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2024 Vol. 44, No. 02 Published: 2024-02-01

	301	Identification of Cucumber Disease and Insect Pest Based on Hyperspectral Imaging
		LI Yang^{1, 2}, LI Cui-ling^{2, 3}, WANG Xiu^{2, 3}, FAN Peng-fei^{2, 3}, LI Yu-kang², ZHAI Chang-yuan^{1, 2, 3*}
		DOI: 10.3964/j.issn.1000-0593(2024)02-0301-09
		Cucumber downy mildew and libria sativa are serious diseases and insect pests that restrict the development of the cucumber industry. In order to realize the rapid identification of cucumber diseases and insect pests, hyperspectral imaging technology and machine learning were used to explore the characteristic wavelengths of cucumber diseases and insect pests, which laid a foundation for the development of practical cucumber diseases and insect pests identification equipment based on multispectral imaging. This study used a hyperspectral imaging system to collect hyperspectral images of asymptomatic leaves, downy mildew leaves and leaf miner-infected leaves. According to the size of the leaf spot area, several regions of interest (ROI) were selected in the spot area, and the average reflectance data of each ROI was calculated as the original spectral data of the leaf. The samples were divided into training sets and test sets in a 3∶1 ratio by the Kennard-Stone algorithm. Direct orthogonal signal correction (DOSC), multiplicative scatter correction (MSC) and moving average(MA) were used to preprocess the original spectral data. Variable iterative space shrinkage approach (VISSA), competitive adaptive reweight sampling method (CARS), iteratively retains informative variables (IRIV) and shuffled frog leaping algorithm (SFLA) were used to extract characteristic wavelengths, respectively obtains 53, 20, 26, 10 characteristic wavelengths. Then, the successive projections algorithm (SPA) was used to perform secondary dimensionality reduction on the characteristic wavelength data, and finally, the characteristic wavelengths extracted by VISSA-SPA were 455, 536, 615, and 726 nm. The characteristic wavelengths extracted by CARS-SPA were 452, 501, 548 and 578 nm. The characteristic wavelengths extracted by IRIV-SPA were 452, 513, 543 and 553 nm. The characteristic wavelengths extracted by SFLA-SPA are 462, 484, 500 and 550 nm. Support vector machine (SVM), Elman neural network and random forest (RF) modeling were carried out for the full-band and characteristic wavelength data. The results showed that the full band spectral data preprocessed by MA had the best recognition effect, in which the OA of the MA-RF model reached 97.89% and the Kappa coefficient was 0.97. The MA-VISSA-RF model had the best effect among the models built by the data of the characteristic wavelength first extracted, with 98.19% OA and 0.97 Kappa coefficient. MA-IRIV-SPA-SVM model had the best effect among the models built by quadratic dimensionality reduction data, with OA 96.23% and Kappa coefficient 0.95. The results showed that hyperspectral imaging technology had a good effect on the identification of cucumber downy mildew and the insect pest, and 452, 513, 543, 553 nm could be used as the characteristic wavelength for identification of cucumber downy mildew and the insect pest, providing a theoretical basis for developing cucumber disease and insect pest identification equipment, providing a theoretical basis for the development of cucumber disease and insect pest rapid identification equipment.
		2024 Vol. 44 (02): 301-309 [Abstract] ( 64 ) RICH HTML PDF (12753 KB) ( 123 )

	310	Application Research of Airborne Optical Fiber Imaging Differential Absorption Spectrometer in Measuring Regional Air Pollution
		ZHANG Xiao-li¹, WANG Yu^{1, 2*}, XI Liang², ZHOU Hai-jin², CHANG Zhen², SI Fu-qi²
		DOI: 10.3964/j.issn.1000-0593(2024)02-0310-08
		Air pollution in China presents regional and complex characteristics. Carrying out stereo monitoring of the regional distribution of polluted gases can help us understand the status quo of the atmospheric environment in a timely manner, study and analyze various factors affecting air quality, and guide air pollution control measures. The airborne imaging differential optical absorption spectroscopy is one of the effective remote sensing methods for the regional distribution of polluted gases. This technology has a large observation area and a high coverage rate, which can provide a detailed regional distribution of polluted gases and realize the visual detection of pollution distribution and transmission. In the past, the airborne imaging differential absorption spectrometer used an overall design that needed to occupy the optical observation window of the aircraft. The optical fiber imaging differential absorption spectrometer introduced in this paper adopts the optical fiber beam transmission method, which needs minimal requirements during installation, greatly facilitates the installation and debugging on the aircraft, and meets the requirements of airworthiness equipment certification. This system uses a special multi-core fiber bundle combined with a Littow-offner structure spectral imaging system, which has the advantages of high spectral imaging resolution, large field of view, and compact structure. The paper introduces the equipment performance parameters in detail, and the verification experiment is carried out using the system around Wuhu City. A data processing algorithm is proposed for the optical fiber imaging differential absorption spectrometer in the application process. In this experiment, the slanted column concentration of polluting gas is obtained by retrieving the collected scattered solar light, and the air quality factor is calculated using the atmospheric radiative transmission model. Then, convert the slanted column concentration into a path-independent vertical column concentration. Finally, the results are displayed on the map combined with the aircraft angles and positions. This equipment can quickly obtain the concentration distribution of NO₂ and SO₂ over Wuhu City and its surrounding areas realize the rapid location of pollution sources and analyze the transmission process. According to the results, there are 4 high-value points of NO₂ vertical column concentration and 2 high-value points of SO₂ vertical column concentration in the experimental area. According to the map, there are industrials around the high-value points, and the results are consistent with the actual situation. Finally, we evaluated the precision between satellite data and airborne data. They have a positive correlation with a correlation coefficient of 0.77. The results show that the scheme of optical fiber imaging differential absorption spectrometer is verified, which can provide a basis popularising air pollution gas remote sensing technology and compensate for the shortage on the spatial scale in ground station and the shortage on the time scale in satellite test.
		2024 Vol. 44 (02): 310-317 [Abstract] ( 52 ) RICH HTML PDF (29772 KB) ( 35 )

	318	Study on Non-Invasive Blood Glucose Detection Technology Based on Time Frequency Domain Analysis
		CHEN Jian-hong, REN Jun-yi, YANG Jia, GUO Ya-ya, QIAO Wei-dong
		DOI: 10.3964/j.issn.1000-0593(2024)02-0318-07
		The non-invasive blood glucose detection technique is an indirect method of measuring glucose levels in the blood, which is safe, fast, and non-invasive without damaging human tissues, breaking the limitations of traditional blood glucose detection, and has important research value. The photoplethysmography signal, containing various physiological and pathological information, is widely used in various clinical studies and is also the focus of attention in the current implementation of the non-invasive glucose detection technique. Current studies of non-invasive blood glucose detection based on photoplethysmography signals have only considered the contribution to system modelling when the time or frequency domains act alone. Although the time domain analysis of the signal can describe the variation of the PPG signal amplitude with time, it cannot visually reflect the energy distribution of the PPG signal frequency. Therefore, the signal analysis of a single domain cannot fully express the PPG signal, which leads to information loss. When using frequency domain analysis to extract the signal spectrum, it is necessary to use all the time domain information of the signal, which is a global transformation and may result in the loss of signal characteristics at a specific time or in a specific frequency band. In summary, this paper proposes a new method for non-invasive blood glucose detection based on the integrated time-frequency domain analysis of photoplethysmography (PPG), using a parallel time-frequency domain method to consider the association between the photoplethysmography signal and blood glucose, a cluster analysis method is used to extract representative waveforms in the time domain of the PPG signal, analyze the correlation between the waveform features and blood glucose, and determine the time domain feature parameters of the waveform. On this basis, the pulse waveform time domain signal is converted to the frequency domain using the Fast Fourier Transform, and the spectral information is studied using principal component analysis to establish the frequency domain characteristic quantities. The BP neural network-based non-invasive blood glucose detection model is constructed by extracting the time-frequency domain feature parameters from the waveform signals obtained through the Oral Glucose Tolerance Test (OGTT) and using the invasive blood glucose concentration detected in real time as a reference. At the same time, in order to improve the accuracy of the model and achieve model optimization, a genetic algorithm is applied to the model for the second correction, and the final MAE and RMSE of the test set reach 1.13 and 1.42 mmol·L^-1. The results of Parker's CEG show that the prediction results in the A and B regions accounted for 80.3% and 19.7%, respectively, which indicates that the method has good prediction accuracy and provides a theoretical basis for the feasibility of daily non-invasive blood glucose monitoring. It is beneficial to improve the detection and monitoring systems for diabetes, to judge the condition better comprehensively, and to prevent, guide, and treat diabetes promptly.
		2024 Vol. 44 (02): 318-324 [Abstract] ( 46 ) RICH HTML PDF (6336 KB) ( 25 )

	325	The Effect of Different Irradiance on the Degradation Time of Realgar
		WU Fu-rong, LI Yan, MA Jun-jie, WANG Yu-hang, WANG Feng-ping^*
		DOI: 10.3964/j.issn.1000-0593(2024)02-0325-06
		The influence of light on materials is inevitable and irreversible, and the photo-induced damage has an accumulated effect. The International Council of Museums classifies materials into four classes based on photochemical stability: insensitive, low sensitive, relatively sensitive, and extremely sensitive. Different photosensitive materials have different capacities to withstand irradiation. Therefore, it is necessary to study the influence of illumination on pigments, which has a guiding significance for protecting and restoring cultural relics. Realgar is a well-known photosensitive material. Under visible light irradiation, realgar can degenerateinto uzonite (As₄S₅) and arsenolite (As₂O₃), and uzonite as an intermediate product is desulfurized to generate pararealgar. The photoinduced degradation is very common, but the results and time of degradation of realgar vary with the irradiation conditions. Raman spectroscopy is a non-destructive testing technology which can be used for qualitative and semi-quantitative analysis of material components. In the photoinduced degradation of realgar, the changesinmaterial structure and composition can be judged by the changesinRaman peak position and intensity. The WLED is commonly used for internal lighting of ancient buildings. According to the time when the Raman signal of realgar completely disappeared under different irradiance measured by Raman technology, the relationship between irradiance y and realgar degradation time x was y=e^9.057/x^0.861, indicating that the time needed for complete degradation of realgar was shorter with higher irradiance. In addition, the study also found that under WLED irradiation, the final products of realgar were the coexistence of pararealgar and uzonite. Itis because, under white light irradiation, pararealgar,as the degradation product of realgar, degraded into the intermediate uzonite under the irradiation of blue light contained in the white light source. In the internal lighting of ancient buildings, the irradiance received by the surface of the photosensitive pigment should be reduced as much as possible. Different lighting sources have different effects on realgar, and the relationship between the complete degradation time of realgar and irradiance is also different, but the lighting source used in this experiment is more consistent with the current lighting situation. Moreover, realgar is an important pigment in ancient buildings' colorful paintings and murals. According to the relationship, ancient buildings can be repaired regularly in combination with the irradiance of the internal lighting of ancient buildings.
		2024 Vol. 44 (02): 325-330 [Abstract] ( 44 ) RICH HTML PDF (7174 KB) ( 21 )

	331	Photo-Excited Frequency Terahertz Switch Based on Various Composite Metamaterial Structures
		CHEN Shan-shan, ZHANG Bo^*
		DOI: 10.3964/j.issn.1000-0593(2024)02-0331-05
		Terahertz(THz) electromagnetic radiation lies between the microwave and far-infrared regions and has attracted much attention due to its wide application. However, due to the lack of terahertz functional devices, it can not fully meet the need of practical applications, so the modular and other terahertz functional devices needs to make a breakthrough. This paper mainly studies the terahertz wave modulator using the transmission terahertz spectral system. Metamaterial can be applied to the absorber. However, when the structural parameters of the metamaterial are once determined, the perfect absorption can only be generated at a specific resonance frequency. We designed three composite metamaterials structures to explore the resonance of composite metamaterials; three structures are a single gap of a metal resonance ring, a single gap of a metal resonance box and asymmetric double gaps of a metal resonance box; in the gap of three structures with photosensitive material indium oxide. We change the conductivity of indium oxide, explore terahertz modulation properties of these composite metamaterial structures and do numerical simulations of the electric field distribution of different resonance frequencies for three structured THz frequency switches. For a single gap of different shapes of the metal resonant rings, the resonance frequency is different, but with the increasing of indium oxide's conductivity, resonance peak absorption intensity gradually decreases. From the corresponding electric-field distribution diagram, with the increasing of indium oxide's conductivity, the gap edge electric field strength is increasingly weak, so the resonance peak absorption strength is more and more weak. This process can be considered a terahertz wave in the resonance frequency dynamic switch. For asymmetric double gaps metal resonance box, we deviate from the gap in the middle to fill the indium oxide; the structure's frequency spectrogram shows two resonance peaks. With the increase of conductivity, a resonance peak absorption strength gradually weakens and the other resonance peak absorption strength doesn't change significantly. Thus, the resonance peak whose absorption strength weakens with the increase conductivity is Fano resonance, and the other resonance peak whose absorption strength does not change significantly is dipole resonance. As can be seen from the corresponding electric-field distribution diagram, the energy of the incoming THz wave of the Fano resonance is mainly concentrated on the right metal arm of the metal resonance box, and as the conductivity increases, the quantity of charges accumulated at the gap of the right metal arm is increasing. In contrast, the energy of the dipole resonance incoming THz wave is mainly concentrated on the left metal arm of the metal resonance box and as the conductivity increasing, the electric-field distribution of the dipole resonance does not change significantly.
		2024 Vol. 44 (02): 331-335 [Abstract] ( 41 ) RICH HTML PDF (7869 KB) ( 36 )

	336	Inversion of Spatial Characteristic Spectrum and Feasibility Study of Outdoor Spectral Correction
		GAO Feng^{1, 2}, XU Jia-yi^{1, 2}, LUO Hua-ping^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2024)02-0336-11
		Outdoor hyperspectral detection can quickly obtain the spectrum information of the sample, but affected by the ambient light and the bidirectional reflectance distribution function of the sample, the collected spectrum cannot accurately reflect the true information of the sample, which has a certain impact on the outdoor detection accuracy. In order to improve the accuracy of outdoor hyperspectral detection, a method of correcting outdoor spectrum using spatial characteristic spectrum was proposed. Walthall, Shibayama, Ross-Li, Roujean and Rahman were used to invert the spatial characteristic spectrum of winter jujube, red grapes and “Xiaobai apricot”, the inverted spatial characteristic spectrum were used to correct the outdoor spectrum. The quality prediction models of darkroom spectrum, outdoor spectrum and correction spectrum were established respectively. The inversion results showed that the spatial characteristic spectrum of the three fruits has good inversion effects, and the inversion errors from low to high are winter jujube, “Xiaobai apricots” and red grapes. The average determination coefficient are 0.957, 0.947, 0.927, and the average errors are 3.56%, 4.90% and 8.23%, respectively; among the five BRDF models, the Walthall model has the best inversion effect, the average determination coefficient and error are 0.949 and 5.33%, respectively. The Ross-li model has the worst inversion effect, the average determination coefficient and error are 0.934 and 6.050%, respectively. The outdoor spectrum correction results show that the noise of the outdoor spectrum is reduced after correction, the spectrum is smooth, and the spectrum trend is consistent with that of the darkroom spectrum; affected by the inversion accuracy, the correction effect of winter jujube spectrum is the best, and the spectrum is smoother, while the correction spectrum of red grapes and “Xiaobai apricot” have more noise. The results of the quality prediction model showed that the accuracy of the quality prediction model of three kinds of fruit was quite different, and the order from high to low are winter jujube, “Xiaobai apricot” and red grape, which might be related to the different quality of fruits; the prediction effects of the models established by the corrected spectrum obtained by the five BRDF models are different, but there is no significant difference; in the prediction model, the prediction model established by darkroom spectrum is the best, and the prediction ability of the model established by modified spectrum is better than that established by outdoor spectrum, indicating that the prediction ability of the model is improved after the outdoor spectrum is corrected. In summary, the BRDF model can better invert the spatial characteristic spectrum of fruits, the corrected spectrum is closer to the darkroom spectrum. The model established by the corrected spectrum is better than the model established by the outdoor spectrum, indicating that the method of using spatial characteristic spectrum to correct the outdoor spectrum is feasible and can provide a new idea for improving the accuracy of outdoor nondestructive testing.
		2024 Vol. 44 (02): 336-346 [Abstract] ( 38 ) RICH HTML PDF (17138 KB) ( 23 )

	347	Study on Spectral Interference Mechanism and Correction Method of Spark-Induced Breakdown Plasma
		CHEN Wei-ze¹, YU Zi-yu¹, QIN Huai-qing¹, LU Zhi-min^{1, 2}, YAO Shun-chun^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2024)02-0347-07
		Aiming at the problem of spectral line interference caused by tungsten electrode excitation in the particle flow-spark induced breakdown spectroscopy, a spectral line interference correction method based on plasma signal detection optimization is studied. The PF-SIBS measurement experimental system was set up. The particle flow of pure chemical graphite was taken as the research object. According to the generation and extinction process of plasma between electrodes, the distribution of characteristic spectral lines in the plasma and the variation of signal intensity of characteristic spectral lines between electrodes, the evaporation, dissociation and excitation process of characteristic elements in the plasma are analyzed, and based on this, the optimal spectral detection position is optimized. The research results show that electrons are generated in the cathode spot, and electrons collide with the electrode metal, graphite particle flow and air medium between electrodes during the process of emission to the anode, resulting in more electron emission, thus forming and maintaining the discharge channel from the cathode to the anode. In the cathode region, the Joule heat generated by the high-energy electric field promotes metal evaporation and sputtering at the cathode tip, and the impact of the expansion causes particles and air to be expelled from the cathode region, and the atoms and electrons of the tungsten metal occupy the cathode area. In the middle of the discharge channel, electrons collide with the dense flow of graphite particles and ionize. In the anode region, the remaining discharge energy is difficult to evaporate the anode metal, and the electrons mainly ionize the air medium. Thus, the region from the cathode to the anode is divided into a cathode metal excitation region, a middle particle excitation region and an anode air excitation region. The ions and neutral atoms of the ionized electrodes metal, graphite particles and air medium occupy their respective excitation regions, forming plasma and radiating corresponding characteristic spectral lines. The characteristic spectral line intensity change from cathode to anode shows the same results as above, The intensity of W 247.78 nm spectral line is stronger in the cathode region and shows a decreasing trend; C 247.86 nm increased first and then decreased and reached the maximum at the center of the electrode spacing; N 744.23 nm gradually increased and reached the maximum at the tip of the anode. Using the C-W signal intensity ratio as the evaluation index of the C-W spectral line interference degree, the optimal spectral detection position was determined to be 0.5 mm away from the anode. Compared with the common spectral detection position (the center of the electrode spacing), the C-W signal intensity ratio increased from 1.200 to 1.348. The ratio of the peak fitting value of C 247.86 nm signal intensity to the observed value increased from 86.02% to 94.93%, and the C-W spectral line interference effect was significantly reduced.
		2024 Vol. 44 (02): 347-353 [Abstract] ( 38 ) RICH HTML PDF (7481 KB) ( 85 )

	354	Identification of Ancient Ceramic by Convolution Neural Network
		SUN He-yang¹, ZHOU Yue^{1, 2}, LI Si-jia^{1, 2}, LI Li¹, YAN Ling-tong¹, FENG Xiang-qian^1*
		DOI: 10.3964/j.issn.1000-0593(2024)02-0354-05
		As a treasure of Chinese culture, ancient ceramics have been sought at home and abroad since ancient times. With the development of ancient commerce and trade, ancient Chinese ceramics spread worldwide and were collected by private individuals or museums. Some were collected in museums after being excavated from tombs and salvaged from sunken ships. Tracing the origin of such ancient ceramics has always been the focus of ceramic archaeology, which is of great significance to studying ancient commerce and cultural exchanges. Using a portable digital microscope, spectrophotometer, X-ray fluorescence and other methods, the celadon porcelain samples excavated from Housi'ao, Silongkou, Fengdongyan and Yaozhou kilns were analyzed, and the data of the microbubble size distribution characteristics, ultraviolet, visible near-infrared spectrum characteristics and glaze composition of the celadon porcelain samples from these four kilns were obtained. The convolution neural network classification model was established by using these three features as variables for training and verification. The results show that the microbubble size distribution features, ultraviolet, visible near-infrared spectral features and glaze composition data of celadon porcelain are effective, but the difference in classification accuracy is very obvious.The average accuracy of model training of 30 randomly divided training sets and test sets: the model of microbubble size distribution features is 75%, the model of ultraviolet, visible near-infrared spectrum features is 89.2%, and the model of component data is 92.1%.The accuracy of the glaze composition data model is the highest, and the difference between the accuracy of training sets and test sets is the smallest. After saving the model parameters trained based on different features for fusion and retraining, it was found that the accuracy of the model after the fusion of ultraviolet, visible and near-infrared spectral features and microbubble size distribution features was improved to 93.7% and the accuracy of the model after the fusion of the three features was improved to the highest 97.4%. The results of the five-fold cross-validation show that the model, after the fusion of multiple features, can effectively avoid the case that the single feature model has many cross misjudgments on the samples from Housi'ao and Silongkou. In general, it is feasible to explore more effective classification features of ancient ceramics based on convolutional neural networks to trace the source of ancient ceramics accurately.
		2024 Vol. 44 (02): 354-358 [Abstract] ( 44 ) RICH HTML PDF (8926 KB) ( 33 )

	359	Multicomponent Trace Gas Detecting and Identifying System Based on MEMS-FPI on-Chip Spectral Device
		LIU Zhao-hai¹, AN Xin-chen^{1, 3}, TAO Zhi^{1, 2}, LIU Xiang^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2024)02-0359-08
		Infrared spectroscopy technology can be carried out to extract the characteristic absorption frequency of gas. However, the present gas spectrum detection technology, such as tunable laser absorption spectroscopy (TDLAS), makes it difficult to balance the wide band absorption and high precision. Therefore, developing multicomponent trace gas detection technology with high integration，speed and stability has always been a researching hotspot in scientific research. In order to broaden the range of infrared laser detection, this project developed a multi-channel distributed feedback (DFB) laser with tunable central wavelengths of 1 543, 1 579, 1 626, 1 653, 1 690 and 1 742 nm as the light source. It realized the synchronous detection with a multi-wavelength infrared laser, identification of multicomponent trace gas, a high efficient filtering of background gases by making use of the MEMS-FPI on-chip device's advantages, such as narrow detecting band width (5 nm), adjustable and addressable working wavelength and efficient filtering capability. This system innovatively adopts the multi-channel wavelength modulation (WMS) technology of an addressable MEMS-FPI spectrum chip and realizes the digital acquisition of the second harmonic (2f) signal through a single phase-locked amplifier loop. The fast trace level detection of seventrace gases (methane CH₄, hydrogen sulfide H₂S, ethylene C₂H₄) has been realized (less than 2 s), which also curtailed the lower limit of multi-component identification. Compared with the direct measuring method by the traditional wide-spectrum absorption, the lower limit of detection has been declined by about 700 times. The experimental results show that the lower limit of methane detection can reach 0.2 μL·L^-1, and the lower limit of other gases except carbon dioxide is 10 μL·L^-1, while the lower limit of other gases is 1～5 μL·L^-1. It fully meets the application requirements of a series of trace multi-component gas detection applications, including double carbon monitoring of greenhouse gases, exhaled gas detection and diagnosis of exhaled breath.
		2024 Vol. 44 (02): 359-366 [Abstract] ( 46 ) RICH HTML PDF (18930 KB) ( 37 )

	367	Freshness Identification of Turbot Based on Convolutional Neural Network and Hyperspectral Imaging Technology
		ZHANG Hai-liang¹, ZHOU Xiao-wen¹, LIU Xue-mei^2*, LUO Wei², ZHAN Bai-shao², PAN Fan³
		DOI: 10.3964/j.issn.1000-0593(2024)02-0367-05
		Identifying fish product freshness has always been an important research topic. Compared with the problems of high cost and long detection time of the current conventional fish quality detection methods, hyperspectral imaging technology (HSI) has been obtained due to its non-destructive and rapid advantages. Convolutional neural network is a widely used model in deep learning, with strong expressive ability and high model efficiency. Therefore, a freshness discrimination model of turbot was established using a convolutional neural network (CNN) combined with hyperspectral imaging technology. First, 160 regions of interest (ROI) spectra of turbot samples were collected and divided into 5 categories of freshness according to the samples' different freeze-thaw times and freezing times. Based on the VGG11 network, adjust the network structure according to the features of spectral data, reduce the number of fully connected layers, reduce model complexity, and compare the effects of different convolution kernels and activation functions on classification performance to determine the best network framework. Due to hyperspectral data and the large amount of redundant information, Uninformative variable elimination algorithm (UVE) and Random frog algorithm (RF) were used to screen the wavelength of hyperspectral data. The hyperspectral data after wavelength screening were respectively input into a convolutional neural network (CNN), least squares support vector machine (LS-SVM) and K-nearest neighbor algorithm (KNN) to establish the model. Finally, the UVE-CNN model based on the 165 feature wavelengths extracted by Uninformative variable elimination (UVE) has the best discrimination effect, and the accuracy of the classification model on the test set reaches 100%. The results showed that the combination of convolutional neural networks and hyperspectral imaging technology could be used to identify the freshness of turbot effectively. This study provides a new idea for non-destructive and accurate identification of turbot freshness.
		2024 Vol. 44 (02): 367-371 [Abstract] ( 53 ) RICH HTML PDF (3822 KB) ( 104 )

	372	Design and Implementation of a THz Anisotropic Metamaterial Polarization Regulator
		LI Yan-hong¹, LIAO Meng-meng², FENG Jie³
		DOI: 10.3964/j.issn.1000-0593(2024)02-0372-08
		Electromagnetic wave polarization will affect the performance of the wireless communication system. With the wide application of electromagnetic fields and microwave technology, free control of the electromagnetic wave polarization to meet the demand for information transmission and access to information becomes very important. It is also important to realize free control of polarization by changing the polarization state in wireless communication and radar target recognition. Compared with microwave communication, terahertz communication has the advantages of richer spectrum resources and higher transmission rates with shorter wavelengths. However, the traditional polarization governor has not been well applied in terahertz communication due to someproblems. This paper has designed a model applicable to the double function of terahertz spectrum polarization governor by using anisotropic metamaterial. First, the coordinate decomposition method is used to analyze the components of the double function of polarization control features, and the analysis results have revealed that the designed controller can realize linear polarization wave control as well as circularly polarized wave control, which is featured by double function control. Then, the surface current method is adopted to analyze the polarization conversion mechanism of the governor. The simulation results have shown that the governor has four resonant points, and the superposition of the fourth order electromagnetic resonance occurs in the metamaterials unit structure, which makes the governor work in a wide frequency band and has a high polarization conversion efficiency. Within the frequency band of 0.45～1.152 THz the efficiency can reach more than 90%. Finally, the effects of different device parameters on their performance are analyzed, and the governor's optimization and actual application conditions are proposed. Through the analysis of structural parameters, it is found that the change of structural parameters will affect the band width of the governor as well as the distribution of the resonance point location. The governor has exclusive performance with their working frequency band width. The governor has a poor performance with wider frequency bandwidth and vice versa. In the practical application of the governor, the structural parameters should be optimized and adjusted according to the specific regulation requirements to obtain satisfactory control features. Through the analysis of incident angle and azimuth angle, it is found that the performance of the governor is very sensitive to the change of incident Angle, and it is pointed out that the governor should be positioned in such a way that the projection of incident wave in the governor is parallel to the edge of the governor. Compared with previous work, the regulatordesigned in this paper has a more efficient performance and simpler structure, and the dual-function characteristics make the use of devices more convenient and diversified. This work provides theoretical reference for developing and applying terahertz polarized regulator.
		2024 Vol. 44 (02): 372-379 [Abstract] ( 45 ) RICH HTML PDF (12678 KB) ( 20 )

	380	Study on Photocatalysis & Light Absorption and High-Pressure Structural Properties of ZnSe and Its Mn Doping Composites
		WANG Shi-xia, WANG Xiao-yu, HU Tian-yi
		DOI: 10.3964/j.issn.1000-0593(2024)02-0380-06
		ZnSe semiconductor material is an important raw material for preparing optoelectronic devices and photocatalytic reaction catalysts. The monomer material exhibits deterioration under strong light and electron-hole recombination. In this study, ZnSematerials were prepared by element doping, and the optical and structural properties of ZnSe enhanced by element doping were studied and compared with those of monomer materials. Pure ZnSe and Mn/Zn with doping ratios of 5%, 10%, 15%, and 20% were prepared by the hydrothermal method in the laboratory to compare the morphology, structure, light absorption, and catalytic performance of the composite materials. The results showed that the sample with a doping ratio of 10% had the highest crystallinity, the least impurities, and the best catalytic performance. Subsequently, the high-pressure structural phase transformation behavior of pure ZnSe and samples doped with 10% Mn/Zn was investigated by in-situ Raman spectroscopy using Diamond Anvil Cell to explore the effect of element doping on the structural properties of the samples. The results are as follows: (1) Scanning electron microscope (SEM) images show that the morphology of the ZnSe sample prepared with Mn element is spherical and similar to the pure sample. Small particles are on the surface of the spherical particles, and with the increase of Mn addition, more substances are loaded on the surface. (2) X-ray diffraction (XRD) patterns show that the structure of the ZnSe sample is a cubic zinc blende structure. With the increase of Mn addition, the characteristic peak of MnSe in the sample is enhanced and the formation of impurity MnO₂ is more completed. The sample with a doping ratio of 10% has a high ZnSe crystallinity and a low impurities formation. (3) Solid-state ultraviolet diffuse reflectance (UV-Vis) results show that the sample with a doping ratio of 10% has the maximum light absorption edge and the smallest bandgap width of 1.65 eV. (4) The results of the photocatalytic experiment show that the sample with a doping ratio of 10% has the highest efficiency in catalyzing the degradation of methyl orange, with a degradation rate of 85.4% in 6 hours. The study demonstrates that the ZnSe composite material doped with 10% Mn element has the best relative optical absorption and catalytic performance. The high-pressure phase transition of ZnSe samples and samples with a doping ratio of 10% were investigated using Diamond Anvil Cells combined with in-situ Raman spectroscopy. The results show that: (1) The LO phonon mode of pure ZnSe disappears at a pressure of 12.3 GPa, and the TO phonon mode disappears at a pressure of 20.8 GPa. No new peaks are generated during the entire pressure process, indicating a high-pressure behavior of the pure ZnSe phase transition from the zincblende phase to the rocksalt phase. (2) The TO phonon mode of the composite material splits at 6.9 GPa, and a new peak appears at 208 cm^-1 at 8.0 GPa, indicating that some samples transform from the zincblende phase to the wurtzite phase at this pressure. The peak of the wurtzite phase disappears at 10.8 GPa, and the system undergoes a phase transition from the wurtzite phase to the rocksalt phase. When the pressure is increased to 18.8 GPa, the LO phonon mode is very weak and almost disappears, indicating that the zincblende phase in the system has completely transformed into the rocksalt phase. This study investigated the photo-catalytic performance and phase transition behavior of ZnSe under different conditions and explored the effects of different doping ratios on the photo-catalytic performance of ZnSe, determining that the sample with a doping ratio of 10% is the best composite material, which enriches the diversity of the physical and chemical properties of ZnSe under extreme conditions.
		2024 Vol. 44 (02): 380-385 [Abstract] ( 42 ) RICH HTML PDF (13510 KB) ( 21 )

	386	Hyperspectral Detection and Visualization of Pigment Content in Different Positions of Tomato Leaf at Seadling Stage
		ZHAO Jian-gui¹, WANG Guo-liang^{1, 2}, ZHANG Yu¹, ZHAO Li-jie³, CHEN Ning¹, WANG Wen-jun¹, DU Hui-ling³, LI Zhi-wei^1*
		DOI: 10.3964/j.issn.1000-0593(2024)02-0386-06
		The leaf pigment content is an important indicator to characterize crop cultivation substrate's nutrient elements and physiological state. Rapid and accurate acquisition of pigment content and leaf position distribution is the basis for precise water and fertilizer management in facility agriculture. Chlorophyll a (Chla), Chlorophyll b (Chlb), Chlorophyll (Chll) and Carotenoid (Caro) at different leaf positions of the tomato seedling stage were used as research indicators. Ten nitrogen concentrations were prepared for the nutrient solution. We picked 1710 slices (285 samples) for VIS-NIR hyperspectral acquisition according to the leaf position. The data were preprocessed by Savitzky-Golay (S-G), standard normal variate (SNV), and multiple scattering correction (MSC). Firstly, the key bands were “roughly” extracted with the competitive adaptive reweighted sampling (CARS) algorithm. Then, the iteratively retains informative variables (IRIV) algorithm to judge the importance of key bands, and “accurately” extract the optimal set of bands by reverse eliminating strong and weak bands. The partial least squares regression (PLSR) models were established. The results showed that: (1) When the nutrient liquid nitrogen concentration was 302.84 mg·L^-1, the leaf pigment content was the largest. Moreover, the inhibitory effect of high concentration is higher than that of low concentration. The pigment content in the leaf position showed the distribution law of upper>middle>low. (2) The CARS-IRIV-PLSR algorithm, “roughly-accurately” key band screening strategy was used to extract 4, 4, 10 and 11 key bands for Chla, Chlb, Chll and Caro, and the R_p was 0.772 2, 0.732 1, 0.847 1 and 0.858 7, respectively. (3) Combined with the optimal model pigment quantitative inversion image visual expression, the distribution rules of Chla, Chlb and Chll are consistent, while the distribution rules of Caro and Chll are opposite. This conclusion is consistent with the plant's physiological characteristics and measurement results. The hyperspectral imaging technology can realize the nondestructive detection and visual expression of leaf pigment content. It provides data support and a theoretical basis for plant leaf pigment distribution, nutrient deficiency and fertilization decision-making in facility agriculture.
		2024 Vol. 44 (02): 386-391 [Abstract] ( 41 ) RICH HTML PDF (8544 KB) ( 40 )

	392	A Novel Classification Method of Foodborne Bacterial Species Based on Hyperspectral Microscopy Imaging Technology
		KANG Rui^{1, 2}, CHENG Ya-wen^{1, 2}, ZHOU Ling-li^{1, 2}, REN Ni^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2024)02-0392-06
		The early and rapid detection of food-borne pathogens still challenges global food safety. Although routine tests such as selective agars served as the gold standard for decades, these methods are time consuming, often exceeding the best control time for foodborne bacterial outbreak. A hyperspectral microscopic imaging (HMI) technology coupled with an artificial intelligence algorithm was proposed to detect the common foodborne bacteria. The HMI technology has a natural trait in generating robust high-resolution spatial and spectral characterization at the cellular level. In this study, the Bi-directional long short-term memory (Bi-LSTM) was employed in the classification of Campylobacter jejuni (C. jejuni), Escherichia coli O157:H7 (E. coli), Salmonella Typhimurium (S. Typhimurium) based on morphological and spectral features extracted from single cell hypercubes. Compared with traditional linear discriminant analysis (LDA, 80.1%) and principal components analysis with support vector machine (PCA-SVM, 88.5%) classifiers, our proposed Bi-LSTM achieved the highest accuracy of 91.0% on the spectral dataset. Serious false-positive problems occurred in recognising E. coli and S. Typhimurium. However, with the involvement of morphological features, the discriminability of all classifiers was significantly improved. The proposed Bi-LSTM classifier achieved the highest accuracy of 98.1% based on the morphological-spectral feature dataset, while the LDA and PCA-SVM all achieved an accuracy of 95.3%. Our study demonstrated the applicability of HMI technology for foodborne bacterial cell characterization. Furthermore, with the advantage of Bi-LSTM in instantly processing the high-dimensional spatial-spectral features, the intelligent HMI shows great potential for rapid detection of foodborne pathogens.
		2024 Vol. 44 (02): 392-397 [Abstract] ( 49 ) RICH HTML PDF (9275 KB) ( 28 )

	398	Effects of 9-Hydroxyphenanthrene on α-Glucosidase Activity and Their Binding Interactions
		ZHANG Jing, WANG Hong-hui, JIN Liang, LIAO Ying-min, LI Heng
		DOI: 10.3964/j.issn.1000-0593(2024)02-0398-08
		Alpha-glucosidase (GAA), as an important glycoside hydrolase, is avital functional protein to maintain human blood glucose balance. For a long time, researchers have focused on exploring foods and drugs with inhibition of α-glucosidase activity in order to reduce blood glucose in people with hyperglycemia. However, few studies have focused on the possible effects of non-active intake of exogenous substances on the normal physiological functions of GAA. Given this, 9-hydroxyphenanthrene (9-OHPhe), a hydroxyl metabolite of a typical polycyclic aromatic hydrocarbon—phenanthrene, was selected in this study to explore its influence on GAA activity and potential mechanism. In order to obtain the binding information of 9-OHPhe and GAA, the PARAFAC method was applied to analyze the three-dimensional fluorescence spectra (EEM) data of 9-OHPhe and GAA with overlapping spectra, and the molecular docking method was used to analyze the microscopic information of their binding at the molecular level. 9-OHPhe inhibited the activity of GAA, and the corresponding IC50 value was (7.59±1.91) μmol·L^-1. PARAFAC method can be effectively used to analyze the fluorescence data of GAA and 9-OHPhe systems with overlapping fluorescence spectra. 9-OHPhe can cause the static quenching of endogenous fluorescence of GAA, and they can form a 1∶1 complex with the binding constant of (8.91±0.68)×10³ L·mol^-1 at 298 K. The hydrophobic interactions existed between 9-OHPhe and GLN281, LEU305, ASN319, LEU321, TYR322, LEU323, TYR352 in GAA, and two hydrogen bonds with bond lengths of 2.71 and 3.05 Å formed for 9-OHPhe with GLN309 and ASN319. A low concentration of 9-OHPhe can stabilize the secondary structure of GAA, while too high a concentration of 9-OHPhe will destroy the structural stability of GAA. 9-OHPhe showed anobvious inhibitory effect on the activity of GAA, suggesting that the glucose balance disorder which might be caused through this pathway after the relevant exogenous pollutants entered the healthy human body was worthy of attention and in-depth study.
		2024 Vol. 44 (02): 398-405 [Abstract] ( 49 ) RICH HTML PDF (10097 KB) ( 25 )

	406	Study on Modeling Method of General Model for Measuring Three Quality Indexes of Pear by Handheld Near-Infrared Spectrometer
		MAO Xin-ran, XIA Jing-jing, XU Wei-xin, WEI Yun, CHEN Yue-yao, CHEN Yue-fei, MIN Shun-geng, XIONG Yan-mei^*
		DOI: 10.3964/j.issn.1000-0593(2024)02-0406-07
		Pear is a very common fruit in life and one of the three major fruits in China. The sugar content, acidity (pH) and hardness of the pear are important indexes to evaluate the quality of the pear. Near infrared spectroscopy (NIR) is widely used to detect the quality of fruits because of its fast, non-destructive and high efficiency advantages. The hand-held near-infrared spectrometer can be applied to the on-site nondestructive testing of pear quality. Different pear sizes will have a certain impact on the spectrum and modeling of pears. The near-infrared spectra of five pear varieties (Sydney, Hongxiangsu, Honey pear, Hongxiao pear and Sour pear) with different sizes are collected. The largest pear, Sydney has an average equatorial circumference of 27.64 cm and a weight of 362.84 g. The smallest pear has an average equatorial circumference of 18.35 cm and a weight of 112.67 g. A total of 197 samples. The spectral range is 900~1 700 cm^-1, three points were selected on the equator of the pear to measure the three chemical indexes of the pear fruit: soluble solids, acidity (PH) and hardness. It was found that the absorbance of small pear was higher than that of large pears. The three-point average spectrum is used to represent the spectrum of the sample and the first-order derivative pretreatment, which improves the consistency of the spectrum, and solves the influence of factors such as sample heterogeneity and different pear sizes. The determination coefficients of the correction set of the linear regression model PLS for soluble solids, acidity (pH) and hardness were 0.739 4, 0.933 5, 0.886 6, 0.755 9, 0.873 4, 0.787 4, and 0.550 4, 0.194 1, 0.518 1, respectively. The RMSEP of the prediction set is 0.656 4, 0.242 0 and 0.669 2 respectively. The determination coefficients of the calibration set of the nonlinear regression model LSSVM for soluble solids, acidity (pH) and hardness are 0.976 3, 0.999 9 and 0.996 0 respectively, the determination coefficients of the prediction set are 0.923 4, 0.977 7 and 0.939 4 respectively, and the RMSEC of the calibration set is 0.194 9, 0.003 3 and 0.089 4 respectively. The RMSEP of the prediction set is 0.316 9, 0.108 9 and 0.361 3 in order. Compare linear algorithm with the nonlinear algorithm; the LS-SVM modeling effect is better than PLS. The LS-SVM algorithm ensures that the model is applicable to the prediction of more varieties and a wider quality index range. The accuracy and stability of the model have been significantly improved. It can establish a general model for pears of different varieties and sizes. The handheld near-infrared spectrometer can be used for the rapid, non-destructive and efficient detection of sugar, hardness and pH value of pear fruits, and it has got rid of the limitations of the laboratory. It can realize on-site rapid detection.
		2024 Vol. 44 (02): 406-412 [Abstract] ( 43 ) RICH HTML PDF (7160 KB) ( 27 )

	413	Intact-Cell Detection of Haloacid Dehalogenase Activity Based on Fluorescence Spectroscopy
		CHEN Peng^{1, 2}, LU Feng², ZHAO Yun-li^1*
		DOI: 10.3964/j.issn.1000-0593(2024)02-0413-06
		Haloacid dehalogenase can degrade halocarboxylic acids that are harmful to the environment. In addition, their stereoselectivity can produce pure chiral halocarboxylic acid. Therefore, haloacid dehalogenase has potential applications in environmental protection and chemical synthesis. It is of great significance to establish a method to detect the activity of haloacid dehalogenases. Haloacid dehalogenase DehE has good catalytic performance and can catalyze the dehalogenation of 2-chloropropionic acid to produce protons in the weak alkaline range (pH 8.00~9.50), changing the pH of the reaction system with weak buffering capacity. The HP of the solution greatly affects the fluorescence intensity of some substances. Based on this, the selected fluorescence pH indicator established an intact-cell detection method for haloacid dehalogenase activity. The results showed that the fluorescence pH indicator 2-naphthol-6,8-disulfonate could sensitively reflect the pH change in the weak alkaline range. The established method has the best detection effect under the condition of 20 mmol·L^-1 HEPES, pH 8.50, 45 ℃ and 45 mmol·L^-1 2-chloropropionic acid, avoiding the appearance of false positive results. A 50% fluorescence change was observed at 15 min with OD₆₀₀ 2.0 of the tested bacterial suspension. HPLC verified the specificity of method. The method can rapidly, and sensitively detect haloacid dehalogenase activity at the intact-cell level. In addition, when the activity of haloacid dehalogenases in the microbe is comparable to that of DehE, the detection limit of the established method for the microbe is OD₆₀₀ 0.3 of the bacterial suspension. In summary, this method has the potential for in situ qualitative screening and analysis of microorganisms containing haloacid dehalogenases.
		2024 Vol. 44 (02): 413-418 [Abstract] ( 41 ) RICH HTML PDF (2104 KB) ( 103 )

	419	The Mechanism of Moisture Influence and Correction of Electroplating Sludges Testing With EDXRF
		TENG Jing^{1, 2}, SHI Yao², LI Hui-quan^{2, 3}, LIU Zuo-hua^1, LI Zhi-hong², HE Ming-xing^{2, 4}, ZHANG Chen-mu²
		DOI: 10.3964/j.issn.1000-0593(2024)02-0419-07
		Electroplating sludges are produced in wastewater treatment in metal processing, electronic component manufacturing and other industries with hazardous waste containing heavy metals. Many electroplating sludges about 10 million tons every year, have been produced in China. It contains various valuable metal elements such as Zn, Cu, Fe, Ni, Cr, its resource utilization potential is huge. The improper disposal of a large amount of sludges will also endanger human health and pollute the environment. The traditional chemical analysis testing process is complex, but energy-dispersive X-ray fluorescence (EDXRF) spectroscopy analysis is fast, simple, cost-effective, and can achieve in-situ detection. However, the high moisture content and unstable component content of electroplating sludge samples affect the accuracy of test results. It is a difficult to ensure the resource conversion efficiency of key elements and difficult to control environmental pollution. Therefore, it is necessary to analyze the mechanism of water influence in EDXRF detection and explore moisture correction methods to improve the accuracy of test results. The mechanism of the influence of moisture on the spectral background, scattering peak, and target element characteristic peak during the EDXRF testing process of electroplating sludge was studied. By the ratio of target element characteristic peak to Rayleigh scattering peak intensity, and the sample moisture content ω₀(wt%) and target element content C_i%, a moisture correction model was established. The experimental correction factors in the moisture correction equation for Ca, Cr, Fe, Ni, Cu, Zn target elements were explored. The results show that the moisture correction model has high accuracy in correcting the five heavy metals Cr, Fe, Ni, Cu, and Zn, and the correlation coefficient R² between the corrected value and the reference value is high, R² are higher than 0.95, and RMSE are lesser than 0.05, indicating a low accuracy in correcting Ca elements R² is 0.93. RMSE is 1.046 require further optimization by adding relevant correction factors. The research is expected to be applied to the moisture correction method for the on-site measurement of electroplating sludge disposal in the recycling copper industry, which can improve the utilization efficiency of electroplating sludge resources and reduce the risk of environmental pollution.
		2024 Vol. 44 (02): 419-425 [Abstract] ( 45 ) RICH HTML PDF (4228 KB) ( 88 )

	426	Ratiometric Fluorescence Determination of Levofloxacin Based on Fluorescence Resonance Energy Transfer Between Tetramethylbenzidine and Acridine Orange
		ZHAI Hao-ying, ZHAO Wen-lin, ZHOU Wen-jun^*
		DOI: 10.3964/j.issn.1000-0593(2024)02-0426-08
		A novel ratiometric fluorescence probe for the determination of levofloxacin hydrochloride (LVF) was established based on fluorescence resonance energy transfer (FRET) between 3, 3’, 5, 5’-tetramethylbenzidine (TMB) and acridine orange (AO). Under 310 nm excitation, the fluorescence spectra of TMB at 350～500 nm overlap with the absorption spectra of AO in the pH 5.0 NaAc-HCl buffer solution. Accordingly, the FRET system is constructed with TMB as the energy donor and AO as the energy receptor. According to the energy transfer theory, the FRET efficiency of the system is 62.5%, and the distance between the donor and receptors is 2.17 nm, further indicating that FRET occurs between TMB and AO. When LVF is added, TMB transfers the fluorescence energy to LVF, which transfers the energy to AO as a donor. LVF acts as a bridge between TMB and AO. LVF transfers the absorbed fluorescence energy of TMB to AO, resulting in a significant decrease in the fluorescence intensity of TMB and a significant increase in the fluorescence intensity of AO, thus improving the FRET efficiency of the system. Under the optimal experimental conditions, there is a good linear relationship between the ratio of F_{546 nm} to F_{402 nm} and LVF concentration in the 2～80 μmol·L^-1 range. The linear regression equation is F_{546 nm}/F_{402 nm}=87.916c+3.108, the linear correlation coefficient is 0. 9993, and the detection limit (LOD) is 15.7 nmol·L^-1. Some common cations (K⁺，Mg²⁺，Ca²⁺，Cu²⁺，Mn²⁺，Zn²⁺，Co²⁺，Ni²⁺，Cr³⁺, etc), anions (F^-，Br^-，NO^-₃，IO^-₃，CO^2-₃，SO^2-₄, etc), sugars (glucose, sucrose and starch), drugs (glutathione, ascorbic acid and isoniazid) and several amino acids (glycine, leucine, cysteine, etc) do not interfere with the determination of levofloxacin, indicating that the ratiometric fluorescent probe has high selectivity for LVF. The method was applied to determine LVF in commercial pharmaceutical preparations with a recovery of 93%～97%. The ratiometric fluorescence probe has great potential in clinical application for the detection of LVF, which provides a good theoretical basis for the development of a simple, selective and sensitive sensor for the determination of LVF in pharmaceutical preparations, and a certain method guidance for improving the safety and rationality of LVF inclinical medication.
		2024 Vol. 44 (02): 426-433 [Abstract] ( 42 ) RICH HTML PDF (4440 KB) ( 89 )

	434	Simulation and Software Development of Electronic Circular Dichroic Spectrum
		XU Fan², SU Jun-kui¹, WEN Yan¹, GAN Li-she^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2024)02-0434-05
		Organic small molecules, especially natural products, have complex and diverse structures and generally contain multiple chiral centers, so the determination of their absolute configuration has always been a challenge in structural elucidation. Electronic circular dichroism (ECD) is a powerful tool for identifying absolute configuration because of its concise curve and without sample loss. With effective use of computer technology and quantum chemistry theories such as density functional theory (DFT) and time-dependent density functional theory (TDDFT), the calculation of theoretical ECD spectrum and comparison with the experimental one has become a state-of-the-art technique for absolute configuration determination. The main process is as follows: First, the relative configuration of the compound needs to be determined before calculation. Conformation analyses are carried out to identify multiple lowest energy conformers, which are then subjected to geometric optimization and vibration analysis (such as the energy threshold within 2.0 kcal·mol^-1). ECD-related parameters, such as electronic excitation energy (eV) and rotor strength (10^-40 erg-esu-cm), are further calculated for each lowest energy conformer. Finally, these data are processed according to Gaussian broadening function for spectrum fitting, and the calculated spectrum of all conformers is averaged according to their Boltzman weight. This article mainly summarizes the simulation method of the ECD curve and the evaluation standards of the ECD calculation result. Furthermore, software was developed for automatically processing Gaussian ECD calculation results and simulation of ECD curve based on Python language. The software can locate keywords in the output files. For the geometry optimization and vibration analysis output files, it can capture the Gibbs free energy data of each conformer and weight the Boltzmann distribution. The ECD-related properties output files can capture the excitation energy (eV), the corresponding oscillator and rotatory strength, and simulate the theoretical spectrum. The software can adjust simulation parameters in real-time and compare them with the experimental curve, facilitating the data processing and result evaluation of the calculated ECD.
		2024 Vol. 44 (02): 434-438 [Abstract] ( 40 ) RICH HTML PDF (4241 KB) ( 125 )

	439	Study on Near-Infrared Spectroscopy, Mechanics and Salt Water Resistance of Epoxy Resin-Based Near-Infrared Absorbing Coatings
		ZHANG Wei-gang, PAN Lu-lu, LÜ Dan-dan
		DOI: 10.3964/j.issn.1000-0593(2024)02-0439-07
		A near-infrared low reflectivity coating with outstanding mechanical properties and salt water resistance was prepared using epoxy resin as a binder, Sm₂O₃ as a functional pigment, silane coupling agent and graphene as modifiers, respectively. The effects of Sm₂O₃ addition, silane coupling agent type, silane coupling agent addition and graphene addition on the coating properties were systematically studied. The results show that the increase of the additional amount of Sm₂O₃ can significantly reduce the reflectivity of the coating to 1.06 μm near-infrared light. When the additional amount of Sm₂O₃ is 50%, the reflectivity of the coating to 1.06 μm near-infrared light can be as low as 31.2%. At this time, the adhesion strength and impact strength of the coating can reach greades 1 and 50 kg·cm, respectively. The coating is modified with a silane coupling agent. The strong polar groups on the coupling agent can form covalent bonds with the resin matrix and the pigment in the coating, respectively, to play a bridging role, which can significantly improve the flexibility of the coating. Among which, KH560 has the best modification effect. When the addition amount of KH560 is 5%, the flexibility of the coating can be significantly improved from 9 mm before modification to 4 mm after modification. Graphene has a special coplanar structure and ultra-long conjugated structure characteristics so that its absorption of incident light can extend to the near-infrared region. In addition, the special lamellar structure of graphene makes it have high impact strength and flexibility. Adding graphene to the coating can significantly improve the mechanical properties of the coating. The study found that the addition of graphene can significantly reduce the reflectivity of the coating to 1.06 μm near-infrared light to further improve the mechanical properties of the coating. When the additional amount of graphene is 8%, the reflectivity of the coating to 1.06 μm near-infrared light can be as low as 12.6%, and the coating can have outstanding laser stealth performance at this time. At the same time, the adhesion strength, flexibility and impact strength of the coating can reach grades 1, 2 mm and 50 kg·cm, respectively, which can meet practical engineering application requirements. Under the synergistic interface optimization of epoxy resin, silane coupling agent and graphene, The microstructure, near-infrared low reflectivity properties and mechanical properties of the coating with the best formulation (50% of Sm₂O₃, 5% of KH560, and 8% of graphene) can remain stable after being corroded by salt water for 21 days. At this time, the reflectivity of the coating to 1.06 μm near-infrared light was 12.47%, and the adhesion strength, flexibility and impact strength of the coating can be maintained at grade 1, 2 mm and 45 kg·cm, respectively, indicating that the prepared coating has good saltwater resistance.
		2024 Vol. 44 (02): 439-445 [Abstract] ( 40 ) RICH HTML PDF (25086 KB) ( 23 )

	446	A Study on Lead Sources of Bronze Spearheads From Cultural Relic Administration Center of Huili County, Sichuan Province by MC-ICP-MS
		XU Jun-ping¹, YANG Ying-dong², WANG Xiao-ting^{3, 4}, DU Jing⁵, TANG Xiang⁶, LUO Wu-gan^{3, 4*}
		DOI: 10.3964/j.issn.1000-0593(2024)02-0446-06
		The Huili area of Liangshan Prefecture has become an important gateway for the Jinsha Raver's middle reaches to Yunnan since the pre-Qin period. The Huili bronze culture shows a strong local primitive cultural foundation, and in the process of historical development, there have been exchanges and interactions with regional cultures, such as the south of the Jinsha River, to varying degrees. Bronze spearheads are bronze weapons commonly unearthed in bronze culture tombs in southwest China. They usually have killing and ritual functions. In addition, because of their unique typological characteristics, they can be used as special tools to distinguish cultural factors. Since the smelting of bronze is restricted by metallurgical technology and the supply of metal ore, the production technology of bronze weapons and the mineral resource are a good example for discussing the exchanges between the bronze culture in southwestern China and the surrounding cultures. In this context, in order to explore the provenance of bronze spearheads unearthed in Huili from the Warring States Period to the early Western Han Dynasty and their interaction with the surrounding culture, this study used a portable X-ray fluorescence spectrometer (pXRF), a multi-receiver inductively coupled plasma mass spectrometer (MC-ICP-MS) and other equipment to determine the composition and lead isotope ratios of four bronze spearheads unearthed from the Guojiabao cemetery. The bronze spearhead samples have willow-shaped leaves with a slight ridge in the middle. They have no ears on the sockets and have no pattern. This type of bronze spearhead is a typical local style. The scientific and technological analysis results show that spearhead samples' alloy composition varies greatly, including Cu-Pb alloy, Cu-Sn-Pb alloy and Cu-Pb-Sb alloy. However, the lead contents of all samples are higher than 2%, which means that the lead material was artificially added. The lead isotopic ratio analysis results revealed that the ore sources of this batch of copper spear samples were divided into two distinct groups: ordinary lead and highly radioactive lead. By comparing the lead isotope data of lead ore in the surrounding areas, it can be seen that the Huili bronze spearhead used the local lead materials and used the lead ore from the Jinshachang in Huize, northeastern Yunnan. From the Warring States Period to the Qin and Han Dynasties, the northeastern part of Yunnan belonged to the control area of the ancient Yelang bronze culture. It can be speculated that the Huili Bronze Culture and the Yelang Bronze Culture had close communication and connections.
		2024 Vol. 44 (02): 446-451 [Abstract] ( 37 ) RICH HTML PDF (5677 KB) ( 20 )

	452	Spectroscopic Analysis of the Mural's Materials in Prince Shi's Palace of the Taiping Heavenly Kingdom
		SHUI Bi-wen^{1, 2, 3}, SUN Man-li^{1, 2}, YU Zong-ren^3*, WANG Zhuo³, ZHAO Jin-li³, CUI Qiang³
		DOI: 10.3964/j.issn.1000-0593(2024)02-0452-08
		The murals in Prince Shi's Palace are typical of the murals in southern China, and they are also the most complete and painted mural relics of the Taiping Heavenly Kingdom. Because it is located in a humid area in the south, under the influence of environmental factors, the murals of Prince Shi's Palace have appeared with various diseases, and the preservation status is not optimistic. In order to protect this important mural, it is necessary to conduct scientific research on the production materials of murals. The nondestructive analysis was carried out by p-XRF and Raman spectroscopy. It was found that cinnabar (HgS) and hematite (Fe₂O₃) were used as the red pigments for the murals, and the white pigments were mainly calcite (CaCO₃). Analytical conditions limit other pigments, and no color components are detected. Several trace pigment and ground samples were obtained by sampling, and spectroscopic analysis techniques such as microscopic infrared spectroscopy (μ-FTIR), X-ray diffraction (XRD), micro-Raman spectroscopy (μ-Raman) and pyrolysis-gas chromatography/mass spectrum(Py-GC/MS) were used in the laboratory to analyze the blue-green pigments, ground components, binding material, types of fibers, etc. The results show that blue pigment is the first modern synthetic pigment prussianblue (Fe₄[Fe(CN)₆]₃), introduced into China and widely used in the middle and late Qianlong period. There are three kinds of green pigments, including synthetic atacamite, lavendulan, green discoloration product of paris green, and cumengite, first discovered in China. However, the current research has not seen the case of the use of cumengite as a pigment, and there is no report of such minerals in China. It is believed that the cumengite found in the murals is the product of the discoloration of other copper containing pigments. The results of Py-GC/MS show that there are proline and hydroxyproline in the pigment layer of the murals in prince Shi's Palace, which are the main components of animal glue, so animal glue is used as the cementing material for the murals. By calculating the infrared spectral characteristic peak ratios (I_{1 595}/I_{1 105}) and R₂ (I_{1 595}/I_{2 900}) of the fibers in the mural mud ground and lime ground, it is concluded that the fibers in the mural mud ground are ramie fibers and the fibers in the lime ground are cotton fibers. The research provides a scientific basis for pigment identification, restoration materials selection and scientific conservation of murals in Prince Shi's Palace of the Taiping Heavenly Kingdom.
		2024 Vol. 44 (02): 452-459 [Abstract] ( 53 ) RICH HTML PDF (46134 KB) ( 57 )

	460	Annual Variation of Solar Spectra in Tibet
		Lagba Tunzhup, Tsoja Wangmu^*, WANG Qian, SHENG Min, WANG Meng-meng, Norsang Geslor
		DOI: 10.3964/j.issn.1000-0593(2024)02-0460-07
		Accurate measurement of solar spectra on the ground can provide field data for the inversion of the atmospheric environment, utilization of solar energy resources, and protection of plant ecology, etc. . According to current satellite and ground-based observations, Tibet is one of the regions with the strongest instantaneous solar irradiance on the earth due to factors such as high altitude and thin air. Observing the characteristics of solar spectral changes in Tibet is of unique significance for studying various fields such as human health, ecological changes, and solar energy utilization under strong radiation environments. From 2020 to 2021, we use the German RAMSES-ACC-VIS spectrometers and the Canadian SolarSIM-G high-precision spectrometers to study the solar spectra of five high-altitude areas in Tibet (Lhasa, Nyingchi, Nacqu, Shigaze and Tingri) for a whole year. For the first time, obtain one-year solar spectral field data from many places in Tibet, and record the daily averaged spectral irradiance of solar ultraviolet, photosynthetically active radiation and infrared radiation for every minute. The annual daily averaged solar spectral characteristics in Tibet are analyzed and studied. It is found that the highest daily averaged spectral peak of 1.12 W·m^-2·nm^-1 appeared at the wavelength of 477.30 nm. The seasonal variation characteristics of the solar spectra in Lhasa, a typical plateau region in Tibet, are studied, and the range of spectral irradiance between the solstices. It is found that the daily averaged spectral irradiance at the summer solstice in Lhasa is more than twice as high as that at the winter solstice. The peak value of the spectral irradiance at the summer solstice is about 1.13 W·m^-2·nm^-1, and that at the winter solstice is 0.43 W·m^-2·nm^-1. The fluctuation change of the annual solar spectra in Shigaze, Tibet is smaller than that in Lhasa. Its spectral change of each solar term is relatively concentrated. The difference between the summer and winter solstice's peak spectral values is smaller than in Lhasa. The characteristics of annually averaged solar spectral irradiance over Tibet are studied. It is found that the annually averaged solar spectral irradiance of Shigaze and Mt. Everest is very close, and the peak value of the two places is about 0.83 W·m^-2·nm^-1; The annually averaged spectrum of Lhasa is slightly lower than that of Shigaze and Tingri, with a peak value of about 0.73 W·m^-2·nm^-1; The annually averaged spectral curve of Nacqu is the lowest, with a peak value of only 0.53 W·m^-2·nm^-1. The annual mean value of the solar spectrum and the distribution characteristics of solar energy resources in different regions have important application value for developing and utilizing solar energy resources on the Tibetan Plateau. In order to compare the solar spectral characteristics of the Tibetan Plateau and the mainland plain, clear sky solar spectra of high altitude Lhasa (3 693 m) and low altitude Beijing (32 m) are observed and studied simultaneously. On June 3, 2021, both places are clear sky days; analyzing the local noon solar spectral characteristics in both places, it is found that the full band spectral integral value of Lhasa at noon is about 20% higher than that of Beijing, and only about 5% lower than that of Air Mass AM0. the peak of the local noon spectrum of Lhasa reaches 1.80 W·m^-2·nm^-1, and that of Beijing is about 1.40 W·m^-2·nm^-1; The solar UV spectral integral value of local noon in Lhasa was about 15% higher than that of in Beijing.
		2024 Vol. 44 (02): 460-466 [Abstract] ( 53 ) RICH HTML PDF (5678 KB) ( 35 )

	467	*Quantitative Modeling and Content Determination of Active Ingredients in Lonicera Japonica* Flos by Fourier Transform Infrared Spectroscopy**
		GU Xu-peng^{1, 2}, YANG Lin-lin^{1, 2}, QI Da-ming^{1, 2}, LIU Tian-liang^{1, 2}, DONG Cheng-ming^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2024)02-0467-07
		Chinese medicinal materials are “safe, stable, effective and reliable”, which is the real demand for the modernization and development of Chinese medicine. To explore new rapid, accurate and non-destructive content determination methods for Chinese medicinal materials with varying quality is one of the urgent problems in the field of quality control of Chinese medicinal materials. The active ingredients of Lonicerae Japonicae Flos are complex and fluctuate in quality. The efficient, non-destructive and rapid determination of the active ingredients of Lonicerae Japonicae Flos using Fourier transform infrared spectroscopy may be an effective measure to promote its quality control. In this study, the HPLC method was combined with Fourier transform infrared spectroscopy to establish a model for the determination of the active ingredients of Lonicerae Japonicae Flos using chemometric methods, in order to provide a new method for the rapid and accurate content determination of Lonicerae Japonicae Flos. In this study, the infrared spectra of 64 Lonicera Japonica Flos samples from Henan, Hebei and Shandong provinces were collected using a Fourier transform spectrometer. Simultaneous determination of the contents of six active ingredients in Lonicera Japonica Flos including chlorogenic acid, sweroside, secoxyloganin, cynaroside, isochlorogenic acid A and isochlorogenic acid C by HPLC. Multiple scattering correction (MSC), stand ard normal transformation (SNV), partial least squares (PLS), stepwise multiple linear regression (SMLR), first derivative (1st), second derivative (2nd), SG curl smoothing and Norris derivative filtering (ND) in TQ analysis software are used for spectral processing to establish the model after the chemometric analysis of 64 Lonicera Japonica Flos samples from Henan, Hebei and Shand ong. The result shows that the model of “PLS+MSC+2nd Der+NS” has the best prediction effect on chlorogenic acid content, with a correlation coefficient of 0.754 9 and an average absolute deviation of 0.24%. The “PLS+MSC+1st Der+ND” model has the best prediction effect on sweroside content, with a correlation coefficient of 0.936 9 and an average absolute deviation of 0.00%. The “PLS+MSC+1st Der+SG” model has the best prediction effect on secoxyloganin content, with a correlation coefficient of 0.967 8 and an average absolute deviation of -0.06%, the model of “PLS+MSC+1st Der+NS, PLS+MSC+1st Der+SG and PLS+SNV+1st Der+SG” has the best prediction effect on cynaroside content, with a correlation coefficient of 0.859 0 and an average absolute deviation of 0.01%. The model of “PLS+MSC+2nd Der+ND” has the best prediction effect on isochlorogenic acid A content, with a correlation coefficient of 0.933 9 and an average absolute deviation of 0.11%. The model of “PLS+MSC+2nd Der+SG” has the best prediction effect on isochlorogenic acid C content, with a correlation coefficient of 0.866 1 and an average absolute deviation of 0. 01%. It can be seen that the quantitative model of the active ingredients in Lonicerae Japonicae Flos established by Fourier transform spectral data can realize the content prediction of the active ingredients in unknown Lonicerae Japonicae Flos samples. This study provides a new method for the rapid and non-destructive testing of the active ingredients of Lonicerae Japonicae Flos, and also helps to achieve stable and controllable quality of traditional Chinese medicinal materials.
		2024 Vol. 44 (02): 467-473 [Abstract] ( 44 ) RICH HTML PDF (2556 KB) ( 118 )

	474	Spectroscopic Characteristics of Soil Humus Components Extracted With Acetone Hydrochloric Acid Mixture
		SONG Ge^{1, 2}, KONG Xiang-shi^3*
		DOI: 10.3964/j.issn.1000-0593(2024)02-0474-06
		The components of soil humic acid (HA) and humin (HU) were extracted by acetone hydrochloric acid mixture, their elemental components were analyzed, and their spectroscopic characteristics were analyzed by UV-Vis diffuse reflectance and infrared spectroscopy. Elemental analysis showed that HA had higher carbon, hydrogen, nitrogen, and sulfur contents while having lower oxygen content than HU. Atomic ratio analysis showed that HA had a higher condensation degree and more complex molecular structure than HU. The UV-Vis diffuse reflectance spectrum analysis showed that HA and HU had no obvious characteristic peak because of the complex composition of humic substances and the mutual interference of various functional groups. The UV absorbance decreased with the increase of wavelength, and HA contained more light absorbing organic components. The UV characteristic parameters of SUV₂₅₄ and E₄/E₆ showed that HA had higher aromaticity and humification degree than HU. Infrared spectrum analysis shows that HA and HU have similar infrared spectra. However, the absorption intensity of characteristic absorption peaks of each research object is different. The vibration amplitude of HA in soil layer of 20～40 cm cultivated black soil and 18～37 cm uncultivated gray soil is larger, indicating that they had high contents of phenolic compounds, hydroxyl functional groups, aliphatic compounds, carboxyl groups, aldehydes, ketones, ethers, carbohydrate and amine compounds. The vibration amplitude of HU in soil layer of 10～20 cm cultivated black soil and 18～37 cm uncultivated gray soil is large, indicating that they contain more phenolic compounds, carboxylic acid, aliphatic hydrocarbons and sugars. In addition, intensity comparison of each absorption peak in the infrared spectrum showed that the content of phenolic compounds, hydroxyl functional groups and aliphatic compounds in HA and HU of black soil increased after cultivation. In contrast, the content of phenolic compounds, carboxyl groups and aliphatic compounds in HA and HU of gray soil decreased after cultivation. These results showed that cultivation has relatively little impact on black soil organic matter, and to a certain extent, increased soil organic matter content, but promoted the decomposition of gray soil organic matter. In conclusion, the acetone hydrochloric acid mixture extraction method provides new technical support for studying the biochemical and physiological activities of humic substances, which provide a theoretical basis for rational utilization of soil resources.
		2024 Vol. 44 (02): 474-479 [Abstract] ( 52 ) RICH HTML PDF (1831 KB) ( 76 )

	480	Study on Hyperspectral Detection of Potato Dry Rot in Gley Stage Based on Convolutional Neural Network
		ZHANG Fan¹, WANG Wen-xiu¹, WANG Chun-shan², ZHOU Ji², PAN Yang³, SUN Jian-feng^1*
		DOI: 10.3964/j.issn.1000-0593(2024)02-0480-10
		Potato is the fourth largest food crop in the world and has rich nutritional value. However, it is easy to be infected by the sickle fungus during storage and transportation, resulting in a huge waste of resources and economic losses. Therefore, it is necessary to quickly and accurately realize the early nondestructive detection of potato dry rot. When pathogenic bacteria infected the samples, they experienced the stages of healthy-gley stage-mild disease-severe disease. The gley stage was difficult to identify, mainly because the disease occurred quickly and no visible disease spots were formed on the surface, similar to the healthy samples. In order to realize the recognition of the gley stage of potato dry rot, this study combined hyperspectral imaging technology and deep learning to carry out early diagnosis of potato dry rot. The hyperspectral images of healthy potatoes and potatoes with different spoilage grades were obtained. Based on the ENVI, healthy parts and spots of samples with different grades of corruption were selected as regions of interest (ROI), and the average spectral value of ROI was calculated as the final spectral information of the sample. The Convolutional Neural Network (CNN) model was established with the spectral data as the input variable and the disease grade as the output variable, and the network structure was optimized. The results of different models were compared and analyzed, and the optimal model was selected as Model_3_3. Based on the optimal structure, the learning rate was optimized, and the Model_0.0001 has the best recognition effect, and its overall accuracy, accuracy, sensitivity and specificity are 99.68%, 99.76%, 98.82% and 99.54%, respectively. In order to further highlight the advantages of CNN in gley stage identification of potato dry rot, LSSVM, RF, KNN and LDAmodels were established. The results showed that the accuracy of the four conventional algorithm models were 90.77%, 92.30%, 93.10% and 92.34%, respectively, and the recognition rate of gley samples was 91.00%, 85.58%, 94.18% and 90.33%, respectively. For overall accuracy, the CNN model improves by 6.58%~8.91% compared with other conventional methods. Compared with conventional methods, the CNN model improved the recognition of gley samples by 5.55%～14.15%. The results show that hyperspectral imaging combined with CNN can effectively recognize the gley stage of potato dry rot, which provides a reference method for improving the intelligence level of early diagnosis of potato disease.
		2024 Vol. 44 (02): 480-489 [Abstract] ( 48 ) RICH HTML PDF (24685 KB) ( 39 )

	490	Composition and Spectral Characteristics of Soil Dissolved Organic Matter Leachate From Different Planted Tree Species
		WANG Hai-zhen^{1, 2, 3}, GUO Jian-fen^{1, 2, 3*}, ZHANG Lei^{1, 2, 3}, LIN Hao^{1, 2, 3}, LIN Jing-wen¹, XIONG De-cheng^{1, 2, 3}, CHEN Shi-dong^{1, 2, 3}, YANG Yu-sheng^{1, 2, 3}
		DOI: 10.3964/j.issn.1000-0593(2024)02-0490-07
		Dissolved organic matter (DOM) is a labile carbon and nutrient pool inforest ecosystems and its properties are affected by plant species, soil properties, hydrological conditions and other factors. To investigate the effects of tree species on the composition and spectral properties of soil DOM leachate, one-year-old seedlings of Castanopsis carlesii (CC), Cunninghamia lanceolata (CL), and Ormosia Henryi (OP) were planted in the root boxes (0～60 cm), and no planting was set as the control. After a rainstorm in August 2021, soil DOM leachate in the root box was collected to determine its composition and spectral characteristics. The results show that: (1) The content of dissolved organic carbon (DOC) in soil leachate of Cunninghamia lanceolata seedlings was significantly higher than those of Ormosia Henryi and Castanopsis carlesii seedlings (p<0.05). (2) The value of the aromatic index (SUVA₂₅₄) in the soil leachate of Castanopsis carlesii was the highest, and that of the hydrophobic index (SUVA₂₆₀) in soil leachate of Cunninghamia lanceolata was the lowest. There was no significant difference in the molecular weight (SUVA₂₈₀) in the soil leachate of different tree species. (3) There were no significant differences in the DOM fluorescence index (FluI), freshness index (Frl) and biogenic index (BIX) of soil leachate among the three tree species and no-tree species in the root box soil leachate. The DOM fluorescence humification index (HIX) of soil leachates in all treatments was less than one, and the HIX of soil DOM leachates of Ormosia Henryi and Castanopsis carlesii were significantly higher than that of no-tree control (p<0.05). Soil DOM leachate was mainly composed of three components, fulvic and humic acid-like (C1), humic acid-like (C2) and soluble microbial products (C3). Compared with the soil DOM leachates of Ormosia Henryi and Cunninghamia lanceolata, the proportions of C1 and C2 in the soil DOM leachate of Castanopsis carlesii was higher, while the proportion of C3 was low. (4) Pearson correlation analysis showed that DOC concentration was negatively correlated with UV index (SUVA₂₅₄, SUVA₂₆₀, SUVA₂₈₀), two-dimensional fluorescence index FluI, and three-dimensional fluorescence component C2, while positively correlated with C3 (p<0.05). The results of this studyprovide some reference value for the study of soil biogeochemical cycles in the subtropical region.
		2024 Vol. 44 (02): 490-496 [Abstract] ( 44 ) RICH HTML PDF (4131 KB) ( 47 )

	497	*Enhanced Up-Conversion Emission of NaGdF₄：Yb³⁺/Eu³⁺Crystal via* Li⁺ Doping for Anti-Counterfeiting Application**
		WANG Chong¹, REN Zhong-xuan^{1, 2}, LI Dong-dong¹, SHE Jiang-bo²
		DOI: 10.3964/j.issn.1000-0593(2024)02-0497-07
		Rare earth luminescent materials have gradually become a research hotspot in fluorescence anti-counterfeiting because of their high purity of luminous color, long fluorescent life, stable physical-chemical properties, and low toxicity. A series of NaGdF₄∶Yb³⁺/Eu³⁺ microcrystals co-doped with various Li⁺ concentrations were synthesized by the hydrothermal method in this paper. The samples' morphology, size, and up-conversion luminescence properties were analyzed by X-ray diffraction (XRD), scanning electron microscopy (SEM), up-conversion emission spectroscopy, and fluorescence lifetime tests. The crystal with strong luminous intensity was further applied to anti-counterfeiting identification. It shows that all the diffraction peaks of NaGdF₄∶Yb³⁺/Eu³⁺/Li⁺ microcrystals are consistent with the standard-NaGdF₄ card. No impurity peak was found in the XRD pattern. The hexagonal NaGdF₄∶Yb³⁺/Eu³⁺/Li⁺ with high purity and crystallinity was synthesized. The SEM image of the crystal shows that the generated sample is a pure hexagonal phase, with uniform distribution, and no reunion. Co-doped Yb³⁺/Eu³⁺/Li⁺ has little effect on crystal structure, morphology and size. It can be seen from the up-conversion emission spectrum that the green luminescence intensity of 15 mol% Li⁺ doped NaGdF₄∶Yb³⁺/Eu³⁺ crystal is 6 times higher than that of the undoped Li⁺ sample. Adjust the power range of the laser to 0.8～2.2 W and observe the change in UCL intensity of the samples doped with 0 mol% Li⁺ and 15 mol% Li⁺. It can be observed that with the increase of pump power, the up-conversion intensity gradually increases. The number of photons required to generate the up-conversion luminescence n is close to 2, indicating that the emission process of the sample is a two-photon process. The fluorescence lifetime of the ⁵D₁ level in the sample is about 1.4 times that of the undoped one. Finally, the NaGdF₄∶0.2Yb/0.02Eu/0.15Li crystal with uniform morphology and strong luminous intensity was further applied as fluorescent ink. Screen printing technology printed The fluorescent anti-counterfeiting patterns on paper, glass and plastic. The pattern emitted bright green light under the pumping of a 980 nm laser. In the natural environment, the anti-counterfeiting pattern on the paper has good concealment. The word “safe” lenght is 5.5 mm, and the spacing between letters is 0.5 mm. The boundaries between letters are clear and easy to distinguish under 980 nm excitation. The plastic printed with the anti-counterfeiting pattern was exposed to the outdoor natural environment for a month, and the pattern did not change significantly. It shows that the anti-counterfeiting pattern made of NaGdF₄∶0.2Yb/0.02Eu/0.15Li has a high resolution, is easy to identify, and is less affected by the environment, and has excellent application prospects in anti-counterfeiting identification.
		2024 Vol. 44 (02): 497-503 [Abstract] ( 32 ) RICH HTML PDF (16975 KB) ( 18 )

	504	The Effect of Substituent Position on Photophysical Properties of Iridium Phosphorescent Complexes Based on Substituted 2,4-Diphenylpyridine
		CHANG Qiao-wen, CHEN Zhu-an, YAN Cai-xian, LIU Wei-ping, FENG Yang-yang^*
		DOI: 10.3964/j.issn.1000-0593(2024)02-0504-06
		Phosphorescent iridium complexes are the electroluminescent materials with the best comprehensive performance. Phosphorescent iridium complexes have been employed in organic light-emitting diodes (OLEDs), electrochemical light-emitting cells (LECs), photocatalysis, tumour diagnosis and sensors owing to their various advantages such as high quantum efficiency, good thermal stability and tunable emission colors. The color tuning of the iridium phosphorescent complex can be realized by changing the chemical structure of the main ligands and auxiliary ligands such as changing the conjugation degree of ligand, electron-donating and with drawing ability of substituents and substituent position. The influence of substituent position on iridium phosphorescent complex's photophysical properties was rarely researched. In this paper, we propose studying the effect of different substitution positions of methyl groups on the photophysical properties of iridium phosphorescent complexes. Two new iridium phosphorescence complexes (2,4-2Me-2,4-dppy)₂Ir(tmd) and (3,5-2Me-dppy)₂Ir(tmd) were synthesized with 2,4-diphenylpyridine of different methyl substituent positions as the main ligand and 2,2,6,6-tetramethylheptanedione as the auxiliary ligands. Their composition and spatial structure were characterized by elemental analysis, nuclear magnetic resonance (¹H NMR and ¹³C NMR) and single-crystal X-ray diffraction. Bothcomplexes show slightly distorted octahedral configuration with space groups of C 12 / C 1 and P-1, with monoclinic and triclinic crystal systems, respectively. The thermal stability was tested by TG curves, the two complexes have good thermal stability with thermal decomposition temperatures of 307 ℃ and 318 ℃ respectively. UV-Vis spectra and photoluminescence spectra studied the photophysical properties of the complexes. The emission wavelengths of the two complexes in solution were 545 and 572 nm, respectively. The quantum yields in solution were 70% and 92%, respectively. The effect of substituent position on the photophysical properties of iridium phosphorescent complexes was further discussed. It was found that the position of the methyl group had a significant effect on the luminescence color and emission wavelength of 2,4-diphenylpyridine iridium phosphorescent complexes. Compared with the iridium phosphorescent complex obtained when the methyl group is at the 2 and 4 positions, the emission wavelength of the iridium complex obtained when the methyl group is at the 3 and 5 positions has a significant redshift, which is pure yellow light emission. It is a potential yellow light material expected to be applied in OLED lighting.
		2024 Vol. 44 (02): 504-509 [Abstract] ( 45 ) RICH HTML PDF (2758 KB) ( 66 )

	510	Study of Fiber Optic Omnidirectional Sensing for Partial Discharge in Transformers by Combining FBG and FP Cavity
		WU Ke-jie¹, CHEN Wei-gen^1*, ZHANG Zhi-xian¹, SONG Yu-xuan¹, TIAN Hao-yuan¹, LI Meng¹, LIU Fan²
		DOI: 10.3964/j.issn.1000-0593(2024)02-0510-09
		To achieve sensitive detection of partial discharge in transformers and avoid missing partial discharge signals, a fiber optic omnidirectional sensing method for partial discharge in transformer oil combined with FBG and FP cavity is proposed based on fiber Bragg grating (FBG) and Fabry-Perot cavity sensing principle. The partial discharge sensing principle of FBG and FP cavity is introduced. The ultrasonic waves generated by partial discharge will cause a shift in the FBG reflection spectrum and the FP cavity interference spectrum, and the detection of partial discharge can be achieved by demodulating the optical intensity through the spectral edge demodulation method. A partial discharge fiber optic omnidirectional sensor was developed. A rectangular probe with the size of 25 mm×25 mm×25 mm was fabricated by 3D printing technology. The hollow structure of the probe was used to insert a single-mode fiber to form an FP cavity. In addition, the four sides of the probe were used to form a diaphragm-type FBG sensing structure, which can receive ultrasonic signals in different directions. The acoustic sensing diaphragm was designed based on the frequency spectrum characteristics of partial discharge in transformer oil and the vibration model of the diaphragm in the liquid phase environment. Corning glass coated with high reflectivity dielectric film was selected as the FP cavity sensing diaphragm with a radius of 1.7 mm and a thickness of 0.165 mm, and its theoretical resonant frequency is 82 kHz. Monocrystalline silicon was selected as the FBG sensing diaphragm with the radius of 2.5 mm and the thickness of 0.1 mm, and its theoretical resonant frequency is 25.6 kHz. The fiber optic sensing system for partial discharge was built, and the performance test was conducted on the partial discharge fiber optic omnidirectional sensor. The resonant frequency of FBG sensing diaphragm in transformer oil is about 23 kHz, and that of FP cavity sensing diaphragm is 71.4 kHz as measured by the pencil-break experiment. The fiber optic omnidirectional sensor was compared with the piezoelectric transducer (PZT) to detect the same partial discharge signal. 83.8 pC of metal tip discharge can be detected by the FBG sensing part and 27.1 pC of metal tip discharge can be detected by the FP cavity sensing part. The partial discharge detection sensitivity of fiber optic omnidirectional sensors is higher than that of PZT. The directional response of the sensor was tested. Ordinary FP sensors have a limited range of highly sensitive detection and a detection blind area. The developed partial discharge fiber optic omnidirectional sensor has the FP cavity sensing and FBG sensing parts. The highly sensitive detection range of the FP cavity sensing part is complementary to that of the FBG sensing part. The sensor can achieve omnidirectional sensitive partial discharge detection and has good directional response performance.
		2024 Vol. 44 (02): 510-518 [Abstract] ( 53 ) RICH HTML PDF (14273 KB) ( 17 )

	519	Spectral Response and Performance Optimization of Antimony Based Solar Cells Under Weak Light
		CAO Yu^{1, 2}, LING Tong^{1, 2}, QU Peng^{1, 2}, WANG Chang-gang^{1, 2*}, ZHAO Yao³, NA Yan-ling^{3, 4}, JIANG Chong-xu^{3, 4}, HU Zi-yang⁵, ZHOU Jing⁶
		DOI: 10.3964/j.issn.1000-0593(2024)02-0519-08
		Antimony-based thin film solar cells have rapidly developed because of their simple preparation method, abundant raw materials, and stable photoelectric performance. Among them, antimony-based light-absorbing layer materials (antimony sulfide, antimony selenide sulfide, and antimony selenide) have high absorption coefficients; thus, they have considerable application potential in indoor or underwater weak light conditions. In this study, two types of attenuation spectra are constructed to study the photoelectric response of a new antimony-based thin film solar cell under weak light. First, the light absorption capacity of the antimony selenide solar cell is adjusted through thickness. It is inferred that when the light absorber is thin, the photoelectric conversion efficiency of the cell has a significant difference. Moreover, when the light absorber is too thick, the device performance is reduced due to the carrier recombination increase. The conversion efficiency of the antimony selenide solar cell is higher than 16% in both the long- and short-wave attenuation spectra when the thickness of the light absorber is in the appropriate range of 0.4～1.2 μm. Subsequently, the selenium content adjusts the spectral absorption range of the antimony-based solar cell. It is found that the device performance of the antimony-based solar cell is significantly higher than the standard spectrum under the long-wave attenuation spectrum, and the best conversion efficiency is obtained at 20%~40% selenium content. In the short-wave attenuation spectrum, the best performance of the antimony-based solar cells appears when the selenium content is 60%. Therefore, specific spectral characteristics should determine, the optimal selenium content of antimony-based thin film solar cells in weak light conditions. Finally, the spectral response characteristics of antimony sulfide/antimony selenide double junction tandem solar cells are studied under two types of attenuation spectra. It is found that the efficiency of the tandem solar cells increases with the increase in the total thickness under the short-wave attenuation spectrum. However, in the long-wave attenuation spectrum, the best performance of the tandem solar cells can be maintained at a high level. When the total thickness of the tandem solar cell is 2 μm, and the thickness of the antimony sulfide top cell is 0.5～1.2 μm, the devices realize the rational distribution of the spectral energy in the two sub-cells under the two attenuation spectra, which maintains the efficiency of the tandem cell above 20%. Through the reasonable design of the device structure of antimony-based solar cells in this study, the high-performance output of single- and double-junction devices under different weak light conditions can be ensured, and the technical support for the research and development of antimony-based thin film solar cells with high environmental adaptability can be provided.
		2024 Vol. 44 (02): 519-526 [Abstract] ( 39 ) RICH HTML PDF (4817 KB) ( 30 )

	527	Surface-Enhanced Raman Scattering Performance of Macroporous Grapefruit-Type Microstructured Fiber Optic Probes
		LI Jia-xuan, FU Zi-zhen, CAO Xi-qing, HU Zhi-guo, FU Xing-hu^*, FU Guang-wei, JIN Wa, BI Wei-hong
		DOI: 10.3964/j.issn.1000-0593(2024)02-0527-07
		With the development of optical fiber preparation technology and nanomaterial preparation technology, fiber probes have become a new type of surface-enhanced Raman scattering (SERS) substrate; by preparing different structures on common single mode fiber or multimode fiber and modifying the corresponding nanomaterials can obtain a variety of types of optical fiber surface-enhanced Raman scattering probes, and achieve better detection results. But the structure of the fiber itself has limited it, common fiber can only use the end face or measurement surface to provide Raman detection “hot spot” area, limiting its SERS performance to further improve. In this paper, a surface-enhanced Raman scattering (SERS) probe for a macroporous grapefruit-type microstructured fibre (MSF) is prepared, in which the macroporous grapefruit-type MSF SERS probe structure is fabricated by fusing a section of stepped multimode fiber to a grapefruit-type microstructured fibre. The SERS performance of the home-made silver nanosol substrates and the macroporous grapefruit-type MSF SERS probes are examined separately. MSF SERS probes loaded with silver nanoparticles are prepared by the sol-gel self-assembly method, and different fibre-optic SERS probes are prepared by controlling the self-assembly time (Ag/MSF-x, where x is the self-assembly time, 15，30，45，60 min, respectively). The solution detection method was used to detect 10^-3 mol·L^-1 methylene blue (MB) probe molecule with Ag/MSF-x probe, and the Ag/MSF-45 probe was screened by comparing the enhancement effect under the same conditions. In order to further detect the SERS performance of the Ag/MSF-45 probe, MB solutions with different concentrations are prepared, and the nano silver soluble substrates and Ag/MSF-45 probe are used to detect them. The experimental results showed that MB's limit of detection (LOD) was 10^-6 mol·L^-1 for the nano-soluble substrate and 10^-7 mol·L^-1 for the Ag/MSF-45 probe. The reproducibility of the Raman signal shows that the RSD values for the nanosilver soluble substrates and the Ag/MSF-45 probe are within a reasonable range for each characteristic peak. A log-transformed fit of the Raman intensity and concentration of the nano silver soluble substrates and the Ag/MSF-45 probe detecting MB at a Raman shift of 1 619 cm^-1, with a good R² of 0.916 28 for the nanosol substrate and 0.988 48 for the Ag/MSF-45 probe. The reproducibility results for both the nanosilver soluble substrates and the Ag/MSF-45 probe show that their RSD values were within a reasonable range for each of the characteristic peaks, but the Ag/MSF-45 probe has a smaller RSD value for each of the characteristic peaks than the nanosilver soluble substrates, with a maximum of 13.89%. The enhancement factor (AEF) of the Ag/MSF-45 probe is calculateed using 10^-6 mol·L^-1 MB, and the AEF of the Ag/MSF-45 probe is reached 6.09×10⁶, showing a good enhancement effect. Therefore, based on the unique air pore structure of the large hole grapefruit-type MSF SERS probe, it has high sensitivity and good reproducibility, and its SERS performance is better than the nano silver soluble substrates, and has a wide range of applications in agriculture, chemical analysis, bioassay and the detection of large molecules.
		2024 Vol. 44 (02): 527-533 [Abstract] ( 46 ) RICH HTML PDF (8869 KB) ( 24 )

	534	Hyperspectral Study on Polyphenol Oxidase Content of Cauliflower at the Early Stages of Gray Mold Infection
		WANG Kai, XUE Jian-xin^*, LI Yao-di, ZHANG Ming-yue
		DOI: 10.3964/j.issn.1000-0593(2024)02-0534-08
		Hyperspectral technique was applied to detect polyphenol oxidase (PPO) content in cauliflower with early botrytis stress. A total of 253 healthy cauliflower samples and 257 infected cauliflower samples were used to acquire hyperspectral within the range of 900~1 700 nm, and the corresponding PPO content in the cauliflowers were measured with the spectrophotometry method in order to make the prediction effect better. The mean value was applied to the analysis of the PPO with cauliflower samples, and results showed that the mean PPO content of healthy cauliflower (10.257 U·g^-1) was less than that of infected cauliflower (12.324 U·g^-1). The SPXY method divides the cauliflower sample set into a calibration set (193 healthy, and 197 infected samples) and a validation set (60 healthy and 60 infected samples). Six kinds of single pretreatment were performed on the divided sample set. The R (correlation coefficient) and RMSE (root mean square error) were used as the model evaluation index, and results showed that pretreatment can effectively improve the accuracy and stability of the mode. It was found that the predictive set modeling effect of healthy samples after NOR pretreatment is the best and that of infected samples after DT pretreatment is the best. Successive projection algorithm (SPA) and regression coefficient (RC) were used to select the characteristic wavelengths. Partial least squares regression, least squares support vector machines, and BP neural networks were built to explore the impact of different feature wavelength extraction methods on the accuracy of the model and compare the accuracy of different modeling methods on the prediction of PPO content of cauliflower. The results showed that extracting the characteristic wavelength can optimize the spectral information, and the number of wavelengths extracted by SPA and RC for the two samples were 9, 12, 7 and 11 respectively. It was found that the LS-SVM model has a good fitting effect on the two samples and their corresponding enzyme activities by comparing and analyzing the effect of the model. It was found that the LS-SVM model had a good fitting effect on the two samples and their corresponding enzyme activities. Finally, the results showed that the SPA-LS-SVM model had a good prediction effect on the PPO content of healthy cauliflower, with an R_p (correlation coefficient of prediction) value of 0.832 and an RMSEP (prediction root mean square error) value of 1.676; and RC-LS-SVM model had a good prediction effect on PPO content of infected cauliflower, with a Rpvalue of 0.848 and a RMSEP value of 1.156. This study showed that the hyperspectral technique can detect PPO content in cauliflower with botrytis stress and provide a theoretical basis for rapid detection of PPO contentin cauliflower and the development of portable instruments.
		2024 Vol. 44 (02): 534-541 [Abstract] ( 45 ) RICH HTML PDF (7899 KB) ( 21 )

	542	Raman Spectroscopy Combined With the WGANGP-ResNet Algorithm to Identify Pathogenic Species
		MENG Xing-zhi, LIU Ya-qiu^*, LIU Li-na
		DOI: 10.3964/j.issn.1000-0593(2024)02-0542-06
		The expeditious identification of pathogenic bacteria plays a prominent role in preventing the spread of infectious diseases, helping combat antimicrobial resistance, and improving patient prognosis. Raman spectroscopy combined with machine learning algorithms can provide simple and fast label-free detection of pathogenic bacteria. However, pathogenic bacteria are diverse and phenotypic. However, deep learning relies on many samples for training, while collecting Raman spectra of large batches of pathogenic bacteria is laborious and vulnerable to factors such as fluorescence. To address the above problems, a pathogenic bacteria Raman spectroscopy detection model based on the combination of the WGAN-GP data enhancement method and ResNet is proposed. Raman spectra of five common ophthalmic pathogenic bacteria were used. The collected raw data are normalized as the input of ResNet and ordinary convolutional neural network (1D-CNN), SG filtering, airPLS baseline correction, PCA data downscaling data preprocessing as the input of K nearest neighbor algorithm (KNN), and the comparative analysis finds that the ResNet model works best and its classification accuracy can reach 96%; build Wasserstein Generative Adversarial Network with Gradient Penalty Model (WGAN-GP) is built to generate a large amount of high-resolution spectral data similar to the real data. In order to verify that the generated data can enrich the data diversity and thus improve the classification accuracy, the expanded dataset was re-entered into the ResNet model for training, and the classification accuracy of WGAN-GP combined with ResNet was finally improved. The classification accuracy of WGAN-GP combined with ResNet was improved to 99.3%. The improved WGAN-GP model is suitable for Raman spectral data enhancement, which solves the problem of mismatch between the validity of the spectra generated by traditional data enhancement methods and the accuracy of the categories. The surface-enhanced Raman spectroscopy (SERS) combined with the WGANGP-ResNet model established by this method for pathogenic bacteria Raman spectra classification reduces the need for a large amount of training data, facilitates rapid learning and analysis of Raman spectra with a low signal-to-noise-ratio, and reduces the spectra acquisition time to 1/10. It has important research significance and application value in pathogenic bacteria's rapid and culture-free clinical identification.
		2024 Vol. 44 (02): 542-547 [Abstract] ( 46 ) RICH HTML PDF (5298 KB) ( 69 )

	548	A Fine Classification Method of Citrus Fruit Trees Based on UAV Hyperspectral Images and SULOV_XGBoost Algorithm
		XIAO Bin^{1, 2}, HE Hong-chang¹, DOU Shi-qing^1*, FAN Dong-lin¹, FU Bo-lin¹, ZHANG Jie¹, XIONG Yuan-kang¹, SHI Jin-ke¹
		DOI: 10.3964/j.issn.1000-0593(2024)02-0548-10
		Accurate and dynamic monitoring of economic crop planting information is an urgent need for agricultural fine management. In order to realize the fine classification of different fruit tree varieties, this paper proposes a fine classification method of citrus fruit trees based on UAV hyperspectral images and the SULOV_XGBoost algorithm in liutang Mocott citrus experimental base in Guilin City. Firstly, multidimensional data sets were constructed by deep mining spectral information from different citrus tree varieties. Then, the SULOV_XGBoost algorithm was used to optimize features, and the XGBoost algorithm was used for the fine classification of citrus fruit varieties. Finally, the accuracy of classification results was compared with that of RF and SVM. The results show that: (1) The proposed SULOV_XGBoost algorithm can effectively classify the different varieties of fruit trees and crops in scenes with small feature gaps, and the overall classification effect is better than the traditional machine learning methods (RF and SVM). (2) The fusion characteristics of the first-order differential inflection point value and the original band value play a great role in improving the precision of fine classification; the combination of different wavelength bands can also significantly improve the fine classification results of citrus fruit trees. (3) SVM has better classification performance and strong anti-interference ability under high ground object discrimination. The research results can provide new ideas and methods for fine classification of different varieties of crops in the same species, and also provide a reference for the precise survey of crop planting information, fine management and layout, adjustment and dynamic monitoring of agricultural industrial structure.
		2024 Vol. 44 (02): 548-557 [Abstract] ( 44 ) RICH HTML PDF (30371 KB) ( 25 )

	558	Automatic Classification of Rock Spectral Features Based on Siamese Network Model
		XIAO Zhi-qiang¹, HE Jin-xin^1*, CHEN De-bo¹, ZHAN Ye², LU Yan-le¹
		DOI: 10.3964/j.issn.1000-0593(2024)02-0558-05
		Rock spectrum is the comprehensive embodiment of rock's physical and chemical properties, composition and structure. Now, it has been widely used in rock classification research. Due to the difficulty of collecting the data on the rock spectrum, it often needs to be collected manually, which not only causes great labor cost but also leads to the limited data on the rock spectrum collected. When the rock spectral classification model is trained with a limited number of samples, the dimensional disaster phenomenon will generally occur. That is, the accuracy of classification will decrease with the rise of the feature dimension, and the rock spectral data coincides with this feature, with a high dimensional number of features. Therefore, to achieve good classification results, a large number of training samples are needed to be used in the training of traditional rock spectral classification models, usually more times than the feature dimension. If the number of samples is small, we must reduce the features to obtain the ideal classification accuracy. Therefore, when the number of samples is small, obtaining a more accurate classification effect on rock spectral data has become a hot research topic. This paper collects the spectral data of typical rocks in Xingcheng, Liaoning Province. Based on the Python programming language, the Siamese Network classification model is constructed with few training samples, and the Triplet Loss is used as the loss function to realize the 3-way-1-shot classification model, and the prediction accuracy of 97.8% is achieved in the verification set. At the same time, four traditional machine learning methods, which include Decision Tree, Random Forest, Support Vector Machine and K-Nearest Neighbor, were used to establish the classification model under the same training samples and compared with them. By drawing the learning curve, it is verified that these four traditional machine learning methods do not have good classification functions in the case of small samples. Since converting the original spectral data into image data will not affect the classification effect of the Siamese Network classification model, the rock spectral classification problem can be transformed into the problem of image classification. Then the image classification methods and means can be used. The experimental results show that the Siamese Network classification model in the case of fewer rock spectral samples can still achieve excellent classification effect, which effectively makes up for the shortcomings of the traditional machine learning model in the case of small samples. Because the data input is paired, it can effectively reduce the overfitting problem caused by too few training samples.
		2024 Vol. 44 (02): 558-562 [Abstract] ( 42 ) RICH HTML PDF (18736 KB) ( 28 )

	563	Spectral Reconstruction Method of Mid-Infrared Surface Characteristics Based on Non-Negative Matrix Factorization
		LI Yin-na^{1, 2}, LI Zheng-qiang^{1, 2*}, ZHENG Yang¹, HOU Wei-zhen^{1, 2}, XU Wen-bin^{1, 3}, MA Yan¹, FAN Cheng¹, GE Bang-yu¹, YAO Qian^{1, 2}, SHI Zheng^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2024)02-0563-08
		In the field of mid-infrared remote sensing, hyperspectral surface reflectance/emissivity has high application value and application demand. However, it is difficult to obtain hyperspectral surface reflectance/emission characteristics in absorption band by satellite remote sensing, and there are still many problems in the method of obtaining full band surface characteristics by spectral reconstruction. In order to solve the problem of mid-infrared full band spectral reconstruction of land surface characteristics, based on the Johns Hopkins University (JHU) surface spectrum library and moderate resolution imaging spectrometer (MODIS) short wave infrared and mid-infrared surface multi spectral satellite products, A method for hyperspectral surface reflectance reconstruction using nonnegative matrix factorization (NMF) is proposed. The spectral resolution of the reconstructed hyperspectral reflectance/emissivity in the mid-infrared range of 2.5~5.0 μm can reach 10 nm. Firstly, four typical types of ground objects (soil, vegetation, artificial materials and rocks) were selected based on the JHU spectral library to establish the sample information of surface features. Then, using the spectral response function of the MODIS sensor, the reflectance results of 2.0~5.0 μm band were resampled to 301 bands with 10 nm spectral interval according to the equivalent calculation formula to obtain the JHU surface reflectance spectrum data set. Four endmember vector spectral curves were extracted by non-negative matrix decomposition of the spectral data set. Combined with the global monthly average surface reflectance/emissivity products of MODIS short wave infrared and mid infrared bands (2.13, 3.75, 3.96 and 4.05 μm), the weight coefficient vector corresponding to each pixel can be calculated, and the spectrum reconstruction of any band can be carried out to obtain the global land 5 km×5 km resolution of the monthly mean surface reflectance reconstruction results. At the same time, in order to comprehensively evaluate the spectral reconstruction method, the sub datasets of MODIS short wave infrared and mid infrared bands (2.13, 3.75, 3.96 and 4.05 μm) were extracted from the spectral data set, and the corresponding weight coefficient vector results were calculated, and the full band reflectance spectral reconstruction in the spectral range of 2.0~5.0 μm was performed. The average absolute error and relative error of the reconstruction results are better than 0.01 and 10%, respectively, which can meet the accuracy requirements of spectral reconstruction under the condition that only MODIS satellite data of 4 bands are available. In order to meet the needs of visualization of reconstruction results, based on WebGIS (Web Geographic information system, WebGIS) technology, using cesium framework and browser/server architecture, a two-dimensional and three-dimensional integrated visualization system was built, which integrated satellite base map, terrain data and spectral reconstruction results, to conduct intuitive multi-factor analysis, It provides support for the demonstration and verification of satellite products.
		2024 Vol. 44 (02): 563-570 [Abstract] ( 53 ) RICH HTML PDF (13185 KB) ( 34 )

	571	Influence of Thermal-Bonding, Concave End-Face and Crystal Rod Diameter on the Er∶YSGG Mid-Infrared Laser Perfomance
		CHENG Mao-jie^{1, 2}, DONG Kun-peng^{1, 2}, HU Lun-zhen^{1, 3}, ZHANG Hui-li^{2, 4}, LUO Jian-qiao^{2, 4}, QUAN Cong^{2, 4}, HAN Zhi-yuan^{1, 2}, SUN Dun-lu^{2, 4*}
		DOI: 10.3964/j.issn.1000-0593(2024)02-0571-09
		This paper demonstrates a systematic comparative study on the mid-infrared laser performance of Er∶YSGG crystals with thermally bonded, concave end-face, and different diameter. After annealing at high temperature, orientation cutting, and precision polishing on the end face, the flatness and surface roughness are less than 0.1λ@633 nm and 0.5 nm. The room temperature optical glueing of YSGG and Er∶YSGG was realized by the precision machining, and then high temperature thermal bonding was carried out. The transmission spectra show that the bonded interface is basically integrated without loss. The thermal focal length shows that the thermal lens effect of crystals at high power pumping condition is improved and compensated efficiently by thermal bonded and concave end-face, which are beneficial to improve the laser performance of crystals. Compared with non-bonded Er∶YSGG, the laser performance under 968 nm LD side-pumping method of bonded and concave end-surfaces Er∶YSGG crystal do not show advantages at low frequencies below 150 Hz, the maximum output power and slope efficiency of the three crystal rods all are about 24 W and 28%, respectively. However, with the increase of repetition frequency, the thermal effect gradually increases, and the laser performance of bonded and concave end-face crystals is improved due to their perfect heat dispassion and concave thermal compensation effect. Under the repetition frequency of 300 Hz, the maximum output power of non-bonded, bonded and concave bonded rods is 15.54, 17.85 and 18.33 W, corresponding to the slope efficiency of 16.6%, 18.3% and 18.4%, respectively. Under the repetition frequency of 600 Hz, these rods' maximum output power and slope efficiency are 9.4, 13.32 and 13.18 W, 6.7%, 8.6%, and 9%, respectively. In addition, the laser properties of Er∶YSGG crystals with different diameters are studied, and the laser properties of these three crystals are similar under the low frequencies below 100 Hz. However, compared with the 3 and 4 mm bonded concave rods, the 2 mm diameter rod possesses a larger specific surface area and better thermal management capability, which is beneficial to improve the laser performance. For example, at 150 Hz, a maximum output of 23.82 W is obtained with a slope efficiency of 27.7% by Er∶YSGG concave bonded crystal rod with 2 mm diameter, which is much higher than 18 W and 23% that is achieved with the 3 and 4 mm crystal rods. Besides, by using a concave bonded rod with 2 mm diameter, the maximum output power of 13.18 W is achieved with a slope efficiency of 9% under the higher repetition frequency of 600 Hz, which is better than that of 9 W and 7% for the concave bonded rod with diameter of 3 and 4 mm. The beam quality factor M²_x/M²_y of Er∶YSGG laser is measured by using 2 mm concave bonded crystal rod at 150 Hz, 200 μs, the values are 6.28/6.30, which indicates that the laser has good beam quality. In conclusion, choosing an appropriate crystal rod diameter and combining bonded with concave surfaces effectively achieve high-performance 2.79 μm lasers.
		2024 Vol. 44 (02): 571-579 [Abstract] ( 52 ) RICH HTML PDF (16319 KB) ( 23 )

	580	A Nondestructive Method for Freshness Detection of Chilled Mutton With Multiple Indicators and Improved Deep Forest Algorithm
		XU Zi-yang^{1, 2}, JIANG Xin-hua^{1, 2*}, BAI Jie^{1, 2}, ZHANG Wen-jing^{1, 2}, LI Jing^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2024)02-0580-08
		Mutton freshness is affected by many factors, and the detection is generally carried out based on sensory properties, physical and chemical products of decomposition, microbial reproduction and other aspects. However, the freshness detection of mutton based on a single indicator has great limitations and low applicability, and it is not easy to evaluate the mutton freshness comprehensively. Moreover, the traditional detection methods are complex and inefficient, which cannot meet the daily actual needs. As a fast, nondestructive and efficient intelligent detection technology, hyperspectral imaging technology can effectively collect the surface, internal composition and physical and chemical changes in the process of mutton putrefaction. This paper proposes an evaluation model for the freshness of chilled mutton based on the improved deep forest algorithm, which adds feature screening to mine the spectral information related to multiple evaluation indicators. It adds layer growth control to prevent the model from over fitting effectively. This paper collects 400~1 000 nm hyperspectral data of mutton samples stored at 4 ℃ for 0~14 days .Total volatile base nitrogen (TVB-N), pH, total aerobic plate count (TAC) and the approximate number of coliforms (ANC) indicator values are measured by laboratory methods. The representative spectra of mutton samples are extracted in the regions of interest. The original spectral data is preprocessed using the smoothing filtering and multivariate scattering correction methods. 18 spectral feature bands are extracted by using the continuous projection method, and the samples of the training set and the testing set are divided at a ratio of 3∶1. Establishment of the freshness classification model is used in the improved deep forest algorithm proposed in this paper. The results show that the overall accuracy of freshness classification is 0.985 7, and use Hamming loss, One-error, Ranking loss and Marco-AUC multi-label metrics to evaluate the performance of the model, which are 0.025 7, 0.014 3, 0.014 2 and 0.998 6 respectively. Theyare better than the traditional multi-label classification algorithm. The research shows that the multi-indicator freshness classification model can be used for rapid, nondestructive testing of mutton freshness. It improves the limitations of single-indicator model classification and provides a research method for multi-indicator nondestructive testing of subsequent hyperspectral imaging technology.
		2024 Vol. 44 (02): 580-587 [Abstract] ( 46 ) RICH HTML PDF (4460 KB) ( 100 )

	588	Rapid Detection of Tocopherol Equivalent Antioxidant Capacity in Tan Mutton Based on the Fusion of Hyperspectral Imaging and Spectral Information
		YUAN Jiang-tao¹, GUO Jia-jun¹, SUN You-rui¹, LIU Gui-shan^1*, LI Yue¹, WU Di¹, JING Yi-xuan²
		DOI: 10.3964/j.issn.1000-0593(2024)02-0588-06
		Trolox-Equivalent Antioxidant Capacity (TEAC) is one of the endogenous antioxidant indexes of muscle, which can be used to determine the antioxidant activity of hydrophilic compounds and free radical scavenging ability. The visible near/infrared (Vis/NIR) hyperspectral imaging technology was used to explore the feasibility of rapid detection of the TEAC in Tan mutton, a quantitative prediction model for TEAC based on spectral information fusion of image texture features (TFS) was built. The samples from different parts were randomly split into calibration set and prediction set according to the ratio of 3∶1. The spectral reflectance images were collected in the range of 400~1 000 nm, and the regions of interest (ROI) were selected to obtain raw spectral data. Four algorithms, including Median Filtering (MF), Baseline, Savitzky-Golay (S-G) and multiplicative scatter correction (MSC), were used to correct the scattering and interference information in the original spectrum, and the Partial Least Squares Regression (PLSR) model was established to correlate spectral data with TEAC values. Representative characteristic spectra of TEAC concentrations were extracted using Interval random frog (IRF), Variable combination population analysis (VCPA), Competitive adaptive reweighted sampling (CARS), and Iteratively variable subset optimization (IVSO) algorithms. The meat's main texture features were extracted sequentially by using the Gray level co-occurrence matrix (GLCM) algorithm. Based on the characteristic spectrum and spectral fusion information, the Back-propagation artificial neural network (BP-ANN) and Least-squares support vector machines (LSSVM) model were established to predict and compare the TEAC content in Tan mutton. The results showed that (1) The PLSR model established by the preprocessed spectra of Baseline was the best with R_c of 0.912 1, RMSEC of 0.963 5, R_p of 0.868 3, RMSEP of 1.277 0; (2) The 71，9，22 and 39 characteristic bands based on the original spectral were extracted by IRF，VCPA，CARS and IVSO methods, respectively, accounting for 56.8%，7.2%，17.6% and 31.2% of the total bands; (3) Compared with model effects of BP-ANN and LSSVM models in feature variables extraction based on multiple algorithms, the optimal prediction model for TEAC content was Baseline-IVSO-LSSVM (R_c=0.913 2, RMSEC=0.962 0, R_p=0.864 6, RMSEP=1.288 3); (4) The fusion model IVSO-TF1-BP-ANN showed better results (R_p=0.891 6) with improving by 0.028 6, compared with model based on the characteristic wavelength.
		2024 Vol. 44 (02): 588-593 [Abstract] ( 44 ) RICH HTML PDF (7713 KB) ( 18 )

	594	The Kinetic Mechanism of Nickel and Lead Adsorption by Converter Steel Slag Powder Was Studied Based on ICP-MS
		XU Xiu-ping^{1, 3}, XU Wei-cheng², YU Xian-kun^{1, 3}, CHEN Yu⁴, YANG Gang⁵, ZHANG Hao^{1, 2, 6*}
		DOI: 10.3964/j.issn.1000-0593(2024)02-0594-07
		With the development of industrialization, heavy metal pollution in water and soil has become increasingly serious. Among them, the heavy metal nickel is a common sensitizing metal, which can cause allergic inflammation in the human body, and even cause cancer; the excessive lead concentration in the blood will harm the human nervous, cardiovascular, and reproductive systems, causing lifelong harm. Therefore, it is of great significance to control the heavy metal pollution of nickel and lead. Steel slag is a by-product produced in the steelmaking process, which has the problems of difficulty in utilization and low added value. At the same time, coupled with the imperfect management system, a large amount of steel slag is piled up in the open air, which seriously impacts land resources, groundwater sources, and air quality. Steel slag powder has the characteristics of a large specific surface area, porosity and high chemical activity. It is widely used and can be used as an adsorbent material. In this paper, the converter steel slag powder is taken as the research object, and the basic properties of the converter steel slag powder are tested by a laser particle size analyzer, inductively coupled plasma mass spectrometer, specific surface area and porosity adsorption analyzer, and X-ray fluorescence spectrometer. The effect of initial concentration, solution pH and adsorption time on the adsorption of Ni²⁺ and Pb²⁺ by the converter steel slag powder, combined with the adsorption kinetics and adsorption isotherm theory to reveal the adsorption mechanism of the converter steel slag powder on Ni²⁺, Pb²⁺, for the treatment of nickel, lead heavy metal pollution and industrial Provide technical support and theoretical basis for wastewater treatment. The results show that when the amount of converter slag powder is greater than 12.5 g·L^-1, the initial concentration of heavy metals is less than 100mg·L^-1, the pH of the solution is greater than 3 and the adsorption time is greater than 120min, the adsorption effect of converter slag powder on Ni²⁺ and Pb²⁺ is good, that is, it reaches 90%. The adsorption of Ni²⁺ and Pb²⁺ by converter slag powder is by the quasi-second-order kinetic model. The adsorption rate is controlled by boundary diffusion and intra-particle diffusion, and the main adsorption process is chemical adsorption. The converter steel slag powder structure has porosity to provide adsorption space for physical adsorption of Ni²⁺ and Pb²⁺. The chemical composition of converter steel slag powder is alkaline to form complex products with Ni²⁺ and Pb²⁺, and CaO and SiO₂ form C—S—H gel during the hydration process. It forms complex adsorption and silicate system encapsulation for Ni²⁺ and Pb²⁺. The adsorption of Ni²⁺ and Pb²⁺ by converter steel slag powder may be multi-layer adsorption. The adsorption process of Ni²⁺ and Pb²⁺ is preferential, and the adsorption is easy to carry out. The theoretical maximum adsorption capacities are 18.785 and 17.002 mg·g^-1, respectively.
		2024 Vol. 44 (02): 594-600 [Abstract] ( 45 ) RICH HTML PDF (2084 KB) ( 97 )

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