SPECTROSCOPY AND SPECTRAL ANALYSIS

News

Forgot your password?

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

Journal Online

Archive

Links

	CAST

	CNCOS

	CNKI

	WanfangDATA

	CHEMSOC

	sinospectroscopy

	CPS

Quick Search

Adv Search

2020 Vol. 40, No. 08 Published: 2020-08-01

	2325	Investigation on the Multiwavelength Laser Operation and Polarization Characteristics of Er∶YAP Crystal
		QUAN Cong^{1, 2}, SUN Dun-lu^1*, LUO Jian-qiao¹, ZHANG Hui-li^1,3, FANG Zhong-qing^{1, 2}, ZHAO Xu-yao^{1, 2}, HU Lun-zhen^{1, 2}, HAN Zhi-yuan^{1, 2}, CHENG Mao-jie¹，YIN Shao-tang¹
		DOI: 10.3964/j.issn.1000-0593(2020)08-2325-07
		In this paper, the polarization absorption and output characteristics and the multi-wavelength laser operation characteristics of 10 at.% Er∶YAP crystal are studied. The polarization absorption spectra of Er∶YAP crystal is measured for the first time, the result indicated that the maximum absorption coefficients of crystal to linearly polarized light parallel to axis a and axis c in the absorption peak corresponding to the ⁴I_11/2 energy level are 4.606 3 cm^-1(at 975.2 nm) and 2.936 6 cm^-1 (at 967.6 nm), respectively. Therefore, the absorption efficiency of Er∶YAP crystal to pump light can be improved by choosing linearly polarized pump light with properly wavelength, which is conducive to improving the laser performance. In the xenon lamp pumped laser expeiments, four spectral lines of 2 710, 2 728, 2 795 and 2 918 nm are realized laser output under the free operation condition, the polarization and threshold characteristics of each spectral line are studied respectively. The laser output of single wavelength of 2 918 nm, four spectral lines of 2 710, 2 821, 2 837, 2 862 nm and single wavelength of 2 710 nm are achieved by adding JGS quartz plate, mica plate and K9 lens selective absorber respectively in the resonator cavity. The laser spectra are measured under the conditions of free operation and different selective absorbers, As well by contrasting with the transmittance spectra of different selective absorbers and the previously reported fluorescence spectra, it is proved that the oscillation is starting spectrum lines in Er∶YAP crystal could be selected by adjusting the resonator cavity. The experimental results show that the polarization direction of 2 918 nm spectral line is parallel to axis c and the polarization direction of 2728 nm spectral line sometimes parallel to the axis c and sometimes parallel to the axis a, besides, the polarization direction of all other spectral lines like 2 710, 2 795, 2 821, 2 837 and 2 862 nm are parallel to the axis c. The four laser spectral lines of 2 710, 2 728, 2 750 and 2 795 nm are obtained under LD end-pumping condition, in which the spectral line of 2 750 nm is realized laser output in Er∶YAP crystal for the first time. All these four spectral lines are linearly polarized light with polarization direction parallel to the c axis of the crystal. In addition, the absorption spectrum of Er∶YAP crystal is measured in 8 K low temperature, the spectrum was peak fitted by Gauss function, according to the fitting results the stark level of the upper and lower level are identified. And combining the laser spectra and fluorescence spectra, the possible laser spectral line transitions are also recognized. In this paper, the research of the Er∶YAP crystal polarization characteristics and multi-wavelength laser operating characteristics have instructive significance for the realization of Er∶YAP crystal Q-switching technique and the selection of electro-optic Q-switching crystal.
		2020 Vol. 40 (08): 2325-2331 [Abstract] ( 265 ) RICH HTML PDF (3498 KB) ( 126 )

	2332	Temporal Variation Model of Ultraviolet Hyperspectral Solar Reference Spectrum
		PEI Guo-chao^{1, 2}, LI Yuan^{3, 4*}, BAI Ting-zhu^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2020)08-2332-07
		The solar reference spectrum is the basis for radiometric calibration and wavelength calibration in the field of on-board calibration. During the solar cycle, the amplitude of the solar irradiance spectrum fluctuates periodically, changing by more than 10% in the ultraviolet band. However, the on-board absolute calibration requirement is 3%. Temporal variation characteristics of the sun cannot be ignored. First of all, we studied the influence of calculation of MgII when given spectra, which are based on interpolation and convolution intervals, with different resolutions and sampling. After selecting appropriate interpolation and convolution interval, we model the periodic variation of the solar-based on the MgII of Climate spectrum and SORCE spectrum. Secondly, we select 80 sets (there are two dates for every set) of amplitude variation of MgII and irradiance at a different wavelength from August 21, 2003, to April 15, 2012. By first order fitting instead of ratio method, the first order fitting method decreases error from 1.167% to 0.125% for Climate spectrum, from 1.057% to 0.558% for SORCE spectrum, when compared to true irradiance data from August 21, 2003, to April 15, 2012. The results show that the first-order fitting method has higher inversion precision and prediction accuracy than the ratio method. Finally, based on time series of MgII we fulfil normalization of time and format of the spectrum. By eliminating large deviated data over the different spectrum, we got a solar reference spectrum with the resolution of 1 nm and sampling of 0.1 nm on June 25, 2008. In addition, the spectrum has an absolute error of 0.982% compared to the average of six spectra without eliminating deviated data in all wavelength. The spectrum can also be converted to any day using solar cycle activity model based on MgII and conversion factor. By promotion of resolution and sampling for this reference spectrum based on KNMI hyperspectral, as a result, we get the solar reference spectrum with the spectrum range of 250~500 nm, resolution of 0.1 nm and sampling of 0.01 nm, which can provide reference spectrum for on-orbit observation and on-board calibration of China’s FY-3 ultraviolet hyperspectral ozone detector (OMS).
		2020 Vol. 40 (08): 2332-2338 [Abstract] ( 199 ) RICH HTML PDF (5017 KB) ( 76 )

	2339	Theoretical Analysis and Experiment of Raman Enhancement of Graphene-Ordered Silver Nanopores
		XING Hao-jian, YIN Zeng-he, ZHANG Jie^*, ZHU Yong
		DOI: 10.3964/j.issn.1000-0593(2020)08-2339-06
		We design a reusable graphene-ordered silver nanohole (GE-AgNHs) substrate. A uniform periodic nanopore array is etched on the silver film by surface plasmons (SPs) photolithography. Graphene is transferred to AgNHs by wet transfer method. Graphene not only provides a molecular adsorption platform, but also serves as a reference and calibration layer to improve surface-enhanced Raman reproducibility. When the silver film is exposed to the air, it is easily oxidized. The graphene covers the surface of the silver film to block the air, thereby slowing down the oxidation of the silver film. The substrate is characterized by optical microscopy, field emission scanning electron microscopy (SEM) and Raman spectroscopy. From the SEM characterization results, it can be seen that the silver nanopores are evenly distributed. Meanwhile, the electric field distribution (\|E\|) of different aperture bases is simulated by Finite-Difference Time-Domain (FDTD) simulation. The simulation results show that the electric field strength increases slightly with the decrease of the aperture. The maximum electric field strength E_max≈11 V·m^-1 is obtained at D=220 nm, and the enhancement factor is calculated to be ~1.46×10⁴. Many experiments were carried on. Firstly, we performed a Raman mapping test on the GE-AgNHs substrate. The results show that the RSD values of graphene D, G and 2D peaks are 18.3%, 22.1% and 19.8%, respectively, with good uniformity. Secondly, Raman test and quantitative analysis are carried on using crystal violet (CV) solution at concentrations of 10^-8~10^-4 mol·L^-1. The exponential fitting of the relative intensity k(k=I_{@1 178}/I_@2D) in the range of 10^-8~10^-4 mol·L^-1, the fitting degree R²=97.7%; if the data of 10^-4 mol·L^-1 is neglected, it performs a linear fit with a fit of 96.8%. Finally, SERS repeatability is performed on the GE-AgNHs substrate with a concentration of 10^-12 mol·L^-1 rhodamine 6G (R6G) solution as the probe molecule and sodium borohydride solution as the cleaning solution. It can be seen from the optical micrograph and the Raman spectrum that there is a small number of impurities on the GE before cleaning; after cleaning, a clean GE Raman signal is obtained. The Raman signal of R6G can be detected before and after cleaning, indicating that the substrate repeatability is good; the Raman intensity is maintained at 50% at 773 cm^-1.
		2020 Vol. 40 (08): 2339-2344 [Abstract] ( 194 ) RICH HTML PDF (4863 KB) ( 62 )

	2345	Influence of Photoacoustic Cell Geometrical Shape on the Performance of Photoacoustic Spectroscopy
		CHENG Gang¹, CAO Ya-nan¹, TIAN Xing¹, CAO Yuan², LIU Kun^2*
		DOI: 10.3964/j.issn.1000-0593(2020)08-2345-07
		With the rapid development of modern industry, the importance of trace gas detection technology is self-evident. At present, trace gas detection technology has been widely used in environmental protection, chemical industry, bio-ecological and medical detection and other fields. Photoacoustic spectroscopy (PAS) has become one of the most important analytical methods in spectroscopic detection due to its advantages of zero background detection, no wavelength limitation of detectors, simple optical elements, convenient system regulation and maintenance. In recent years, with the rapid development of weak signal detection and laser technology, photoacoustic spectroscopy has also attracted more attention of scholars. Relevant research results provide an important design reference for improving the detection performance of photoacoustic spectroscopy. However, the current literature report rarely involves the optimization of photoacoustic cells, such as the shape of photoacoustic cells. There is a lack of in-depth exploration on such problems as the shape structure. The photoacoustic cell is one of the most important core components in the photoacoustic spectroscopy detection system. It is the cavity for carrying the gas to be tested and the place where photoacoustic coupling occurs. Its shape greatly affects the relationship between light and sound. The coupling situation affects the signal-to-noise ratio and sensitivity of the whole system. Therefore, exploring the shape of the photoacoustic pool has important theoretical significance and engineering application value. Therefore, based on the design basis of the traditional cylindrical photoacoustic cell, this paper explores and studies the structural model of the photoacoustic cell with eight typical shapes such as circle, triangle, ellipse and so on, and simulates its sound field characteristics. 3D printing technology has produced all kinds of photoacoustic cells, and analyzed the performance indexes of 8 photoacoustic cells through experiments. The longitudinal length of the photoacoustic cell designed by the constraint is equal to the perimeter of the longitudinal section. The simulation results show that the longitudinal acoustic modes of the eight photoacoustic cells are the same. The experimental results show that the acoustic resonance frequencies of the eight photoacoustic cells are the same. The size is basically the same, and is affected by the coupling of the laser source and the acoustic mode in the cavity. Their quality factors are arranged from large to small: circular, short-axis ellipse, regular pentagon, square, large circular axis, and equilateral triangle. Small circle axis shape, long axis ellipse, their cell constants are arranged in order from large to small: circular, long axis ellipse, regular pentagon, square, large circular axis shape, small circular axis shape, regular triangle, short axis ellipse . The overall results show that for the design of the photoacoustic cell in photoacoustic spectroscopy, the shape of photoacoustic cell should be circular in priority without special requirements. The research process and results of this paper can provide a reference for the optimization design of the photoacoustic cell in photoacoustic spectroscopy.
		2020 Vol. 40 (08): 2345-2351 [Abstract] ( 227 ) RICH HTML PDF (3405 KB) ( 125 )

	2352	Kinect Sensor Moving for Low-Cost Mobile Phenotyping of 3D Plant Structures
		MENG Xiang-shuang, LIN Yi^*
		DOI: 10.3964/j.issn.1000-0593(2020)08-2352-06
		Phenotyping is important for understanding of the relationships between plant genotypes and environment. Developing efficient and low-cost phenotyping technologies is a typical demand in many fields such asprecision agriculture. As a representative RGB-D device, Kinect has been used for plant phenotyping, but its technical potential has not been fully explored. To address this gap, this study compared the three mainstream principles of Kinect characterizing three-dimensional structures, i.e., point clouds generated from depth images (DI), from the color images using the method of Structure from Motion (SfM), and from the data by merging the DI- and SfM-derived data (MD). The performance of the three methods was evaluated based on the reference data, which was measured by a FAROX330 laser scanner. The results after the analyses in the case of Hosta plantaginea showed that DI made the most accurate estimationsin terms of leaf areas, MD out performed DI and SfM when regarding the predictions of leaf circularities and eccentricities, and SfM had the best performance on the retrievals of leaf inclinations. The difference between the results of the three methods stems from their distinctive performance for different structures. For leaf area estimation,SfMcan characterize plant leaves in a relatively incomplete way, while the edges of the MD-recon structed leaves are not smooth, resulting in the lowness of accuracy for these two methods. For the geometric characteristics of leaves, MD point clouds generated by merging the related DI and SfM data can achieve the effect of information enhancement, making its performance better than DI and SFM point clouds. The leaf inclination angle is more sensitive to the accuracy of depth measurement. Due to Kinect depth measurement often with the errors, the accuracies of the DI and MD point cloud-based leaf inclination retrievals may be low. TheSfM point cloudsare only generated from the color images, and so this method canpresent the best performance on retrieval of leaf inclination angles. Performance comparison sindicated that the three methods have their advantages for different structural features.Their integration can help to improve the overall performance of Kinect for plant phenotyping and,eventually, forma new Kinect-based mobile phenotyping technique. In addition, the proposed leaf geometry delineation (LGD) model proved todraw the contours of leaves and restore the geometries of those partially occluded leaves. Overall, this study developed a novel Kinect-based low-cost but efficient mobile three-dimensional plant structure phenotyping technique, which is of implications for promoting crop monitoring and increasing agricultural production.
		2020 Vol. 40 (08): 2352-2357 [Abstract] ( 200 ) RICH HTML PDF (3326 KB) ( 51 )

	2358	Effect of Far-Infrared Ceramic Powder on the Interaction Between Essential Oil and BSA
		HUANG Fang¹, LIU Ming-xue^{1, 2*}, XIONG Jie¹, CHEN Lü-qi¹, GAO Zhu-xin¹, CHEN Hui-ming¹, WANG Dan-ni¹
		DOI: 10.3964/j.issn.1000-0593(2020)08-2358-08
		Essential oil and far-infrared ceramic powder(cFIR) are often used in physiotherapy or related health-care products, but the interaction and mechanism between them and biomolecules are less concerned. In this research, the influence and mechanism of cFIR on the interaction between rose essential oil(REO) and bovine serum albumin (BSA) were studied through different spectroscopy methods and infrared thermography under simulated physiological conditions. The results of the fluorescence spectrum show that both the REO and the cFIR can quench the intrinsic fluorescence of BSA. Whether the cFIR exists or not, the quenching mode of the REO to BSA is static quenching. The fitting calculation of Stern-Volmer equation shows that the binding sites n between BSA and REO is increased from 0.55 to 0.96 by adding cFIR, and the binding constant is also significantly increased, which shows that the affinity of REO to BSA can be improved with the existence of cFIR. The effects of cFIR and REO on the secondary structure of BSA were studied through synchronous fluorescence spectrum, three-dimensional fluorescence spectrum and Fourier transform infrared spectrum. The results show that they can cause the increase of hydrophobicity around the protein and have little effect on the conformation of BSA; in addition, cFIR and REO show the synergistic effect on the quenching of BSA intrinsic fluorescence through the formation of association compounds with BSA. Critical distance (R₀) and binding distance (r) were calculated based on Förster’s non-radiative energy transfer theory. The binding distance (r) between BSA and REO changes from 1.445 nm to 1.453 nm after the addition of cFIR, R₀ is basically unchanged and R₀ is less than r. These results suggest that whether the cFIR exists, the static quenching of BSA fluorescence by REO is accompanied by non-radiative energy transfer. The cFIR mainly improves the affinity of REO to BSA by changing the conformation of BSA due to different non-competitive binding sites between the cFIR and REO on BSA molecular surface. Infrared thermal imaging techniques was used to explore the interaction of REO and cFIR with macromolecules. Infrared thermal imaging results show that REO can reduce the temperature of biomolecules, while cFIR can increase the temperature of biomolecules. The addition of the cFIR can increase a response temperature of BSA-REO system, which indicates the thermal effect will increase (p<0.05). The above results show that the cFIR with nano-size effect and far-infrared radiation can affect the microenvironment of the system by forming association compounds when it interacts with REO, thus affect the fluorescence characteristics and energy transfer of biomolecules. The results of this study can provide a reference for further application of essential oil combined with cFIR in physiotherapy and mechanism research.
		2020 Vol. 40 (08): 2358-2365 [Abstract] ( 207 ) RICH HTML PDF (5013 KB) ( 62 )

	2366	A Study on Ground Deformations Monitoring in Tianshan Mountain of Xinjiang on Active Microwave Spectral Imagines
		WANG Zhi-wei^{1, 2, 3}, YUE Guang-yang^1*, WU Xiao-dong¹, ZHANG Wen², WANG Pu-chang², SONG Xue-lian², WU Jia-hai²
		DOI: 10.3964/j.issn.1000-0593(2020)08-2366-07
		As global warming, permafrost has degraded seriously. The ecological security of many regions has faced a serious threat to their ecological environment, especially the Tianshan mountain regions, which is one of the five major animal husbandry production bases. At present, in these regions, most studies focus on glacier analysis and few pieces of research about permafrost measure. According to 39 ENVISAT ASAR imagines, covered form 2003 June 17th to 2010 June 15th, surface deformation in permafrost region was monitored by SBAS-InSAR method. In this paper, the principles of deformation algorithm were introduced first. When generating the connection graph of the single look complex image of ASAR dataset, there was 126 differential interferogram based on 500 m and 550 days for temporal and spatial baseline respectively. Because of Spatio-temporal baselines and the Doppler centroid difference, 6 ASAR imagines were not generated the connection graph. Then using STRM V4 DEM, 52 low-quality pair of interferogram were eliminated, after the processes of interferograms flattening, adaptive filter, coherence generation and unwrapping. The ground deformation results of the study area were calculated by external ground control points, refinement and re-flattening, estimation of displacement velocity and residual deformation, coherence threshold control, SVD, spatially low-path filtering and temporally high-path filtering. There were 33 results of ground deformation, which covered from 2004 to 2010. According to the deformation results, there were different subsidence and uplift phenomenon in study areas. The deformation rate of the overall study area was no more than ±5 cm·yr^-1, and its average deformation rate was (-0.07±3.38) mm·yr^-1. It is indicating that there is a slight subsidence phenomenon in the study area. With the altitude of 3 000 m, the deformation changing mechanism were excavated for the plains and mountain areas distributed by seasonal frozen ground and permafrost respectively. From the research results, deformations in the plain region were uplift except for deformations in the area near cities were subsidence largely. In the mountainous region, the deformations were very scattered than them in the plain region. The overall trend of deformations of the mountain was dominated by subsidence, and subsidence and uplift in the western and eastern regions respectively. There were 15 198 deformation points, which altitude were more than 3 000 m. The annual variation mechanisms of temperature and precipitation about overall deformation points and different deformation intervals points were demonstrated by temperature and precipitation dataset. The results showed that both trends of them have a gradual warming phenomenon. The numbers of deformation rate points about different intervals were 6 364, 6 449 and 2 385 for rates lower than -2.0 cm·yr^-1, from -2.0 to 2.0 cm·yr^-1 and higher than 2.0 cm·yr^-1 in the study mountainous region respectively. Points with negative values were more than points with positive values in the mountainous region, which reflected that subsidence positions were more than uplift positions. This result was also consistent with that global warming cause permafrost degradation then ground subsided. In this paper, the ground deformation results of the study area were successfully calculated by ASAR dataset which was active microwave spectrum. Meanwhile, the deformation results were discussed and prospected in the respects of space, time and the time lag of the permafrost deformation. The study results could provide a new way and reference for the monitoring of permafrost deformation in the Tianshan mountain region.
		2020 Vol. 40 (08): 2366-2372 [Abstract] ( 174 ) RICH HTML PDF (5565 KB) ( 50 )

	2373	Progress in the Analysis of Elements in PM_2.5 by ICP-MS
		YUAN Xiao-xue, ZHOU Ding-you, LI Jie^, XU Xian-shun, YONG Li, HU Bin, LIU Tao^
		DOI: 10.3964/j.issn.1000-0593(2020)08-2373-09
		Atmospheric fine particles (PM_2.5), with small particle size and large specific surface area, are easy to adsorb pollutants such as metals, organic compounds, viruses, bacteria etc., and become carriers and reactants of toxic and harmful substances, which seriously affect air quality and have become the primary pollutants in the atmospheric environment. Metal and metalloid elements in PM_2.5 seriously pollute the natural environment because of their non-degradability and hysteresis. When PM_2.5 is inhaled into the human body, toxic and harmful metal and metalloid elements are deposited in the alveoli from the respiratory tract and then transferred to the blood and other organs. They can affect the normal physiological functions of the human body, resulting in a slow development of the body length, and even lead to cancer and other diseases, which seriously threaten human health. In recent years, many cities in China have also carried out corresponding studies on the pollution characteristics, distribution level and source analysis of metal elements in PM_2.5. For these reasons, the method of effectively collecting metal and metalloid elements in PM_2.5, the pretreatment method with high digestion efficiency and the detection method with simple, rapid, accurate, sensitive and strong anti-interference ability have become the research focus and hotspots in elemental analysis of PM_2.5. The analytical method based on inductively coupled plasma mass spectrometry (ICP-MS) can not only satisfy the simultaneous determination of multiple elements in PM_2.5 but also has a wide dynamic linear range, low detection limit and high sensitivity. Scholars have carried out a lot of studies and formed a relatively complete research system. This method can provide theoretical data support for the composition, origin, temporal and spatial distribution, morphological and corresponding isotopic analysis, physiological toxicity and transformation mechanism of metals and metalloids in PM_2.5. Therefore, the analytical methods for the determination of metal and metalloid elements in PM_2.5 by ICP-MS are reviewed in this paper. The selection of the sampling filter, the pretreatment method and the selection of the digestion solution are described in detail. The applications of several ICP-MS combined techniques in the speciation and isotope analysis of metal and metalloid elements in PM_2.5 are emphasized. The advantages and disadvantages of various sampling filters, pretreatment methods, digestion solutions and detection techniques are summarized, and the future challenges and research directions in this field are also proposed. This paper can provide theoretical reference for the further development of simple, rapid, sensitive and selective detection of metal and metalloid elements in PM_2.5 by ICP-MS.
		2020 Vol. 40 (08): 2373-2381 [Abstract] ( 162 ) RICH HTML PDF (918 KB) ( 101 )

	2382	Detection of Purple Rice Adulteration by Terahertz Time Domain Spectroscopy
		LIU Yan-de, DU Xiu-yang, LI Bin, ZHENG Yi-lei, HU Jun, LI Xiong, XU Jia
		DOI: 10.3964/j.issn.1000-0593(2020)08-2382-06
		Purple rice is a common ingredient in life and has rich nutritional value. Due to the high price of purple rice, the dyed purple rice has entered the market in large quantities. In this paper, terahertz time-domain spectroscopy combined with chemometric methods is used to explore the rapid detection method of purple rice adulteration. The spectral data of purple rice adulteration in the range of 0～7 THz was collected by Terahertz Time domain Spectroscopy (THz-TDS), and the absorption coefficient spectrum and refractive index spectrum of 0.5～2.5 THz band were selected for analysis and adopted. The chemometric method models and analyzes the spectral data. Savitzky-Golay convolution smoothing (SG smoothing), baseline correction (Baseline), normalization (Normalization), multiple scattering correction (MSC) and other methods are used for spectral preprocessing. Qualitative analysis of purple rice, purple rice mixed with rice and purple rice mixed with black rice was carried out by partial least squares decision analysis (PLS-DA). Qualitative analysis showed that there were significant differences in the plane distribution of the three samples by Principal Component Analysis (PCA); the PLS-DA model established by baseline corrected spectral data had the best effect, and the false positive rate was 0. Then using partial least squares (PLS) combined with SG smoothing, Baseline, Normalization, MSC and other pretreatment methods to establish a PLS quantitative model for the spectral data of the black rice mixed with dyed rice and purple rice. The results showed that the PLS model with baseline correction pretreatment method had the best effect. The correlation coefficient of the prediction set of purple rice-doped rice was 0.936, and the root means square error of prediction (RMSEP) was 0.095. The correlation coefficient of the prediction set of purple rice blended black rice was 0.914, and the root mean square error of the prediction set was 0.096. In order to compare and analyze the prediction accuracy of linear (PLS) and nonlinear (LS-SVM) quantitative model methods, the least squares support vector machine (least squares support vector) is established by using the same pretreatment method. Machine, LS-SVM) predictive model, using radial basis function (RBF) as the kernel function. The results showed that the LS-SVM model had the best effect after baseline correction. RMSEP of the predicted rice with purple rice was 0.092, and the correlation coefficient (R_p) of the prediction set was 0.979. RMSEP of the meter is 0.093, and the prediction set correlation coefficient (R_p) is 0.948. The comparison found that the LS-SVM prediction model for the content of purple rice adulteration is better and more accurate than the PLS model. Studies have shown that terahertz time-domain spectroscopy combined with chemometric methods can provide a fast and accurate analytical method for qualitative and quantitative analysis of purple rice adulteration.
		2020 Vol. 40 (08): 2382-2387 [Abstract] ( 179 ) RICH HTML PDF (2508 KB) ( 65 )

	2388	Detection of DNA, RNA Bases and Rare Bases by Terahertz Spectroscopy
		TANG Ming-jie^{1, 2}, YAN Shi-han¹, ZHANG Ming-kun¹, WEI Dong-shan¹, DU Chun-lei^1*, CUI Hong-liang¹
		DOI: 10.3964/j.issn.1000-0593(2020)08-2388-04
		Spectral analysis of nucleic acid molecular bases is of great significance to the study of biogenetics. In this paper, the feasibility of terahertz time domain spectroscopy (THz-TDS) and Raman spectroscopy for the spectroscopic detection of DNA, RNA bases and rare bases is discussed. The terahertz and Raman spectra of seven solid nucleic acid bases were analyzed, and the THz-TDS and Raman spectroscopy techniques were compared. In THz-TDS experiments, cytosine (C), guanine (G), adenine (A), thymine (T, DNA-specific) and uracil (U, RNA-specific) and rare bases (5-methylcytosine (m⁵C), 1-methyladenine (m¹A)) were identified. Signature absorption peaks and absorption intensities differ significantly in the 0.2～2.0 THz, and the differences of seven bases can be identified intuitively; In Raman spectroscopy, the seven bases also show many distinct characteristic peaks, however the characteristic peaks of Raman spectroscopy are complex and many, so it is not intuitive to identify many substances. The difference of absorption intensity is related to the thickness of powder, particle size and the depth of light focusing. The fluorescence of samples also interfere with Raman spectra. The laser may also damage biological samples. The experimental results show that these two technologies can identify seven common and rare bases. THz-TDS technology is superior to Raman spectroscopy in the ability to identify these seven bases, showing a relatively concise, fast and non-destructive detection performance. THz-TDS technology not only provides a fast and accurate method for the identification of DNA, RNA and rare bases, but also lays an experimental foundation for the study of biogenetics.
		2020 Vol. 40 (08): 2388-2391 [Abstract] ( 254 ) RICH HTML PDF (2315 KB) ( 64 )

	2392	Spectral Characterization for Liquid Crystal Display (LCD)
		ZHANG Xiao-hui¹, LI Xue-ping², GAO Cheng^{1, 2}, WANG Zhi-feng^{1, 2}, XU Yang², LI Chang-jun^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2020)08-2392-05
		Display characterization is one of the key-problems for colour management, and in the early stage focus is on developing transforms between the display digital driving signals RGB and the colorimetric values XYZ. The GOG and PLCC models were widely considered for this kind of applications in the literature. Recently, in order to reproduce colour match in spectral, display spectral characterization becomes a hot research topic, which has a very important application for the reproduction of multispectral images. In this paper, the well-known GOG and PLCC models are proposed for spectral characterization for the liquid crystal displays. Though the GOG and PLCC models have been widely considered for the display characterization application, it seems that there are no discussions for the display spectral characterization in the literature. It is first shown in this paper that the GOG and PLCC models can indeed be used for display spectral characterization under the assumptions of channel independence and chromaticity constancy for each channel. Performance of the proposed models together with SRPM and SRPPM models are considered using the two widely used professional displays: EIZO CG277 and BENQ PG2401 LCD. At the same time, comparisons are also considered for the GOG and PLCC models trained using the pure red/green/blue colour data and the grey scale (neutral point) data respectively. The comparison results have shown that both GOG and PLCC perform better trained using the grey scale (neutral point) data than those trained using the pure red/green/blue colour data. Furthermore, the comparison results have also shown that PLCC model trained using the grey scale (neutral-point) data performs better than the SRPPM and GOG models according to both forward and inverse models. Especially, the inverse of the PLCC model is much simpler than the inverse of the SRPPM model. Hence the PLCC model is recommended for the LCD spectral characterization.
		2020 Vol. 40 (08): 2392-2396 [Abstract] ( 191 ) RICH HTML PDF (1716 KB) ( 75 )

	2397	Terahertz Spectrum Inversion Modeling of Lead Content in Different pH Soils
		LI Chao^{1, 2}, LI Bin^{2, 3}, ZHANG Li-qiong², YE Da-peng^1, ZHENG Shu-he¹
		DOI: 10.3964/j.issn.1000-0593(2020)08-2397-06
		Aiming at the quantitative determination of heavy metal lead in soils, the optimal inversion prediction model of lead content in soils at different pH was studied based on terahertz spectroscopy. Lead-containing soil samples with pH of 8.5, 7.0 and 5.5 were prepared. Terahertz time-domain spectroscopy system TERA K15 was used to collect the Terahertz spectra of the samples, and multivariate scattering correction (MSC), baseline correction and Savoitzky-Golay smoothing were used to pre-process the spectra. For the spectral data of pre-treatment, successive projection algorithm (SPA) was used to select the sensitive frequencies of spectral data. Based on the selected sensitive frequencies, partial least squares (PLS), support vector machine (SVM) and back propagation neural network (BPNN) was used to establish inversion prediction models of lead content in the soil. The correlation coefficient of calibration (R_c), root mean square error of calibration (RMSEC), the correlation coefficient of prediction (R_p), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD) were used as model evaluation parameters to evaluate the performance of the model, and to determine the best prediction model of leadship in different pH soils. The experimental results show that the modeling effect after SPA choosing sensitive frequencies is generally better than that of full spectrum. Among them, the best prediction models for the samples with pH 8. 5 were SPA-PLS, R_c, R_p, RMSEC, RMSEP and RPD were 0.997 7, 0.994 6, 14.52 mg·kg^-1, 22.70 mg·kg^-1 and 9.63, respectively; the best prediction models for the samples with pH 7.0 were SPA-SVM, R_c, R_p, RMSEC, RMSEP and RPD were 0.996 2, 0.975 7, 20.25 mg·kg^-1, 33.04 mg·kg^-1 and 4.56, respectively; and the samples with pH 5.5 were the best. The prediction models are SPA-BPNN, R_c, R_p, RMSEC, RMSEP and RPD are 0.968 7, 0.974 4, 48.83 mg·kg^-1, 55.03 mg·kg^-1 and 4.44, respectively. The results provide a new idea for inversion prediction of lead content in different pH soils, and also provide theoretical methods and technical support for other heavy metals inversion prediction models in different pH soils.
		2020 Vol. 40 (08): 2397-2402 [Abstract] ( 185 ) RICH HTML PDF (2134 KB) ( 70 )

	2403	Study on the Influence of Wavelength and Low Temperature on COD Detection by Ultraviolet Spectroscopy
		LI Xin¹, SU Cheng-zhi^1,2*, YU Dan-yang¹, SHENG Yu-bo¹, CHANG Chuan¹, SHI Lei¹, JIANG Ji-guang¹
		DOI: 10.3964/j.issn.1000-0593(2020)08-2403-06
		COD represents the degree of water pollution by reducing substances, compared with the traditional method to detect COD, the detection time is long and the operation is complicated. Ultraviolet spectroscopy has become a mainstream detection method due to its fast detection speed and no need for chemical reagents. Based on the Lambert Beer law, using potassium hydrogen phthalate powder to prepare standard solution as an experimental object, aiming at the detection accuracy of COD ultraviolet spectrum at low temperature, the optimal detection wavelength of COD and the influence of temperature on the detection value of COD were studied respectively. At the same time, the surface water in a certain area of Changchun City is selected as the research object to verify the applicability of the best COD detection wavelength in the actual water sample and the accuracy of the temperature compensation model. When studying the influence of detection wavelength on COD detection value, choose A₂₅₆，A₂₆₆，A₂₇₆，A₂₈₆，A₂₉₆ five wavelengths to regression analysis samples, including A₂₅₆，A₂₆₆，A₂₇₆，A₂₈₆，A₂₉₆ is A wavelength of 256, 266, 276, 286 and 296 nm absorbance, the absorbance of A linear regression with the COD standard solution, can be seen from the fitting data 276, 286 and 296 nm model representative, 286 nm in fitting out the best effect, 296 nm, Finally, it is 276 nm, of which the correlation coefficient r of 286 nm is 0.994 6 and the determination coefficient R² is 0.989 4，SSE=0.011 4 and RMSE=0.037 7 at 296 nm, but the determinant coefficient R² is low. It can be seen that 286 nm is the highest correlation and the smallest error. The results show that 286 nm is also suitable for the detection of actual water samples, and 286 nm is the best detection wavelength. When studying the influence of temperature on COD detection value, UV absorption spectra of COD water samples and standard water samples were collected at different temperatures. The results show that the UV absorption of COD solution increases with the increase of temperature. After thoroughly studying the spectral absorption of the actual and standard water samples with the same concentration of COD at the standard temperature (20 ℃), in order to eliminate the influence of temperature on COD measurement, a temperature compensation model was established by the least square method. The accuracy of the temperature compensation model is verified by the actual water sample, and the error analysis is carried out at the same time. The results show that the maximum relative error between the actual value of COD and the compensated value is 6.38%, the minimum relative error is 0.63%, and most of the relative errors are concentrated in 4%, which shows that the fitting effect of the model is good. Thus, COD temperature compensation model has high compensation accuracy and good effect. Finally, the conclusion is drawn that the best wavelength and temperature compensation model selected for COD detection can effectively improve the accuracy of COD low temperature detection.
		2020 Vol. 40 (08): 2403-2408 [Abstract] ( 231 ) RICH HTML PDF (3253 KB) ( 77 )

	2409	The Effect of Spectral Pretreatment on the LSSVM Model of Nitrogen in Intertidal Sediments
		LÜ Mei-rong¹, REN Guo-xing^{1, 2}, LI Xue-ying¹, FAN Ping-ping¹, LIU Jie¹, SUN Zhong-liang¹, HOU Guang-li¹, LIU Yan^1*
		Spectral data transformation and feature wavelength extraction are two important spectral pretreatment methods, which play an important role in eliminating environmental interference. Previous literature mainly compared different spectral data transformation methods and there was less studyon the spectral feature wavelength extraction methods and the combination of the two methods. In order to obtain suitable spectral pretreatment method and improve the accuracy of LSSVM model of sediment nitrogen in the intertidal zone, the effect of 4 spectral transformation methods combined with 3 characteristic wavelength extraction methods on the accuracy of LSSVM model of sediment nitrogen is studied for accurate prediction of sediment nitrogen in the intertidal zone. The results showed that the spectral transformation methods of multivariate scattering correction (MSC) or normal distribution (SVN) increasedthe correlation between spectra and nitrogen content and the highest correlation reached 0.69 and 0.71 respectively. MSC and SVN improved the prediction accuracy of LSSVM model, and the prediction R² and RPD are 0.88, 0.87 and 2.78, 2.69, respectively. The feature wavelength extraction method of uninformative variable elimination (UVE) also improved the prediction accuracy of LSSVM model, model test R² and RPD were 0.89 and 2.70, respectively. However, not all of the characteristic wavelengths extracted by UVE have a high correlation with nitrogen content. In addition, the combination of UVE and MSC or SVN also improved the prediction accuracy of the model, but it is not better than UVE alone or MSC or SVN alone. The results of this paper can provide a technical reference for nitrogen estimation and spectral data preprocessing of intertidal sediments.
		2020 Vol. 40 (08): 2409-2414 [Abstract] ( 134 ) RICH HTML PDF (1957 KB) ( 143 )

	2415	Watercore Identification of Xinjiang Fuji Apple Based on Manifold Learning Algorithm and Near Infrared Transmission Spectroscopy
		GUO Jun-xian¹, MA Yong-jie¹, GUO Zhi-ming², HUANG Hua³, SHI Yong¹, ZHOU Jun¹
		DOI: 10.3964/j.issn.1000-0593(2020)08-2415-06
		Apple watercore occurs in many major apple producing areas, while there is no suitable way to sort apple type with watercore quickly. This research applies near infrared transmission spectroscopy, chemometric methods and manifold learning algorithm, selecting Xinjiang Red Fuji apple and watercore disease ones as samples, collecting near infrared transmission spectrum within 590 to 1 250 nm, spectroscopically corrected spectrum is used to do ten more speciesof spectral pretreatment. Firstly, full-wavelength pattern recognition is performed on the pre-processed spectral data to find out that multivariate scattering correction is the best pretreatment method. Then dataset preprocessed by multivariate scattering correction is used to make dimension reduction by using many other manifold learning algorithms such as Multidimensional Scaling, Stochastic Neighbor Embedding, Symmetric Stochastic Neighbor Embedding, t-Distributed Stochastic Neighbor Embedding, Laplacian Eigenmaps, Isomap, Landmark Isomap, Locally Linear Embedding, Diffusion Maps, combining Mahalanobis distance discrimination, quadratic discriminant analysis, K-nearest neighbor method to identify if watercore exist or not. Results indicate that an optimal identification model is obtained by using MSC-Landmark Isomap-KNN when principal components equal to twelve, and the identification rates for the calibration set and prediction set are 97.5% and 96.3% respectively. Hence, manifold learning algorithm and near infrared transmission spectroscopy technology can successfully realize the watercore identification of Xinjiang Red Fuji apple, which provides a theoretical basis for developing identification device in further research.
		2020 Vol. 40 (08): 2415-2420 [Abstract] ( 216 ) RICH HTML PDF (3363 KB) ( 58 )

	2421	Quantitative Analysis of Perennial Buckwheat Leaves Protein and GABA Using Near Infrared Spectroscopy
		ZHU Li-wei¹, ZHOU Yan¹, CAI Fang¹, DENG Jiao¹, HUANG Juan¹, ZHANG Xiao-na¹, ZHANG Jin-ge², CHEN Qing-fu^1*
		DOI: 10.3964/j.issn.1000-0593(2020)08-2421-06
		In order to aidthe buckwheat breeding work, quantitative identification models for testing the content of protein and γ-aminobutyric acid (GABA) in perennial buckwheat leaves were built by near-infrared reflectance spectroscopy (NIRS) with quantitative partial least squares (QPLS). NIR spectra of 222 buckwheat samples were collected, and calibration models were established based on the spectra and chemical values. It was found the average, maximum and minimum protein contents of the samples were 164, 331 and 121 mg·g^-1, respectively; the mean, maximum and minimum GABA contents of the samples were 2.489, 3.968 and 1.439 mg·g^-1, respectively. Protein modeling results were as follows: when using different spectral regions, themean coefficient of determination (R²), standard error of calibration(SEC) and relative standard deviation(RSD) for the calibration set was 93.46%, 0.63 and 3.82% respectively, for the validation set, the mean R², SEC and RSD was 91.77%, 0.88 and 5.28% respectively; when using different ratios of the modeling samples and testing samples, the R², SEC and RSD for the calibration set was 93.55%, 0.63 and 3.82%, for the validation set, the mean R², SEC and RSD was 92.18%, 0.87 and 5.20% respectively; when through second derivative (13) pretreatment, the wave number range of 4 000~9 000 cm^-1 was appropriate for modeling (calibration sets∶validation set=4∶1), the R², SEC and RSD for the calibration set was 93.57%, 0.55 and 3.38% respectively, for the validation set, the mean R², SEC and RSD was 93.35%, 0.73 and 4.40% respectively. GABA modeling results were as follows: using different spectral regions, the mean R², SEC and RSD for the calibration set was 86.28%, 0.21 and 8.30% respectively, for the validation set, the mean R², SEC and RSD was 84.35%, 0.22 and 8.76% respectively; using different ratios of the modeling samples and testing samples, the mean R², SEC and RSD for the calibration set was 88.51%, 0.20 and 8.04%, for the validation set, the mean R², SEC and RSD was 86.80%, 0.21 and 8.40% respectively; no pretreatment, the wave number range of 4 000~10 000 cm^-1 was appropriate for modeling (calibration sets∶validation set=4∶1), the R², SEC and RSD for the calibration set was 93.28%, 0.15 and 6.10% respectively, for the validation set, the mean R², SEC and RSD was 91.49%, 0.17 and 6.68% respectively. This study has demonstrated the feasibility and reliability of using NIRS to detect the content of protein and GABA in perennial buckwheat leaves.
		2020 Vol. 40 (08): 2421-2426 [Abstract] ( 174 ) RICH HTML PDF (2120 KB) ( 58 )

	2427	Chlorophyll Fluorescence-Spectral Characteristics of Vegetables Under Different Fertilizer Treatments
		WANG Yuan^{1, 2, 3}, WANG Jin-liang^{1, 2, 3*}
		DOI: 10.3964/j.issn.1000-0593(2020)08-2427-07
		The reflectance spectra and chlorophyll fluorescence parameters of Brassica campestris L. and Brassica pekinensis Rupr. under different fertilization conditions were measured in order to further analyze the growth physiology of vegetables under different fertilization conditions and the response relationship between the spectra and chlorophyll fluorescence. The results show that: (1) In the visible light range, the reflectance spectrum of Brassica pekinensis Rupr. increased with the growth and development of vegetables. The reflection spectrum of the Brassica campestris L. increased first and then decreased with the growth of vegetables; in the near-infrared range, the reflection of Brassica campestris L. and yellow cabbage The spectrum increases with the growth and development of vegetables. (2) Under different fertilization conditions, the spectrum of vegetables was significantly different, and it showed significant performance in the near-infrared band. During the growth period, the reflectance of Brassica pekinensis Rupr. was higher at the C3 and C5 levels, and the reflectance of the Brassica campestris L. at the C2 and C3 levels was high. At the maturity stage, the spectral reflectance of the Brassica pekinensis Rupr. had a higher reflectance at the C5 and C6 levels; the Brassica campestris L. was higher at the C3 and C5 levels. (3) The chlorophyll fluorescence parameters Fv/Fm of Brassica campestris L. and Brassica pekinensis Rupr. increased with the development of the growth period. Fv/Fm of Brassica campestris L. was the highest at C6 level, and Fv/Fm of Brassica pekinensis Rupr. was the highest at C2 and C6 level. (4) Under different fertilization conditions, the characteristic spectral parameters and chlorophyll fluorescence showed a significant positive and negative correlation. The relationship between chlorophyll fluorescence and spectral characteristics can provide a reference for monitoring the growth physiology and health status of vegetables.
		2020 Vol. 40 (08): 2427-2433 [Abstract] ( 167 ) RICH HTML PDF (4157 KB) ( 75 )

	2434	The Structural Characteristics of Organic-Inorganic Complexes and the Mechanism of Its Influences on Soil Color in the Calci-Aquic Vertisols
		GUO Cheng-shi^{1, 2}, MA Dong-hao¹, ZHANG Cong-zhi¹, ZHANG Jia-bao^1*, CAI Tai-yi^{1, 3}, ZHOU Gui-xiang¹, CHEN Jie¹
		DOI: 10.3964/j.issn.1000-0593(2020)08-2434-06
		Soil color is an important physical property for studying the genesis, formation environment and fertility of the soil. Generally, the soil with a higher organic matter content appears darker, but the soil color of the Calci-Aquic (CA) Vertisols with low organic matter contents also appear very black. The results based on the traditional chemical extraction method of black matters indicated that the combination of highly aromatized humus with soil particles makes the CA Vertisols appearing black. However, the chemical extraction method only partially extracted the humus ingredients, and what is more important, it destroyed the structure of organic matter and organic-inorganic complexes. The study on the black matter extracted from the CA Vertisols by the physical extraction method without destroying structures of organic-inorganic complexes showed that the black organic-inorganic complexes formed from smectites adsorbing organic matters were the decisive factor of the CA Vertisols apprearing black. However, the effects of the structures of the organic matters absorbed by the smectites on the color of the black organic-inorganic complexes remains unclear. Therefore, this study aims to explore the mechanism of these organic-inorganic complexes appearing black from the structural characteristics of the organic matters in the black organic-inorganic complexes and their relationships to smectites. Firstly, the physical method was adopted to extract the light-colored components (>53 μm particles, white (W) and light white (LW))) and black components (light black (LB), black (B) and nano black (NB)) from the topsoil layer (0～40 cm) of the typical CA Vertisols in three sites of the Huang-Huai-Hai Plain in China. The blackness, organic matter structures and smectite contents of the extracted components were then measured by Spectrophotometer, solid-state ¹³C NMR spectrometer and X-ray diffractometer. Finally, correlation analysis and path analysis of smectites, organic matter structures and soil blackness showed that the direct and indirect effects through alkyl C, carboxyl C, amino C and O-alkyl C on soil blackness are strong in all three soils, while both of the direct and indirect effects of aromatic C content and aromaticity on soil blackness are weak. Besides, the direct and the indirect effects through carboxyl C, amino C and alkyl C of smectites on soil blackness are also strong. Therefore, it is the carboxyl C, amino C, alkyl C and O-alkyl C, rather than the aromatic carbon and high aromaticity in the traditional view, that determine the black color of the CA Vertisols were by being selectively absorbed by the widely existing smectites in the CA Vertisols to form organic-inorganic complexes.
		2020 Vol. 40 (08): 2434-2439 [Abstract] ( 189 ) RICH HTML PDF (1328 KB) ( 62 )

	2440	*Study on Differentiation of Swertia leducii* and Its Closely Relative Species Based on Data Fusion of Spectra and Chromatography**
		YU Ye-xia^1,2, LI Li^1, WANG Yuan-zhong^2
		DOI: 10.3964/j.issn.1000-0593(2020)08-2440-07
		Swertia leducii is an annual herbaceous plant of the genus Swertia. It has a remarkable high effective in treating liver inflammation. The appearance of S. leducii and the species of the same genus is very similar, and the whole dry herb of Swertia plants is often used as medicine. It is very difficult to correctly identify different species from the morphology. Nevertheless, It is different in treating effective due to different species with different chemical components. In this study, based on data fusion of spectra and chromatography, an effective identification method of S. leducii and its closest relative species was established to provide the scientific basis for authenticity and security of S. leducii medication. Fourier transform infrared (FTIR) and ultra performance liquid chromatography (UPLC) of 102 samples of Swertia were collected from 5 species. Standard normal variate (SNV), multiplicative signal correction (MSC), Savitzky-Golay smoothing (SG), first derivative (1D) and second derivative (2D) were used to treat raw spectral data. Then, the optimal spectral data was utilized to process Hierarchical cluster analysis (HCA) for analyzing the similarity and dissimilarity of genus Swertia with different species. Kennard-Stone algorithm was applied to divide 102 samples into the calibration set and validation set in accordance with 2∶1 ratio. The calibration set was established the random forest (RF) discriminant model basing on FTIR, UPLC, low-level and mid-level data fusion, and the validation set was used to test the predictive ability of these models. In addition, the model performance was evaluated by sensitivity, specificity, precision and accuracy. The results indicated that: (1) SNV+SG+2D was the optimal pretreatment that all samples were correctly classified with the highest R²Y (91.2%) and Q² (84.1%). (2) HCA could reflect the classification and genetic relationship of S. leducii and its wild relatives. The other 4 species excepting S. punicea were correctly classified and its total accuracy rate reached 93.1%. S. punicea, S. cincta and S. davidii had closed relationship with S. leducii while S. angustifolia was relative far. (3) Comparing the FTIR, UPLC, low-level data fusion and mid-level data fusion, the number of error samples in the classification of RF analysis were 1, 5, 1 and 0, respectively. In the RF models, the best classification of mid-level data fusion with none error samples was better than other data matrices. Mid-level data fusion combined with RF methods can identify different species of genus Swertia and display the genetic relationship between S. leducii and its wild relatives. Besides, it could provide a theoretical basis for the development of plant resources and quality control of genus Swertia.
		2020 Vol. 40 (08): 2440-2446 [Abstract] ( 149 ) RICH HTML PDF (3480 KB) ( 128 )

	2447	Theoretical Study on the Molecular Structure and Infrared Spectroscopy of Indometacin in External Electric Field
		GE Hao-ran^{1, 3}, WANG Fang-yuan^{1, 3}, LI Gui-qin², YE Song^{1, 3}, WANG Jie-jun^{1, 3}, LI Shu^{1, 3}, WANG Xin-qiang^{1, 3*}
		DOI: 10.3964/j.issn.1000-0593(2020)08-2447-06
		Waste drug compounds can end up in the environment as pollutants in natural drinking water and municipal wastewater if not properly treated. Hospital sewage will contain low concentrations of drugs, and when these drugs enter the environment, they will become pollutants, which will seriously pollute the natural ecosystem. Indomethacin is a widely used non-steroidal anti-inflammatory drug, but it is not easily soluble in water, and refractory degradation makes drug degradation in sewage a challenge. In order to study the changes of the molecular structure and spectrum of indomethacin under the action of the external electric field (EEF), the density functional theory (DFT) and the 6-31+G(d, p) basis set are used along the Y-axis (N15-C16). The EEF (0～0.025 a.u.) was applied and the ground state geometry of the indomethacin molecule was optimized. The total energy, bond length, infrared spectrum (IR), dipole moment and HOMO-LUMO energy gap were investigated. The results show that in the absence of EEF, the single bond between C2 and C17 in the indomethacin molecule is optimized to become a double bond between the benzene rings, which makes the electrons of C16 and C17 and the isolated electrons of N15 form a strong bond with the benzene ring. The conjugated system minimizes the energy of indomethacin and forms the most stable configuration. The total energy of the ground state decreases slowly with the increase of EEF. When F≥0.015 a. u., it decreases significantly, and the change of dipole moment is opposite. As the EEF is enhanced, the expansion and contraction of each key length vary. The bond lengths of C3-C4，C3-N15，C5-C6，O10-C11 and N15-C16 are elongated, especially the bond lengths of O10-C11, C3-N15 and N15-C16 are drastically changed, and the easiest to break and then Indomethacin decomposition. When the EEF becomes larger, the energy gap is continuously reduced, indicating that the electrons of the indomethacin in the EEF are easily transitioned to a high energy level, and the molecules are excited to an excited state. The IR generated by the vibration of different chemical bonds in the indomethacin molecule, corresponding to different spectral shifts, is mainly related to the energy level, the energy level difference is reduced, the frequency is reduced, resulting in red shift (RS), and vice versa. Shift (BS); but the correspondence between N15-C40, C16-C18 bond length change ΔR and frequency shift change Δf indicates that the spectrum shift is also related to factors such as molecular orbital configuration and dipole moment change. Stronger 4, 5, 6, and 7 absorption peaks occur RS and the vibration intensity increases, indicating that the corresponding chemical bonds become weak and cause a fracture. All these phenomena indicate that indomethacin molecules become unstable and prone to dissociation with the enhancement of EEF. Analysis of the molecular structure and IR under EEF can be used to study the degradation of indomethacin by electric field dissociation method, in order to provide theoretical guidance for the degradation of stubborn drugs in sewage.
		2020 Vol. 40 (08): 2447-2452 [Abstract] ( 166 ) RICH HTML PDF (2400 KB) ( 51 )

	2453	Field Observations of the Bidirectional Reflectance Characteristics of Lake Ice
		YU Miao¹, LU Peng^1*，CAO Xiao-wei¹, TANG Ming-guang¹, WANG Qing-kai¹, LI Zhi-jun^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2020)08-2453-09
		Ice surface albedo is an essential parameter associating with the energy exchange between water and atmosphere in cold regions, which can be retrieved from satellite remote sensing data. However, reflectivity data is not equal to the ice surface albedo because satellites always have a limited field of view at specific wavelength bands and observational angles. Anisotropy corrections are also needed according to the conditions of underlying surfaces. Since ice has strong forward scattering and its optical properties are sensitive to its physics, there is large difference in reflectance among different ice types and at different observational angles, which results in uncertainties in ice albedo retrievals. The field observations on lake ice were conducted in Wuliangsuhai lake, Inner Mongoliain February 2019. Spectral measurements of surface albedo, bidirectional reflectance distribution function(BRDF) and anisotropy reflectance factor(ARF) were conducted for the five types of lake ice: (Ⅰ) ice with non-uniform bubbles under overcast sky; (Ⅱ) ice with sands on surface; (Ⅲ) ice with big bubbles inside; (Ⅳ) ice with dense small bubbles inside, and (Ⅴ) melting ice. The differences among them are discussed. The results reveal that lake ice albedo increases with the solar zenith, except for the melting ice case, showing an opposite trend. The bidirectional reflectance characteristics of ice present an obvious anisotropy. Peak reflectivity takes place in the direction of the forward scattering, and the location is significantly affected by the ice surface condition. The reflected light in the other directions mainly come from volume scattering in ice, which is insensitive to the observed zenith and can be affected by ice’s uniformity at shortwave band rather than at longwave band. Results on BRDF indicate that the spectral shape of volume scattering is similar to albedo, but the attenuation rate in the longwave band of BRDF is faster than that of albedo. That is, the energy of volume scatter is more concentrated in the shortwave band. However, in the direction near the reflectivity peak, the energy is more concentrated in the longwave band than in the shortwave band. ARF results reveal that the contribution of volume scattering to surface albedo decrease with wavelength, but the role of surface reflection is on the contrary. More importantly, the order of the ARF was not the same as that of the BRDF, which suggests that the retrieval parameters for the surface albedo of different ice types are not identical even under the same observational angle.
		2020 Vol. 40 (08): 2453-2461 [Abstract] ( 180 ) RICH HTML PDF (6961 KB) ( 59 )

	2462	Cy3-Labeled Aptamer Combined with Surface-Enhanced Raman Scattering Using for Specific Detection of Trace Acetamiprid
		TENG Yuan-jie, WEI Qi-zhen, LIU Wen-han, LIU Jiang-mei, NIE Yong-hui, LI Pan
		DOI: 10.3964/j.issn.1000-0593(2020)08-2462-06
		In this work, aptamer modified by Cy3 (1,1’-bis(3-hydroxypropyl)-3,3,3’, 3’-tetramethylindocarbocyanine) dye which has a strong Raman signal, was applied for sensitive and specific detection of trace acetamiprid by Surface-enhanced Raman Scattering (SERS). The good stability and dispersity of negative silver colloid were obtained by adding the proper concentration of sodium polyacrylate according to the principle of colloid stabilization and coagulation. During the detection process, these high stable silver nanoparticles were needed to be agglomerated by using the agglomerating agent to form more SERS enhancement hotspots to improve the SERS intensity. The effects of different agglomerating agents (NaCl, KCl, NaOH, HNO₃, H₃PO₄, H₂SO₄, HCl) were investigated using acetamiprid as a probe. The results showed that the good SERS effect was showed when the electrolyte precipitator contains H⁺ and PO^3-₄. Furthermore, UV-Vis spectra show that the surface charge properties play a decisive role in the SERS effect. Furthermore, spermine with positive charges was selected to neutralize the negative charges on the phosphoric acid skeleton of Cy3-aptamer which could shorten the distance between Cy3-aptamer and silver colloid to enhance the Raman signal. The optimum reaction times of spermine with Cy3-aptamer and Cy3-aptamer with acetamiprid were 5 and 20 min, respectively. At last, quantitative detection of the acetamiprid method was established and the linearship was established between the logarithm concentration of acetamiprid and the relative intensity of the characteristic peak area at 1 392 cm^-1 divided by the OH stretching vibration of water. The linear range is from 1×10^-8 to 2.5×10^-7 mol·L^-1. The proposed method was applied to the determination of the spiked acetamiprid in water samples with the recovery of 97.4%～99.4%. The results show that the silver colloid dispersed by sodium polyacrylate and modified by spermine were helpful to capture the Cy3-aptamer and the reactants of Cy3-aptamer with acetamiprid, that the sensitivity and reliability of the method were improved.
		2020 Vol. 40 (08): 2462-2467 [Abstract] ( 160 ) RICH HTML PDF (3032 KB) ( 48 )

	2468	Infrared Spectroscopic Quantitative Analysis of Raw Material Used as Coal-Based Needle Coke in the Coking Process
		YUE Li, CHEN Zhao, LAI Shi-quan, ZHU Ya-ming, ZHAO Xue-fei^*
		DOI: 10.3964/j.issn.1000-0593(2020)08-2468-06
		Soft coal tar pitch (SCTP) with low QI content is the preferred raw material for preparing coal-based needle coke, the study on its structure changes in the stage of liquid-phase carbonization into coke (350~550 ℃) is helpful to prepare high-quality needle coke. In this paper, a detailed analysis on the C—H stretching vibration peaks in the range of 3 100～2 800 cm^-1 and the aromatic C—H bending vibration peaks in the range of 900～700 cm^-1 has been carried by the peak-fitting technique using the infrared spectra of the sample. And then based on the calibration factors of the corresponding C—H vibration peaks for the standard substances, the mass percentages of the different types of aromatic hydrogen (H_solo, H_duo, H_trio and H_quarto) and aliphatic hydrogen (H_CH₃, H_CH₂ and H_CH) of SCTP were quantitated at different carbonization temperatures (400, 500, 600 and 800 ℃). Furthermore, the contents of SP² hybridized Carbon (SP²C) and SP³ hybridized Carbon (SP³C) as well as these structural parameters such as H/C atomic ratio, aromatic index (I_ar), aromatic ortho-substitution index (I_os) and branched index (CH₃/CH₂) were calculated, and the changes of aromatic structure of SCTP during the coking process were also discussed. The results showed that the coal-based needle coke raw material SCTP is mainly composed of aromatic hydrocarbons with a low number of the ring and few side chains, its I_ar is 0.77, and about 82% of its aromatic hydrogen is distributed in the structure containing three/four adjacent aromatic C—H, while its aliphatic hydrogens are mainly distributed in the CH₂ of naphthenic structures. With the increase of carbonization temperature, the aliphatic hydrogen or SP³C of SCTP decreased almost linearly, losing about 50% at 400 ℃, which was mainly attributed to the loss of light components and the dehydrogenation of naphthenic structures. The green coke formed at 500 ℃ had Only 0.15 Wt.% aliphatic hydrogen and 0.88 Wt.% SP³C, and the presence of aliphatic hydrogen was not detected at 600 ℃. However, the aromatic hydrogen increased slightly from 3.89 Wt.% of the raw material to 4.5 Wt.% before 400 ℃ because of the conversion of the naphthenic structuresinto aromatic rings. As the temperature increases further, aromatic hydrogen decreases rapidly, reaching only 1.14 Wt.% when the temperature reaches 500 ℃, indicating that the aromatic hydrocarbon molecules undergo intense dehydrogenation condensation reaction during the mesophase formation stage at 400~500 ℃, which was also confirmed by the conversion of a large number of protonated SP²C into unprotonated SP²C. Aromatic hydrogen continued to decrease after 500 ℃, and their presence was not detected at 800 ℃. In addition, it was found that the out-of-planebending vibration of aromatic C—H is more sensitive to infrared light than its in-plane stretching vibration. The increase of I_arand the decrease of these parameters such as H/C atomic ratio, I_os, CH₃/CH₂ indicated that the aromatic molecules in the SCTP are gradually grown up by their condensation, and its aromaticity increased in the coking process. The fast quantification of various types of hydrogen by infrared spectrum can timely understand the structural changes of aromatic hydrocarbon molecules of the pitch in the coking process, which is helpful to the production of needle coke.
		2020 Vol. 40 (08): 2468-2473 [Abstract] ( 187 ) RICH HTML PDF (2716 KB) ( 59 )

	2474	Research on Inversion Model of Low-Grade Porphyry Copper Deposit Based on Visible-Near Infrared Spectroscopy
		MAO Ya-chun^1,2, DING Rui-bo^1*, LIU Shan-jun^1,2, BAO Ni-sha^1,2
		DOI: 10.3964/j.issn.1000-0593(2020)08-2474-05
		At present, the analysis of copper grades at home and abroad is mainly based on chemical analysis. Due to the disadvantages of high cost, long time and residual pollutants, the chemical analysis method has a serious hysteresis effect on the relative ore blending process, resulting in that the copper content of the tailings is too high, which will inevitably lead to waste of resources. It is an effective way to solve this problem by conducting visible-near-infrared spectroscopy and modeling of porphyry copper deposits. Based on the chemical analysis and spectral test data of 121 Wushan porphyry copper deposits, the visible-near-infrared spectral characteristics of porphyry copper deposits are analyzed. The original spectral data is processed by principal component analysis (PCA) and local linear embedding algorithm (LLE). The reduced dimension is 3 and 5 dimensions respectively. At the same time, the genetic algorithm (GA) is used to select the band of the original spectral data. A total of 467 optimal bands are selected. Then, this paper takes the BP neural network as the modeling method, respectively uses visible-near-infrared spectroscopic data of 92 and 29 porphyry copper deposits as the modeling and testing samples, and establishes a quantitative inversion model of visible-near infrared spectroscopy for porphyry copper deposits. The average absolute error of the grade inversion model based on the original data is only 0.104%. The average absolute error of the grade model based on the model processed by the principal component analysis method, the locally linear embedding algorithm and the genetic algorithm is 0.110%, 0.093% and 0.045% respectively. It can be seen that the grade inversion accuracy of the model based on the data processed by principal component analysis method is poor, the accuracy of grade inversion model based on locally linear embedding algorithm is slightly improved, and the grade inversion accuracy of the model based on the data processed by the genetic algorithm is improved obviously. The research result shows that the grade analysis based on the inversion model of visible-near infrared spectroscopic data of low-grade porphyry copper deposits is feasible, providing an effective method for rapid grade detection of low-grade porphyry copper deposits in China.
		2020 Vol. 40 (08): 2474-2478 [Abstract] ( 180 ) RICH HTML PDF (1758 KB) ( 60 )

	2479	Micro Raman Spectral Characteristics and Implication of Pyrite in the Jiaojia Gold Deposit, Jiaodong Area, Shandong Province, China
		YAO Chang¹, SONG Hao^{1, 2*}, LI Qi¹, LI Na¹, ZHANG Gang-yang¹
		DOI: 10.3964/j.issn.1000-0593(2020)08-2479-05
		Pyrite is one of the most common metallic minerals in gold deposits. It not only has a close relationship with the gold mineralization, but also serves as the main gold-carrier. Therefore, pyrite can provide much information for growth and forming of gold. However, previous scholars study the pyrite in gold deposits by a series of geochemistry methods, such as EPMA or SIMS, to quantify the gold content and trace elements. Nevertheless, these methods are not only highly expensive but also time-spending. Therefore, we need an efficient and reliable technology. Raman spectroscopy, more convenient and reliable, is used in materials science to identify molecules and study chemical bonding and intramolecular bonds. So, it might be regarded as an effective geological tool. Therefore, we will study the formation and structure of pyrite in different alteration zones by Raman spectrum and petrography in this paper. The Jiaojia gold deposit is located in Jiaodong area, the most important gold resources in China currently. Jiaojia gold mine is a typical altered rock type deposit, with the prominent alteration zonation and structural ore-control characteristics. The wall rock is the Linglong granite and pyrite is the main ore minerals. The wall rock alteration along the fault zone in the mining area, and the wall rock alterations are mainly composed of K-feldsparization, sericitization, pyritization. By studying the Raman spectral peak data of samples in different depths and alteration zones, we discuss the Raman shift and the half height width (FWHM) of the characteristic peak of pyrite including their geological significance. Analyzing result shows that though the Raman shift of Ag has some deviation in transforming part of different alterations, it has an obviously positive correlation with the depth roughly. Pyrite in the ore body and sericitization-zone FWHM value (median) are mainly concentrated in 3.3, 3.2~5.5 cm^-1 respectively. In the K-feldspathization-halo which is located away from the ore body, FWHM value (median) is concentrated in 4.1~8.4 cm^-1. We can find that the FWHM declines from K-feldspathization-halo (shallow depth) to ore body firstly, then it increases gradually to K-feldspathization-halo (deep depth). We deem that from the K-feldspathization-halo to the ore body, the crystallinity and order degree of pyrite are becoming higher and higher, and the pyrite in K-feldspathization-halo has a trend to change into low crystallinity and disorder. On the other hand, it implicates that the pyrite in different alteration zones various forming temperature. So, it is not difficult to find that the pyrite in alteration zones is forming at a higher temperature with the low crystalline degree. Pyrite in the ore body are forming at a lower temperature with the high crystalline degree. This phenomenon agrees well with the petrographic study previously. In addition, we also assume that the formation temperature of pyrite for various depths is distributed symmetrically. It fits roughly to the distribution of alteration zones.
		2020 Vol. 40 (08): 2479-2483 [Abstract] ( 187 ) RICH HTML PDF (1527 KB) ( 61 )

	2484	In-Situ Measurement of Total Organic Carbon Concentration in Seawater Based on Ultraviolet Absorption Spectrometry
		BI Wei-hong^1,2, FAN Jun-bo^1,2, LI Zhe^1,2, LI Yu^1,2, WANG Si-yuan^1,2, WANG Hao^1,2, FU Guang-wei^1,2, ZHANG Bao-jun^1,2
		DOI: 10.3964/j.issn.1000-0593(2020)08-2484-06
		Total Organic Carbon（TOC) refers to the total carbon content of the organic substances dissolved and suspended in water, which is a comprehensive indicator for the total amount of organic substances in water. The traditional measurement technologies of TOC arethe national standard combustion method and the wet chemical method, which always involves complicated test methods, long measurement time, slow speed, some atmospheric environment, and can only be completed in the laboratory and not available to the seawater online in-situ measurement. The concentration of TOC in seawater is measured with ultraviolet absorption spectroscopy technology using the optical in-situ sensor developed by our research team, which achieves online in-situ quick measurement of TOC without adding reagents, doesn’t induce secondary pollution, and is not restricted by the laboratory environment. In this paper, the sensor developed by our research team is used to real underground seawater TOC measurements for different sea areas (the sea area around Huanghua Portand Qinhuangdao City, in Hebei Province), and comparison of correlation, consistent and measurement error between sensor measurement method andnational standard method is conducted, which shows that: The evolution trend of the concentration of TOC from the 13 different seawater samples in the Huanghua Port area and the 14 different seawater samples in the area around Qinhuangdao obtained using TOC optical in-situ sensor are basically consistent with that obtainedfrom the national standard method. Better linear correlation and consistency is demonstrated, and there are very few water samples that deviate from the overall sample curve. The experimental data shows a good correlation through the linear fitting, and the data fitting curves and conventional error are analyzed for two different sea areas. The correlation coefficient of the linear fitting for the water sample of Huanghua Port is r=0.859 0, and the sum of squared residuals is 0.165 4. The correlation coefficient of the linear fitting for the water sample around Qinhuangdao is r=0.939 9, and the sum of squared residuals is 3. 5131. Because the correlation coefficient r=0.939 9>r=0.859 0, which means that the linear fitting effect of water samples around Qinhuangdao is better than that of Huanghua Port experiment. The conventional error is 0.165 4<3.513 1, which is caused bymore serious pollution induced by some samples around river estuaries in Qinhuangdao city. Domestic sewage and industrial wastewater induce more interfering factors in water quality, which cause certain influence to the accuracy and stability of marine TOC optical in-situ sensors; TOC in-situ optical sensors based on ultraviolet absorption spectroscopy technology and traditional methods are different from the national standard method, which uses smaller sample set and sample concentration coverage, however, the marine environment is complicated and changeable, and the sensor cannot completely avoid the influence of all other factors, such as turbidity, temperature, PH, plankton, etc., which is the main source of the measurement error. The future exploration is how to eliminate the influence of complicate interference factors in the marine environment, reduce the error of sensor measurement values, make the measurement results more accurate and true.
		2020 Vol. 40 (08): 2484-2489 [Abstract] ( 193 ) RICH HTML PDF (2305 KB) ( 94 )

	2490	Open-Path FTIR Gas Detection Method Based on Two-Dimensional Correlation Infrared Spectroscopy
		WANG Na^{1, 3}, DONG Da-ming^{1, 3*}, JIAO Lei-zi^2，3
		DOI: 10.3964/j.issn.1000-0593(2020)08-2490-05
		Open-Path Fourier Transform infrared spectroscopy (OP-FTIR) enables fast, flexible, and quantitative detection of gas, but OP-FTIR signal is weak compared to gas pool extraction methods, and its ability to detect gas is restricted. In order to improve its detecting capacity of gas, two-dimensional correlation analysis is performed on the measured infrared spectrum data of the gas with natural gas flow disturbance. The ethanol gas and two kinds of Chinese spirits’ volatiles were used as the verification objects. The infrared absorption spectra of ethanol gas and the volatiles of Luzhouteniang and Fenjiu were measured by OP-FTIR method. In the untreated infrared absorption spectrum of ethanol gas, no obvious characteristic peak of ethanol was observed. The two-dimensional correlation analysis of the infrared absorption spectrum data showed that there was an obvious autopeak centered at 1 050 cm^-1 in the two-dimensional correlation synchronous spectrum, and the autopeak came from ethanol. The results verified that the gas detection ability of the OP-FTIR method which is combined with two-dimensional correlation infrared spectroscopy was improved. The infrared absorption spectrum data of different concentrations of ethanol gas were processed by synchronous two-dimensional correlation. It was found that the autopeak intensity centered at 1 050 cm^-1 in the two-dimensional correlation synchronous spectrum increased with the increase of ethanol gas concentration, indicating that OP-FTIR gas detection method based on two-dimensional correlation spectrum has a certain quantitative analysis capability. When detecting the volatiles of Luzhouteniang and Fenjiu by OP-FTIR method, the ethanol gas in the volatile matter was detected in the region of 820～1 480 cm^-1, and the gas content was measured by the intensity of the auto peak at (1 050, 1 050 cm^-1) in the two-dimensional correlation synchronous spectrum. The results showed that the ethanol gas content in the volatiles of the Luzhouteniang is higher than that in Fenjiu; the aroma components in the volatile matter were detected by the region of 1 700～1 820 and 1 400～1 600 cm^-1, by comparing the two-dimensional asynchronous spectrum of the volatiles of the Luzhouteniang and Fenjiu, it found that there are more cross peaks in the two-dimensional asynchronous spectrum of the volatiles of Luzhouteniang, so Luzhouteniang showed more abundant aroma substances information compared to the volatiles of Fenjiu, this difference can be used to identify the volatiles of Fenjiu and Luzhouteniang. The research proved that the OP-FTIR gas detection method based on two-dimensional correlation infrared spectroscopy realized the improvement of the gas detection ability of OP-FTIR method, and has certain quantitative analysis ability. At the same time, combined with two-dimensional correlation infrared spectroscopy, OP-FTIR also has further research significance for identifying different volatile matter.
		2020 Vol. 40 (08): 2490-2494 [Abstract] ( 191 ) RICH HTML PDF (3689 KB) ( 80 )

	2495	Fast Reconstruction for Multi-Channel Raman Imaging Based on and Sample Optimization and PCA
		FAN Xian-guang^{1, 2}, LIU Long¹, ZHI Yu-liang¹, KANG Zhe-ming¹, XIA Hong¹, ZHANG Jia-jie¹, WANG Xin^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2020)08-2495-05
		Raman imaging is a noninvasive, label-free spectral imaging technique that has been widely used in the biomedical field. However, the spontaneous Raman signals of most biological samples are weak. It takes a long time to obtain an image with a high signal-to-noise ratio, which seriously affects the spatial and temporal resolution of Raman imaging and hinders its application in fast dynamic systems. The multi-channel Raman imaging is one of the effective ways to solve this problem. The reconstruction of the full Raman spectrum is the key in this system, and the corresponding algorithm of reconstruction is needed to be developed. At present, the algorithms capable for spectral reconstruction are pseudo-inverse and Wiener estimation. Although these methods are simple and easy to be carried out, they are susceptible to nonlinear factors such as noise and vibration when applied to the system of multi-channel. On the other hand, the numbers of the training sample are relatively small, and the bad sample affects the reconstruction in the system of multi-channel. In order to solve those problems, we propose an algorithm based on sample optimization and principal component analysis (PCA). Firstly, the simulated narrow-band measurements of the training samples are calculated by using the spectral response function of the filter, and the full Raman spectra are reconstructed by Wiener estimation, and then the simulated narrow-band measurements of the reconstructed spectra are achieved. The sample gets Optimized by comparing the simulated narrow-band measurements of the sample and the reconstructed spectra. Second, the interference of nonlinear factors is reduced by introducing the polynomial regression and expanding the optimized narrow-band measurements. At last, the main information of training samples is extracted, and the calculation is reduced by using PCA, and the transform matrix is completed. At the same time, the normalization is introduced to realize the reconstruction of Raman spectra. In the experiment, the polymethyl methacrylate is selected as the experimental sample, and the Raman spectrum is reconstructed by pseudo-inverse, Wiener estimation and our algorithm. The root means square error is used to evaluate the accuracy of the reconstructed spectra. The result proves that our algorithm is significant. It provides theoretical support for the further application of Raman imaging technology in fast dynamic systems.
		2020 Vol. 40 (08): 2495-2499 [Abstract] ( 180 ) RICH HTML PDF (2690 KB) ( 53 )

	2500	Spectral Characteristics of an Argon/Oxygen Plasma Plumes Excited by DC Voltage and Operated Underwater
		WU Jia-cun, WU Kai-yue, JIA Bo-yu, JIA Peng-ying^*, LI Xue-chen
		DOI: 10.3964/j.issn.1000-0593(2020)08-2500-05
		Atmospheric pressure glow discharge (APGD) is abundant with active species, and a vacuum device is dispensable for APGD. Due to these good merits, APGD has extensive application prospects in material surface modification, biomedical application, pollutant treatment, and so on. In application research for APGD, oxygen-containing active species, such as OH radicals and O atoms, play an important role. Unfortunately, the influence of oxygen content in working gas on the concentration of the produced oxygen atom is not very clear up to now. Aim to this status, and a diffused atmospheric pressure plasma is excited by a direct-current voltage with a needle-mesh geometry, which is operated underwater of deionized water and with argon/oxygen mixture used as working gas. Discharge image presents three distinct regions, including anode glow, negative glow, and a positive column between them. The presence of these characteristic regions suggests that the discharge is operated in a glow discharge regime. By optical and electrical methods, results show that both gap voltage applied between the two electrodes and light emission signal is time-invariant, that is to say, the discharge operates in a continuous mode, other than the pulsed mode. Moreover, the voltage-current curve of discharge has a negative slope at low current and voltage stabilizing at high current, revealing that the discharge operated underwater is in a subnormal glow discharge regime at low current, and in a normal glow discharge regime at high current. By optical emission spectroscopy, spectrum collected in the range from 250 to 900 nm contains spectral lines mainly in the range of 680 to 900 nm, which are composed of Ar Ⅰ and O Ⅰ (777.4 and 844.0 nm). In addition, an OH line with weak intensity is also observed at 308 nm. With increasing O₂ content of working gas, the intensity of Ar Ⅰ(750.4 and 763.5 nm) monotonously decreases. However, the intensity of O Ⅰ increases firstly, reaches a maximum with an oxygen content of 1.5%, then decreases with increasing O₂ content. In order to analyze this phenomenon, the concentration of oxygen atom is then investigated as a function of oxygen content in working gas by using an intensity of O Ⅰ at 777.4 nm ratio to intensity of Ar Ⅰ at 750.4 nm. Results indicate that oxygen atom concentration with increasing oxygen content of working gas has a similar trend with O Ⅰ intensity, that is to say, oxygen atom concentration increases firstly and then decreases with increasing O₂ content, and its maximum is reached with an oxygen content of 1.5%. Finally, a qualitative explanation is given through analyzing the generation process of oxygen atoms and the loss procedure of electrons attached by oxygen molecules. These results are of great significance for the application of APGD.
		2020 Vol. 40 (08): 2500-2504 [Abstract] ( 186 ) RICH HTML PDF (2265 KB) ( 48 )

	2505	Spectral Characteristics of Dissolved Organic Matter Released From Biochar at Different Pyrolysis Temperatures
		ZHAO Min^1,2, CHEN Bing-fa^1,2, FENG Mu-hua¹, CHEN Kai-ning¹, PAN Ji-zheng^1*
		DOI: 10.3964/j.issn.1000-0593(2020)08-2505-07
		The dissolved organic matter (DOM) released from biochar has complex biogeochemical characteristics, affecting the migration and transformation of pollutants, carbon cycle and many other environmental processes. Compared with researches on the physicochemical and structural characteristics of biochar, researches on biochar DOM are few. The spectral characteristics of DOM released by biochar driven by pyrolysis temperature are rarely reported. We choose cypress and bamboo biochar, which are common and have a good application prospect, as research object. Spectral characteristics of DOM released from two kinds of biochar under different pyrolysis temperature (100~700 ℃) were identified by ultraviolet-visible spectra，and three-dimensional fluorescence spectra combined with parallel factor method (3DEEMs-PARAFACA). The results show that the pyrolysis temperature determines the DOM release potential and spectral characteristics of biochar. The amount of DOM decreases when the pyrolysis temperature increase and 400℃ is the critical temperature. When the pyrolysis temperature is lower than 400 ℃, the biochar DOM is obviously released; but the release amount of DOM is low and tends to be stable when the pyrolysis temperature is lower than 400 ℃. The amount of DOM released from cypress biochar is apparently higher than bamboo biochar. During the pyrolysis process at low temperature (<300 ℃), a large number of UV-visible chromophore exists in the DOM of biochar, which decomposes gradually with the increase of pyrolysis temperature. We isolated two humic-like fluorescent components (C1 and C2) and one protein-like fluorescence component (C3) from the fluorescent dissolved organic matter (FDOM) by 3DEEMs-PARAFAC. Three components show different responses to pyrolysis temperature, humic-like components appeared fluorescent intensity peak at 300 ℃, and then decrease when the temperature rises. Meanwhile, the fluorescent intensity of protein-like component decrease from beginning to end. FDOM under low pyrolysis temperature (＜200 ℃) is dominated by protein-like substance, but humic-like substance predominated when pyrolysis temperature increase. In addition, pyrolysis temperature also affects many biogeochemical characteristics of two kinds of biochar. With the increase of temperature, the relative molecular weight, aromaticity, hydrophobicity and humification degree firstly increase and then decrease, but the peak appears in different temperature. Due to the differences in raw materials, the relative molecular weight, aromaticity, hydrophobicity and humification degree of bamboo biochar was significantly higher than that of cypress. The conclusion of this study further provides beneficial references for the study on the environmental behavior of biochar DOM and the environmental management and assessment in the engineering application of biochar.
		2020 Vol. 40 (08): 2505-2511 [Abstract] ( 189 ) RICH HTML PDF (3316 KB) ( 82 )

	2512	Near Infrared Spectral Analysis Modeling Method Based on Deep Belief Network
		ZHANG Meng, ZHAO Zhong-gai^*
		DOI: 10.3964/j.issn.1000-0593(2020)08-2512-06
		Near infrared NIR spectroscopy is a fast, non-destructive quantitative analysis tool that has been widely used in various industries. How to build an effective and accurate model is of importance to the application of NIR spectroscopy. At present, most commonly used quantitative analysis methods are based on shallow models, while Deep Belief Network (DBN) is a probability-based deep model. It can automatically learn the effective feature representation of the input, and as long as the number of last hidden layer output nodes is lower than the dimension of the input spectrum, the spectral data can be reduced in dimension while the feature extraction is completed on the spectral data. Near-infrared spectroscopy is characterized by a large sample size, large variables, and high dimensionality. This paper proposes a near-infrared spectroscopy modeling method based on a deep belief network to estimate the physical concentration. The method uses near-infrared spectroscopy data as the input layer. Firstly, unsupervised learning of the multi-restricted Boltzmenn Machines (RBM) is employed to achieve the feature extraction of the spectrum itself. Then the target physicochemical value is used to fine tune the network, and optimize model parameters. Based on the DBN calibration model, the final regression layer of the deep belief network is developed by the PLS method, and the DBN-PLS calibration model may avoid the optimal local problem caused by the gradient descent algorithm. In this paper, the feasibility of DBN modeling and DBN-PLS modeling is verified by two model evaluation indexes including decision coefficient (R²) and mean square error (mse), and the traditional BP modeling and DBN modeling are compared and analyzed. The analysis results show thatDBN method modeling and DBN-PLS method modeling can improve the prediction accuracy.
		2020 Vol. 40 (08): 2512-2517 [Abstract] ( 174 ) RICH HTML PDF (3888 KB) ( 53 )

	2518	Study on the Interaction Between Chlortetracycline Hydrochloride and Pepsin by Multispectral and Molecular Docking
		WANG Xiao-xia^1*, YU Yang-yang², MA Li-tong¹, NIE Zhi-hua³, WANG Zheng-de¹, CUI Jin-long¹, SAI Hua-zheng¹, ZHAO Wen-yuan¹
		DOI: 10.3964/j.issn.1000-0593(2020)08-2518-07
		The mechanism of interaction between CTC and PEP was investigated by using fluorescence spectra, UV-Vis absorption spectra, circular dichroism (CD), 3D fluorescence spectra, synchronous fluorescence spectra and molecular docking methods.The quenching mechanism associated with the CTC-PEP interaction was determined by performing fluorescence measurements at different temperatures. The binding constants (K_A) at three temperatures (298, 303, and 308 K) were 4.345×10⁷, 2.836×10⁷ and 1.734×10⁷ L·mol^-1 respectively, and the number of binding sites (n) was 1.618, 1.587, and 1.555, respectively. The n value was close to unity, which meant that there was only one independent class of binding site on pepsin for CTC. Based on the thermodynamic analysis, thermodynamic parameters at 298 K were calculated as follows: ΔH (-70.13 kJ·mol^-1), ΔG (-43.57 kJ·mol^-1), and ΔS (-89.00 J·(mol·K)^-1). It was known from ΔH<0 and ΔS<0 that Van der Waals’ forces and hydrogen bonds were the main forces between CTC and PEP, the reaction was spontaneous from ΔG<0. According to Förster’s dipole-dipole non-radiative energy transfer theory, the specific binding distance of CTC-PEP system was 3.240 nm, it proved that there was non-radiative energy transfer between CTC and PEP. Molecular docking further suggested that CTC molecule bound within the active pocket of PEP. There were the van der Waals forces between CTC and residues VAL30, SER35, TYR189, THR74, THR77, GLY78 and LEU112 of PEP, and hydrogen bonds between CTC and GLU13, GLY217, ASP32, ASP215 and GLY76. There also was a hydrophobic interaction between CTC and the amino acid residue TYR75 of PEP. Various forces make CTC and PEP form a stable complex.The effects of CTC on the conformation of PEP were analyzed by UV absorption spectroscopy, synchronous fluorescence spectroscopyand 3D fluorescence spectroscopy. It is demonstrated in detail that CTC can increase microenvironment polarity and decrease the hydrophobicity of tryptophan (Trp) residues in PEP. Circular dichroism spectra indicated the secondary structure of PEP was partially changed by CTC with the percentage of α-helix increasing from 11.6% to 21.0% andthe percentage of β-sheet decreasing from 47.3% to 28.2%.The content of β-Turnstructure increased from 19.6% to 24.2%, and the content of Random coil increased from 27.6% to 34.2%, indicating that CTC interacted with PEP, and CTC changed the microenvironment around PEP, and also changed the secondary structure of PEP. The results of this study are helpful to understand the binding mechanism of CTC and PEP, and provide an important basis for the rational use of CTC.
		2020 Vol. 40 (08): 2518-2524 [Abstract] ( 160 ) RICH HTML PDF (2890 KB) ( 55 )

	2525	In Situ Raman Spectra Characterization of Zonal Arsenic-Bearing Pyrite and Arsenopyrite in the Baiyunpu Gold Deposit, Hunan
		GAO Shang^{1, 2}, HUANG Fei^2*, LIU Jia³, SU Li-min⁴, WANG Wei¹
		DOI: 10.3964/j.issn.1000-0593(2020)08-2525-06
		Arsenic-bearing pyrite and arsenopyrite are important gold-bearing minerals in various types of gold deposits. They often develop multi-stage concentric rings, which provide a lot of information for understanding the genesis and formation process of the deposit. The variation characteristics of morphology and composition of zonal arsenic-bearing pyrite and arsenopyrite grains had been fully studied, but no systematic in-situ Raman spectra data have been reported. Meanwhile, the study of Raman peak migration in layered zones can also provide some reference value for understanding the occurrence forms of invisible gold. Electron microprobe analysis results show that arsenic-bearing pyrite decreases first and then increases in S and Fe content from the core to the outer layer (Py1→Py2→Py3), and opposite in As content (up to 10.86% in Py2). The content of Au is positively correlated with that of As, and it is also relatively enriched in Py2 (up to 0.14%). From the core to the outer layer of arsenopyrite (Apy1→Apy2), the S and Fe content decreases, while the As content increases. In situ Raman spectra analysis shows that there are three main Raman peaks in different layered zones of arsenic-bearing pyrite, corresponding to Fe-[S₂]^2- deformation vibration peak (E_g), Fe-[S₂]^2- stretching vibration peak (A_g) and S-S stretching vibration peak (T_g) of pyrite, respectively. The Raman shifts of inner core Py1 are concentrated in 345.8~346.9, 382.0~382.9 and 434.6~434.8 cm^-1. That of intermediate zone Py2 are concentrated in 331.9~338.7, 359.2~365.4, 404.3~414.2 cm^-1; and that of outer zone Py3 are 343.0~344.9, 375.5~378.3 and 417.3~431.5 cm^-1. The Raman peaks of Py2 shift significantly to low frequency with the offset ranging from 3.1 to 27.2 cm^-1. It is concluded that the Raman shift change of pyrite is mainly related to the substitution of As and Au ions. The invisible gold in arsenic-bearing pyrite may enter the lattice in the form of chemical bonding state, resulting in the change of chemical bonding force constant and reduced mass, and it leads to the decrease of Raman peak vibration frequency and the shift to low frequency. There are six Raman peaks in arsenopyrite of 136.2~139.8, 174.8~179.4, 198.9~200.7, 307.0~314.2, 338.5~343.9 and 407.8~410.5 cm^-1, which is similar to the data of R050071 sample in RUEFF database and some reference value in relevant pieces of literature. In addition, the Raman peaks of Apy2 shift slightly to low frequency related to Apy1, and the offset ranges from 0.7 to 5.4 cm^-1. We thought that the change of Raman shifts in arsenopyrite is mainly related to the vibration migration caused by the isomorphic substitution of S ions by As ions. The study on in-situ Raman spectra characteristics of zonal arsenic-bearing pyrite and arsenopyrite from Baiyunpu samples provide abundant Raman spectra data for the identification of pyrite and arsenopyrite minerals with different compositions, and provide an important reference for revealing the frequency shift of Raman peaks measured in different layered zones and exploring the existence state of invisible gold.
		2020 Vol. 40 (08): 2525-2530 [Abstract] ( 275 ) RICH HTML PDF (3320 KB) ( 66 )

	2531	Color and Genesis of Beihong Agate and Its Spectroscopic Characteristics
		LU Zhi-yun, HE Xue-mei^*, GUO Qing-feng
		DOI: 10.3964/j.issn.1000-0593(2020)08-2531-07
		The Beihong agate is commonly known as agate with the translucent and yellowish-red appearance and is widely produced in the southern section of Xing’an Mountains. In this paper, the phase composition, chemical composition and spectroscopic characteristics of Beihong agate and its yellow and white control samples were investigated by polarizing microscope observation, X-ray powder diffraction, Raman spectra, UV-VIS absorption spectra and whole rock chemical analysis. The results show that Beihong agate is composed mainly by α-quartz, with moganite, goethite as the minor mineral composition, a very small amount of hematite can also exist in Beihong agate. The yellowish-red appearance of Beihong agate is related to goethite and a very small amount of hematite, which is different from the coloration mechanism of Nanghong agate by hematite. Based on distribution pattern, goethite and hematite can be divided into scattered and disseminated forms. The size of goethite and hematite with scattered distribution is about 10 μm, but they possess amorphous morphology, it is presumed that the scattered minerals were the aggregates of goethite and hematite crystal at the submicron scale. In addition, the disseminated goethite and hematite exhibit invisible pattern, which are similar to the scattered minerals and goethite and hematite crystal that are all sub-micron in size, but they do not aggregate to form microscopic scattered aggregates. On the whole, the content of goethite and hematite in Beihong agate is higher than that in the yellow control sample, as the content of goethite and hematite increases, the hue of Beihong agate changes from yellowish-red to red. The Beihong agate exhibited ⁶A₁→⁴E, ⁶A₁→⁴E⁴A₁, 2(⁶A₁)→2(⁴T₁)(4G), ⁶A₁→⁴T₂(4G) electron transitions of goethite and ⁶A₁→⁴E⁴A₁, ⁶A₁→⁴T₂ electron transitions of hematite and the charge transfer between O^2- and Fe³⁺, the synergy of electron transition in the act of the crystal field and charge transfer produce significant yellowish-red color. In the first derivative spectra of UV-VIS absorption spectra, the minimum value position of Beihong agate, yellow and light-yellow contrast samples are 555～556, 530 and 502 nm, respectively. As the red tone of agate decreases gradually, the position of the minimum value in the visible range of the first derivative spectrum decreases gradually. It can be used to characterize red to yellow hue of agate, which is also significant for the variety identification and color grade of quartz jades.
		2020 Vol. 40 (08): 2531-2537 [Abstract] ( 283 ) RICH HTML PDF (5944 KB) ( 118 )

	2538	Hyperspectral Anomaly Detection Based on Approximate Posterior Information
		WANG Qiang-hui¹, HUA Wen-shen^1*, HUANG Fu-yu¹, ZHANG Yan¹, YAN Yang²
		DOI: 10.3964/j.issn.1000-0593(2020)08-2538-08
		Hyperspectral Remote Sensing technology records radiation signals with spectral information of objects through imaging spectrometers to obtain three-dimensional hyperspectral images containing spectral information and spatial information. It has been widely used in spectral unmixing, image classification, and target detection. In recent years, with the development of remote sensing technology and the increasing demand for accurate location of targets, target detection has achieved rapid development. According to whether the target spectrum is grasped in advance as a priori information, target detection is divided into spectrum matching detection and anomaly detection. Spectrum matching detection requires the target spectrum as a priori information, and usually has higher detection accuracy and better results. The anomaly detection does not require prior information and has a wider application range, but the detection accuracy is usually lower than that of spectral matching detection. Due to the lack of a complete and practical spectral library in practical applications, it is difficult to obtain prior information, and anomaly detection that does not require prior information has become a research hotspot. This paper proposes an Approximate Posterior Information-based Hyperspectral Anomaly Detection Algorithm. First, the matrix decomposition algorithm is used to decompose the original hyperspectral image data to obtain a pure background matrix and an anomaly matrix containing noise. The anomaly matrix is discarded, and the obtained background matrix is used as approximate background information. Then calculate the Mahalanobis distance between the spectral vector of all the pixels in the image and the mean vector in the background matrix to perform initial anomaly detection on the image to obtain the initial anomaly. Finally, the approximate background information and approximate target information are used as prior information, and orthogonal subspace projection is performed to obtain the final anomaly detection algorithm. Applying this algorithm to all the pixels in the image, we get the anomaly detection result for the whole image. In order to prove the excellent effect of this algorithm, a group of simulation data and a group of AVIRIS real hyperspectral data were used for experiments, and compared with RX, LRX, LSMAD algorithms. Experiments show that the algorithm can effectively suppress noise, both from a qualitative perspective and a quantitative perspective, and can still effectively detect anomalous targets in the image when the signal-to-noise ratio is relatively low. The effect of detection efficiency is small, and good detection results have been achieved.
		2020 Vol. 40 (08): 2538-2545 [Abstract] ( 189 ) RICH HTML PDF (7068 KB) ( 47 )

	2546	Hyperspectral SFIM-RFR Model on Predicting the Total Iron Contents of Iron Ore Powders
		GAO Wei¹, YANG Ke-ming^1*, LI Meng-qian², LI Yan-ru¹, HAN Qian-qian¹
		DOI: 10.3964/j.issn.1000-0593(2020)08-2546-06
		Iron ore is one of the most abundant metallic minerals in the world. Total iron contents is an important index to evaluate the quality of iron ore and iron ore powder, and it has a special significance in iron ore mining, ore dressing, ore smelting and other production links. The traditional chemical methods have the disadvantages of a time-consuming, complex operation, seriously pollution. Therefore, exploring a new method of rapid, effective and pollution-free detection has become a hot spot in mine environment research. Hyperspectral technology has the characteristics of high spectral resolution, continuous curve, no damage, no pollution and accurate detection of characteristics or components of materials. The purpose of this paper is to establisha data evaluation index of spectral feature importance measures (SFIM) and to screen spectral features based on the hyperspectral data of iron ore powder, and then combined with random forest regression (RFR) to establish the SFIM-RFR prediction model and predict the total iron contents of iron ore powder. First, taking Sanyizhuang iron mine in Yangyuan county, Hebei province as a research object, based on the iron concentrate and iron powder tail collected in the research area in November 2018 and March 2019, the first batch of iron ore powder samples in the training group and the testing group and the second batch of iron ore powder samples in the second testing group were made respectively. Spectral data of samples were measured by the ASD Field Spec4 spectrometer. Then, spectral data of the first batch of training group were used in the SFIM-RFR model training, and the total iron contents in the samples of the first batch of the testing group were predicted. Meanwhile, conventional methods, including RFR and linear regression (LR) prediction model, were used to compare and analyze the predicted results of total iron contents in iron ore powder samples. Finally, the spectral data of the second testing group were used to validatethe robustness of the multi-model. The results show that the R-Square values of prediction results of total iron contentsby the SFIM-RFR, RFR and LR models were 0.991 8, 0.988 4, 0.898 7, and RMSE valuesare 0.016 9, 0.020 1, 0.059 6. The results of multi-model prediction overall are good, and the SFIM-RFR model has the minimum error, which indicates the feasibility and effectiveness of this model in predicting the total iron contents of iron ore powder. Moreover, the prediction ability of SFIM-RFR model is better than that of conventional prediction models. The R-Square values of the prediction results of total iron contents by the SFIM-RFR, RFR and LR models are 0.976 8, 0.974 5 and 0.914 0. The RMSE values are 0.034 6, 0.036 2 and 0.071 9, which proves that the prediction ability of the SFIM-RFR model is the best and the robustness of the prediction model is the best.
		2020 Vol. 40 (08): 2546-2551 [Abstract] ( 163 ) RICH HTML PDF (2965 KB) ( 52 )

	2552	The Study on Thickness Detection Technology of Reflective Thermal Insulation Coatings for Buildings Based on Hyperspectral Technology
		LI Xiao-fang¹, WANG Yan-cang^{2, 3*}, GU Xiao-he⁴, WANG Li-mei¹, LI Xiao-peng¹, FENG Hua², CHEN Ting-yu²
		DOI: 10.3964/j.issn.1000-0593(2020)08-2552-06
		As a new type of building coatings, reflective heat insulation coatings have been widely used in building construction by virtue of its advantages of energy saving and environmental protection. The high and low performance of reflective heat insulation coatings directly affects the performance of building energy saving and environmental protection, and has a great impact on the indoor environment of buildings. Reflective thermal insulation coatings for buildings mainly achieve energy saving and environmental protection by reflecting and absorbing solar radiation (visible-near infrared) and building radiation (thermal infrared). For specific building reflective heat insulation coatings, the interaction between them and light mainly depends on the construction parameters, such as coating thickness. Therefore, hyperspectral technology is used to quantitatively analyze the reflection and absorption characteristics of building reflective heat insulation coatings, and to study the influence of coating construction parameters (thickness) on the performance of building reflective heat insulation coatings, so as to provide scientific and technological support for coating construction detection. With the help of hyperspectral technology, this study measured the spectral data of different coatings thickness, analyzed the evolution law of the spectral characteristics of coatings with the increase of the thickness of coatings, studied the coatings index which can characterize the thickness of coatings construction, and analyzed the correlation between the spectral data of coatings and the coatings index constructed by them and the thickness of coatings respectively. Selecting and screening the sensitive indicators of coatings construction thickness, building the thickness detection model of coatings construction, and searching for the method suitable for the thickness detection of coatings construction. The results show that: (1) the spectral data located in the 420～1 070 nm range are sensitive to the thickness of coatings 0.1～2.5 mm, and the correlation coefficient r with the thickness of coatings construction is high and phase-wise. For stability, it shows that the spectral range is sensitive to the thickness of coatings and can be used to detect the thickness of coatings; (2) Compared with the original spectrum, the coating index can effectively enhance the sensitivity of the spectrum to the thickness of coatings, and the RCI index constructed from 484 and 479 nm is the best parameter to characterize the thickness of coatings in the five categories of coatings index; (3) Among the five kinds of coatings indices, the model based on RCI index has the highest accuracy and is the best one, and its R²=0.973, RMSE=0.185, RPD=4.018.
		2020 Vol. 40 (08): 2552-2557 [Abstract] ( 154 ) RICH HTML PDF (3413 KB) ( 66 )

	2558	Hyperspectral Model Optimization for Tenderness of Chilled Tan-Sheep Mutton Based on IVISSA
		LIU Gui-shan, ZHANG Chong, FAN Nai-yun, CHENG Li-juan, YU Jiang-yong, YUAN Rui-rui
		DOI: 10.3964/j.issn.1000-0593(2020)08-2558-06
		Hyperspectral imaging can obtain both the image information and spectral information of the detected object, and make qualitative and quantitative analysis with internal components. The research on meat quality by hyperspectral imaging technology focuses on water, total viable count, color, pH, total volatile basic nitrogen etc. There are few studies on meat tenderness based on interval variable iterative space contraction method. In this paper, tenderness values of chilled Tan-sheep were detected non-destructively by visible-near-infrared and near-infrared bands (400~1 000, 900~1 700 nm) combined with chemometric methods to obtain the best modeling bands. Firstly, hyperspectral images of lamb sample were collected and extracted the spectral values of the region of interest; lamb tenderness was measured using a TA-XTplus texture analyzer; Secondly, the original spectral data between 400～1 000 and 900～1 700 nm were preprocessed by multiple scattering correction (MSC), de-trending, standard normal variate (SNV), baseline, normalize, Savitzky-Golay; optimal bands were selected by successive projection algorithm (SPA), competitive adaptive reweighted sampling (CARS), variables combination population analysis (VCPA) and interval variable iterative space shrinkage approach (IVISSA). Finally, optimal bands were selected and partial least squares regression (PLSR) model of chilled mutton was established. The results showed that: (1) the prediction performance of original spectral model in the region of 900～1 700 nm was better than that of 400～1 000 nm. (2) original spectral mode of the tenderness of chilled Tan-sheep had the best performance R_c=0.83, R_p=0.79, RMSEC=874.94, RMSEP=1 465.97 in the near-infrared region using different pretreatment methods. (3) the original spectrum of 900～1 700 nm was selected by SPA, CARS, VCPA and IVISSA with 15, 16, 13 and 123 characteristic wavelengths, accounting for 7%, 6%, 5% and 54% of the total wavelength. (4) the prediction model of chilled Tan-sheep tenderness was the best in combination with hyperspectral technique and OS-IVISSA-PLSR with R_c=0.85, RMSEC=850.86, RMSECV=1 193.42, R_p=0.79, RMSEP=1 497.11. It was indicated that IVISSA algorithm could greatly reduce the number of model operations and ensure the predictability and stability of the model. It is feasible to adopt OS-IVISSA-PLSR method to analyze the tenderness of chilled Tan-sheep mutton.
		2020 Vol. 40 (08): 2558-2563 [Abstract] ( 319 ) RICH HTML PDF (3044 KB) ( 73 )

	2564	Detection of Shape Characteristics of Kiwifruit Based on Hyperspectral Imaging Technology
		LI Jing^{1, 2, 3}, WU Chen-peng¹, LIU Mu-hua^{1, 2, 3}, CHEN Jin-yin³, ZHENG Jian-hong¹, ZHANG Yi-fan¹, WANG Wei¹, LAI Qu-fang¹, XUE Long^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2020)08-2564-07
		The shape characteristic of kiwifruit, an important indicator in the post-harvest grading process, not only affects the appearance quality of fruits but also determines the level division of them. Most of the traditional shape grading methods were adopted manual grading, which had the disadvantages of long time-consuming, low efficiency, poor repeatability and strong subjective influence. This paper used visible and near-infrared (VIS/NIR) hyperspectral imaging technique to discriminate normal and malformed kiwifruit. Firstly, 248 mature “Jinkui” kiwifruit (107 normal samples and 141 malformed samples) were prepared. The visible-near-infrared hyperspectral imaging acquisition system (400~1 000 nm) was constructed to acquire the hyperspectral image of kiwifruit. After completing the spectral image acquisition, used principal component analysis (PCA) method to reduce dimensions and obtain the first principal component image for extracting three characteristic wavelengths (682, 809 and 858 nm). Then, the wavelengths were calculated to generate a new spectral image (fused image). Furthermore, the image was segmented by the quadtree decomposition algorithm, and the corresponding 12 sets of shape characteristic parameters were calculated based on the extracted mask images. The classification models by partial least squares-linear discriminant analysis (PLS-LDA), backpropagation neural network (BPNN), and least squares support vector machine (LSSVM) were established. Finally, compared and analyzed, the best model of kiwifruit shape characteristics was obtained. The results showed that among three classification models, BPNN and LSSVM models had better classification consequences: the overall classification accuracy was above 95%; The effects of PLS-LDA model was slightly worst: the overall accuracy of the training and test sets were 80.12% and 76.83%, respectively. Among them, the overall classification accuracy of BPNN was 98.19% and 97.56% in training and test set, respectively, and the total number of misjudgments were 3 and 2, respectively. Yet, the overall accuracy of LSSVM model was 97.59% and 95.12%, respectively, the total number of misjudgments were 4 and 4, respectively. For the classification effects of kiwifruit normal, the performances of three models were: LSSVM best, BPNN followed, and PLS-LDA bottom. For the classification effects of malformation, the performances of three models were: BPNN optimal, LSSVM followed, and PLS-LDA foot. Therefore, the best classification model for kiwifruit shape characteristics was BPNN. The experimental results showed that the shape characteristics of kiwifruit could be classified and identified and had an ideal effect. In the future, it is feasible to detect fruit shape combining the visible-near-infrared hyperspectral imaging technique. The result can provide the theoretical support for the rapid and accurate non-destructive detection of kiwifruit shape features using spectral information.
		2020 Vol. 40 (08): 2564-2570 [Abstract] ( 219 ) RICH HTML PDF (2130 KB) ( 67 )

	2571	Hyperspectral-Based Estimation on the Chlorophyll Content of Turfgrass
		JI Tong^{1, 2}, WANG Bo^{1, 2}, YANG Jun-yin^{1, 2}, LIU Xiao-ni^{1, 2*}, WANG Hong-wei³, WANG Cai-ling⁴, PAN Dong-rong⁵, XU Jun⁶
		DOI: 10.3964/j.issn.1000-0593(2020)08-2571-07
		Lawn color is the most obvious indicator of ornamental lawn value. It is of great significance to explore the relationship between chlorophyll content of turfgrass and the hyperspectral reflectance. This relationship can be used to develop models to calculate the chlorophyll content for lawn quality evaluation purpose. In this study, three common lawn grass species—Festuca arundinacea CV. Hongxiang, Lolium perenne CV. Bailingniao and Poa pratensis CV. Kentucky was cultivated in pots. Measurements of chlorophyll content and hyperspectral reflectance were made during active growth period by tys-a3500 chlorophyll meter and SOC710VP imaging spectrometer to determine the relative chlorophyll content (SPAD) and spectral data of turf grass canopy, respectively. Person correlation analysis for each of the SPAD, 1/SPAD and log(1/SPAD) was conducted with a group of variables including vegetation index—10 G (green vegetation index), ARVI (atmospheric impedance difference vegetation index), VARI (visual pressure impedance index), NDVI705 normalized difference vegetation index (705), MSR705 red edge ratio vegetation index (improved), NDVI670 normalized difference vegetation index (670), CI (chlorophyll index), PSRI attenuation (vegetation index), RGI (relatively green index) and EVI ( Enhance the correlation of vegetation index). After screening the hyperspectral bands of vegetation index with the highest correlation with chlorophyll content, models were developed using the vegetation index based on these bands. After the best model was selecting through an accuracy test, the model was used to estimate the chlorophyll SPAD values change for turf grasses under different concentrations of heavy metals Pb²⁺ stress. The results are summarized as follows: (1) the overall trends of spectral curves of different turfgrass were not significantly different, but the reflectance (REF) of different species were different. At the band of 730~1 000 nm, there was no significant difference between “lark” perennial ryegrass and “red elephant” tallfestia REF, but the spectral characteristics of “Kentucky bluegrass” were unique with a higher REF. (2) among the 10 vegetation indexes, VARI, RGI and PSRI were extremely significantly correlated with 3 chlorophyll indexes of turfgrass, and the absolute value of correlation coefficient R² was all greater than 0.65, indicating that it is feasible to estimate the chlorophyll content of turfgrass with these 3 vegetation indexes. (3) Stepwise regression analysis of vegetation index and chlorophyll index shows that in the single-factor regression model, the model determination coefficient (R²) of estimating 1/SPAD using vegetation index VARI, RGI and PSRI was above 0.626, which was generally higher than the estimation of SPAD and log(1/SPAD). In multiple linear regression, the model determination coefficient (R²) constructed by 10 vegetation indexes and chlorophyll index 1/SPAD was also the highest (0.817), showing that SPAD reciprocal form is applicable to be used the in model estimation of chlorophyll in turfgrass. (4) The best model selected from the models with a high determination coefficient (>0.7) through accuracy test was y_1/SPAD=0.161x_RGI+0.007x_GI-0.054 (R²=0.817, RMSE=0.023).
		2020 Vol. 40 (08): 2571-2577 [Abstract] ( 191 ) RICH HTML PDF (4371 KB) ( 95 )

	2578	Hyperspectral Estimation Method of Chlorophyll Content in MOSO Bamboo under Pests Stress
		LI Kai^{1, 2}, CHEN Yun-zhi^{1, 2*}, XU Zhang-hua^{1, 2, 3}, HUANG Xu-ying⁴, HU Xin-yu³, WANG Xiao-qin^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2020)08-2578-06
		As the most important pigment involved in photosynthesis of plant, the chlorophyll is an important indicator for monitoring bamboo pests. This study aims to establish the hyperspectral estimation model for the chlorophyll content of bamboo leaves under pests stress by wavelength screening of different spectral data sets, and provide a theoretical basis for monitoring the pests of bamboo by hyperspectral remote sensing. The test was carried out in Shunchang County, the bamboo production base in Fujian Province. The ASD FieldSpec 3 spectrometer was used to collect 102 bamboo leaves spectra of different pest levels, and the chlorophyll content of the corresponding leaves was determined by SPAD-502 chlorophyll meter. By comparing the spectral characteristics of bamboo leaves with different pest levels, the mechanism of estimating chlorophyll content with hyperspectral data was explored. The original spectrum (OS) of the bamboo leaves was subjected to continuum removal (CR), first derivative (FD), and continuum removal-first derivative (CR-FD), and the correlation between different spectral data and chlorophyll content was analyzed. The characteristic wavelengths of the four spectra were extracted by the successive projection algorithm (SPA). Four spectral datasets were divided by sample set partitioning based on joint x-y distances method (SPXY) and random method. Combined with multiple stepwise regression (MSR), the chlorophyll content estimation model of bamboo leaves was established, and the effects of spectral transformation and sample partitioning on estimating chlorophyll content were analyzed. The results showed that there were significant differences in the spectral reflectance of bamboo leaves with different pest levels. The main manifestations were the gradual disappearance of the “green peak” and “red valley” in the visible light range, the “red edge” was levelled and the near-infrared wavelength reflectance was reduced. The spectral transformation could effectively improve the correlation between the spectrum and chlorophyll content, and the correlation coefficient between the CR-FD spectrum and chlorophyll content at 724 nm was the largest. The characteristic wavelengths of different spectral data sets extracted by the successive projection algorithm were concentrated in the green band, red band, and “red edge”, and the multiple selected wavelengths were located in bands (600～750 nm) that highly correlated with chlorophyll content. The MSR model based on SPXY sample partitioning method could significantly improve the estimation accuracy of chlorophyll content compared with the random sample partitioning method, in which R² and RPD increased by 0.1 and 0.5, and RMSE decreased by 0.7 on average. The multiple stepwise regression model established by CR-FD spectrum characteristic wavelengths combined with SPXY sample partitioning method had the highest accuracy for estimating chlorophyll content of bamboo leaves, and the R², RMSE, RPD were 0.835, 2.604 and 2.364 respectively, which could accurately estimate the chlorophyll content of bamboo leaves under pests stress.
		2020 Vol. 40 (08): 2578-2583 [Abstract] ( 183 ) RICH HTML PDF (1716 KB) ( 78 )

	2584	Inversion Based on High Spectrum and NSGA2-ELM Algorithm for the Nitrogen Content of Japonica Rice Leaves
		FENG Shuai¹, CAO Ying-li^1,2*, XU Tong-yu^1,2, YU Feng-hua^1,2, CHEN Chun-ling^1,2, ZHAO Dong-xue¹, JIN Yan¹
		DOI: 10.3964/j.issn.1000-0593(2020)08-2584-08
		In order to provide an efficient, rapid and non-destructive Inversion method for the nitrogen content of japonica rice leaves, based on the japonica rice plot experiment, using high spectrum technology and laboratory chemistry experiments to obtain the effective data for three growth periods of japonica rice in the tillering stage, joining stage and heading stage. A total of 280 sets of leaf high spectrum data and corresponding rice leaf nitrogen content data were obtained to analyze the spectral characteristics of japonica rice leaves with different nitrogen treatment levels. The random frog algorithm (Random_frog) is combined with the iteratively retaining informative variables algorithm (IRIV) to screen the feature bands, and any two spectral bands are randomly combined to construct the difference vegetation index DSI (R_i, R_j), ratio vegetation index. RSI (R_i, R_j) and normalized vegetation index NDSI (R_i, R_j), respectively, combine the superior feature band combination and vegetation index as model inputs. Therefore, BP neural network, support vector machine (SVR) and non-dominated elite strategy genetic algorithm optimization limit learning machine (NSGA2-ELM) japonica rice leaf nitrogen content Inversion model were constructed, and the model was verified and analyzed. The results showed that with the increasing level of nitrogen fertilizer treatment, the reflectivity of the japonica rice leaves in the near-infrared range gradually increased, while the reflectance decreased gradually in the visible range. A total of 8 characteristic bands were obtained by combining Random_frog and IRIV. Among them, there are 7 visible light bands, which are 414.2, 430.9, 439.6, 447.9, 682.7, 685.4 and 686.3 nm, respectively. Only one of the near-infrared bands is 999.1 nm. This method effectively eliminates interference information and greatly reduces the collinearity between the bands. At the same time, it can be analyzed from the three vegetation index (DSI (R_i, R_j), RSI (R_i, R_j), NDSI (R_i, R_j)) and the determination coefficient of the nitrogen content of the japonica rice leaves. DSI (R_648.1, R_738.1), RSI (R_532.8, R_677.3) and NDSI (R_654.8, R_532.9) have the best correlation with leaf nitrogen content, R² are 0.811 4, 0.829 7 and 0.816 9, respectively. In the comparative analysis of the input parameters with different input parameters, the model Inversion with the feature band combination as the model input is slightly better than the vegetation index combination, R² is greater than 0.7, and the RMSE is less than 0.57. In the comparative analysis between the Inversion models, the estimation effect of the NSGA2-ELMInversion model proposed in this paper is significantly better than the BP neural network model and the SVR model. The training set determination coefficient R² is 0.817 2, and the root means square error RMSE is 0.355 5. The set R² is 0.849 7 and the RMSE is 0.301 1. According to the results of this study, the Random_frog-IRIV screening characteristic band method combined with NSGA2-ELM modeling method has a significant advantage in rapidly detecting the nitrogen content of japonica rice leaves. The research results can provide a theoretical reference for field precision fertilization of japonica rice.
		2020 Vol. 40 (08): 2584-2591 [Abstract] ( 170 ) RICH HTML PDF (5534 KB) ( 97 )

	2592	Prediction Method for Production Year of Antai Pills Based on Near Infrared Spectroscopy
		CHEN Bei¹, ZHENG En-rang^1*, MA Jin-fang², GE Fa-huan³, XIAO Huan-xian⁴
		DOI: 10.3964/j.issn.1000-0593(2020)08-2592-06
		With the increase of the storage time of traditional Chinese medicine, the content of its effective components gradually decreases. Chemical detection means to consume the samples, with a long period and a high cost. In this paper, near infrared spectroscopy was used to identify the years of Antai pills of the classical prescriptions with different years. In order to explore the feasibility of this nondestructive and rapid quality control method, the absorbance data of 105 samples in 1 000～1 799 nm band near infrared spectroscopy of three years were collected, 80 samples were randomly selected as training sets and 25 samples as test sets. Firstly, the Successive Projection Algorithm (SPA) was adopted to eliminate the redundant information in the original spectral data, and the full input spectrum was optimized and the dimensionality was reduced. According to the internal of the test sets, the error value of the root mean square was cross-verified, 11 characteristic wavelengths were extracted from 800 wavelengths, respectively: (1 692, 1 714, 1 405, 1 001, 1 114, 1 478, 1 514, 1 788, 1 202, 1 014, 1 164) nm. Then the Support Vector Machine (SVM) classification model was established. Since the selection of the parameters in SVM model has a great influence on the classification accuracy, the Particle Swarm Optimization (PSO) algorithm was used to optimize the penalty parameter C and the kernel function parametersin SVM model to form PSOSVM classification model. Finally, after SPA dimension reduction, the characteristic wavelength was input into PSOSVM classification algorithm. Matlab software was used in the simulation test, and SVM, SPA-SVM classification models and SPA-PSOSVM classification model in this paper were respectively constructed. The classification test accuracy reached 76%, 92% and 100% respectively. From the simulation results, it can be seen that the SPA wavelength optimization could effectively reduce the redundant spectral information and reduce the time required for modeling. The PSO-SVM classification model, the complexity of the model was reduced and the classification accuracy was improved. The results show that the near infrared algorithm established in this paper could accurately and nondestructively distinguish the production years of the traditional Chinese medicine Antai pills, and this study could provide a way of thinking for the evaluation of the differences of the years of traditional Chinese medicine.
		2020 Vol. 40 (08): 2592-2597 [Abstract] ( 167 ) RICH HTML PDF (2808 KB) ( 70 )

	2598	*The Discrimination of the Flower Tea of Dendrobium Huoshanense, Dendrobium Officinale* and Dendrobium Henanense by a Multi-Step FTIR Method**
		CHEN Nai-dong
		DOI: 10.3964/j.issn.1000-0593(2020)08-2598-07
		The flower tea dried from the flowers of Dendrobium plants was becoming a kind of more and more favorable drink these years. Among them, the flower tea of Dendrobium huoshanense was the most expensive because of its lower yield, better mouthfeel and relative higher pharmaceutical activity comparing with other Dendrobium flower teas. Thus, the flower tea of D. huoshanense was often masqueraded by the cheaper Dendrobium flower tea, such as D. officinale and D. henanense, due to the economic interests. In this paper, a multi-step FTIR method was established to rapidly discriminate the flower tea of Dendrobium huoshanense, Dendrobium officinale and Dendrobium henanese. Different Dendrobium flower tea samples were collected from different manufacturers in July, 2018, then their Attenuated Total Reflection Flouriertransformed Infrared (ATR-FTIR) Spectroscopy and the two-dimensional correlation infrared (2D COS IR) spectra perturbed by temperatures were detected in the range of 4 000～400 cm^-1. The second derivative infrared (SD-IR) spectra were calculated from their corresponding ATR-FTIR spectroscopy. The results showed that, although direct discrimination of the Dendrobium flower tea by FTIR spectrum is quite difficult, different intensities and peak positions could be found by analysis of their ATR-FTIR files. The flower tea of D. huoshanese and D. officinale had characteristic peaks at 1 398 and 1 542 cm^-1, respectively, while D. henanese obtained characteristic peaks at 1 610, 1 332, 811, 703 and 603 cm^-1. Treatment by second derivative can improve the spectral resolution and sensitive remarkably and direct discrimination can be observed in SD-IR spectrum. The three kinds of Dendrobium flower tea could be discriminated by the “M” shape of D. huoshanese in the range of 1 750～1 690 cm^-1, by the “W” shape of D. huoshanese and D. henanese, the irregular shape of D. officinale in the range of 1 140～1 080 cm^-1, and by the “M” shape of D. huoshanese while the “W” shape of D. officinale and D. henanese in the range of 1 000～930 cm^-1. As for the 2D COS IR spectra, in the range of 1 230～1 130 cm^-1, the three kinds of flower tea could be discriminated by the auto-peaks at 1 134, 1 155, 1 182, 1 196 and 1 211 cm^-1 for D. huoshanese, at 1 186 and 1 210 cm^-1 for D. officinale, at 1 186 and 1 210 cm^-1 for D. henanese. In addition, There were two positive-correlation cross-peaks at 1 182 and 1 210 cm^-1, at 1 135 and 1 181 cm^-1, and one negative-correlation cross-peak at 1 197 and 1 155 cm^-1 in the 2D COS IR spectrum of the flower tea of D. huoshanese, while no cross-peak was observed in the 2D COS IR spectrum of the flower tea of D. officinale and D. henanese in the range of 1 230～1 130 cm^-1. The multi-step FTIR technology involving ATR-FTIR, SD-IR and 2D COS IR could be used to rapidly identify the flower tea of D. huoshanese, D. officinale and D. henanese.
		2020 Vol. 40 (08): 2598-2604 [Abstract] ( 224 ) RICH HTML PDF (3473 KB) ( 53 )

	2605	Assessment of Influence Sampling Position Variability on Precision of Near Infrared Models for Huanglongbing of Navel Orange
		ZOU Jun-cheng^1,2, LU Zhan-jun^1,3*, QIAO Ning², RAO Min²，KUANG Min², ZHONG Yan-wen², HUANG Xue-yuan²
		DOI: 10.3964/j.issn.1000-0593(2020)08-2605-06
		The near-infrared models have been applied in huanglongbing detection and it has been proved to be feasible, but the present studies are limited to taking leaves as samples. The phloem of bark is a channel to transport pathogens and nutriment, it has been shown to play an important role in pathological initiation, progression and maintenance, so that we can detect huanglongbing in the early stages with the specific information of barks. In order to explore the feasibility of infrared spectroscopy based on the bark samples and analyze the influence of sampling position variability on near infrared models for huanglongbing, three kinds of sampling plan were designed in this paper: navel orange leaves, navel orange barks and composite samples (navel orange leaves and navel orange barks). Then, we established the prediction model of HLB (huanglongbing) with PLSR (partial least square regression) and PCR (principal component regression), when the normalization was turned out to be the optimal data preprocessing method. We found that the RMSEP (root mean squared error of prediction) are all at the level of 10^-5: RMSEPL (RMSEP of leaves, 1.690 9×10^-5) < RMSEPB (RMSEP of barks, 1.889 0×10^-5) < RMSEPC (RMSEP of composite samples, 1.690 9×10^-5)；and the r² (determination coefficient of prediction) are all greater than 0.9: r²_L (r² of leaves, 0.939 6) ＜r²_B (r² of barks, 0.941 5) ＜r²_C (r² of composite samples, 0.960 3). It means that all of the models have good accuracy and prediction ability. The model based on the leaves is the most accurate but the least predictive, and the model based on the composite samples is the least accurate but the most predictive. Only based on the barks can the accuracy and predictive ability of the model maintained at the mid-range level. In this study, the original spectra and model effects of leaves and barks were compared and analyzed, the feasibility of rapid infrared spectroscopy based on the bark samples was discussed, it provides a new idea for the application of near infrared in the diagnosis of huanglongbing.
		2020 Vol. 40 (08): 2605-2610 [Abstract] ( 309 ) RICH HTML PDF (3682 KB) ( 83 )

	2611	Study on Simultaneous Analysis Method of Inclusion Size and Content in Steel by LIBS
		JIA Yun-hai^{1, 2}, LIU Jia^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2020)08-2611-06
		Inclusions are an important factor for steel performance. Many methods can be used to analyze the size and component. But no report was found that inclusion size and concentration was determined simultaneously. The metallographic microscope and SEM require fine polishing sample surface in inclusion analysis. Steel samples should be grinded at 800 mesh grinding paper and polished to mirror surface, and it is a time-consuming process. LIBS can analyze the inclusion size distribution over 1 μm and content average in steel and sample surface can be ground by over 80 mesh grinding paper, the mirror surface is not needed. When LIBS was used analyzing steel samples, if burn shot contains soluble element and its inclusion, homogenized soluble element in the matrix Fe presents in Gaussian distribution, inclusion as an “element concentrated area” yields high intensity than soluble element and additive to soluble element intensity. Inclusion intensity which was separated from the total intensity contains information of inclusion size and average inclusion concentration. When inclusion was excited, the enrichment element comes to the plasma and emit hight light intensity. Analyzing the steel samples which contain Al₂O₃ and MnS inclusions, the inclusion size and area were obtained and make a correlation with the LIBS inclusion intensity. The results show that the inclusion area and LIBS inclusion intensity are linear correlation, the diameter of globular inclusion and LIBS inclusion intensity are parabolic correlation. Average inclusion concentration which comes from multi-shot and LIBS inclusion intensity is linear correlation. Formulas （1），（10），（20）were given which using the same intensity data to analyze the inclusion size, area and concentration. The principle for simultaneous analysis of inclusion size (or area) and average content in steel by LIBS are explained. The Al₂O₃ inclusion in steel samples is analyzed and verified. The Al₂O₃ inclusion content analysis results and formula are coincided each other.
		2020 Vol. 40 (08): 2611-2616 [Abstract] ( 167 ) RICH HTML PDF (2946 KB) ( 50 )

	2617	Optimization of Determination Method of Lithium in Oil-Field Water Based on DOE
		LI Ling^{1, 2, 3}, NAI Xue-ying^{1, 2*}, CHAI Xiao-li^{1, 2, 3}, LIU Xin^{1, 2}, GAO Dan-dan^{1, 2}, DONG Ya-ping^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2020)08-2617-05
		The oil-field water in Nanyi Mountain，located in the west of Qaidam Basin of Qinghai-Tibet Plateau，is rich in lithium，calcium and other components. Thus，it was difficult to determine the exact content of lithium due to the matrix interference problems using traditional flame atomic absorption spectrometry，especially in the process of different evaporation stages. Though the general matrix matching method can resolve this issue，it was tedious and time-consuming. In this work，DOE was applied to study the influences of main coexisting ions，and the flame atomic absorption spectrometry was optimized based on the analysis of main coexisting elements，releasing agent selection as well as the establishment of the interference model. The results indicated that Ca²⁺，Sr²⁺，Mg²⁺，Na⁺ and Ca²⁺B had the significant interferences on lithium determination，and the sequencing was Ca²⁺＞Sr²⁺＞Mg²⁺＞Ca²⁺B＞Na⁺. The comparative study suggested that potassium oxalate showed excellent performances as the releasing agent to eliminate the influences of Ca²⁺，Sr²⁺，Mg²⁺，Na⁺ and Ca²⁺*B. And The relative error of lithium determination was reduced from -20.75% to -12.15% Meanwhile，results showed the response surface experimental design was beneficial to eliminate the influences of Na⁺，which was proved by the variance analysis and fitting degree analysis. In order to verify the conclusion further，different kinds of oil-field water were used. The results manifested the standard recovery of lithium was 89.30%~98.60% after adding potassium oxalate as the releasing agent，and the standard recovery increased to 98.88%~101.40% after the correction using the sodium interference model. All of the data indicated that the accuracy of lithium determination was improved greatly. The optimized method was not only applicable to the whole separation process of the oil-field water in Nanyi Mountain，but also applicable to other brines. And it proposed a guideline for the accurate determination of lithium for enterprises.
		2020 Vol. 40 (08): 2617-2621 [Abstract] ( 197 ) RICH HTML PDF (1021 KB) ( 57 )

	2622	Determination of Trace Impurity Elements in Zircaloy by Ion Exchange-Inductively Coupled Plasma Mass Spectroscopy
		ZHANG Liang-liang, WANG Chang-hua, HU Fang-fei, MO Shu-min, LI Ji-dong^*
		DOI: 10.3964/j.issn.1000-0593(2020)08-2622-07
		Zircaloy has been widely applied in the nuclear industry for its excellent nuclear properties，in which the impurity element content is usually controlled at a very low level. Inductively coupled plasma mass spectrometry（ICP-MS）is an inorganic mass spectrometry for the simultaneous analysis of multiple elements and has widely been used in the metallurgical analysis. ICP-MS has such advantages as simple spectrogram and high sensitivity，but inevitably there is mass spectrum interference problems，which need to be solved by other auxiliary means. Matrix separation is required for all isotopes are interfered by polyatomic ions or isobars of Zr and Sn when Cd in zircaloy was determined by ICP-MS. A method for the determination of 11 trace impurity elements including Al，B，Mg in zircaloy by ICP-MS was developed，among which 6 elements such as Cd and Mg were separated and enriched by micro cation exchange column. The potential interference of ¹¹³In on ¹¹³Cd was corrected by the interference correction equation. Other impurity elements ions were directly determined by internal standard method without separation. Impurity ions such as Cd²⁺ in dilute hydrofluoric acid were adsorbed on the cation exchange column，while Zr forms a complex anion which was not adsorbed，thus impurity ions was separated from matrix elements and got enriched. The impurity ions were eluted with hydrochloric acid and detected by ICP-MS，thereby eliminating the interference of Zr on the determination of Cd. The experimental conditions for the separation of Cd and Zr were studied，including medium acidity，leaching acidity，elution acidity，sampling concentration and flow rate. The behavior of other impurity elements under the separation conditions obtained by an optimization experiment was also investigated. The results demonstrate that Mg，Mn，Co，Cu，Pb have similar behavior of separation and enrichment to Cd and can be determined simultaneously. The final separation conditions were as follows. 2 mL sample with concentration of 50 mg·mL^-1 was pumped with a flow rate of 2 mL·min^-1 （medium acidity was 0.5% hydrofluoric acid），then leached with 0.5% hydrofluoric acid for 9 min，and finally eluted with 10% hydrochloric acid for 4.5 min. The separation period of the method is about 15 min，and detection limit were 0.005 8~0.21 μg·g^-1. The recoveries ranged from 85% to 110%，and RSD is less than 5% for each element. The 11 impurity elements in Zr-zirlo zircaloy sample of nuclear grade were analyzed by this method，and the precision and accuracy of results both meet the requirements of corresponding product standard.
		2020 Vol. 40 (08): 2622-2628 [Abstract] ( 187 ) RICH HTML PDF (2856 KB) ( 223 )

	2629	Classification Analysis and Heavy Metal Detection of Panax Ginseng Sample by Using LIBS Technology
		ZHAO Shang-yong¹, ZHOU Zhi-ming¹, SONG Chao^2, SUN Chang-kai¹, LEI Jun-jie³, GAO Xun^1
		DOI: 10.3964/j.issn.1000-0593(2020)08-2629-05
		The Panax ginseng is one of the most important commercial crop and precious medicine in northeastern China. With the rapid development of the economy, people’s living standard continuously improved, so the demand for health products also increased levels. At present, Due to the market mechanism has less of management and supervision measures, some problems of excessive pesticide residues, poor quality, confusion of quality and variety need to be solved. The heavy metal in Panax ginseng is extremely harmful to human health. The traditional analysis method of Panax ginseng classification is mainly based on the ginseng origin, shape, microscope and physicochemical properties. However, these methods have some problems, such as human factors, complicated sample pretreatment and secondary pollution, and reliable and rapid detection is not possible. In this study, laser-induced breakdown spectroscopy (LIBS) combined with the principal component analysis (PCA) algorithm model is established. A set of six habitats from five different locations, and three different part of Panax ginseng samples were used for LIBS experiment, the mean values of the LIBS spectrum (200~975 nm) were pretreated. The experiment results found that by dimensionality reduction and cluster analysis of spectral data, the PCA models have a good ability of classification for different habitats Panax ginseng the six habitates ginseng has a better classification. Finally, the quantitatively analyzed method was proposed, the limits of detection (LODs) of Pb and Cr is 9.55 and 10.86 mg·kg^-1, the RMSECV is 0.011 Wt.% and 0.023 Wt.%, respectively. It is shown that LIBS combined with PCA algorithm to the ginseng classification and heavy metal detection has good effect and foreground.
		2020 Vol. 40 (08): 2629-2633 [Abstract] ( 189 ) RICH HTML PDF (2134 KB) ( 91 )

	2634	Study on the Chemical Composition and Origin of Qingbai Porcelains in Song Dynasty Excavated From Luohe City Site
		CUI Ming-fang¹, ZHU Jian-hua^2*
		DOI: 10.3964/j.issn.1000-0593(2020)08-2634-06
		In this paper, the ancient porcelains excavated from Luohe city site in Song and Jin stratum were characterized comprehensively. The microscopic optical structures of the porcelain body reveal that they are typical south quartz and sericite porcelains. The energy dispersive X-ray fluorescence (EDXRF) spectra show that they contain high silicon and low aluminum chemical component. They were produced via unitary formulation process, and china stone might be the single raw material. Combined with the appearance of enamel and the whiteness, we concluded that they were typical Qingbai porcelains produced in the south of ancient China. As the regional feature could be disclosed by the composition of porcelain body, we compared the porcelain body and glaze of these samples with other Qingbai porcelain samples produced in the south kilns nearby at the same time via the PCA method, which provided sufficient supporting information to reveal the Qingbai porcelains’ technique level and trace the origin of these excavated porcelains. The scatter diagrams demonstrated that there were great similarities between the excavated porcelains and those produced in Hutian Kiln of Jingdezhen and Fanchang Kiln of Anhui. Further analyses based on the scatter diagrams of all chemical component implied that these excavated Qingbai porcelains were most possibly fired in Hutian Kiln, which were produced for the upper-middle class in Kaifeng. They were transported to central China by means of the ancient trade circulation. Combined with the ancient documents, the possible routine of ancient trade circulation was estimated. Our studies are of great importance to ascertain the ancient technique level of Qingbai porcelains and the routine of ancient trade circulation, as well as to establish the historical and cultural status of Luohe cite the site.
		2020 Vol. 40 (08): 2634-2639 [Abstract] ( 178 ) RICH HTML PDF (2324 KB) ( 61 )

	2640	X-Ray Fluorescence Spectroscopy Combined With Discriminant Analysis to Identify Imported Iron Ore Origin and Brand
		ZHANG Bo^1，2, MIN Hong², LIU Shu^2, AN Ya-rui^1, LI Chen², ZHU Zhi-xiu²
		DOI: 10.3964/j.issn.1000-0593(2020)08-2640-07
		Iron ore is an important raw material for the iron and steel industry. Imported iron ore with different origins and brands varies in elemental composition and content. Phenomena such as doping, adulteration and shoddy of imported iron ore are endangering the national security and economy safety, so it is necessary to establish a rapid identification model of the origin and brand of imported iron ore in major importing countries, can support the risk supervision of imported iron ore, and ensure trade facilitation. The research objects of this paper are 236 imported iron ore samples from 14 brands in Australia, South Africa and Brazil, including Pilbara Blend Fines (Lumps), Yandi Fines, Newman Blend Fines(Lumps), Jimblebar Blend Fins, Kings Fines, Fortescue Blend Fines, Kumba Standard Fines (Lumps), and Carajas Iron Ore, etc. The elemental composition and content of all research samples were determined by wavelength dispersive X-ray fluorescence spectrum standard-less analysis method, and it turned out that elements detected from iron ore samples are 24 in total, including Fe, O, Si, Ca, Al, Mn, Tb, Ti, Mg, P, K, S, Cr, Na, Sr, Zr, Zn, V, Cu, Gd, Ba, Cl, Ni, and Co. Among them, we chose 12 elements and conducted a stepwise discriminant-Fisher discriminant analysis modeling, including Fe, O, Si, Ca, Al, Mn, Tb, Ti, Mg, P, Cr, and S. Moreover, 10 elements including Fe, O, Si, Ca, Al, Mn, Ti, Mg, P, S were screened out as valid variables by the stepwise discriminant method. A two-dimensional Fisher discriminant model was thus established to realize the identification of imported iron ore from Australia, South Africa and Brazil. The recognition accuracy of the model for the modeled sample was 97.40%, the one of cross-validation was 95.30%, and that of the test sample reached 95.50%. For the 14 brands of iron ore, 10 elements including Fe, O, Si, Ca, Al, Mn, Ti, Mg, P, and S were used to establish a ten-dimensional Fisher discriminant model, and its recognition accuracy for the modeled sample was 100%. The accuracy of cross-validation was 97.90%, while one of the test samples reached 100%. Although wavelength dispersion X-ray fluorescence spectrum standard-less analysis method is a semi-quantitative analysis method, the analysis is fast and stable, wavelength dispersive X-ray fluorescence spectrum standard-less analysis method together with the stepwise discriminant-Fisher discriminant analysis can realize the identification of importing countries and brands of iron ore.
		2020 Vol. 40 (08): 2640-2646 [Abstract] ( 173 ) RICH HTML PDF (2693 KB) ( 77 )

	2647	Study on Metal Grating Structure for Improving Spectral Absorptivity of Infrared Microbolometer
		ZHANG Yu-feng¹, WANG Yang¹, WU Yuan-qing¹, DAI Jing-min²
		DOI: 10.3964/j.issn.1000-0593(2020)08-2647-04
		In order to improve the spectral absorptivity of infrared microbolometer, a metal grating absorption promoting structure based on surface plasmon was designed, and the influence of grating structure parameters on the spectral absorptivity was studied. Using the gold as grating material and the resonance structure of plasmon, the high reflectivity of metal material is overcome to enhance the infrared absorption capacity of infrared microbolometer. By changing the structure parameters of the grating and adjusting the resonance wavelength of the plasma, the spectral absorption efficiency in the working band of the infrared microbolometer can be improved. The influence mechanism of grating parameters on spectral absorptivity was analyzed by finite difference method. The regulation of the period, duty cycle, position and height of metal grating on spectral absorptivity was studied. With the grating period increasing from 2 to 5 microns, the peak wavelength of the absorption peak has a significant red shift, and the height of the absorption peak has a significant change. Although the overall trend is downward, the absorption peak at 3 microns is slightly higher than that at 2 microns. As the duty cycle of grating increases from 0.2 to 0.5, the infrared absorption peak shifts to short wavelength, and the height of the absorption peak increase gradually, but the width also narrows slightly. With the increase of grating thickness, the peak value of absorption peak is not affected very much, especially when uhe thickness increases to a certain extent, the peak value remains basically unchanged. however，the peak wavelength decreases with the increase of thickness. With the increase of thickness, the peak wavelength decreases slowly, and basically maintains near 10.6 μm. Based on the analysis of the mechanism of the influence of grating structure parameters on spectral absorptivity, the infrared absorption of vanadium oxide infrared microbolometer is greatly improved by further optimization of grating structure parameters. The average absorption of 8～14 μm is 61.6%, and the peak absorption is over 99%. The research on the absorption-promoting structure of metal grating has important guiding significance for the design of high-performance infrared microbolometer.
		2020 Vol. 40 (08): 2647-2650 [Abstract] ( 175 ) RICH HTML PDF (2244 KB) ( 50 )

	2651	Edible Oil Classification Based on Molecular Spectra Analysis With SIMCA-SVDD Method
		ZHAO Zhong^1*, LI Bin¹, WU Yan-xian¹, YUAN Hong-fu²
		DOI: 10.3964/j.issn.1000-0593(2020)08-2651-06
		Edible oil is a necessity in daily life. The nutritional value and price of different types of edible oils on the market vary a lot. Because of the spurious activities in the market, it is necessary to establish effective detection methods to classify the quality of the edible oils in the market. Traditional edible oil classification methods are usually time-consuming and requiring complex pre-treatment in the lab. Molecular spectroscopy can elucidate the sample information of both compositions and properties at the molecular level, and molecular spectra analysis has the advantages of fast speed detection and non-destructive testing for edible oil classification. Molecular spectra analysis combined with the chemometrics is becoming a popular method for rapid classification of edible oil. SIMCA (Soft Independent Modeling of Class Analogy) is widely applied to molecular spectra analysis. However, the Euclidean distance is used in SIMCA to classify the extracted features with PCA and F test. Therefore it is difficult to classify the irregular feature spaces. When the molecular spectral differences among the different types of samples are tiny such as edible oils, it is usually difficult to identify them with the traditional SIMCA method. SVDD（Support Vector Domain Description）algorithm is a support domain method for solving the one-class classification problem. SVDD can get a hypersphere to include as many objective samples as possible by solving the convex quadratic programming problem. In this work, a method of molecular spectra analysis based on SIMCA-SVDD method for rapid classification of edible oils is proposed. In order to accomplish recognition of the different types of edible oils, the attenuated total reflectance infrared spectra of four types of edible oil are scanned on ATR-FTIR. SIMCA is applied to extract the classification features T² and Q. Since the extracted edible oil classification features T² and Q distribute irregularly, instead of classification with Euclidean distance in SIMCA, Support Vector Domain Description (SVDD) is applied in this work to classify the extracted features. Since SVDD can map the extracted classification features to high dimensional space by mapping functions, then an optimal classification hypersphere can be trained to classify the irregular distributing feature spaces by solving the convex quadratic programming problem. Comparative experiments to identify the same molecular spectra samples with the proposed SIMCA-SVDD method and the SIMCA method have also been done. Comparative experiment results have verified that the classification results with the proposed SIMCA-SVDD method are obviously better than that with SIMCA. The proposed SIMCA-SVDD method has provided a new way to classify the edible oil rapidly based on molecular spectra analysis.
		2020 Vol. 40 (08): 2651-2656 [Abstract] ( 168 ) RICH HTML PDF (2167 KB) ( 95 )

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