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2024 Vol. 44, No. 05 Published: 2024-05-01

	1201	Spatially Offset Raman Spectroscopy Analysis Technology and Application in Food Subsurface Detection
		LIU Zhen-fang, HUANG Min^*, ZHU Qi-bing, ZHAO Xin, YAN Sheng-qi
		DOI: 10.3964/j.issn.1000-0593(2024)05-1201-08
		Spatially Offset Raman Spectroscopy (SORS) is a novel Raman spectroscopy technique for deep nondestructive turbid/layered media testing. Raman signals at different depths of layered materials have regular changes that contribute to detectors with the increase of transmission distance. Therefore, the SORS collects Raman spectra of offset laser points at different distances, combines the methods of optimal offset signal enhancement, subsurface spectral peak identification, subsurface signal separation, etc., to reduce the interference of the surface layer, and obtains pure Raman signals of subsurface materials. Then, the non-destructive qualitative and quantitative detection of subsurface materials is realized by the molecular specificity of Raman. This paper introduces the basic concept and measurement technology of SORS, and the analysis method of SORS and application of the technique in food subsurface inspection are described in detail. Finally, the limitations of SORS are discussed, and the future development of this field is prospected.
		2024 Vol. 44 (05): 1201-1208 [Abstract] ( 25 ) RICH HTML PDF (9453 KB) ( 49 )

	1209	Research Progress and Trends of CDs-Based Fluorescent Probes in the Detection of Fermented Foods Such as Alcoholic Beverages
		CHEN Hong-qin, YAN Meng-ru, YAN Heng, LI Yuan-lin^, HUANG Yong-guang^, CHENG Yu-xin
		DOI: 10.3964/j.issn.1000-0593(2024)05-1209-09
		Fermented food is an indispensable part of the human food chain. Due to complex raw materials, processes and strain fermentation, there are certain limitations in its rapid and intuitive analysis of flavor components, determination of harmful substances, and identification of counterfeit and inferior products. Carbon dots (CDs) are a fluorescent nanomaterial with good fluorescence characteristics, excellent biocompatibility, simple production and modifiability. As a type of detector, CDs fluorescent probes have shown great potential in food ingredient analysis, food safety detection, and food authenticity identification. Compared with large-scale detection instruments, CDs fluorescent probes have the advantages of simplicity, high sensitivity, and rapid response in the detection of fermented food. Their adjustable fluorescence characteristics and stable fluorescence signal output enable rapid extraction and conversion of key substance information in fermented food. Combined with chemical stoichiometry, they can achieve rapid in situ detection and authenticity identification of fermented food. Here, a brief overview is provided on the preparation, optical properties, and formation mechanism of CDs, with a focus on the application of CDs fluorescent probes in the analysis of flavor components, detection of harmful substances in alcoholic fermented foods, and detection of harmful substances in non-alcoholic fermented foods. Summarized the challenges faced by CDs fluorescent probes in the detection of fermented food and made prospects, further expanding the application of CDs fluorescent probes in the detection of fermented food, in order to provide a reference for the development and application of CDs fluorescent probes in the field of fermented food detection.
		2024 Vol. 44 (05): 1209-1217 [Abstract] ( 24 ) RICH HTML PDF (9723 KB) ( 28 )

	1218	Recent Advances in the Application of the Field-Portable Hyperspectral Radiometer to Characterize Materials Concerning Cultural Heritage
		WANG Cong^{1, 2}, Mara Camaiti³, LIU Dai-yun⁴, TIE Fu-de^{2, 5}, CAO Yi-jian^{5, 6*}
		DOI: 10.3964/j.issn.1000-0593(2024)05-1218-09
		Cultural heritage is the precious, non-renewable cultural resource of all humanity. Due to the preciousness of cultural heritage and also based on the basic principle of minimal intervention in heritage conservation, non-destructive analysis has always been the most important technology for materials characterization in the field of heritage science (e.g. studies on the original manufacturing process, deterioration mechanism and conservation/restoration technology). Therefore, developing and applying novel non-destructive analysis technology is an indispensable research direction in heritage science. Recently, the field-portable hyperspectral radiometer, originating from remote sensing as a light energy radiometer, has shown great application potential in analyzing heritage objects and has already been successfully applied in restoring ancient stone architecture, paintings, and others. As a non-invasive spectral technique that does not require sampling, the field-portable hyperspectral radiometer can acquire a full-band, high-resolution reflectance spectrum covering visible-near-infrared and shortwave infrared bands (350~2 500 nm) in a very short time. At the same time, it is highly portable. It can be used in the field or archaeological sites regardless of the environmental conditions. Moreover, remote sensing technology can be used to realize remote transmission and analysis of spectral data during spectral acquisition. All these characteristics are unique advantages for their application in characterizing artworks. This paper introduces the equipment type and characteristics of the field-portable hyperspectral radiometer commonly used first. The application status in the qualitative and quantitative analysis of organic/inorganic artworks, the analysis of conservation materials, and the in situ and real-time monitoring of the conservation/restoration process in the past ten years are reviewed afterwards. Then, two key problems that affect the accuracy and efficiency of using this technique are discussed in depth, i.e. the specification of spectral pre-treatment and the establishment of standard spectra databases. Finally, the development trend of this technique is forecasted. It is expected to have broad prospects in analysing fragile organic heritage objects, combining application of various analysis techniques and quantitative analysis.
		2024 Vol. 44 (05): 1218-1226 [Abstract] ( 20 ) RICH HTML PDF (10830 KB) ( 29 )

	1227	Research on Spectral Reflectance Reconstruction Sample Selection Based on NSGA-Ⅱ Algorithm
		LIN Lu, WANG Zhi-feng^*, LI Chao
		DOI: 10.3964/j.issn.1000-0593(2024)05-1227-06
		To solve the problems of heavy workload and low reconstruction accuracy caused by the large number of training samples in the process of spectral reflectance reconstruction, a sample selection method for spectral reflectance reconstruction based on the NSGA-Ⅱ algorithm was proposed. Recently, Liang et al. proposed a new method to select representative samples from many sample data. The spectral reconstruction error was defined as the product of the root mean square error and goodness-of-fit coefficient. Based on this standard, the sample with the smallest spectral reconstruction error was selected as the representative sample for spectral reflectance reconstruction. Inspired by the work of Liang et al., this method combined with the NSGA-Ⅱ algorithm to select representative samples. First, the polynomial regression algorithm and pseudo-inverse method were used to reconstruct spectral reflectance for all training samples. Then, the NSGA-Ⅱ algorithm was used to set two objective functions. One is the sum of the spectral root mean square error of the required number of representative samples; the other is the sum of the reciprocal of the goodness-of-fit coefficients, which minimizes the values of the two objective functions. All samples with Pareto level 1 selected by NSGA-Ⅱ algorithm are sorted according to the occurrence times of samples from high to low and selected as representative samples from high to low until the required number of representative samples is reached. Suppose the number of representative samples selected from the sample set with Pareto level 1 is less than the required number. In that case,the samples that appear most frequently in the next level and have not been selected are selected until the number of representative samples reaches the demand. The experiment divided 1 269 dull Munsell standard color cards into even color cards and odd color cards according to sample subscript. In the first group of experiments, Munsell odd color cards were used as the whole training samples, and 20 color blocks were randomly selected from Munsell even color cards as the test samples. In the second group of experiments, Munsell even color cards were selected as the whole training samples, and 20 color blocks were randomly selected from Munsell odd color cards as the test samples. The third group of experimental training samples is the same as the first group, and the RC24 color card is the test sample. The proposed method is compared with the three sample selection methods proposed by Mohammadi, Cao and Liang. The experimental results show that the NSGA-Ⅱ algorithm combined with polynomial regression and pseudo-inverse method to select representative samples for spectral reflectance reconstruction is superior to the existing sample selection methods in terms of root mean square error and color difference, and this method is not for a specific system has generality.
		2024 Vol. 44 (05): 1227-1232 [Abstract] ( 19 ) RICH HTML PDF (3955 KB) ( 19 )

	1233	Preparation of Silver Film Based on Odontotermes Formosanus Wings and SERS Detection of Harmful Substances
		TIAN Tian^{1, 2}, CHANG Fa-xian^{1, 2}, ZHANG De-qing^{1, 2}, SI Min-zhen^{1, 2}, YANG Yong-an^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2024)05-1233-06
		In this paper, using magnetron sputtering technology, the 3D SERS substrates (Ag/OFW substrates) were prepared by depositing silver films on the wings of Odontotermes Formosanus(commonly known as flying ants). By optimizing the preparation conditions, it was found that the substrate possessed the best enhancement effect when the deposition time was 7.5 minutes. FDTD simulation was used to analyze Ag/OFW substrate's enhancement effect with different deposition times. The results demonstrated that the substrate with the sputtering time of 7.5 min showed stronger electric field distribution; that is to say, the substrate with the sputtering time of 7.5min possessed the best enhancement effect. It was consistent with the results of using rhodamine 6G (R6G) as a probe molecule to conduct an SERS study on the Ag/OFW substrates with different deposition times. The high-performance substrate exhibited a low detection limit (LOD) of 10^-9 mol·L^-1 for R6G, indicating an excellent enhancement effect. When the Ag/OFW substrate was employed to solve critical pesticide residue problems for the detection of thiram, the detection concentration of thiram could reach 5.0×10^-8 mol·L^-1, which exceeded the detection standard of thiram solution residue (4.16×10^-7 mol·L^-1) established by China in 2021. Moreover, the detection method was expected to be used for the rapid detection of the residues of harmful substances.
		2024 Vol. 44 (05): 1233-1238 [Abstract] ( 20 ) RICH HTML PDF (12442 KB) ( 17 )

	1239	Nano-Resolution TXM-XANES Study of the Chemistry and Morphology of Lithium Battery Cathode Materials
		GAO Ruo-yang^{1, 2, 3}, ZHANG Ling^3, TAO Fen³, WANG Jun³, SU Bo^{1, 2, 3}, BI Zhi-jie⁴, DU Guo-hao³, DENG Biao^{1, 2, 3}, XIAO Ti-qiao³
		DOI: 10.3964/j.issn.1000-0593(2024)05-1239-06
		High-nickel ternary cathode materials for lithium-ion batteries are one of the research hot spots in energy storage. After multiple cycles, the internal chemical in homogeneity and morphological defects of the materials will cause battery failure and performance degradation. Understanding changes in battery capacity decay and their causes requires fast, efficient and non-destructive tests of materials. Transmission X-ray Microscope (TXM) based on synchrotron radiation is a nanometer-resolved non-destructively imaging technique for internal structure research. In recent years, with the development of high-brightness and high-performance synchrotron radiation light sources, TXM technology based on synchrotron radiation has developed rapidly, which makes TXM imaging methods have higher experimental efficiency and spatial resolution. X-ray nano-spectral imaging (TXM-XANES) is an imaging method that combines TXM with X-ray Absorption Near Edge Structure (XANES). TXM-XANES can characterize the spatial distribution and chemical state of internal elements of micron-scale energy materials on the nanoscale. It solves the problem of the lack of overall characterization due to the characterization of local regions and the characterization of the average value properties but missing local chemical state changes of materials. As a multimodal joint characterization technology based on TXM, TXM-XANES has gradually become one of the important experimental methods for energy materials research. This paper first introduces the nano-3D imaging beamline in SSRF and its TXM imaging system, then expounds the principle and characteristics of the X-ray nano-spectral imaging method. The powder LiNi_0.6Co_0.2Mn_0.2O₂(NCM622) of cathode-high nickel-layeredterary oxide material for lithium-ion batteries was characterized by spectral imaging and nano-CT methods. The spatial distribution information of Ni element chemical state and three-dimensional structure information of single particle in NCM622 single particle samples at the nanoscale were obtained. Finally, the three-dimensional x-ray nano-spectral imaging methods of battery materials are introduced and prospected.
		2024 Vol. 44 (05): 1239-1244 [Abstract] ( 20 ) RICH HTML PDF (10225 KB) ( 11 )

	1245	Study on Detection of Antibiotic Residues in Eggs by Laser-Induced Fluorescence
		CHENG Wen-xuan¹, ZHANG Qing-xian^1, LIU Yu¹, ZOU Li-kou^2
		DOI: 10.3964/j.issn.1000-0593(2024)05-1245-10
		In recent years, the issue of excessive antibiotic residues in the poultry egg industry has drawn considerable attention as a serious food safety concern. Currently, immunoassay, high-performance liquid chromatography, and microbial detection are the three primary techniques used to detect antibiotic residues in livestock and poultry products. When it comes to quick on-site sample testing, these technologies do have certain drawbacks. This study established a quick, accurate, and fast approach for detecting antibiotic residues in eggs using laser-induced fluorescence analysis. The antibiotics that might be found in chicken eggs were chosen for the samples, including ciprofloxacin, norfloxacin, ofloxacin, tetracycline, and gentamicin. The samples were created using egg white as the solvent. Antibiotic reagents were applied to imitate antibiotic residues in eggs, and the fluorescence spectra of antibiotics at various doses were examined. Euclidean distance and probability density approaches were used for the qualitative analysis, which had a 100% accuracy rate within three standard deviations. After examining samples at different concentrations, each antibiotic's calibration curves (c-S curves) were created. The results showed that within the effective detection range (ciprofloxacin: 0.000 1 to 1 mg·mL^-1, norfloxacin: 0.000 2 to 1 mg·mL^-1, ofloxacin: 0.000 05 to 1 mg·mL^-1, tetracycline: 0.000 1 to 0.2 mg·mL^-1, chloramphenicol: 0.01 to 1 mg·mL^-1), the antibiotic content could be calculated more accurately based on the net peak area of the fluorescence spectra. Ultimately, the precision and detection bound of the antibiotic quantitative curve were computed, suggesting that the technique is applicable to detect antibiotic residues in eggs; however, the high detection limit remains an issue, necessitating additional investigation to lower the detection limit.
		2024 Vol. 44 (05): 1245-1254 [Abstract] ( 17 ) RICH HTML PDF (9350 KB) ( 11 )

	1255	Vibrational Mode Analysis of Leucine and Isoleucine Terahertz Spectra
		LIU Xiao-song^{1, 2}, ZHAO Guo-zhong^1*, QU Yuan²
		DOI: 10.3964/j.issn.1000-0593(2024)05-1255-07
		As organic compounds containing an alkaline amino group and acidic carboxyl group, an amino acid is the basic unit of protein, whose type, quantity and arrangement directly affect the biological function of protein with great significance to maintain the body function. Most amino acid intermolecular vibrational modes (torsion, hydrogen bonding and collective vibrations) occur in the THz band and exhibit unique absorption characteristics. Consequently, THz spectroscopic studies of amino acids can give a more comprehensive understanding of biological properties. It was a summary of the absorption spectra of leucine and isoleucine located in the 0.2~2.6 THz band measured by previous authors, and, at the same time, the formation mechanism was explained using quantum chemical calculations. Using Gaussian09 software for single-molecule configuration simulations, the simulations were performed by semi-empirical method (PM6), ab initio method (HF, MP2) and density functional theory (B3LYP, M06-2X) combined with 6-311+G(d,p) Gaussian basis groups. Materials Studio 2019 software was used to calculate the cell configuration simulations for four density generalized gradient approximations such as PBE, PBEsol, RPBE and WC combined with plane wave basis groups. The results indicated that the single-molecule configuration simulations lacked absorption peak positions, and the peak positions were calculated differently for the same vibrational mode by different methods. So, for structures with strong intermolecular interactions, the simulation of this configuration by a single method did not correctly match the vibrational modes to a large extent and was influenced by the linear combination of atomic orbitals method. Compared to the input structure, the output structure changed from COO^- and NH⁺₃ groups to COOH and NH₂, which did not reflect the actual vibrational mode. The intra and intermolecular vibrational modes were described by the cell configuration simulation. The absorption peak positions matched well with the measured values without proton transfer. The vibrational modes of the measured peak positions were better identified. The closest results of leucine and isoleucine calculations using the PBEsol general function to the measured values indicated that full consideration needs to be given to the matching of structure and general function in the simulation, i.e., the description of the structure exchange association energy and showed the universality of the same general function for the isomers. In addition, the difference after structural optimization cannot be used as the criterion to judge functional applicability. The results of cell configuration calculation include the intermolecular vibration mode, which cannot be obtained with a single molecular configuration. Moreover, the full width at half maximum fitting leads to the difference in the vibration mode of the two configuration results at a measured peak position.
		2024 Vol. 44 (05): 1255-1261 [Abstract] ( 17 ) RICH HTML PDF (4502 KB) ( 10 )

	1262	Influence of Medium's Optical Properties on Glucose Detection Sensitivity in Tissue Phantoms
		GE Qing, LIU Jin^*, HAN Tong-shuai, LIU Wen-bo, LIU Rong, XU Ke-xin
		DOI: 10.3964/j.issn.1000-0593(2024)05-1262-07
		Due to the extremely weak blood glucose signal carried by photons transmitted through human tissues, the sensitivity of near-infrared spectroscopy for measuring blood glucose is low, making it difficult to achieve high accuracy. Therefore, ongoing research has attempted to enhance sensitivity by optimizing measurement wavelengths, distances, and other factors. However, these studies have often focused on variations in tissue absorption and scattering coefficients caused by blood glucose while neglecting the impact of the optical properties of the measured tissue itself on sensitivity. They lack comparisons between different anatomical locations to optimize measurement sites. The optical parameters of the tissue itself affect absorption and scattering changes through their influence on optical path length, affecting the coefficient of the interaction between scattering and intensity changes. Therefore, a more reasonable approach is to comprehensively consider both factors when determining glucose measurement sensitivity. This study selected four concentrations of intralipid solution (2%, 5%, 10%, and 20%) as tissue phantoms to simulate human tissue. Using Monte Carlo simulation, the study investigated glucose sensitivity within the 1 000~1 660 nm wavelength range, considering glucose's absorption, scattering, and combined effects in the four solutions. The study also explored the relationship between the sensitivity of each component and its optical parameters. The results indicate that the strongest glucose signal was detected in the 20% intralipid solution, which had the highest scattering coefficient. Based on this, the study provides a basis for site selection to achieve higher glucose sensitivity. Additionally, analyzing glucose signals within the 1 000~1 660 nm wavelength range, it was found that in the 1 000~1 350 nm range, the absorption effect of glucose could be generally ignored, and signal differences mainly stemmed from changes in scattering. In the 1 350~1 660 nm range, scattering and absorption jointly influenced the signal, with scattering contributing more significantly. The optimal measurement wavelength for scattering was around 1 450 nm while considering the combined effects of scattering and absorption, the optimal measurement wavelength was around 1 400 nm. Finally, to validate the theoretical analysis further, measurement experiments were conducted on the four solutions using six typical wavelengths within the 1 000~1 660 nm range. The results showed that the wavelength with the highest glucose signal in all four solutions was 1 409 nm, and the sensitivity of the glucose signal in the 20% intralipid solution was the highest. It indicates good agreement between experimental results and theoretical analysis. This study provides valuable insights for selecting appropriate measurement sites and wavelengths for non-invasive blood glucose detection in the human body.
		2024 Vol. 44 (05): 1262-1268 [Abstract] ( 16 ) RICH HTML PDF (4628 KB) ( 6 )

	1269	Terahertz Detection and Density Functional Theory Identify Analysis of Typical Feed Amino Acid
		LIANG Shuang^{1, 2}, WANG Ying³, ZHAO Wen-wen², ZHANG Zhi-yong¹, YUE Jian-min², LI Bin^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2024)05-1269-08
		To explore the terahertz band fingerprint properties of typical amino acids used for feeding low-protein diets to livestock and poultry and their correlation with molecular structure, this paper presents experimental analysis and theoretical vibrational calculations of six feed amino acids, including methionine, based on terahertz time-domain spectroscopy technique and Density Functional Theory (DFT). First, experimental samples of amino acids were prepared. Their terahertz absorption spectra were measured from 0.5 to 2.0 THz. It was found that methionine at 1.48 and 1.54 THz, lysine at 0.95 and 1.67 THz, tryptophan at 1.2 and 1.4 THz, threonine at 1.42 THz, histidine at 1.4 THz, isoleucine at 1.41 and 1.51 THz showed significant absorption characteristics; Then, GaussView software was used to construct the single-molecule structures of the six amino acids, and the structure was optimized by applying the B3LYP/6-311G (d, p) level of theory of DFT theory. The spectral properties of their terahertz bands were obtained through theoretical calculations. It was found that methionine at 1.51 THz, lysine at 0.89 and 1.68 THz, tryptophan at 0.67 and 1.39 THz, threonine at 1.4 THz, histidine at 1.4 THz, and isoleucine at 1.56 and 1.75 THz certain absorptionwere present. Which is consistent withthe actual experimental measurement of the absorption peaks. Finally, the vibrational modes of the six amino acids at the absorption peaks in the 0.5～2.0 THz band were analyzed by Gaussian software, and it was found that the absorption peak at 1.51 THz for methionine originated from the in-plane rocking vibration of itsmethyl group; the absorption peaks at 0.89 and 1.68 THz for lysine originated from the rotation of carboxyl group and the in-plane bending vibration of itsamino group; the characteristic peak at 1.39 THz for tryptophan originated from the out-of-plane bending of itscarboxyl group; the absorption peak at 1.4 THz for threonine originated from the out-of-plane bending of itscarboxyl group and the in-plane rocking vibration of itsamino group; the absorption peak at 1.4 THz for histidine originated from the in-plane bending of itsamino group and the overall rocking vibration; the absorption peaks at 1.56 THz for isoleucine originated from the overall rocking of its methyl groupsand amino groups and the out-of-plane rocking vibration of its carboxyl group, and the characteristic peaks at 1.75 THz originated from the overall rocking of its methyl group and out-of-plane rocking vibration of its carboxyl group. This study is a theoretical reference for the rapid qualitative and quantitative studies of typical feedamino acids using terahertz spectroscopy.
		2024 Vol. 44 (05): 1269-1276 [Abstract] ( 20 ) RICH HTML PDF (14473 KB) ( 44 )

	1277	Mid-IR Laser Absorption Diagnosis on Flow Characteristics for Mars Entry
		ZENG Hui, WEN Peng, YANG Guo-ming, ZHU Xing-ying, OU Dong-bin
		DOI: 10.3964/j.issn.1000-0593(2024)05-1277-06
		The Mars exploration mission is important to the national deep space exploration project. The successful landing of “Tianwen” on Mars in 2021 is a big step forward in China's space exploration and research on Mars. The Martian atmosphere is mainly dominated by carbon dioxide, and the surface pressure is much lower than the Earth's. Due to the differences in atmospheric composition and entry orbit, the thermal environment of Mars entry vehicles is very different from that of Earth space vehicles. The entry process involves a non-air high-speed flow, leading to serious aerothermal heating problems. The arc-heated wind tunnels are used to simulate the aerothermal heating environment for Mars entry, which is a key step in validating the thermal protection system design for Mars exploration. The -high-temperature flow simulated by the arc-heated wind tunnel includes a dominated CO₂ dissociation reaction, and dissociation species such as CO interact with the thermal materials of the Mars entry vehicles, which would cause a catalytic effect and significantly affect the aerothermal environment. In this paper, the mid-infrared quantum cascade laser absorption spectroscopy is carried out for in-situ and quantitative measurements of the flow characteristics of ground-based simulation for Mars entry in the arc-heated facility. The in-situ diagnosis in the arc-heated facility utilizes the spectral line of CO with a central wavelength of 2 212.625 cm^-1 (ν″=0, R(19)) near 4.5 μm, to achieve a high signal-to-noise ratio measurement of the ground-based flow field. A single-line direct absorption spectroscopy obtains the static temperature and CO mole fraction of free stream in the arc-heated wind tunnel. Under a typical condition for Mar entry, the static temperature and CO mole fraction of freestream remain stable throughout the operation, showing good stability in the arc-heated flow field. Six repeated experiments show that the static temperature and CO mole fraction are in the range of （1 757±69） K and （0.189±0.027） respectively, with fluctuation of less than or equal to 3.9% in flow temperature and fluctuation of less than or equal to 14.3% in CO concentration, demonstrating great repeatability for the ground-based simulated flow field. The developed mid-infrared laser absorption spectroscopy diagnostic technology in the arc-heated wind tunnel can provide refined measurement capabilities for research of the aerothermal environment and ablation-catalytic properties of the thermal protection materials of the Mars entry vehicles.
		2024 Vol. 44 (05): 1277-1282 [Abstract] ( 15 ) RICH HTML PDF (2773 KB) ( 11 )

	1283	Spectral Ripple Algorithm Based on Asymmetric Polynomial Fitting
		SUN Sheng-lin, XU Hong-jie, YANG Sheng-min, FANG Jia-hao, LIANG Jia-hui
		DOI: 10.3964/j.issn.1000-0593(2024)05-1283-08
		Super luminescent diode (SLD) and amplified spontaneous emission (ASE) light sources are often used in fiber optic gyroscopes. Their wide spectrum can effectively suppress the influence of polarization noise, back reflection and Rayleigh scattering. Ripple, as an important index in SLD and ASE light sources, mainly coming from the laser part of broadband light source that is not completely suppressed, impacts the accuracy of fiber optic gyroscope. In the military standard, ripple is defined as the range of mode amplitude near the peak wavelength of the spectral curve, with dB as the unit. At present, ripple measurement is mainly based on the logarithmic spectrum observed by human eyes. However, in human eye observation, the subjective factors of a human and the external interference may lead to subjectivity and contingency of the results, and measurement errors cannot be ruled out. Additionally, the spectrum in logarithmic coordinates cannot accurately reflect the spectral characteristics. Because of this, the present study analyzed the ripple in the asymmetric spectrum of the broadband light source, compared the advantages and disadvantages of multi-peak Gaussian fitting and polynomial fitting. Finally, adopted the polynomial fitting method. Through theoretical analysis and experimental verification, it was revealed that the quintic polynomial fitting can meet the requirements. Besides, a new method which can precisely calculate the ripple based on the triple standard deviation principle was proposed. AQ6370D spectrometer and a self-made “Spectral Ripple Fitting” software were utilized to experiment with ASE and SLD light sources, and the results obtained were in good agreement with the observation data of human eyes. On this basis, repeated validation experiments were carried out, the five experimental data of the same light source were recorded, and their ripple coefficients were calculated respectively. Compared with the human eye observation results, the experimental results demonstrate that the spectral ripple coefficient algorithm can well eliminate the influence of subjectivity and contingency, indicating that it is feasible. With the self-made “Spectral ripple Test” software, the average wavelength, peak wavelength, center wavelength, spectral width, ripple, linear coordinates and logarithmic coordinates of the spectrum and their fitting curve expressions can be obtained on the interactive interface, which makes the experimental analysis more convenient and speedy, thus significantly improving the experimental efficiency. It has been proved that the spectral ripple algorithm based on asymmetric polynomial fitting proposed in this paper can effectively judge the light source ripple, improve the calculation efficiency, and eliminate the influence of subjectivity and contingency, showing a broad application prospect. Furthermore, it is a supplement to the national military standard as well.
		2024 Vol. 44 (05): 1283-1290 [Abstract] ( 20 ) RICH HTML PDF (13022 KB) ( 12 )

	1291	Research of Induction Delay Line Anode Photon Counting Detector
		ZHANG Rui-li¹, LIU Yong-an¹, ZHANG Ya-long^{1, 2}, YANG Xiang-hui¹, LIU Zhe¹, SU Tong¹, ZHAO Bao-sheng¹, SHENG Li-zhi^1*
		DOI: 10.3964/j.issn.1000-0593(2024)05-1291-06
		In this paper, we developed a photo-counting imaging detector based on the delay-line anode with induction readout, which has the advantages of high sensitivity and large detective area features. This novel detector is expected to be used in space astronomy, bioluminescence and spectral measurement applications. This detector consists of a microchannel plate (MCP) , position-sensitive anode and readout. Among these key parameters, the performance of position-sensitive anode decides the performances of detectors to a large extent. As a charge induction readout delay line anode, the delay line anode decodes the position information of the incident photon by measuring the time delay between two ends of a propagation line. The detector with the anode can obtain high detection sensitivity and a large imaging area. Image charge pickup anode is placed outside the sealed vacuum tube, which not only simplifies the process difficulty of anode production but also improves the detector's reliability. Firstly, An inductive readout delay line anode was designed. We analyzed the influence of different thicknesses and mediums material of the detector on the induction charge of the position-sensitive anode. Then, a method is used to tackle the induction charge of different layers unbalance issue. After that, we designed and fabricated a 40 mm×40 mm position-sensitive anode. The experiment results indicate that the transmission attenuation of the anode output is less than 10%, and the inter-pole crosstalk is less than 3%. Finally, we implemented aphoton-counting imaging experimental system based on this anode. This experimental system provides better than 150um spatial resolution and can promote the theoretical and practical development of large-area array and highly sensitive detector for space astronomical UV spectrum measurement.
		2024 Vol. 44 (05): 1291-1296 [Abstract] ( 17 ) RICH HTML PDF (23655 KB) ( 4 )

	1297	Analysis and Calculation of Escape Peaks in Silicon Drift Detectors
		LIAO Xue-liang, LIU Ming-bo, CHENG Da-wei, SHEN Xue-jing
		DOI: 10.3964/j.issn.1000-0593(2024)05-1297-04
		During the detection process, the silicon drift detector (SDD) used in energy-dispersive X-ray fluorescence spectrometry will form escape peaks on the low-energy side of the solid characteristic peaks generated by the individual elements to be measured with high content, and the corresponding characteristic peaks are also will lose some strength, and the location of the escape peak is related to the composition of the detector. The energy difference between the incident characteristic peak and the escape peak in the SDD detector is 1.739 keV, which is equal to the Ｋ_α characteristic energy of the silicon element. The intensity of the escape peak is proportional to the intensity of the incident X-ray, that is, proportional to the content of the corresponding element/characteristic peak intensity. The escape probability of the incident characteristic peak is usually low, and the influence on the test results is small when the escape peak intensity is low. It can be seen from theoretical calculations that the probability of generating escape peaks is related to the detector angle and element types, and with the increase of the incident characteristic line energy, the mass absorption coefficient of the silicon atom and the corresponding escape peak generation probability will also reduce. When the escape peak coincides with the characteristic energy peaks of other elements to be measured, it will interfere with the accurate measurement of the corresponding element, especially when the content of the element to be measured is low. The interference will be relatively more significant. Therefore, it is necessary to calculate and correct the escape peak accurately. In this paper, a corresponding platform is built for testing, and taking Fe and Mn elements as examples, through theoretical analysis and calculation of the escape peak probability in the SDD detector and compared with the escape probability value obtained from the actual test spectrum, it is found that the two data are in good agreement, and after the comparison it was found that the escape peak of Fe∶Ｋ_β line in Fe₂O₃ sample overlapped with Cr∶Ｋ_α peak, and the escape peak of Fe∶Ｋ_α line partially overlapped with Ti∶Ｋ_α peak. After deducting the escape peak, Cr and Ti can be better analyzed for accurate quantification. This method can be extended to the calculation and correction of escape peaks of other elements with higher content, especially in the application of multi-element detection in samples with high content of individual elements such as soil, mineral, alloy detection, etc, and improve the test accuracy of X-ray fluorescence method.
		2024 Vol. 44 (05): 1297-1300 [Abstract] ( 18 ) RICH HTML PDF (2417 KB) ( 12 )

	1301	Green-Light Emitted Nanocomposites of Gd, N-Doped Carbon Dots/Hydrotalcite for Recognition of Latent Fingerprints
		ZHANG Xing-fu¹, ZHANG Xiao-tong¹, LI Da-wu², YOU Nan^1, DING Bao-hong^1
		DOI: 10.3964/j.issn.1000-0593(2024)05-1301-06
		Carbon dots (CDs) areone of the green nano-fluorescent agents. Suspension of CDs can show good fluorescence performance. However, aggregation-induced quenching effects in solid-state CDs can lead to the disappearance of the fluorescence properties of CDs powder, which limits their practicability. In this work, CDs are obtained by doping other elements in CDs to change fluorescent wavelength and color to improve the contrast between the LFPs and the substrate backgrounds. Another improvement is the good dispersion of CDs on the surface of low-cost hydrotalcite for avoiding the occurrence of fluorescence quenching. Herein, Gd/N-doped CDs (Gd/N-CDs) are obtained using tartaric acid as carbon source, triethylenetetramine as nitrogen source, and GdCl₃ by hydrothermal method, and then green emissive nanocomposite has been synthesized by depositing the Gd/N-doped carbon dots into hydrotalcite (Gd/N-CDs@H) via hydrothermal process for the recognition of LFPs. The good dispersion of the nano-sized Gd/N-CDs on the surface of hydrotalcite overcomes the fluorescence quenching of the Gd/N-CDs in the solid-state and can enhance the solid-state fluorescence. The Gd/N-CDs@H emits stable, strong green fluorescence and exhibits vivid images of LFPs on various substrates such as glass slides, copper foil, tiles, plastic, aluminum foil and paper. The high-level details of ridge patterns of fresh and aged LFPs can be clearly identified with good clarity and high contrast without background interferences under an excitation of 450 nm light source.
		2024 Vol. 44 (05): 1301-1306 [Abstract] ( 18 ) RICH HTML PDF (38967 KB) ( 9 )

	1307	*Determination of Mineral Elements and Dissolution Characteristics in Lycium Ruthenicum* Murray**
		ZHANG Chen-ling, HAN Mei^*, LIU Jia, JIA Na, LIU Bing-bing, ZHANG Yong-tao
		DOI: 10.3964/j.issn.1000-0593(2024)05-1307-05
		Lycium ruthenicum Murray (Solanaceae Lycium) is rich in various mineral elements, which have extremely important biological effects on the growth and development of human beings. Lycium ruthenicum Murray is a homologous substance used in medicine and food. It is necessary to analyze its dissolution characteristics and correlation analysis to understand its nutritional value and seek healthy diet guidance and further utilization. In this study, Lycium ruthenicum Murray was pretreated using the microwave digestion method and the pure water extraction method. Digestion solutions were prepared using a microwave digestion apparatus using nitric acid and hydrogen peroxide as digestion acid. Soaking solutions were prepared with pure water at different temperatures. Contents of mineral elements, including K, Na, Ca, Mg, Zn, Fe, Mn, Cu, Li and Sr, were determined by inductively coupled plasma optical emission spectrometry (ICP-OES), and the dissolution characteristics and correlation analysis of mineral elements were studied then. Under the optimal working conditions of microwave digestion and the spectrometer, a good linear relationship (r>0.999 5), lower detection limit (LOD<0.01 mg·L^-1), and high accuracy and precision were obtained. Recovery rates of the elements were between 97.2% and 101.8%, with a relative standard deviation (RSD) lower than 1.99%. The results showed that beneficial mineral elements are rich in Lycium ruthenicum Murray. It is high in K, followed by Na, Ca and Mg, then Fe, Li and Sr, and lower in Mn, Zn and Cu. The K/Na value in Lycium ruthenicum Murray is greater than 8. Moreover, it proved that Lycium ruthenicum Murray is a typical food with high potassium and low sodium. Ca, Mg, Fe, Zn, Li, Sr, Mn and Cu are also important components of various enzymes, hormones and vitamins in the human body. Lycium ruthenicum Murray is certified as an ideal food. Li content is not obviously correlated with Ca, Zn, and Fe content in the soaking solutions. Mg content is not obviously correlated with Zn content. Besides, other correlations between one content and another were significantly positive or extremely significant positive. It showed that there was no obvious antagonism in the mineral elements. The dissolved amount of minerals in the soaking solutions increased with the brewing time and brewing temperature. The extraction temperature of 40℃ and boiling water, and extraction time of 5, 10 and 20 min were selected to study the influence of extraction temperature and time on the dissolution rate. K, Na and Zn have the highest dissolution rates among the then elements. Although contents of Ca, Mg, Sr, Mn and Cu vary greatly from each other, the dissolution rates are similar, which may be due to the same valence states and the similar extraction efficiency. The dissolution rate of Li is greatly affected by the extraction temperature, and the dissolution rate in boiling water is 1.5~2 times that in 40 ℃ water with different extraction duration. The content of Fe in trace elements is the highest, but the dissolution rate is the lowest, mainly because Fe is combined with proteins and is difficult to extract. The study could provide reliable evidence for a healthy diet and the further utilization of Lycium ruthenicum Murray.
		2024 Vol. 44 (05): 1307-1311 [Abstract] ( 20 ) RICH HTML PDF (892 KB) ( 11 )

	1312	Research on Fast ICA Blind Separation Algorithm of Mixed Hyperspectral and Influencing Factors
		DAI Jia-le, WANG Jin-hua^*, LI Meng-qian, HAN Xiu-li, MIAO Ruo-fan
		DOI: 10.3964/j.issn.1000-0593(2024)05-1312-09
		Hyperspectral analysis of mixtures is a key technology for nondestructive testing of minerals. The spectral reflectance variation of mixtures in the 350 nm to 2 500 nm interval is regarded as a one-dimensional sequence signal with time-domain variation, and the mixture spectral separation is transformed into a blind source separation problem of time-domain signals in the paper. In order to analyze the influencing factors of the speed and accuracy of mixture spectral demixing, a blind source demixing test was conducted on the measured hyperspectral reflectance curve of the mixture using Fast ICA mathematical model, and the results of spectral demixing were analyzed from three aspects of the demixing process: the whitening mode, the initial power array, and the Gaussianity of the source spectrum, which provided a research basis for the later analysis of the mixture spectral detection. The chemically pure copper oxide and cuprous oxide mixtures, alkaline copper carbonate and copper hydroxide mixtures were selected as test objects. The source spectral Gaussianity was compared with the g-function, ZCA and PCA whitening methods, and three initial weights of unitary, random and specified weights on the unmixing spectral results using the unmixing performance index PI, the root mean square error of the spectrum and the angular distance of the spectrum as evaluation indexes. The experimental results show that the Fast ICA algorithm can effectively separate the mixture component source spectra based on unknown hyperspectral a priori information of mixed minerals. The sample separation accuracy PI values are all less than 0.18, and the effect of spectral blind source unmixing is remarkable. The spectral curves after unmixing are consistent with the source spectral curves in terms of characteristic trends, with the same absorption positions and characteristic peaks, but there are certain scale differences. In addition, the Gaussianity of the source spectrum and the selection of the unmixing g function directly affect the value of the unmixing results, and the separation accuracy of the sub-Gaussian interval curve is better than that of the super-Gaussian part. The absorption characteristics of the segmental demixing results based on Gaussianity are prominent, and the difference with the reflectance values of the source spectra increases; the whitening method of spectral preprocessing has a small impact on the accuracy of the demixing results, and the separation accuracy and spectral accuracy of the demixing results are slightly higher after ZCA whitening than PCA whitening; the comparison of the demixing results of the three initial weights of the Fast ICA model shows that the initial iterations with In the comparison of the three initial weights of the Fast ICA model, it was found that the separation accuracy, demixing accuracy and demixing time were the best and the demixing process was easier to converge when the specified weights calculated by the first iteration were used for the iterative demixing. The results show that the g-function is selected according to the full-band Gaussian performance to demix the best. The separation index PI is less than 0.14, the spectral angular distance is about 0.1, ZCA whitening has less effect on the demixing spectrum than PCA whitening, the separation index of the two groups of mixtures after ZCA whitening is about 0.1, and the separation index PI of PCA whitening is higher than 0.13 when the designation right is used as the initial weight, it helps to improve the convergence speed in the Newton iteration, so that the unmixing spectrum is closer to the known spectrum of the components, the unmixing time of the specified weight is less than 0.2 seconds, and the other two weighting methods are more than 0.3 seconds.
		2024 Vol. 44 (05): 1312-1320 [Abstract] ( 17 ) RICH HTML PDF (14581 KB) ( 5 )

	1321	Application of Fluorescent Probe Tetraphenyl-1,3-Butadiene in the Detection of Antibiotics
		WANG Rui¹, ZHENG Lu-ying¹, HU Bo¹, ZHANG Xin-yu², ZHAO Si-si^1, ZHANG Hang^1
		DOI: 10.3964/j.issn.1000-0593(2024)05-1321-09
		Antibiotics have the advantages of strong antibacterial activity and low cost and have been widely used in production and daily life. However, the abuse of antibiotics may lead to their accumulation in the human body or food, causing public health problems such as ototoxicity, nephrotoxicity, allergic reactions, and bacterial resistance. Therefore, this article selects fluorescence detection techniques with advantages such as high sensitivity, good selectivity, simple preparation, fast speed, and practical sample detection, which are significant for improving food safety and rational drug use. Based on the application of fluorescence technology in detecting antibiotics, this article selects tetraphenyl-1,3-butadiene (TPB), a typical representative with AIE effect, which has advantages such as stable chemical properties, good luminescence performance and is not limited by solution conditions. It is made into a fluorescence probe to explore the photochemical properties of TPB and the impact of antibiotics on its quenching effect. The research results show that the maximum excitation wavelength of TPB is 365 nm, and the maximum emission wavelength is 435 nm. TPB has strong fluorescence characteristics. At an excitation wavelength of 365 nm, the quantum yield of TPB is 51.9%. When the water volume fraction is 80%, the fluorescence effect of TPB is the best. The fluorescent probe TPB has high selectivity and strong anti-interference ability to tetracycline antibiotics. Tetracycline antibiotics have a high quenching effect on TPB, which meets the condition of fluorescence internal filtering effect, while sulfonamides and quinolones have a poor quenching effect on TPB. The fluorescence intensity of the system decreases with the increase of tetracycline hydrochloride concentration, and there is a strong correlation. The linear regression equation is y=-1.338x+984.20, and the detection limit is 0.042 7 mmol·L^-1; When pH≤7, the quenching effect is better; After adding tetracycline hydrochloride solution, the fluorescence intensity of the lake water, sea water and milk system was significantly weakened, and the change of the fluorescence intensity could indirectly reflect the change of the concentration of tetracycline antibiotics solution. This article explores the quenching of TPB by antibiotics, and the detection of antibiotic residues in the environment and food is of great significance, providing a reference for human governance of residual antibiotics in the food and environment.
		2024 Vol. 44 (05): 1321-1329 [Abstract] ( 18 ) RICH HTML PDF (4572 KB) ( 13 )

	1330	The Distributions and Spectral Characteristics of Molecular Weight-Fractionated Dissolved Organic Matter Derived From Mushroom Residue and Rice Straw Compost
		CHENG Ao¹, CHEN Dan¹, REN Lan-tian², JI Wen-chao^{1, 3}, FAN Xing-jun^{1, 3*}, LIU Xiao-long¹, YU Xu-fang¹
		DOI: 10.3964/j.issn.1000-0593(2024)05-1330-08
		Molecular weight (MW) is an important factor affecting compost DOM's chemical properties and environmental behavior. However, the current understanding of the MW distribution of compost DOM still needs to be clarified. This study employed ultrafiltration to separate the different MW fractions from the DOM in mushroom residue compost (MRC) and rice straw compost (RSC). Subsequently, different compost-derived MV fractions' distributions and spectral characteristics were comprehensively investigated. The results of the dissolved organic carbon (DOC) revealed that HMW DOM (>10 kDa) was the major fraction in MRC and RSC, accounting for 80% and 71% of DOC, respectively. Meanwhile, MMW DOM (5~10 kDa) and LMW DOM (<5 kDa) represented 12%~15% and 9%~15% of the total DOC, respectively. These findings suggested that HMW DOM would play a crucial role in determining DOM's chemical composition and molecular structure in compost. Moreover, the results of spectral characteristic parameters, such as SUVA254, E₂/E₃ and HIX, indicated that the degree of aromatization and humification of MW DOM showed a similar trend in the order of HMW>MMW>LMW. In contrast, the BIX and FI values showed an opposite distribution. These findings evidenced that HMW DOM enriched in unsaturated conjugated structures, such as aromatic rings, while MMW and LMW DOM contained high autogenetic contributions. The three-dimensional fluorescence-parallel factor analysis demonstrated that the compost DOM and its MW fractions were primarily composed of three types of humus (C1—C3) and one protein (C4). HMW DOM in MRC and RSC consisted mainly of long-wavelength humic acid (C3), which accounted for 34% and 85% of the total fluorescence intensity of HMW fractions in MRC and RSC DOM, respectively. MMW and LMW DOM were mostly composed of fulvic acid (C1, 41%~53%) and short-wavelength humic acid (C2, 25%~36%). The infrared spectroscopy (FTIR) analysis showed that the HMW DOM contained more hydrophobic benzene ring structures. In contrast, MMW and LMW fractions contained more hydrophilic oxygen-containing functional groups, such as carbonyl and carboxyl groups. Overall, our findings advanced the understanding of the chemical composition and molecular structure of compost DOM and provided crucial data for further evaluation of the maturation, stabilization, and environmental behavior of compost.
		2024 Vol. 44 (05): 1330-1337 [Abstract] ( 21 ) RICH HTML PDF (5522 KB) ( 7 )

	1338	Spectral Pattern Recognition of Erasable Ink Based on Hilbert Filter
		WANG Xiao-bin, ZHANG Ao-lin, ZOU Ying-fang, YANG Lei
		DOI: 10.3964/j.issn.1000-0593(2024)05-1338-08
		The authenticity of documents is an important work in the current stage of litigation review. In judicial cases, erasablepens are often used to forge documents, contracts and other criminal acts. The identification of ink composition and handwriting modification is the key research in the field of document inspection. Special thermal color pigment is the main component of erasable ink; its color principle is that temperature change will produce the disappearance and recurrence of handwriting, color fades above 65℃, and color recurrence below -18 ℃. The identification of its species can identify the authenticity of the case evidence and provide support for the litigation process of the case. The ultra-high spectral resolution of hyperspectrum has good feature selectivity for polymer materials, which can effectively collect data for common ink components. In this experiment, a total of 45 erasable pen ink samples from 22 brands were collected, which can be divided into four types: tungsten carbide pen beads, bullet pen beads, full needle tube and half needle tube, and the hyperspectral information of 450~950 nm band was collected uniformly. As for the redundancy of background noise in spectral data, the principal component analysis (PCA) was used to reduce the dimensionality of the data and extract the feature variables. Based on the dimensionality reduction data, different Hilbert transform (HT) types were used for signal filtering, and effective signals were further selected to improve the modeling effect. Two artificial neural network models, Multilayer Perceptron (MLP) and radial basis function neural network (RBFNN), were selected for sample recognition. The feature variable class modeling accuracy based on 23-dimensional principal component extraction is 81% and 84%, respectively. After the Hilbert high-pass filtering processing, the classification accuracy can be increased to 88.9% and 92%, effectively improving recognition accuracy. In order to further distinguish the types of different samples, Fisher discriminant analysis method was selected for modeling. The identification accuracy of the original data of each sample in the FDA model was 44%, and the FDA modeling accuracy of the optimal PCA-HT treatment was 93.3%, which could distinguish different types of erasable ink. The results show that PCA can reduce the dimension based on retaining the effective spectral information, improving the model accuracy and shortening the running time. Compared with the original spectral data, the modeling effect is good, and the spectral data after the Hilbert transform can further improve the effective spectral information to further improve the modeling accuracy. This experiment determined the optimal PCA-HT-FDA model and the best erasable ink hyperspectral identification model, which can provide a certain reference for forensic experts.
		2024 Vol. 44 (05): 1338-1345 [Abstract] ( 16 ) RICH HTML PDF (13155 KB) ( 5 )

	1346	Non-Destructive Near-Infrared Spectroscopy of Physical and Chemical Indicator of Pork Meat
		LIU Yu-ming^{1, 2, 3}, WANG Qiao-hua^{1, 2, 3*}, CHEN Yuan-zhe¹, LIU Cheng-kang¹, FAN Wei¹, ZHU Zhi-hui¹, LIU Shi-wei¹
		DOI: 10.3964/j.issn.1000-0593(2024)05-1346-08
		China is the world's largest pork producer and consumer. The quality of pork affects the quality of protein intake for people. There needs to be more effective rapid non-destructive testing methods to cope with the huge testing needs. In order to rapidly determine volatile salt nitrogen (TVB-N), pH and moisture content of frozen pork and to propose a new method for pork quality testing, this paper uses near-infrared spectroscopy combined with chemometric methods to establish mathematical models for TVB-N, pH and moisture content of frozen pork. The NIR spectral data were collected and combined with chemometric tests to obtain the measured values of TVB-N, pH and moisture content. ~5 000 cm^-1 region, while the absorption peaks around 8 600～8 450 cm^-1 were significantly smaller than the other absorption peaks. The SPXY (sample set partitioning based on joint X-Y distances) algorithm was used to partition the data set into a training set and a test set in the ratio of 3∶1. The abnormal data were removed using Monte Carlo cross-validation (MCCV) and a partial least squares regression (PLSR) was used to establish The regression relationships of TVB-N, pH, water content and full-band spectral information were established by partial least squares regression (PLSR), and the raw spectra were pre-processed using data centering, Savitzky-Golay(S-G) first-order derivatization, S-G second-order derivatization, direct difference second-order derivatization and multiple scattering corrections to explore the appropriate pre-processing methods. The results show that the data centering, direct differential second-order derivation and second-order derivation achieve good experimental results, so the combination of competitive adaptive reweighted sampling (CARS), uninformative variables elimination (UVE), and multiplicative scatter correction (MSC) has been applied. The PLSR feature band model was developed and analysed by combining the competitive adaptive reweighted sampling (CARS), uninformative variables elimination (UVE) and successive projections algorithm (SPA). The results showed that the prediction models for TVB-N, pH and water content had excellent performance when the structures were data centered-CARS-PLSR, direct difference second-order derivative-CARS-PLSR and second-order derivative-CARS-PLSR, respectively, where the training set correlation coefficients R_C were 0.947 1, 0.998 8 and 0.997 1, respectively, and the root mean square errors (RMSE) were 1.208 8, 0.008 7 and 0.001 5, respectively; the test set correlation coefficients R_P were 0.927 5, 0.963 0 and 0.945 9, respectively, and the RMSE were 1.683 6, 0.051 7 and 0.005 6, respectively. In summary, it can be seen that the NIR band region is significantly correlated with pork TVB-N, pH and moisture content, and the use of NIR spectra can The NIR spectra can be used to predict TVB-N, pH and moisture content in pork accurately.
		2024 Vol. 44 (05): 1346-1353 [Abstract] ( 23 ) RICH HTML PDF (6600 KB) ( 16 )

	1354	Simultaneous Determination of Five Banned Sartan Compounds in Antihypertensive Health Food Using Thin-Layer Chromatography Combined With Surface-Enhanced Raman Spectroscopy (TLC-SERS)
		HUANG Li-jun¹, ZHUANG Shun-qian², FENG Yong-wei¹, YANG Fang-wei², SUN Zhen¹, XIE Yun-fei^2*, XUE Qing-hai¹
		DOI: 10.3964/j.issn.1000-0593(2024)05-1354-10
		Due to the current unhealthy diet structure and lifestyle habits, as well as the aging population and other factors, the incidence of chronic diseases such as hypertension is gradually increasing, and people gradually favor antihypertensive health food. However, in order to improve the efficacy of healthy food, there are unscrupulous businessmen in the market who illegally add antihypertensive drugs, especially sartans antihypertensive drugs, to healthy food. Based on the above phenomenon, this study established a Thin-Layer Chromatography (TLC) and Surface-enhanced Raman spectroscopy (SERS) method to investigate five possible prohibited ingredients of sartans (Olmesartan Medoxomil, Irbesartan, Losartan potassium, Telmisartan and Valsartan) in antihypertensive health food products. In this study, we investigated the optimal conditions for the SERS detection of five drugs, compared the effects of TLC spreaders with different ratios of different components on the separation of the five drugs. We successfully obtained the separation system of cyclohexane-ethyl acetate-methanol-glacial acetic acid=53∶35∶12∶0.25 (v/v/v/v) after extensive formulation tests. After determining the exact conditions of this experiment, the preliminary separation of drug standard solution, mock positive sample solution and real sample solution was carried out by using TLC separation technique. After separation, gold gel was added dropwise at the spot in situ with different ratio shift values on the thin layer plate for SERS detection. The SERS spectra of drug standard solution as well as mock positive sample solution at the spot in situ were collected, compared and determined. The results showed that the five prohibited additive ingredients of sartans could be clearly separated by TLC, their SERS spectra were consistent and reproducible, and the qualitative analysis could be performed quickly according to their respective characteristic peaks, with detection limits between 0.1 and 1 mg·kg^-1. The TLC-SERS method established in this study is simple and rapid. It can provide a reference for the simultaneous on-site rapid detection of prohibited added ingredients in health food.
		2024 Vol. 44 (05): 1354-1363 [Abstract] ( 20 ) RICH HTML PDF (19417 KB) ( 4 )

	1364	Early Apple Bruise Detection Based on Near Infrared Spectroscopy and Near Infrared Camera Multi-Band Imaging
		YANG Zeng-rong^{1, 2}, WANG Huai-bin^{1, 2}, TIAN Mi-mi^{1, 2}, LI Jun-hui^{1, 2}, ZHAO Long-lian^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2024)05-1364-08
		Early light bruising in apples is an important factor affecting apple quality. Since early minor bruises cannot be identified by the naked eye in visible light, and in order to control the time of bruise production, a red Fuji apple was selected as the research object, and different degrees of apple bruises were artificially created through an inverted pendulum device. To find an efficient method to identify early minor apple bruises, Fourier transforms near-infrared spectrometer was first used to collect near-infrared diffuse reflectance spectra of 80 undamaged samples, 60 lightly damaged samples, and 60 heavily damaged samples at 0, 10, 20 and 30 min post-damage, respectively. SNV is used as the spectral data preprocessing method. The spectral range is 4 000~9 000 cm^-1, and the number of principal components is 9. The “Nondestructive-damage” classification model is established by partial least squares -discriminant analysis (PLS-DA) and support vector machine (SVM) respectively. The average recognition rate of the prediction set was 85.00% and 89.80%, respectively, and the model recognition effect needs to be improved. Based on the above experimental results, the NIR images of apples with no damage, light bruise, moderate bruise, and severe bruise of 100 apples were acquired by using NIR cameras with a wavelength range of 1 000 to 2 350 nm. The NIR images of these apples were acquired again with the addition of 1 150 and 1 400 nm filters, respectively. 1 200 images of apples in 3 bands and 4 bruise levels were acquired. The image absorbance information was extracted, and KNN, SVM, and DT classification models were built respectively. The highest recognition rates of 99.00% and 94.67% were achieved by the “nondestructive-damage” classification model and the “nondestructive-mild damage-severe damage” classification model using the DT method, respectively. Compared with the NIR spectroscopy method, the NIR camera multi-band imaging method has higher recognition accuracy in applying both early bruises and bruise degree classification on apple surfaces. At the same time, the NIR camera imaging method is convenient for determining the location of the bruise, which provides a fast and efficient new idea for real-time online detection and classification of bruises on apple surfaces.
		2024 Vol. 44 (05): 1364-1371 [Abstract] ( 20 ) RICH HTML PDF (15692 KB) ( 12 )

	1372	Mineralogical and Spectral Characteristics of Azurite Ores From Different Origins
		XU Cui-xiang¹, CHEN Yu-di², ZOU Tao², YANG Ying²
		DOI: 10.3964/j.issn.1000-0593(2024)05-1372-07
		Azurite is a copper-containing carbonate mineral that occurs in the oxidation zone of copper deposits. It is a secondary mineral, and its presence can serve as an indicator for searching primary copper deposits. There is relatively little spectroscopic research on azurite by domestic scholars, and the comparison of mineralogical and spectroscopic characteristics of azurite from different famous locations worldwide is an area that has not been explored. In this paper, the composition, structure, and spectroscopic characteristics of two samples of azurite from China (Liufengshan, Anhui; Yangchun, Guangdong) and two samples from foreign locations (Vietnam, Australia) were analyzed and discussed using scanning electron microscopes(SEM), X-ray diffraction (XRD), simultaneous thermal analysis (STA) and Fourier transform infrared spectrometer (FTIR). The energy dispersive elemental analysis results show that the main elements in all four mineral samples are C, O, and Cu. X-ray diffraction results indicate that, except for the sample from Liufengshan, Anhui, the X-ray diffraction phase analysis of the other three samples from different locations correspond to azurite Cu₃(OH)₂(CO₃)₂. In addition to the diffraction peaks of the main phase azurite, diffraction peaks were also detected at other positions in the sample from Liufengshan, Anhui, indicating the presence of the second phase malachite CuCO₃·Cu(OH)₂ in the sample. From the thermal analysis curve obtained from synchronous thermal analysis, it can be observed that there are mainly two weight loss stages. The weight loss before 300 ℃ may be attributed to the decomposition of a small amount of malachite in azurite, while the weight loss between 300 ℃ and 600 ℃ corresponds to the decomposition of azurite. The main infrared peaks observed in the infrared spectra are characteristic peaks of azurite, and the infrared spectra from the four different locations are relatively similar. Combined with the visual characteristics of azurite, this study can provide a basis for identifying and detecting azurite from different locations.
		2024 Vol. 44 (05): 1372-1378 [Abstract] ( 24 ) RICH HTML PDF (31221 KB) ( 21 )

	1379	BRRDF Simulation Study on the Influence of Atmospheric Turbulence on LIF Detection of Sea Surface Oil Spill
		XIE Bei-bei^{1, 2}, ZHAO Jia-wei¹, ZHOU Xuan-yu¹, ZHANG Xiao-dan³, LIU Yu-jia⁴
		DOI: 10.3964/j.issn.1000-0593(2024)05-1379-07
		Laser-induced fluorescence (LIF) can be integrated into unmanned aerial vehicles to build LIF radar systems for marine environmental monitoring. The LIF radar system operates in the atmosphere, where atmospheric turbulence induces signal attenuation. The Bidirectional Reflectance Distribution Function (BRRDF) can describe the fluorescence characteristics of oil-contaminated seawater. Based on the theory of atmospheric turbulence and the Monte Carlo method, a BRRDF model has been developed by us for studying oil-contaminated seawater. The model was used to simulate the BRRDF of oil-contaminated seawater under irradiance scintillation, beam wander, and beam spreading conditions. The simulation results demonstrate that the fluorescence signals exhibit isotropy, and their intensity is directly proportional to the intensity of the excitation light. The influence of beam wander on the fluorescence signals is weak and can be neglected. Under weak atmospheric turbulence conditions(Turbulence intensity parameters σ²_R＜1), with the fluorescence signal intensity concentrated within the range of 2×10^-5 to 5×10^-5 and the fluorescence spot radius expanding from 1 to 5 mm, the LIF radar system can operate normally in the turbulent channel. Under moderate atmospheric turbulent conditions (σ²_R≈1), the fluorescence signal fluctuates from 10^-5 to 10^-4. The fluorescence spot radius expands to 15 mm. The LIF radar system's resistance to turbulence needs to be improved by appropriately increasing the aperture of the receiving lens. Under strong atmospheric turbulent conditions (σ²_R＝25), the LIF radar system connot detect the fluorescence signal. The analysis and discussion in this study can provide references for the design and optimization of LIF radar systems.
		2024 Vol. 44 (05): 1379-1385 [Abstract] ( 18 ) RICH HTML PDF (5128 KB) ( 8 )

	1386	*Study on the Identification Method of Lycium Barbarum* Cultivars in Ningxia Based on Infrared Spectrum and Cluster Analysis**
		XU Rong¹, AO Dong-mei^2, XU Xin^{1, 2}, WANG Zhan-lin^{1, 2}, HU Ying², LIU Sai¹, QIAO Hai-li¹, XU Chang-qing^1
		DOI: 10.3964/j.issn.1000-0593(2024)05-1386-06
		Lycium barbarum(Lycii Fructus, wolfberry) is a valuable traditional Chinese medicinal material for medicine and food. Ningxia Zhongning wolfberry cultivars have been introduced to Gansu, Xinjiang, Qinghai and other provinces. Due to long-term introduction and improvement, there are many varieties of Lycium barbarum, one of the important factors affecting the quality of Lycii Fructus. This study used Fourier transforms infrared spectroscopy (FTIR) to determine the collected Lycii Fructus of Ningqi No.1, No.4, No.5, No.7, No.0909 and No.10 from Zhongning, Ningxia. The range of the one-dimensional infrared spectrum and the second derivative spectrum was 4 000~650 cm^-1. After obtaining the spectrum, the infrared spectrum's similarity coefficient was calculated using the fingerprint region (1 800~650 cm^-1) with dense spectral bands. Then, the infrared fingerprints of different varieties of Lycii Fructus were classified and compared with SMICA cluster analysis. The results show that the one-dimensional infrared spectroscopy of different varieties of Lycium barbarum samples are relatively similar, with the location, peak height and peak shape of the peaks being relatively close. Their common absorption peaks are more numerous, and only the intensity, peak location and peak shape of the absorption peaks at around 3 282～3 288, 1 239～1 242 and 1 143～1 147 cm^-1 are different, indicating that the polysaccharides, glycosides, proteins, lipids, and The types and contents of polysaccharides, glycosides, proteins, lipids, flavonoids and other components in different varieties of Lycium barbarum varied. In the second-order derivative spectra, the absorption peaks of NingQi 1, 4 and 7 were not apparentat 2 880 cm^-1, and 0909 at 969 cm^-1. The similarity of different varieties of Lycii Fructus ranges from 0.9489 to 0.9928, indicating certain differences among different varieties. Ningqi 7 has the lowest average similarity coefficient of 0.9640, indicating that its component specificity is the highest. The similarity coefficient of No.0909 and Ningqi 10 is 0.992 8, the two varieties with the highest similarity. The cluster analysis was carried out using the Assure ID software with the absorption wave number of each medicinal material as a variable. The class spacing between Ningqi No.1 and other varieties was small, ranging from 2.17 to 2.97. The class spacing between No.0909 and other varieties was the largest, ranging from 2.97 to 8.06. In the clustering model, the recognition rate of different varieties of Lycii Fructus is 100%, only the rejection rate of Ningqi No.1 is 66%, which can easy to be confused with other varieties of Lycii Fructus, and the rejection rate of No.0909 is 100%, which is the easiest to distinguish. In the class model diagram, No.0909 and Ningqi No.5, No.0909 and Ningqi No.7 are separated in pairs, which can identify the samples of different varieties. The cluster analysis model was verified using known varieties of Lycii Fructus, and its recognition and rejection rates were the same as those of the cluster analysis model. The results of the one-dimensional infrared spectrum, second derivative spectrum, similarity, class spacing, recognition rate and rejection rate of different varieties of Lycii Fructus showed that Ningqi No.1 was the original variety of other varieties of Lycii Fructus, and No.0909 was significantly different from other varieties. Therefore, the combination of infrared spectrum and cluster analysis can quickly and nondestructively identify different varieties of Lycii Fructus, which has a certain guiding role in the breeding and production of Lycii Fructus in Ningxia.
		2024 Vol. 44 (05): 1386-1391 [Abstract] ( 23 ) RICH HTML PDF (2083 KB) ( 23 )

	1392	Identification of Sorghum Breed by Hyperspectral Image Technology
		SONG Shao-zhong¹, LIU Yuan-yuan², ZHOU Zi-yang³, TENG Xing³, LI Ji-hong³, LIU Jun-ling¹, GAO Xun^2*
		DOI: 10.3964/j.issn.1000-0593(2024)05-1392-06
		Sorghum is an important raw material for liquor brewing. The components of sorghum are very important to the trace components and quality of liquor, and the quality of sorghum can affect the quality and flavor of liquor. Therefore, the nondestructive and rapid identification of sorghum breeds is an urgent and important question for improving the quality of liquor. In this paper, hyperspectral imaging technology combined with a machine learning algorithm is used to classify and identify sorghum breeds. By using the hyperspectral imaging technology, hyperspectral spectral lines and image texture data of 10 breeds of sorghum are obtained at the same time. Multivariate scattering correction (MSC) is used to preprocess the hyperspectral spectrum, and a continuous projection algorithm (SPA) is used to screen 62 feature bands. The gray level co-occurrence matrix extracts four texture features of sorghum. The hyperspectral spectral data and spectral-image fusion data are used, respectively, and four machine learning algorithms, including PLS-DA, SVM, ELM and RF, are used to classify and identify the sorghum breed. The results show that the hyperspectral characteristic bands extracted by SPA dimensionality reduction can be represented by the data information of the full hyperspectral spectral information after MSC pretreatment, which improves the stability of the PLS-DA algorithm model in the identification of the sorghum breed. The identification accuracy of 10 breeds of sorghum is improved from 67.58% to 93.85%, and the identification accuracy is increased by 27%.After the fusion of hyperspectral spectral data and image texture feature data, the identification accuracy of the sorghum breed by using the PLS-DA model under the conditions of full-spectrum and feature spectrum is improved to 96.47% and 97.16%, respectively, which is more suitable for the classification and identification of sorghum breed compared with the single hyperspectral data. Compared with the results of SVM, ELM, and RF machine learning algorithms, the PLS-DA machine learning algorithm model has the best identification accuracy for the sorghum breed. The research has proved the effectiveness of hyperspectral imaging technology combined with machine learning algorithms in the identification of sorghum breeds, which can achieve fast and accurate quality inspection of sorghum products.
		2024 Vol. 44 (05): 1392-1397 [Abstract] ( 17 ) RICH HTML PDF (11408 KB) ( 20 )

	1398	Study on Abnormal Wear Location of Integrated Transmission Components Based on Oil Spectral Data
		XU Feng¹, ZHANG Qian-qian², JI Wen-long¹, JIA Ran^3*, ZHANG Peng⁴, ZHENG Chang-song⁴
		DOI: 10.3964/j.issn.1000-0593(2024)05-1398-07
		Wear is one of the important factors affecting the working reliability and service life of the integrated transmission device. Abnormal wear of the components of the integrated transmission device will reduce its operating efficiency and even cause its random failure, resulting in significant economic and military losses.Therefore, it has become an important method to improve the reliability of integrated transmission devices to quickly and accurately detect the characteristics of wear elements and locate the parts with abnormal wear by using oil spectral data. However, oil spectral data samples generally contain many interfering and additive elements, etc. Clustering, principal component analysis, weighted fusion and other methods commonly used in current studies lack consideration of the increase of abnormal wear of specific element concentration indexesover time.In order to analyze the wear state of different parts of the integrated transmission, a method of abnormal wear location analysis of parts based on oil spectral data was proposed. A clustering method based on the correlation distance of the time window was proposed to separate the elements representing the wear states of different parts. The wear trend classification method of wear elements was proposed, with high wear trend elements as the cluster center, so the clustering results could be interpreted. The weight of component wear elements was determined by classification coefficient, and the wear elements of each component were fused to obtain the representation of the wear state of different components. Abnormal wear can be identified by abnormal wear threshold value to locate abnormal wear of parts. The parts and period of abnormal wear were detected and judged. The test results show that Fe, Cu and Pb have the highest wear trend classification coefficient and carry a lot of wear information, which can effectively characterize the wear state of the device. The centralized clustering method based on the correlation distance of the time window successfully divides the oil spectral data into Fe, Cu and Pb, which can effectively characterize the wear state of the whole body, friction plate and gear group. The weighted fusion method based on the classification coefficient can effectively detect and judge the abnormal wear parts and period of the device and provide technical guidance for the subsequent fault prevention and maintenance.
		2024 Vol. 44 (05): 1398-1404 [Abstract] ( 17 ) RICH HTML PDF (5577 KB) ( 6 )

	1405	New Nondestructive Method of Methanol Detection in Insulating Oil Based on Terahertz Spectrum
		HE Yu-xin¹, YANG Li-jun^1*, YU Hua², CHEN Qi-yu¹, CHENG Li¹, LIAO Rui-jin¹
		DOI: 10.3964/j.issn.1000-0593(2024)05-1405-07
		Methanol is a unique aging marker of cellulose in oil-paper insulation. Headspace gas chromatography/mass spectrometry and spectrophotometry are the main methods for measuring methanol, which have a complex and long testing process. Raman spectroscopy and infrared spectroscopy also make it difficult to realize the perception of low-concentration (ppm) methanol. This paper proposes a new method for non-destructive detection of trace methanol in insulating oil by utilizing terahertz detection technology's sensitivity to polar substances. The insulating oil samples containing methanol were completed with Karamay #25 mineral insulating oil and chromatographic grade methanol. The concentrations were 99, 59.4, 19.8, 9.9, 4.95, 2.48, 1.24, 0.62, 0.31, and 0.15 ppm. Detection of the terahertz absorption spectrum showed a characteristic peak around 1.7 THz, which exhibits satisfactory quantitative correlation with methanol concentration in oil, and the minimum detection limit of 0.15 ppm trace methanol in the new insulating oil was preliminarily realized in the laboratory. Quantum chemical analysis methods can be used to study the interaction between molecules and molecules. The complex intermolecular force between methanol and the insulating oil that causes cooperative vibration between oil and methanol molecules is the mechanism of characteristic peaks in the terahertz frequency band. Meanwhile, hydrogen bonds are formed between methanol molecules for easy association. Therefore, the different association ratios of methanol molecules with different concentrations of insulating oil molecules result in a nonlinear relationship between the intensity of the absorption peak and the methanol concentration. The terahertz spectrum of aged insulating oil containing trace methanol also demonstrates an absorption peak at approximately 1.7 THz. The intensity of the absorption peak increases with the increase of aging days, and the increase is nonlinear with the degree of aging at the same methanol concentration. This finding may be related to the content of pyrolysis products of insulating oil in different periods. Polymer and insulating oil exhibit low absorption of terahertz waves. We will reduce the lower limit of the test and eliminate the influence of aging factors by further increasing the optical path, analyzing the cooperative vibration mechanism of insulating oil aging products and methanol, and utilizing adaptive big data signal extraction algorithms in future investigations to achieve the accuracy of the methanol content in the nondestructive measurement of full-cycle insulating oil and realize the rapid in situ detection of low-concentration methanol in the insulating oil of the transformer.
		2024 Vol. 44 (05): 1405-1411 [Abstract] ( 17 ) RICH HTML PDF (11466 KB) ( 9 )

	1412	On Line Simultaneous Measurement of CO/CO₂/H₂S Concentration Based on Laser Absorption Spectrum
		ZHANG Xue-jun¹, CHEN Qin-gen², YANG Zhan¹, DENG Qin¹, HE Shuan-ling³, PENG Zhi-min^3*
		DOI: 10.3964/j.issn.1000-0593(2024)05-1412-05
		CO, CO₂ and H₂S are important components of the atmosphere in the coal-fired boiler. Their concentrations can not only reflect the combustion conditions but also serve as the basis for judging the high-temperature corrosion degree of the water wall. Therefore, it is of great significance to measure the concentrations of CO, CO₂, and H₂S accurately. In this work, the WM-DAS method and Herriott cell with a length of about 40 m were used to carry out synchronous measurement of three kinds of gas absorptivity under different CO/CO₂ concentration ratios at room temperature and low pressure. The results showed that the measured values of the absorptivity of the three gases agree very well with the theoretical calculation values, and the relative error is within 6.82%, which suggests the highly reliable of this method. Subsequently, the dynamic measurement of CO/CO₂ (0~2 000 μL·L^-1） and H₂S （0~20 μL·L^-1) was carried out. The results showed that the measurement system has good linearity in response to the concentration changes of the three components.
		2024 Vol. 44 (05): 1412-1416 [Abstract] ( 17 ) RICH HTML PDF (6050 KB) ( 11 )

	1417	Prediction Method of Wool Content in Waste Spinning Samples Based on Semi Supervised Regression of Generative Adversarial Network
		HU Jin-quan^{1, 2}, YANG Hui-hua¹, ZHAO Guo-liang³, ZHOU Rui-zhi⁴, LI Ling-qiao⁵
		DOI: 10.3964/j.issn.1000-0593(2024)05-1417-08
		In this paper, a semi-supervised regression method based on a Generative adversarial network is proposed to meet the demand for online sorting for waste textile recycling, which uses some labeled samples and a large number of unlabeled samples to train the semi-supervised regression. The semi-supervised regression consists of a generator composed of neural networks and a discriminator composed of neural networks. The generator generates a mixed sample that is as close as possible to the actual labeled and unlabeled training dataset content. The discriminator is used to validate the samples generated by the generator and predict the continuous labeling of these samples. The generated network is trained through feature matching loss, which is the average error between the output of the actual sample in the middle layer of the discriminator and the generated sample. The discriminant has two outputs, one for predicting sequence markers and the other for determining the probability of whether the generated sample is a true or false sample. Train discriminants by using a combination of traditional unsupervised generative adversarial network loss functions and supervised regression losses. The generated network is trained through feature matching loss, which is the average error between the output of the actual sample in the middle layer of the discriminator and the generated sample. We have collected 400 blended samples with different wool contents and 3 000 blended samples with unknown components. 70% of labeled and unlabeled mixed samples were randomly selected as the training set, while the remaining 30% of labeled samples were used as the test set for repeated experiments. This article has conducted multiple experiments for verification. The first experiment is a blended spectrum generation experiment, which is used to verify that the generative adversarial network can effectively generate mixed sample spectra based on intrinsic laws. The second experiment is a semi-supervised adversarial network quantitative analysis performance comparison experiment, which trains and tests the wool composition analysis model, and compares the performance of this semi-supervised adversarial network quantitative analysis model with other quantitative models. The third experiment is a prediction and comparison experiment of on-site high wool content blended yarn segmentation models. Composition analysis is conducted on blended yarn samples with wool content between 80% and 99%, and the performance of this semi-supervised adversarial network quantitative analysis model is compared with that of other quantitative models. The fourth is a field prediction experiment for the subdivision comprehensive model of medium to high wool content blended fabrics. A semi-supervised adversarial network quantitative analysis model is trained using blended fabric samples with wool content between 40% and 99% and deployed in the sorting system. The operator conducts on-site testing data for accuracy, analysis time, and other tests. The experimental results show that the semi-supervised regression method based on a Generative adversarial network is superior to PCR，PLSR, SVR, BPNN and other models, and the prediction R² of this model reaches 0.94. After repeated on-site testing, the model can quickly extract blended samples with a wool content of over 40%.
		2024 Vol. 44 (05): 1417-1424 [Abstract] ( 16 ) RICH HTML PDF (8169 KB) ( 11 )

	1425	Three-Scale Deconstruction and Sparse Representation of Infrared and Visible Image Fusion
		JI Jing-yu, ZHANG Yu-hua, XING Na, WANG Chang-long, LIN Zhi-long^*, YAO Jiang-yi
		DOI: 10.3964/j.issn.1000-0593(2024)05-1425-14
		To improve the processing performance of source images with noise and improve the contrast and structural information of the fused images, an infrared and visible image fusion algorithm based on three-scale decomposition and sparse representation is proposed. First, to enhance the noise removal effect and maintain the structure and edge characteristics of the source image, the rolling guidance filter is used to decompose the source image, and the source image is decomposed into the base layer and the detail layer. Secondly, in order to make full use of the details and energy in the base component and reduce the complexity of the model, a structure-texture decomposition model is constructed. The base layer is decomposed into the base structure layer and base texture layer again, Then by analyzing the different characteristics of the three components, different fusion rules are utilized to fuse the three components respectively. The detail component contains the main noise components, but the noise level is different. Therefore, the sparse fusion denoising parameter is adaptively determined according to the noise level of the image to realize the fusion and denoising of the detail component at the same time and can effectively improve computational efficiency; for the base structure components, which contain fewer detail features, the weighted average technology based on the visual saliency map is directly used for pre-fusion; for the base texture components, because they contain visually important information or image features, such as edges, lines and contours and other activity information, which can reflect the main details of the original base image, the principal component analysis method is used for pre-fusion. Finally, the fused image is obtained by reconstructing the detail, base structure and texture layers. In order to verify the effectiveness of the proposed method, several groups of infrared and visible images were selected for experiments and compared with five recent methods, including CNN, FPDE, ResNet, IFEVIP and TIF, and the results were analyzed in a subjective and objective form. The experimental results show that, compared with other image fusion algorithms, this method can consider the fusion of noise-perturbed and noise-free images and can retain the details, brightness and structure of the source image in the fusion image with or without noise. Moreover, can effectively eliminate noise.
		2024 Vol. 44 (05): 1425-1438 [Abstract] ( 18 ) RICH HTML PDF (3311 KB) ( 6 )

	1439	Measurements of CRCS Dunhuang Gobi Surface Reflectance Spectrum Using Multi-Rotor UAV and Its Calibration Evaluations
		ZHANG Yong^{1, 2, 3}, XU Han-lie^{1, 2}, ZHANG Li-jun^{1, 2}, LI Yuan^{1, 2}, SUN Ling^{1, 2}, QIN Dan-yu^{1, 2}, RONG Zhi-guo^{1, 2}, HU Xiu-qing^{1, 2}, LU Qi-feng⁴, LU Nai-meng^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2024)05-1439-10
		The satellite-ground synchronous observation experiment at China Radiometric Calibration Sites (CRCS) Dunhuang is one of the primary methods for achieving absolute radiometric calibration of China's meteorology, oceanography, land resource, environmental disaster monitoring, and military series satellite optical imaging payloads solar reflection bands. However, the traditional method of surface reflectance spectral satellite-ground synchronous measurement at CRCS Dunhuang Site is based on vehicle observation, which not only consumes significant resources and can damage the site but results in measurement data lacking regional representativeness. To address this issue, the 2016 satellite-ground synchronous observation experiment at CRCS Dunhuang primarily utilized rotor drones for low-altitude synchronous measurements supplemented by vehicle observations. The experiment covered all process aspects, including route design, altitude selection, instrument parameter configuration, sampling strategy, and aviation data processing. Multiple flight tests have shown that using rotor drones for low-altitude measurements, instead of vehicle-based measurements, improves the spatial consistency and representativeness of ground reflectance characteristics. Using drone-based measurements also increases the efficiency of assessing ground reflectance. It effectively protects the precious Gobi surface of CRCS Dunhuang, resulting in significant savings of resources. Comparisons of surface reflectance data obtained through aerial and vehicle-based measurements indicate that the mean values of multiple surface reflectance measurements are relatively close, However, the standard deviation of the aerial measurements is smaller. Evaluating the radiometric calibration of reflectance data obtained by drones using synchronous measurements from the Terra MODIS sensor indicates that the relative deviation of the drone data is within 5%. Drone-based measurements can replace vehicle-based field measurements for calibration purposes, and the accuracy meets requirements. With further optimization and improvement in drone performance, drones are anticipated to have more extensive and intensive applications in satellite-ground synchronous calibration testing, playing a more significant and important role in the future.
		2024 Vol. 44 (05): 1439-1448 [Abstract] ( 19 ) RICH HTML PDF (9381 KB) ( 5 )

	1449	Effect of Differential Spectral Transformation on Soil Heavy Metal Content Inversion Accuracy
		BAI Zong-fan¹, HAN Ling^1*, JIANG Xu-hai¹, WU Chun-lin²
		DOI: 10.3964/j.issn.1000-0593(2024)05-1449-08
		With the increasing development of industry and agriculture in China, heavy metal pollution in soil represented by nickel (Ni), iron (Fe), copper (Cu), chromium (Cr), lead (Pb), etc., has a serious impact on human life. Hyperspectral technology has advantages such as being real-time, non-destructive, and fast, which provides scientific means to obtain information on soil heavy metal content efficiently and accurately. At the same time, the spectral transformation method significantly impacts the inversion accuracy of soil heavy metal content. To clarify the relationship between the spectral transformation method and the inversion accuracy, 60 soil samples were collected in the study area to determine the Ni, Fe, Cr, Cu, and Pb heavy metals content and the corresponding spectral reflectance between 350～2 500 nm. Based on the correlation coefficient (CC) analysis, the feature bands for remote sensing detection of soil heavy metals were selected by the modified discrete binary particle swarm optimization (MDBPSO) method. Finally, the inverse models of Ni, Fe, Cr, Cu and Pb contents were constructed by the random forest (RF) algorithm with the feature bands as independent variables. In this study, based on Gaussian smoothing of the original reflectance, the effects of four differential spectral transformation methods, including first-order differential (R′), first-order differential of logarithmic inverse (1/lgR)′, first-order differential of inverse (1/R)′, and first-order differential of exponential (e^R)′, on the accuracy of soil heavy metal inversion were compared and analyzed. The results show that based on the CC analysis method, the MDBPSO algorithm can effectively reduce the redundancy of spectral data and improve the efficiency of the model operation. The number of feature bands sensitive to Ni, Fe, Cr, Cu and Pb in R′, (1/lgR)′, (1/R)′, (e^R)′, has been reduced by at least 154, 363, 135, 744 and 889, respectively. (1/lgR)′, R′, R′, (1/R)′, and R′ spectral transformation methods were applied to the combined operation of Ni, Fe, Cr, Cu, and Pb feature bands, respectively. The accuracy of the estimated models was better than other differential transformation methods, where the coefficients of determination of the model test set were 0.913, 0.906, 0.872, 0.912, and 0.876. The root mean square errors were 0.743, 0.095, 2.588, 1.541, and 1.453, respectively. This study provides a scientific reference for selecting of differential spectral transformation methods when using remote sensing data to retrieve soil heavy metal content. It provides new ideas for further realizing large-area high-precision remote sensing monitoring of soil heavy metal content.
		2024 Vol. 44 (05): 1449-1456 [Abstract] ( 16 ) RICH HTML PDF (5156 KB) ( 7 )

	1457	Research on Spectral Feature Extraction and Detection Method of Rice Leaf Blast by UAV Hyperspectral Remote Sensing
		LIU Zi-yang^{1, 2}, FENG Shuai^{1, 2}, ZHAO Dong-xue^{1, 2}, LI Jin-peng^{1, 2}, GUAN Qiang^{1, 2}, XU Tong-yu^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2024)05-1457-07
		To determine the optimal classification model for unmanned aerial hyperspectral remote sensing for detection of leaf blast in rice canopies, the research is based on rice field trials, hyperspectral images of unmanned aerial vehicles (UAVs) in the 400~1 000 nm band were acquired, referring to the national standard GBT 15790-2009 specification for rice blast detection and survey, leaf blast is categorized into five classes according to the disease index, a total of 227 hyperspectral data sets were extracted for levels 0 to 4. The data were preprocessed using Savitzky- Golay smoothing (SG smoothing), first-order differential spectroscopy (1-Der) and second-order differential spectroscopy (2-Der) methods, and SVM models are constructed and compared to arrive at a better preprocessing method. Principal component analysis (PCA) was used to select the cumulative contribution of the principal components, continuous projection (SPA) and random frog (RF) methods for screening spectral signature bands, and using the results of the screening as inputs to the model, constructing Particle Swarm Optimization for Extreme Learning Machines (PSO-ELM), Extreme Learning Machines (ELM), Support Vector Machines (SVM) and Decision Tree (DT) classification models, respectively. The results show that compared with 1-Der and 2-Der, the SG smoothing method has better denoising effect, higher classification accuracy, and is a better preprocessing method, the classification accuracy and Kappa coefficient were 93.47% and 91.85%, respectively. The cumulative contribution of the first 2 PCs of the PCA was 93.13%, and for the effective construction of the model, the first 6 PCs were finally selected with a cumulative contribution of 99.02%,SPA used RMSE as the criterion for the selection of the best spectral signature bands, showing a total of seven best spectral signature bands, The visible wavelength bands are 400.8, 416.7 and 426.2 nm, the green wavelength band is 566nm, the red wavelength band is 683.9nm, and the near-infrared wavelength bands are 830.2 and 916.4 nm, RF selected the bands with a screening probability greater than 0.2 as the best spectral signature bands, and finally screened eight spectral signature bands, including 663.4 and 694.2 nm for red light, and 784.4, 787.9, 791.4, 905.5, 927.2, and 930.9 nm for the near-infrared band, this method effectively reduces the inter-band correlation and redundancy, while the three screening results are constructed into classification models separately, and the results show that the overall classification accuracies of all models are all greater than 92.61%, the modeling results were better, in which the PSO-ELM model was used to classify PCA with an accuracy of 97.77% and a Kappa coefficient of 97.22%, the highest classification accuracy among all models, 1.42% and 1.56% higher compared to the highest classification accuracy and Kappa coefficient of the ELM model, the highest classification accuracy and Kappa coefficient are 2.12% and 2.66% higher compared to SVM model and 4.44% and 5.58% higher compared to DT model. The comprehensive evaluation of PSO-ELM model modeling is better than ELM model, SVM model and DT model, which is the optimal classification model. Therefore, it is feasible to use UAV hyperspectral remote sensing to detect rice leaf blast, providing scientific basis and technical support for rice production and leaf blast detection.
		2024 Vol. 44 (05): 1457-1463 [Abstract] ( 21 ) RICH HTML PDF (10167 KB) ( 18 )

	1464	An Improved XGBoosting Algorithm Based on Fat Content in Infant Milk Powder Prediction Model
		ZHANG Wen-jing^{1, 2}, XUE He-ru^{1, 2*}, JIANG Xin-hua^{1, 2}, LIU Jiang-ping^{1, 2}, HUANG Qing¹
		DOI: 10.3964/j.issn.1000-0593(2024)05-1464-08
		Fat plays an essential role in the composition of infant formula. Not only is fat a vital component of a baby's growth and development, but it also provides essential energy for growth. It is crucial for the development of the infant brain and the formation of nerve myelin. Chemical methods for determining the fat content of infant milk powder, such as ether extraction, are sensitive but have the disadvantage of destroying samples and having a long detection period. In this paper, the hyperspectral data undergoes preprocessing processes with standard normal transform (SNV), multiple scattering corrections (MSC), Savitzky-Golay smoothing, and Roust method using different stages of infant milk powder in Inner Mongolia, China. A competitive adaptive re-weighting algorithm, CARS, was used to sift out redundant wavelengths from the spectroscopic data at 125 feature wavelengths, leaving 66 valid wavelengths. The Bayesian optimization algorithm optimizes the XGBoosting prediction model, leading to a BO-XGBoosting model that predicts the fat content of infant formula better than the original model. The experimental results show that the model predicts better than the traditional partial least squares regression (PLSR) and support vector machine (SVR) regression model, outperforming the Bagging and GrdientBoosting algorithms in the integrated algorithm. In the BO-XGBoosting model in the test set experiments, the decision coefficient R² and root mean square error of prediction (RMSEP) obtained are 0.953 7 and 0.577 3, which are 2.91% higher and 19.2% lower than the determination coefficient R² and root mean squared error of prediction (RMSEP) of the XGBoosting model's R² and RMSEP, respectively. This study provides algorithmic support and a theoretical foundation for BO-XGBooting based rapid, non-destructive detection of infant formula fat content.
		2024 Vol. 44 (05): 1464-1471 [Abstract] ( 18 ) RICH HTML PDF (4992 KB) ( 11 )

	1472	Evaluation of Soil As Concentration Estimation Method Based on Spectral Indices
		NING Jing^{1, 2}, ZOU Bin^{1, 2*}, TU Yu-long^{1, 2}, ZHANG Xia³, WANG Yu-long^{1, 2}, TIAN Rong-cai^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2024)05-1472-10
		To explore the validity and applicability of the estimation of soil arsenic (As) content based on spectral indices, 42 soil samples were collected from a farmland in Hebei Province, China. The reflectance spectra and As content were respectively determined by using a PSR-3500 portable ground spectrometer and Inductively Coupled Plasma Atomic Emission Spectrometry. The chlorophyll index (CI), difference index (DI), sum index (SI), ratio index (RI) and simple normalized difference spectral indices (NDI and NPDI) were calculated based onlaboratory spectra, field spectra, and the direct standardization (DS) transferred field spectra. Random forest regression (RFR) models were used to estimate the soil As values using the strongly correlated spectral indices, and indices were evaluated according to the modeling accuracy. Compared with thecharacteristic absorption bands of typical soil components, the internal mechanism of spectral indices improving the inversion accuracy of soil As content was analyzed. The results show that the spectral indices method significantly enhances the correlation between spectra data and As content by combining some low-correlation band information. When compared with the full-band RFR model, the spectral indices method increased the R²_p and RPD from 0.243 and 1.2 to 0.730 and 2.009, 0.264 and 1.213 to 0.669 and 1.809, 0.334 and 1.279 to 0.678 and 1.841 in the lab spectra, field spectra, and field-DS spectra respectively, and CI has the best comprehensive performance (R²_p>0.66 and RPD>1.8). However, some of the exponential characteristic bands of the optimal spectra indices lack interpretability and cannot reveal the band combination rules for exponentially amplifying effective information and eliminating noise. The research results can provide a scientific basis for estimating heavy-metal contamination in soil using remote sensing spectroscopy based on spectral indices and even the band design of satellite payloads.
		2024 Vol. 44 (05): 1472-1481 [Abstract] ( 16 ) RICH HTML PDF (25962 KB) ( 24 )

	1482	Study on the Effect of Nano Zinc Oxide on the Intrinsic and Spectral Properties of Perovskite Films
		YU Man^, XIE Guo-xin, ZHAO Xiao-juan, LI Zhao^
		DOI: 10.3964/j.issn.1000-0593(2024)05-1482-05
		Organic-inorganic hybrid halide perovskite solar cells have become a research hotspot in the photovoltaic field due to their excellent photoelectric properties, low preparation costs, and high conversion efficiency. As the core layer of perovskite devices, the electron transport layer mainly plays a role in extracting and transporting photogenerated charge carriers, and can serve as a hole blocking layer to suppress charge recombination in the perovskite active layer. Therefore, excellent performance of the electron transport layer is crucial for developing perovskite solar cells. However, the rigid electron transport layer (mesoporous or compact layer) commonly used in perovskite photovoltaic devices currently requires high-temperature sintering, which limits its application in flexible perovskite devices. Therefore, developing a flexible electron transport layer that can be applied in the field of perovskite photovoltaics has become an urgent problem to solve. Nano ZnO has suitable energy levels and high electron mobility and can be prepared at low temperatures, widely used as an electron transport layer in photovoltaic devices. Therefore, this work prepared rigid and flexible nano ZnO electron transport layers using spin coating and electrospinning methods, respectively, and determined the optimal preparation process for flexible nano ZnO using the electrospinning method. The effects of rigid and flexible nano ZnO on perovskite thin films' morphology, structure, and spectral properties were systematically studied by scanning electron microscopy, X-ray diffraction, UV-Vis absorption spectroscopy, and steady-state/transient fluorescence spectroscopy. The results indicate that the morphology of perovskite films strongly depends on the morphology of substrate nano ZnO. The perovskite thin films based on rigid and flexible nano ZnO exhibit almost the same structure and spectral absorption range (400~800 nm), with fluorescence emission peaks around 770 nm. The fluorescence quenching efficiency of flexible nano ZnO is 82%, almost comparable to that of rigid nano ZnO (85%). Furthermore, based on transient fluorescence kinetics data, the interfacial charge separation efficiencies of rigid and flexible nano ZnO were calculated to be 61% and 41%, respectively. It indicates that the flexible nano ZnO prepared by electrospinning has certain interfacial charge separation capabilities and is expected to become a new type of flexible electron transport layer. It provides an important reference value for designing flexible substrate perovskite solar cells and has practical significance for promoting perovskite photovoltaic applications.
		2024 Vol. 44 (05): 1482-1486 [Abstract] ( 21 ) RICH HTML PDF (15085 KB) ( 14 )

	1487	Research of Flame Retardant Mechanism of Rigid Polyurethane Foam/Steel Slag/Aluminum Hypophosphite Composites Based on Spectroscopy Analysis
		LIU Meng-ru¹, DAI Zhen², LONG Hong-ming^{3, 4}, ZHANG Hao^{1, 3, 4}, JI Yi-long^{3, 4}, YANG Ya-dong¹, TANG Gang^{1, 3, 4*}
		DOI: 10.3964/j.issn.1000-0593(2024)05-1487-07
		The excellent performance of rigid polyurethane foam (RPUF) makes it widely used in various fields, but its flammability has laid an enormous security risk in the application process. As a solid waste discharged after refining iron concentrate, steel slag (SS) causes environmental pollution problems due to its low comprehensive utilization efficiency. To improve the fire safety of RPUF and the added value of steel slag, SS and aluminium hypophosphate (AHP) were introduced into RPUF.A series of flame retardant RPUF (FR-RPUF) composites were prepared using one-step water-blown method. The chemical composition of SS was investigated by X-ray fluorescence spectroscopy (XRF), and the effects of SS/AHP on the microstructure, thermal stability, flame retardancy and gas phase products of FR-RPUF composites were systematically studied. XRF test showed that the chemical components of steel slag were mainly CaO, SiO₂, Al₂O₃, Fe₂O₃, SO₃, MgO, et al, which could be used as synergistic agents to promote the char formation of polymer and cover the surface of the material to block combustion heat, to achieve the purpose of condensed phase flame retardant.Scanning electron microscope (SEM) test indicated that the poor compatibility between SS/AHP and RPUF matrix led to varying degrees of damage of FR-RPUF cells. The flame retardant tests made known that the limiting oxygen indexes of RPUF-1, RPUF-4, and RPUF-5 were 24.2 vol%, 23.4 vol%, and 19.7 vol%, respectively, indicating that SS and AHP had a synergistic flame retardant effect. The RPUF/SS/AHP composites all passed UL-94 V-0 level, meeting the requirements of external wall insulation materials. Thermogravimetry-infrared (TG-FTIR) analysis showed that SS/AHP did not change the degradation process of RPUF. The gaseous products were mainly hydrocarbons, carbonyl compounds, carbamates, CO₂, isocyanate compounds, aromatic compounds, hydrogen cyanide, carbonyl compounds and esters.TG-FTIR tests implied that RPUF and FR-RPUF generated carbamates, hydrocarbons, CO₂, isocyanates, carbonyl compounds, aromatic compounds, esters and hydrogen cyanide. Further analysis of typical volatile products showed that the addition of AHP and SS promoted the early degradation of RPUF matrix. Raman test confirmed that the peak area ratio (I_D/I_G) of D peak to G peak of RPUF-4 was the smallest when SS/AHP was added to RPUF, indicating that the addition of SS/AHP improved the compactness and graphitization degree of FR-RPUF composites. The flame retardant mechanism was proposed. Firstly, AHP endothermic decomposition reduced the temperature around the flame, and the decomposed PO free radicals captured free HO ·to inhibited the chain reaction. Secondly, the decomposed aluminum pyrophosphate and char layer were covered on the substrate surface, which inhibited the diffusion of flame and combustible gas. The PH3 produced by AHP decomposition reacted with oxygen to form acidic substances (phosphoric acid and polyphosphoric acid), which promoted the dehydration of RPUF into char. The mineral components in steel slag reacted with phosphoric acid or polyphosphoric acid to form a dense char layer, which played a synergistic flame retardant effect with AHP.
		2024 Vol. 44 (05): 1487-1493 [Abstract] ( 20 ) RICH HTML PDF (11614 KB) ( 7 )

	1494	Identification of Citri Grandis Fructus Immaturus Based on Hyperspectral Combined With HHO-KELM
		XIE Bai-heng¹, MA Jin-fang¹, ZHOU Yong-xin¹, HAN Xue-qin¹, CHEN Jia-ze¹, ZHU Si-qi¹, YANG Mao-xun^{2, 3}, HUANG Fu-rong^1
		DOI: 10.3964/j.issn.1000-0593(2024)05-1494-07
		Citri grandis fructus immaturus is a local Chinese medicinal material with a long history of medicinal use in Guangdong Province, because the higher the price of the product with the older the production year, the phenomenon of shoddy charging is often in the market. The study used hyperspectral imaging technology combined with the Harris Eagle optimized(HHO) kernel extreme learning machine(KELM) to identify four sets of different years of citri grandis fructus immaturus. In this study, 193 orange-red tire section samples were collected in four years, and hyperspectral images of 400~1 000 nm were collected. Firstly, the original reflection spectra of orange-red tire sections were analyzed by principal component analysis (PCA), and then Savitzky-Golay smoothing (S-G), multiple scattering correction (MSC),and standard normal variable exchange (SNV) were used to pretreat the sample spectra and establish KELM model, and found that the discrimination accuracy of the sample spectra treated by SNV was the highest, reaching 99.24% of the training set and 95.56% of the test set. Further, use of competitive adaptive weighting algorithm (CARS) and Monte Carlo Information-Free Variable Elimination (MCUVE) to select the characteristic wavelength of the sample spectrum; Finally, the discriminant model is established by KELM, and the HHO is used to optimize the KELM parameter selection and compare the modeling effect. The results show that the discrimination effect based on HHO-KELM is 0.76%~4.44% higher than that of KELM. The redundancy of feature band information obtained by MCUVE screening is significantly reduced, The accuracy is improved, and the optimal accuracy can reach 100% of the training set and 100% of the test set, so the use of hyperspectral imaging technology can realize the non-destructive identification of citri grandis fructus immaturus in different years.
		2024 Vol. 44 (05): 1494-1500 [Abstract] ( 14 ) RICH HTML PDF (12689 KB) ( 16 )

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