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2022 Vol. 42, No. 12
Published: 2022-12-01

 
3653 Application of Raman Spectroscopy in Detection of Pathogenic Microorganisms
LIU Feng-xiang, HE Shuai, ZHANG Li-hao, HUANG Xia, SONG Yi-zhi*
DOI: 10.3964/j.issn.1000-0593(2022)12-3653-06
Pathogenic microorganisms refer to microorganisms that can invade the human body and cause infections. Clinically, diseases caused by pathogenic microorganisms infection are extremely common. The traditional diagnosis of clinical pathogenic bacteria mainly relies on bacterial culture, but this method takes a long time and often takes 2-5 days to get the results, and there are some problems that the culture of bacteria is difficult or even impossible. Doctors who are unable to identify bacterial species and drug sensitivity use broad-spectrum antibiotics based on their experience to accelerate the emergence of bacterial resistance. Therefore, highly sensitive detection and identification of pathogenic microorganisms have become an important research direction of scholars at home and abroad. Raman spectroscopy is a kind of treatment of samples in situ, non-invasive, no mark detection technology, can be in the single cell level and provides different microbial cells biological molecular fingerprint information. Through this information, can determine the kinds of microorganisms, physical characteristics and mutation phenotype, achieve rapid detection of microbial samples. With the rapid development of laser spectroscopy and the continuous increase in clinical demand, sub-techniques with Raman spectroscopy detection technology as the core was born (such as surface-enhanced Raman spectroscopy, Fourier transform Raman spectroscopy, laser resonance Raman spectroscopy, confocal Raman microscopy, coherent anti-Stokes Raman spectroscopy, stimulated Raman spectroscopy and other related technologies), while improving the weak signal strength of the previous Raman spectroscopy technology to achieve High-precision rapid detection and analysis of microorganisms. Relying on its advantages of no restriction on the state of samples and the ability to detect small changes in the composition of substances, the research on Raman spectroscopy in the field of pathogenic microorganisms has been increasing in recent years. In this paper, the research status of microbial detection has carried on the investigation and analysis around the principle of Raman spectroscopy technology for its application in microbiological detection has carried on the detailed elaboration, mainly in pathogenic microorganisms identification with the technology and discusses the research progress in drug susceptibility testing, and with the traditional testing technology and advantages were analyzed. The differences between It provides a new method for rapid detection of pathogenic microorganisms.
2022 Vol. 42 (12): 3653-3658 [Abstract] ( 161 ) RICH HTML PDF (961 KB)  ( 206 )
3659 Research Progress and Design on Reference Materials of Atmospheric Particulates
PAN Han-jiang, GU Tie-xin, LIU Mei, YANG Rong*, ZHAO Kai, GU Xue
DOI: 10.3964/j.issn.1000-0593(2022)12-3659-06
Atmospheric particulate matter has become the primary pollutant of urban air. Due to the difficulty and high technical requirements of accurately determining the chemical composition of atmospheric particulate matter, corresponding reference materials are needed to ensure the accuracy and traceability of the measurement results. This article summarized the research progress of atmospheric particulate reference materials domestic and overseas in terms of source composition, sample collection, preparation technology, target components and analysis technics. The problems with domestic reference materials of atmospheric particulates were analyzed, including a few matrix types, backward sampling and preparation technology, and shortage of samples. Based on the foreign research experience and China’s major needs for environmental monitoring and governance, research designs were made to ensure the representativeness and practicability of reference materials of atmospheric particulates. The innovation is that based on the composition and source analysis results of atmospheric particulate matter, main source substances should be collected in the study area, and the combination of source substances will be prepared according to the target matrix and content requirements, finally a series of target content candidates sample will be obtained.
2022 Vol. 42 (12): 3659-3664 [Abstract] ( 95 ) RICH HTML PDF (1360 KB)  ( 289 )
3665 Research on an Equivalent Evaluation Algorithm for the Oil Spill Volume of Oil-in-Water Emulsion on the Sea Surface
ZHANG Xiao-dan1, KONG De-ming2*, ZHONG Mei-yu1, MA Qin-yong1, KONG Ling-fu1
DOI: 10.3964/j.issn.1000-0593(2022)12-3665-07
The oil spill volume of the oil-in-water emulsion is an important indicator for evaluating and analysing oil spill pollution on the sea surface. Laser-Induced Fluorescence (LIF) is currently one of the most distinguished technologies in remote sensing detection of oil spills on the sea. Currently, there is no effective and complete algorithm for assessing the oil spill volume of oil-in-water emulsion on the sea surface based on LIF detection technology. In view of this, firstly, an equivalent evaluation model of the oil spill volume of oil-in-water emulsion is designed: the dispersed phase oil droplets in the oil-in-water emulsion are assumed to gather into a piece of oil film floating on the sea surface, so the evaluation of the oil spill volume of oil-in-water emulsion is transformed into the estimation of oil film thickness in the equivalent model with the same fluorescence effect; Secondly, based on LIF detection mechanism and fluorescence radiation transmission process, the equation of fluorescence signal received by LIF system is established, furthermore, the calculation formula of oil film thickness is obtained by inversion; Finally, two representative heavy and light oils are selected, the correctness of the equivalent model is verified by simulation experiments, simultaneously, the fluorescence signal intensity of the detected oil-in-water emulsion was calculated by the equivalent algorithm to obtain the oil film thickness and the error analysis was carried out, and then the applicable conditions of the equivalent evaluation algorithm are obtained: that is, when the actual oil spill thickness of oil-in-water emulsion is less than or equal to the minimum oil spill thickness when its fluorescence is stable, the equivalent evaluation algorithm in this paper has high accuracy, and its average error is less than 8%; Nevertheless when the actual oil spill thickness is greater than the minimum oil spill thickness when the fluorescence is stable, the equivalent evaluation error increases, and the average value exceeds 25%. Meanwhile, when using the algorithm in this paper to evaluate the oil spill volume of heavy and light oil-in-water emulsions, better estimation results can be acquired when the actual oil spill thickness is not greater than 2 and 16 μm, respectively. Therefore, the research content of this paper is a feasible method to evaluate the oil spill volume of oil-in-water emulsion on the sea surface based on LIF technology.
2022 Vol. 42 (12): 3665-3671 [Abstract] ( 97 ) RICH HTML PDF (2896 KB)  ( 125 )
3672 Preparation and Optical Characterization of Copper Indium Sulfide Nanocrystal/PMMA Composite Film
ZHOU Qing-chao
DOI: 10.3964/j.issn.1000-0593(2022)12-3672-06
Copper indium sulfide (CuInS2) nanocrystalshave the advantages of wide emission spectra, tunable emission wavelength, high quantum yield, low synthesis cost, and easy integration with encapsulation materials. It has broad application prospects in white LEDs with remote configuration. The remote white LED structure is a new type of encapsulation structure proposed for the problem of LED heat dissipation. The composite fluorescent coating (composite film) and the blue chip are encapsulated by a distance in this structure. This structure greatly reduces the requirements for the thermal stability of nanocrystals in the composite film. In this paper, we prepared CuInS2 nanocrystal fluorescent materials with different emission wavelengths, and then the nanocrystals were encapsulated into the PMMA matrix to fabricate a series of CuInS2 nanocrystal/PMMA composite films.Through the methods of fluorescence spectroscopy and ultraviolet-visible absorption spectroscopy, we conducted a detailed study on the red shift of emission wavelength and inconsistent transmittance of nanocrystal/PMMA composite films.
2022 Vol. 42 (12): 3672-3677 [Abstract] ( 112 ) RICH HTML PDF (3367 KB)  ( 36 )
3678 Research of Carbon Monoxide Concentration Measurement in Combustion Field by Off-Axis Integrated Cavity Output Spectroscopy
LOU Deng-cheng, RAO Wei*, SONG Jun-ling, WANG Kai, JIANG Ya-jing, GUO Jian-yu
DOI: 10.3964/j.issn.1000-0593(2022)12-3678-07
Carbon monoxide (CO) is one of the important products of insufficient combustion of hydrocarbon fuels and is often used as a marker of reaction combustion efficiency. The accurate measurement of CO concentration in the combustion field is of great significance to the engine to improve combustion efficiency and reduce pollutant emissions. Off-axis Integrating Cavity Output Spectroscopy (OA-ICOS) is a technology to analyze and measure a material by using the specific absorption of the substance to the laser spectrum. It has the advantages of non-contact, stability and high sensitivity. Aiming at the characteristics of low CO concentration and strong background signal interference in the combustion field, an OA-ICOS system was built with a distributed feedback (DFB) laser to measure the CO concentration in high-temperature combustion field by direct absorption spectroscopy (DAS) method. The first broadband R(10) absorption line, which is more prominent at room temperature and not interfered with by other combustion products at high temperature, was selected near the center wavelength of the DFB laser by absorbance simulation. The effective optical length of the OA-ICOS system was calibrated by comparing the absorbance with the fixed optical path cell. The best wavelength scanning frequency was obtained by comparing the signal-to-noise ratio of the absorption line at different scanning frequencies and the standard deviation of the linear fitting residuals; The system error was analyzed by measuring the absorption signal of CO mixed gas of different concentrations. The production of CO on the CH4/Air premixed flat flame furnace under different combustion conditions was evaluated. The influence of the temperature distribution uncertainty on the CO measurement results was described by the temperature distribution in the measurement area of the combustion field. A minimum concentration detection limit of 5.83×10-6 was achieved under the time resolution of 10 ms, the system measurement error was less than 4.5%, and the uncertainty of CO concentration measurement caused by the temperature uncertainty of the combustion field was 5.6% when the equivalence ratio is 1.0. The variation ranges of average temperature and CO concentration are 1 275~1 368 K and 0.041%~1.57% when the equivalence ratio changes from 0.8 to 1.2. The experimental results show that the OA-ICOS has the advantages of a high signal-to-noise ratio and high detection sensitivity to measure the gas parameters in the combustion field and can develop an accurate measurement of the concentration of trace gas components.
2022 Vol. 42 (12): 3678-3684 [Abstract] ( 87 ) RICH HTML PDF (3850 KB)  ( 40 )
3685 Non-Destructive Detection of Egg Fertilization Status Based on Hyperspectral Diffuse Reflectance
CUI De-jian1, LIU Yang-yang1, XIA Yuan-tian1, JIA Wei-e1, LIAN Zheng-xing2, LI Lin1*
DOI: 10.3964/j.issn.1000-0593(2022)12-3685-07
During the incubation period of the breeding eggs, a lot of workforce and material resources are consumed, and the eggs during the incubation period cannot be guaranteed to be healthy fertilized eggs. It is necessary to quickly and accurately select the infertile eggs and dead sperm eggs in the early stage of the breeding eggs to reduce production costs. We take Bailaihang eggs as the research object and use a hyperspectral sorter to collect 119 fertilized, unfertilized, and dead eggs in batches with hyperspectral data in the range of 382~1 026 nm. The original spectrum is corrected by the black and white correction method to obtain the diffuse reflectance of the egg.After experimental comparison and actual production needs, 3d and 5d spectral data are selected as modeling data.We also propose a method to convert spectral data into image data, which achieves the effect of visualizing spectral vector data under the premise of maximizing the guarantee of the original spectral data and can be effectively combined with deep learning image recognition algorithms.We use SPA and CARS to filter the spectral bands and establish a discriminant model based on the full band, the characteristic wavelengths filtered by CARS, the characteristic wavelengths filtered by SPA and SVM, the Random Forest algorithm and AlexNet, MobileNet network. The highest accuracy rate of AlexNet-5d Full Wave Bands is 93.22%. By comparing the experimental results of the data after the screening of different characteristic wavelength algorithms, it is found that the modeling effect of the characteristic wavelengths filtered by the SPA algorithm is better than that of CARS. The accuracy of the SVM-SPA3d model is 91.52%. The accuracy of the RandomForest-SPA3d model is 89.83%. The accuracy of the AlexNet-SPA3d model is 89.83%. The results show that the characteristic wavelengths screened by SPA can save more effective information about the difference inbreeding egg information. The research results in this paper show that the diffuse reflectance spectrum values of batches of hatching eggs are collected by a hyperspectral sorter first, and then the original spectral diffuse reflectance data is converted into image data. Combining image data with deep learning image recognition algorithms is feasible to accurately and non-destructively identify the fertilization state of eggs. This study provides technical support for subsequent related automated batch testing.
2022 Vol. 42 (12): 3685-3691 [Abstract] ( 100 ) RICH HTML PDF (4761 KB)  ( 75 )
3692 Research on Gas Pressure Measurement Method Based on Absorption Spectroscopy and Laser Interference Technology
ZHANG Bo-han, YANG Jun, HUANG Qian-kun, XIE Xing-juan
DOI: 10.3964/j.issn.1000-0593(2022)12-3692-05
Optical non-contact measurement of gas pressure is currently one of the important application fields of laser technology,and the temperature coupling problem in the process of gas pressure measurement is a difficult point in the current research work.Therefore, a combined measurement method of spectral and laser interference technology is proposed, which realizes the calculation of gas pressure value and temperature value by integrating absorbance and refractive index. The principle of direct absorption measurement of tunable semiconductor laser spectroscopy (TDLAS) and the principle of laser interferometry based on the refractive index are analyzed, and the pressure measurement model based on absorption spectrum and the laser interferometric pressure measurement model based on the refractive index are established. The method of fitting the intensity function of the absorption spectrum by the cubic polynomial equation establishes a mathematical model for the solution of the gas pressure value and temperature value based on the integral absorbance and refractive index. In the experiment, a gas pressure detection system based on TDLAS technology and laser interference technology was built. A tunable semiconductor laser with a center wavelength of 2 004 nm and a laser interferometer with a fixed wavelength of 632.8 nm wasused. The length of the gas cell was 24.8 cm. CO2 was selected forthe research. Use the measurement results of the high-precision pressure controller and temperature sensor as the pressure and temperature reference values, and use the vacuum signal as the background signal to measure and calculate the integrated absorbance and refractive index values after the gas pressure changes in a room temperature environment. Finally, the gas pressure and temperature values are obtained by the solution. The realization results show that the maximum relative error of the pressure measurement result is 3.61%, the minimum relative error is 0.5%, and the average relative error is 1.99%. Under the premise of temperature in Kelvin, the maximum absolute error of the temperature solution is 7.66 K, the absolute minimum error is 0.78 K, and the average absolute error of the measurement is 3.29 K. The measurement results are in good agreement with the reference results. This work can provide a reference for future analysis and research on the influence of optical methods on gas pressure and temperature.
2022 Vol. 42 (12): 3692-3696 [Abstract] ( 129 ) RICH HTML PDF (2668 KB)  ( 61 )
3697 Study on the Common Effect of Heat Treatment, Dyeing or Irradiation Treatment on UV-Vis Diffuse Reflectance Spectra of Pearls
YAN Jun1, FANG Shi-bin1, YAN Xue-jun1, SHENG Jia-wei2, XU Jiang1, XU Chong3, ZHANG Jian2*
DOI: 10.3964/j.issn.1000-0593(2022)12-3697-06
The effects of heat treatment, dyeing treatment with organic or inorganic dyes and Co60-γ ray irradiation treatment on the reflection spectra of freshwater or seawater cultured pearls and shells were comparatively investigated mainly by UV-Vis diffuse reflection spectrometer, respectively. The results show that: (1) these three different kinds of treatment have a clear common effect on the absorption peak of 280 nm in the reflection spectra of the nacre of pearls and shells. Furthermore, the absorption located at 280 nm is attributed to the organic matrix, which is one of the important components of nacre from pearls, and it is not directly responsible for coloring of colored pearls. (2) It is clearly seen that the intensity of the above absorption peak gradually reduces until it disappear with the increase of intensity of different treatment process. Furthermore, the intensity of the main wavelength of the reflection peak weakened gradually in the ultraviolet region of diffuse reflection spectra, and red-shifted toward the visible light. To sum up, this present study may provide the basis and theoretical support for the investigation of the coloring mechanism and identification of pearls and the corresponding treated ones.
2022 Vol. 42 (12): 3697-3702 [Abstract] ( 101 ) RICH HTML PDF (6233 KB)  ( 71 )
3703 The Types of UV-Vis Diffuse Reflectance Spectra of Common Gray Pearls and Their Coloring Mechanism
FANG Shi-bin1, JIANG Yang-ming1, YAN Jun1, 2, YAN Xue-jun1, ZHOU Yang3, ZHANG Jian2*
DOI: 10.3964/j.issn.1000-0593(2022)12-3703-06
The spectral types of usual gray pearls were classified based on UV-Vis diffuse reflection spectra. The coloring mechanism of gray pearl was further investigated. The results show that :(1) based on the presence or absence of absorption peak nearby 280 nm in the reflectance spectra of gray pearls, which are firstly divided into typeⅠ (obvious absorption) andⅡ (no absorption or weak absorption). Furthermore, according to the shape of spectra and the position of the main wavelength of the reflection peak, the type Ⅰ pearls are further divided into three subtypes: Ⅰn, Ⅰp andⅠf. Among them, the color of the nucleus of typeⅠp pearl is white, and a brown or blackish-brown transition layer exists between the nucleus and nacre, which may be the direct cause of the gray color of the pearl. Meanwhile, the type ofⅠp pearls are generally considered to be untreated in the field of gemstone identification. (2) because of the change in the color of nacre before and after irradiation and the variation characteristics of the UV-Vis reflection spectrum in this work and the previous work on irradiated pearls, it is preliminarily concluded that irradiation is still one of the main reasons for the coloring mechanism of gray pearls. Moreover, the pearl can be identified as having been treated based on the disappearance of the absorption peak or the presence of only one absorption shoulder near 280 nm in the corresponding reflectance spectrum. According to the typeⅡ gray pearls section structure, the nucleated and non-nucleated pearls coexist in the circulation field. A more accurate method used to identify the irradiated pearl should be developed.
2022 Vol. 42 (12): 3703-3708 [Abstract] ( 115 ) RICH HTML PDF (5198 KB)  ( 70 )
3709 Effect of Au Polymer Adsorption Sites on Surface Enhanced Raman Spectroscopy of Amitrole Molecule
GU Yi-fan1, LIAN Shuai1, GAO Xun1*, SONG Shao-zhong2*, LIN Jing-quan1
DOI: 10.3964/j.issn.1000-0593(2022)12-3709-05
Amitrole is a chemical herbicide in the form of white crystalline powder.It is extremely destructive to the environment, and heavy use can contaminate food and cause cancer. There are relatively few researches on Raman enhancement mechanism of amitrole molecules using density functional theory. Therefore, a model describing the adsorption pattern between the molecule and the substrate was established to predict the surface-enhanced Raman spectrum of amitrole molecules. First, Multiwfn and VMD software were used to calculate the surface electrostatic potential distribution of amitrole molecules and search for the best coordination position between amitrole molecules and Au atoms. It can be obtained that N1, N4 and N6 is the best place for amitrole molecules to coordinate with Au. Based on density functional theory, software GaussView5.0 and Gaussian09, was used to optimize the geometric configuration of amitrole molecules by B3LYP/6-31++G(d, p) basis set. And 6-31++G(d, p)(C, H, N)/Lanladz(Au) basis set was used to calculate the conventional Raman scattering spectra of amitrole molecules and the surface adsorption of amitrole molecules and Au4 clusters and Au6 clusters enhanced Raman scattering spectra. Finally, feature peak identification and comparison are carried out. The results show that the position of the characteristic peaks does not change greatly, but the intensity of some characteristic peaks increases obviously. In the complex formed by coordination between Au and N1, the Raman activity of amitrole molecules was obvious at 1 064, 1 200, 1 392 and 1 592 cm-1. In the complex formed by coordination between Au and N4, the Raman activity of amitrole molecules was obvious at 1 304 cm-1. In the complex formed by coordination between Au and N6, the Raman activity of amitrole molecules was obvious at 1 064, 1 520 and 1 592 cm-1. Through comparison, the compound formed by coordination between Au and N1, N6 has a better enhancement effect, and the maximum enhancement of characteristic peak reached 41, 81, 55 and 96 times respectively. The results show that the complexes formed by coordinating Au with N1 and N6 have a better reinforcement effect. The maximum enhancement factor of Au4 polymer and Au6 polymer with N1 adsorption reached 41 and 81 times respectively; The maximum enhancement factor of Au4 polymer and Au6 polymer with N6 adsorption reached 55 and 96 times respectively. Amitrole molecules and Au atoms have an obvious Raman enhancement effect. When the number of Au polymers increases from four to six, the Raman spectrum enhancement effect is obvious. This work laid a foundation for studying the SERS enhanced mechanism of amitrole molecules.
2022 Vol. 42 (12): 3709-3713 [Abstract] ( 81 ) RICH HTML PDF (1833 KB)  ( 31 )
3714 Rapid Identification of Fish Products Using Handheld Laser Induced Breakdown Spectroscopy Combined With Random Forest
YAN Wen-hao1, YANG Xiao-ying1, GENG Xin1, WANG Le-shan1, LÜ Liang1, TIAN Ye1*, LI Ying1, LIN Hong2
DOI: 10.3964/j.issn.1000-0593(2022)12-3714-05
China is a big country of aquatic products production and consumption. Due to the great quality and price gap between the fish products from closely related species, the phenomena of adulteration and mislabeling of fish products have occurred frequently, which greatly encroached on the consumers’ legitimate rights. Therefore, it is important to realize a rapid detection of the variety and quality of fish products. Laser-induced breakdown spectroscopy (LIBS) utilizes a pulsed laser to ablate the sample surface and generate a laser-induced plasma. Then the emission spectrum from the plasma is used for a qualitative or quantitative analysis of the elemental components of the sample. LIBS has shown great potential to be used in the food fast detection field with no or minimal sample preparation, multi-elemental analysis, and rapid detection capabilities. This paper applied LIBS combined with the random forest (RF) method to rapidly identify different fish products. Firstly, six fish samples were prepared into pellets, and the LIBS spectra were acquired using a handheld LIBS device. Clear spectral lines of C, Mg, CN, Ca, Na, H, K and O can be observed in the hand held-LIBS spectrum. After normalization of the raw spectral data, the principal component analysis (PCA) was used for clustering, and it was shown that the salt water fishes and freshwater fishes could be distinguished. In contrast, the different types inside the saltwater fishes or freshwater fishes can hardly be distinguished, indicating a limited capability of PCA method for the classification. Then, a nonlinear RF method was used to build the classification model. After optimizing the model parameters, including the decision tree number and the maximum depth, the RF model got an overall classification accuracy of 90%. In order to further improve the classification accuracy and efficiency, a feature selection method was performed by utilizing the variable importance of the RF model. It was shown that after feature selection, the classification accuracy was improved to 94.44%, and the number of input variables of the RF model was reduced from 23 431 to 597. Thus the computing time of the RF model was clearly reduced. The obtained results suggested that the RF model combined with variable importance selection can successfully distinguish the weak LIBS signals which have high impacts on the classification and eliminate the interferences from the spectral noise, background and other redundant variables, and therefore have a good classification accuracy and efficiency. This work proves the feasibility of handheld LIBS combined with machine learning for the application of rapid fish product identification in the market.
2022 Vol. 42 (12): 3714-3718 [Abstract] ( 80 ) RICH HTML PDF (2606 KB)  ( 50 )
3719 Infrared Spectroscopy Study on Temperature Characteristics of Several Common Antibiotics and Therapeutic COVID-19 Drugs
WANG Fang1, 3, ZHU Nan2, CHEN Jing-yi1, ZAN Jia-nan3, XIAO Zi-kang1, LIU Chang1, LIU Yun-fei3*
DOI: 10.3964/j.issn.1000-0593(2022)12-3719-11
The far infrared (1~10 THz) and mid-infrared (400~4 000 cm-1) spectra of six common antibiotics (Ofloxacin capsules, Ofloxacin tablets, Norfloxacin capsules, Azithromycin tablets, Roxithromycin tablets and Levofloxacin hydrochloride tablets), three antiviral drugs for COVID-19 (Ribavirin tablets, Abidol hydrochloride tablets and Chloroquine phosphate tablets) and an expectorant drug (Ambroxol hydrochloride tablets) within shelf-life were studied. The effects of vehicles and another high temperature environment (65 ℃) on the structure and crystal form of drugs were simulated and fed back to the changes in infrared spectra. After two months of continuous experiments, it was found that the structure and crystal form of other drugs had hardly changed except in ambroxol hydrochloride tablets. When capsule drugs were placed in high-temperature environment for a long time, the epidermis would become brittle and easy to rupture, but the efficacy of internal drugs had hardly changed. Taking fluoroquinolone antibiotics (Ofloxacin and Norfloxacin) as examples, combined with density functional theory (DFT) and the potential energy distribution (PED) method, the theoretical infrared spectra of the two antibiotics monomers, polymers and crystals were calculated by Crystal 14 and Gaussian 16 software with B3LYP/6-311++G(d,p) basis set. The vibrational modes and their contribution rates corresponding to all characteristic peaks were obtained, and the experimental spectrum was accurately identified. It was also found that from monomer to polymer and then to crystal, the stacking force (π—π interaction) between lattices accounted for the largest proportion of inter-molecular interaction, more than 90%. Therefore, the theoretical calculation was more consistent with the experimental results only when the crystal with periodic boundary conditions was taken as the initial configuration. The vibrational modes in the far infrared band mainly came from the collective vibration of molecules (vibration accounts for more than 99%, rotation and translation account for less than 1%), and the out-of-plane bending caused by inter-molecular hydrogen bond and Van der Waals force contributes the most, more than 90%. In the mid-infrared band, there were also a certain proportion of inter-molecular interactions. For example, the peaks of norfloxacin at 1 440 cm-1 and ofloxacin at 1 524 cm-1 can only be reproduced in the theoretical spectrum with the crystal as the configuration, respectively, from the collective vibration and the stretching of O—H…O bonds.
2022 Vol. 42 (12): 3719-3729 [Abstract] ( 115 ) RICH HTML PDF (10936 KB)  ( 37 )
3730 Baseline Correction Method Based on Block Sparse Signal Recovery
CHEN Su-yi, LI Hao-ran, DAI Ji-sheng*
DOI: 10.3964/j.issn.1000-0593(2022)12-3730-06
Baseline deviation often occurs with the spectrum data acquisition, making the subsequent identification and analysis results deviate from the true values. Therefore, it is necessary to utilize the baseline correction technology to obtain more accurate spectrum data before the spectrum data analysis. The sparse Bayesian learning (SBL)-based baseline correction method can provide the optimal baseline correction results within the Bayesian framework, and it does not need to select parameters manually. However, the SBL framework is too simple to apply to complex sparsity structures. In practical implementations, if the peak of the pure spectrum is wide, the corresponding sparse representation vector would exhibit a block-sparsity property. The performance of the SBL method will be further improved if the additional block-sparse structure can be exploited appropriately. To this end, we introduce a coupling pattern model into the SBL framework to adaptively learn the block-sparse structure. Due to the inherent learning capability of the SBL framework, the proposed method can significantly improve the baseline correction performance. We conducted several simulations to evaluate the performance improvement, where the proposed method is compared to SSFBCSP and SBL-BC with different noise variances. The simulation results verify the superiority of the proposed method for wide peak recovery. Specifically, it has good stability when the noise level is high, but the performance of other methods degrades substantially. Monte Carlo simulation results further demonstrate that our method can significantly improve the pure spectrum fitting’s normalized mean square error (NMSE) performance. Finally, one real chromatogram dataset and three Raman datasets are used to validate the performance of the proposed method. The experimental results indicate that our method can produce smoother pure spectrum fitting and better denoising effects than others.
2022 Vol. 42 (12): 3730-3735 [Abstract] ( 118 ) RICH HTML PDF (3644 KB)  ( 40 )
3736 Study on the Material and Mineral Source Characteristics of Jade Excavated From Longwangshan Tomb in Jingmen
HU Qiao1, YANG Ming-xing1, 2*, LIU Yue1, LIU Ji-fu1, DAI Lu-lu1
DOI: 10.3964/j.issn.1000-0593(2022)12-3736-09
Longwangshan Tomb, located in Jingmen city, Hubei Province, belongs to a key transitional period between the Daxi Culture and the Qujialing Culture, dating back about 5, 000 years. The tomb unearths 73 pieces of jade, whose quality is generally good. In the past a few years, few jade articles have been unearthed in the middle reaches of the Yangtze River. At the same time, the changing period of time is also a period of social change. The study of jade articles unearthed from the Longwangshan Tomb is of great significance in terms of geographical location and period. Relative density detection, infrared spectrometer and laser ablation inductively coupled plasma mass spectrometer are used to study the spectral and chemical composition characteristics of unearthed jade articles, identify their material, and explore the level of selecting jade material and mineral source. The infrared spectrometer results show that the infrared absorption spectrum of jade excavated from Longwangshan Tomb can be divided into two categories: tremolite and agate. The infrared absorption peaks of tremolite jades are at 1 207, 1 123, 1 028, 928, 775, 700, 602, 488 and 425 cm-1. The infrared absorption peaks of agate jades are at 1 158,814,790,702,572,521 and 405 cm-1. There are 71 pieces of tremolite jade, and the quality is very good, indicating that the level of jade selected by the ancestors of the Longwangshan Tomb is very high. Comparing the level of selecting jade in the tombs of Longwangshan with that of other archaeological cultures of the same period, the level of selecting jade in the tombs of Longwangshan is far superior to that of the same period. Comparing the level of selecting jade in the tombs of Longwangshan with that in the Neolithic age of Hubei province, the level of selecting jade in the tombs of Longwangshan is far higher than the average level of Hubei province. The laser ablation inductively coupled plasma mass spectrometer showed that trace elements of jades made of tremolite mainly consist of Al, Na, Mn, K, P, etc. and are enriched in W, U, P and Sb elements, while Th and Tielements are depleted. The rare earth distribution patterns of jades are diverse, including horizontal seagull shape, left inclined type and right inclined type. Ce anomalies are generally not obvious, while Eu anomalies are mainly positive and negative. With the help of SPASS software, the rare earth elements and trace elements content of the jade excavated from Longwangshan Tomb were analyzed, and the jade was inferred to be from a deposit with the similar metallogenic environment to Xinjiang. However, the possibility of multiple sources of jade was not ruled out because of the diversity of its geochemical characteristics.
2022 Vol. 42 (12): 3736-3744 [Abstract] ( 114 ) RICH HTML PDF (6104 KB)  ( 84 )
3745 Analysis of Spectral Characteristic Loss Law of Architectural Reflective Thermal Insulation Coatings Based on Hyperspectral Technology
LI Xiao-fang1*, WANG Yan-cang2, WANG Li-mei1, LI Xiao-peng1, ZHANG Guo-dong1
DOI: 10.3964/j.issn.1000-0593(2022)12-3745-06
The reflection and thermal insulation performance of building reflective thermal insulation coatings will be impaired due to the influence of solar radiation, meteorological conditions and other uncontrollable external factors. However, the change in the performance of building reflective thermal insulation coatings in the time dimension is the key basic data to evaluate the energy-saving effect of buildings in a specific period, so it is of great practical and theoretical significance to clarify the impairment law of the performance of building reflective thermal insulation coatings in the time dimension. Architectural reflective thermal insulation coatings’ reflection and absorption characteristics are the intuitive embodiment of their properties. The change characteristics of coating properties in time scale can be correctly revealed by using hyperspectral technology to analyze the reflection and absorption characteristics of coatings quantitatively. In order to study and analyze the loss law of the performance of architectural reflective thermal insulation coatings on the time scale, hyperspectral technology is used as the main technical means in this study. Through the combination of indoor paint spectral determination experiment and paint sample external experiment to collect paint spectral data in different periods, and combined with spectral processing methods such as absorption peak depth and spectral analysis, the variation characteristics of spectral reflection and absorption characteristics of coatings in time dimension were quantitatively analyzed. In order to study and analyze the loss law of spectral reflectance of coatings under the influence of the external environment, the conclusions are as follows: (1) in the range of 350~2 250 nm, the spectral reflectivity of architectural reflective thermal insulation coatings decreases with the increase of time. The decreasing range of spectral reflectance increased from January to May but decreased from May to October, and the decreasing range of spectral reflectance in the visible region was significantly higher than that in the near-infrared region. (2) the absorption peak depth of building reflective thermal insulation coating decreases with the increase of time, and the decreasing range is within [0, 0.163]. (3) the coating thickness has an important influence on the coating spectral reflectivity (coating performance) and its variation on the time scale, and the effect has strong stability, and the coating thickness has a strong influence on the weakening range of the coating spectral reflectivity. The consistency of the spectral reflectivity of architectural reflective thermal insulation coatings with single thickness changes with time and weakens with the increase.
2022 Vol. 42 (12): 3745-3750 [Abstract] ( 78 ) RICH HTML PDF (3307 KB)  ( 39 )
3751 Synthesis and Properties of Novel Benzidine-Based Narrow Band Gap Conjugated Polymer From Simple Monomers
Salima Rahmat1, 2, LI Jia-jia1, Arzugul Muslim1, 2*, Kalbinur Matsawut1
DOI: 10.3964/j.issn.1000-0593(2022)12-3751-06
With the increasing depletion of fossil fuels, the demand for energy in human society is increasing. In order to balance the energy application demand and improve energy efficiency, developing high-efficiency energy conversion materials and electrochemical energy storage materials has become an important research topic. Conductive polymer-based electrode materials faces the challenges of low energy and power density and poor cycle performance in corresponding energy storage devices. Structural modification is needed to improve their conductivity and interface properties. Since the skeleton structure of conjugated chains determines the electronic structure, optical and electrochemical properties of conjugated polymers, the structural modification of conductive conjugated polymers to improve their charge transport properties and carrier mobility, and then the design and synthesis of new high mobility conductive polymer based conjugated polymers is the key to improve the characteristics of their corresponding devices. Most of the reported studies use complex structural designs to improve mobility. This paper designed and synthesised a new narrow-band gap polybenzidine based conjugated polymer with simple structure and helpful to improve charge transfer. Spectroscopic and electrochemical methods characterized the structure and properties of the materials. The structures of the monomers and polymers were characterized by 1H NMR, FTIR and X-ray powder diffraction. Their optical and electrochemical properties were tested by UV-Vis spectrum, UV-Vis diffuse reflection, cyclic voltammetry, chronopotentiometry and electrochemical impedance spectrum. The results show that the conjugated polymer with the expected structure is successfully prepared, and the obtained polymer has good crystallinity. The optical band gap Eoptg is 1.85 eV, and the HOMO and LUMO energy levels are -5.44 and -3.59 eV, respectively. The former is higher than the values published in the literature, while the latter is lower than most literature values, indicating the polymer presents the structural characteristics of promoting p-type and n-type doping simultaneously, and has the performance advantage of enhancing the charge holding capacity of the material. The energy storage properties of polymers are affected by chemical structure, crystal structure and micromorphology. The microstructure characteristics of polybenzidine-based conjugated polymer help to improve their electronic conductivity, but its morphological characteristics of layered, dense blocks limit their ionic conductivity. The electrochemical performance test results show that the polymer has certain electrochemical activity, and small charge transfer impedance and meets the conditions for smooth ion diffusion. The discharge-specific capacitance at 0.05 A·g-1 is 256.6 F·g-1. The results show that the prepared polybenzidine-based narrow band gap conjugated polymers have broad application prospects in photoelectric conversion, energy storage and micro-electronic devices.
2022 Vol. 42 (12): 3751-3756 [Abstract] ( 78 ) RICH HTML PDF (3590 KB)  ( 34 )
3757 Redox-Controlled Turn-on Fluorescence Sensor for H2O2 and Glucose Using DNA-Template Gold Nanoclusters
OU Li-juan1*, LI Jing1, ZHANG Chao-qun1, LUO Jian-xin1, WEI Ji1, WANG Hai-bo2*, ZHANG Chun-yan1
DOI: 10.3964/j.issn.1000-0593(2022)12-3757-05
A novel turn-on sensitive fluorescent assay was proposed for H2O2 and glucose based on H2O2 oxidation of thiols to disulfides inhibiting the quenching of AuNCs with highly fluorescent emission. As a fluorescence probe, gold nanoclusters (AuNCs) have exhibited outstanding properties, such as superior fluorescence properties, excellent stability and facile synthesis. Cysteine with free —SH group could interact with AuNCs through Au-S bonds, leading to the fluorescence quenching of AuNCs. After adding H2O2, cysteine was oxidized to cystine with disulfide bonds. The thiols’ effect between cysteine and AuNCs was prevented, and obvious fluorescence emissions of AuNCs at 471 nm could be observed. Moreover, it was known that GOx could specifically catalyze glucose to generate H2O2 in the presence of oxygen. Therefore, fluorescent glucose detection could be achieved through the oxidase-catalyzed producing H2O2. Utilizing the variation of fluorescence intensity F/F0 as abscissa, H2O2 or glucose concentration as ordinate, a sensitive, selective, simple and fast analysis method for H2O2 and glucose was constructed. A linear relationship was observed from 10 to 100 μmol·L-1 for H2O2, 10 to 200 μmol·L-1 for glucose, with the detection limit of 2.8 and 3.1 μmol·L-1, respectively. Four other carbohydrates and five metal ions were selected as the interferent. All of them could not inhibit the Au-S bonding reaction triggered quenching effect, which revealed the high selectivity of the sensor towards glucose. In addition, the strategy was successfully applied for the detection of glucose in FBS samples with satisfactory recoveries from 94.5%~112.7%. Moreover, the present sensing system could be easily broadened to detect multi-analytes (cholesterol, horseradish peroxidase) based on oxidase-catalyzed producing H2O2. Therefore, the method may offer a new clinical diagnosis and food analysis platform.
2022 Vol. 42 (12): 3757-3761 [Abstract] ( 121 ) RICH HTML PDF (2526 KB)  ( 36 )
3762 Quantitative Analysis and Source of Trans-Boundary Gas Pollution in Industrial Park
CHENG Xiao-xiao1, 2, LIU Jian-guo1, XU Liang1*, XU Han-yang1, JIN Ling1, SHEN Xian-chun1, SUN Yong-feng1
DOI: 10.3964/j.issn.1000-0593(2022)12-3762-08
The concentration of pollution gas at the boundary of industrial parks is not only affected by the discharge of unorganized pollution sources in industrial parks but also by the diffusion of vehicle exhaust gas on roads in industrial parks. The ag-FTIR-DA3000 open-FTIR system was used to measure the polluted gas at the plant boundary in real-time and determine the measured concentration of the polluted gas at the plant boundary. At the same time, aiming at the problem that the diffusion of motor vehicle exhaust affects the concentration of polluting gas at the factory boundary, the concentration of motor vehicle exhaust pollution source with different emission standards is determined by ag-FTIR-DX4000 portable Fourier to transform infrared(FTIR) measurement system. A mathematical model of Gaussian diffusion was established based on the results of portable FTIR measurement, wind speed and direction, atmospheric stability, traffic flow and other variable factors. Combined with the open-FTIR measurement method, the integral calculation of the Open-FTIR measurement path was carried out, and the point-line source diffusion model was constructed to establish the smoke cluster line-source diffusion table of various emission standards. The concentration measured by Open-FTIR was combined with the concentration simulated by the point-line diffusion model to analyze the concentration source at the industrial park’s boundary. The comprehensive analysis results show that other polluting gases at the factory boundary mainly include carbon monoxide, methane, ethylene, acetaldehyde, propylene, methanol, propyl aldehyde, isobutene, formaldehyde and sulfur dioxide. The concentrations of carbon monoxide, methane and ethylene at the boundary are greatly affected by motor vehicle exhaust, and the concentrations of polluting gas at the boundary are greatly affected by motor vehicle exhaust diffusion at the peak time in the morning and evening. Off-peak, the concentration rises sharply at 1:00 and 4:00-6:00, and the high concentration point appears, which is not in line with the motor vehicle exhaust model emission rules, mainly affected by the park emissions. The maximum and average concentrations were 5.50 and 4.00 mg·m-3, respectively. 1.85 and 1.60 mg·m-3; 78.00 and 40.00 μg·m-3.The diffusion concentration distribution results of tail gas are consistent. The highest and average values of other components were 1.65 and 1.40 mg·m-3 respectively. 2.60 and 1.27 mg·m-3; 43.53 and 11.40 mg·m-3; 310.23 and 839.05 μg·m-3; 76.32 and 38.96 μg·m-3; 47.70 and 25.20 μg·m-3; 1.33 and 1.16 mg·m-3. This study not only realized the real-time online measurement of multi-component polluted gas at the boundary of the industrial park but also built a point-line source diffusion model, combined with the field environment and portable FTIR measurement results to achieve the mixed determination of the concentration of polluted gas at the boundary of the factory. It provides an analytical thought for judging the future source of polluting gas at the boundary of the industrial park.
2022 Vol. 42 (12): 3762-3769 [Abstract] ( 90 ) RICH HTML PDF (4594 KB)  ( 37 )
3770 Raman Spectral Characteristics of Pyrite in Luyuangou Gold Deposit, Western Henan Province and Its Indicative Significance for Multiphase Metallogenesis
ZHANG Jian1, LIU Ya-jian2, CAO Ji-hu3
DOI: 10.3964/j.issn.1000-0593(2022)12-3770-05
Luyuangou gold deposit is an important fractured altered gold deposit in Xiong’er Mountain, and pyrite is its main gold-bearing mineral. Testing the major elements, trace elements and isotope of pyrite can analyze the mineralization process of gold deposits. The conventional testing methods mainly include electron microprobe and laser-ablation inductively coupled plasma mass spectrometry, but these methods have the disadvantages of long test times and high costs. Because of forming under different temperature and pressure conditions, the spectral characteristics of pyrite are different. Conducting laser Raman test to analyze the displacement of Raman characteristic peaks and the change of full width at half maximum (FWHM), we can judge the temperature and pressure of pyrite formation and further infer the mineralization process of gold deposit, which has economic and efficient advantages compared with traditional analysis and test methods. Analyzing Raman spectroscopic of pyrite samples at a different elevation from 430 to 670 m, it found that the characteristic Raman displacement Ag near 379 cm-1 showed an increasing trend from elevation 430 to 500 m, the decreasing trend from elevation 500 to 580 m and a increasing trend from elevation 580 to 670 m. The Ag generally increases with mineralization pressure, and it is inferred that there are two phases of tectonic activity in the ore-controlling structure. The fragmentation zone of the first phase of tectonic activity reaches about elevation of 500 m, and the second phase of structural activity continues to develop upward based on the first phase, reaching an elevation of about 670 m. The FWHM of the characteristic peak at 379 cm-1 can indicate the crystallization and order of pyrite crystals. Generally, the wider FWHM of the characteristic peak, the worse crystallinity and order, and the higher the crystallization and precipitation temperature. The FWHM of gold-bearing pyrite near the peak of 379 cm-1 from elevation 430 to 500 m, increased gradually from 7.94 to 12.81, and from elevation 500 to 670 m, it gradually decreased from 12.81 to 8.81. It is speculated that corresponding to the two-phase structure-activity. There are two-phase hydrothermal activities. Electron microprobe sweeps analysis of pyrite at elevation 430 m revealed -two-phase hydrothermal activity indeed, with low As content in the first phase and higher As content in the second phase. Raman spectroscopy of pyrite formed from the second hydrothermal phase at elevation 430 m with Ag of 381.86 indicating the lower crystallization and precipitation pressure and FWHM of 12.80 indicating the higher crystallization and precipitation temperature, which testify the inferred geology process.
2022 Vol. 42 (12): 3770-3774 [Abstract] ( 113 ) RICH HTML PDF (1734 KB)  ( 53 )
3775 Optimization of Near-Infrared Detection Model of Blueberry Sugar Content Based on Deep Belief Network and Hybrid Wavelength Selection Method
ZHU Jin-yan, ZHU Yu-jie*, FENG Guo-hong*, ZENG Ming-fei, LIU Si-qi
DOI: 10.3964/j.issn.1000-0593(2022)12-3775-08
Using near-infrared spectroscopy technology combined with synergy interval partial least square (SiPLS), competitive adaptive reweighted sampling (CARS), successive projection algorithm (SPA) and uninformative variable elimination (UVE) feature extraction methods, the universal detection models of blueberry sugar content were established by deep belief network (DBN) to achieve on-line non-destructive rapid detection. The near-infrared spectra of 280 blueberry samples of “Bluecrop” and “Reka” were collected, and the sugar content of blueberries was determined by a hand-held refractometer. Firstly, using the outlier samples detection based on joint X-Y distances (ODXY) method to detect abnormal samples, there were 2 and 4 abnormal samples from Bluecrop and Reka respectively. After eliminating 6 abnormal samples, the remaining 274 samples were divided into a training set and test set in a ratio of 3∶1 by the sample set partitioning based on the joint X-Y algorithm (SPXY). Secondly, Compared and analyzed the improvement effect of Savitzky-Golay smoothing (S-G smoothing), centralization, multiplicative scatter correction and other pretreatment methods on the original spectrum of blueberry. Using SiPLS to reduce the spectral dimension and filter the characteristic band and using SPA, UVE and CARS, choose characteristic wavelengths again. We established partial least square regression (PLSR) and DBN models with the optimal characteristic wavelengths. The results showed that the optimal pretreatment method of the blueberry sugar content near-infrared detection model was S-G smoothing, the optimal band of blueberry sugar screening by SiPLS method were 593~765 and 1 458~1 630 nm, and the UVE algorithm was used to select 159 optimal wavelengths from 346 variables screened by SiPLS. When establishing the DBN model of blueberry sugar content, we analyzed the influence of different hidden layer numbers on the detection model, and the root means square error of cross-validation (RMSECV) as a fitness function, the particle swarm optimization (PSO) was used to optimize the number of neurons in each hidden layer between [1, 100]. It is found that the RMSECV of the DBN model reached the minimum value of 0.397 7 when the hidden layer was 3 layers, and the hidden layer node number was 67-43-25. Whether in the full spectrum or modeling characteristic wavelengths, the near-infrared DBN models of blueberry sugar content were superior to the conventional PLSR method. In particular, the characteristic wavelengths selected by the UVE method can greatly reduce the modeling variables, and the model accuracy was high. The correlation coefficient (RP) and root mean square error (RMSEP) of the optimal PLSR model were 0.887 5 and 0.395 9, respectively. TheRP and RMSEP of the optimal DBN model were 0.954 2 and 0.310 5. The research shows that the detection model of blueberry sugar content based on the characteristic wavelength extracted by SiPLS-UVE combined with the deep belief network method can better complete the accurate online analysis of blueberry sugar content, and the method is expected to be applied to the internal quality detection of blueberries and other fruits and vegetables.
2022 Vol. 42 (12): 3775-3782 [Abstract] ( 116 ) RICH HTML PDF (4144 KB)  ( 47 )
3783 Interval Genetic Algorithm for Double Spectra and Its Applications in Calibration Transfer
ZHENG Kai-yi, SHEN Ye, ZHANG Wen, ZHOU Chen-guang, DING Fu-yuan, ZHANG Yang, ZHANG Rou-jia, SHI Ji-yong, ZOU Xiao-bo*
DOI: 10.3964/j.issn.1000-0593(2022)12-3783-06
As a non-destructive detection method, near-infrared (NIR) spectra have been widely used in food analysis. In NIR analysis, the model between spectra and sample concentrations should be calibrated in advance, and the concentrations of new samples can be predicted by substituting their spectra with the calibrated model. However, the variation of measurement conditions can lead to spectra changes. This problem can be solved by calibration transfer which corrects the new spectra (secondary spectra) to be accurately predicted by the old spectra (primary spectra) model. The calibration transfer always uses full primary and secondary spectra for correction. However, full primary and secondary spectra contain interference, including noise and background, which can increase prediction errors. Hence, variable select is used to selecting the informative regions of NIR for calibration transfer. The commonly used variable selection method always treats primary spectra, and both primary and secondary spectra share the same regions for calibration transfer. However, in practical work, the informative regions of primary and secondary spectra are not the same. Thus, both primary and secondary spectra using the same regions for calibration transfer can increase prediction errors. Moreover, the original spectral ranges of primary and secondary spectra may not be the same, and the secondary spectra can not use the regions selected by primary spectra for calibration transfer. In order to solve this problem, this paper proposed a Genetic algorithm for intervals of double spectra (GA-IDS), which selects informative regions for both primary and secondary spectra simultaneously for calibration transfer. The procedure of GA-IDS includes(1)Randomly generating chromosomes in the population;(2)Analyzing each one of the chromosomes and deleting the error ones; (3)Obtaining the primary and secondary spectra regions and the corresponding Root mean squared error of validation (RMSEV) based on each one of the chromosomes; (4)Executing selection, crossover and mutation operations. After finishing one loop, the GA-IDS goes to step (2) to repeat execute errors correction, RMSEV computation, selection, crossover and mutation operation. After achieving the criterion of the final termination, the spectra regions with minimal RMSEV can be retained. Two datasets, including corn and wheat datasets, were used to evaluate this algorithm. The results show that, compared with full variables, GA-IDS can select good regions for both primary and secondary spectra to reduce prediction errors. Compared with Iterative interval backward selection (IIBS), GA-IDS can achieve lower errors at the small size transfer set.
2022 Vol. 42 (12): 3783-3788 [Abstract] ( 106 ) RICH HTML PDF (2955 KB)  ( 37 )
3789 Rapid Detection of Pesticide Residues on Navel Oranges by Fluorescence Hyperspectral Imaging Technology Combined With Characteristic Wavelength Selection
HAO Jie, DONG Fu-jia, WANG Song-lei*, LI Ya-lei, CUI Jia-rui, LIU Si-jia, LÜ Yu
DOI: 10.3964/j.issn.1000-0593(2022)12-3789-08
In this study, fluorescence hyperspectral imaging technology identified different concentrations of chlorpyrifos and carbendazim on the surface of navel oranges. Hyperspectral images of the concentrations of chlorpyrifos at 0, 0.5, 1 and 2 mg·kg-1 and carbendazim at 0, 1, 3 and 5 mg·kg-1 were acquired by a hyperspectral imaging system (392~998.2 nm) excited by a xenon light source. The sample’s region of interest (ROI) was captured by ENVI software. Raw spectral data were pre-processed by a spectral pre-processing methods, including SG, SNV and FD. The interval variable iterative spatial shrinkage (iVISSA), uninformative variable elimination algorithm (UVE) and competitive adaptive reweighted sampling (CARS) were used for the primary extraction of feature wavelengths and the two-dimensional correlation spectroscopy (2D-COS) method for secondary extraction of feature wavelengths. PLS-DA and PCA-LDA model developed primaryand secondary feature wavelength extraction at different concentrations of chlorpyrifos and carbendazim residues on the surface of navel oranges. 3 methods studied the spectral pretreatment. The results showed that the model effect of SG methods was best. A total of 26 feature wavelengths were extracted by the iVISSA method for the spectral data using the SG chlorpyrifos; A total of 30 feature wavelengths were extracted by the CARS method for the spectral data using the SG method of carbendazim. The 2D-COS algorithm was used for the secondary extraction of 26 and 30 feature wavelengths, resulting in 10 and 12 feature wavelengths, respectively. Discriminant models based on spectral data of primary and secondary extraction of feature wavelengths were established to identify the samples. The results showed that the PCA-LDA model based on iVISSA-2D-COS was the best with the calibration set and prediction set discrimination rates of 98.61% and 95.83% for different concentrations of chlorpyrifos. The PCA-LDA model based on CARS-2D-COS was the best with the calibration set and prediction set discrimination rates of 97.22% and 95.83% for different concentrations of carbendazim, respectively, which were higher than the discrimination rates of full-band spectral data and once-extraction feature spectral data. In this study, secondary extraction of the optimal feature wavelengths by 2D-COS has developed discrimination models, and the results can provide some reference for rapid and non-destructive discrimination for different concentrations of pesticide residues on the surface of navel oranges.
2022 Vol. 42 (12): 3789-3796 [Abstract] ( 115 ) RICH HTML PDF (5757 KB)  ( 81 )
3797 Application of Solution Cathode Glow Discharge-Atomic Emission Spectrometry for the Rapid Determination of Calcium in Milk
HAO Jun1, WANG Yu2, LIU Cong2, WU Zan2, SHAO Peng2, ZU Wen-chuan2*
DOI: 10.3964/j.issn.1000-0593(2022)12-3797-05
The content of calcium is closely associated with the quality of milk. The traditional analytic methods based on tedious wet digestion or dry ashing preparation techniques are low efficiency. Meanwhile, the milk samples for determination are too much as milk is an important and common food origin for calcium nutrient income. Therefore, it’s in urgent demand for the establishment of the rapid and field analytic method of calcium in milk. Recently, significant attention has been drawn to solution cathode glow discharge-atomic emission spectrometry (SCGD-AES) due to the absence of vacuum conditions as well as the addition of airflow of the fuel and carrier gas, etc. Thus, a portable SCGD-AES instrument was developed with an inside CCD detector, through which practicability for calcium determination in milk was inspected based on direct dilution sampling. Furthermore, the rapid and convenient method was established to rapidly determine calcium in milk using a home-made solution cathode glow discharger coupled with a portable optical fiber spectrometer based on direct dilution sampling. The conditions and parameters influencing the analytical sensitivity of potassium were optimized comprehensively, including the emission wavelength, the acidity of the cathode solution, etc. The results showed that acidity was a key parameter influencing the analytical sensitivity, and when 1%(V/V)HNO3 was used as the medium,the best analytical performances could be acquired. Therefore,1% (V/V) HNO3 was chosen as the dilution reagent. Furthermore, the selection of the dilution times of the real milk samples was investigated. The results showed that when the milk samples were diluted to 100 times or above, no significant matrix interference was observed and the accuracy could be assured. Under the optimized conditions, when the milk sample was diluted 100 times, the limit of determination for calcium in milk was 35 mg·L-1, which was just suitable for the direct determination, and the relative standard deviations based on 6 duplicate tests of the same milk sample were below 5%. The spiked recoveries were within the range of 89.0%~109.7%. The results showed that the method was simple and reliable and could satisfy the demands of rapid detection of calcium in milk for laboratory and field tests.
2022 Vol. 42 (12): 3797-3801 [Abstract] ( 114 ) RICH HTML PDF (1797 KB)  ( 38 )
3802 Study on Stability and Sensitivity of Deep Ultraviolet Spectrophotometry Detection System
ZHANG Xue-fei1, DUAN Ning1, 2*, JIANG Lin-hua1, 2*, CHENG Wen2, YU Zhao-sheng3, LI Wei-dong2, ZHU Guang-bin4, XU Yan-li2
DOI: 10.3964/j.issn.1000-0593(2022)12-3802-09
The existing national standard photometric method can not directly determine the pollutants in the production process of continuous reaction units in the process industry. The main reason is that the absorption of ultraviolet light by oxygen in the deep ultraviolet region interferes with the detection of target substances by ultraviolet spectrophotometer, resulting in a certain degree of deviation in the detection results. Therefore, the key to solving this problem is to stably obtain the highly sensitive photometric information of substances with different characteristic wavelengths in the deep ultraviolet region. In this study, a nitrogen transmission and distribution system was installed based on a UV spectrophotometer. At the same time, an automatic injection flow cell and tray are designed to realize automatic sample injection between detection gaps. The nitrogen flows into the optical system area, sample room and data receiving area of the instrument is accurately controlled at 6, 2 and 3 L·min-1 respectively, so that the average value of the baseline flatness of the instrument is reduced from 0.108 to 0.010, which is 90.7% less than the air conditioner. Comparing the differences in the absorbance, sensitivity, sensitivity change and linear range of SO2-4 between air and nitrogen atmospheres, reveals that the absorbance and sensitivity of detection results in nitrogen atmosphere are improved in the range optical pathlengths b=1~100 mm. The sensitivity change increases from 10.42% to 30.65% when b=1 mm to b=100 mm, but the linear range decreases from 0.09 to 0.03 g·L-1 with increasing of optical path lengths. It shows that the nitrogen transmission and distribution system successfully inhibits the attenuation of UV intensity in the detection process. Compared with ion chromatography, one of the common methods for detecting SO2-4, this method has the advantages of convenient detection, stable and reliable detection results and good economic benefits, laying a foundation for industrial application.
2022 Vol. 42 (12): 3802-3810 [Abstract] ( 101 ) RICH HTML PDF (5395 KB)  ( 47 )
3811 Detection of Hydrolyzed Leather Protein Adulteration in Infant Formula Based on Wavelength Attention Convolutional Network and Near-Infrared Spectroscopy
CHEN Guo-xi1, 2, ZHOU Song-bin2*, CHEN Qi1, LIU Yi-sen2, ZHAO Lu-lu2, HAN Wei2
DOI: 10.3964/j.issn.1000-0593(2022)12-3811-06
In recent years, deep learning has made a series of breakthroughs in processing near-infrared spectroscopy, Raman spectroscopy, fluorescence spectroscopy and other spectroscopy data. However, due to the high demand for deep learning methods for the size of the training set, and it is difficult to obtain a large number of labeled samples in the field of analytical chemistry, the overfitting issue has always been highly-concerned by researchers in the application of deep neural network in chemometrics. In response to this problem, this paper proposed a near-infrared spectra modeling method based on the wavelength attention-convolutional neural networks (WA-CNN) and applied it to the quantitative analysis of hydrolyzed leather protein (HPL) adulteration in infant formula. WA-CNN adds a wavelength attention module based on the traditional convolutional network. This module uses convolution operation to learn the attention weights and activates the effective bands in the form of multiplication, thereby effectively alleviating the redundancy and over-fitting problem in NIR modeling based on deep learning. A total of 100 HLP adulterated infant formula samples were tested, and the adulteration ratio was in the range of 0% to 20%. Random sampling was performed 10 times for modeling, in which 60% of the samples were used for training, while the remaining 40% of samples were adopted for testing. The model was evaluated by the mean of root mean square error (RMSEP), coefficient of determination (R2) and relative analysis error (RPD). Three traditional models, namely partial least squares regression (PLS), support vector machine regression (SVR) and conventional one-dimensional convolutional neural network (CNN), were also established for comparison. Compared with the above comparison methods, WA-CNN achieved the best model prediction results and obtained RMSEP=1.32%±0.12%, R2=0.96±0.01, RPD=4.92±0.41. In addition, the results also show that the WA-CNN has a faster and more stable convergence process than the traditional CNN for both the training set and the test set during the training process. Moreover, in the case of different training sample sizes (ranging from 20% to 80%), WA-CNN also achieves the best accuracies among all the examined models.
2022 Vol. 42 (12): 3811-3816 [Abstract] ( 93 ) RICH HTML PDF (3155 KB)  ( 39 )
3817 Research on On-Line Monitoring Technology of Water Sediment Concentration Based on Transmission Spectrum
YANG Hua-dong1, 2, ZHU Hao1, 2, WANG Zi-chao1, 2, LIU Zhi-ang1, 2
DOI: 10.3964/j.issn.1000-0593(2022)12-3817-06
Monitoring water sediment concentration has always been important in hydrological observation and water construction. Real-time and effective monitoring of water sediment concentration has important practical value. Traditional manual measurement methods are inefficient and unable to monitor in real-time. Although instrument monitoring methods based on an ultrasonic wave can realize the real-time measurement of sediment concentration in a water body, they have disadvantages in terms of safety, stability and measuring range. The technology of material content monitoring based on spectroscopy is fast, non-destructive, accurate and efficient and has been widely used in various fields in recent years, providing new ideas and methods for on-line monitoring of water sediment content. However, direct transmission spectroscopy is susceptible to the instability of the light source and the interference of stray light from outside, resulting in spectral noise. At the same time, due to the light intensity saturation of the instrument and equipment, its measuring range is limited. Based on this, this paper focuses on direct transmission spectrum noise processing and multi-section calibration technology and designs a fast and large-range on-line monitoring system for water-sediment content based on transmission spectrum. First, the relationship between sediment content and transmitted light intensity in a water body is analyzed based on Lambert-Bill’s basic law theory. Then, a sediment monitoring test system for a water body is established by using colorimetric dish holder laboratory, and standard solutions with different sediment content ratios are prepared to calibrate the actual correlation degree of intensity-sediment content. In order to overcome the influence of spectral noise, the original transmission spectrum is pre-processed by a wavelet threshold denoising algorithm. Spectral noise is eliminated using sym7 wavelet base, minimum and maximum threshold selection rule and 7 times of wavelet decomposition. With different integration times, a large range measurement of sediment content from 4% to 22% is realized by multi-section calibration, and the calibration function and measurement range are automatically matched in the algorithm. The results show that the R-square values of the calibration curves are all above 0.99, with good linearity and by the theory. Finally, the on-line monitoring system for water-sediment content is designed and tested for actual accuracy. The results show that the measurement errors are all controlled below 0.4% in the wide range of measurement, the mean of full range error is 0.173%, and the standard deviation of error is 0.115%, which can meet the actual requirements of the project. Therefore, an on-line monitoring system for water-sediment concentration over a wide range is proposed in this paper, and the system’s measurement accuracy is verified by tests, which can be used for real-time on-line monitoring of water sediment concentration.
2022 Vol. 42 (12): 3817-3822 [Abstract] ( 121 ) RICH HTML PDF (3781 KB)  ( 47 )
3823 Near-Infrared Spectroscopy Combined With Random Forest Algorithm: A Fast and Effective Strategy for Origin Traceability of Fuzi
GONG Sheng1, ZHU Ya-ning2, ZENG Chen-juan3, MA Xiu-ying3, PENG Cheng1, GUO Li1*
DOI: 10.3964/j.issn.1000-0593(2022)12-3823-07
Effective and reliable methods of origin certification are essential for protecting high-value Chinese medicinal materials (e.g geo-authentic Chinese medicinal materials, geographical indication products, etc.) from designated regions. As a famous traditional Chinese medicine and a geo-authentic Chinese medicinal material produced in Sichuan Province, Aconiti Lateralis Radix Praeparata (Fuzi) has a remarkable curative effect and wide clinical application is in great demand in domestic and international markets. The efficacy and price of the Fuzi of different origins vary, and it is difficult for the public to identify them through traditional experience accurately. Mass spectrometry-based on plant metabolomics is a tedious and lengthy test sample preparation process, complicated operation, long detection time, and low reproducibility. Near-infrared (NIR) spectroscopy, a mature, fast and nondestructive detection technique was integrated with machine learning to bring new ways for online quality supervision and control of Chinese medicinal materials. Therefore, a non-destructive identification model based on NIR spectroscopy combined with a random forest (RF) algorithm was developed for different origins of Fuzi. A total of 255 samples of Fuzi were collected from the major cultivation regions of Sichuan, Shaanxi and Yunnan, and the diffuse reflectance spectral information of all samples was obtained using Fourier transform NIR spectroscopy. Single and combined spectral preprocessing methods are used to eliminate multiple interferences in the spectra, and the best preprocessing method is screened and used as an input indicator to build an RF model. The comprehensive performance of the RF model was evaluated using sensitivity, specificity and balanced accuracy. The results showed that Savitzky-Golay 11-point smoothing combined with multivariate scattering correction was the best preprocessing method.Using only the full wavelength data, the prediction accuracy of the RF model for the three groups of provincial samples was also checked over 90%, and the prediction accuracy after preprocessing reached 98.39%. For the city/county level samples, the RF model also had the excellent discriminative ability, greater than 75% accuracy. The RF model achieved 100% recognition rate for samples from cultivation areas around the traditional production areas. The top 100 feature wave numbers were filtered out, and the model was re-optimized, and the recognition accuracy of the model for each city/county level region was over 85%, especially for some samples from the highlands was significantly improved. In this study, an environment-friendly traceability strategy with faster analysis, less sample loss and higher precision was adopted, providing a new model for the rapid and efficient identification of Fuzi of different origins and a reference for the subsequent identification and traceability of Fuzi and its related processed products.
2022 Vol. 42 (12): 3823-3829 [Abstract] ( 145 ) RICH HTML PDF (4128 KB)  ( 54 )
3830 Rapid Identification of Transgenic Soybean Oil Based on Ultraviolet Raman Spectroscopy
GUO Zong-yu, GUO Yi-xin, JIN Wei-qi*, HE Yu-qing, QIU Su
DOI: 10.3964/j.issn.1000-0593(2022)12-3830-06
Transgenic technology plays an important role in increasing crop yield and quality, and reducing pesticide use and production cost, but it also has a certain potential threat to the ecological environment. In order to prevent the abuse of genetically modified soybean in food, the research on rapid identification technology of genetically modified products is particularly urgent. UV Raman spectroscopy detection technology can be effectively used in material telemetry and identification with many advantages, such as long-distance non-destructive telemetry detection, simplicity, efficiency, rapidity and accuracy. Based on UV Raman spectroscopy, the feasibility of identifying transgenic/non-transgenic soybean oil and other types of edible oil was studied. The UV Raman spectra of five different edible oils (500 samples of each brand of GM/non-GM soybean oil and 100 samples of one kind of rice oil, 2 100 samples in total) in the wavelength range of 3 500~400 cm-1(268~293 nm) were collected. In order to improve the signal-to-noise ratio of spectral data and ensure the accuracy of classification, we used Savitzky-Golay filtering to denoise, adaptive iterative weighted penalty least squares (airPLS) to correct baseline and multiple scattering correction (MSC) to standardize spectrum. According to the UV Raman fingerprint of soybean oil, the main chemical components were analyzed, including fats, proteins and amides. We divided each kind of soybean oil into the training set and test set according to 1∶1, input the training set data into a support vector machine (SVM) for training, and established the best model by 10-fold cross-validation. The recognition accuracy was 99.81%, which had a significant effect on detecting the transgenic soybean. Principal component analysis (PCA) is used for data dimensionality reduction, and 8 principal components were extracted, with a cumulative contribution rate of 74.84%, which can represent most of the characteristics of the original data. On this basis, the preprocessed spectral data were divided into the training set and test set according to 4∶1. The partial least squares regression discriminant analysis (PLS-DA) and 10-fold cross validation method were used to establish the best PLS-DA model of the whole spectrum (the discrimination threshold was set to 0.5) with the accuracy of 70.95%. It is shown that UV Raman spectroscopy can accurately and rapidly identify GM/non-GM soybean oil and rice oil. The study provides an important practical and theoretical basis for the on-site detection of transgenic soybean oil and its food and is of great significance in promoting the development of telemetry identification technology for transgenic products.
2022 Vol. 42 (12): 3830-3835 [Abstract] ( 118 ) RICH HTML PDF (4067 KB)  ( 75 )
3836 Research on LIBS Signal Processing Based on EEMD-MRA Method
LI Ming, ZHANG Shuai, WU Tian-yu, WANG Jian, GUAN Cong-rong*, CHEN Ji-wen*
DOI: 10.3964/j.issn.1000-0593(2022)12-3836-06
LIBS technology has many advantages, but the analysis accuracy is affected by factors such as spectral noise interference and matrix effect[1]; the EEMD method can decompose the different characteristic components of LIBS signal adaptively. The MRA method can compensate for the mutual interference between element signals and improve LIBS data accuracy. In this paper, the original signal of the standard sample is obtained through the self-built test system. After being processed by the EEMD-MRA method, the correlation coefficient R2 of the element concentration curve has been greatly improved, greatly improved the accuracy of data, and provided a new way for processing LIBS signal.
2022 Vol. 42 (12): 3836-3841 [Abstract] ( 106 ) RICH HTML PDF (5147 KB)  ( 53 )
3842 Design and Realization of High-Speed Acquisition System for Two Dimensional Fourier Transform Solar Spectrometer
ZHU Xiao-ming1, 2, 3, BAI Xian-yong1, 2, 3*, LIN Jia-ben1, 2, DUAN Wei1, 2, ZHANG Zhi-yong1, 2, FENG Zhi-wei1, 2, DENG Yuan-yong1, 2, YANG Xiao1, 2, HUANG Wei1, 2, 3, HU Xing1, 2, 3
DOI: 10.3964/j.issn.1000-0593(2022)12-3842-09
Simultaneous or quasi-simultaneous multi-spectral solar imaging can be used to obtain the solar atmosphere’s three-dimensional magnetic field and thermodynamic parameters, which is a key development direction of the focal plane terminal equipment for solar observations in the future. The Fourier transform spectrometer (FTS) has a wide bandwidth, high sensitivity and a high spectral resolution, but it is restricted by high frame rate and large area array detector. It has not been used for routine solar spectrum imaging yet. However, with the rapid development of CMOS image sensor technology, in the visible and near-infrared bands, the size and frame rate of the detector array have been qualitatively improved compared to traditional CCD detectors, making it possible to develop an area array, Fourier, solar spectrometer. Here in this paper, we introduce an area array, and high frame rate CMOS image sensor and design a set of high-speed data acquisition software and hardware systems for the scientific needs of area array Fourier transform solar spectrometers. It realizes the 10 kHz high-speed triggering, fast acquisition of 10 000 frames per second, 0.5 GB·s-1 large data volume continuous, real-time storage and other functions. Combining with the above system and the existing point source FTS at the Huairou Solar Observing Station and targeting the visible light chromosphere line (Hα 656.3 nm) and its nearby photosphere line, we set up a visible light experimental system and carried out surface source solar spectrum detection. We used the laboratory tungsten lamp and the sun as the light source, performed equal optical path difference interval sampling, and successfully obtained the area array interferogram. We obtained the narrow-band continuum spectrum and the solar chromosphere and photosphere line near 656.3 nm. Using the cross-calibration method, we compared our solar spectrum at the same resolution with the standard spectrum obtained by the National Solar Astronomical Observatory’s NSO Fourier Spectrometer, and the results are the same, verifying the performance of the data acquisition system for the FTS of the plane array and the feasibility of area array Fourier Transform Solar Spectrometer in solar observation. This research lays a technical foundation for the wide-band solar FTS of the plane array in the visible region and at the same time, accumulates valuable experience for the subsequent extension of “The Infrared System for the Accurate Measurement of Solar Magnetic Field” (AIMS) from the line source to the plane source.
2022 Vol. 42 (12): 3842-3850 [Abstract] ( 126 ) RICH HTML PDF (6576 KB)  ( 54 )
3851 Study on Spectroscopy and Locality Characteristics of the Nephrites in Yutian, Xinjiang
HE Yan1, SU Yue1, YANG Ming-xing1, 2*
DOI: 10.3964/j.issn.1000-0593(2022)12-3851-07
Xinjiang is one of the important nephrites origins in the world, and primary nephrites from Yutian have a representative of high quality. 48 nephrites samples from Hanilake, Alamas, Saidikulamu and Qihakule were analyzed by conventional instrument testing, Fourier transforms infrared spectroscopy (FTIR), laser Raman spectroscopy and laser ablation inductively coupled plasma mass spectroscopy (LA-ICP-MS) analysis for the investigation of spectroscopic characteristics and chemical compositions. The result showed that nephrites from Yutian, Xingjiang varied from cyan, bluish white, bluish yellow, and yellowish white to gray. The samples are opaque to translucent with greasy to glass luster. As polycrystalline aggregates, nephrites had a variety of specific refractive indices(1.61~1.62) and gravity (2.95~2.99). Infrared spectroscopy spectra displayed the typical tremolite absorption between 900~1 200 and 400~760 cm-1. Infrared absorption bands at 1 143,1 096,1 040,995,925 cm-1 were induced by O—Si—O anti-symmetric stretching vibration and O—Si—O symmetric stretching vibration, 763,689 cm-1 were induced by Si—O—Si anti-symmetric stretching vibration, and 538,512,465,420 cm-1 were induced by Si—O bending vibration, M—O lattice vibration and OH horizontal vibration. Raman spectroscopy spectra of nephrites from Yutian, Xinjiang were consistent with the tremolite characteristics. 120, 175, 220, 365, 389 cm-1 were the lattice vibration peak, 670 cm-1 represented the Si—O—Si stretching vibration of amphibole minerals, 931, 1 029, 1 060 cm-1 were due to Si—O stretching vibration, 3 672, 3 680 cm-1 belongs to M—OH stretching vibration. The main components of Yutian nephrites are MgO, CaO and SiO2, and rare earth element characteristics had ranges of 0.068 to 3.902 for δCe, 1.064 for average; δEu ranges from 0 to 8.832, 0.343 for average, with negative Eu anomaly. LREE/HREE ranges from 0.010 to 3.369, 0.682 for average. The ΣREE ranges from 0.407 to 18.768, 3.138 on average. Based on the characteristics of trace elements and rare earth elements, nephrite from Yutian, Xinjiang can be distinguished from other representative areas such as Chuncheon (Korea), Qiemo(Xinjiang) and Sanchahe(Qinghai). The spectroscopic characteristics and chemical compositions of nephrites from Yutian, Xinjiang have enriched the information and data of nephrites’ origin and provided a reference for further study. In the future, the origin information of nephrites from other producing areas can be extracted based on gemological characteristics, spectral characteristics, rare earth elements and trace elements. Combined with the background of ore-forming geological conditions, it is possible to trace the origin of nephrites to every vein.
2022 Vol. 42 (12): 3851-3857 [Abstract] ( 153 ) RICH HTML PDF (4166 KB)  ( 145 )
3858 Effect of Granularity on the Characteristics of Visible-Near Infrared Spectra of Different Coal Particles
ZHANG Chao1, 2, LIU Shan-jun1*, YI Wen-hua1, XIE Zi-chao2, LIU Bo-xiong2, YUE Heng1
DOI: 10.3964/j.issn.1000-0593(2022)12-3858-06
Coal is the most important energy source in China. In mining, coal cutting, transportation, washing, processing, and cleaning coal storage, it is necessary to know the composition and content of coal and the degree of mixed gangue in time of determining, master and monitor the quality of coal. At present, based on visible light to the near-infrared emission spectrum of coal, in situ testing technology has become a research hotspot, and the granularity is one of the important factors affecting spectral characteristics to carry out the granularity to study the influence of the different spectral reflectance characteristics of coal, to understand the spectral characteristics of coal deeply. Coal spectrum recognition accuracy is of great significance. For this purpose, this article selects the main coal enrichment region (including Inner Mongolia Wuhai, Xinjiang Hami, Shanxi Yangquan) of lignite, bituminous coal, and anthracite as the research object by using an SVC HR-1024 spectrometer with different granularity coal- near-infrared spectrum of visible light sample test, analyzes the particle degree of the influence law of spectral reflectance of coal samples, and the difference of the influence of granularity on the spectrum of different coal. On this basis, the physical mechanism behind the experimental phenomenon is analyzed and discussed. The results show that the emission spectrum characteristics of coals with different metamorphic degrees are similar. In other words, the reflectance is the low invisible band and decreases slowly with the increase of wavelength, while it rises rapidly in the near-infrared band. When the granularity of the coal sample is greater than 0.10 mm, the granularity has little influence on the spectral characteristics, and the change law of the reflection spectrum with granularity is not obvious. When the granularity is less than 0.10 mm, the influence of granularity on the spectrum of the coal sample increases. In addition, the influence is mainly reflected in the slope of the reflectance spectral curve of the near-infrared band. The smaller the granularity is, the more significant the reflectivity increment is and the larger the slope of the spectral curve is. A granularity of 0.10 mm can be used as the sensitive limit of granularity’s influence on the coal’s spectral characteristics. The spectral curves of different coal types are affected by particle size to different extents, and the impact on lignite is the largest, followed by bituminous coal, and the least impact on anthracite. It can be seen that when using the reflectance spectrum to analyze coal quality and identify coal species, the effect of selecting a powder sample with granularity of less than 0.10 mm is better than that of a large particle or lump sample.
2022 Vol. 42 (12): 3858-3863 [Abstract] ( 115 ) RICH HTML PDF (3486 KB)  ( 41 )
3864 Effects of Different LED Light Quality on the Physiological Characteristics and Ultrastructure of Ginseng Seedling Leaves
FANG Ping1, 2, YANG He1, 3, NIU Chen1, 3, DONG Xing-min1, 3, XU Yong-hua1, 3*, LIU Zhi3*
DOI: 10.3964/j.issn.1000-0593(2022)12-3864-08
The present study is mainly aimed at studying the effect of different light quality on the growth of ginseng seedling leaves, to explore the excellent light quality of ginseng factory seedlings, and provide a basis for improving the quality of ginseng seedlings. The experiment set up six groups of treatments, namely white light (W, as a control), blue light (B, 460~480 nm), red light (R, 615~635 nm), green light (G, 510~530 nm), yellow light (Y, 585~605 nm), red and blue (RB, R/B=4∶1), white light as the contrast light source. The study results showed that the leaves of ginseng seedlings grown under different light qualities had obvious changes in appearance, physiological characteristics and cell structure. In the process of leaf area growth, the leaf area under red, blue and white light is larger, next is red light and the smallest under blue light. In the distribution of chlorophyll, the treatment of adding blue light is significantly higher than the control, indicating the Blue light plays a key role in the synthesis of chlorophyll. Moreover, it is the lowest under red light. The electron efficiency of chlorophyll fluorescence is higher under blue, yellow and white light. In terms of stomata characteristics, there is more stomata numbers in green, red and white light, and the area of a single stomata is larger under B and RB light. Through observation of leaf ultrastructure under an electron microscope, it is found that different light qualities significantly impact the cell structure of leaves, mainly in the distribution of mitochondria and chloroplasts and the structure of chloroplasts. White light and blue light have more mitochondria and chloroplasts, and the number of stacks of chloroplast lamella structure is also more compact and rich. In addition, the senescence process of the seedling leaves grown under different light quality also had obvious differences. The B and RB treatment senescence speeds were fast. In summary, different light qualities have different effects on the growth of ginseng seedling leaves, but blue light and red-blue composite light have more excellent characteristics and better physiological parameters. However, in application and practice, it is also necessary to formulate corresponding light quality ratio strategies according to specific needs to achieve the purpose of strong seedlings and high yield.
2022 Vol. 42 (12): 3864-3871 [Abstract] ( 104 ) RICH HTML PDF (6351 KB)  ( 24 )
3872 Fluorescence Characteristics of Soil WSOC Under Straw Cover Rotation on Slope Farmland of Low Mountains and Hills
LI Yu-mei1, WANG Nan-nan1, 2, LIU Zheng-yu3, WANG Gen-lin1*, SHI Yan3, WANG Wei1, YU Hong-jiu1, ZHANG Lei4
DOI: 10.3964/j.issn.1000-0593(2022)12-3872-07
In order to improve the efficiency of straw returning and increase the soil organic carbon, a protective tillage method based on the combination of planting and feeding on sloping farmland was explored. The effects of straw mulching and rotation tillage technology on soil water-soluble organic carbon (WSOC) fluorescence characteristics and aggregate organic carbon through field experiments were studied, which included current season straw mulching and leisure, last season straw mulching and rotary tillage. Compared with conventional farming, which was rotating tillage after straw removal. The results show that WSOC resolved into 4 groups C1, C2, C3, C4, under the above three treatments on the sandy dark brown soil, in which fluorescent components mainly include fulvic acid (Peak A and Peak C)in the ultraviolet and visible regions and humic acid (F) and short-wave tryptophan (protein-like B, D peaks) and other components. SRT treatment increased the content of fulvic acid (Peak A and Peak C) and protein-like component C4. Compared with SFT and CRT, whose components of C1 and C2 increased by 112.73%, 109.35% and 107.77%, 66.07% and the group C4 increased by 28.26% and 42.31%, the difference was significant. While increased the content of humic acid C3 from the autogenic humus componentunder the CRT treatment was increased by 16.76% and 49.74% compared with the SRT and SFT treatments. Soil aggregate organic matter in 0~20 cm cultivated layer was mainly distributed in the mineral bound state (MOM) of <0.053 mm, with an average proportion of 63.90%, followed by 0.25~0.053 mm fine particulate organic matter (oPOM), accounting for 23.8%, and the content of coarse-grained organic matter (>0.25 mm) was the lowest, only 11.2%. SRT treatment significantly increased the content of oPOC, and the values of FI and HIX increased, which means the accumulation of soil humus increased. The accumulation trend was strengthened, providing a scientific basis for implementing protective tillage techniques for straw mulching and returning to the field in low mountain and hilly areas.
2022 Vol. 42 (12): 3872-3878 [Abstract] ( 95 ) RICH HTML PDF (4052 KB)  ( 39 )
3879 Investigation and Research on the Characteristics of Heavy Metal Pollution in Children’s Sandpits Based on XRF Detection
TANG Ju1, 2, DAI Zi-yun2*, LI Xin-yu2, SUN Zheng-hai1*
DOI: 10.3964/j.issn.1000-0593(2022)12-3879-04
Sandpit is an important outdoor playground for children. Moreover, it also has good rainwater permeability, which makes it easy to accumulate pollutants that accompany the surrounding surface runoff. Therefore, children playing in the sandpit face the health risk of heavy metal pollutants entering the body. A method for quantitative and rapid detection of the characteristics of heavy metal pollution in children’s sandpits in Beijing using the X-ray fluorescence spectroscopy (XRF) analyzer was introduced in this study. The results showed that: (1) The relative standard deviation and relative error between the measured values and theoretical values of Pb, Cu, As, and Cd in the self-made standard samples by XRF were -1.3%~7.5%, and 1.1%~5.3%, respectively, which were all consistent with the requirements of instrument testing specified in the relevant environmental quality testing technical specifications (less than 10%). (2) There was a very significant positive correlation between the measured values and the theoretical values of the four heavy metals (p<0.001), and their coefficients of determination (R2) were 0.999, 0.999, 0.996, and 0.998, respectively. The results established fitting equations of measured and theoretical values; (3) XRF was used to determine the heavy metal content of children’s sandpits in 17 parks and 13 residential areas in Beijing. The Pb and As content in the two groups of samples were significantly different, but there was no significant difference between the Cu and Cd content. The coefficients of variation of the standard deviations of the four heavy metals ranged from 0.24~0.43. These values were all greater than 0.3, except for Cd, which indicated significant spatial variability; (4) Compared with the background values of soil elements in Beijing, the average content of Pb, Cu and Cd in children’s sandpits was significantly higher, which were 1.87 and 1.53, 1.79 and 2.23, 12.02 and 11.68 times, respectively. It can be seen that Pb, Cu, and Cd are enriched in different degrees in children’s sandpits at sampling sites, and their health risks cannot be ignored. XRF can provide accurate and fast data support for managing and maintaining children’s playgrounds.
2022 Vol. 42 (12): 3879-3882 [Abstract] ( 95 ) RICH HTML PDF (1362 KB)  ( 66 )
3883 Changes in Organic Carbon Components and Structure of Black Rhizosphere Soil Under Long-Term Different Fertilization
CHEN Lei1, 2, HAO Xiao-yu1, MA Xing-zhu1, ZHOU Bao-ku1, WEI Dan3, ZHOU Lei4, LIU Rong-le5, WANG Hong2*
DOI: 10.3964/j.issn.1000-0593(2022)12-3883-06
Soil organic carbon is the crucial driver and regulator of the agricultural ecosystem. In particular, the quantification of rhizosphere organic carbon plays an important role in the soil carbon cycle and mineral nutrient release. Through the research on the changes of organic carbon, labile organic carbon and organic carbon structure in soybean rhizosphere soil under different long-term fertilization, we can further understand the mechanism of rhizosphere organic carbon fixation and stability. The outcome of this research would provide a scientific basis and theoretical support for improving carbon fixation of farmland ecosystem and sustainable development of farmland. The experiment uses a long-term black soil positioning test. Chemical analysis and 13C-NMR were used to study dynamic changes in organic carbon, labile organic carbon and organic carbon structure in soybean rhizosphere soil. The results showed that organic carbon concentrations were generally higher in rhizosphere soil than in bulk soil. Long-term fertilization treatment could significantly increase concentrations of organic carbon and low labile organic carbon in rhizosphere soil, and MNPK treatment had the best effect. Compared with CK treatment, MNPK treatment significantly increased the proportion of alkyl C, O-alkyl C and the ratios of alkyl C to O-alkyl C, and decreased aromatic C and the ratios of aromatic C to total C in rhizosphere soil, especially in bulk soil.NPK treatment increased the proportion of aromatic C and the ratios of aromatic C to total C, increased alkyl C and the ratios of alkyl C to O-alkyl C in rhizosphere soil, and decreased O-alkyl C, which the results were opposite in bulk soil. The above analysis showed that: MNPK treatment significantly increased the content of rhizosphere organic carbon, increased alkyl C, O-alkyl C and the ratios of alkyl C to O-alkyl C while promoting the formation of aggregates and increased the stability of soil particle structure. NPK treatment increased aromatic C, and the ratios of aromatic C to total C reduced the rhizosphere O-alkyl C, which decreased the stability of aggregates. At the same time, it is proved that 13C-NMR technology combined with semi-quantitative analysis could be used to comprehensively analyze the structural changes of different organic carbon functional groups to gain a deeper understanding of the stability mechanism of rhizosphere soil organic carbon.
2022 Vol. 42 (12): 3883-3888 [Abstract] ( 102 ) RICH HTML PDF (1213 KB)  ( 38 )
3889 Design and Experiment of a Handheld Multi-Channel Discrete Spectrum Detection Device for Potato Processing Quality
WANG Wei, LI Yong-yu*, PENG Yan-kun, YANG Yan-ming, YAN Shuai, MA Shao-jin
DOI: 10.3964/j.issn.1000-0593(2022)12-3889-07
Potatoes are China’s fourth major food crop. With the government’s continuous emphasis on potato production and sales and the strategy of potato staple foods, its market share has also increased year by year. However, the quality of potatoes varies from place to place and even in the same region, which has a serious impact. The development of the potato industry. Therefore, realizing rapid non-destructive testing of potato quality has important practical significance for developing the potato staple food industry. This paper aims to develop a low-cost non-destructive rapid detection device for the potato quality. The successive projections algorithm (SPA) is used to analyze the distribution of characteristic wavelengths of potato processing quality in a spectrometer environment. According to the model results in the preprocessing state of the standard normal variate transformation (SNV), a selection of 7 bands (700,750,800,850,900,950 and 1 000 nm) is selected. Based on the potato’s special epidermal characteristics and internal texture uniformity, a handheld potato multi-quality visible/near infrared local diffuse transmission detection device is designed, including a light source module, a spectrum acquisition module, a control module, and a power supply. Module, display module, the size of the whole device is 140 mm×80 mm×70 mm, and the weight is 340 g. A potato multi-quality partial least squares prediction model was established using the research and development equipment. The root means square error of the potato dry matter and starch content prediction model verification sets were 1.05% and 1.02%, respectively. At the same time, based on the development tools of QT, the real-time analysis equipment control software was written in C language, which realized the one-click real-time non-destructive inspection of the internal quality of potatoes. Finally, the testing stability and accuracy of the R&D device were tested and verified. The results show that the developed handheld potato multi-quality sensor detection device can meet the needs of on-site real-time detection and provide technical support for developing the potato staple food industry.
2022 Vol. 42 (12): 3889-3895 [Abstract] ( 94 ) RICH HTML PDF (5860 KB)  ( 38 )
3896 Extraction Method of Oasis Shelterbelt Systems Based on Remote-Sensing Images ——A Case Study of Dengkou County
GAO Feng1, 2, 3, JIANG Qun-ou1, 2, 3*, XIN Zhi-ming4, XIAO Hui-jie1, 2, LÜ Ke-xin1, QIAO Zhi1
DOI: 10.3964/j.issn.1000-0593(2022)12-3896-10
Shelterbelt systems are the main type of vegetation in the desert oasis regions, which provide a strong guarantee for wind-break and sand fixation, salt-water regulation and water-heat balance. It is important to investigate the spatial distribution information of shelterbelts. However, precisely mapping shelterbelts systems on a large scale are difficult due to narrow strips, small patches and wide & scattered distribution. This study aims to accurately map shelterbelts using object-oriented extraction based on GF-2 satellite imagery in Dengkou oasis. Firstly, the optimal scale parameter of SF segmentation was determined by local variance (LV) and rate of change (ROC) curve, and then the features space and classifier’s parameters were optimized by Out of bag error (OOB error) and Gini index through Random Forest (RF) algorithm prior to classification. Finally, Random Forest, CART decision tree, Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) were compared and validated for shelterbelt systems extraction. The results showed that: (1) the ROC-LV curve method can obtain the possible value of optimal scale parameter more objective and more efficiently than iterating all scale parameter values. (2) OOB error and Gini index through RF algorithm can effectively eliminate the redundant features among spectral, shape and texture. The processing time was sharply reduced and ensuring the accuracy of the classification. (3) The classification results were verified based on the measured data sets, and the results showed that the feature optimization based on the RF algorithm combined with the SVM classifier was the best method for extracting the desert oasis shelterbelt systems, with the highest producer accuracy of 97.14%. Meanwhile, the extracted area of shelterbelt systems was 208.99 km2, which was close to reality (210 km2). The SVM classifier performs better than the other three classifiers while zooming in a small areas; (4) Due to the high resolution of GF-2 images and the near-infrared band, sub-meter information can be obtained through appropriate band fusion. Based on the object-oriented method, a single shelterbelt can be used as the basic unit to explore the attributes and characteristics of the shelterbelts net. For example, the broken shelterbelts information could be extracted. All these conclusions will provideimportant technical support for the shelterbeltextraction in the desert oasis areas.
2022 Vol. 42 (12): 3896-3905 [Abstract] ( 140 ) RICH HTML PDF (7693 KB)  ( 31 )
3906 Thermal Oxidative Aging Mechanism of Modified Steel Slag/Rubber Composites Based on SEM and FTIR
ZHANG Hao1, 2, HAN Wei-sheng1, CHENG Zheng-ming3, FAN Wei-wei1, LONG Hong-ming2, LIU Zi-min4, ZHANG Gui-wen5
DOI: 10.3964/j.issn.1000-0593(2022)12-3906-07
Steel slag tailings are the main solid waste in the metallurgical industry, with the production of 15%~20% of crude steel. Due to limited technology, the utilization ratio is quite low and only reaches 10% of steel slag tailings production. Meanwhile, steel slag tailings are disposed of in direct stacking and landfill since the management system is not perfect, which pollutes land, underground water, and air quality. In the face of the above problems, in this study, the modified steel slag powder was developed by hot slag, electric furnace slag and air quenching slag, and the modified steel slag powder was compounded with composite rubber to prepare modified steel slag/rubber composites. According to the “Accelerated aging and heat resistance test of vulcanized rubber or thermoplastic rubber in hot air” (GB/T3512—2014), the modified steel slag/rubber composites were subjected to thermo-oxidative aging treatment. The cross-linking density of the modified steel slag/rubber composites was determined by the equilibrium swelling method. The microstructure, weight loss rate and structural composition of the modified steel slag/rubber composites were tested by scanning electron microscopy (SEM), thermogravimetric analyzer (TGA), and Fourier transform infrared spectrometer (FTIR), respectively. The thermo-oxidative aging mechanism of the modified steel slag/rubber composites was expounded from the micro level. The results show that the cross-linked bond formation reaction is the main reaction in the surface of modified steel slag/rubber composites during the early thermal-oxidative aging. In the middle stage of thermo-oxidative aging, the aging effect has acted on the internal of modified steel slag/rubber composites, resulting in the fracture reaction rate of cross-linking bonds higher than that of forming a large number of broken cross-linking bonds. In the later stage of thermal-oxidative aging, many broken cross-linked bonds have been formed in the modified steel slag/rubber composites, resulting in the decrease of the fracture speed of the main chain and cross-linked bonds and the formation of cross-linked bonds is dominant. The modified steel slag powder with high SiO2 content as raw material is beneficial to form the structure of polymer macromolecular chain through carbon black network and improves the comprehensive performance, especially the physical and mechanical properties and hysteresis. Preparation of modified steel slag powder with electric furnace slag and air quenching slag (high Fe2O3 content) is beneficial to improving heat conduction performance.
2022 Vol. 42 (12): 3906-3912 [Abstract] ( 77 ) RICH HTML PDF (6426 KB)  ( 56 )
3913 XRF Analysis of the Whole-Area Component of the Oil Painting “Lady in Evening Dress”
XIANG Xiong-zhi1, ZHONG Rong-qu1, GAO Shi-han1, SU Xiao-wei1, CHE Da2*
DOI: 10.3964/j.issn.1000-0593(2022)12-3913-04
An XRF device has been adopted to study the whole-area componential distribution of the pigments in the oil painting “Lady in Evening Dress” created in 1955, and the material information of the pigments of this oil painting is analyzed. The major pigments used in this painting created in the middle of the 20th century are still mineral pigments. In addition, organic pigments were also applied in a small number of areas in the painting, and the pigments in some parts are non-standard oil paints prepared by the painter himself. Due to the artistic characteristics of the oil painting, the componential content of some areas with similar colors is the same; however, there are a few areas with large fluctuations. Therefore, the components of a specific area can be regarded as the unique fingerprint information to provide a basis for its identification.
2022 Vol. 42 (12): 3913-3916 [Abstract] ( 99 ) RICH HTML PDF (3810 KB)  ( 49 )
3917 The Effect of Electrode Polarity on Arc Plasma Spectral Characteristics of Self-Shielded Flux Cored Arc Welding
ZHANG Heng-ming1, SHI Yu1*, LI Chun-kai1, 2, 3, GU Yu-fen1, ZHU Ming1
DOI: 10.3964/j.issn.1000-0593(2022)12-3917-10
Owing to the wind resistance and excellent weld bead performance of self-shielded flux cored wire. It has been widely used in pipeline welding and the repair of large machinery in the field. Especially, electrode polarity has a great effect on the welding process. In order to study the influence mechanism of electrode polarity on arc plasma, a synchronous acquisition system was designed to scan each point in arc plasma space. Through the analysis of characteristic spectra lines, the Stark profile method was used to calculate the electron density, and the arc plasma temperature was calculated based on the Boltzmann mapping method. At the same time, the distribution characteristics of Al and Mg active elements were analyzed. The results show that electron density distribution, arc plasma temperature and active elements in the central area of the arc column were like the water drop along the negative direction of the Y axis in DCEN (direct current electrode negative). Under the DCEP (direct current electrode positive), the distribution characteristics of arc plasma electron density, arc temperature and active elements in the central area of the arc column were fingerlike. According to the principle of self-magnetic contraction, the electromagnetic force was less in the radial direction under DCEP, and the distribution of active elements was divergent. Under DCEP, the active elements are subjected to more electromagnetic force in the radial direction, and the shrinkage was serious. In addition, the arc plasma electron density and arc temperature in the center of the arc column were higher in DCEP than those under DCEN when the same electrical parameters were used. The distribution characteristics of electron density and ionization degree were the main factors affecting the arc plasma temperature. The arc plasma temperature and electron density were raised with the current and voltage increase under the same electrode polarity.
2022 Vol. 42 (12): 3917-3926 [Abstract] ( 110 ) RICH HTML PDF (5744 KB)  ( 57 )
3927 Research on Classification of Construction Waste Based on UAV Hyperspectral Image
XU Long-xin1, 2, 3, 4, SUN Yong-hua2, 3, 4*, WU Wen-huan1, ZOU Kai2, 3, 4, HE Shi-jun2, 3, 4, ZHAO Yuan-ming2, 3, 4, YE Miao2, 3, 4, ZHANG Xiao-han2, 3, 4
DOI: 10.3964/j.issn.1000-0593(2022)12-3927-08
The “siege” of construction waste has become the main problem of urban environmental pollution at this stage, severely restricting the sustainable development of the urban ecological environment. A good classification of construction waste is of great significance to protecting urban water resources, improving the utilization rate of urban land and improving residents’ quality of life. In this paper, the GaiaSky-mini 2 push-broom airborne specular imager (400~1 000 nm) is mounted on the DJ MATRICE M600Pro UAV, and a clean and windless test environment is selected to collect hyperspectral remote sensing images of the study area in real-time. The hyperspectral remote sensing images of the study area were preprocessed by geometric correction, image cropping and radiometric correction; The objects in the study were divided into two categories: background objects, including reed, wormwood, water, shadow, bare soil and asphalt road, and construction waste including white plastic, dust cloth, foundation residue and rubble sand. Based on pixel points, select the regions of interest (ROI) of various features as training samples, extract the spectral information of six background features and four types of construction waste in the study area, and make spectral curves based on different spectral feature differences between features. Select feature bands, calculate statistics through bands and select reasonable thresholds, use decision tree classification to separate background features and identify and extract construction waste in the study area. Target different background features and construction waste types were selected to verify the sample points and evaluate the accuracy of the separation results of background features and the identification results of construction waste.The results show that the overall recognition and classification accuracy of background features and construction waste is 85.91%, and the Kappa coefficient is 0.845. According to the established decision tree for the separation of background features, the classification effect of six background features is good, among which the producer accuracy of reed, asphalt road and bare soil is 95%, and the overall separation of background features is good. According to the established construction waste identification decision tree, the producer accuracy of dust cloth and rubble sand is 95%, and the producer accuracy of white plastic and foundation residue is 90%, which can accurately extract construction waste in the study area. This study shows that decision tree classification is realized in the unmanned aerial vehicle (UAV) hyperspectral remote sensing image recognition and extraction of the construction waste has good classification accuracy. Moreover, to verify the unscrewed aerial vehicle (UAV) hyperspectral remote sensing in the field of construction waste classification to extract the scientific nature and feasibility of construction waste classification recognition for future work has a specific practical significance.
2022 Vol. 42 (12): 3927-3934 [Abstract] ( 165 ) RICH HTML PDF (4509 KB)  ( 58 )
3935 A Combination of Hyperspectral Imaging With Two-Dimensional Correlation Spectroscopy for Monitoring the Hemicellulose Content in Lingwu Long Jujube
LI Yue1, LIU Gui-shan1*, FAN Nai-yun1*, HE Jian-guo1, LI Yan1, SUN You-rui1, PU Fang-ning2
DOI: 10.3964/j.issn.1000-0593(2022)12-3935-06
In this paper, hemicellulose content in Lingwu long jujube was determined by hyperspectral imaging and two-dimensional correlation spectroscopy (2D-COS) combined with stoichiometry. A quantitative bruising device was used to obtain the level 0,Ⅰ,Ⅱ,Ⅲ and Ⅳbruising model of jujube. Hyperspectral images and hemicellulose content of samples were obtained by hyperspectral and spectrophotometer, respectively. After the outliers were eliminated by the Monte Carlo cross-validation method, sample sets were divided into corrected and prediction sets by random sampling (RS),kennard-stone method (KS),sample set partitioning based on joint X-Y distances (SPXY) and 3∶1 partitioning method, respectively. The original spectrum of long jujube was preprocessed by baseline calibration, de-trending and normalising, and then a partial least square regression model was established to determine the optimal sample set division method and spectral pretreatment method.The spectral signal was extended to the second dimension by 2D-COS, and sensitive wavelength areas related to hemicellulose content were searched in the full spectral range. Competitive adaptive reweighted sampling (CARS), bootstrapping soft shrinkage (BOSS), interval variable iterative space shrinkage approach (iVISSA), variables combination population analysis (VCPA), iVISSA+BOSS, iVISSA+CARS and iVISSA+VCPA combination methods were used to extract characteristic wavelengths in the 2D-COS sensitive wavelength areas, and establish PLSR model based on characteristic wavelengths.The results showed that the PLSR model of full band established after the sample set was divided by 3∶1 and Baseline preprocessed was optimal. Therefore, the optimal sample set division method is 3∶1, and the spectral pretreatment method is Baseline, which isused for the subsequent characteristic wavelength modeling. Three autocorrelation peaks containing 401, 641 and 752 nm were found by 2D-COS analysis, respectively. The BOSS, CARS, iVISSA, VCPA, iVISSA+BOSS, iVISSA+CARS, iVISSA+VCPA methods were applied to selected 14, 26, 39, 12, 15, 22 and 11 corresponding characteristic wavelengths from 2D-COS spectra, accounting for 18.9%, 35.1%, 52.7%, 16.2%, 20.2%, 29.7%, 14.8% of the total wavelength, respectively. Comparedwith the PLSR model established by 2D-COS and characteristic waves, the 2D-COS+iVISSA-PLSR model had the best performance, with R2C=0.747 9, R2P=0.604 7, RMSEC=0.043 8, RMSEP=0.060 3. The results showed that hyperspectral imaging technology combined with 2D-COS could be used to detect hemicellulose content in Lingwu long jujube quickly.
2022 Vol. 42 (12): 3935-3940 [Abstract] ( 86 ) RICH HTML PDF (3407 KB)  ( 62 )
3941 Research on Fluorescence Retrieval Algorithm of Chlorophyll a Concentration in Nanyi Lake
DAI Qian-cheng1, XIE Yong1*, TAO Zui2, SHAO Wen1, PENG Fei-yu1, SU Yi1, YANG Bang-hui2
DOI: 10.3964/j.issn.1000-0593(2022)12-3941-07
Serving as a representative indicator for phytoplankton and water quality monitoring, Chlorophyll a (Chl-a) is of great significance to evaluating lake eutrophication level. In order to explore the hyperspectral characteristics of multi-temporal Chl-a concentration and to select the best inversion methods of Nanyi Lake, 98 sets of hyperspectral data and Chl-a concentration data were collected simultaneously from 8 navigational water experiments in Nanyi Lake from 2020 to 2021 were selected. To extract the characteristic bands most sensitive to Chl-a concentration, measured spectrum data of Nanyi Lake under different Chl-a concentration levels were analyzed, considering the influence of changes in water quality at different timeson the spectrum. Then, the peak and valley distance method, the fluorescence line height method, the Normalized peak area method and the peak area above valley method was introduced to jointly invert the concentration of Chl-a in Nanyi Lake, followed by inter-comparing the results of the abovementioned algorithms based on the 5-fold cross-validation. The results areas follows: (1) As the concentration of Chl-a increases, the absorption valley and fluorescence peak of Chl-a tend to deepen and increase, respectively. At the same time, the position of the fluorescence peak moves towards the infrared part with increasing Chl-a concentration. The obvious difference between peak and valley under different Chl-a concentration levels indicates spectrum before and after fluorescence peak is highly sensitive to the change of Chl-a concentration. (2) Validation results using a 5-fold cross-validation method show that the mean values of RMSE and MAPE extreme differences for each method for different groups of validation sets were 0.437 5 μg·L-1 and 28.27%. It can be seen that the sampling method of the modeling set and verification set will introduce evaluation error, which can effectively be reduced by the 5-fold cross-validation method, obtaining the pros and cons of each method to the greatest extent based on samples. (3) Best inversion results have been achieved by the peak area above valley method, which was proposed in combination with the horizontal tangent line at the minimum value of the absorption valley of Chl-a concentration, with R2=0.756 7, RMSE=1.653 1 μg·L-1, and MAPE=40.77%. Compared with the peak and valley distance method, the fluorescence line height method and the Normalized peak area method witnessed significant improvement in the inversion accuracy and provided a new idea for the inversion of chlorophyll concentration based on fluorescence.
2022 Vol. 42 (12): 3941-3947 [Abstract] ( 106 ) RICH HTML PDF (4178 KB)  ( 54 )
3948 Analysis of Fluorescence Fingerprint Characteristics of Water Quality in the Estuary of the Yangtze River
ZHANG Yi1, 3, LIU Chuan-yang2, 3, CHENG Cheng2, 3, SHEN Jian2, 3, CHAI Yi-di2, 3, LI Fang2, 3, CHEN Chong-jun1, MEI Juan1*, WU Jing2, 3*
DOI: 10.3964/j.issn.1000-0593(2022)12-3948-06
The technique of aqueous fluorescence fingerprint is an emerging technology in water pollution detection in recent years, which can reveal the composition information of the water organic matter and make up for the shortcomings of conventional water quality parameters. The coastwise area of Yangtze River Estuary is an industry-intensive belt in China with high regional urbanization and developed industry. In this basin, water quality change would directly affect economic development and human health. Therefore, it is of great significance to study the water quality change in the Yangtze River Estuary. Different variation trends appeared among pH, conductivity, NH3-N, CODMn, TP, TN and TOC in the study area. However, the four indicators of conductivity, TN, CODMn and TOC, still reflected that there was a certain pollution accumulation from upstream to downstream along the estuary section of the Yangtze River, especially at the downstream sampling points CJ-11 and CJ-12, which may be greatly affected by pollution sources. The results of conventional indicators and TOC could not directly reflect the pollution information, but could only reflect the increase of total pollution from upstream to downstream. Aqueous fluorescence fingerprint in the estuary of the Yangtze River mainly contained three fluorescence peaks, which were recorded as peak A, peak B and peak C. The [excitation wavelength and emission wavelength] were [275, 335] nm, [230, 345] nm and [250, 450] nm respectively. The synchronous variation trend of fluorescence intensity was between peak A and peak B with a high correlation, and the correlation coefficient reached 0.994 8, indicating that the two peaks were likely to come from the same pollution source. Through the similarity comparison algorithm of aqueous fluorescence fingerprints, the similarity of aqueous fluorescence fingerprints between the sampling points of the Yangtze River estuary (CJ-11 and CJ-12) and tributary of the estuary (HPJ-1) were 86% and 88%, respectively. Meanwhile, the similarity to CJ-10 was all less than 60%. It indicated that the change of aqueous fluorescence fingerprints (CJ-11 and CJ-12) in the lower reaches of the Yangtze River Estuary might be caused by the tributary HPJ, which flows into the Yangtze River Estuary. The similarity between the aqueous fluorescence fingerprint of tributary HPJ and the fluorescence fingerprint database of the printing and dyeing industry was approximately 90%, illustrating that the aqueous fluorescence fingerprint of tributary HPJ might be related to the discharge of local printing and dyeing wastewater. Based on the terrific linear positive correlation between the peak intensity, including peak A and peak B, and the concentration of NH3-N in the estuary of the Yangtze River (the correlation coefficient is 0. 8855), the aqueous fluorescence fingerprint technique could have the potential to indicate the concentration of NH3-N in the estuary of the Yangtze River. Aqueous fluorescence fingerprint technology could reveal the composition and source of organic matter in water and have important application value in pollution identification and water quality evaluation.
2022 Vol. 42 (12): 3948-3953 [Abstract] ( 133 ) RICH HTML PDF (3518 KB)  ( 50 )
3954 Research on Measuring Oil Film Thickness Based on Laser-Induced Water Raman Suppression Method
CHEN Yu-nan1, 2, 3, YANG Rui-fang1, 3*, ZHAO Nan-jing1, 3*, ZHU Wei1, 2, 3, CHEN Xiao-wei1, 2, 3, ZHANG Rui-qi1, 2, 3
DOI: 10.3964/j.issn.1000-0593(2022)12-3954-09
In this work, using a 266 nm laser as the excitation light source of the detection system, the water Raman spectra under the oil film of different thicknesses were obtained based on the laser-induced water Raman spectroscopy technology. The Gaussian function fitting method was used to correct the interference of the fluorescence spectrum on the Raman spectrum. And then, the oil film thickness inversion model could be established according to the water Raman suppression method combined with the nonlinear least square optimization algorithm. The results show that the six oils’ detectable oil film thickness range (92# gasoline, 0# diesel, Mobil oil 20w-40, Shell Helix10w-40, Lifeguard Fluid AG6 and crude oil) is from 0.19 to 379.22 μm. The average relative error of oil film thickness prediction ranges from 8.14% to 15.81% according to the water Raman spectrum-oil film thickness inversion model. This method can realize the measurement of micron-level oil film under laboratory conditions.
2022 Vol. 42 (12): 3954-3962 [Abstract] ( 108 ) RICH HTML PDF (4667 KB)  ( 53 )
3963 《光谱学与光谱分析》2022年(第42卷)总目次(第1~12期)
《光谱学与光谱分析》编辑部
2022 Vol. 42 (12): 3963-3984 [Abstract] ( 121 ) PDF (1046 KB)  ( 172 )