm excitation light were studied in detail. It is worth noting that the emission intensity of nanoparticles gradually increases with the change of Gd³⁺ doping concentration, and the tendency of green to red emission occurs.
		2020 Vol. 40 (01): 10-14 [Abstract] ( 212 ) RICH HTML PDF (3114 KB) ( 106 )

	15	The Theoretical Study on the Infrared Spectra and Molecular Interaction of 3-Furoic Acid
		LI Hui-xue, WANG Jia-peng
		DOI: 10.3964/j.issn.1000-0593(2020)01-0015-07
		The single molecular configuration of 3-furoic acid was optimized using the density functional theory B3LYP/6-311G+(d,p) and the second-order perturbation theory MP2/6-311+G (d,p), and both the stable geometries were obtained, the barrier of the isomerization reaction, which corresponds to the configuration I turning into the configuration II, is 32.10 kJ·mol^-1, which implies the isomerization reaction is very difficult to occur. The percentage of the configuration I with low energy is much more than that of the configuration II with high energy based on Boltzmann distribution law, which shows that the configuration I is stabler at room temperature. The vibration frequency of the monomer was calculated based on the stable structures at the same level in anharmonic force field, the potential energy distribution（PED） of each vibration frequency was calculated and the normal modes were analyzed and assigned, and the absorption peaks between 2 000~2 500 cm^-1 can be explained using double frequency and combined frequency. It was found that the calculated IR spectrum of the monomer matched up with the experimental gaseous IR spectrum. As to the dimer, the M06 density functional was employed to simulate the nature for including the corrective term of weak interaction, the calculated IR spectrum of the dimer in anharmonic force field was familiar to the experimental IR spectrum of the solid-state, based on the theoretical computation, the weak peaks appearing on 2 000~3 000 cm^-1 wavenumbers correspond to all kinds of overtone vibrations, the infrared transition between the vibrational ground state, of which the quantum number is 0, and the second vibrational excited state, of which the quantum number is 2, is too weak and can be ignored, and these overtone peaks are mainly from the sum of the fundamental frequencies, due to the dimers binding together with hydrogen bonds instead of chemical bonds, the rigidity of dimers is lower, and the anharmonicity of dimers increases, the intensity of the related overtone peaks also increases with the anharmonicity, these peaks in the dimer become very evident compared with those in the monomer, which agree with the experimental spectrum, however, because of a variety of dimers and polymers in the actual solid state, the intensity of the absorption peaks of the hydroxyl is reduced and the peak width of that is widened, in addition to the lack of the suitable parameters to calculate weak interaction, the universal force field and reasonable dispersion correcton factors in quantum chemistry makes the calculated spectra have certain error compared with the experiment ones, further more, the natural bond orbital (NBO) analysis was performed to reveal the origin of interaction, and it was found that the second order stabilization energy from the oxygen atom in the carboxyl group as the donor and the hydroxyl as the acceptor is 121.4 kJ·mol^-1, the binding energy between the dimer is 65.27 kJ·mol^-1, the amount of transferred charge from the donor orbital to the acceptor orbital is 0.067 electron. The result showed that the intermolecular interaction of 3-furoic acid mainly originated from the intermolecular hydrogen bond. The Gibbs free energy change ΔG of the dimer under different temperatures were computed, the dimer will become unstable at 500 K for the ΔG of the dimer being positive value, the hydrogen bond is destroyed, and all the monomers will get together with molecular interaction.
		2020 Vol. 40 (01): 15-21 [Abstract] ( 220 ) RICH HTML PDF (1807 KB) ( 104 )

	22	*Removal Behavior and Mechanism of Uranium by Bacillus Siamensis* Based on Spectroscopic Analysis: the Role of Biological Phosphorus**
		ZHOU Lin^{1, 2}, DONG Fa-qin^2*, ZHANG Wei^{3, 4}, TANG Zi-han⁵, XIONG Xin⁵, ZHOU Lei², LI Dong-kun², HUO Ting-ting², CHEN Xiao-ming⁵，LIU Jin-feng^{1, 2}, FENG Chen-xun², LI Ruo-fei⁵
		DOI: 10.3964/j.issn.1000-0593(2020)01-0022-07
		In this experiment, Bacillus Siamensis (B. siamensis) was taken as research object, and B. siamensis had a high ratio of surface area to volume, indicating that B. siamensis has a great performance on adsorbing heavy metals. However, the studies of previous experts and scholars on B. siamensis mostly focused on degradation of starch or cellulose and antifungal activity. And the mechanism of the interaction between B. siamensis and heavy metals or radionuclides was to tally not researched. Therefore, the purposes of this experiment were to use ICP-OES and ICP-MS to study the effects of pH value of solution, initial uranium concentration and biomass on removal of uranium by B. siamensis and the relationship between biological phosphorus released by cells and removal of uranium during the process, FTIR and SEM to characterize the morphology and group changes of B. siamensis before and after interaction with uranium, XPS and EDS to analyze the distribution and valence of elements on the surface of B. siamensis, and then the removal mechanism of uranium by B. siamensis was discussed. The results showed that the removal of uranium by B. siamensis under different pH varied greatly due to the difference of growth activities of B. siamensis, the existence forms of uranium and the amount of phosphorus element released by cells in the process under different pH values conditions. The removal effect was the best at pH=5.0. Increasing the biomass was beneficial to the removal of uranium by B. siamensis. The Langmuir and Freundlich adsorption isotherm models were used to fit the experimental data, and the fitting results showed that the removal behavior of uranium by B. siamensis conformed to the Langmuir isotherm adsorption model. And the maximum adsorption capacity obtained from the initial uranium concentration experiment was higher than the theoretical maximum adsorption capacity calculated from the Langmuir isotherm adsorption model, indicating that the removal of uranium by B. siamensis could be a combination of physical and chemical behavior. B. siamensis could effectively remove uranium from water. The maximum removal rate obtained in this experiment was 96.5% and the maximum adsorption capacity was 450.3 mg·g^-1, which were higher than those of most of the Bacillus strains used to adsorb uranium. SEM test of B. siamensis before and after the reaction showed that scale-like precipitate appeared on the surface of the cells after the reaction. XPS and EDS showed that the precipitate was a phosphorus-containing uranium substance. Combined with FTIR analysis, it was presumed that the removal mechanism of uranium by B. siamensis is as follows: Firstly, uranium was rapidly attracted to the surface of B. siamensis through electrostatic action, then adsorbed by phosphate groups, amino groups, hydroxyl groups and carboxyl groups on the bacteria in coordination form, and at the same time interacting with phosphate-containing substances released by the bacteria to form phosphorus-containing precipitation of uranium and then immobilized on the surface of the bacteria. During this process, a part of the hexavalent uranium was reduced to tetravalent uranium by intracellular substances released by the B. siamensis and then settled. It was speculated that the precipitation on the surface of the cell might be the mixture of the phosphate precipitation of uranium and the complexes of phosphorus-containing compounds and uranium complexes.
		2020 Vol. 40 (01): 22-28 [Abstract] ( 232 ) RICH HTML PDF (3933 KB) ( 96 )

	29	Study on the Relationship Between Apodization Function and Signal-to-Noise Ratio of Hyperspectral Spatial Interferogram
		LI Zhi-wei^{1, 2}, SHI Hai-liang^{1, 2}, LUO Hai-yan^{1, 2}, XIONG Wei^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2020)01-0029-05
		The application of interferometric spectroscopy in many fields, such as atmospheric remote sensing, astronomical exploration and geophysical prospecting, is a research hotspot at home and abroad. Spectral reconstruction, as an important part of remote sensing data processing, is closely related to the detection accuracy. Interferogram due to limited optical path difference sampling results in frequency leakage in the restored spectrum. The apodization function can play a role in smoothing the spectrum, maintaining the spectral consistency of the interferometric spectroscopy and other spectroscopy techniques, but at the same time, the resolution (Full Width at Half Maximum, FWHM) of the reconstructed spectrum will be reduced. It has been shown that the apodization function does not improve the inversion accuracy, and the apodization function is not used in the ground data processing of several typical atmospheric remote sensing loads. Spatial heterodyne spectroscopy (SHS) has attracted wide attention at home and abroad due to its many advantages. Based on this technology, Anhui Institute of Optics and Fine Mechanics of Chinese Academy of Sciences has successfully developed a prototype for atmospheric CO₂ detection. Signal-to-noise ratio (SNR) is one of the key indicators of spectrometer. This paper studies the influence of apodization function on spectral reconstruction of interferogram from the relationship between SNR, spectral resolution and detection accuracy. In view of the fact that the traditional apodization function does not achieve the optimal side-lobe suppression, this paper constructs ten apodization functions with different spectral extending based on Norton-Beer apodization function and the criterion of obtaining the maximum side-lobe suppression under the same resolution reduction. Radiative transfer Model of SCIATRAN was used to analyze the difference of atmospheric top radiance caused by different gas concentration in atmospheric CO₂ remote sensing. The spectral SNR requirement of different spectral resolution meets the requirement of 1% detection accuracy under typical conditions was calculated. Based on the parameters of the laboratory prototype, the relationship between spectral resolution and SNR under different extending was analyzed by simulating interferogram and constructed apodization function in this paper. Finally, the experimental verification was carried out by using a prototype developed by the laboratory. The interferograms were obtained by observing the stable uniform integrating sphere, and the SNR was calculated without apodization, and the SNR was calculated after different apodization extending. The simulation and experimental results show that of the SNR is gradually increased due to the reduction of noise by apodization, and the spectral resolution is gradually reduced, while the requirement of SNR for detection accuracy is gradually increased due to the decrease of resolution. The spectral SNR requirement of detection accuracy is obviously higher than that under the apodization. The SNR of simulation data and measured data is lower than that of the requirement of detection accuracy when apodization extendings are greater than 1.6 times and 1.8 times, respectively. The need for the SNR of the instrument, that is, the white noise is dominant, is not conducive to the detection accuracy. The results of this paper can be used as a reference for spectral reconstruction, and the influence of inversion accuracy will be further analyzed in the future.
		2020 Vol. 40 (01): 29-33 [Abstract] ( 253 ) RICH HTML PDF (2216 KB) ( 193 )

	34	Spectroscopic Imaging of Cutaneous Squamous Cell Carcinoma Based on Acousto-Optic Filtering
		SHENG Zhen-fei¹, ZHANG Chun-guang^1, QIU Ze-long¹, WANG Hao^{1, 2}, ZHANG Xiao-fa¹, HUANG Xi¹, TAN Zhi-wei¹, QIU Wei-jie¹, WANG Peng-chong^{1, 2*}, LIU Wen-yao³, DUAN Mao-qiang^{1, 4}, HUANG Xiao-li^{1, 5}, HUANG Zu-fang¹, LIU Yi-ping¹, XING Yu-wei¹, LIN Bin-bin¹
		DOI: 10.3964/j.issn.1000-0593(2020)01-0034-07
		Noncollinear acousto-optic tunable filter (AOTF) based on TeO₂ is a type of good light splitting device with the electric tuning. Because of its advantages of compact size, high stability, fast tuning, and being easy to carry out, it has high practical application value in hyperspectral imaging field. In this study, a hyperspectral microscopic imaging system was built by combining noncollinear AOTF with optical inverted microscope. In the range of visible light, the hyperspectral imaging of cutaneous squamous cell carcinoma was studied, and the spectra and the corresponding microscopic images at a series of optical central wavelengths were got. The performance of the hyperspectral imaging system was tested. The results shown that the bandwidth of the diffracted light in the range of 110~180 MHz was only 1.28~2.84 nm, which indicated that the AOTF in this study had a high spectral resolution with more than 102 spectral channels, and it could meet the needs of hyperspectral microscopic imaging and accurate identification of biological tissue structure. The system used higher quality TeO₂ crystal, higher quality double balsaming lens and optimized RF driver to effectively depress the sidelobe of the diffraction spectrum. The tuning relationship between the acoustic frequency and the diffracted optical wavelength, and the relationship between the spectral bandwidth and the acoustic frequency were analyzed. The experimental results were in good agreement with the related the theoretical calculation. The experimental results shown the high image quality of the system because no obvious image shift with the optical wavelength was observed. By comparing the microscopic images of the cutaneous squamous cell carcinoma with different diffraction central wavelengths, the images were also the clearest at 522.52 nm, and the details of the cutaneous squamous cell carcinoma could be distinguished obviously. The difference of the whole brightness and the transmission difference coefficient with the optical wavelength were studied, and the regulations were agreed with the intuitive observation. Through the analysis of the image edge extraction, the results shown that 497.87~551.29 nm can be used to observe and study the cutaneous squamous cell carcinoma with a bright whole field of vision, meanwhile, the results also shown that 509.69~527.59 nm was the best window for accurate identification and analysis of cutaneous squamous cell carcinoma. This study provided a new method for the simple, flexible and rapid detection and diagnosis of human cutaneous squamous cell carcinoma.
		2020 Vol. 40 (01): 34-40 [Abstract] ( 219 ) RICH HTML PDF (3891 KB) ( 76 )

	41	Online Analysis Method of Cement Raw Materials Based on Fourier Transform Infrared Spectroscopy
		HU Rong^{1, 2}, LIU Wen-qing², XU Liang^2*, JIN Ling², YANG Wei-feng², WANG Yu-hao², HU Kai², LIU Jian-guo²
		DOI: 10.3964/j.issn.1000-0593(2020)01-0041-07
		Timely analysis of the key components in cement raw materials is critical to the quality control of cement products. While on-site manual sampling and sample preparation are required for current analytical methods, they lead to a problem on timeliness. To quickly and safely determine the four key components of Fe₂O₃, SiO₂, CaO and Al₂O₃ in raw meal of cement samples, a quantitative analysis method based on fourier transform infrared (FTIR) spectroscopy was developedin the paper. The theoretical basis on FTIR technology to determine the composition in cement raw materials was discusse dat first. Cement raw materials are complex multicomponent mixtures of minerals and rocks, which are mainly made up with iron raw materials (such as limonite), siliceous raw materials (such as quartz), calcium raw materials (such as calcite) and aluminum raw materials (such as beryl) and so on. These minerals and rocks have broad characteristic bands in the visible and near-infrared spectrum with many overlapping bands, and the intensities of the characteristic bands are low. Therefore, multivariate calibration was used for quantitative analysis. The corresponding experimental system was designed and built to analyze the composition content in raw meal of cement samples subsequently. The samples were 60 ground cement raw meal samples with different contents of key ingredients, which were provided by the cement manufacturers. The compositions of samples covered four key oxides of Fe₂O₃, SiO₂, CaO and Al₂O₃. The diffuse reflectance spectra of the samples were collected by the experimental platform. X-ray fluorescence （XRF） analysis was used to determine the content of each oxide component in the sample as the reference values. The quantitative analysis models of Fe₂O₃, SiO₂, CaO and Al₂O₃ were next established by partial least squares method (PLS). The sample set was first divided into a calibration set and a prediction set in a 7∶3 ratio by Kennard-Stone algorithm. The wavenumber range of 4 000～5 000 cm^-1 was selected in the PLS model with 520 spectral elements in total. A regression model was established between the spectra of 42 samples and their contents of Fe₂O₃, SiO₂, CaO and Al₂O₃ in the calibration set. According to the condition of Q²_h≥0.009 75, seven factors were selected to establish the final quantitative analysis model. In the FTIR quantitative analysis model of the four oxides of Fe₂O₃, SiO₂, CaO and Al₂O₃, the correlation coefficients between the calibrated four oxide contents and the content measured by XRF analysis respectively were 98.49%, 98.03%, 98.18% and 99.24%, and the root mean square error respectively were 0.04, 0.22, 0.26, and 0.08. The model had a high accuracy of calibration. The quantitative analysis models of the four components were used to predict the four component content of samples in the prediction set, and the predicted values were compared with the reference values measured by XRF analysis lastly. The quantitative analysis models of the four components for Fe₂O₃, SiO₂, CaO and Al₂O₃ had a high prediction accuracy with the prediction correlation coefficients of 91.35%, 91.50%, 91.57%, 94.67% and the predicted root mean square error of 0.08, 0.45, 0.54, 0.26, respectively. The foundation of rapid quantitative analysis of components in cement raw materials based on the fourier transform infrared spectroscopy during the cement production control process was established.
		2020 Vol. 40 (01): 41-47 [Abstract] ( 285 ) RICH HTML PDF (3459 KB) ( 111 )

	48	Three-Dimensional Arc Spectrum and Anti-Interference Decoupling in Micro Plasma Arc Welding
		ZHANG Hu, HE Jian-ping^*, LINYANG Sheng-lan
		DOI: 10.3964/j.issn.1000-0593(2020)01-0048-06
		In view of the limitation in temperature field measurement of welding arc by two-dimensional arc spectral method, the detection of light radiation intensity at arbitrary points within arc based on three-dimensionally spectral acquisition system with confocal optic path as the key is studied. With arc light radiation intensity at each point on the central line (this line was on an arc transverse) perpendicular to detecting direction, Abel Inverse Transform is used for a reference for anti-interference de-coupling, in order relative emission coefficients of light radiation intensity at arbitrary points within arc to be rebuilt. Interference problems resulted from focally spectral measurement at an arbitrary point within arc using the studied three-dimensionally spectral acquisition systemwere solved. According to rebuilt relative emission coefficient about Ar Ⅱ characteristic spectrum (wave length arc 771.308 and 856.221 nm) of arc in micro-plasma arc welding with 2 mm torch height and 2 A welding current, three-dimensional temperature distribution of arc was obtained by relatively spectral intensity. Furthermore, Arc temperature distribution and arc geometry achieved in this way were discussed, and temperature field was compared with the numerical calculation results under same welding conditions. It is shown in the study that the studied three-dimensionally spectral acquisition system can be effectively used to acquire light radiation at a point in arc three-dimensional space. Radially spectral maps were non-axisymmetric with elongation due to a limitation of confocal optic path. However, the radially spectral maps with anti-interference decoupling were axisymmetric. Although the distribution of arc light relative emission coefficients with interference resistance de-coupling appears off-axis phenomenon, light radiation at the off-axis arc center reached maximum. The maximum light radiation at the location from nozzle to workpiece reduced firstly and then increased. This distribution is in agreement with “two-peak” distribution of arc light radiation. Moreover, when the location of arc was from nozzle to workpiece, arc radius decreased firstly, then kept certain value followed by increasing, leading to a quasi-column profile. This arc profile agreed with short arc geometry (height of arc torch was 2 mm) relative to welding current 2 A. In addition, the maximum value indirectly detected for welding current 2 A using three-dimensionally spectral acquisition and anti-interference de-coupling is in the temperature range of arc in micro-plasma arc welding. Furthermore, radial temperature distribution detected in this study is in agreement with the results by numerical simulation for temperature field. The maximum error was only about 0.03.
		2020 Vol. 40 (01): 48-53 [Abstract] ( 187 ) RICH HTML PDF (2757 KB) ( 67 )

	54	Research on Raman Spectral Signal Characteristics Based on Ensemble Empirical Mode Decomposition
		LI Ming^{1, 2}, ZHAO Ying^{1, 2}, CUI Fei-peng², LIU Jia²
		DOI: 10.3964/j.issn.1000-0593(2020)01-0054-05
		Raman spectrum signal is a kind of scattering signal based on molecular vibration. The laser source wavelength of Raman spectrometer is generally nanometer. As it is a typical non-stationary signal and considering the scattering frequency shift, the effective information of Raman spectrum is mainly concentrated in the higher frequency band. Because Raman scattering is very weak, and the signal is easily disturbed by high frequency noise and fluorescence background. In order to obtain more comprehensive Raman information, the signal needs to be processed. The results of Raman signal analysis by wavelet transform depend on the choice of wavelet bases, and the results of different wavelet bases are different; Empirical Mode Decomposition (EMD) method can analyze signals adaptively without setting parameters, but it has the problem of mode mixing. The Ensemble Empirical Mode Decomposition (EEMD) effectively solves the problem of mode mixing in EMD method, and can more clearly divide the components of different frequencies in signals, so it is more suitable for the characteristic analysis and processing of Raman signal which has rich frequency components. In this paper, Raman spectrum of soybean oil, peanut oil, corn oil and sunflower seed oil samples are collected by Raman spectrometer. Raman spectrum of edible oil are adaptively decomposed and processed by EEMD, and a total of 10 orders Intrinsic Mode Function (IMF) are obtained. According to the energy distribution and amplitude characteristics of the signal, IMF1 and IMF2 are characterized as the noise components of the signal, IMF3—IMF7 as the Raman characteristic signal components, the last order IMF10 as the fluorescence background component, and IMF8 and IMF9 as the frequency components of other physical meanings. After filtering out the high frequency noise components of IMF1 and IMF2, it obtains the Raman signal after de-noising. In addition, the signal-to-noise ratio of Raman signal is increased by 2～5 times by enhancing and reconstructing the characteristics of the effective signal component. Among them, the dynamic peak at 1 745 cm^-1 caused by the ester bond carbonyl stretching vibration is significantly enhanced, which is difficult to detect. Finally, the baseline of original signal and the characteristicenhancing signal are deducted by PLS method based on continuous wavelet transform. After principal component analysis, the different data samples without enhancement overlap with each other, and there is no obvious class spacing, so it is difficult to distinguish the type of samples completely. The data samples based on feature enhancement are gathered separately, and each kind of data samples is clustered obviously. Types can be identified from each other, which provides a new way for Raman spectroscopic signal processing.
		2020 Vol. 40 (01): 54-58 [Abstract] ( 198 ) RICH HTML PDF (4259 KB) ( 77 )

	59	Structural and Luminescence Properties of Eu²⁺ Doped CaAlSiN₃ Silicon Nitride Red Emitting Phosphor
		ZHANG Hong¹, WANG Le^1*, LUO Dong¹, ZHENG Zi-shan¹, LI Yang-hui^{1, 2}, PAN Gui-ming¹
		DOI: 10.3964/j.issn.1000-0593(2020)01-0059-06
		White light-emitting diodes (wLEDs) are one of most efficient and environmentally friendly lighting technologies, which are known as indispensable solid-state light sources. At present, the commercial way to produce wLEDs is combining a blue chip with yellow phosphor material as YAG∶Ce³⁺. The luminous efficacy of the wLEDs could reach the ideal value, but the color rendering is poor, which could be ascribed to the lack of red component in the emission spectrum. Thus, the development of wLEDs is limited in the application of high-quality general lighting, such as showcase lighting, medical illumination and projection display. A promising deep red phosphor, Eu²⁺ doped CaAlSiN₃ (CASN) was prepared by high temperature solid reaction in a gas pressure sintering furnace. In this work, luminescent properties, crystal structure of the CASN were investigated via X-ray diffraction (XRD) and photoluminescence spectra (PL), by applying the structure and bandgap engineering strategies, we have revealed the essential energy transfer mechanism of its luminescence phenomenon. The XRD results indicate that the sample is well-crystallized in the combustion procedure, and its crystal structure has not changed when doped with low concentrations of rare-earth ions. Ca_0.992AlSiN₃∶0.008Eu²⁺ phosphors could be effectively excited by a broad emission spectrum extending from 200 to 600 nm, and this broad excitation band could be deconvoluted into five sub-bands by Gaussian fitting. A substantial red spectra is centered at 650 nm under the 450 nm excitation, with a wide broad full width at half maximum (FWHM) of the emission spectrum(91.4 nm), due to the electron transfer of Eu²⁺ from 5d to 4f. The band structure calculation shows that Ca_{0.937 5}AlSiN₃∶0.062 5Eu²⁺ has an indirect band gap with an energy gap of about 3.14 eV, with the atomic projected Ca-3p, Eu-3d, N-2p, Al-3p, Si-3p states. An optimal spectral model was designed to guide packaging of the phosphor-converted wLEDs, and the influence of the various combination of Ca_0.992AlSiN₃∶0.008Eu²⁺ phosphors was studied with the wLED packaging. A super wLED was attained by combining red Ca_0.992AlSiN₃∶0.008Eu²⁺ phosphor and green β-sialon phosphor with a blue LED chip, showing a high color rendering index of 92.1, a high luminous efficacy of 101 lm·W^-1, and a warm color temperature of 3 464 K. The phosphor of Ca_0.992AlSiN₃∶0.008Eu²⁺ is effective to improve color rendering indexes for wLEDs with the contribution of its red spectral part with simultaneous spectral broadening, meanwhile it is of great value in luminous efficacy, color temperature and stability, which means that it is a promising candidate for the red phosphor material for wLEDs.
		2020 Vol. 40 (01): 59-64 [Abstract] ( 228 ) RICH HTML PDF (3164 KB) ( 223 )

	65	Preparation and Luminescent Properties of Green Phosphors LaGaO₃∶Tb³⁺,Sn⁴⁺
		FAN Bin¹, LIU Jun², QI Shi-mei³, ZHAO Wen-yu^1*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0065-06
		Rare earth doped LaGaO₃ phosphors could be suitable for use in field emission display and LED applications, owing to the excellent luminescent properties, high color rendition and stability, et al. The luminescent intensity and color purity of LaGaO₃∶Tb³⁺ are higher than those of commercial Y₂SiO₅∶Ce³⁺ phosphor. In order to expand application in white LED, the luminescent intensity of LaGaO₃∶Tb³⁺ is enhanced by co-doping Sn⁴⁺ ions in this paper. A series of green phosphor LaGaO₃∶Tb³⁺ and LaGaO₃∶Tb³⁺,Sn⁴⁺ were synthesized by high-temperature solid-state method. The crystal structures and luminescent properties were characterized by XRD and photoluminescence spectrum, respectively. The results show that all Tb³⁺ and Sn⁴⁺ ions preferably substitute for La³⁺ and Ga³⁺ ions, respectively, in the crystal lattice of LaGaO₃ without impurity phases, indicating obtained samples are single phase phosphors. All excitation spectra consist of some broad peaks (231, 257, and 274 nm) and sharp peaks (from 300 to 500 nm). The bands at 231 and 274 nm are assigned to the spin allowed transition (LS, ⁷F₆→⁷D_J, ΔS=0) and the spin forbidden transition (⁷F₆→⁹D_J, ΔS=1) for 4f-5d of Tb³⁺, respectively. The band at 257 nm is assigned to the transition of a self-activated optical center related to octahedral coordinated GaO₆ groups. Some excitation peaks in the range of 300～500 nm are attributed to f-f characteristic transitions of Tb³⁺, such as ⁷F₆→⁵H₆, ⁵H₇, ⁵L₆, ⁵L₉, ⁵L₁₀, ⁵G₉ and ⁵D₄. Compared with LaGaO₃∶Tb³⁺, co-doped Sn⁴⁺ion can enhance the 4f-4f characteristic excitation intensity of Tb³⁺. The main excitation peak changes from f-d transition of Tb³⁺ to its f-f transition. Under excitation at 308 nm, the emission spectra of LaGaO₃∶Tb³⁺ and LaGaO₃∶Tb³⁺,Sn⁴ all consist of Tb³⁺ ions characteristic transitions, such as ⁵D₄→⁷F₆ (487, 493 nm), ⁵D₄→⁷F₅ (545 nm), ⁵D₄→⁷F₄ (584, 589 nm), and ⁵D₄→⁷F₃ (622 nm). The strongest emission peak is at 545 nm. The CIE color coordinates of LaGaO₃∶Tb³⁺ and LaGaO₃∶Tb³⁺,Sn⁴⁺ are (0.287 4, 0.545 9) and (0.279 7, 0.576 1) in green region, respectively. The fluorescence lifetime of LaGaO₃∶Tb³⁺ and LaGaO₃∶Tb³⁺,Sn⁴⁺are 1.63 and 1.38 ms, respectively；the color purity values of LaGaO₃∶Tb³⁺ and LaGaO₃∶Tb³⁺,Sn⁴⁺ are 54.81% and 62.67%, respectively. Co-doped Sn⁴⁺ ion has no impact on the position of emission peaks, but the emission intensity of Tb³⁺ increases to nearly double. Mechanism of concentration quenching can be changed from dipole-quadrupole (d-q) to quadrupole-quadrupole (q-q) interactions. The optimum doping concentration of Tb³⁺ is 0.05 and 0.07 in the LaGaO₃∶Tb³⁺and LaGaO₃∶Tb³⁺,Sn⁴⁺, respectively. The optimum Sn⁴⁺ doping concentration is 0.03. The optimum doping concentration of Tb³⁺ increases by co-doped Sn⁴⁺, which is beneficial to improving luminous intensity. The luminous efficacy values of the radiation (LER) of LaGaO₃∶0.05Tb³⁺ and LaGaO₃∶0.07Tb³⁺, 0.03Sn⁴⁺ are 464 and 485 lm·W^-1, respectively. The internal quantum efficiency values of LaGaO₃∶0.05Tb³⁺ and LaGaO₃∶0.07Tb³⁺, 0∶03Sn⁴⁺ are 21.8% and 39.2%, respectively. The emission intensity decreases gradually with the increasing temperature due to the thermal quenching. The emission intensity of the LaGaO₃∶Tb³⁺,Sn⁴⁺ sample remains to be above 70% at 150 ℃. According to the Arrhenius equation, the thermal activation energy ΔE for quenching is calculated to be 0.169 0 eV, which indicates that this phosphor has excellent thermal stability. All the results show that the LaGaO₃∶Tb³⁺,Sn⁴⁺ phosphor is a promising green phosphor for the n-UV excited w-LEDs.
		2020 Vol. 40 (01): 65-70 [Abstract] ( 173 ) RICH HTML PDF (2486 KB) ( 59 )

	71	Research on Spatial Offset Raman Spectroscopy and Data Processing Method
		LI Yang-yu¹, MA Jian-guang^2*, LI Da-cheng¹, CUI Fang-xiao¹, WANG An-jing¹, WU Jun¹
		DOI: 10.3964/j.issn.1000-0593(2020)01-0071-04
		Traditional Raman spectroscopy is highly susceptible to fluorescence and Raman scattering of the container wall when detecting unknown samples in containers, which often limits its commercial applications to transparent plastic or glass packaging. Since the photon migration direction inside the medium is random, the Raman scattered photons generated at the inner deep layer are more likely to migrate laterally during the diffusion process. Therefore, the Raman spectrum at different distances from the laser incident point contains different Raman spectral information of depth layers. The spatially offset Raman spectroscopy (SORS) can suppress the fluorescence and Raman scattering interference of the container wall by deviating the Raman light collection point from the laser incident point, there by realizing effective detection of the sample in the colored and opaque package. By designing a SORS experimental device, the offset distance of -1.0~10.0 mm can be adjusted. A cyan, opaque 1 mm thick PMMA plate was used to simulate the container wall, and calcium carbonate (CaCO₃) powder was used as the internal sample to be tested. The samples were measured by the conventional method (zero offset) and the spatially offset method. The acquired raw spectra were first averaged and fitted by a 7th order polynomial to remove the baseline. Then the average of the three largest spectral peaks was used as the spectral intensity, and the variation law of the SORS signal with the offset distance was analyzed. It was found that: as the spatial offset distance increases, the Raman scattering intensity of the container wall decreases rapidly, while the Raman scattering intensity of the internal sample first rises and then decreases slowly; for samples of uniform thickness and isotropic, the trend of change is symmetrical about the zero offset, and the oblique incidence of the laser beam causes a slight asymmetry; at a certain offset distance, the ratio of the spectral intensity of the sample to the container wall reaches a maximum value, and there is an optimal detection offset distance (for this sample, the optimal offset distance is 1.2 mm). In the case where the material of the container and the sample is unknown, the clean Raman spectrum of each layer can still be obtained by the method of proportional subtraction. By calculating the spectrum at the zero offset and the optimal offset, the clean Raman spectra of the container wall and the internal sample are obtained respectively, which can be used in later spectral analysis and identification processes. This work demonstrates the potential of SORS for the detection of samples in opaque, colored containers, and provides a basis for further research on SORS and data processing methods.
		2020 Vol. 40 (01): 71-74 [Abstract] ( 319 ) RICH HTML PDF (2148 KB) ( 92 )

	80	Study on Recognition Mechanism of Al³⁺ by Cyanuric Chloride Molecules of Dual-Probe Group (DPG)
		NING Xiao-yu¹, WEI Gang², GUANG Shan-yi^1*, ZHAO Gang², XU Hong-yao^2,3
		DOI: 10.3964/j.issn.1000-0593(2020)01-0080-05
		The metabolism of aluminum in the human body is extremely slow, the ingested aluminum will accumulate in the body gradually, and the Al³⁺ of abnormal concentration will damage the central nervous system, leading to serious neurological diseases, so the detection of Al³⁺ efficiently and sensitively is very important. Fluorescent probes are widely used for analysis and detection of metal ion because of their advantages of convenient carrying, quick and easy detection, low price, good selectivity, etc., and a large number of literature for the detection of Al³⁺ are based on being complexed with Single-Probe Group (SPG) molecules at 1∶1, 2∶1, 3∶1, etc. In this paper, an active cyanuric chloride as a bridging group, a rhodamine B amide and a Schiff base derivative, p-amino benzoyl salicylic acid, as a cyanuric chloride molecule (RBCS) of a dual-probe group (DPG) was studied. It is prepared in one step by an easily controlled thermodynamic method. The total concentration of immobilized RBCS+Al³⁺ was 20 μmol·L^-1, and the experimental results of Job-plot show that the fluorescence intensity at 578 nm reaches the highest value when the ratio of ions to total concentration is 0.68, by adjusting the concentration ration of the two, the result indicates that RBCS and Al³⁺ are mainly coordinated by 1∶2. The MALDI-TOF-MASS study found that the new peak of RBCS-Al³⁺ at 900.07 compared to the spectrum without Al³⁺, further verified that the DPG cyanuric chloride (RBCS) and Al³⁺ are complexed at 1∶2. The recognition mechanism of RBCS to Al³⁺ was studied in detail by the ¹H NMR titration experiment with 0, 0.5, 1, 2, 3 equivalents of Al³⁺ added to the probe RBCS (10 mg) to compare the change of the characteristic H position. The results indicate that when Al³⁺ is present, the complexation of Al³⁺ with the carbonyl O, amino N and cyanuric chloride N on the rhodamine part of RBCS leads to the ring opening of rhodamine, at the same time, the imino group N of Schiff base and two O of carboxylic acid radical and phenol radical also bind with Al³⁺ respectively which solidifies the C═N bond and increases the overall conjugation resulting in fluorescence. In conclusion, the cyanuric chloride molecule (RBCS) can be used as a Double-probe group molecule for the recognition of Al³⁺ ions. RBCS-Al³⁺ showed orange-red fluorescence under 365 nm ultraviolet lamp irradiation, and the fluorescence increased gradually with the increase of Al³⁺ concentration. After optimizing the testing conditions of RBCS optical properties, the optical properties of RBCS were studied in ethanol/water (99/1, V/V) solution. The RBCS (10 μmol·L^-1) in the ethanol/water (99/1, V/V) solution was carried out by fluorescence titration experiments at an excitation wavelength of 557 nm and an emission wavelength of 578 nm finally. The fluorescence intensity changes of RBCS (10 μmol·L^-1) for different concentrations of Al³⁺ (0.01～8 eq) were tested, and the data was linearly regressed. The equation was y=32.336 0+65.364 1x, R²=0.993 3, and the linear range was 1～10 μmol·L^-1. The detection limit of RBCS for Al3+ calculated by 3σ/k is 15.0 nmol·L^-1. The research in this study can provide a reference for the design of double probe group (DPG) molecules for the detection of metal ions.
		2020 Vol. 40 (01): 80-84 [Abstract] ( 189 ) RICH HTML PDF (2477 KB) ( 65 )

	85	The Bioavailability Characteristics of CDOM in Lake Hongze and Lake Luoma under Different Hydrological Scenarios
		ZHANG Liu-qing^1,2, PENG Kai^1,3, YANG Yan², SHI Yu¹, LI Yuan-peng¹, ZHOU Lei^1,3, ZHOU Yong-qiang^1,3*, ZHANG Yun-lin^1,3
		DOI: 10.3964/j.issn.1000-0593(2020)01-0085-06
		We investigated the bioavailability characteristics of chromophoric dissolved organic matter (CDOM) in different hydrological scenarios of Lake Hongze and Lake Luoma using bio-incubation experiments coupled with excitation-emission matrices and parallel factor analysis (EEMs-PARAFAC). The results showed that (1) Three fluorescent components were obtained using PARAFAC, including a humic-like C1, a tryptophan-like C2 and a tyrosine-like C3. (2) After 28 days of bio-incubation, the bioavailability of dissolved organic carbon (BDOC) in Lake Hongze and Lake Luoma in dry season (17%±4% and 15%±4%) was higher than that in flood season (5%±5% and 10%±7%), and the high %BDOC values of the two lakes were mainly distributed in the inflowing river mouths. (3) The specific absorbance at 254 nm SUVA₂₅₄ and humic-like components in the two lakes during dry season was significantly higher than that pre-bio-incubation, and ΔSUVA₂₅₄ and ΔC1 were negative. The tyrosine-like component was significantly lower than that pre-bio-incubation and ΔC3 was positive, indicating that the microorganisms preferentially utilized the less stable tyrosine-like component in the dry season, and produced more stable humic-like C1 and also increased the humification of the samples collected from the two lakes. (4) There were significant negative correlations between BDOC, %BDOC and ΔSUVA₂₅₄, ΔC3, %ΔC3, respectively. These results indicated that CDOM optical composition directly affects its bioavailability in the two lakes.
		2020 Vol. 40 (01): 85-90 [Abstract] ( 239 ) RICH HTML PDF (4277 KB) ( 132 )

	91	The Quantification of the Contrast for Latent Fingerprint Development Based on Fluorescent Spectrometry
		SHEN Dun-pu¹, LI Ming^{1, 2}, YUAN Chuan-jun^{1, 2}, YU Hai-feng¹, WANG Meng^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2020)01-0091-07
		Latent fingerprint development is considered as one of the most important technologies in forensic sciences. After fingerprint development, researchers usually evaluate the effect of fingerprint development according to whether the outline is complete, whether the ridges are clear and coherent, whether the detail features are obvious, and whether the background interference is serious, etc. . However, all above descriptions for evaluation are subjective, which are lack of objectivity, accuracy and scientificity. In order to quantitatively evaluate the effect of fingerprint development objectively, comprehensively and accurately, the contrast of fingerprint development was systematically studied by spectral analysis, and then the accurate quantitative evaluation was achieved. Firstly, we proposed the concept of contrast as the contrast between the fingerprint (signal) and the background (noise), for fingerprint development based on fluorescent methods. The contrast were depended on differences of fluorescent intensity (Intensity Index, I) and fluorescent color (Chroma Index, C) between the friction ridges and the background. Secondly, the substrates, fingerprint developing powders as well as fingerprints developed after fluorescent powder were characterized by spectral instrument and chromaticity software. The calculation method of the fingerprint development contrast, which was defined as the common logarithmic value of I and multiply by C, was finally established. Then, combined with the vision effects and the spectral analysis results, the accuracy of calculated fingerprint development contrast was verified. The results showed that our method had been successfully used in evaluating the contrast of fingerprint development based on fluorescent spectral analysis methods. Finally, combined with spectral analysis technology, the influence factors of the fingerprint development contrast, including the differences of fluorescent intensity, fluorescent color and luminescent mechanisms between the fingerprint development powders, were analyzed in detail. The experimental results showed that the quantitative method of fingerprint development contrast based on spectral analysis could quantitatively evaluate the effect of fingerprint development objectively, scientifically and comprehensively. Moreover, according to Intensity Index and Chroma Index, we summarized the approaches to promote the contrast of fingerprint development, providing beneficial references for the selection of fingerprint development methods in practice applications.
		2020 Vol. 40 (01): 91-97 [Abstract] ( 245 ) RICH HTML PDF (4179 KB) ( 81 )

	98	Photoluminscence Spectra and Ternary CIE Colour Image of (Mg_1-x-yBa_xSr_y)_1.95SiO₄∶0.05Eu Phosphor Series
		SUN Chuan-yao¹, LUO Lan^{1, 2*}, WANG Yu¹, GUO Rui¹, ZHANG Yuan-bo¹
		DOI: 10.3964/j.issn.1000-0593(2020)01-0098-09
		A novel (Mg_1-x-yBa_xSr_y)_1.95SiO₄∶0.05Eu phosphor was prepared by high-temperature solid state reaction method, including 3 binary alkaline earth ion ratio series and 3 representative ternary alkaline earth ion ratio series (Ba is constant and the Mg/Sr ratio is continuously changed, the Mg/Sr ratio is constant and the Ba content is continuously changed.). As for the 6 series, the spectral properties (excitation and emission spectra), ultraviolet (254 and 365 nm) luminescence recordings and CIE values corresponding to the color images were studied in detail. Like the way to establish a ternary phase diagram, a ternary colour image is derived from these binary and representative ternary data. It can be used to study and screen a new phosphor series in a more efficient way. The prepared phosphor series include: Mg₂SiO₄-Sr₂SiO₄, Ba₂SiO₄-Sr₂SiO₄, Mg₂SiO₄-Ba₂SiO₄, Ba atomic ratio of 0.2 (Mg/Sr atomic ratio continuously changed), Ba atomic ratio of 0.6 (Mg/Sr atomic ratio continuously changes), the atomic ratio of Mg/Sr is 1/4 (the series of continuous changes in Ba atomic content). Its corresponding spectral performance, luminescence recording, and CIE chromatic analysis at 254 nm excitation indicate that: Eu ions exist trivalent and divalent in (Mg_1-x-yBa_xSr_y)₂SiO₄; for the binary series (as the matrix as (Mg_1-xBa_x)₂SiO₄ or (Ba_1-ySr_y)₂SiO₄), with the increase of Ba atomic ratio, the phosphor gradually turns red (corresponding to Eu³⁺ ions ⁵D₀→⁷F₁ and ⁵D₀→⁷F₂ electron transition narrow band emission) to green (corresponding to Eu²⁺ ion 4f^n-15d→4fⁿ electronic transition emission broadband emission), and the former series change faster; the binary series as (Mg_1-ySr_y)₂SiO₄ were red phosphors, and the red luminescence increases with the increase of Sr content. For the ternary series (Ba_x(Mg_0.2Sr_0.8)_1-x)₂SiO₄ (Mg/Sr=1/4), as Ba ion amount increases, the phosphor gradually changes from red to green, and the rate of change is determined by the ratio of Mg/Sr equal to 0 (ie Ba₂SiO₄-Sr₂SiO₄ series) and the ratio of Mg/Sr is equal to ∝ (ie Ba₂SiO₄-Mg₂SiO₄ series); the ternary series (Ba_0.2Sr_yMg_0.8-y)_1.95SiO₄ are also red phosphors, and (Ba_0.6Sr_yMg_0.4-y)₂SiO₄ gradually turn blue and green with the atomic ratio of Mg/Sr increasing. The evolution of fluorescence emission at 365 nm excitation is generally consistent with that at 254 nm excitation, but the emission of green light in the same sample at 365 nm is stronger than that at 254 nm and the emission in the red band is weaker than that at 254 nm. Therefore, the contents of Ba in (Mg_1-xBa_x)₂SiO₄, (Ba_1-ySr_y)₂SiO₄, (Ba_x(Mg_0.2Sr_0.8)_1-x)₂ from red to green are 40at%, 60at%, 60at%, respectively (60at%, 80at%, 70at% at 254nm excitation), and Mg/Sr ratio from red to green in (Ba_0.6Sr_yMg_0.4-y)₂SiO₄ is 1/4 (2/3 at 254 nm excitation). Based on this, ternary CIE colour image of Eu-doped Ba₂SiO₄-Mg₂SiO₄-Sr₂SiO₄ is established. It can be seen from the spectral image that the (Mg_1-x-yBa_xSr_y)_1.95SiO₄∶0.05Eu phosphor emits light under UV excitation, that is, the matrix component emits green near the Ba₂SiO₄ corner and emits red near the Mg₂SiO₄ or Sr₂SiO₄ corner. The larger the Mg/Sr ratio is, the faster the phosphor turns from red to green as the Ba atom increases. The green light emission of the same sample is stronger than the 254 nm excitation at 365 nm excitation and the red emission is weaker than the 254nm excitation. (Mg_1-x-yBa_xSr_y)_1.95SiO₄∶0.05Eu phosphor is Ba>80at%, and Mg>90at% (or Sr>80at%) phosphor can be used as high-efficiency green and red fluorescence, respectively; when the composition is (Mg_0.8Sr_0.2)_1.95SiO₄∶0.05Eu, (Ba_0.8Mg_0.16Sr_0.04)_1.95SiO₄∶0.05Eu is the best red and green phosphor for UV excitation.
		2020 Vol. 40 (01): 98-106 [Abstract] ( 184 ) RICH HTML PDF (7082 KB) ( 62 )

	107	Experimental Investigation of Infrared Spectral Emissivity of Pure Tungsten
		YU Kun¹, SHI Rui-tao¹, ZHANG Hui-yan¹, WANG Wen-bao², LIU Yu-fang¹
		DOI: 10.3964/j.issn.1000-0593(2020)01-0107-06
		Spectral emissivity can be considered as a surface thermal physical property of materials, which is widely applied in radiation thermometry, heat transfer calculation and so on. Tungsten is a significant metal, but its spectral emissivity is rarely reported. Based on energy contrast method, a device measuring spectral emissivity is built, which is composed of four parts: standard reference blackbody, a Fourier transform infrared (FTIR) spectrometer, sample heating chamber, and optical system. This device can measure the spectral emissivity of samples in the wavelength range of 3～20 μm, and the overall uncertainty of this apparatus is better than 5%. The normal spectral emissivity of pure tungsten is measured by this device at four temperatures (573, 673, 773, 873 K), and the effects of oxidation, temperature, wavelength and heating time on the normal spectral emissivity of pure tungsten are analyzed in detail. The results showed that the variations of the spectral emissivity of unoxidized pure tungsten at four different temperatures were basically similar, and the difference of these values was relatively small, however, the spectral emissivity rapidly increased when the sample was oxidized and the strong oscillations were found at some wavelengths. The effect of temperature on the spectral emissivity of pure tungsten was slight when the sample wasn’t oxidized, while the spectral emissivity rapidly increased with increasing temperature when the samples was oxidized. The spectral emissivity of pure tungsten decreased with increasing wavelength. When the surface of the sample was oxidized, four peaks appeared at 4, 9, 12.5 and 16.5 μm due to the interference effect between the oxide layer and the metal substrate. At 573 and 673 K, the spectral emissivity of pure tungsten does not change significantly with increasing heating time. However, as the temperature increased, the spectral emissivity increased with increasing heating time at 773 and 873 K. At 773 K, the rate of the spectral emissivity increasing with increasing heating is relatively fast, and the surface of pure tungsten begins to be oxidized with large oxidation rate. At 873 K, the increase of spectral emissivity with increasing heating time is relatively flat, and remains stable. In summary, the variation of spectral emissivity of pure tungsten is relatively stable at lower temperature and unoxidizedstate. As the temperature increases, the spectral emissivity increases rapidly and strong oscillation occurs at multiple wavelengths when the surface is oxidized. It can be seen that the spectral emissivity of pure tungsten is greatly affected by the heating time, temperature and wavelength. In practice, especially in radiation thermometry, if the spectral emissivity of pure tungsten is regarded as a constant, the measurement error will be large. This study will further enrich the data of spectral emissivity of pure tungsten, and provide reference for scientific research and applications.
		2020 Vol. 40 (01): 107-112 [Abstract] ( 502 ) RICH HTML PDF (4755 KB) ( 179 )

	113	Rapid Determination of Phenol in Water by Three-Dimensional Fluorescence Combined with Second-Order Calibration
		WANG Xuan-rui¹, ZHANG Li-juan^1,2, WANG Yu-tian¹, SHANG Feng-kai^1*, SUN Yang-yang¹, ZHANG Hui¹, ZHANG Yan¹, WANG Shu-tao¹
		DOI: 10.3964/j.issn.1000-0593(2020)01-0113-06
		Phenolic compounds are widely used in metallurgy, oil refining, machinery manufacturing, medicine, pesticide and paint industries, but they are toxic, if not treated properly they will pollute environment. Water is the source of life, and the detection of phenols in the water environment is particularly important. Three- dimensional fluorescence spectrometry has the characteristics of highly sensitivity, fast detection speed, convenient pretreatment and tracing detection. The second-order correction method can identify the interesting components in compounds. In this paper, three-dimensional fluorescence spectroscopy will be combined with second-order correction method to test phenols in the water. M-cresol and resorcinol were selected as the tested substances in this experiment, and they were divided into two kinds of samples: adding interference and without interference. The data of three-dimensional fluorescence spectra of eight corrected samples and eight predicted samples were measured by FLS920 steady-state fluorescence spectrometer, and the data above were preprocessed: scattering interference contained in the original spectrum was removed; corrected by the excitation/emission correction. Then, the spectral data were compressed by the wavelet packet generated by db3 wavelet function, and the redundant information in the spectral data was removed through this approach. The compression score achieved 91.67%, and the recovery score achieved 96.62%. Then two second-order calibration methods: parallel factor analysis (PARAFAC) and self-weighted alternating trilinear decomposition (SWATLD) were used to analyse the preprocessed data qualitatively and quantitatively separately. According to the results of consistency analysis combined with residual discriminant analysis, the component number of samples without interference was chose as 2, and the samples with interference was chosen as 3. Qualitative analysis showed that regardless of the existing or inexisting interference, these two second-order calibration methods all could identify m-cresol and resorcinol in samples accurately. The fluorescence peak position of m-cresol and resorcinol were located at λ_em=298 nm/λ_ex=274 nm and λ_em=304 nm/λ_ex=275 nm separately. The quantitative analysis results show that the average recovery rate of m-cresol and resorcinol reached 93.37%±4.92% and 95.19%±5.25% respectively by PARAFAC without adding interference and under interference, meanwhile the average recovery rate of m-cresol and resorcinol were 92.09%±2.64% and 97.08%±5.28%. Under the same conditions, when we chose SWATLD , the average recovery rate of m-cresol and resorcinol reached 93.11%±4.73% and 96.80%±5.04% respectively, meanwhile the average recovery rate of m-cresol and resorcinol were 97.30%±4.52% and 96.92%±5.61% respectively. The root mean square error of prediction (RMSEP) of the two methods are all less than 0.03 mg·L^-1. The experimental results show that two second-order calibration algorithms: PARAFAC and SWATLD can all quickly and accurately test phenols in water when the fluorescence peaks are contiguous, and the spectra overlap seriously meanwhile there are interference in the compounds.
		2020 Vol. 40 (01): 113-118 [Abstract] ( 216 ) RICH HTML PDF (4070 KB) ( 143 )

	119	Determination of Two Phenols in Water by Three Dimensional Fluorescence Spectroscopy Combined with Second-Order Calibration Method
		SUN Yang-yang¹, ZHANG Li-juan², WANG Yu-tian^1*, SHANG Feng-kai¹, WANG Xuan-rui¹, ZHANG Hui¹
		DOI: 10.3964/j.issn.1000-0593(2020)01-0119-06
		Water is the source of life, which is indispensable to people’s diurnal production and life. In recent years, water contamination has become increasingly severe, which has endangered humanity health. Phenolic compounds are organic pollutants that are widespread and difficult to degrade, which refers to hydroxyl-containing derivatives produced by hydroxyl substitution of hydrogen atoms in benzene rings of aromatic hydrocarbons. They are highly toxic to animal, plant and human life activities. Resorcinol (RES) and hydroquinone (HYD) were selected as research object of experiment, and phenol (PHE) was added to three groups of predicted samplesas interference. The samples and blank solvent were scanned by the laboratory FS920 steady-state fluorescence spectrometer to obtain fluorescence spectrum data. The influence of Raman scattering would be eliminated through the deduction of blank solvents method. The obtained data contain the important information in the original spectrum with the greatest extent is preserved while eliminating interference. The spectrum becomes smoother and the fluorescence intensity raise significantly, so the spectral information is more accurate after correction. Second-order correction methods: parallel factor analysis (PARAFAC) and alternating penalty trilinear decomposition (APTLD) together with three-dimensional fluorescence spectroscopy (EEM) were used to measure RES and HYD in form of qualitative and quantitative analysis fast, directly and accurately in two cases: under interference and without interfering stuff meanwhile excitation-emission spectra overlap severely. Because PARAFAC algorithm is sensitive to the component number (i. e. chemical rank) of the mixture system, when the component number is too large the algotithem will arise: falling into the “swamp”, iterations number increases more time consuming. In this paper, Core Consistency Diagnosis (CORCONDIA) is used to estimate component number precisely, which ensures algorithm calculating faster and more accurate. As qualitative analysis results showed that PARAFAC can accurately distinguish RES and HYD without interference. The peak position of RES and HYD are very close, thus it is difficult to distinguish them via traditional methods and “second-order advantage” of combining three-dimensional fluorescence spectroscopy with second-order calibration is demonstrated. The results of quantitative analysis give out that the accuracy of this method is slightly reduced and RMSEP value increases slightly in the presence of interference, but these two methods can still complete the determination accurately. The recovery rate of PARAFAC is 93.4%±0.5%~97.1%±1.0% and the predicted root mean square error is less than 0.190 mg·L^-1. Manwhile, the recovery rate of APTLD is 95.9%±1.6%~97.2%±0.8% and the predicted root mean square error is less than 0.116 mg·L^-1. By comparing the performance of the above methods, we know PARAFAC is sensitive to the number of components in the samples and strictly linear to the decomposed spectral data. However APTLD has obvious advantages: being insensitive to the number of components, fast calculation speed, strong anti-noise ability, stable results, all of which highlight its advantages.
		2020 Vol. 40 (01): 119-124 [Abstract] ( 183 ) RICH HTML PDF (2960 KB) ( 71 )

	125	Integrity Detection of Hollow Fiber Membrane Bioreactor Based on Fluorescence Spectrum Response
		XIN Chang-chun^{1, 2}, JIA Hui^{1, 2, 3*}, LI Juan^{1, 2}, WEN Hai-tao^{2, 3}, LI Jing-yu², WANG Jie^{1, 2, 3}
		DOI: 10.3964/j.issn.1000-0593(2020)01-0125-06
		Membrane bioreactor (MBR) has the advantages of good effluent quality, small footprint and low sludge yield. However, once the membrane module is easy to be damaged during system operation, it will directly affect the effluent quality. In this study, the fluorescence emission spectral response was used as a technology to discuss the effects of hollow fiber membrane breakage rate, sludge concentration and breakage response time on membrane integrity monitoring in hollow fiber membrane bioreactor (MBR). The results showed that the MBR with hollow fiber membrane can retain the protein-like components (C₁) in the sewage effectively, while the fulvic-like components (C₂) and humic-like component (C₃) have poor interception performance. Based on the experiment results, a fluorescent component of the ultraviolet region-like tryptophan component with peaks（Ex 230 nm/Em 335 nm）was used as the detection index, the fluorescence interception change index （f_i） was used as the determination method, and the humic-like component with peaks（Ex 330 nm/Em 415 nm）was used as a reference index. Under the minimum detection accuracy θ, we found that the sludge concentration in the bioreactor had an important influence on the membrane breakage. The f_i in different sludge concentrations from MBR-1 to MBR-5 were 12.4%, 3.7%, 13.9%, 15.9%, and 15.8%. The reference indicator factors (R_i) were 1.87, 1.92, 1.35, 2.19, and 2.69, which are all morethan the indication factor R_θ under the lowest detection accuracy. The f_i can reflect the breakage of the membrane module effectively. As the number of broken fiber increases, the f_i increases gradually. It is also found that the membrane modules have self-repairing ability due to the foulantblockage with system running. Thesludge would enter the membrane lumen through the damaged portion of the membrane module. Base on the valid detection of ultraviolet region-like tryptophan component, fluorescence will become stable after about 80 minutes of operation. The f_i is satisfied tallies with the particle counter detection results. The system can identify the breakage information with very short response speed. The emission spectrum scanning based on the fluorescence spectral response can test the integrity of the membrane module, which is convenient, quick, and good practicability. Moreover, it can achieve the distributed detection in every membrane module.
		2020 Vol. 40 (01): 125-130 [Abstract] ( 191 ) RICH HTML PDF (5262 KB) ( 44 )

	131	Label-Free Detection of MicroRNA Based on Fluorescence Resonance Energy Transfer
		ZHANG Wen-yue¹, HAO Wen-hui¹, ZHAO Jing², WANG Yu-cong^1*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0131-05
		A label-free analysis strategy of miRNA is designed using the rolling circle amplification (RCA) and fluorescence resonance energy transfer (FRET) with cationic conjugated polymer (CCP) as donor. In this strategy, the cationic poly [(9, 9-bis(6’-N, N, N-triethylammonium)hexyl) fluorenylenephenylene dibromide] (PFP) serves as the donor of FRET and SYBR Green Ⅰ（SG）serves as the acceptor. PFP is a water-soluble π-conjugated polymer with cationic charged side chain functionalities. Its structure allows for efficient intrachain and interchain energy transfer mechanisms. It can be combined with DNA by electrostatic interaction. SG is an asymmetrical cyanine dye which preferentially binds to double-stranded DNA (ds-DNA) and stains single-stranded DNA with lower performance. The fluorescence of SG is weak in the free state, but greatly enhanced once the DNA-SG-complex is formed. Let 7a is used as the target molecule. A padlock probe matched with let 7a and the DNA probes matched with the RCA product are designed. In the presence of loret 7a, the hybridization of the padlock probe and target sequences brings two ends of padlock probe close together and can be covalently ligated into a loop in the catalyzing of T4 DNA ligase. When phi29 DNA polymerase and dNTPs are added, the rolling circle amplification of the circularized padlock probe is initiated from the target molecules and then a long single strand DNA with a lot of repetitive sequences is generated. When DNA probes and SG are added, a long ds-DNA is produced and stained by SG. The DNA-SG-complex and PFP are absorbed together through electrostatic interaction and the strong FRET from PFP to SG occurs due to the overlapping between the fluorescent emitting spectrum of the PFP and the absorption spectrum of SG. In the absence of let 7a, the padlock probe is not circularized, which induces the inhibition of rolling circle amplification and hybridization process. Therefore, the FRET also cannot occur. As a result, the let 7a can be quantitatively determined by monitoring the change of FRET signal. The results show that the let 7a concentrations in the range of 0.05～5 nmol·L^-1 are linearly proportional to the detection signals. The specificity of this method is studied and the most of tested interfering substances have no influence on the test result of let 7a except let 7b and let 7c. Additionally, by the detection of let 7a concentration in the extract solution of cells, it is indicated that the strategy can be applied to the practical samples analysis. Because fluorescent labeling is not required, this strategy reduces the detection cost and simplifies the operation steps. Therefore, this protocol shows certain potential in the study of miRNA-related biological processes as well as disease diagnosis.
		2020 Vol. 40 (01): 131-135 [Abstract] ( 226 ) RICH HTML PDF (1893 KB) ( 65 )

	136	Rapid Detection of Acid Orange Ⅱ by Surface-Enhanced Raman Spectroscopy Coated with Different Nano-Substrates
		WANG Xiao-hui¹, XU Tao-tao^{1, 2}, HUANG Yi-qun³, OU Yi-ming^1,4, LAI Ke-qiang^{1, 2}, FAN Yu-xia^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2020)01-0136-06
		Acid Orange Ⅱ, as an azo chemical dye, displays strong carcinogenesis and teratogenicity. Therefore, it is prohibited to use it in food industry. However, due to the bright color, good dyeing force and low price of Acid Orange Ⅱ, unscrupulous merchants illegally added Acid Orange Ⅱ to food for coloring, which seriously threatens food safety and consumer health. Acid Orange Ⅱ can be detected by traditional instrumental analysis methods. These methods have their own limitation such as complicated preprocessing, being time-consuming, and could not match the purpose of rapid detection and identification. Surface-enhanced Raman spectroscopy (SERS), as a fast, sensitive and novel fingerprint spectral analysis technology, has received extensive attention in the field of food safety detection. Therefore, this study aims to apply SERS spectroscopy technique combined with different nanosubstrates to explore the rapid detection method of Acid Orange Ⅱ. Firstly, gold nanoparticles (AuNPs), gold nanorods (AuNRs) substrate were synthesized in our laboratory, and we characterized its structure and properties using transmission electron microscipy (TEM). The results indicated that the nanosubstrates have the uniform scale and good dispersion. Then, the effect of two different Raman excitation sources was analyzed, which included the wavelengths of 633 and 780 nm. The results showed that the SERS response signal of Acid Orange Ⅱ is stronger based on the 633 nm excitation source. On this basis, three different substrates (Klarite^TM commercial solid substrate, AuNPs, and AuNRs) were compared and the substrate enhancement performance was studied. The SERS signal of Acid Orange Ⅱ was significantly different based on different gold nanoparticle sizes. It exhibited better reinforcing properties for (18±2) AuNPs. Acid Orange Ⅱ standard solutions with a series of concentrations were detected using SERS combined with three nanosubstrates (Klarite^TM, AuNPs with the diameter of (18±2) nm and AuNRs with an aspect ratio of 1.8), which showed almost similar enhancement for SERS signal of Acid Orange Ⅱ. The results demonstrated that the lowest detection concentrations of Acid Orange Ⅱ were 0.2, 0.1, and 0.1 mg·L^-1 based on Klarite^TM, AuNPs w and AuNRs substrates, respectively. As the SERS intensity increased with the increase of the concentration，the quantitative analysis models of Acid Orange Ⅱ were established. The Raman intensities of the selected peaks at 1 184, 1 385 and 1597 cm^-1 were in linear relationship with the concentrations of Acid Orange Ⅱ. The linear determination coefficient R² ranges were from 0.861 to 0.938, the RMSE is 0.88～1.15 mg·L^-1, and the RPD is 2.5～4.0. The linear regression model between 1 597 cm^-1 peak intensity and concentration (R²=0.933, RMSE=0.88 mg·L^-1, RPD=4.0) showed the best linear correlation. The results showed SERS spectroscopy could be used for qualitative and quantitative analysis of Acid Orange Ⅱ. The proposed method, as a simple, rapid and highly sensitive approach, could be applied for detection colorants.
		2020 Vol. 40 (01): 136-141 [Abstract] ( 196 ) RICH HTML PDF (2834 KB) ( 104 )

	142	*Isotopically-Labeled in-situ* FTIR Study of PtRh Catalyst under Different Temperatures**
		ZHU Fu-chun, TU Kun-fang, LI Guang, JIANG Yan-xia^*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0142-05
		Direct ethanol fuel cells are attracting much attention due to their excellent performance. Electro-oxidation of ethanol is not a combustion process, which involves multiple reaction processes. The low C—C bond cleavage ability and the poisoning caused by ethanol oxidation intermediate C1 molecules adsorb on the surface of catalysts are bottlenecks which restrict its application. Electrochemical in-situ fourier transform infrared spectroscopy (in-situ FTIRS) is to collect the vibration information of the specific functional groups of the reaction species in situ and reveal the reaction process at the molecular level, helping to understand the reaction mechanism. High performance PtRh/RGO catalyst was used, to investigate the electro-oxidation of ethanol at different temperatures through the combination of isotope tracer and electrochemical in-situ FTIRS. Cyclic voltammetry studies revealed that the electro-oxidation properties of ethanol and the selectivity of C—C bond cleavage ability decreased in the order of: PtRh/RGO (45 ℃)>PtRh/RGO (25 ℃)>commercial Pt/C. Electrochemical in-situ FTIRS revealed the electro-oxidation process at the molecular level. It was found that CO₂, CO, —CH₃ and —CO characteristic bands increased gradually with the increase of potential. CO₂ and CH₃COOH are the products of complete oxidation and incomplete oxidation of ethanol, respectively. Therefore, the ratio of the integrated area of the characteristic bands in the infrared spectrum [CO₂]/[CH₃COOH] is the measurement of CO₂ selectivity. The band at 1 280 cm^-1 was used to quantitatively calibrate CH₃COOH, but for the infrared spectra of PtRh/RGO catalyst, the superposition of band CH₃COOH at 1 280 cm^-1 and methanol derivative appeared at 1 214 cm^-1. The superposition band subtraction method was developed to calculate the CO₂ selectivity of PtRh/RGO. The selectivity of CO₂ on PtRh/RGO at 45 ℃ was improved compared with that at 25 ℃, increased 48.1% at 0.3 V, slightly increased at 0.5 and 0.6 V, but decreased at 0.4 V, which might ascribe to the competitive adsorption of β-C in ethanol and —OH in water. At both reaction temperatures, CO₂ selectivity show a downward trend at potentials above 0.4 V. To further investigate the complete oxidation of CO₂ derived from α-C or β-C, isotopically-labeled ¹³CH₃¹²CH₂OH was used as the probe molecule, combined with electrochemical in-situ FTIRS to study the electro-oxidation of ethanol on PtRh/RGO electrodes at 25 and 45 ℃. The results show that the initial potential of complete oxidation of β-C is independent of temperature, both of which are 0.3 V. By quantitatively analyze the ratio of the integrated area of ¹³CO₂/¹²CO₂, it was found that the ratio under 0.3～0.5 V at 45 ℃ increased 0.11, 0.18 and 0.22 compared with that at 25 ℃, which indicated that the selectivity of β-C increased with the increase of temperature or potential.
		2020 Vol. 40 (01): 142-146 [Abstract] ( 227 ) RICH HTML PDF (2218 KB) ( 97 )

	147	The UV-Vis Spectral Study on Thermal Treatment of Yellowish-Green Apatites
		ZHANG Jin-qiu, SHAO Tian, Andy Hsitien Shen^*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0147-05
		Recently, a special kind of apatites in the gem trade has been popular for its charming color which is similar to “Paraiba” bluish-green tourmaline. In order to prove whether the color of this apatite is processed, this paper put apatite samples with different colors respectively in the air atmosphere heated from 400 to 800 ℃. The experimental results show that, after heated at 650 ℃, yellowish-green samples can be changed into bluish-green. With temperature adding up to 800 ℃, all samples’ color were vanished. According to X-ray diffraction data, there is no phase transformation during the treatment. Subsequently, some yellowish-green samples are treated with different experimental parameters. Results show that the color change of samples is very similar in both air atmosphere and reducing atmosphere, which indicates that the color change is not related to the variation of the valence states. The UV-Vis spectra (200～800 nm) obtained at room temperature show that there are three apparent regions: a strong absorption between 300 and 450 nm, a transmittance from 450 to 550 nm, and a wide absorption band between 620 and 720 nm. Besides, there are some tiny peaks at 515, 528, 578, 739 and 747 nm. With the increase of temperature, the absorption coefficient of the samples is decreased significantly, causing color light. The absorption edge shifts to short wavelength, which reduces the absorption in the blue region and makes sample bluer. When the temperature reaches 400 ℃, the maximum absorption position in 620～720 nm displays a blue-shift resulting in less yellow tone. In the following, the absorption in 620～720 nm disappear and the color of sample vanish for the absorption coefficient keeping at a low level when the temperature adds up to 800 ℃. However, those tiny peaks still exist. Therefore, the color change in the heat treatment process is mainly related to the absorption edge and 620～720 nm absorption band.
		2020 Vol. 40 (01): 147-151 [Abstract] ( 293 ) RICH HTML PDF (3008 KB) ( 148 )

	152	Qualitative Identification and Quantitative Analysis of Maca Adulteration Based on Multispectral Imaging Technology
		ZHANG Hong-rui^{1, 2}, LIU Chang-hong¹, ZHANG Jiu-kai², HAN Jian-xun², CHEN Ying², ZHENG Lei^1*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0152-05
		Maca (Lepidium meyenii Walp.), an annual or biennial herb of Brassicaceae family, grows at high altitudes and contains rich nutritional value and bio-health benefits. After being listed as a new resource food in 2011, Maca is gradually becoming familiar to the public, the Maca industry has developed rapidly and price has risen steadily. Due to the fact that the shape of turnip (Brassica rapa L.) is very similar to that of Maca, driven by economic interests, illegal businessmen often pass turnip off as Maca to make Maca powder, slices and drinks in order to make exorbitant profits, which has brought serious negative impact on the orderly development of Maca healthy industry. Therefore, the authenticity identification of Maca is very necessary, but most of methods for the authenticity identification of Maca are traditional, and there are few rapid detection methods. In this study, a new method for rapid and non-destructive identification of Maca and turnip was established by using multispectral imaging technology. The experiment mainly focuses on the authenticity identification of Maca slices and Maca powder. One is to identify the authenticity of Maca slices. A total of 240 Maca and turnip slices (120 Maca slices and 120 turnip slices, respectively) were selected to collect data by the Videometer Lab equipment, which acquired the multispectral images at 19 different wavelengths from the visual region to the lower wavelengths of the NIR region and the detailed information of the measured wavelength were 405, 435, 450, 470, 505, 525, 570, 590, 630, 645, 660, 700, 780, 850, 870, 890, 910, 940 and 970 nm. In order to identify Maca and turnip effectively, the principal component analysis (PCA) was first performed. Then the qualitative analysis model was generated using support vector machine (SVM), genetic algorithm optimization support vector machine (GA-SVM) and back propagation neural network (BPNN) algorithm, and the ratio of the the calibration set to the prediction set is 3∶1. The results demonstrated that clear differences between Maca and turnip could be easily visualized by PCA. The predictive accuracies by SVM model for Maca and turnip slices were 98.33% and 100%, respectively, and the predictive accuracies by GA-SVM and BPNN model could be as high as 100%. The other is the identification of Maca powder. 120 samples of Maca powder were selected and 20%, 40%, 60%, 80%, 4 different adulterated levels (W/W) of turnip powder were mixed for multispectral data acquisition, Combining partial least squares (PLS) and least squares support vector machine (LS-SVM), the adulteration ratio of turnip was quantitatively predicted. The study found that the prediction coefficient (R²_P) of PLS and LS-SVM models were 0.992 and 0.994, the predicted root mean square error (RMSEP) were 2.718% and 2.675% and the relative prediction error (RPD) were 12.782 and 12.987, respectively. In comparison, the LS-SVM model had higher R²_P，RPD, lower RMSEP, so it was considered to have better predictive performance for the proportion of turnip powder adulterated to Maca powder. In conclusion, the research results provide a method for the rapid and non-destructive identification of Maca authenticity.
		2020 Vol. 40 (01): 152-156 [Abstract] ( 172 ) RICH HTML PDF (1515 KB) ( 64 )

	157	Miniature Snapshot Narrow Band Multi-Spectral Imaging Technology for Cervical Cancer Screening
		YI Ding-rong¹, ZHAO Yan-li¹, KONG Ling-hua^2*, WANG Wen-qi¹, HUANG Cai-hong¹
		DOI: 10.3964/j.issn.1000-0593(2020)01-0157-05
		Indeed, the contrast of white-light colposcope image is rather low, which would not be ideal for cervical cancer screening. According to the fact that cancerous tissue has a rich composition of hemoglobin, which has multiple characteristic spectral bands. In contrary to traditional hyperspectral imaging or sequential multi-spectral imaging, which needs scanning in the either spatial or spectral domain, here, we propose the utilization ofminiature snapshot narrow-band imaging (SNBI) method to expedite the spectral image acquisition process and enhance the contrast between different tissues. The goal is to realize a fast computer-aided diagnosis method for early screening of cervical cancer. Firstly, we usedan SNBI technology to capture the images of cervix tissues at four characteristic bands of hemoglobin, namely two of its absorption peaks at (415±10) and (525±10) nm, one reflectance peak at (620±10) nm, and one background band at (450±10) nm. Secondly, we fused those spectral images via simple algebric operation to enhance the contrast between normal and abnormal tissues. Thirdly, Euclidean distance algorithm was applied to the fused image to classify the tissues into different lesion grades. This is the first computer aided optical pathological diagnosis method with a diagnosis rate of over 20 fps. Herein, white-light colposcope, and miniature SNBI video camera were usedto separately capture images of fresh cervical tissues that were surgically dissected within 10 minutes. The same Euclidean distance classification algorithm was applied to the images obtained by the white light colposcope, and to the spectrally fused image obtained by the SNBI video camera. The classification accuracy of the two imaging methods was calculated and compared, using the histopathologic diagnosis as a standard reference. Euclidean classification accuracy upon the spectral fused image acquired by the SNBI was approximately 100%, which is undoubtedly better than that of the color image acquired by the conventional colposcopy. Multiple experienced gynecologists also subjectively agreed with the computer-generated classification upon the fused image, and highly acknowledged its clinical value especially on challenging areas where multiple degreed lesion layered together. The proposed SNBI method could improve the acquisition frame rate and contrast of the spectrally fused image, and effectively classify the cervical tissue into pathological-diagnosis-consistent types of tissues. Due to its advantages of being objective, intact and instant, SNBI has excellent potential to enlarge the coverage of cervical screening population in a low-income district and to assistprecise treatment of cervical cancer under image guidance.
		2020 Vol. 40 (01): 157-161 [Abstract] ( 198 ) RICH HTML PDF (1883 KB) ( 73 )

	162	Determination of DNA Methyltransferases 1 by a Method of Fluorescence Immunoassay Based on Magnetic Particles
		CHEN Yi-xue¹, NIU Shan-shan², LI Hong-ping², YU Fei¹, WU Yong-jun¹, LIU Li-e^1*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0162-06
		DNA methyltransferases1 (DNMT1)，a dominant enzyme responsible for maintaining the genetic stability of DNA methylation，is closely related to the occurrence and development of a variety of tumors. However, till now, most of the studies on DNA methyltransferases (DNMTs) detection have focused on prokaryote methyltransferases and been limited to laboratory studies. Therefore, a fluorescence immunoassay (FLISA) for the high sensitivity and high throughput detection of DNMT1 level in human serum samples was established to provide new ideas for early cancer diagnosis and clinical cancer therapy. The functional carboxyl Fe₃O₄ magnetic beads were used as solid phase carriers. 1-chloride-3-dimethylamino-propyl-3-ethylcarbodiimide hydrochloric acid (EDC) and sulfo-N-hydroxysuccinimide (Sulfo-NHS) were used as coupling agents to prepare immune-magnetic capture probe Fe₃O₄@ McAb_DNMT1 (monoclonal antibody DNMT1). After that, the immune-fluorescent detective probe 5-TAMRA@PcAb_DNMT1（5-carboxytetramethylrhodamine@polyclonal antibody DNMT1）was also made. Their structure and activity were characterized by infrared absorption, UV-Vis spectra, Zeta potential and immunocompetence. Then, the content of DNMT1 in human serum samples was detected based on the double-anti-sandwich method by FLISA with high sensitivity. Finally, methodology evaluation and comparison were conducted. The results showed that the probes conjugated successfully and maintained the immunocompetence of the original antibody. The linear equation was y=222.046+48.323x, the linear range was 0.05～80 ng·mL^-1, and the correlation coefficient was 0.991 4, the detection limit was 0.005 ng·mL^-1, the intra-and inter-panel RSD was 4.7%～8.8% and 1.6%～10.0% (n=6), respectively, intra- and inter-panel recoveries were 91.3%～102.4% and 88.0%～98.8% (n=6), respectively. The cross-reactivity rates with other two DNA methyltransferase 3a/3b were lower, and the specificity of FLISA was well. Compared with ELISA and MELISA, FLISA has the lowest detection limit and shortest analysis time. Compared with ELISA kits, the result displayed a high correlation between two methods, and the difference of them was not statistically significant (p＞0.05). The result suggests that the FLISA system would be used to detect multiple samples at the same time for the rapid analysis of DNMT1 in human serum samples.
		2020 Vol. 40 (01): 162-167 [Abstract] ( 191 ) RICH HTML PDF (2995 KB) ( 54 )

	168	Age Estimation of Bloodstains Based on Visible-Near Infrared Multi-Spectrum Combined Ensembling Model
		RONG Nian-ci, HUANG Mei-zhen^*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0168-06
		The accurate estimation of blood age is of great significance in the forensic identification of criminal investigation. In this paper, a visible-near-infrared multispectral imaging system with 8 LEDs as illumination source and monochrome CCD camera as image input unit is constructed. The ensembling model based on k nearest neighbor method, support vector machine and random forest method is used to analyze and estimate the age of bloodstains. The feasibility of using the visible-near-infrared reflectance multispectral to accurately estimate the age of human blood was investigated, and the results were compared with the previous studies using hyperspectral techniques for blood age estimation. The influence of blood specificity was also tested. The experiment recorded images of 8 channels from 400 to 940 nm on days 1 to days 20 of 11 human blood samples, and the spectra were preprocessed using standard normal variate transformation (SNV) to eliminate spectral differences due to the baseline shift and scattering. Seven preprocessed samples were randomly selected as training set to build the model, and the remaining four samples were used as test sets to test the model, a model ensembling model based on k nearest neighbor method, support vector machine and random forest method was built. Compared with the results by k-NN model, SVM model and RF model the result is better. The correct classification rate (CCR) of the samples between 0 and 2 d is 80%, the average error is 0.053 d, and the CCR between 2 and 20 d is 69%. The average error is 0.442 d, which is comparable or better than that obtained by using hyperspectral techniques. In order to test the practical applicability of the method, this paper tested the effect of blood specificity on the model. The test sample was 20 blood samples taken from 8 different donors, 10 of which from 4 donors were used to refine the original model, and 10 samples from another 4 donors were used as test sets to test the effect of blood specificity. The estimated age of blood from different sources is: CCR is 75.6% between 0 and 2 d, and the average error is 0.063 1 d. After adding blood samples from different donors, there was no significant decrease in CCR, indicating that the model still has good adaptability to blood samples from different sources. The results show that compared with the previous research results, multispectral technology combined with model ensembling algorithm could obtain more accurate age estimation results, and has the advantages of simple set-ups, low-cost and good stability, which might be a high-precision blood age estimation method and have important application value in the field of forensic science.
		2020 Vol. 40 (01): 168-173 [Abstract] ( 224 ) RICH HTML PDF (2437 KB) ( 108 )

	174	*Identification of Piper longum* L. from Different Areas by FTIR and HPLC Fingerprint Methods**
		ZHANG Hui-wen^{1, 2}, SONG Xiao-ling², SHI Song-li², ZHANG Sha-sha¹, LIANG Yue³, WANG Huan-yun^1*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0174-05
		Piper longum L. is an edible Traditional Chinese Medicine (TCM), and used as mongolian, tibetan and uyghur medicines, and listed in the Chinese Pharmacopoeia to treat disease, such as stomachache and diarrhoea, which is also used as spice and flavoring. Active Ingredients in Piper longum L. are amide alkaloids. While reported articles mostly focus on the contents of piperine or piperlonguminine by high performance liquid chromatography, and the quality control method is relatively simple and lack of holism and innovation. This paper analyzed six batches of Piper longum L. from four areas by FTIR and HPLC fingerprint. The common peak ratio and variant peak ratio were calculated by FTIR spectroscopy of the six samples, and the dual index sequence of common peak ratio and variant peak ratio were established. Entire compositions of Piper longum L. were analyzed by HPLC fingerprint, and the contents of piperine or piperlonguminine were listed. The result showed that the evaluation results of the samples by the two methods were mutual corroboration. Six batches of Piper longum L. contained similar compositions with relatively stable quality. Among them, Piper longum L. rised in Yunnan (S1) was different from the other five batches. Results showed that common peak ratio and variant peak ratio of IR could evaluate the quality of the compositions in TCM integrally and comprehensively, as well as HPLC fingerprint. while the HPLC fingerprints only showed the compounds with ultraviolet absorption at 254 nm. Therefore, IR was suitable to analyze the composition system of complex TCM. The absorption peak strength and peak shape in the IR are the results of the interaction of various functional groups and generated by the superposition of various chemical components in the infrared spectrum of Piper longum L., The HPLC fingerprint of Piper longum L. showed 17 common peaks and the similarity verified the results of IR. Contents of piperine and piperlonguminine were higher in Piper longum L. from Bozhou and Guangxi than Yunnan and Hainan, and results demonstrated single component was difficult to represent the entire quality of TCM. This paper reported the FTIR and HPLC fingerprint methods in the quality control of Piper longum L. for the first time, and the two methods were simple and rapid with small usages, and complemented each other. The methods provided research basis for chemical compositions, quality controls, developments and application of Piper longum L., and probed the influence of planting resources on herbal medicines.
		2020 Vol. 40 (01): 174-178 [Abstract] ( 246 ) RICH HTML PDF (1625 KB) ( 95 )

	179	*Prediction of the Main Components in S₂ of Plectocomia himalayana* Fiber Based on Raman Spectra**
		ZHANG Fei-fei^{1, 2}, JI Bi-chao¹, WANG You-hong^1*, XUE Xia¹, LI Dan¹, MA Jian-feng³
		DOI: 10.3964/j.issn.1000-0593(2020)01-0179-05
		Rattan, belonging to Calamoideae of Palmae, is a multipurpose plant resource found in highly tropical forest, and it is an important non-timber forest product inferior to timber and bamboo, with high economic value and development prospects. There are 13 genera and more than 660 species in the world, of which 4 genera and 37 species of 5 varieties are naturally distributed in China, but there are less than 30 species with high economic value. At present, little is known about the cell structure of rattan, especially the cell wall structure of fiber, which seriously limits the research, processing and utilization of rattan. Therefore, in order to construct the fiber wall structure model of rattan, Plectocomia himalayana was chosen as the research material, and from which samples were cut, softened, embedded with polyethylene glycol and sliced at the base, 2 m, middle and tip respectively. After the slices were soaked in 0.2 mol·L^-1 NaBH₄ for 5~6 h at room temperature and washed with distilled water, the spectral data were obtained by point-by-point scanning microscopic probe imaging method with the LabRam XploRA microscopic confocal Raman spectrometer. The relative content of cellulose, hemicellulose and lignin in the central layer of secondary wall (S₂) of fiber in cortex, middle layer and core at different parts of P. himalayana cane was obtained after the spectral data were processed by LabSpec 5 software, and then the variation of relative content in radial direction and axial direction was also analyzed. The research results show that, in terms of S₂ of fiber at 2 m, the relative content of cellulose and hemicellulose is the highest and the relative content of lignin is the lowest in cortex, while the relative content of cellulose and hemicellulose is the lowest and the relative content of lignin is the highest in core, and the relative content of cellulose, hemicellulose and lignin in middle layer is between that of cortex and core in the radial direction. In the axial direction, the relative content of cellulose and hemicellulose of S₂ of fiber in cortex is the highest at 2 m, and that of lignin in tip is the highest. The relative content of cellulose, lignin and hemicellulose of S₂ of fiber in core is the highest at the middle, 2 m and base respectively. The cortex and core are the same as cane of rattan, the relative content of cellulose in S₂ of fiber is the minimum in the tip, and that of hemicellulose and lignin is the least in the middle. Based on the above analysis, the relative contents of cellulose, hemicellulose and lignin in S₂ of rattan fiber are different in different parts of rattan.
		2020 Vol. 40 (01): 179-183 [Abstract] ( 172 ) RICH HTML PDF (1912 KB) ( 58 )

	184	Rapid Detection of Microstructural Characteristics of Heartwood and Sapwood of Chinese Fir Clones
		SUN Hai-yan^{1, 2}, JIA Ru^{1, 2}, WU Yan-hua², ZHOU Liang³, LIU Sheng-quan³, WANG Yu-rong^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2020)01-0184-05
		Chinese fir (Cunninghamia lanceolata) is the most important fast-growing coniferous species in China, which is widely used in buildings, furniture and ships. Its heartwood formed earlier, and there are obvious differences between heartwood and sapwood. Rapid detection of chemical composition, cell wall ultrastructure and microstructural differences between heartwood and sapwood of new clones can provide important structural data for evaluating the quality characteristics of heartwood and sapwood. In this paper, the chemical composition of cell wall, crystallinity of cell wall cellulose and microstructure of heartwood and sapwood of Chinese fir clone Yang 61 were determined by Fourier transform infrared spectroscopy, X-ray diffraction, optical microscopy combined with Image J. The results showed that the wave numbers of chemical functional groups in FTIR spectra of heartwood and sapwood were basically the same, that is, the main structure of chemical composition was the same, and the difference between them was mainly in peak intensity. The characteristic peaks of phenols and alcohols (1 034 and 1 122 cm^-1) and Caryl-O stretching vibration (1 264 and 1 232 cm^-1) in infrared spectra of heartwood were higher than those in sapwood. So this showed that the content of heartwood extracts and the degree of crosslinking of lignin in Chinese fir clones heartwood are possibly higher than those of sapwood. At the same time, the change of relative content of three chemical components was analyzed by characteristic peak ratio method. It was found that the relative content of lignin in heartwood increased by 2%～4%, the relative content of cellulose decreased by 2%, and the hemicellulose content remained unchanged compared with sapwood. By analyzing the X-ray diffraction patterns, it was found that the shape of the diffraction patterns of heartwood and sapwood of Chinese fir were basically the same, but the width of the peak of sapwood was narrower than that of heartwood, and the peak intensity of sapwood was higher at 2θ=22.5°than that of heartwood. The relative crystallinity of heartwood was 35.1% and that of sapwood was 43.1%. There was a significant difference between them at p<0.01. Microscopic images of heartwood and sapwood of Chinese fir were obtained by optical microscopy. The average area and area ratio of tracheid lumen were quickly detected by Image J analysis technology, and it was found that average area and area ratio of tracheid lumen of heartwood were smaller than those of sapwood, that is, heartwood cells have thicker walls and smaller lumens compared with sapwood. The above research found that FTIR, X-ray diffraction, optical microscopy combined with Image J can quickly and accurately detect the differences of microstructure characteristics between wood heartwood and sapwood of Chinese fir clones. The results can provide theoretical guidance and scientific basis for evaluation of physical and mechanical properties, cell wall modification and efficient utilization of heartwood and sapwood.
		2020 Vol. 40 (01): 184-188 [Abstract] ( 274 ) RICH HTML PDF (2583 KB) ( 86 )

	189	Rapid Detection of Crab Freshness Based on Near Infrared Spectroscopy
		LI Xin-xing¹, YAO Jiu-bin¹, CHENG Jian-hong², SUN Long-qing¹, CAO Xia-min³, ZHANG Xiao-shuan^4*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0189-06
		The freshness of river crab is the most important factor that most consumers consider when buying. Total volatile base nitrogen (TVB-N) is a commonly used international index for evaluating meat freshness, However, its detection process is cumbersome and time-consuming, which can not meet the urgent needs of the current market for rapid and objective evaluation of river crab freshness. Therefore, it is an urgent problem to establish a rapid method for detecting freshness of river crabs. A total of 126 crabs purchased from aquatic market were rapidly transported to the laboratory by polyethylene oxygenation bag. After treatment on a clean bench, the crabs were divided into 42 experimental samples, with 3 fresh crabs in each sample; 42 experimental samples were stored in a constant temperature biochemical incubator at low temperature of 4 ℃. 6 crab samples were taken from the incubator on time every day for spectral data collection and freshness index determination for 7 days. In this paper, near infrared spectroscopy (NIRS) was used to evaluate the freshness of river crabs stored at different time, and total volatile base nitrogen (TVB-N) was used as an index to evaluate the freshness of crabs. Firstly, by comparing influence on the model prediction effect of 5-fold Cross Validation, Kennard-stone algorithm and sample set partitioning based on joint X-Y distance algorithm, finally, the 5-fold CrossValidation algorithm was used to divide the samples. 32 samples were used as training sets for model building, and the remaining 10 samples were used as test sets for model testing. Then, on the basis of dividing the samples by five fold cross validation algorithm, wavelet transform (WT), Savitzky-Golay smoothing, first derivative (Db1), second derivative (Db2) and wavelet transform (WT) combined with Savitzky-Golay smoothing were used to pretreat. Wave transform (WT) pretreatment was the best spectral pretreatment method, which eliminated the useless information in the spectrum and improved the signal-to-noise ratio. Once more, on the basis of the WT pretreatment, principal component analysis (PCA) and successive projection algorithm (SPA) were used to extract spectral feature bands, and the principal component analysis (PCA) was used as the optimal wavelength selection method by comparing the model prediction effect. With the selected 16 feature bands as the input of the model, which not only improved the running speed of the model, but also improve the stability of the model. Finally, after PCA feature extraction, by using partial least squares regression (PLSR) and multiple linear regression (MLR) built the TVB-N quantitative prediction model, by comparing the two kinds of model prediction effect to determined the partial least squares regression (PLSR) model for the optimal modeling method, this paper finally determine the optimal model based on WT-PCA-PLSR model, model prediction determination coefficient R² was 0.89, and the root mean square error of prediction RMSEP was 3.00. In conclusion, the prediction model established in this study has a high accuracy, and this method can realize the rapid detection of the freshness of river crabs, and has a good market application prospect.
		2020 Vol. 40 (01): 189-194 [Abstract] ( 223 ) RICH HTML PDF (1549 KB) ( 141 )

	195	Rapid Determination of Total Nitrogen in Aquaculture Water Based on Ultraviolet Spectroscopy
		LI Xin-xing¹, ZHOU Jing¹, TANG Hong², SUN Long-qing¹, CAO Xia-min³, ZHANG Xiao-shuan^4*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0195-07
		The paper is intended to achieve rapid determination of total nitrogen (TN) concentration by using Ultraviolet (UV) spectroscopy technology, which was one of the most important indicators to measure the pollution degree in aquaculture water. The original dataset used in the paper contains 88 samples data with actual concentration value and spectral absorbance value. It is helpful to select the optimal model through the five stages that include sample set division algorithms, data preprocessing algorithms, feature band extraction algorithms, model selection algorithms and latent values (LVs) selection method. In the first four stages, the comparison results of different methods show that each stage is necessary, and only by comparing the advantages and disadvantages of modeling results with various algorithms can we find the most suitable modeling process and method. First of all, the original sample set is processed by the concentration gradient (CG) method, then three models are built which respectively are principal component regression (PCR), stepwise regression (SR) and partial least squares regression(PLSR), and it proves that the PLSR is the best prediction model. The number of LVs can greatly influence the accuracy of model, and usually when the value of the model root mean square error of prediction (RMSEP) is the minimum, the LV number is optimal. Secondly, it is testified that the SPXY algorithm is the best by comparing the effect of random sampling (RS) algorithm, concentration gradient (CG) algorithm, kennard stone (KS) algorithm and SPXY algorithm. Thirdly, based on SPXY algorithm, the paper uses five preprocessing algorithms which are wavelet transform (WT) method, first derivative (Der1st), and second derivative (Der2nd) three single preprocessing algorithms, WT-Der1st and WT-Der2nd. Fourthly, according to the results of data processing, using successive projections algorithm (SPA) and stepwise regression (SR) for feature band extraction algorithms, the results show that the extraction efficiency of SPA not only can greatly reduce the complexity of model, but also improve the prediction accuracy. The feature band extracted based on WT-Der1st-SPA is 218 nm, which is consistent with the characteristics of total nitrogen band range, indicating the method was relatively scientific. Finally, considering the prediction accuracy and complexity of model, the PLSR based on WT-Der1st-SPA with the best results with the determination coefficient (r²) and RMSEP being 0.996 and 0.042 mg·L^-1 for the prediction set in 10 models. In short, the prediction model established could be applied to the rapid and accurate determination of total nitrogen concentration. Moreover, this study laid the foundation for further implementation of online analysis of aquaculture water and rapid determination of other water quality parameters.
		2020 Vol. 40 (01): 195-201 [Abstract] ( 218 ) RICH HTML PDF (2149 KB) ( 115 )

	202	Study on Detection System of Grape Seed Oil Adulteration Based on Visible/Near Infrared Spectroscopy
		TANG Yun-feng^{1, 2}, CHAI Qin-qin^{1, 2*}, LIN Shuang-jie^{1, 2}, HUANG Jie^{1, 2}, LI Yu-rong^{1, 2}, WANG Wu^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2020)01-0202-07
		Various kinds of adulterated grape seed oil and concealed adulterated means cause a severe problem in food safety detection. In order to regulate the edible oil market, it is especially important to provide a convenient and reliable method for identifying the quality of grape seed oil. However, traditional methods for chromatography and mass spectrometry are time consuming, reagent intensive, highly specialized, etc.; and the near infrared spectrometer that realizes non-destructive analysis is expensive and has high operating environment requirements. Thus, a visible/near infrared spectrometer with low cost and high accuracy was designed to discriminate grape seed oil adulteration. Firstly, a visible/near infrared spectrometer hardware platform based on USB6500-Pro detector was built, and a simple human-computer interaction interface based on Qt was designed to realize the collection and processing of spectral data and the display of grape seed oil adulteration discrimination results. Secondly, for the spectral noise brought by hardware and detection environment, wavelet transform was used to filter out noise and reduce spectral distortion. Finally, considering that the existing quality discrimination models based on machine learning often rely on the known oil training sample set to predict the different adulterated categories; and driven by interest adulteration means will emerge in endlessly which will result in the emerging of new adulteration categories not in the original training set, the existing quality identification methods are difficult to give accurate results. Therefore, a discrimination method for known and new adulterated oil spectra was designed in the detection system. This method was realized by two steps: (1) classification: the extreme learning machine (ELM) classifier model was established by using the training set in the modeling database to realize the preliminary judgment of the preliminary adulteration category; (2) correction: the automatic clustering algorithm was then used to further correct the prediction result. If a clustering center is generated with the correction data set, it is proved that the prediction result is correct and belongs to the known adulteration category in the modeling database; if two cluster centers are generated, the prediction result is incorrect and the sample is a new adulteration category which does not appear in the modeling database. The result of the accurate adulterated category was eventually obtained. In order to test the performance of the system, five classes of oil, including pure grape seed oil, and grape seed oil blended with different proportions of soybean oil, corn oil, sunflower oil and blend oil were analyzed by the visible/near infrared hardware platform and their spectroscopy data were collected. It contains 30 sets of data for each class of oil, totals 150 sets. Before inputting the visible/near infrared spectroscopy data into the detection system, they were firstly de-noised by wavelet threshold method and pre-processed by multiple scattering correction. Assuming that the first four classes were known adulteration class in the modeling database and the fifth class was new adulteration class, samples from each of the four known adulteration classes were divided into 20 training sets and 10 test sets by using K-S algorithm. Then, ELM classification model was established by using 80 training sets, and 40 test sets were input into ELM for preliminary discrimination. The discrimination results were further analyzed and corrected by clustering. There was one clustering center, which meant that the ELM model discriminated accurately and could recognize 100% of the known classes. However, when 30 samples from the new adulterated class were put into the ELM model, all of them were discriminated as pure grape seed oil. The discrimination results were further clustered and corrected. There were two clustering centers, which showed that the model was misjudged and the fifth class was qualitatively determined as a new adulterated class. The experimental results showed that the designed visible/near infrared spectroscopy detection system was simple and fast, and can identify not only the known adulteration categories but also the new adulteration categories.
		2020 Vol. 40 (01): 202-208 [Abstract] ( 205 ) RICH HTML PDF (2790 KB) ( 102 )

	209	A Model on Detecting the Polluted Degree of Maize Leaves by Cu Pollution Vegetation Index
		CHENG Feng, YANG Ke-ming^*, CUI Ying, LU Tian-yu, CHEN Li-fan, RONG Kun-peng
		DOI: 10.3964/j.issn.1000-0593(2020)01-0209-06
		The use of hyperspectral remote sensing to monitor heavy metal pollution in crops has become an important part of remote sensing research. The difference in the amount of heavy metal content in the contaminated crop leaves mapped to the spectrum is weak, so it is challenging to dig sensitively the value information contained in it. In this paper, based on the spectrum of crop leaves, a pollution detection model of copper pollution vegetation index (CPVI) was proposed by combining multiple spectral feature bands to characterize the pollution degree of heavy metal copper on crops. Firstly, a pot experiment was conducted to add CuSO₄·5H₂O powder with different concentration gradients to the soil to simulate copper-contaminated soil environment and stress corn growth. The spectra of old, middle and new leaves at the ear of corn were collected, and the Cu²⁺ content and relative chlorophyll concentration in the leaves were determined. Then, using 58 randomly selected corn leaf spectra as experimental data, the spectral reflectances of the two groups of wavelengths λ₁ and λ₂ were selected in the wavelength range of 380~900 nm. The Pearson correlation coefficient between CPVI [λ₁, λ₂] and Cu²⁺ content in the corresponding leaves was calculated, and the absolute value matrix of correlation characteristics was obtained. Secondly, according to the obtained correlation feature matrix, the characteristic band of 690 and 465 nm with high correlation coefficient was extracted and combined with the band 850 nm to establish the Copper pollution index of maize (CPVI_m). After that, CPVI_m index was verified based on 26 other groups of data, and Normalized difference vegetation index (NDVI), MERIS terrestrial chlorophyll index (MTCI) and other conventional vegetation indexes were compared to verify the effectiveness and superiority of CPVI_m. The results showed that the highest correlation coefficient between NDVI, MTCI, REP, DVI and Cu²⁺ content in leaves was 0.68, and the lowest residual sum of squares was 70.99. However, CPVI_m was significantly negatively correlated with Cu²⁺ content in leaves. The correlation coefficient was -0.80, and the residual sum of squares was 48.52, which were better than conventional indexes such as NDVI and MTCI. It proved that CPVI_m is more sensitive to heavy metal stress. At the same time, the robustness of CPVI_m index was verified by using the spectral data of different varieties of maize in different years. The correlation coefficient of CPVI_m and Cu²⁺ content were -0.90 and -0.96, respectively, which were significantly correlated. It shows that CPVI_m is still suitable for detecting the pollution degree of different maize varieties. In addition, using Cu²⁺ content, CPVI_m and chlorophyll relative concentration in maize leaves, a three-dimensional analysis model was constructed, which reflected the correlation between them from a spatial point of view. The CPVI detection model based on the combination of spectral characteristic bands can be used as a reference method to evaluate the pollution degree of heavy metals in crops. The CPVI_m index based on this method can effectively identify the degree of heavy metal Cu²⁺ pollution in maize.
		2020 Vol. 40 (01): 209-214 [Abstract] ( 190 ) RICH HTML PDF (3875 KB) ( 72 )

	215	The Research on Quantitative Analysis of Feed Crude Fat and Corase Fiber Based on Near Infrared Spectroscopy and Variables Selection Methods
		HAO Yong, WU Wen-hui, SHANG Qing-yuan
		DOI: 10.3964/j.issn.1000-0593(2020)01-0215-06
		Near infrared spectroscopy (NIRS) combined with partial least squares (PLS) method was used to achieve rapid quantitative analysis of crude fat and corase fiber in feed. The norris-williams derivation (NW) and multiplicative scatter correction (MSC) methods were used to pretreat the spectrum, and the monte carlo based uninformative variable elimination (MCUVE), variables combination population analysis (VCPA) and interval variable iterative space shrinkage approach (iVISSA) were used to select and optimize the variables of the spectrum. PLS was used for the establishment of the spectral calibration model, and the parameters of calibration set correlation coefficient (R_c), root mean square error of cross validation (RMSECV), prediction set correlation coefficient (R_p) and root mean square error of prediction (RMSEP) were used to evaluate the models. Compared with other pretreatment methods, the RMSECV and RMSEP values of the spectral model after MSC treatment decreased, while the R_c and R_p values increased. In the crude fat quantitative analysis model, the RMSECV and R_c of the original spectral model were 0.21 and 0.87, RMSEP and R_p were 0.20 and 0.88, and the number of variables (V_n) was 1501. After selecting variables by MCUVE method, RMSECV and R_c were 0.17 and 0.92, RMSEP and R_p were 0.19 and 0.89, and V_n was 400. For VCPA-PLS model, the RMSECV and R_c were 0.206 and 0.87, RMSEP and R_p were 0.25 and 0.81, and V_n was 12. For iVISSA-PLS model, the RMSECV and R_c were 0.21 and 0.86, RMSEP and R_p were 0.20 and 0.87, and V_n was 20. In the corase fiber model, the RMSECV and R_c of the original PLS model were 0.28 and 0.91, RMSEP and R_p were 0.23 and 0.95, and V_n was 1 501. After MCUVE selection, the RMSECV and R_c of the model were 0.23 and 0.95, RMSEP and R_p were 0.25 and 0.94, and V_n was 740. After VCPA selection, the RMSECV and R_c of the model were 0.27 and 0.91, RMSEP and R_p were 0.30 and 0.91, and V_n was 11. After iVISSA selection, the RMSECV and R_c of the model were 0.29 and 0.90, RMSEP and R_p were 0.27 and 0.93, and V_n was 20. The results showed that the MSC method could effectively improve the spectral quality and eliminate the spectral translation error; the MCUVE variable selection method could simplify the model to improve the model accuracy and stability, and establish the optimal model. In the crude fat quantitative analysis model, after the MSC-processed spectrum was selected by MCUVE, the remaining 400 were used to establish the PLS model, R_c and R_p were improved by 0.05 and 0.01 compared to the full-spectrum model, and the RMSECV and RMSEP were reduced to 0.17 and 0.19; The model selected by VCPA and iVISSA had almost the same result as the full-spectrum model, and its greatest feature was that only 12 and 20 variables were selected. In the corase fiber model, 740 variables selected by MCUVE were used to establish the PLS model with R_c and R_p of 0.95 and 0.94, RMSECV and RMSEP of 0.23 and 0.23, respectively; VCPA and iVISSA used 11 and 12 variables to establish the regression model, but its model results were all worse than the MCUVE model. The establishment of MSC-MCUVE-PLS quantitative analysis model using feed near-infrared spectroscopy could effectively quantify crude fat and corase fiber in feed.
		2020 Vol. 40 (01): 215-220 [Abstract] ( 213 ) RICH HTML PDF (3848 KB) ( 92 )

	221	Study on the Method of Determining the Survival Rate of Rice Seeds Based on Visible-Near Infrared Multispectral Data
		LUO Long-qiang¹, YAO Xin-li¹, HE Sai-ling^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2020)01-0221-06
		The seed vigor was greatly affected by the storage condition. This work collected seeds that were affected by different storage conditions under real circumstance, and verified their germination rate difference by germination experiment. After that, we took some samples from them and measured the visible-near-infrared reflection spectra of each single grain. By adapting different spectral preprocessing techniques, combined with several machine learning modeling methods, we tried to distinguish the seeds according to their germination rates. In our experiments, some spectral pretreatment methods were compared, such as standard reflection spectrum correction. It also compared supervised machine learning modeling method such as support vector machine, K-near neighbor and discriminant analysis. From the perspective of recognition accuracy, we believed that standard reflection spectrum correction method can greatly improve the spectral difference of seeds with different survival rates, and thus achieve higher recognition accuracy through machine learning. At the same time, we compared the supervised machine learning modeling methods such as support vector, k near neighbor and distance discriminant analysis, and find that the standard reflection spectrum correction method combined with distance discriminant analysis can achieve hundred-percent accuracy of predicting different seeds category. Furthermore, in order to meet the requirements of rapid identification in practical applications, in the experiment we compressed high-resolution spectral data into low-resolution multi-channel band-pass spectral data, which can greatly reduce the spectral data length and save the time spent in training and classifying of various machine learner. The prediction accuracy of models trained by those simplified spectra data is still close to 90%. It fully demonstrates that the use of multi-channel broadband spectral data combining with the selection of appropriate machine learning modeling methods is sufficient to meet the general needs of the actual seed selection industry, and it is a potential technique for rapid identification of rice grain survival rates in the future. The experiment also used a variety of bandpass widths to simplify the spectra, and analyze and compare the effects of different bandpass widths on the recognition accuracy. In general, due to the increase in bandwidth, the length of data is reduced, and the recognition speed is faster, but the recognition accuracy is decreased. In the experiment, we changed the spectral bandwidth from 10 to 50 nm, and the recognition accuracy of the simplified spectrum after standard reflection correction decreased from 87.50% to 58.75%. In practical use, it is necessary to balance the recognition rate and the expected recognition accuracy, and select a reasonable bandwidth. This study verified that the simplified near-infrared reflectance spectroscopy can quickly and accurately identify the survival rate of rice seeds, which lays a foundation for rapid seed survival rate recognition technique based on bandpass filters in the future.
		2020 Vol. 40 (01): 221-226 [Abstract] ( 207 ) RICH HTML PDF (1233 KB) ( 110 )

	227	Estimation of Disease Severity for Downy Mildew of Greenhouse Cucumber Based on Visible Spectral and Machine Learning
		ZHANG Ling-xian¹, TIAN Xiao¹, LI Yun-xia¹, CHEN Yun-qiang¹, CHEN Ying-yi¹, MA Jun-cheng^2*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0227-06
		Accurate estimation of disease severity for downy mildew of greenhouse cucumber is a prerequisite for scientific disease control. It is of great significance to reduce the use of pesticides and to improve the quality of greenhouse cucumber, as well as farmers’ income. With the application of machine learning in the field of plant disease diagnosis, estimating the severity of plant diseases is gaining concerns. In order to increase the accuracy, this paper used the digital images of greenhouse cucumber downy mildew and machine learning methods to estimate the disease severity for downy mildew of greenhouse cucumber. A digital camera was used to collect images of greenhouse cucumber leaves with downy mildew, whose background were manually eliminated. An estimation model based on Convolutional Neural Network (CNN) was constructed with cucumber downy mildew leaf image as input. The initial symptom segmentation was achieved by using the combination of three visible color features (CVCF) and support vector machine. The segmentation results were optimized by using the speeded up robust feature (SURF) feature and morphological operation. After obtaining the segmentation image of cucumber downy mildew symptoms, the average and standard deviation of 15 color components in five color spaces of RGB, HSV, L^a^b^*, YCbCr and HSI were extracted. On this basis, the gray level co-occurrence matrix was used to extract four texture features of each color component, including contrast, correlation, entropy and stability, resulting in 90 features. Pearson correlation analysis was used for feature selection. Shallow machine learning estimation models, including Support Vector Machine Regression and BP Neural Network, were constructed based on the image features with high correlation with the actual severity value of downy mildew of greenhouse cucumber. Based on the three estimation models, the disease severity for downy mildew of cucumber was estimated. The accuracy of the three estimation models was quantitatively evaluated by using Coefficient of Determination (R²) and Normalized Root-Mean-Squared Error (NRMSE). The results showed that there was a good linear relationship between the severity of downy mildew of greenhouse cucumber estimated by the model and the actual values. The model based on CNN achieved the best accuracy, whose R² was 0.919 0 and NRMSE was 23.33%, followed by the model based on BPNN, with R² being 0.890 8, NRMSE being 24.64%, while the model based on SVR was the last, with R² being 0.890 1 and NRMSE being 31.08%. The evaluation results showed that by using the digital images of cucumber downy mildew and the convolution neural network estimation model, the disease severity for downy mildew of greenhouse cucumber could be accurately estimated, which could provide support to the scientific control of downy mildew of greenhouse cucumber and reduce the use of pesticides.
		2020 Vol. 40 (01): 227-232 [Abstract] ( 256 ) RICH HTML PDF (2236 KB) ( 264 )

	233	Research on Chalky Rice Detection Based on Visible Spectrogram and Deep Neural Network Technology
		LIN Ping¹, ZHANG Hua-zhe¹, HE Jian-qiang¹, ZOU Zhi-yong², CHEN Yong-ming^1*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0233-06
		Aiming at the problems of subjective randomness, low repeatability, being time-consuming and low accuracy of traditional chalky rice detection, a new method based on visible spectrogram combined with deep learning algorithm is proposed to meet the requirement of rapid and accurate rice quality parameters in modern agricultural production. In the experiment, CCD color camera was used to obtain the visible spectra of chalky rice and normal rice. Random image transformation methods such as rotation, flipping and contrast adjustment were used to enhance the network training data set to prevent the fitting phenomenon of the depth detection model in the learning process. In this paper, seven deep-level convolution neural network models, including convolution layer, pooling layer, full-connection layer and input-output layer is constructed. The visible spectral image of rice is convoluted and pooled by network model. The characteristic parameters of visible spectral image of rice in convolution layer are obtained by iterative learning training method. The non-linear ReLU activation function is used to accelerate the convergence rate of the effective abstract feature extraction of rice; then the pool layer is employed to obtain the distinguishable semantic features that can express normal rice and chalky rice; finally, the data are transported into the full connection layer. The chalky rice can be identified accurately by classification. The method of rice chalkness detection based on convolution neural network eliminates the complicated steps of feature extraction compared with the traditional method. Because the features extracted by convolution network have more robust expression for specific targets, the algorithm has higher accuracy and less complexity, and the generalization effect is better than the traditional method based on visible spectrogram. The recognition accuracy is up to 90%. The recognition accuracy of SIFT+SVM, PHOG+SVM and GIST+SVM are 70.83%, 77.08% and 79.16% respectively. The proposed method provides a theoretical basis and effective technical means for the realization of automatic and accurate detection of rice quality in modern agricultural production. Therefore, this study has certain theoretical value and practical significance for the realization of artificial intelligence detection of rice quality.
		2020 Vol. 40 (01): 233-238 [Abstract] ( 226 ) RICH HTML PDF (2158 KB) ( 127 )

	239	Grass Biomass Inversion Based on Landsat 8 Spectral Derived Data Classification System
		ZHANG Ai-wu^{1, 2}, ZHANG Shuai^{1, 2}, GUO Chao-fan^{1, 2*}, LIU Lu-lu^{1, 2}, HU Shao-xing³, CHAI Sha-tuo⁴
		DOI: 10.3964/j.issn.1000-0593(2020)01-0239-08
		Estimation of forage biomass is of great significance for the rational use of grassland resources and monitoring of livestock load balance, and it is a key indicator for evaluating the sustainable development of grassland ecosystems and grassland resources. The rapid and non-destructive study of large-area vegetation biomass estimation based on Landsat remote sensing technology has been widely used. Most of the current researches are based on single variable or several commonly used vegetation indices to construct inversion models. These indices often cannot reflect the physical and chemical characteristics of vegetation inmany aspects. In this paper, the classification systems of different Landsat8-derived data were constructed by their corresponding physicochemical characteristics of vegetation andintersectional pattern with plants. A multivariable nonlinear biomass estimation model based on stochastic gradient boosting algorithm was proposed and the model estimation results were discussed with different combinations of derived data categories. The program feasibility study was carried out with Haiyan County in Qinghai Province as the study area. The results showed that the Landsat8-derived data reflected the physical and chemical characteristics of vegetation mainly from the aspects of vegetation greenness, yellowness, coverage, moisture content, texture characteristics and elimination of atmospheric disturbance and soil background interference(7 subcategories). On the other hand, these data can also be summarized into three categories: direct factors (greenness, yellowness, coverage, moisture content), indirect factors (eliminating atmospheric interference and eliminating soil background interference), and spatial factors (texture characteristics). The derived data categories have obvious complementarity. The direct factor (GNDVI，TCW，NDTI，NDSVI，TCD)-indirect factor (SAVI，VARI)-space factor(Mean_B3，Mean_B6，Hom_Ⅱ，Dis_B5) model had the best estimation accuracy, and R² reached 0.88; the RMSE was 141.00 g·m^-2, however the single direct factor model estimates result was the worst. Compared with the results of six typical biomass estimation models, the proposed method had obvious advantages. Compared with the univariate models, R² increased by 42%～60%, RMSE decreased by more than 47%, R²_cv increased by 31%～53%, and RMSE_cv decreased by more than 29%; Compared with the multivariate models, R² increased by 29%～42%, RMSE decreased by more than 35%; and R²_cv increased by 2%～18%, RMSEcv decreased by more than 2%. In addition, the proposed model also had some effect in eliminatingoversaturation problem. In summary, this paper uses Landsat8 data to construct an inversion model from the perspective of reflecting different physical and chemical characteristics of vegetation to achieve accurate estimation of forage biomass, which has important guiding significance for the real-time monitoring of pastage growth and the sustainable use and management of grassland resources. The research results can also provide reference and reference for future large-area regional grassland dynamic monitoring and other agricultural research.
		2020 Vol. 40 (01): 239-246 [Abstract] ( 208 ) RICH HTML PDF (2918 KB) ( 65 )

	247	Identification of Sodium Ion Spectral Characteristics of Halophytes Based on Parameter Optimized SVM Method
		DENG Lai-fei^{1, 2}, ZHANG Fei^{1, 2, 3*}, QI Ya-xiao^{1, 2}, YUAN Jie^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2020)01-0247-08
		There are a wide range of saline soils in Xinjiang. It covers a large area. Various types of halophytes which have prominent significance for improving the saline lands, maintaining ecological stability and promoting ecological balance grow on these saline soils. Studies have shown that many halophytes absorb a large amount of sodium. Both sodium and potassium can increase the cell osmotic pressure to adapt to the high-salt condition, producing turgor pressure and promoting cell elongation. So it is beneficial to its growth and can partially replace the function of potassium. Thus, mastering the sodium characteristics of halophytes is helpful to understand the long-term adaptation and response of halophytes to the ecological environment. In this paper, HyperSpectral technique was used to effectively explore the characteristics of leaf sodium. Firstly, the discrete wavelet transform (DWT) and db5 wavelet were used to decompose the original spectral in 9 layers, and the optimal decomposition layer is 5 layers. Secondly, the original spectral were decomposed by db5 wavelet in 5 layers, and the wavelet vegetation indices were created by the decomposed high-frequency components and low-frequency components. We selected the wavelet vegetation indices which could sensitively characterize sodium ion content of halophytes. Finally, the SVR, LS-SVR, PSO-SVR and PSO-LS-SVR models were used to estimate the sodium ion content of halophytes vegetation. The results were compared to the models created by the spectral vegetation indices of original spectral. In addition, we used the partial least squares regression model as a comparison to evaluate the advantages of the parameter-optimized support vector machine method in estimating the sodium ion content of the leaves of the halophytes vegetation using hyperspectral techniques. The results showed that: (1) The prediction results of the five models showed that PSO can effectively optimize the parameters (c, g) of SVR and LS-SVR models, and improve the accuracy and prediction ability of the models. The optimized models had the advantages of high prediction accuracy, strong generalization ability and good robustness performance. (2) The model constructed by the multiple wavelet index was an inversion model of integrated multi-scale and multi-resolution data, which can reflect the vegetation information from different aspects. Therefore, the four models constructed by the multiple wavelet index were superior to the models constructed by the single wavelet index. (3) Contrasting the inversion results of two types index, the Na⁺ content prediction model constructed by a single wavelet vegetation index can achieve a better prediction results. The single spectral index is not effective in estimating Na⁺ content, which is because the wavelet transform can reduce the noise of the original spectral and highlight the detailed feature of the spectral, improving the prediction results. The model accuracy and prediction effect of the integrated wavelet vegetation index were better than those of the integrated spectral index. More spectral subtle feature can be highlighted by wavelet transform, thus improving the ability of retrieving Na⁺ content in leaves by HyperSpectral method.
		2020 Vol. 40 (01): 247-254 [Abstract] ( 213 ) RICH HTML PDF (4390 KB) ( 64 )

	255	On-Line Plasma Spectrum Detection of Laser Cleaning of Aluminum Alloy Before Welding
		TONG Yan-qun¹, LU Qin-hui¹, ZHOU Jian-zhong¹, YAO Hong-bing¹, YE Yun-xia², REN Xu-dong^1*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0255-06
		The technology of aluminum alloy welding is widely used in industrial production, manufacturing and maintenance. Porosity in welding seam leads to the decrease of welding quality, which is a common problem in aluminum alloy welding technology. The metal oxide on the surface of aluminum alloy is the main source of pore formation, therefore, on-line detection of laser cleaning process can analyze the cleaning status of surface oxides in real time and avoid damage or secondary oxidation of matrix surface caused by excessive cleaning at the same time. In this paper, laser-induced breakdown spectroscopy (LIBS) was used to detect the laser cleaning process of aluminum alloy before welding and to characterize the surface state of aluminum alloy after cleaning. LIBS technology can simultaneously detect multi-element components, with a lower detection limit and higher accuracy. In this paper, an on-line detection system for laser cleaning of aluminum alloy before welding based on AdorMechelle 5000 spectrometer was built, eliminated the influence of air environment on the experimental results, the LIBS spectra of 6061 aluminum alloy surface oxide and aluminum alloy matrix were measured, analyzed their elemental characteristic spectra, verified the accuracy of elemental characteristic spectra by using EDS test results, and explored the feasibility of LIBS technology in on-line detection of laser cleaning process. The relationship between spectral line intensity of plasma and laser energy density was tested experimentally. The damage threshold of single pulse laser for removing oxide on aluminum alloy surface was obtained. The cause and effect of laser damage threshold were researched by combining the results of X-ray energy spectrum. The relationship between the characteristic spectral lines of plasma spectra and the number of pulses in laser cleaning process was researched. Based on the intensity ratio of O/Al characteristic spectral lines, a criterion for on-line detection of cleaning effect and secondary oxidation damage was proposed. To verify the accuracy of the criterion, the trend of the intensity ratio of O/Al characteristic lines with cleaning times was compared with that of oxygen atom percentage obtained by X-ray energy spectra. The experimental results showed that the influence of air atmosphere can be eliminated by analyzing the laser cleaning state with the spectral characteristics of laser-induced plasma in the range of 200～700 nm; The characteristic spectra of oxygen and aluminum elements accurately reflect the composition difference between the oxide film on the surface and the aluminum alloy substrate; The element composition and content detected by X-ray energy spectrum showed that the oxygen content first decreased and then increased with the laser cleaning energy density, and the laser energy threshold of secondary oxidation damage of single cleaning aluminum alloy is 11.46 J·cm^-2. The laser energy density less than the damage threshold does not cause damage to the aluminum alloy matrix after multiple cleaning, and the intensity of plasma spectral characteristic lines is correlated with surface states; The ratio of 656.5 nm (O Ⅱ)/396.2 nm (Al Ⅰ) spectral line intensity (≤1.5%) is the criterion of laser cleaning. The research results are beneficial to the real-time control technology of laser cleaning of aluminum alloy and the integration of welding devices.
		2020 Vol. 40 (01): 255-260 [Abstract] ( 202 ) RICH HTML PDF (2866 KB) ( 63 )

	261	Investigation on Resonance and Non-Resonance Doublet Based Self-Absorption-Free LIBS Technique
		HOU Jia-jia¹, ZHANG Lei^{1, 2}, ZHAO Yang¹, YIN Wang-bao^{1, 2}, DONG Lei^{1, 2}, MA Wei-guang^{1, 2}, XIAO Lian-tuan^{1, 2}, JIA Suo-tang^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2020)01-0261-05
		The self-absorption effect in quantitative analysis of LIBS not only reduces the spectral line intensity and increases its width, but also causes saturation effects in calibration, thus affecting the analytical accuracy. A resonance and non-resonance doublet based self-absorption-free laser-induced breakdown spectroscopy (SAF-LIBS) technique is proposed to eliminate its influence. The optically thin time is obtained by matching the measured lines intensity ratios with the theoretical one, and the applicable measurement range is expanded by utilizing the resonance and non-resonance lines. This technique can be divided into two analytical processes: calibration and quantification. The calibration process is: calculating the theoretical intensity ratio of the resonant doublet and non-resonant doublet of the element, and the optically thin time of plasma can be determined by matching these ratios with the measured values at different delay times. Using a series of standard samples to establish a univariate calibration curve of non-resonance line by conventional LIBS and using quasi-optically thin spectra to establish the univariate multi-segment calibration curve of resonance and non-resonance lines by SAF-LIBS. For quantitative measurements, the segment to which the unknown sample belongs is determined firstly by using the conventional LIBS calibration curve, and then the SAF-LIBS spectra and the resonance or non-resonance calibration curve that corresponds to the predetermined segment are used for implementing the quantitative analysis. The calibration results for Cu showed that the optimal delay time increased with the increase of the Cu content, and the resonance lines could be considered as quasi-optically thin only for Cu content no larger than 0.05%. With the increase of element content, the self-absorption effect became so serious that it was impossible to acquire any optically thin spectra. The non-resonance lines could be considered as quasi-optically thin over a wide content range of 0.01%~30%. However, when the content was larger than 50.7%, the optically thin lines could never be captured during the lifetime of plasma. The quantitative analysis of Cu showed that the resonance and non-resonance doublet based SAF-LIBS can effectively avoid the self-absorption effect. The linearity of each segment calibration curve is greater than 0.99, the absolute errors of two unknown samples are 0.01% and 0.1%, respectively, the limit of detection is 1.35×10^-4%, and the maximum measurable range is extended to 50.7%.
		2020 Vol. 40 (01): 261-265 [Abstract] ( 206 ) RICH HTML PDF (2520 KB) ( 55 )

	266	A LIBS Spectral Self-Absorption Correction Method Using Voigt Profile Fitting for the Application of Magnesium Analysis in Phosphorus Ore
		ZHANG Peng^{1, 2, 3, 4}, SUN Lan-xiang^{1, 2, 3*}, YU Hai-bin^{1, 2, 3}, QI Li-feng^{1, 2, 3}, ZENG Peng^{1, 2, 3}
		DOI: 10.3964/j.issn.1000-0593(2020)01-0266-05
		The concentration of MgO is one of the most important parameters in the phosphate ore flotation. The fast detection of the concentration of MgO has great significance for the optimization of the flotation, the improvement of the efficiency and the reduction of the cost. Therefore, LIBS (Laser Induced Breakdown Spectroscopy) is introduced into the analysis of Mg in phosphate. But the common used strong lines of Mg (Mg Ⅱ 279.6 nm, Mg Ⅱ 280.3 nm, Mg Ⅰ 285.2 nm) are resonance lines in LIBS analysis. For the effect of the self-absorption, the spectral intensity of the resonance line is lower than the theoretical value, and this intensity reduction will reduce the accuracy of the analysis. In this work, a method based on an approximate function of Voigt profile was proposed. Firstly, simplified the Voigt profile function with the approximate function; secondly, determined the center of the spectral line and the full width at half maximum (FWHM) under ideal conditions with the low concentration samples; then, determined the wing area for fitting by calculating the slope of the spectral area near the spectral peak; finally, obtained the fitting profile closer to the theoretical one, by fitting the approximate function with the wing area selected above. In the application of the quantitative analysis of Mg in phosphate ore, the internal standard method was used forthe calibration. The fitting spectral areas of Mg Ⅰ 285.2 nm and Si Ⅰ 288.2 nm were chosen as the analytical line intensity and the reference line intensity, respectively. Comparing the internal standard method without fitting, the determination coefficient (R²) with the proposed method was improved from 0.923 to 0.998; the root-mean-square error (RMSE) and the average relative error (ARE) were reduced from 0.96 and 38.65% to 0.16 and 2.79%, respectively. The calibration results proved that with the proposed method, the measurement accuracy can be improved significantly for the application of magnesium analysis in phosphorus ore.
		2020 Vol. 40 (01): 266-270 [Abstract] ( 242 ) RICH HTML PDF (2815 KB) ( 73 )

	271	Ca and Mg Analysis in Solution by Solution Cathode Glow Discharge Combined with Standard Addition Method and Background Removal
		ZHENG Pei-chao¹, HE Miao¹, WANG Jin-mei^1*, WANG Ning-shen¹, LI Wei-qi¹, LUO Yuan-jiang¹, DONG Da-ming², ZHENG Kun-peng¹, YAN Bo-wen¹
		DOI: 10.3964/j.issn.1000-0593(2020)01-0271-06
		Solution cathode glow discharge atmosphere emission spectrometry (SCGD-AES) is affected by the matrix effect in aqueous solution. Moreover, actual water contains many elements and the components are relatively complex, which makes matrix effect more serious and leads to a decrease in accuracy of metal element concentration prediction. In order to reduce matrix effect of aqueous solution in SCGD-AES, quantitative analysis methods are often used to analyze metal elements. Among these methods, standard addition method is especially suitable for the situation that matrix effect or interfering substance is relatively significant. However, standard addition method is vulnerable to background interference, resulting in the error of results. Therefore, the background interference must be eliminated before standard addition method is carried out. The simplest method to eliminate the interference is off-peak correction method, which deduces the background intensity value measured at the left and right of the linear peak, so as to eliminate the background interference. Wavelet transform method is also applicable to eliminate background interference and it is universal. This method is applied to multi-scale stratification of wavelet, and then the low-frequency coefficient of wavelet is processed to obtain the corrected data. Here, Ca and Mg content in solution were predicted by off-peak correction and wavelet transform method based on standard addition method in a homemade SCGD- AES system. For the traditional standard addition method, the relative error of the Ca samples with concentrations of 5, 10 and 20 mg·L^-1 were measured as 157.0%, 105.1% and 47.0%, respectively. The REs of Mg in the three groups of samples were 20.1%, 3.1% and 2.8%, respectively. However, when the standard addition method and off-peak correction were combined, REs of Ca were reduced to 15.4%, -8.8% and 3.3%, and REs of Mg were reduced to 14.5%, 0.1% and 0.8%, respectively. When standard addition method by wavelet transform to eliminate background interference was employed, REs of Ca decreased to 13.2%, -7.6% and -1.4% respectively, and REs of Mg decreased to 13.4%, -0.4% and 0.5% respectively. The experimental results show that the accuracy of Ca and Mg measurement is significantly improved by off-peak and wavelet transform method. The two methods can effectively eliminate background interference, reduce matrix effect and improve the prediction accuracy. The wavelet transform combined with standard addition method can be used for various background correction occasions, without selecting appropriate background correction points, and the prediction accuracy is higher, which has advantages compared with off-peak correction method.
		2020 Vol. 40 (01): 271-276 [Abstract] ( 202 ) RICH HTML PDF (1990 KB) ( 65 )

	277	The Improvement of Signal-to-Back Ratio in Polarization Resolved Laser-Induced Breakdown Spectroscopy of Al-Fe Alloy
		CHENG De-wei, LU Jing-qi^*, JIA Xin-ting, WU Zi-jun, HUANG Jian
		DOI: 10.3964/j.issn.1000-0593(2020)01-0277-07
		Polarization-resolved laser-induced breakdown spectroscopy (PRLIBS) has important significance in reducing the detection limit of LIBS with its advantage of background suppressing. However, the controversy in theory of polarization and the unstable improvement of the signal-to-back ratio limit its application prospects. In order to investigate the theory of polarization characteristics and the improvement of the signal-to-back ratio, this study used 1 064 nm nanosecond pulsed laser and fiber optic spectrometer to conduct an exploratory experiment on the improvement of polarization-resolved LIBS signal-to-back ratio and polarization mechanism of aluminum-iron alloy samples. According to estimation of the energy of bremsstrahlung radiation, it’s confirmed that proportion of bremsstrahlung radiation in background reduces with time. By varying the energy density, detection angle, analyzer angle, delay, integration time and other factors, the spectral intensity and wavelength data were collected, and polarization degree and the signal-to-background ratio were calculated. It was observed that the background and the discrete spectrum of the plasma spectrum of the aluminum-iron alloy was partial polarized. There were phenomena of polarization of spectrum and there were differences in polarization degree and directions of polarization. It was found that the effect of polarized LIBS to improve the signal-to-back ratio is related to experimental parameters including energy density, delay time, detection angle and wavelength: signal-to-back ratio of PRLIBS varies with respect to energy density similar to that of LIBS. SBR becomes low and flat when the energy density is large. The analyzer angle affects the SBR, which is related to the polarization direction and degree of polarization of the spectrum. The formula for improvement about the polarization degree, the angle of detection and the polarization direction is derived. The polarization degree of continuum is flat at all wavelengths and polarization degree of the discrete spectrum decreases as the spectral intensity increases. Though not obvious, the polarization degree changes with the delay increasing. The reason is that the amount of change in the delay time is too little compared to the integration time. The trend of the signal-to-back ratio is consistent with non-polarized LIBS. The representative explanations of the PRLIBS mechanism at home and abroad are summarized and discussed. It’s proved that laser field, Fresnel reflection effect, anisotropic electron velocity distribution and other factors play an inconclusive role in the polarization properties of the plasma. The conclusion is that in the ns-LIBS experiment, most of the background in the visible and ultraviolet spectrum comes from the recombination radiation. The polarization characteristics are mainly due to the anisotropic recombining process during the recombination stage of plasma. During this process, the number of magnetic sublevel of the excited atoms is imbalanced, and the difference between the polarization degree and direction of the background and the atomic spectrum mainly depends on the mechanism of polarization. Studies have shown that PRLIBS does not always improve the signal-to-back ratio of elements, especially for weak discrete spectrum. When the energy densities, analyzer angle, delay and integration time of PRLIBS are controlled, a better background effect can be obtained. With the energy density of 20 J·cm^-2 and the integration time at 30 μs, the SBR at Fe 407.12 nm increased from 4.86 to 12.97. It was found out that polarization degree is less correlated with the variable detection angle, for which the reason is probably that the Fresnel reflection effect of the conductor is too weak. The research results provided an effective theoretical basis for the research and application of PRLIBS.
		2020 Vol. 40 (01): 277-283 [Abstract] ( 189 ) RICH HTML PDF (2744 KB) ( 70 )

	284	Wood Quality of Chinese Zither Panels Based on Convolutional Neural Network and Near-Infrared Spectroscopy
		MENG Shi-yu¹, HUANG Ying-lai^1*, ZHAO Peng¹, LI Chao¹, LIU Zhen-bo², LIU Yi-xing², XU Yan³
		DOI: 10.3964/j.issn.1000-0593(2020)01-0284-06
		Currently, the instrument production industry relies mainly on the subjective judgment of instrumental technicians when selecting the wood for Chinese zither panels. However, this method lacks a summary of scientific theories and is inefficient, which limits the objectivity of the selection and the improvement of the yield. Moreover, the current model for judging the wood grade cannot satisfy the large demand of the musical instrument market. Therefore, achieving rapid and intelligent grading of wood for Chinese zither panels is an urgent problem to be solved. Near-infrared spectroscopy contains information about the molecular structure of an object and is very suitable for measuring organic substances containing hydrogen. The chemical bonds of the main chemical components of wood used in Chinese zither panels are composed of hydrogen-containing groups, and the chemical compositions of the panels of different grades are different. These differences are reflected in near-infrared spectral data by light, which makes it possible to judge the wood grade. Simultaneously, convolutional neural network (CNN) has a strong feature extraction ability for nonlinear data. Therefore, this paper proposes a method to analyze the spectral data by using the CNN model to determine the wood grade. In the experiment, this paper applied two spectral preprocessing methods, like the Savitzky Golay first-derivative and second-derivative preprocessing methods, and two data compression methods, like kernel principal component analysis (KPCA) and successive projections algorithm. Through the CNN model designed in the paper, the optimal preprocessing and data compression methods were selected by using the classification accuracy rate of samples and the loss value in the model construction process as the judgment indicators. In order to improve the ability of the experimental model to extract and analyze spectral data and avoid overfitting, this experiment applied multi-channel convolution kernel, batch normalization and early stopping strategies. Finally, the feature information extracted by the two convolution layers was sent into the fully connected layers to extract other residual features, and the prediction grade of the panel was obtained using the softmax function. Thus, the final experimental model was determined. Finally, Savitzky Golay first-derivative and KPCA were the optimal data processing methods. At the same time, the main key bands for distinguishing different wood grades were obtained, which were 1 163~1 243 and 1 346~1 375 and 1 525~1 584 nm, respectively. Applying the proposed model to the test set samples, the grade classification accuracy of the wood for Chinese zither panels was 95.5%. Experimental results revealed that the proposed method can efficiently process spectral data and identify the key features of different grades of wood for Chinese zither panels. Therefore, it can provide specific technical support for the broad instrument market.
		2020 Vol. 40 (01): 284-289 [Abstract] ( 210 ) RICH HTML PDF (2321 KB) ( 131 )

	290	Spectral Analysis of Host Galaxy from Possible Dual AGNs
		WANG Meng-xin^1，2, LUO A-li^1，2
		DOI: 10.3964/j.issn.1000-0593(2020)01-0290-04
		The merger of massive galaxies can also invoke a series of phenomena such as the starburst and SMBH activities, besides galaxies pairing and dual AGNs. When two galaxies merger to kiloparsec (kpc) scale and begin to co-rotate with each other, and the adjacent narrow line regions are sensed by a single spectrograph slit or fiber, double-peaked emission lines would appear in the integrated spectra. In this paper, starting from this observation characteristic, we systematically search for dual AGN candidates whose spectra display double-peaked narrow emission line features in the Data Release 4 of LAMOST survey (LAMOST DR4). The profiles of emission lines of AGN spectra are composed of several different dynamic components, which can be divided into three types including narrow line components (Hβ, [OⅢ], Hα and [NⅡ]), wings of [OⅢ] lines, and broad Balmer emission lines. Based on LAMOST DR4 extragalactic spectra, we apply a set of search process, after the initial screening (involving the signal-to-noise ratio, the equivalent width and redshift cuts) and visual check and selection, we establish a sample with double-peaked narrow emission lines, which meets with our criteria of fluxes, full-width-half-maximum and velocity gap between two narrow components in their multi-gaussians fitting. Based on the Baldwin-Phillips-Terlevich (BPT) diagnosis, we finally detect 28 dual AGN candidates. In order to obtain more accurate and find the common characteristics of this kind of dual AGN candidates, we re-correct the spectral flux of these 28 objects with a low-order polynomial and combine them with the traditional interpolation and median method to obtain a high signal-to-noise ratio spectrum. We also take a composite spectra constructed from single type Ⅱ AGNs in LAMOST DR4 as the control sample. The software STARLIGHT is carried out to fit these two spectra, and the contributions of stars of different ages and metallicities are quantified for more direct comprehension. We find that dual AGN candidates will host more contributions from the middle age and the old populations than the single AGN composite, indicating a more intense central black hole activity. As for the metallicity effects, the dominant stellar population of single AGN is the population with solar metallicity Z_⊙, while the spectra from dual AGN candidates show a significant contribution from populations with metallicities 0.2 Z_⊙ and 2.5 Z_⊙, showing a heterogeneous feature and revealing a more complicated star formation history encodes in these possible dual AGNs than it exists in corresponding regular sample. A power-law is considered when we conduct the fitting, and the contributions of this featureless continuum component in single AGN account for 8.2%, which is significantly higher than that in the dual AGN candidates.
		2020 Vol. 40 (01): 290-293 [Abstract] ( 200 ) RICH HTML PDF (2183 KB) ( 119 )

	294	Optical Properties of Perovskite Films Fabricated by Vacuum Flash Method
		ZHANG Chun-mei, WANG Dong-dong, ZHANG Ao, LI Mi-dan, WU Wei-xia, SUN Lu, GUAN Hao-tian, ZHANG Zhi-peng, LANG Wen-jun, MENG Tao^*
		DOI: 10.3964/j.issn.1000-0593(2020)01-0294-04
		In recent years, thin film solar cells with perovskite materials as light absorbers have attracted increased attention. The power conversion efficiencies (PCE) of organic lead-halide perovskite solar cells have reached 23% in ten years, resulting from perovskite absorber material with high absorption coefficient, suitable and adjustable bandgap, long carrier diffusion length. In 2016, GrtzelL introduced a simple vacuum-flash solution processing method (VFSP) to obtain FA and MA mixed perovskite film with high quality. Compared with other traditional solution processing methods, VFSP paved the way to realize high-PCE and large-area perovskite solar cells. In this work, the perovsikte films were fabricated by VFSP, and scanning electron microscopy (SEM), X-ray diffraction (XRD), absorption and photoluminescence spectra were used to investigate the morphology, structure and optical properties. The results showed that this method can be used to prepared uniform and pinhole-free perovskite films with FA-, Br and Cl-doping, including (FAPbI₃)_0.85(MAPbBr₃)_0.15, MAPbI₃ and MAPb(I_xCl_1-x)₃. The crystal grain sizes were 500, 100 and 200 nm, respectively. The growing process of the film was that the intermediate-phase was formed during the vacuum-flash process, and then turned into perovskite phase after annealing. The films had strong absorption in the visible region, and the absorption edges were about 750 nm. The optical absorption edge (Eg) values of the films with different compositions were about 1.6 eV. The PL intensity of the film with Cl-doping decreased and the peak showed a blue-shift compared to MAPbI₃ film, which might be caused by the increase of the grain size and the reduction of the defect density.
		2020 Vol. 40 (01): 294-297 [Abstract] ( 240 ) RICH HTML PDF (3108 KB) ( 127 )

	298	Analysis of Simulation Results of Orbit Observation of Stellar Occultation Technology
		SUN Ming-chen^{1, 2}, WU Xiao-cheng^1*, HU Xiong¹
		DOI: 10.3964/j.issn.1000-0593(2020)01-0298-07
		Stellar occultation is an effective means of measuring the trace components density, temperature, aerosol, etc. on the Earth and other planets using stellar spectra. Thedetection principle mainly shows different absorption characteristics in different positions of the stellar spectrum according to different atmosphericcomponents, and the specific performance is as follows: the ultraviolet band can measure ozone, oxygen, hydrogen, etc., the visible spectrum can detect nitrogen dioxide, nitrogen trioxide, oxygen, etc., and infrared can detect water vapor, aerosol, methane, carbon dioxide, oxygen and so on. The realization process of the stellar occultation is: when the LEO satellite and the stellars are located on both sides of the earth, the light emitted by the stellar passes through the absorption and scattering of the earth’s atmosphere, and is received by the LEO on the other side, which constitutes an occultation observation. According to the spectral flow, the magnitude range of stellars is obtained, and the distribution of stars in the celestial coordinate system and different spectral types are given, as well as the atmospheric components detectable by each spectral type. The stellar-LEO occultation orbit observation simulation is carried out using the relative positions of the stellars and LEO satellite in the ground-solid coordinate system. The basic process is: firstly, reading the orbital position of the LEO satellite and the position of the target stellar, setting the simulation time of 24 hours, and then judging whether it is in the occultation state. When the occultation starts, parameters of occulation, such as the latitude and longitude are calculated and output until the end of the simulation time, which involves the process of the stellar transformation from the celestial coordinate system to the ground-solid system and calculation of LEO satellite orbit, occultation point latitude and longitude, etc. Through calculation and analysis of the daily measurement, global distribution, duration, and drift velocity of the occultation event according to the simulation process, the following results are obtained: (1)The target stellars have a certain number of distributions in the whole sky zone. (2)During the 24-hour orbital simulation of the stellar occultation, the daily observation is 5 563 times, including 2 737 rising occultations and 2 826 descending occultations. (3)From the perspective of global distribution, occultation events are mainly distributed at low latitudes, with the least two poles, the other latitudes are equal, the longitude direction is evenly distributed. (4)According to the azimuthal distribution, the normal occultation ratio is 78.25%, the average duration is 1.5 minutes, and horizontal drift of the tangent point is between 18 and 600 km. (5)The side occultation is 21.75%, longer than the normal occultation, the horizontal drift speed of the tangent point is large, and the azimuth angle is also large. The above results provide theoretical guidance for satellite orbit design and detection of load design.
		2020 Vol. 40 (01): 298-304 [Abstract] ( 205 ) RICH HTML PDF (2897 KB) ( 66 )

	305	Study of Density Functional Theory on Surface Enhanced Raman Spectroscopy of Fipronil
		YI Zhen-fei¹, LIU Chun-yu^{1, 2*}, XIN Min-si¹, KUANG Shang-qi¹, ZHOU Cheng-cheng¹, YAO Zhi-hai^{1, 2}, CAI Hong-xing¹
		DOI: 10.3964/j.issn.1000-0593(2020)01-0305-05
		At the beginning of August 2017, Netherlands reported that a wide range of eggs were contaminated with the insecticide fipronil. In this study, the Raman spectroscopy was used to solve the problem of fipronil detection. The stable configuration and all vibration modes of the molecule were obtained after the geometrical structure optimization and frequency calculation, and the theoretical Raman Scattering spectroscopy of the stable configuration of fipronil was also calculated. Normal Raman spectroscopy and surface enhanced Raman spectroscopy of fipronil were collected by HORIBA’s T64000 grating confocal micro-Raman spectroscopy and Ag/Cu nano-substrate. The strong peaks appeared at 211, 308, 350, 867, 1 323, 1 432 cm^-1, and the sub-strong peak appeared at 254, 407, 443, 463, 511, 607, 646, 712, 800, 1 065, 1 639 cm^-1. The results show that the theoretically calculated vibration frequency agrees well with the experimental measurements at all strong peaks and most sub-strong peaks. The vibration modes corresponding to the frequencies of the fipronil molecule in the range of 200～2 000 cm^-1 were assigned. The six strong peaks arranged from small to large were judged to be 21H-22H torsional vibration, 10F-11F deformation vibration, 21H-22H out-of-plane torsional vibration, 15N-22H twisting vibration, 6C stretching vibration and 21H in-plane torsional vibration, benzene ring breathing vibration and stretching vibration of 9C, 7H-8H in-plane torsional vibration. It was found that the surface-enhanced Raman spectrum has a slight frequency shift with respect to the Raman spectrum. The peaks at 211, 867, 1400, and 1 432 cm^-1 in the surface-enhanced Raman spectroscopy were selectively enhanced. According to the selection rule of surface-enhanced Raman spectroscopy, it is interpreted as the atom corresponding to the relevant vibration peak and the surface of the silver substrate may be in a nearly vertical state and may be stick to the silver surface. In the next step, fipronil will be planned to be mixed into eggs, and the identification of fipronil in different concentrations in eggs will be carried out. The results of the study can provide a theoretical basis for the Raman spectroscopy of fipronil, which will promote the rapid detection and on-line detection of fipronil residues in food and agricultural products. Raman spectroscopy will be used as a supplement to conventional chemical detection methods.
		2020 Vol. 40 (01): 305-309 [Abstract] ( 236 ) RICH HTML PDF (1218 KB) ( 55 )

	310	Study on the Overlapping Characteristics of Fluorescence Signals of Machine Oil and Diesel Mixtures in Soil Based on Iterative Approximation Algorithm
		ZUO Zhao-lu^1,2,3, ZHAO Nan-jing^1,3*, MENG De-shuo^1,3, HUANG Yao^1,2,3, YIN Gao-fang^1,3, LIU Jian-guo^1,3
		DOI: 10.3964/j.issn.1000-0593(2020)01-0310-06
		Petroleum hydrocarbons such as machine oil and diesel are important components of soil pollution, and are of great significance for rapid and accurate detection of organic pollutants such as machine oil and diesel in soil. Laser-induced fluorescence (LIF) technology has the advantages of fast detection speed, high sensitivity and on-site detection. However, when detecting organic pollutants in soil, it faces serious problems such as overlapping fluorescence spectra. In order to study the overlapping characteristic of the fluorescence signals of the machine oil and diesel mixture in the soil, 10 soil samples containing different concentrations of machine oil and diesel mixture were prepared. By establishing the LIF experimental system, the fluorescence signals of different mixing concentrations of machine oil and diesel were obtained, and the inversion relationship between the mixed spectra of machine oil and diesel was established. The iterative approximation algorithm was used to calculate the fluorescence contribution rate of diesel and machine oil samples in soil fluorescence spectra. In the process of calculating the fluorescence contribution rate, the two methods of full spectrum and intercepted characteristic spectrum were compared. When linearly fitting with the machine oil sample concentration, the fitting coefficient R of the intercepted characteristic spectrum method was 0.989, and the average relative error was 3.38%, which was better than the full spectrum of 0.923, 8.79%. At the time of verification, the average relative error of multiple linear regressions was 10.11% compared with the multiple linear regression method, which prove that the intercepted characteristic spectroscopy method is still excellent. There was a good linear relationship between the fluorescence contribution rate of machine oil and diesel in soil and its own concentration, indicating that there is no chemical reaction after mixing machine oil and diesel in soil, and the overlapping characteristic of fluorescence signals in soil are linearly superimposed. The method is equally applicable to the separation of fluorescence spectra of other petroleum hydrocarbon mixtures in the soil. Through the research in this paper, the accuracy of qualitative and quantitative detection of petroleum hydrocarbon pollutants in soil by LIF technology was improved. It provided method support for rapid detection of petroleum hydrocarbons in the soil.
		2020 Vol. 40 (01): 310-315 [Abstract] ( 175 ) RICH HTML PDF (2084 KB) ( 50 )

	316	Study of the Retrieval and Adsorption Mechanism of Soil Heavy Metals Based on Spectral Absorption Characteristics
		WANG Hui-min^{1, 2}, TAN Kun^{1, 2, 3*}, WU Fu-yu^{1, 2}, CHEN Yu^{1, 2}, CHEN Li-han^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2020)01-0316-08
		Heavy metals are scarce in soil, and it is difficult to identify their obvious characteristics in the soil spectrum. The previous soil heavy metal estimation methods have mostly applied statistical methods to find the characteristic bands, which cannot accurately explain the retrieval mechanism. It is therefore difficult to establish a universal model for soil heavy metal estimation. In order to investigate the influence of soil heavy metals in visible and near-infrared spectroscopy and analyze the retrieval mechanism of soil heavy metals, it is necessary to study the absorption characteristics of iron/manganese oxides, organic matter, clay minerals, etc. In this study, 80 soil samples were collected from the experimental field at Xuzhou, China. The spectra of the soil samples were measured with an Analytical Spectral Devices (ASD) field spectrometer. The soil heavy metal contents (Cr, Cd, Cu, Pb, and Zn) were determined by inductively coupled plasma-mass spectrometry. The soil spectra were processed by continuum removal. The absorption peaks related to heavy metals were around 480, 1 780, and 2 200 nm, which can be mainly attributed to iron/manganese oxides, organic matter, and clay minerals in the soil. The four spectral absorption characteristic parameters of Depth₄₈₀, Depth_{1 780}, Depth_{2 200}, and Area_{2 200} were extracted at the positions of the absorption peaks. The variation trends of the parameters, along with the contents of the five heavy metals, were then analyzed. It was found that the four parameters were strongly correlated with the contents of the five heavy metals. Using a single variable to estimate the heavy metals, it was found that Depth₄₈₀ had a higher estimation accuracy for Cr and Pb, and Area_{2 200} and Depth_{1 780} had a higher estimation accuracy for Cd, Cu, and Zn. The four spectral absorption characteristic parameters were implemented as independent variables, and the regression coefficients were obtained by ordinary least squares, ridge regression, and support vector regression. The heavy metal estimation model using the four spectral absorption characteristic parameters was stronger and more stable than those using only a single parameter. The best R²_p (determination coefficient of prediction) values of the estimation models (Cr, Cd, Cu, Pb, and Zn) were 0.71, 0.84, 0.92, 0.80, and 0.89 respectively. The results suggest that Cr and Pb are easily adsorbed by iron/manganese oxides, while Cd, Cu, and Zn are more easily adsorbed by organic matter and clay minerals in this study area. The results of this study will provide a reference for researchers exploring the relationship between soil spectral characteristics and heavy metals.
		2020 Vol. 40 (01): 316-323 [Abstract] ( 265 ) RICH HTML PDF (2512 KB) ( 149 )

	324	Ambiguity of Polystyrene Aerosol Beads Properties Found with Mie Spectra Analysis
		Petrov D V^*, Zhuzhulina E A
		DOI: 10.3964/j.issn.1000-0593(2020)01-0324-04
		Broadband Mie scattering is used to determine the parameters of polystyrene aerosol beads in air, such as size and wavelength dependence of refractive index. This method consists in the selection of such parameters of the scattering object, which reproduce observed spectrum properties. That is why it is very sensitive and hence very precise. We found that there is an ambiguity of polystyrene aerosol beads properties, determined with this method. Different combinations of polystyrene particle size and its refractive index can give the same position of Mie resonances. This ambiguity leads to an increase in the error in determining the size and refractive index of the particle. The refined errors are calculated and the way of their reduction is indicated.
		2020 Vol. 40 (01): 324-327 [Abstract] ( 160 ) RICH HTML PDF (1256 KB) ( 66 )

	328	Examination of Polymeric Azomethine Compounds and Their Transition Metal Complexes by Using XRF and XRD Technique
		Ömer Söğüt^1*, Betül Demirezen Kara¹, Gökhan Apaydın², Erhan Cengiz³, Ayşe Kazancı⁴
		DOI: 10.3964/j.issn.1000-0593(2020)01-0328-05
		In this study, the electronic transition properties and structural analysis of the metal complexes (Ni(Ⅱ), Co(Ⅱ), Cu(Ⅱ) and Mn(Ⅱ)) of three different polymer ligands were performed by using XRF and X-ray diffraction (XRD) techniques, respectively. The structural analysis of the polymers and their complexes were performed by XRD technique and some of the polymers were found to be in the face-centred cubic (fcc) structure. In addition, the values of the present K X-ray intensity ratios are significantly greater than the values reported in literature.
		2020 Vol. 40 (01): 328-332 [Abstract] ( 179 ) RICH HTML PDF (1550 KB) ( 89 )

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