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2021 Vol. 41, No. 12
Published: 2021-12-01

 
3653 Recent Advances in Application of Near-Infrared Spectroscopy for Quality Detections of Grapes and Grape Products
ZHANG Jing1, 2, XU Yang1, JIANG Yan-wu1, ZHENG Cheng-yu2, ZHOU Jun1,2, HAN Chang-jie1*
DOI: 10.3964/j.issn.1000-0593(2021)12-3653-07
Grape, which is one of the fruits with the largest planting area globally, has rich nutritional value, medicinal value and economic value. According to consumers’ consumption demands and storage and transportation requirements for products, grapes were processed into common grape products, such as raisins, grape juice, wine, and grape seed oil. Based on the growing concerns over the quality and safety of foods and the demands for high-quality fruits and vegetables, how to quickly and effectively evaluate the quality of grapes and grape products has become urgent and imperative. With the development of non-destructive testing technology and equipment, near-infrared (NIR) spectroscopy technology has been gradually applied in quality testing of fruits, vegetables and other agricultural products due to its advantages of rapid, non-destructive, accurate, cost-effective, and convenient for online analysis. Nowadays, domestic and foreign scholars have combined the methods of chemometrics and data processing methods, such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), principal component regression (PCR), partial least squares regression (PLSR), support vector machine (SVM), and neural network (NN), etc., to determine the relationship between the general components (such as sugar, alcohol, acid, etc.) and specific components (such as pigments, tannins, aromatic substances, etc.) of grapes and grape products and effective spectral information non-destructively using NIR technology. The correlation between the content of quality components and spectral information has been explored to establish qualitative and quantitative analysis models for the main quality indicators of grapes and grape products, which provided some technical supports for the development of portable near-infrared inspection equipment for grape and online monitoring system for grape juice and wine brewing process. This review systematically summarized NIR technology's domestic and foreign application status in grapes, wine, grape juice and grape products in the past ten years for the first time, aiming to provide technical reference for the subsequent classification and identification and quality evaluation of grapes and grape products. Studies have shown that NIR technology could achieve multi-component detection and classification identification of grapes' complex physical and chemical components through quantitative and qualitative analysis. The research on the determination of physical and chemical properties and internal quality of grapes had made great progress, and the research and application of monitoring and qualitative identification of wine and grape juice are gradually increasing. They were gradually applied to the analysis of grape products, such as polyphenols and anthocyanins in grape skins, and the monitoring of the nutritional growth status of grapevines and grape leaves. This further confirmed that NIR technology is emerging as an effective detection tool for the quality evaluation of grape and grape products, improving the quality values of grapes and grape products and providing technical support for real-time and efficient production management have a broad range of applications. For the future research, to sense grape information during the process of growth, harvest, and post-harvest production, and realize quality control and on-line monitoring of grape and its products in the whole production process, studies are heading to investigate the correlation between the spectral information reflected by the detection data of different categories and the inherent quality of grapes and grape products, and build a robust prediction model with high accuracy based on the multi-source information fusion technology of vision, volatile, taste, and smell.
2021 Vol. 41 (12): 3653-3659 [Abstract] ( 240 ) RICH HTML PDF (1738 KB)  ( 489 )
3660 Terahertz Time-Domain Spectral Study of Paracetamol
ZHENG Zhuan-ping, LI Ai-dong, LI Chun-yan, DONG Jun
DOI: 10.3964/j.issn.1000-0593(2021)12-3660-05
Terahertz (THz) has laid a foundation for applying terahertz time-domain spectroscopy (THz TDS) in material detection, structure resolution, qualitative and quantitative analysis due to its unique characteristics of perspective, security and high spectral resolution. As the prevention or treatment of human diseases, drugs have always been closely related to people’s lives. However, recently the news of drugs endangering people’s health is often seen due to their quality problems. There are more and more calls for effective drug detection methods. THz-TDS, as a new non-destructive detection technology, has been gradually applied to drug detection. Thus, in this paper, we studied the THz absorption spectra of paracetamol using THz-TDS. Firstly, the THz spectra of paracetamol were measured in the range of 0.3~4.5 THz. Six characteristic absorption peaks and one shoulder peak were obtained. Specifically, these peaks are located at 1.46, 1.88, 2.11, 2.52, 2.95, 3.48 and 4.27 THz. Then, the simulation calculation based on isolated-molecule density functional theory was carried out. It was found that the intramolecular vibrations contributed to the experimental peaks. However, the -isolated-molecule simulation cannot interpret the measured peaks completely because intermolecular forces are not taken into account. Then the solid-state simulation was performed to interpret the measured peaks. Depending on the comparison between experimental and theoretical results, it was found that the absorption peaks of 1.46 and 2.11 THz are caused by the combination of intermolecular and intramolecular forces, the absorption peaks of 1.88, 2.52 and 2.95 THz mainly come from the intermolecular forces, and the absorption peaks of 3.48 and 4.27 THz primarily originate from the intramolecular forces. Finally, the THz absorption peaks of commercial paracetamol tablets in the range of 0.3~2.75 THz before and after the deterioration were measured. According to the comparison, it was found that the absorption peaks of commercial tablets and paracetamol samples were completely matched, indicating that the drug can be calibrated by the THz characteristic peak. Besides, the THz characteristic peaks in CNR measurement are all disappeared, implying that intermolecular forces mainly contribute the THz peaks of 1.46 and 2.11 THz. On the other hand, it also suggested that the corresponding THz absorption peaks of drugs would be changed with chemical properties. A new characteristic absorption peak at 0.69 THz emerged in the CNR measurement, indicating that the new intermolecular forces have been formed and the new physicochemical functions are produced after deterioration.
2021 Vol. 41 (12): 3660-3664 [Abstract] ( 223 ) RICH HTML PDF (2219 KB)  ( 105 )
3665 A Method of Terahertz Spectrum Material Identification Based on Wavelet Coefficient Graph
CHEN Yan-ling, CHENG Liang-lun*, WU Heng*, XU Li-min, HE Wei-jian, LI Feng
DOI: 10.3964/j.issn.1000-0593(2021)12-3665-06
The terahertz spectrum material identification method mainly relies on finding the different characteristics of the different spectra of the substance in the terahertz band to identify a specific substance. The methods of absorption peak extraction are commonly used spectral feature extraction algorithm. However, when the spectrum has no obvious characteristic absorption peaks or peak positions, and peaks are similar or difficult to distinguish, it is difficult to use the absorption peak characteristics to distinguish substances. Although machine learning and statistical learning techniques to identify terahertz spectra reduces the interference of absorption peaks, it often requires an artificial definition of features to cause classification errors. The deep learning method can automatically extract features, but it often requires complex preprocessing operations before recognition, and it is easy to lose some features in the feature extraction process, leading to classification errors. A method of terahertz spectrum identification based on wavelet coefficient graph and convolutional neural network is proposed. When using the terahertz spectrum signal for wavelet transformation, each row of the wavelet coefficient matrix has a corresponding relationship with the original spectrum signal. The absorption coefficient of the terahertz spectrum is expanded in the frequency domain through wavelet transformation to obtain different two-dimensional frequency-scale distribution diagrams, which are also known as wavelet coefficient maps. Then a convolutional neural network (CNN) is constructed to classify the wavelet coefficient graph, and the classification result of the terahertz spectrum material can be obtained. To verify the effectiveness of the proposed algorithm, the three sets of wavelet coefficient maps and the original spectral data were input into three different classifiers of CNN, Support Vector Machin (SVM), Multilayer Perceptron (MLP) respectively for comparison. From the experimental results, we can find the recognition of the algorithm in the three sets of data. The rates reach 100%, indicating that compared with traditional methods, the method in this paper can still accurately classify spectra without obvious characteristic absorption peaks, which proves the effectiveness of using convolutional neural networks to identify wavelet coefficient maps. To show the advantages of the proposed algorithm in this paper, we compared it with the wavelet ridge peak-finding recognition algorithm. The experimental results show that the proposed algorithm is hardly affected by peak frequency, peak position, and peak value. Whether to identify the starch without an absorption peak or to identify high similarity sucrose and glucose, a high recognition rate is achieved by the proposed algorithm, and the classification accuracy rate is up to 97.62%, which proves the superiority of the proposed algorithm. The proposed algorithm provides a new idea for identifying terahertz spectrum data and can also be extended to the identification of other spectrum substances.
2021 Vol. 41 (12): 3665-3670 [Abstract] ( 192 ) RICH HTML PDF (2201 KB)  ( 106 )
3671 Study on the Analysis Total As in Bentonite With Microwave Plasma Atomic Emission Spectrometry
LI Ai-yang1, FU Liang2*
DOI: 10.3964/j.issn.1000-0593(2021)12-3671-05
Bentonite is natural clay of layered phyllosilicates, composed of Si—O tetrahedral and Al—O octahedral sheets in the ratio of 2∶1. Its vesicular structure, chemical composition, exchangeable ion type and small crystal size result in unique properties including large chemically active surface area, high cation exchange capacity and high porosity. It is widely used in petrochemical, metallurgy, food, medicine, environmental protection and other fields. As an element, bentonite may pose a potential risk to human health during the development and utilization of bentonite. This paper determined the total As content in bentonite by microwave plasma atomic emission spectrometry (MP-AES) combined with multimode sample introduction system (MSIS). Nitric acid, hydrochloric acid and hydrofluoric acid were used for microwave digestion of bentonite. After adding perchloric acid, the digestion solution was dissolved at low temperature on an electric heating plate. 25% (w/v) potassium iodide solution was used as prereduction solution to reduce As(Ⅴ) to As(Ⅲ), and sodium borohydride/sodium hydroxide was used to transform As(Ⅲ) into gaseous hydride (AsH3) in the MSIS. By optimizing the best viewing position and nebulizer gas flow of MP-AES, the best analytical performance of As measurement is achieved. The interference of spectral lines overlapping was avoided by selecting 188.979 nm as the analytical wavelength of As. The background interference was corrected by the fast linear interference correction (FLIC) model. The matrix effect was corrected by selecting 261.542 nm as the wavelength of the internal standard element Lu. The limit of detection (LOD) of As is 0.41 μg·L-1. The analysis method was evaluated by the determination of national standard reference materials. The determination value of As was consistent with the certified value of standard reference material, and the relative standard deviation (RSD) was less than 2.80%, which verified the accuracy and precision of the method. The analysis of 12 bentonite samples from different places in China showed that the total As concentration was relatively low (the average content of As was between 3.51~12.6 mg·kg-1). Based on the limits set by the National Standard of the People’s Republic of China GB 2760—2014 food safety national standard food additive bentonite, the As content in all samples did not exceed the standard. MP-AES using atmospheric nitrogen as the plasma source reduces the operation cost, improves the analysis efficiency, and provides a reliable method for the quality control of bentonite. It has the advantages of safe and stable operation, simple and rapid operation and strong applicability.
2021 Vol. 41 (12): 3671-3675 [Abstract] ( 179 ) RICH HTML PDF (1754 KB)  ( 97 )
3676 Research on the Relationship Between Modulation Depth and Center of High Order Harmonic in TDLAS Wavelength Modulation Method
CHEN Hao1, 2, JU Yu3,HAN Li1
DOI: 10.3964/j.issn.1000-0593(2021)12-3676-06
Tunable Semiconductor Laser Spectroscopy (TDLAS) has been a rapidly developing spectral detection technology in recent years. Compared with other spectral detection technologies, TDLAS has the advantages of high sensitivity, high resolution, real-time monitoring, good portability and miniaturization, and has been widely used in the fields of industrial environmental protection, medical detection, meteorological monitoring and so on. The harmonic signal in the TDLAS wavelength modulation method is susceptible to air pressure. It is found that the influence of air pressure is the influence of modulation depth on the harmonic signal. Based on the principle of the harmonic method in TDLAS technology, the relationship between each harmonic and modulation depth is studied. The modulation depth of the current air pressure environment is calculated by calculating the center amplitude ratio of the fourth harmonic to the second harmonic. To adjust the amplitude of the modulation frequency so that the modulation depth is close to the optimal modulation depth value of each subharmonic, and the signal-to-noise ratio of the harmonic signal is optimal to improve the detection accuracy. The second and fourth harmonic signals under 10.2~177.9 kPa pressure were extracted by the TDLAS water vapor detection system. The simulation and experimental analysis were carried out. The simulation results show that the maximum relative error of the center amplitude ratio of the fourth harmonic to the second harmonic is -1.44%, and the maximum relative error of the modulation depth simulation to the theoretical value is 1.78%. The experimental results show that the modulation depth value is calculated based on the modulation depth function. When m=2.226 7, the measured central frequency amplitude of the second harmonic reaches the maximum value. When m=4.061 0, the measured central frequency amplitude of the fourth harmonic reaches the maximum value, which is consistent with the theoretical results. When 30.2 kPa<p<177.9 kPa, the relative error between the modulation depth and the pressure product MP value is small. The maximum relative error is not more than ±3.2%. It shows that the MP value under this pressure does not fluctuate much. The modulation depth value calculated by the modulation depth function approximates the actual value, which verifies the accuracy of the modulation depth function theory.
2021 Vol. 41 (12): 3676-3681 [Abstract] ( 216 ) RICH HTML PDF (3107 KB)  ( 89 )
3682 Effect of Soil Particle Size on Prediction of Soil Total Nitrogen Using Discrete Wavelength NIR Spectral Data
ZHOU Peng, WANG Wei-chao, YANG Wei*, JI Rong-hua, LI Min-zan
DOI: 10.3964/j.issn.1000-0593(2021)12-3682-06
Soil particle size is one recognized factor that cause serious interference to the Near-Infrared (NIR) spectroscopy. Generally, grinding and sieving soil are used to reduce soil particle size interference in the sample pre-processing stage. Mathematical methods such as the continuous spectrum derivative method are used to eliminate soil particle size interference in the data processing stage. However, for the discrete NIR spectral data, so far, there is still no effective methods to eliminate the interference of soil particle size. In this paper, the discrete NIR absorbance data of the soil samples are taken as the research object, to solve the problem of soil particle size interference elimination, and a soil particle size correction method is proposed. Firstly, establishing a soil particle size correction model. After drying the standard soil samples collected from the field to eliminate the interference of soil moisture, the soil samples are prepared. Finally, a total of 96 soil samples under four soil particle sizes (2.0, 0.9, 0.45, 0.2 mm) and six soil total nitrogen (TN) concentration levels (0, 0.04, 0.08, 0.12, 0.16 and 0.2 g·kg-1) were obtained. Calculating the standard deviation of four different particle sizes (each particle size contains 24 soil samples) and all 96 soil samples at each wavelength (850~2 500 nm), and the 1 361 nm and 1 870 nm were confirmed to be the characteristic wavebands of the soil particle size. The characteristic wavebands ratio was used as a single input variable to establish the SVM soil particle size classification model, and the overall classification accuracy of soil particle size was 93.8%. The results showed that it was feasible to use to classify the soil particle size. Based on the above results, a soil particle size correction method is proposed to eliminate the interference of soil particle size to the discrete NIR spectral data. Our team selected the six discrete NIR wavebands (1 070, 1 130, 1 245, 1 375, 1 550, 1 680 nm) using in the TN detector developed by our team to verify the soil particle size correction method proposed in this paper. The results showed that the corrected 2.0, 0.9, 0.45 mm and original soil absorbance were reduced by 62%, 74%, 111% and 61%, respectively. It showed that the soil particle size correction method could reduce the interference of soil particle size to discrete NIR spectral data. Finally, BPNN was used to establish the TN models with different absorbance data. The results showed that the R2v of the corrected soil absorbance model was improved by 25% compared with the original absorbance model. In summary, the soil particle size correction method proposed in this paper reduce the interference of the soil particle size on the discrete NIR spectral data, and improve the detection accuracy of the vehicle-mounted TN detector.
2021 Vol. 41 (12): 3682-3687 [Abstract] ( 144 ) RICH HTML PDF (2587 KB)  ( 89 )
3688 Rapid Determination of αs1-Casein and κ-Casein in Milk Based on Fourier Transform Infrared Spectroscopy
XIAO Shi-jie1, WANG Qiao-hua1, 2*, FAN Yi-kai3, LIU Rui3, RUAN Jian3, WEN Wan4, LI Ji-qi4, SHAO Huai-feng4, LIU Wei-hua5, ZHANG Shu-jun3*
DOI: 10.3964/j.issn.1000-0593(2021)12-3688-07
In order to find a rapid detection method for the content of two main allergens (αs1 and κ-casein) in milk, 211 Chinese Holstein milk samples from four provinces of Henan, Hubei, Ningxia and Inner Mongolia were selected as the research objects, and a non-destructive and rapid detection model of αs1 and κ-casein in milk was established based on Fourier transform mid infrared spectroscopy. Firstly, the original spectrum of milk was pre-analyzed, and it was found that strongly influenced the spectral absorption of milk. The two main absorption regions of water (1 597~1 712 and 3 024~3 680 cm-1) were analyzed. It was found that the absorption region of water (1 597~1 712 cm-1) overlapped with that of protein (1 558~1 705 cm-1)(amide Ⅰ). By comparing the effect of removing 1 597~1 712 cm-1, the spectral region of 925.92~3 005.382 cm-1 was selected as the sensitive band for subsequent analysis. The dimension of the selected full spectrum was reduced manually, and MCCV eliminated the abnormal samples. The support vector machine regression model (SVR) was established by using eight preprocessing algorithms, such as Savitzky-Golay convolution smoothing (S-G), standard normal variable (SNV). Meanwhile, three feature selection algorithms were combined, such as competitive adaptive reweighting algorithm (CARS) and information-free variable elimination algorithm (UVE). The results showed that for αs1- casein, the SVR model established by the combination of the first derivative and CARS algorithm was the best, the training set correlation coefficient (RC) and test set correlation coefficient (RP) were 0.882 7 and 0.899 8, respectively, and the training set root mean square error (RMSEC) and test set root mean square error (RMSEP) were 1.136 3 and 1.372 6, respectively. For κ-casein, the SVR model established by the combination of second-order difference and UVE algorithm was the best. The training set correlation coefficient (RC) and test set correlation coefficient (RP) were 0.914 7 and 0.887 7, respectively, and the training set root mean square error (RMSEC) and test set root mean square error (RMSEP) were 0.473 5 and 0.558 1, respectively. The results showed that the SVR model based on Fourier transform mid-infrared spectroscopy can be used to detect the content of allergens αs1 and κ-casein in milk, and the prediction effect was good. This study can make up for the blank of rapid and non-destructive detection of casein in milk by spectral technology in China.
2021 Vol. 41 (12): 3688-3694 [Abstract] ( 150 ) RICH HTML PDF (3610 KB)  ( 135 )
3695 A Nondestructive Identification Method of Producing Regions of Citrus Based on Near Infrared Spectroscopy
ZHANG Xin-xin1, LI Shang-ke1, LI Pao1, 2*, SHAN Yang2, JIANG Li-wen1, LIU Xia1
DOI: 10.3964/j.issn.1000-0593(2021)12-3695-06
Citrus is one of the popular fruits in the world. There are differences in internal quality and price of different-regions citrus. However, the appearance differences are small, and it is difficult for laypeople to identify by appearance. Methods such as DNA labeling and instrumental analysis are complex in operation and destructive to samples, which cannot achieve rapid and non-destructive analysis, affecting the secondary sales of products. Near-infrared spectroscopy is a fast and nondestructive detection method that can be used to identify different-regions agricultural products. Due to the large interference of citrus peel on the spectra, there is a lack of nondestructive identification of citrus origin. Besides, citrus is large. Therefore, it is necessary to optimize the spectral collection points. This paper proposed a new method for nondestructive identification of different-regions citrus based on near infrared spectroscopy and chemometrics. The diffuse reflectance spectra of 120 fertile oranges from Yunnan, Hunan, Wuming and Laibin of Guangxi were obtained by near-infrared spectroscopy. Single and combined spectral pretreatment was used to eliminate multiple interferences in the spectra. The principal component analysis method was used to reduce the data dimension, which was used as the input value. Combining with Fisher linear discriminant analysis method, the citrus origin identification model was obtained and compared with the principal component analysis model. In addition, the effects of different spectral collection locations (4 collection points along the equator, top and bottom) on the results were investigated. The results showed that the principal component analysis method combined with the optimized spectral pretreatment method could not accurately identify different-regions citrus, and the best identification accuracy was 5%. When the principal component analysis-Fisher linear discriminant analysis was used, the average spectra of 4 collection points along the equator combined with De-bias correction or multivariate scattering correction pretreatment method could achieve 100% identification analysis of different-regions citrus. Furthermore, the average spectra of 6 collection points combined with raw data could achieve 100% identification analysis of different-regions citrus. Therefore, by optimizing the spectral pretreatment methods and spectral collection points, the accurate identification model of different-regions citrus can be established by using principal component analysis-Fisher linear discriminant analysis method, which provides a new method for rapid identification of different-regions citrus.
2021 Vol. 41 (12): 3695-3700 [Abstract] ( 154 ) RICH HTML PDF (3840 KB)  ( 105 )
3701 Vis-NIR Spectra Discriminant of Pesticide Residues on the Hami Melon Surface by GADF and Multi-Scale CNN
YU Guo-wei1, MA Ben-xue1,2*, CHEN Jin-cheng1,3, DANG Fu-min4,5, LI Xiao-zhan1, LI Cong1, WANG Gang1
DOI: 10.3964/j.issn.1000-0593(2021)12-3701-07
Given the costly and destructive detection of pesticide residues on the Hami melon surface, the feasibility of visible/near-infrared (Vis/NIR) spectroscopy for the qualitative discriminant was assessed. In this study, Hami melon was taken as experimental samples. Two pesticides were taken as the research objects, including chlorothalonil and imidacloprid. Hami melon’s Vis/NIR spectra of Hami melon with no, chlorothalonil and imidacloprid residues were collected in the diffuse reflectance mode. Then the one-dimensional spectrum was transformed into a two-dimensional image by using gramian angular fields (GAF). The GAF image data set was constructed. A multi-scale convolutional neural network (CNN) architecture incorporatedan Inception module was developed, including aninput layer, three convolution layers, amerging layer, aflatten layer, two fully-connected layers, and an output layer. The confusion matrix result of the multi-scale CNN model suggested that the best method for expressing Vis/NIR spectral features was gramian angular difference fields (GADF) transformation. Moreover, two CNN models (AlexNet and VGG-16) and two machine learning models (support vector machine (SVM) and extreme learning machine (ELM)) were established toverify the proposed model performance. With higher average accuracy than SVM and ELM models, the CNN models had a better effect to identifying whether there were pesticide residues on the Hami melon surface. Compared with AlexNet and VGG-16 models, the proposed multi-scale CNN model had the best performance with the shortest training time of 14 s and the highest test accuracy of 98.33%.The multi-scale CNN structure can capture different level and scale features by using combinations of various small-size filters (1 1, 3 3 and 5 5) and stacking of parallel convolutions. The multi-scale deep feature fusion was carried out in the concatenation mode, which can improve the feature extraction ability of the CNN model. Compared with traditional CNN models with large depth, the model proposed in this study improved the discriminant accuracy while keeping the computational complexity constant. The overall research results reflected that GADF transformation combined with a multi-scale CNN model can effectively achieve the qualitative spectral data analysis. Vis/NIR spectroscopy can realize the qualitative discriminant of pesticide residues on the Hami melon surface. These findings can provide a reference for the rapid non-destructive detection of pesticide residues on the surface of other large melons and fruit.
2021 Vol. 41 (12): 3701-3707 [Abstract] ( 200 ) RICH HTML PDF (3638 KB)  ( 80 )
3708 Rapid Identification of Crude and Processed Polygonui Multiflori Radix With Mid-IR and Pattern Recognition
LIN Yan1, XIA Bo-hou1, LI Chun2, LIN Li-mei1, LI Ya-mei1*
DOI: 10.3964/j.issn.1000-0593(2021)12-3708-04
The roots of Polygonum multiflorum are traditional Chinese medicinal herbs in processed form or raw state. Raw Polygonum multiflorum can detoxify and loosen the bowel and relieves constipation, but processed Polygonum multiflorum can benefit blood, hair, strong muscles and bones, turbidness and lipid lowering. The raw and processed Polygonum multiflorum contain chemical components such as stilbene glycosides, anthraquinone and phospholipid, but their contents are different. The toxicity of raw Polygonum multiflorum decreased after processing. The chemical composition, efficacy and hepatotoxicity of raw and processed Polygonum multiflorum are different. It was easy to recognize the difference in appearance between raw and processed Polygonum multiflorum, but it was not easy to distinguish the power of raw and processed Polygonum multiflorum. Therefore, it is necessary to find a fast and simple method for distinguishing them. Mid-IR has the advantages of fast detection speed and nondestructive. Mid-IR has been widely used in the identification of traditional Chinese medicine. This paper aimsf to establish the fingerprint of the mid-infrared spectrum of raw and processed Polygonum multiflorum and identify them by orthogonal partial least-squares discriminant analysis (OPLS-DA). The chemical composition in 38 batches of raw and processed Polygonum multiflorum were determined by mid-IR of 4 000~700 cm-1, and the characteristic peaks of chemical composition were analyzed. OPLS-DA of simca13.0 software analyzed the data. The mid-infrared fingerprints of 38 batches of polygonum multiflorum from different sources were established, mainly including protein, nucleic acid, fatty acid, anthraquinone, stilbene glycosides and phospholipids. The peak shape and peak intensity of the infrared spectrum were analyzed, and the difference of peak shape between the raw and the processed radix aconitum was less, but the peak strength was different. OPLS-DA was used to establish the infrared spectral difference model of raw/processed Polygonum multiflorum. The results showed that the raw and processed Polygonum multiflorum could be well divided into two categories. The left was raw Polygonum multiflorum, and the right was processed Polygonum multiflorum. SPSS 13.0 statistical software was used to perform the t-test. Constituents with VIP>1 and p<0.05 (t-test) were considered statistically significant. The differential constituents of raw and processed Polygonum multiflorum were stilbene glycosides, anthraquinone and phospholipid. The results showed that the content of stilbene glycosides, anthraquinone and phospholipid were different in the raw and processed Polygonum multiflorum. The differential constituents of raw and processed Polygonum multiflorum found by mid-IR and pattern recognition is consistent with the literature reports. The results showed that this method was feasible. In this study, the medium infrared spectrum was successfully used for the rapid detection and overall quality evaluation of Polygonum multiflorum. Identifying Polygonum multiflorum with Mid-IR and pattern recognition could provide the basis for the quality control and rapid identification of Traditional Chinese medicine. The study can successfully identify theraw and processed Polygonum multiflorum by mid-IR and pattern recognition and provide a reference for quality control and quick identification of TCM.
2021 Vol. 41 (12): 3708-3711 [Abstract] ( 173 ) RICH HTML PDF (1478 KB)  ( 184 )
3712 A Near-Infrared TDLAS Online Detection Device for Dissolved Gas in Transformer Oil
CHEN Yang, DAI Jing-min*, WANG Zhen-tao, YANG Zong-ju
DOI: 10.3964/j.issn.1000-0593(2021)12-3712-05
Transformer insulating oil uses paraffin (CnH2n+2) as the main chemical component. Due to electric arc, discharge, overheating, moisture, etc., the chemical bonds are broken, and characteristic gases (methane, ethane, ethylene, acetylene, carbon dioxide, carbon monoxide) are generated during the long-term operation of the transformer. Therefore, Multi-component gas will be dissolved in transformer insulating oil, so an online detection device for multi-component gas is needed to ensure the normal operation of the transformer. According to the assembly requirements of the power industry, this paper conducts an online detection device of 6 types of fault characteristic gases based on near-infrared tunable diode laser absorption spectroscopy (TDLAS). Based on the near-infrared absorption bands of 6 types of fault characteristic gases, the device selects four near-infrared lasers at 1 580, 1 654, 1 626 and 1 530 nm respectively. It uses the time-division multiplexing technology of time-sharing scanning to achieve fast time-sharing of multi-component gases Sequentially detect and adopt wavelength modulation technology to eliminate the cross-interference of the background gas. The designed near-infrared TDALS multi-component gas detection device mainly detects methane (CH4), ethane (C2H6), ethylene (C2H4), acetylene (C2H2), carbon monoxide (CO) and carbon dioxide (CO2). The developed experimental device is verified with the traditional transformer oil dissolved gas method (transformer oil meteorological chromatographic measurement method), and the working condition stability test is carried out. The measurement range of acetylene concentration is 0.5~1 000 μL·L-1. When the range is less than 5 μL·L-1, the maximum measurement error is less than 0.8 μL·L-1. When the range is 5~1 000 μL·L-1, the maximum error is below 6 μL·L-1; the concentration measurement range of methane, ethane, and ethylene is 0.5~1 000 μL·L-1, the maximum measurement error is less than 6 ppm; The measurement ranges of CO and O2 are 25~5 000 and 25~15 000 μL·L-1, and their maximum measurement errors are below 2 and 20 μL·L-1 respectively. The designed near-infrared TDALS multi-component gas detection device can be used for online detection of dissolved gases in transformer oil, and the measurement meets the requirements of online detection. It can operate stably and adapt to harsh working conditions. The successful design of this on-line detection device provides practical experience for on-line measurement of dissolved gases in the detection of transformer oil.
2021 Vol. 41 (12): 3712-3716 [Abstract] ( 174 ) RICH HTML PDF (2745 KB)  ( 192 )
3717 IR Spectral Inversion of Methane Concentration and Emission Rate in Shale Gas Backflow
CHENG Xiao-xiao1, 2, LIU Jian-guo1, XU Liang1*, XU Han-yang1, JIN Ling1, XUE Ming3
DOI: 10.3964/j.issn.1000-0593(2021)12-3717-05
With the development of shale gas, the traditional handheld methane meter cannot cope with the complex shale gas production conditions due to the need for manual contact sampling. In view of the difficulty of real-time online monitoring of the emission concentration and rate of greenhouse gas methane in the process of shale gas development, we use the self-designed and built open Fourier transform infrared(FTIR) measurement system to measure the backflow liquid under various working conditions in the process of shale gas production. The FTIR resolution is 1 cm-1 and the optical path is 50 m. The light source passes directly above the backflow liquid and is received by the spectrometer. The measured infrared spectra are averaged several times, the hyperspectral mass is maintained, and the inverse calculation is carried out. The absorption cross-section calculated from the HITRAN database, considering the influence of environment and instruments, the measured temperature was modified, the appropriate methane absorption band was selected, and the absorption peak was superimposed with the absorption cross-section of water vapor to synthesize the standard spectrum. The methane concentration was calculated by fitting the measured spectrum with the standard spectrum using the least square method. The methane emission rate during shale gas exploitation was calculated according to the emission rate of the backflow fluid and combining the distance of the light path through the backflow pool and the infrared spectrum inversion concentration. The results show that spectral inversion concentration fluctuates obviously under different mining conditions. When the three separators were replaced, the methane concentration increased obviously. When the torch was lit, the methane concentration continued to be low, and the results of infrared spectrum inversion concentration were consistent with the methane emission in shale gas development and construction. The spectrum was averaged several times to improve the spectral quality, and methane in the backflow liquid was measured in a unit hour and continuous 80 hours. Within the unit hour, the methane concentration fluctuated within the range of 100~800 μmol·mol-1, and the variation trend was continuous and obvious. The emission rate of methane fluctuated between 50 and 300 m3·h-1. After 80 hour’ continuous measurement of the backflow fluid, the maximum methane concentration was 936.4 μmol·mol-1, and the maximum emission rate reached 535.1 m3·h-1. The lowest value was 36.82 μmol·mol-1, and its minimum emission rate was 18.63 m3·h-1. The result of inversion data shows that the backflow fluid is an irregular methane emission source in the development process of shale gas, and the change is very obvious in a short time. At the same time, the infrared spectrum inversion concentration was compared with the results of the traditional handheld methane measurement instrument, and the correlation coefficient was 0.743 6. Compared with the traditional handheld methane measurement instrument, the infrared spectral inversion method has the advantages of faster response, non-contact distance, real-time online measurement, etc.
2021 Vol. 41 (12): 3717-3721 [Abstract] ( 154 ) RICH HTML PDF (2575 KB)  ( 41 )
3722 Study on the Soot Order Degree and Functional Groups of Doping CH4 Into C2H4/H2 Diffusion Flame With Raman and FTIR
ZHU Yu-han, GU Ming-yan*, ZHU Ben-cheng, WU Jia-jia, LIN Yu-yu
DOI: 10.3964/j.issn.1000-0593(2021)12-3722-05
The soot formation characteristics of mixed diffusion flame of methane doping into ethylene/hydrogen were explored with Laser Confocal Raman spectrum (Raman) and Fourier Transform Infrared Reflection (FTIR), the soot order degree and the functional group’s distribution characteristic in the mixed flame with different proportions of methane doping were investigated. The influence of methane doping on soot formation of ethylene/hydrogen (30% hydrogen) laminar diffusion flame was studied. Results show that the order of soot in the range of flame height less than 4 cm was significantly reduced when the methane mixing ratio was 3% and 7% respectively, indicating that there is an obvious synergistic effect in this region; when the methane doping ratio increased by more than 10%, the synergistic effect disappeared and the order degree of soot increased. The influence of methane on the composition of soot functional groups was obvious. After being mixed with methane, the relative content of aliphatic functional groups increased overall. With the gradual increase of the doping ratio of methane, the relative content of CH2 reached the peak value. When the proportion of methane continued to increase, the relative content of CH2 decreased. The content of aromatic functional groups in soot decreased significantly with the increase of flame height. When mixed with 3% and 7% methane, the content of aromatic functional groups increased significantly at the flame height of 2 and 3 cm, respectively. When mixed with over 10% methane, the content of aromatic functional groups decreased, which showed that a small amount of methane doping provided a new way for CH3 and C3H3 generation. While CH3 and C3H3 increased, C2H4 and C2H2 decreased insignificantly, which promoted the formation of PAHs. Continuous increase of methane reduced the formation of C2H2 and the formation of PAHs accordingly; as the relative content of aromatic decreased, the formation of soot was reduced. This study reveals the interaction between methane and soot formation in ethylene / hydrogen laminar diffusion flame. There is a synergistic effect to promote soot growth at low a methane doping ratio, but it disappears at a high methane doping ratio.
2021 Vol. 41 (12): 3722-3726 [Abstract] ( 132 ) RICH HTML PDF (3069 KB)  ( 43 )
3727 Recognition of Different Parts of Wild Cordyceps Sinensis Based on Infrared Spectrum
CHEN Tao1, GUO Hui1, YUAN Man1, TAN Fu-yuan3*, LI Yi-zhou2*, LI Meng-long1
DOI: 10.3964/j.issn.1000-0593(2021)12-3727-06
Cordyceps Sinensis, a famous Chinese medicinal material, is favored due to its good medicinal value. Recently, investigations have focused on the study of its active ingredient content and pharmacological effects. However, scarce studies were reported on the identification of different parts of wild Cordyceps. This study is based on infrared spectroscopy data, combined with the analytical preponderance of chemometrics in multi-dimensional complex systems to classify and identify different parts of Cordyceps Sinensis. First, preprocessing methods, standard normal variation (SNV) and multiplicative scatter correction (MSC) were used on a total of 808 spectral data of five different parts of wild Cordyceps, including head of stroma(HS), middle of stroma(MS), head(HD), the middle larva body(ML) and the end larva body(EL). Then, competitive adaptive reweighted sampling (CARS) and variable combination population analysis (VCPA) were hired to select characteristic variables with representative significance. Ultimately, partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) were engaged for modeling and predictive analysis. Ten-fold cross-validation was used on the training set, and accuracy (Acc) was employedas the evaluation index. The results showed that the prediction accuracies of the PLS-DA model on the 10-fold cross-validation and independent test set on this data were 90.1% and 92.0%, respectively, while using the LDA model, the prediction accuracies reduced to 86.7% and 85.8%, respectively. In addition, the dimensions of the features can be effectively reduced from 3 601 to 669 and 420, respectively, when using CARS and VCPA feature selection methods, but keeping the prediction accuracies equivalent to that of all features. The selected wavenumbers 630, 625, 1 024, 1 028, 1 084, and 1 089 cm-1were related to mannitol in cordyceps, and 879 and 874 cm-1 were related polysaccharides in cordyceps. The Wilcoxon rank-sum test on the selected wavenumbers further showed significant differences between the five parts of Cordyceps. This study showed that chemometric methods combined with infrared spectroscopy could effectively identify different parts of Cordyceps Sinensis, thereby deepening the understanding of the formation of Cordyceps at the molecular level and providing a reference for the efficient use of different parts of Cordyceps.
2021 Vol. 41 (12): 3727-3732 [Abstract] ( 175 ) RICH HTML PDF (4383 KB)  ( 54 )
3733 Syntheses,Spectral Study and Antitumor Properties of Two Polyoxogermanotungstates
HUANG Xiao-hui1,2, HUANG Xiao-xing3, YING Shao-ming2, BI Wen-chao1, GAO Xiao-mei1, CHEN Yi-ping1*, SUN Yan-qiong1
DOI: 10.3964/j.issn.1000-0593(2021)12-3733-07
Two Keggin-type polyoxogermanotungstates [M(phen)3]2[GeW12O40]·2H2O (M=Zn (1), Co(2)) were synthesized by hydrothermal method. Compounds 1 and 2 are isomorphic, with the Pnma space group. 2D layers are linked by the hydrogen bonds between ligands and cluster anions. The layers were connected to form a three-dimensional supramolecule by strong molecular inter-atomic forces between adjacent phenanthroline. The compounds were characterized by XRD, FTIR, two-dimensional (2D) correlation infrared spectroscopy under magnetic and thermal perturbation, TG, etc. XRD showed that the spectrum was consistent with the simulation by single crystal structure data, and the main peaks were the same, indicating that the synthesized compound was relatively pure. The FTIR spectrum indicated that the wide absorption peak was νas(O—H)near 3 400 cm-1, the peak between 1 650 and 1 350 cm-1 was the skeleton stretching vibration peak of the aromatic ring, and there was four characteristic stretching vibrations of Keggin cluster anion skeleton in the range of 1 100 to 700 cm-1. Furthermore, the two-dimensional infrared correlation spectroscopy under 5~50 mT magnetic showed that the obvious difference between compound 1 and compound 2 in the range of 1 300~1 500 and 3 000~3 300 cm-1 may be caused by the transition metal (Zn(Ⅱ), Co(Ⅱ)) in the compounds which assigned to the C—C skeleton of phen and C—H…π hydrogen bond varies. TGA showed that the weight loss process could be divided into three stages. In the first stage, the free water was lost, and in the second, the coordinated phen was lost. At last, in the third stage, the framework of the tungsten oxide cluster began to collapse from 620 ℃. Results of the experiment on antitumor activities in vitro showed that two compounds inhibited five different human cancer cell lines (gastric cancer cell line, HGC-27 and SNU668; liver cancer cell line Huh7; and colon cancer cell line HCT116 and SW480) demonstrated dose dependency and selectivity. It was found that the IC50 of the two compounds against the five kinds of human tumor cells was less than 100 μmol·L-1. The synergistic effect of the organic ligand and cluster anions enhanced the antitumor activity of compounds 1 and 2 compared to unmodified POM. The two compounds showed the highest antitumor activity against colon cancer cell SW480 and the lowest inhibitory effect against gastric cancer cell SNU668. Although compounds 1 and 2 isomorphisms, the transition metal is different, lead to varying widely in their antitumor activity, compound 2 the inhibitory effect of five kinds of human tumor cells better than compound 1, the compound 2 for inhibition of colon cancer cells SW480 was 2.7 times than that of compound 1. The varied antitumor potencies of title compounds can provide direction for further research into the development of POM drugs.
2021 Vol. 41 (12): 3733-3739 [Abstract] ( 129 ) RICH HTML PDF (5696 KB)  ( 36 )
3740 Quantitative Detection of Agaricus Bisporus Freshness Based on VIS-NIR Spectroscopy
MA Hao1, 2, ZHANG Kai1, JI Jiang-tao1, 2*, JIN Xin1, 2, ZHAO Kai-xuan1, 2
DOI: 10.3964/j.issn.1000-0593(2021)12-3740-07
Agaricus bisporus is fragile and nutritious, which helps lower blood pressure, lowering blood lipids, reducing inflammation and protecting the liver. The freshness is one of the most important indicators to reflect the internal and external quality of Agaricus bisporus. At present, the freshness identification of Agaricus bisporus is mostly based on appearance quality (browning), and there is a lack of an accurate quantitative evaluation method. Therefore, in this research, a quantitative index for freshness detection was proposed based on storage days, which was used to analyze the freshness of Ag aricus bisporus with VIS-NIR spectroscopy technology. According to the different storage days, the samples of Agaricus bisporus were divided into 1 to 5 groups, each with 40 samples, and the near-infrared spectral data of each group was collected in turn using a fiber optic spectrometer. For the collected raw spectral data, firstly, the SG and MSC transform methods were selected to correct and eliminate the effects of spectral noise, baseline shift and light scattering. Moreover, the spectral band sranging from 399.81 to 999.81 nm were selected as the data processing range simultaneously.Then the method of principal components analysis (PCA) and successive projections algorithm (SPA) were respectively used to reducethe spectral dimensionalities and select the characteristic wavelengths. And the Extreme Learning Machine (ELM) classifier was established based on the spectral features. Since the initial parameters have a greater impact on the classification accuracy of the ELM model, the Particle Swarm Optimization (PSO) and Seagull Optimization Algorithm (SOA) was used to optimize the initial values of weight and threshold for ELM classifier to establish PSO-ELM and SOA-ELM classifiers. Finally, the full spectrum, the extracted principal components and the selected characteristic wavelengths {556.87, 445.51, 481.15, 885.10, 802.25, 720.90, 861.34, 909.79, 924.44, 873.17} nm were input into the classification model to establish the freshness detection model of Pleurotus ostreatus with different inputs and different classification models. The final test results show that when the ELM is the classification model, the prediction accuracy with full spectrum, principal component and characteristic wavelength as input is 75%,95% and 88% respectively; the training set accuracy of PSO-ELM and SOA-ELM classification model with SPA preferred characteristic wavelength as input is 96.25%,93.25%, and the accuracy of prediction set is 92.5%, 94%. It can be seen that the method of SPA was effective to reduce the redundant information of VIS-NIR spectra and accelerate the modeling. At the same time, the SOAwas better to optimize the initial parameters of the ELM classifier and significantly improve the classification accuracy, and the classification accuracy is 6.8% higher than that of the ELM model. Therefore, the freshness of Agaricus bisporus can be identified quickly and accurately by using spectral features. The research results provide a theoretical basis for the development of portable equipment for rapid non-destructive testing of the freshness of Agaricus bisporus.
2021 Vol. 41 (12): 3740-3746 [Abstract] ( 164 ) RICH HTML PDF (3828 KB)  ( 62 )
3747 A Method for Detecting Sucrose in Living Sugarcane With Visible-NIR Transmittance Spectroscopy
LÜ Xue-gang1, 2,LI Xiu-hua1, 2*,ZHANG Shi-min2,ZHANG Mu-qing1, JIANG Hong-tao1
DOI: 10.3964/j.issn.1000-0593(2021)12-3747-06
Sucrose content is an important indicator to measure the quality of sugarcane. It is of great significance to study the non-destructive detection method of sucrose content in living sugarcane based on the principle of spectroscopy. Sugarcane has a cylindrical shape with a hard skin and waxy surface. Different spectra detection angles and surface conditions will affect the modeling results to a certain extent. In addition, dimension reduction of characteristic wavelengths extraction is another factor that affects the model’s accuracy. In this study, the effect of different spectral measurement styles on the accuracy of the sucrose content prediction model was evaluated, an improved method for characteristic wavelengths extraction was proposed, and a sucrose prediction model was eventually constructed. A spectra acquisition platform was designed to obtain the transmittance spectra of sugarcane stalks. When acquiring the transmittance spectra, there were three different acquisition angles (120°, 150° and 180°) between the incident light and the measurement probe and two surface conditions (wax-not-removed and wax-removed).Six data sets of 123 samples were obtained in total. Firstly, PLS modeling result was used to evaluate the effect of different spectral pretreatment methods, including S-G smoothing, standard normal variation (SNV), multiplicative scatter correction (MSC), first derivation (FD), etc., and the result showed that SNV had the best comprehensive performance and was selected for further study.Then the effect of different measurement styles on the modeling of sucrose content was evaluated.The result found that: (1) regarding the effect of wax coverage,the spectral transmittance after wax-removed was high, the spectral difference among different collection sites of a single sample was lower, and the correlation with sucrose was much higher; (2) regarding the effect of the spectra acquisition angle, the transmittance decreased as the angle increased in a certain range; (3) the best modeling result was obtained (Rp=0.790 6, RMSEP=0.898 6) with the measurement style of wax-removed and 120° measurement angle. Finally, the interval partial least squares method (i-PLS), genetic algorithm (GA), ant colony algorithm (ACO) and an improved ant colony algorithm (VRC-ACO) based on full wavelengths PLS modeling variable regression coefficient proposed in this study were used to extract the characteristic wavelengths. The result showed that the number of characteristic wavelengths selected by the VRC-ACO algorithm, which had only ten wavelengths,was the least, yet the prediction accuracy was the best (Rp=0.861 6, 9.0% higher than the full-band model; RMSEP=0.746 6, 20.0% lower than the full-band model). This research provides theoretical support for the non-destructive detection of sugarcane and the development of corresponding sensors.
2021 Vol. 41 (12): 3747-3752 [Abstract] ( 229 ) RICH HTML PDF (2451 KB)  ( 69 )
3753 A Flexible Water Structure: Evidence From Raman Spectroscopy
HU Qing-cheng, ZHAO Hai-wen
DOI: 10.3964/j.issn.1000-0593(2021)12-3753-06
There are still large controversial ideas on water structure, mainly focused on classifying the hydrogen bonding configurations and their relative amounts. To understand water structure, the Raman spectra of H2O/D2O under different temperatures, H↔D isotopic substitution (IS) ratios and chlorine ion concentrations. For the OH stretch bands, the bandwidth is largely reduced, the main peak blue-shifts and the relative intensity between the shoulders and the main peak changes as the temperature rises from 253 to 753 K, indicating various hydrogen bonding configurations in water. Using Gaussian deconvolution, we assign these spectral features to the five main hydrogen-bonding configurations: two tetrahedral, single donor (SD), single hydrogen bonded water (SHW), and free water (FW). The tetrahedral configuration is the structural basis for the bending mode, librational+bending sum mode and intermolecular couplings. The estimated tetrahedralitlly indicates a more flexible water structure, and most of the structure configurations in water are nontetrahedral. The temperature increase leads to a water structure transition from the tetrahedral to a single donor, single hydrogen-bonded water and free water. IS can reduce the relative intensity of the lower-frequency shoulder to the main peak but intensify the higher-frequency shoulder, and especially, the higher-frequency shoulder turns into the main peak of the OH/OD bands for the VH2O/VD2O=1/4 or 4/1 water. These spectral features strongly support a multi-structure mode of water: IS promotes the transition of hydrogen bonding structures that the primary O—D…O(O—H…O) (non)tetrahedral hydrogen bonding configurations are decreased due to the O—D…O↔O—H…O transformation. The transition of structures in water with the temperature rise is further evidenced from the observation that the FW mode is intensified with IS so that it becomes the main peak of the OD/OH stretch band at higher temperatures. The multi-mode concept concerning the multi-structure body of water is sufficient to explain the OD/OH band features for H2O/D2O—NaCl solutions. Adding NaCl can greatly reduce the population of the tetrahedral configurations and transform them to SD and SHW at temperatures lower than 433 K, but above 513 K, NaCl slightly enhances the hydrogen bonding in water. The classification scheme on the structureal details in water derived from the Raman spectral features at wide condition ranges by this study can provide the theoretical basis for the spectroscopic and structural studies in the area of geologic aqueous fluids.
2021 Vol. 41 (12): 3753-3758 [Abstract] ( 277 ) RICH HTML PDF (4168 KB)  ( 117 )
3759 Rapid Detection of Levamisole Residue in Pork by Surface Enhanced Raman Spectroscopy
SHI Si-qian, YANG Fang-wei, YAO Wei-rong, YU Hang, XIE Yun-fei*
DOI: 10.3964/j.issn.1000-0593(2021)12-3759-06
Levamisole is a broad-spectrum anti-insect drug widely used to fight against nematodes in pigs, cattle and other livestock. Meanwhile, levamisole has a special immunomodulatory effect often used in anti-bacterial, anti-inflammatory, anti-virus and growth-promoting aspects in animal breeding. When it is used irrationally, it is easy to produce residues in poultry meat. At present, the common detection methods of levamisole are liquid chromatography and gas chromatography, which have the disadvantages of complex operation, long time consumption and high cost. Surface-enhanced Raman spectroscopy (SERS) has the advantages of fast analysis speed, high detection sensitivity and good specificity and has been widely used in the rapid detection of pesticide residues and animal residues in recent years. In order to realize the rapid detection of levamisole residues in pork, a rapid detection method of levamisole residues in pork by SERS was established. Through a single factor experiment, the optimal volume ratio of gold colloid to sample solution and the optimal integration time are determined to be 2∶1 and 20 s, respectively. By comparing the extraction effects of different extraction methods and solvents on the residual levamisole hydrochloride in pork, the extraction conditions of centrifugation after liquid-liquid extraction with n-hexane and redissolution with nitrogen blowing were determined. The theoretical spectrum of levamisole hydrochloride was calculated by B3LYP/6-311+G(d) basis set in density functional theory. After optimizing the molecular structure, the frequency and Raman spectrum was calculated. The theoretically calculated spectrum was in good agreement with the peaks of the solid spectrum and solution spectrum. According to theoretical calculation spectrum, solid spectrum and solution spectrum, SERS characteristic peaks of levamisole hydrochloride are determined, and vibration attribution is carried out. The characteristic peaks at 469, 627 and 969 cm-1 are obtained as characteristic quantitative peaks of levamisole hydrochloride, in which 469 cm-1 is C—S bond stretching vibration, 627 cm-1 is benzene ring C—C bending deformation vibration, and 969 cm-1 is imidazole ring in-plane bending and side chain skeleton vibration. Under the optimum experimental conditions, the standard curve of SERS signal and levamisole hydrochloride standard solution concentration was established, and the R2 values of linear equations were all above 0.9. The average recovery of levamisole hydrochloride with different spiked concentrations was 80.39%~95.94%, and RSD was 3.08%~6.20%. The method is stable and straight forward and can be used for rapid and accurate determination of levamisole residues in pork without complex pretreatment.
2021 Vol. 41 (12): 3759-3764 [Abstract] ( 158 ) RICH HTML PDF (2611 KB)  ( 59 )
3765 Quantitative Detection of Ascorbic Acid Additive in Flour Based on Raman Imaging Technology
WANG Xiao-bin1, 2, 3, ZHANG Xi1, GUAN Chen-zhi1, HONG Hua-xiu1, HUANG Shuang-gen2*, ZHAO Chun-jiang3
DOI: 10.3964/j.issn.1000-0593(2021)12-3765-06
Ascorbic acid is a common flour quality improver, which is used to improve the rheological properties of dough and the baking quality of bread. In this study, the mixed samples containing different concentrations of ascorbic acid in flour were used as the research object, and the detection, identification and quantitative analysis of ascorbic acid in flour were explored by Raman imaging technology. Raman images of flour, ascorbic acid and flour-ascorbic acid mixed samples were collected respectively, and the region of interest and spectral range were determined. The average Raman spectra of the mixed samples were analyzed based on the three Raman peaks (631, 1 128 and 1 658 cm-1) of the ascorbic acid Raman spectrum with higher intensity and different from the flour. The results showed that it could not effectively evaluate the content of ascorbic acid in flour. The Raman spectrum corresponding to each pixel in the image was analyzed to detect ascorbic acid effectively in flour. The partial least squares (PLS) model was established by using the Raman spectra of each pixel in the mixed sample image as the correction set and the linear combination spectra of flour average Raman spectra and ascorbic acid average Raman spectra as the verification set. The regression coefficients of the model were used to reconstruct the three-dimensional Raman image of the sample into a two-dimensional grayscale image. The threshold segmentation method was used to classify flour pixels and ascorbic acid pixels in the image, and a quantitative analysis model was established based on the classification results. The results showed that the PLS model’s highest and lowest regression coefficients correspond to the highest Raman peaks of ascorbic acid and flour respectively. After all regression coefficients were applied to Raman images and converted into grayscale images, the flour and ascorbic acid pixels were still difficult to recognise. The threshold segmentation method transforms the gray image into a binary image to classify flour pixels and ascorbic acid pixels, which realizes the effective detection of ascorbic acid in flour. The minimum detection concentration of ascorbic acid in flour in this study was determined to be 0.01% (100 mg·kg-1) by analyzing the number of ascorbic acid pixels identified in the corresponding sub-samples of mixed samples with different concentrations of ascorbic acid. There was a good linear relationship between ascorbic acid concentration in the mixed sample, and the identified ascorbic acid pixels in the image in the range of 0.01%~0.20%, and the coefficient of determination was 0.996 0. The research results provide method support for the quantitative detection of ascorbic acid additives in flour and provide technical reference for large-scale rapid screening.
2021 Vol. 41 (12): 3765-3770 [Abstract] ( 183 ) RICH HTML PDF (2464 KB)  ( 60 )
3771 Rapid Detection of Anthocyanin in Mulberry Based on Raman Spectroscopy
ZHANG Hui-jie, CAI Chong*, CUI Xu-hong, ZHANG Lei-lei
DOI: 10.3964/j.issn.1000-0593(2021)12-3771-05
Anthocyanin is a natural water-soluble flavonoid pigment with various medicinal values, which is widely found in mulberry and has become an important indicator for evaluating the quality of mulberry products. Because the implementation of the traditional detection methods could cost a lot of time and effort, it is significant to achieve the rapid detection of anthocyanin content in the development and utilization of mulberry products. In this study, anthocyanin in mulberry was taken as the research object to explore the relationship between anthocyanin and Raman spectral characteristics and the feasibility of quantitative detection of anthocyanin by Raman spectroscopy. The Raman spectra of mulberry and three kinds of anthocyanin were analyzed. The peak positions at 545, 634 and 737 cm-1 could be regarded as Raman characteristic peaks of anthocyanin in mulberry, to judge whether there was anthocyanin in mulberry, and the content of anthocyanin could be qualitatively determined as per the peak values. The spectroscopic data were preprocessed with the multiplicative scatter correction (MSC), baseline correction (airPLS), Normalized and the combined methods, and the best preprocessing method was selected by combining PLSR. It could be found that the best preprocessing method was airPLS+MSC+Normalized, and the PLSR model had a better effect. In the modeling set, the coefficient of determination is 0.97 and RMSEc is 2.74, while in the prediction set, the coefficient of determination is 0.82, and RMSEp is 13.69. Based on the spectra preprocessed with airPLS+MSC+Normalized, competitive adaptive reweighting sampling (CARS) was adopted to extract the characteristic wavelengths of the spectra. PLSR model and SVR model were established respectively regarding the selected wavelength variables as input variables, and the research into the predicting effects of both models was conducted. As per the results, the two models processed with CARS could predict the content of anthocyanin accurately, and the SVR model established with the screening of CARS variables had the best performance in the prediction accuracy, with the coefficient of the determination being 0.98 and RMSEc being 1.92 in the modeling set, and the coefficient of the determination being 0.94 and RMSEp being 4.70 in the prediction set. Therefore, the rapid and accurate prediction of anthocyanin content in mulberry could be achieved by Raman spectroscopy.
2021 Vol. 41 (12): 3771-3775 [Abstract] ( 178 ) RICH HTML PDF (2125 KB)  ( 65 )
3776 The Occurrence and Distribution of REE Minerals in Fluorite-Type Ores in Bayan Obo:Constraints From Raman Mapping
ZHANG Tie-zhu1, 2, ZHANG Yu-xuan2, 3, LIU Sai-yu2, 4, LI Hang-ren2, XU Wen-ce1, 2, ZHANG Jin-shan1*, OUYANG Shun-li2*, WU Nan-nan4
DOI: 10.3964/j.issn.1000-0593(2021)12-3776-06
Bayan Obo is famous for its rich mineral resources and huge reserves. Monazite is one of the main raw materials of rare earth, widely used in metallurgy, Military and chemical materials. The mineralogical characteristics of Bayan Obo have been studied. However, we need to understand the occurrence state of rare earth minerals at the present stage with the increased mining depth and the original minerals. Here, the Raman Mapping and Scanning Electron Microscope (SEM) and Energy Dispersive Spectrometer (EDS) were used to study the occurrence characteristics of minerals associated with REE in Bayan Obo. The EDS and energy spectrum analysis results showed that the minerals of the scanning area were composed of fluorite, barite, monazite, apatite, and iron-bearing minerals. Basis minerals were fluorite (CaF2) under the confocal microscopic diagram scanning by Raman Mapping analysis. The characteristic peaks of the Raman spectrum were generally appeared in (220~650 cm-1), which was slightly different from previously reported results. The larger grains were barite (BaSO4), typical sulfate minerals. The medium-size minerals were monazite (Ce, La, Nd) PO4, whereas the fine particles were apatite minerals (Ca5[PO4]3F). Monazite and apatite share the same phosphate root structure with different binding types of external metal cations and Raman peaks. Raman Mapping and EDS technology analyzed the relationships between occurrence characteristics and distribution of minerals. The monazite particles were in the form of plates or blocks and sizes about 50~120 μm. It was distributed between barite and apatite or between apatite and fluorite. The barite particles were coarsely distributed as bulk aggregates, and the size was 50~200 μm. It always grows closely with monazite particles. It was granular or massive, which was distributed similarly to the infection around in fluorite. A small amount of apatite and monazite was distributed metasomatism into irregular paragenesis. There were most of the monomer apatite distributed among around monazite and barite. The fluorites were the most abundant account for about 55% of minerals. There were co-associated with monazite, barite, apatite, and iron ore. It’s formation period that had been judged from the occurrence state should be earlier than others. It was multi-genesis and complicated associated minerals in the Bayan Obo deposit. EDS can analyze the basic relationship of mineralogy, but the energy spectra of monazite and barite partly coincide. The reason was that the excitation energy lineages of Ba and S are too close to the rare earth elements Ce, La, and Nd, and the energy spectral low resolution. Raman mapping imaging technology has the advantages of simplicity and reliability in mineral identification, making up for EDS misjudgment analysis. Raman mapping can provide a new identification idea for Mineralogical analysis of minerals and provide a reference Raman spectrum for mineral identification of Bayan Obo.
2021 Vol. 41 (12): 3776-3781 [Abstract] ( 177 ) RICH HTML PDF (4458 KB)  ( 61 )
3782 Design and Batchable Fabrication of High Performance 3D Nanostructure SERS Chips and Their Applications to Trace Mercury Ions Detection
HUANG Hui1, 2, TIAN Yi2, ZHANG Meng-die1, 2, XU Tao-ran2, MU Da1*, CHEN Pei-pei2, 3*, CHU Wei-guo2, 3*
DOI: 10.3964/j.issn.1000-0593(2021)12-3782-09
Surface-enhanced Raman scattering (SERS) is a powerful technique for detecting trace heavy metal ions due to its non-destructiveness, high sensitivity and fast acquirement of the signal. Localized surface plasmon resonance (LSPR) is well known to enhance the electromagnetic field by reducing the gaps between plasmonic metal nanoparticles, which could greatly increase SERS performance. Recently, a new emerging route is more attractive, which can effectively enhance SERS by boosting the coupling between LSPR and surface plasmon polariton (SPP) through designing specific 3D nanostructures. Herein, we proposed a novel configuration of high-performance SERS chips with 3D periodic metal/dielectrics nanostructures, which can be fabricated in large areas and batches using nanoimprint lithography (NIL) based on a new concept of the stress-homogenized dual-layer template. The SERS chips fabricated using low-cost NIL were successfully applied to detection trace mercury (Hg) ions. The combination of theory and experiments allows a methodology for designing stress-homogenized nanoimprinting templates with vertical configuration and horizontal dimension as the key design parameters. The simulation of micro-/nano-scale interfacial stress evolution during NIL using finite element analysis (FEA) showed the formation of both high and low-stress sub-areas on a patterned template by introducing an extra structure layer normal to the template. Compared to the extra-layer free template, the area with high stress is about 72% that of the patterned area, accompanied by 17% improvement in stress distribution uniformity. A stress area as low as about 28% surrounding the patterned structure is also favorable for demolding during NIL. The horizontal dimension of the template was also revealed to have a dramatic effect on the micro-/nano-scale interfacial stress in whichreducing the size of the template would increase the overall interface stress significantly by one to two orders of magnitude. Various nanoimprint templates with different configurations and dimensions were employed to successfully nanoimprint large area and uniform dielectric nanostructures, demonstrating the stress homogenization proposed based on the simulations. We combined Au nanoparticles, and nanoimprint lithography resists to form the 3D periodic nanostructures of SERS chips. The SERS chips realized the detection limit for Rhodamine 6G (R6G) model molecule of 2.08×10-12 mol·L-1, an enhancement factor (EF) of up to 3×108, and a uniformity of 8.07%. Furthermore, the SERS chips were also successfully applied to detect trace Hg ions as low as 5.0×10-11 mol·L-1 (10 ppt) with a good linear relationship (R2=0.966) ranging from 5.0×10-11 to 5.0×10-5 mol·L-1, which is quite prominent for Hg ions detection. The SERS chips designed and fabricated here can provide a solution to trace detection of heavy metal ions and other trace substances. The concept of stress-homogenized dual-layer template proposed in this work makes it possible to fabricate high-performance, uniform and low-cost SERS chips with 3D nanostructures. The roadmap proposed in this study will undoubtedly promote greatly practical applications of SERS probes from the perspectives of both design and low-cost and batchable fabrication.
2021 Vol. 41 (12): 3782-3790 [Abstract] ( 186 ) RICH HTML PDF (5948 KB)  ( 48 )
3791 Fluorescence Excitation Emission Matrix Properties of the Effluents From the Wastewater Treatment Plants in Jiangyin City, Jiangsu Province
CHENG Cheng1,2,3, QIAN Yu-ting4, HUANG Zhen-rong4, JIANG Jing4, SHAO Li4, WANG Zhong-xi4, LÜ Wei-ming4, WU Jing1,2,3*
DOI: 10.3964/j.issn.1000-0593(2021)12-3791-06
Textile printing and dyeing is one of the major industrial sectors in Jiangyin City, Jiangsu Province and textile wastewater was received by many wastewater treatment plants (WWTPs) in Jiangyin City. Dissolved organic matter (DOM) was the major removal target during the wastewater treatment process. Due to fast and convenient measurement, high sensitivity and moderate selectivity, excitation-emission matrix (EEM) has been extensively used to characterize DOM in various water bodies. In this study, the DOM components of the effluents from the main WWTPs in Jiangyin were investigated by EEM. The SUV254 values of the effluents were 1.42~5.71 L·(mg·m)-1, which indicated higher aromaticity than treated municipal wastewater. The effluents generally exhibited two protein-like fluorophores. The protein-like fluorescence intensity per unit of DOC of the effluents from the WWTPs employing biological or “biological + coagulation” process (>2.86 R. U.·L·mg-1) was much higher than that of the effluents from the WWTPs with strong oxidation process (<0.60 R. U.·L·mg-1), which was ascribed to the decomposition of aromatic structure of protein-like fluorescent DOM by strong oxidation. The effluents from about 33% of the WWTPs showed humic-like fluorescence with a higher humification index than the effluents from the other WWTPs. Two parallel factor analysis obtained two protein-like components with the peaks at 225, 280/320 nm and 230, 285/340 nm and one humic-like component with the peak at 240/415 nm. These protein-like fluorophores could be mainly ascribed to Dispersant MF, a kind of common commercial dye additives to improve the dispersion performance of vat and disperse dyes. The main components of Dispersant MF are the formaldehyde condensates of sulfonated washing oil, which are poorly biodegradable. The findings of this work contributed to a profound understanding of the DOM composition in the effluents from the WWTPs in Jiangyin, which was significant to optimization of the treatment process and development of advanced treatment process.
2021 Vol. 41 (12): 3791-3796 [Abstract] ( 167 ) RICH HTML PDF (3787 KB)  ( 51 )
3797 BRRDF Simulation Research on Multiple Detection Parameters of Water-in-Oil Emulsion of Oil Spill on the Sea Surface
ZHANG Xiao-dan1, KONG De-ming2*, YUAN Li1, KONG De-han3, KONG Ling-fu1
DOI: 10.3964/j.issn.1000-0593(2021)12-3797-05
Oil spill pollution on the sea surface is one of the most common pollutions, which usually exists on the sea surface in different weathering states, such as oil film in the unemulsified stage, oil-in-water and water-in-oil in the emulsified stage. Therefore, rapid and accurate monitoring of oil spill information on the sea surface, and identification, classification and quantitative assessment of oil spill pollution at different stages are of great significance to the rapid control of marine pollution and the restoration of the ecological environment. Laser induced fluorescence (LIF) is currently one of the most effective technologies for remote sensing detection of the sea surfaces. The bidirectional reflectance and reradiation distribution function (BRRDF) characterizes the fluorescence properties of the target by describing the fluorescence distribution of the stimulated emission. At present, the fluorescence characteristics of water-in-oil emulsion in the emulsification stage have not been studied except oil film in the unemulsified stage and oil-in-water in the emulsification stage based on LIF detection technology. Because of this, the optical parameters of water-in-oil emulsion are obtained using the Mie scattering theory. The Monte Carlo photon transmission model of water-in-oil emulsion is established to carry out BRRDF research. The variation of fBRRDFcosθrcosθi (the zenith angle of fluorescence emission is θr, and the zenith angle of laser incidence is θi) of water-in-oil emulsion under the parameters of oil content, incident-receiving angle, and thickness is discussed and analyzed. The experimental data of the fluorescence spectrum are compared with the simulation. The results show that the value of fBRRDFcosθrcosθi decreases with the increase of the oil content of the emulsion (the oil content of the surface emulsion of sea-water) and has a consistent trend with the spectral data collected by the experiment, which provides the basis for inferring the oil content of water-in-oil emulsion based on LIF technology. The value of fBRRDFcosθrcosθi first stabilizes with the increase of θi and decreases rapidly when θi>65°, and gradually decreases with the increase of θr, which is consistent with the trend of spectral data collected by experiments. This trend indicates that the incident angle of the laser should not exceed 65°, and the maximum optical signal can be received perpendicular to the sea surface when LIF technology is used to detect the water-in-oil emulsion on the sea surface. The value of fBRRDFcosθrcosθi rises first and then becomes stable with the increase of emulsion thickness, which indicates that fBRRDFcosθrcosθi can be used to evaluate the minimum thickness of water-in-oil emulsion. The research content of this paper provides theoretical and technical support for detecting oil spills on the sea surface based on LIF technology.
2021 Vol. 41 (12): 3797-3801 [Abstract] ( 123 ) RICH HTML PDF (2894 KB)  ( 43 )
3802 Fluorescence Imaging and Chiral Specific Biological Recognition
FEI Xue-ning*, ZHENG Yuan-jie, GU Ying-chun, LI Guang-min, ZHAO Hong-bin, ZHANG Bao-lian
DOI: 10.3964/j.issn.1000-0593(2021)12-3802-06
Cancer is one of the major diseases threatening human health. Early detection and early treatment are important means to reduce cancer mortality. At present, in many ways of cancer recognition, fluorescence detection has attracted more and more attention due to its advantages of non-invasive, fast detection and visualization. In this paper, we reviewed the new progress of fluorescent probe targeted tumour recognition and introduced and analyzed the research progress of folate (FA) and folate receptor (FR) mediated fluorescence probe targeting. Folate receptor (FR) is a specific substance over expressed on the surface of cancer cells. Using the characteristic of specific binding between folate (FA) and folate receptor, folic acid can modify the fluorescent probe molecules to give the fluorescent probe the ability to recognize cancer cells. There are four subtypes of folate receptor (FRα, FRβ, FRγ and FRδ). The former two FRα and FRβ are highly expressed on the surface of cancer cells and inflammatory macrophages, respectively. FRα and FRβ have about 70% homology. Both of them can bind to folate, which makes it difficult for fluorescent probes to distinguish cancer cells from inflammatory macrophages in the process of biological recognition. It is difficult to distinguish folate receptor subtypes by modified fluorescent probes, which leads to confusion between cancer cells and inflammatory macrophages. The chiral characteristics of the two folate receptor subtypes are analyzed: FRα and FRβ is mainly located in three untranslated regions. Three kinds of amino acids with different chiral characteristics form a triangular cavity to bind folate molecules. The three kinds of amino acids fixed on the nodes of amino acid accumulation form a regional “chiral space” with different chiral characteristics. The structures of FRα and FRβare different for different ligands. Based on the “chiral space” differences of folate receptor subtypes, the possibility of constructing fluorescent and chiral recognition probes is discussed. It is expected that with the help of spectral imaging, the two folate receptor subtypes can be distinguished by the recognition of amino acids by chiral fluorescent probes, and the recognition problem of tumor cells and inflammatory macrophages can be realized to improve the recognition ability of cancer cells in this paper, the principle of amino acid recognition by chiral fluorescent probes and the progress of structural optimization design are introduced. In recent years, the research of chiral quantum dots on different enantiomers of amino acids has attracted much attention. This paper summarises the nature of chiral generation of inorganic chiral quantum dots and the recognition of amino acid enantiomers. Finally, the prospect of fluorescent probes and chiral recognition is discussed.
2021 Vol. 41 (12): 3802-3807 [Abstract] ( 129 ) RICH HTML PDF (2888 KB)  ( 46 )
3808 X-Ray Fluorescence Spectroscopy Combined With SEM-EDS Analysis to Glaze Composition of Glazed Tiles in Yuan Dynasty
SHI Ruo-yu1, WEN Rui1*, GAO Xiang2, WANG Wen-xuan1, BAO Li-ge3, ZHAO Xue-feng4, LI Zi-xuan1, CAO Kun1, XIAO Wei1, LI Yu-long1
DOI: 10.3964/j.issn.1000-0593(2021)12-3808-07
The glazed tile production technology of the Yuan Dynasty was inherited from the Song and Liao dynasties, which had an important impact on Ming and Qing Dynasties. It was a transitional period for the development of glazed tile production technology in China. The glazed tiles used in Shangdu and Zhongdu of the Yuan Dynasty represent the highest glazed tile production technology in the early and middle Yuan Dynasty. In order to explore the manufacturing technology and process characteristics of glazed tiles in different periods of Yuan Dynasty, this paper analyzes the composition of glaze layer of glazed tiles unearthed from the Yuanshangdu and the Yuanzhongdu by EDXRF and SEM-EDS, combined with archaeological data and related literature.The results show that the glaze layer of the Yuanshangdu and the Yuanzhongdu includes glaze and clay, and the thickness of clay is between 122 and 260 μm. The glaze of Shangdu Malachite blue glazed tile belongs to the PbO-K2O-SiO2 system, which is similar to that of Yuandu Malachite a blue glaze. The raw materials are composed of quartz, nitrate, lead powder and copper powder. The structure of blue glazed tile is compact, and the content of Cao and SiO2 is more than 20%. The raw materials may be anorthite and clay, which should be a part of the glaze. Shangdu green glaze and Zhongdu green glaze yellow glaze tile glaze are both Pbo-SiO2 systems. The basic raw materials are quartz, lead powder, and colorants are copper and iron respectively. The formula of green glaze in the Yuanshangdu is close to that of the Northern Song Dynasty, and the formula of glaze is also in line with the records of “Yingzao Fashi”, but the proportion of lead is gradually reduced to obtain lighter glaze color which is stable in the middle of Yuan Dynasty. The Pb/Si of yellow glazed tile in the Yuanzhongdu is similar to that of the Yuandadu, and the formula is gradually fixed in the exploration during middle period of Yuan Dynasty which is the basis of improving glaze during middle period of Ming Dynasty. All the glazed tiles’ glaze is closely combined with body and slip. The clay has a high content of Ca and a thin thickness. It is likely to be Ca(OH)2. The craftsman can not only save the cost but also improve the product quality when applying the clay. The three kinds of glaze colors belong to PbO-K2O-SiO2 and PbO-SiO2 systems respectively, with obvious differences in composition materials. They are all used in architectural decoration, which greatly enriches the glaze color of the glass. The application of make-up clay in glass technology is also an innovation. Energy-dispersive X-ray fluorescence spectroscopy has the characteristics of fast analysis and stable state, which has been widely used in the research of glazed tile. The research results of glazed tile in Shangdu and Zhongdu of Yuan Dynasty supplement the research data of glazed tile in the Yuan Dynasty, and provide some scientific basis for exploring the development history of glazed tile technology in China.
2021 Vol. 41 (12): 3808-3814 [Abstract] ( 140 ) RICH HTML PDF (2796 KB)  ( 43 )
3815 Study on Sample Preparation Method of Plant Powder Samples for Total Reflection X-Ray Fluorescence Analysis
JIA Wen-bao1, TANG Xin-ru1, ZHANG Xin-lei1, SHAO Jin-fa2, XIONG Gen-chao1, LING Yong-sheng1, HEI Dai-qian3, SHAN Qing1*
DOI: 10.3964/j.issn.1000-0593(2021)12-3815-07
Total reflection X-ray fluorescence spectrometry (TXRF) is a widely used, economical and rapid method for analysing trace elements. With the rapid development of machine automation in modern science and technology, sample preparation has become a key issue in TXRF quantitative analysis. In this paper, tea powder was used as the analysis object, the influence of dispersant, sample quantity and particle size on the sample preparation, repeatability and measurement accuracy of powder suspension samples in the process of TXRF analysis was discussed. The results showed that: (1) Global precision of the TXRF method was tested by analyzing five independent replicates of tea powder samples with particle size larger than 180 mesh. The stability of the instrument and the uncertainty in the sample preparation process were analyzed by error propagation. The results show that the uncertainty associated with the sample preparation step has a significant contribution (>60%) to the global precision of the obtained results regardless of the element and concentration range. Therefore sample preparation is the main source of analysis error;(2) By dispersing tea powder samples with a particle size range larger than 180 mesh into 1% Triton X-100 and deionized water, the effect on the dispersant was studied. Compared with the 1% Triton X-100 nonionic surfactant, deionized water has better repeatability. Its RSD was between 2.45%~11.64%, which is more suitable for dispersing tea powder samples with a particle size larger than 180 mesh, and could make the quantitative determination of medium and high atomic number elements more accurate; (3) The influence of the sample quantity was evaluated by adding powder samples of different masses in 5 mL deionized water. If the sample quantity is too low, the sample preparation repeatability will be poor, and if the sample quantity is too high, the sample film thickness will exceed the measured thickness of the X-ray, which may no longer be in the total reflection condition. 20 mg/5 mL is a suitable sample quantity for plant powder samples; (4) Through the measurement and analysis of powder samples in 7 types of particle size ranges, the influence of particle size on the measurement results was studied. The counts increased with the decrease of particle size when the particle size is less than 180 mesh; the precision increase with the decrease of particle size when the particle size is less than 200 mesh; the particle size has no significant effect on the accuracy except Mn; the uncertainty decreased rapidly in the range of 80~200 mesh, and less than 10% when the particle size more than 200 mesh. It is suggested that the particle size range should be between 200 and 300 mesh in the sample preparation process. The research results can provide an effective reference for the sample preparation method of plant powder samples.
2021 Vol. 41 (12): 3815-3821 [Abstract] ( 173 ) RICH HTML PDF (3917 KB)  ( 58 )
3822 Determination of 5 Kinds of Selenium Species in Livestock and Poultry Meat With Ion Pair Reversed Phase Liquid Chromatography-Atomic Fluorescence Spectrometry
WEI Yi-hua1, HUANG Qing-qing2, ZHANG Jin-yan1*, QIU Su-yan1, 3, TU Tian-hua1, YUAN Lin-feng1, DAI Ting-can1, ZHANG Biao-jin1, LI Wei-hong1, YAN Han1
DOI: 10.3964/j.issn.1000-0593(2021)12-3822-06
A method of ion-pair reversed phased liquid chromatography-ultraviolet (IP-RP-HPLC)-hydride generation-atomic fluorescence spectrometry (AFS) was established to determine the contents of selenocystine, methylselenocysteine, selenotmethionine, selenateand selenite in livestock and poultry meat. Organic Se species contents in samples were extracted by trypsin and protease (XIV, pronase), and inorganic Se species contents in samples were extracted with iodine acetamide solution and water incubated at 55 ℃ with shaking at 200 r·min-1for 20 h. The extraction solution of samples was centrifuged at high speedand then centrifuged with microsep for purification. C18 separated the solution of samples reversed phase column by using 30 mmol·L-1diammonium hydrogen phosphate, 0.5 mmol·L-1tetrabutyl-ammonium bromide and 5% (V/V) methanol as moblie phase. The pH of the mobile phase was adjusted to 6.0 by 20% (V/V) formic acid. IP-RP-HPLC-AFS determined the contents of five Se species in samples solution. The impurities are qualitatively determined by contrasting with the standard sample and quantitatively determined by calculating the peak areas. Selenocystine, methylselenocysteine, selenotmethionine, selenate and selenite had good linearities in the range of 5~200 μg·L-1, and the correlation coefficients were all greater than 0.999, the detection limits of five Se species were 0.89, 0.78, 0.55, 0.94 and 0.70 μg·L-1, respectively. There coveries were between 76.8%~109%, the within-run precisions and between-run precisions were 2.7%~6.8% and 3.5%~12.3% respectively. The proposed method has the advantages of rapid, simple, high sensitivity and high accuracy, and it is suitable for Se species analysis in livestock and poultry meat samples.
2021 Vol. 41 (12): 3822-3827 [Abstract] ( 133 ) RICH HTML PDF (1686 KB)  ( 36 )
3828 Inversion of Wheat Tiller Density Based on Visible-Band Images of Drone
DU Meng-meng1, Ali Roshanianfard2, LIU Ying-chao3
DOI: 10.3964/j.issn.1000-0593(2021)12-3828-09
Nitrogen topdressing is a vital agrotechnical measure to boost tillering process and improve the population structure of wheat stalks. However, uniform nitrogen topdressing is apt to cause excessive application and low agronomic efficiency of nitrogen fertilizer. However, variable-rate fertilization can solve the contradiction between individual development and formation of population structure of wheat stalks, by decreasing the application of nitrogen fertilizer according to the actual growing status of wheat stalks in the field. The key technology to improve the population structure of wheat stalks using variable-rate nitrogen topdressing is to accurately obtain the information of spatial variations of wheat stalk numbers at field scale. Thus, with the objectives of fertilizer reduction and yield increasing, this research studies wheat growth status in the tillering stage to invert and regulate population densities of wheat stalks at field scale. Firstly, a DJI mini 2 with a CMOS (Complementary Metal Oxide Semiconductors) image sensor is utilized to acquire visible-band imagery of wheat from the experimental field. Secondly, vegetation indices of ratio type such asVDVI (Visible-band Difference Vegetation Index), NGRDI(Normalized Green-Red Difference Index), NGBDI (Normalized Green-Blue Difference Index), and RGRI (Ratio Green-Red Index)were calculated out of the visible-band images, in order to highlight vegetation features and reduce the impact of uneven light intensity on remote sensing images. Furthermore, FVC (Fractional Vegetation Coverage), which indicates the growth vigor of both individuals of wheat tillers and stalk population as a whole, was calculated based on the VDVI map. Subsequently, a BP (Backward Propagation) Neural Network prediction model was built to quantitatively invert wheat stalk density, using FGV, VDVI, NGRDI, NGBDI, and RGRI the input layer, and ground truth samples of wheat stalk densities as output layer. Upon completion of the BP Neural Network training, weight and threshold values of the prediction model were obtained, and a validation experiment was implemented. The result of the validation experiment showed that the RMSE (Root Mean Square Error) and MAPE (Mean Absolute Percentage Error) of the BP Neural Network prediction model is 19 and 3.62%, respectively. Compared with the average value of 635 of the wheat stalk density’s ground truth values, the BP Neural Network model has extraordinary wheat stalk density prediction accuracy. The statistical data of the inversed wheat stalk density at field scale indicated that the area of wheat stalk density below 500 stalks·m-2, between 501~800 stalks·m-2, and above 800 stalks·m-2 accounted for 6.67%, 74.67%, 18.66%, respectively, which provided data support for variable-rate nitrogen topdressing. The implementation of this research under the background of “negative growth of fertilizer usage” proposed by the state is the actual demand for developing resource-saving and environment-friendly Green Agriculture. The research results provide new approaches and technical support for digitalization of wheat plantation, theoretical basis and data support for creating a high and stable yield of wheat in a large area, which is of great scientific significance.
2021 Vol. 41 (12): 3828-3836 [Abstract] ( 183 ) RICH HTML PDF (4832 KB)  ( 165 )
3837 Study on the Identification Method of Citrus Leaves Based on Hyperspectral Imaging Technique
WU Ye-lan1, CHEN Yi-yu1, LIAN Xiao-qin1, LIAO Yu2, GAO Chao1, GUAN Hui-ning1, YU Chong-chong1
DOI: 10.3964/j.issn.1000-0593(2021)12-3837-07
To monitor citrus growth and realize nondestructive identification of pests and diseases, the leaf classification of citrus diseases was studied using hyperspectral imaging technology and machine learning method. Using hyperspectral imager to collect hyperspectral images of 46 normal citrus leaves, 46 canker leaves, 80 herbicide-damaged leaves, 51 red spider diseased leaves, and 98 soot diseased leaves. A 5×5 regions of interest (ROI) were extracted from one or more diseased areas of each leaf in the 478~900 nm spectral range. Taking the reflectance value of each pixel in the ROI as the spectral information, one ROI would get 25 spectral information samples, and finally the five types of leaves get a total of 13 250 spectral samples. The samples were divided into 9938 training sets and 3 312 test sets by random method. The first derivative (1st Der), multiple scattering correction (MSC) and standard normal transformation (SNV) were used to preprocess the original spectral information, and principal component analysis (PCA) was used to extract the characteristic wavelength of the data after different preprocessing methods. After 1st Der pretreatment, 7 characteristic wavelengths were obtained, which were 520.2, 689,704.83, 715.38, 731.2, 741.75 and 757.58nm respectively. After MSC and SNV pretreatment, 7 identical characteristic wavelengths were obtained, which were 551.85, 678.45, 704.83, 710.1, 725.93, 731.2 and 757.58 nm, respectively. The original spectrum obtained seven characteristic wavelengths, which were 525.48, 678.45, 710.1, 720.65, 725.93, 757.58 and 762.85 nm, respectively. The scatter plot of sample distribution after PCA analysis showed that there was a certain degree of clustering of normal leaves, canker leaves and starscream leaves, and a large amount of overlap between herbicide leaves and soot leaves, so the identification of pest and disease leaves could not be completed only based on PCA. Support vector machine (SVM) and random forest (RF) were used to model the all-band spectrum (FS) and PCA characteristic wavelength data under different pretreatment methods, and the results showed that: The OA of 1st Der-FS-SVM model was 95.98%, the Kappa coefficient was 0.948 2, the OA of 1st Der-FS-RF model was 91.42%, the Kappa coefficient was 0.889 2, the OA of 1st Der-FS-SVM model was 90.82%, and the Kappa coefficient was 0.881 6, OA and Kappa coefficient in 1st Der-PA-RF model was 91.79% and 0.894 respectively. For PCA characteristic wavelength data modeling, the recognition rate of SVM and RF models reached 84%, and the recognition rate of the full-band spectrum model was above 88%. The FS data modeling effect was better than that of PCA characteristic wavelength. The results show that it is feasible and effective to classify citrus leaves by hyperspectral imaging technique combined with machine learning method, which provides a theoretical basis for the accurate and nondestructive identification of citrus pests and diseases.
2021 Vol. 41 (12): 3837-3843 [Abstract] ( 162 ) RICH HTML PDF (3027 KB)  ( 84 )
3844 Research on Rich Borer Detection Methods Based on Hyperspectral Imaging Technology
OUYANG Ai-guo, WAN Qi-ming, LI Xiong, XIONG Zhi-yi, WANG Shun, LIAO Qi-cheng
DOI: 10.3964/j.issn.1000-0593(2021)12-3844-07
To be able to forewarn rice borers and control the spraying pesticide dosage, to realize the nondestructive detection of rice borers’ damage. A feature band detection method based on principal component analysis and an optimal band detection method based on iterative threshold is proposed, the characteristic band and the optimal band of rice stem borers detection are determined, and the images of single band and the combined band are extracted to segment wormholes, to realize the accurate nondestructive detection of rice borers. Firstly, the reflectance information of 120 samples obtained by hyperspectral analysis determined that the spectral region was 450~1 000 nm. Band detection method based on principal component analysis characteristics, principal component analysis in the hyperspectral image, in which the first five principal components determine the third principal component images as the best image comparison, and then according to the third principal component in the image, the contribution rate of each band features to select wavelength (668.8 and 750 nm). Finally, global threshold segmentation and image masking are combined to distinguish the wormhole region. Moreover, utilization based on iterative threshold detection method, the optimal band in the visible band 450~750 nm range and near-infrared band 750~1 000 nm range application to pick the best single band, mixing distance by single band combination, a combination of single band and band to iterative threshold segmentation. Among them, 753.2 nm single band has the best segmentation effect, and 753.5 nm single band is determined as the optimal band. And then extract the band images using a wormhole extraction method based on iterative threshold and morphological processing. Finally, we can distinguish the rice stalk foraminifera region to realize the existence of rice stems infested with borers. The results showed that the detection rates of 60 pest-rice stalks and 60 normal rice stalks were 95.8% and 93.3% respectively, at 668.8 and 750 nm bands by using the principal component analysis-based characteristic band detection method. The optimal band detection method based on the iterative threshold has a detection rate of 96.7% at 753.5 nm band. This indicates that the optimal band detection method based on the iterative threshold is more accurate for the detection of rice borer and also indicates that the acquired characteristic band and optimal band provide theoretical reference for the future multi-spectral imaging technology of rice borers’ damage.
2021 Vol. 41 (12): 3844-3850 [Abstract] ( 135 ) RICH HTML PDF (3639 KB)  ( 51 )
3851 Classification of Camouflages Using Hyperspectral Images Combined With Fusing Adaptive Sparse Representation and Correlation Coefficient
ZHOU Bing, LI Bing-xuan*, HE Xuan, LIU He-xiong,WANG Fa-zhen
DOI: 10.3964/j.issn.1000-0593(2021)12-3851-06
In recent years,with the rapid development of military reconnaissance and identification technology,military equipment used for reconnaissance and detection has gradually achieved high-precision levels. The troops with high-tech reconnaissance methods can often perform precise strikes on targets, significantly reducing the cost of victory in war. The more mature hyperspectral imaging methods include satellite remote sensing and high-altitude aerial imaging technologies. The two imaging methods have roughly the same reconnaissance time and the same direction of incident light. Therefore, the spectral curve of the ground object is relatively fixed. However, under land-based conditions, the spectral curve of the ground feature is prominently affected by the imaging environment, so the method of hyperspectral image classification is suitable for land-based conditions should be studied. In land-based hyperspectral images, the identification and classification of each feature are beneficial to the subsequent identification and processing of camouflage targets. Different from traditional remote sensing spectral image classification, the classification of hyperspectral camouflage targets under land-based conditions is not only difficult to obtain training samples, and in hyperspectral images under land-based conditions, the correlation between training samples under land-based conditions, the correlation between training samples varies with the target type. The parameters of the detector and the imaging environment are constantly changing. Classification methods based on sparse representation have been widely used to deal with image problems and various machine vision problems, including hyperspectral image classification. For land-based hyperspectral images, sparse coding strategies based on fixed norm constraints cannot be adapted under land-based conditions, hyperspectral imaging. For land-based hyperspectral images, sparse coding strategies based on fixed norm constraints cannot be adapted. Under land-based conditions, hyperspectral imaging is a changeable environment, and adaptive sparse representation can adaptively adjust norm constraints based on sample correlation. Correlation coefficients can improve the image’s recognition accuracy of destructive factors (shadows, noise points, etc.). This paper proposes a new hyperspectral image classification method by introducing regularization parameters, fusing adaptive sparse representation and correlation coefficients. In order to verify the effectiveness of the proposed method, camouflage objects were set in the green vegetation background and the desert background, and different classification methods classified the images. The experimental results show that the method in this paper is obvious, whether it is classification accuracy or classification consistency. The advantages of this can be applied to the classification of hyperspectral images under land-based conditions, providing a theoretical basis for camouflage reconnaissance and identification.
2021 Vol. 41 (12): 3851-3856 [Abstract] ( 193 ) RICH HTML PDF (4052 KB)  ( 68 )
3857 Combine Hyperspectral Imaging and Machine Learning to Identify the Age of Cotton Seeds
DUAN Long1, YAN Tian-ying1, WANG Jiang-li2, 3, YE Wei-xin1, CHEN Wei1, GAO Pan1, 2*, LÜ Xin2, 3*
DOI: 10.3964/j.issn.1000-0593(2021)12-3857-07
At present, the technology of precision cotton seeding has been promoted comprehensively in Xinjiang Corps, which can accurately achieve the agronomic technical standards of one grain per hole, but it also sets higher demands for the screening of high-quality cotton seeds. To avoid the decrease of germination rate caused by the cotton seeds with lack of vitality in previous years, machine learning and near-infrared (NIR) hyperspectral imaging (HSI) technology can be used to identify cotton seed years with high precision and to screen cotton seeds quickly and nondestructively. A total of 1 440 cotton seeds with no difference in appearance were collected in 2016, 2017, 2018, and 2019, and 360 seeds per year (According to 3∶1∶1, it is divided into the training set, validation set, and test set.) as samples. Hyperspectral images of cotton seeds in the range of 915~1 698 nm were collected according to each batch of 60 seeds, and average spectra (1 002~1 602 nm) for removing obvious noise at the beginning and the end were extracted as the raw data. SavitzkyGolay (SG) smoothing algorithm was used to preprocess the spectra. The principal component analysis loading (PCA-loading) method was used to select 13 effective wavelengths. Six classification models, including logistic regression (LR), partial least squares discriminant analysis (PLS-DA),support vector machine (SVM), recurrent neural network (RNN), long-short memory network (LSTM), and convolution neural network (CNN), were established based on full spectra and effective wavelengths. When using full spectra to build models, the identification accuracy of the six classification models on the test set was 96.27%, 98.98%, 99.32%, 96.95%, 97.63%, and 100%, respectively, among which CNN and SVM models had achieved good results. When using effective wavelengths to build models, the identification accuracy of the six classification models on the test set was 93.56%, 97.29%, 98.30%, 95.25%, 94.24%, and 99.66%, respectively, among which CNN and SVM models still had excellent classification results. The results showed that the six classification models could achieve high precision cotton seed years identification when the full spectra were used, and the identification accuracy of CNN and SVM models was still up to 98% when the effective wavelengths were used. The deep learning methods are generally better than the traditional machine learning methods, but traditional machine learning methods can still maintain good identification accuracy. Therefore, the combination of near-infrared hyperspectral imaging technology and machine learning methods can achieve high-precision identification of cotton seed years. It provides theories foundation and methods for selecting high-quality cotton seeds in the process of precision sowing.
2021 Vol. 41 (12): 3857-3863 [Abstract] ( 192 ) RICH HTML PDF (4145 KB)  ( 123 )
3864 Research on the Cause of Splitting of OH Vibration Spectrum in “Heibi”
DAI Lu-lu1, YANG Ming-xing1, 2*
DOI: 10.3964/j.issn.1000-0593(2021)12-3864-05
“Heibi” refers to serpentinite-related black nephrites whose main components are actinolite. Electron probe microanalysis (EPMA) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) analysis showed that “Heibi” was jasper (actinolite). There are three main peaks in OH vibration of Raman spectrum and infrared spectrum, which to MgMgMg-OH,MgMgFe2+-OH(Fe2+M1MgM1MgM3-OH,MgM1MgM1Fe2+M3-OH),MgFe2+Fe2+-OH(MgM1Fe2+M1Fe2+M3-OH,Fe2+M1Fe2+M1MgM3-OH), but differing from the common Hetian jade is that the three main peaks of “Heibi” split in the vibration region of OH (3 600~3 700 cm-1) in Raman spectrum and frequency doubling vibration region of OH (7 200~7 100 cm-1) in infrared spectrum. The “Heibi” was divided into five regions: HB-1, HB-2, HB-3, HB-4, HB-5. The in-situ EPMA and Raman spectroscopy analysis that there are main peaks (A, B, C) in the Raman spectrum from 3 600 to 3 700 cm-1. The main peaks were divided into six secondary peaks (A′ and A″, B′ and B″, C′ and C″), and the average wavenumber difference between the secondary peaks was 5 cm-1. Previous views on the splitting of the main peak at OH vibration of amphibole are various. Based on the in-situ EPMA data of “Heibi” and previous studies, it is found that the cation distribution at B(M4) position in amphibole is the main reason for the splitting. The B(M4) position of amphibole is not directly connected with the OH at W position, the cations on B (M4) position indirectly affect OH at W position by affecting oxygen bridging atoms of TO4, thus causing certain changes in OH vibration spectrum. Comparing the crystal-chemical formula of amphibole samples with “Heibi” which have similar splitting spectrum, it is found there are Ca2+ and Mn2+ distributing in B (M4) position of all samples.While the cation occupation in other positions is various, which proves that the splitting of OH vibration spectrum of “Heibi” is related to the distribution of Ca2+ and Mn2+ at B(M4). Therefore, it is considered that splitting of OH vibration spectrums in “Heibi” ascribe to occupations of Ca2+ and Mn2+ in B(M4), the high-wavenumber peaks ascribe to Ca2+, and the low-wavenumber peaks ascribe to Mn2+, which is A′, B′, C′ ascribe to Ca2+, and A″, B″, C″ ascribe to Mn2+.
2021 Vol. 41 (12): 3864-3868 [Abstract] ( 134 ) RICH HTML PDF (2576 KB)  ( 49 )
3869 Original Position Statistic Distribution Analysis (OPA) and Characterization of Components in Titanium Alloy Welding Sample by Laser Induced Breakdown Spectroscopy (LIBS)
SHEN Xue-jing1, 2, GUO Fei-fei2, XU Peng2, CUI Fei-peng2, LI Xiao-peng2, LIU Jia1, 2
DOI: 10.3964/j.issn.1000-0593(2021)12-3869-07
Titanium alloys have been used in many fields such as aerospace, marine, biomedicine, etc. due to their high strength, good corrosion resistance, and high heat resistance. Due to the heat resistance, strength, plasticity, toughness, formability, weldability, corrosion resistance and biological phase of Ti-6Al-4V (TC4) alloy. It has become the best alloy in the titanium alloy industry. When titanium alloy is welded by laser, when a surfactant is added, weld penetration can be increased, welding efficiency is improved, and the unevenness of the weld microstructure is improved, but the content and distribution of elements in the fusion zone and weld zone may be changed. So the performance of the material may be affected. In this paper, laser-induced breakdown spectroscopy (LIBS) analysis technology is used to scan the surface of TC4 titanium alloy welding specimens to obtain multi-element composition information simultaneously. At the same time, combined with the original position statistic distribution analysis method (OPA), the composition and its distribution state of base material, fusion zone, weld composition of titanium alloy can be quickly characterized, and a new evaluation method will be provided for the selection of the active agent and the material properties of titanium alloy after welding. In this paper, two different active agents are selected to weld the TC4 titanium alloy sheet. The longitudinal section of the weld is used as the analysis surface, 320 mesh alumina sandpaper is used for surface treatment LIBSOPA system is used for composition distribution analysis. Firstly, the condition optimization experiment was carried out on the excitation spot and ablation conditions. Finally, the 200 μm excitation spot, 10 pre-ablation pulses and 10 ablation pulses were selected for the experiment; secondly, the calibration curves of C,Al, V, Fe, Si, Ti six elements were established (Si element mainly comes from the active agent), and then the area scanning of the titanium alloy welding samples was finished, and the element content and distribution state were characterized. Samples were taken from different parts of the titanium alloy welding samples, and the high-frequency infrared method was used to analyze the C element content, which verified the correctness of the LIBSOPA technology analysis C results. The distribution results of the elements Al, V, Fe, Si and Ti correspond to the microbeam X-ray fluorescence spectrometry. In this paper, LIBSOPA technology is used to characterize the composition distribution of multiple elements in the titanium alloy base metal, fusion zone and weld, which provides a new evaluation and characterization method for quickly determining the composition and distribution status titanium alloy weld.
2021 Vol. 41 (12): 3869-3875 [Abstract] ( 155 ) RICH HTML PDF (7308 KB)  ( 52 )
3876 Investigation of Lithium Analysis in Geothermal Water by Inductively Coupled Plasma Optical Emission Spectrometry
ZHANG Chen-ling, JIA Na*, LIU Jia, LIU Bing-bing, HAN Mei
DOI: 10.3964/j.issn.1000-0593(2021)12-3876-05
Lithium is an important metal resource and new material, and is widely used in nuclear, photoelectric, and other industries. It occupies an important strategic position in economic construction. Geothermal resources refer to a complex, which is integrated by thermal energy, geothermal fluids and their useful minerals that humans can use. There is the considerable reserve of liquid lithium in China. It is of great significance to develop a convenient and accurate determination method ahead of lithium’s exploration, development and utilization. In determining lithium in geothermal water by inductively coupled plasma optical emission spectrometry (ICP-OES), the sample matrix does not produce significant spectral interference, but it does bring serious matrix effect. The high concentration of sodium, potassium, calcium, magnesium and other easily ionized elements in geothermal water has a strong sensitization effect on the determination of lithium. Moreover, the sensitization degree of the four elements varies with each other under different observation modes. Higher sensitization is observed in axial mode than that of radial mode. Furthermore, the apparent sensitization effect by four elements is not a simple superposition of the ionic strength. Experiments also found that the interference degree of sample matrix was greatly affected by atomization flow in both radial and axial observation modes. The lithium recovery decreased with the increase of flow at low flow rates. At medium and high flow rates, lithium recovery increased with the increase of flow. The compositions of batch geothermal water samples vary greatly, so it is not easy to control the accuracy by adjusting the atomization gas flow in lithium analysis. In order to reduce matrix interference conveniently and effectively, a modified matrix matching method was applied in this study. Single sodium chloride was added in standard solutions and geothermal water samples to match different coexisting ions. The detection limit of the proposed method was not significantly higher than that of the traditional method without matrix matching. The detection limits of the proposed method are 0.20 μg·L-1 (axial) and 0.41 μg·L-1 (radial). While those of the traditional method is 0.11 μg·L-1 (axial) and 0.39 μg·L-1 (radial). The modified method was verified by the analyte addition test and dilution test. The spiked recoveries of three geothermal water samples were 96.5% to 105.6%, with relative standard deviations lower than 2%. The results were consistent with those obtained by inductively coupled plasma mass spectrometry (ICP-MS). The values of dilution samples agreed well with ±2.0% of the original determination. The improved matrix matching method can effectively reduce the matrix interference caused by easily ionized elements. The proposed method in this study is simplified, swift, accurate, and is suitable for batch analysis with different matrix compositions.
2021 Vol. 41 (12): 3876-3880 [Abstract] ( 147 ) RICH HTML PDF (1390 KB)  ( 285 )
3881 Evaluations of Environmental Trace Gases Monitoring Instrument (EMI) Level 1 Data
CHENG Liang-xiao1, 2, TAO Jin-hua1*, ZHOU Hai-jin3, YU Chao1, FAN Meng1, WANG Ya-peng4, WANG Zhi-bao5, CHEN Liang-fu1
DOI: 10.3964/j.issn.1000-0593(2021)12-3881-06
The Environmental trace gases Monitoring Instrument (EMI) is the first high spectral resolution imaging spectrometer in China designed to monitor trace gas in tropospheric and stratospheric. To fully understand the instrument’s characteristics and make better use of the level 1 (L1) data, comprehensive evaluations of irradiance and radiance data measured by the EMI instrument were carried out in this study. For both ultraviolet-2 and visible-1 bands,the slit function change drastically as a function of detectors in the across-track direction of charge-coupled device (CCD), which is more than 6 times larger than that of TROP(OMI). The use of different slit functions according to the row can improve the calibration accuracy. Small wavelength shifts were found in both irradiance and radiance data with an average value of 0.015 and 0.03 nm, respectively. Although they meet the requirement of the design specification (0.05 nm), wavelength calibration is still needed during the trace gas retrieval. EMI irradiance data agree highly (r>0.95) with OMI and TROPOMI and the reference solar spectrum. EMI radiance data also shows a better agreement (r>0.93) with OMI and TROPOMI by averaging the cloud-free pixels over the clean Pacific region. This study demonstrates the good quality of current EMI L1 data for trace gas retrieval, and it provides a reference for the design and data quality evaluation scheme of subsequent instruments.
2021 Vol. 41 (12): 3881-3886 [Abstract] ( 137 ) RICH HTML PDF (5812 KB)  ( 46 )
3887 A Multispectrum Fitting Program Based on Non-Linear Least-Squares Method for Line Parameters:Application to 12CH4
MA Hong-liang1, 2, ZHENG Jian-jie1, 3, 4, LIU Qiang1, 3*, QIAN Xian-mei1, 3, ZHU Wen-yue1, 3
DOI: 10.3964/j.issn.1000-0593(2021)12-3887-05
The precise knowledge of the experimental spectroscopic line parameters of methane is widely used in atmospheric science and astronomical exploration, especially its collision broadening and temperature-dependent coefficients, which are important to study the methane molecular concentration profile. Precise experimental measurement is the significant method to obtain accurate spectral line parameters. In order to derive unknown parameters through a non-linear least-squares method, it is necessary to the simultaneous treatment of several experimental spectra in the same region were recorded with known experimental conditions (concentration, temperature, total pressure, absorption optical path and mixture ratio of gas molecule species, etc.). Then these spectra were usually fitted separately using spectrum-by-spectrum fitting procedure, but this method was often time-consuming and errors were easily produced. In order to solve this problem, a multispectrum fitting procedure based upon the non-linear least-squares and Levenberg-Marquardt method have been developed, able to treat simultaneously several laboratory spectra obtained by tunable diode laser absorption spectroscopy. This procedure can obtain a set of spectral parameters based on the global fitting method. The theory, data processing and application of the procedure are presented in detail. The laboratory spectra of 6 transition lines of 12CH4 molecules in the 2 958~2 959 cm-1 region are processed by using the Voigt profile of the multispectrum fitting program, and these lines air-broadening coefficients were obtained at five temperatures (296.0,251.0,223.0,198.0,173.0 K). The air-broadening coefficients of the present work are compared with the available values reported in the literature, which were obtained by spectrum-by-spectrum fitting procedure, and the difference between them lies within -4.97%~1.58%. The results show that the broadening coefficients of these transitions in this work agree well with those available values. Among the 30 sets of correlation data, there are 4 sets whose fitting errors obtained by the spectrum-by-spectrum fitting program are smaller than those by the multispectrum fitting program, 2 sets with equal error values, and the remaining 24 sets whose fitting errors obtained by the multispectrum fitting program are smaller. Therefore, the multispectrum fitting program has good reliability and is suitable for processing gas molecular absorption spectrum.
2021 Vol. 41 (12): 3887-3891 [Abstract] ( 176 ) RICH HTML PDF (1579 KB)  ( 76 )
3892 Solar Radiation Observation During a Solar Eclipse in Tibet
WANG Qian, Norsang Gelsor*, Tsoja Wangmu, Lagba Tunzhup, Pu Dopwang, LIU Juan, ZHOU Yi, ZE Xi
DOI: 10.3964/j.issn.1000-0593(2021)12-3892-09
Solar eclipses cause corresponding impacts on the earth’s solar radiation, meteorology and human activities. A Solar eclipse occurred on June 21(summer solstice), 2020, in Tibet, the maximum magnitude of the annular eclipse was reached 0.995 in Ngari, and the maximum magnitude of 0.953 for the partial eclipse in Lhasa, Tibet. The eclipses for both locations occurred around the local noons. We, by taking the rare opportunity for appearing the solar eclipse, observed the solar spectra, global solar irradiance and solar UV radiation measured by the RAMSES solar spectrometers made in Germany, the CMP11global solar radiometers by Holland and the NILU-UV solar ultraviolet detectors made in Norway, respectively during the solar eclipse in Tibet. The observations show that the annular eclipse lasted about 3 hours 27 minutes. Around the local noon (Beijing time 14:41) in Ngari. The eclipse in Lhasa was 26 minutes behind Ngari and lasted about 3 minutes and 28 seconds shorter than Ngari. The observation showed that the peak value of strongest monochromatic (476.6 nm) light for Ngari’s spectra decreased sharply from 1 669.234 mW·m-2·nm-1 at the first contact phase (13:01 min) to 61.936 mW·m-2·nm-1 at the maximum phase (14:44 min), with a loss of about 96.0%. Simultaneously, the global solar irradiance decreased from 1 221.217 to 56.086 W·m-2, and the loss was about 95.4% for Ngari. The peak value of the strongest monochromatic (476.6 nm) light during the solar eclipse in Lhasa decreased from 1 563.876 mW·m-2·nm-1 at the first contact phase (13:27) to 26.391 mW·m-2·nm-1 at the maximum phase of the eclipse (15:13), the deficit was about 98.3%, the global solar irradiance decreased from 1 605.663 to 28.169 W·m-2 for the above corresponding time, and the net loss was about 98.2% too. We observed that the dose rates for solar UVB in Lhasa were also decreased about 98.5% for the value of 60.8 W·m-2 at the first contact phase to 0.9 W·m-2 at the maximum phase of the eclipse. The current solar eclipse caused more than 95% energy loss to Tibet’s surface solar radiation intensity.
2021 Vol. 41 (12): 3892-3900 [Abstract] ( 159 ) RICH HTML PDF (8875 KB)  ( 35 )
3901 Flame Retardant Mechanism Investigation of Thermoplastic Polyurethane Composite/Ammonium Polyphosphate/Aluminum Hydroxide Composites Based on Spectroscopy Analysis
PENG Jian-wen1, XIAO Chong1, SONG Qiang1, PENG Zhong-chao1, HUANG Ruo-sen1, YANG Ya-dong3, TANG Gang1, 2, 3*
DOI: 10.3964/j.issn.1000-0593(2021)12-3901-08
Ammonium polyphosphate (APP) and aluminum hydroxide (ATH) was introduced to prepare a series of ammonium polyphosphate/aluminum hydroxide/thermoplastic polyurethane composites (TPU/APP/ATH) by melting blending technology. Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM) and laser Raman spectroscopy test were applied to investigate micro-morphology, surface structure, elemental composition, bonding state and graphitization degree of the char residue for TPU and flame retardant TPU composites, which combined with flame retardant tests to discover synergistic flame retardant mechanism of APP and ATH. SEM analysis revealed that TPU/APP/ATH char residue had less void structure and higher densification than APP and ATH alone. XPS revealed that the content of the C element in FR-TPU slag decreased compared with pure TPU, while the content of the O element increased. In these samples, the content of C element in TPU/APP10/ATH10 decreased from 88.2% to 69.24%, the content of O element increased from 8.07% to 17.78%. Compared with TPU/APP20 and TPU/ATH20, the content of P and Al element in TPU/APP10/ATH10 were decreased to 3.91% and 3.31%, respectively. Furthermore, peak fitting for bonding state of C element showed that C—C/C—H, C—O/C—N and CO/CN structure in char residue of TPU was 61.05%, 35.65% and 3.30%. In comparison, those in char residue of TPU/APP10/ATH10 were 45.38%, 45.00% and 9.63%, indicating ATH and APP facilitated the formation of ester, ether, carbonyl, the carboxylic acid (salt), ester group, et al. Peak fitting for the binding state of O element showed that O2/H2O,—O— and O structure in char residue of TPU were 28.75%, 44.36% and 26.89%, compared with 44.33%, 32.78% and 22.89% in char residue of TPU/APP10/ATH10, indicating that the addition of APP or/and ATH was conducive to the formation of O2/H2O structure of O elements. Peak fitting for bonding state of N element showed that —NH— and N structure in char residue of TPU was 40.93% and 59.07%, compared with 47.17% and 52.83% in char residue of TPU/APP10/ATH10, implying ATH and APP promoted the formation of —NH— structure. The Raman spectroscopy test showed that the char layers of TPU/APP10/ATH10 were more graphitized and densified than the sample with APP and ATH used alone. Based on the above researches and flame-retardant tests, the flame retardancy mechanism of TPU/APP/ATH composites can be obtained as follows: ATH was thermally decomposed into alumina, which absorbed heat and released large amounts of water vapor, effectively facilitating APP degradation, producing incombustible ammonia and polyphosphoric acid, which diluted the concentration of flammable gas. As the temperature continued to rise, alumina reacts with polyphosphoric acid to form aluminum metaphosphate (Al(PO3)3), which synchronously catalyzes the carbonization of the polyurethane matrix to form a highly graphitized char layer. The graphitized char layer covered the surface of the matrix together with aluminum metaphosphate, effectively inhibiting the transport of substances and energy in the combustion area, thus achieving flame retardation.
2021 Vol. 41 (12): 3901-3908 [Abstract] ( 139 ) RICH HTML PDF (5853 KB)  ( 44 )
3909 Mechanism Investigation of Cement-Based Permeable Crystalline Waterproof Material Based on Spectral Analysis
HE Xiong-fei1, 2, HUANG Wei3, TANG Gang3, ZHANG Hao3*
DOI: 10.3964/j.issn.1000-0593(2021)12-3909-06
In this work, permeable crystalline waterproof material was used as the research object, which was added into cement-based materials to fabricate cement-based permeable crystalline waterproof material (CCCW). X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) were applied to investigate the composition of CCCW. On this base, the effect of CCCW on mechanical properties to the samples were researched, and scanning electron microscope (SEM) as well as X-ray diffraction (XRD) were introduced to investigate micro-morphology and phase composition of the samples, which were combined with the relevant data about compress strength restoration ratio and permeability resistance to illuminate work mechanism of CCCW. It was confirmed that permeable crystalline waterproof material contained calcium oxide, sodium silicate, sodium disilicate, calcium carbonate, calcium hydroxide, PAH based water reducing agent and ethylenediaminetetraacetate. CCCW samples with permeable crystalline waterproof material loading exhibited excellent mechanical property, permeability resistance and self-healing property. The sample presented flexural strength at 7, 14 and 28 d of 2.65, 3.29 and 4.35 MPa, and exhibited compress strength of 12.11,14.57 and 16.77 MPa, respectively. The CCCW sample presented first permeability and second permeability of 0.8 and 0.9 MPa, which showed compress strength restoration at 7, 14, 28 and 56 d for 80.91%,90.35%, 100.44% and 105.90%, respectively. The work mechanism of CCCW has proposed: sodium silicate and sodium disilicate in permeable crystalline waterproof material reacted with Ca2+ in cement to form calcium silicate hydrate gel (C—S—H) and effectively repair the cracks. Calcium oxide, calcium hydroxide and calcium carbonate played as Ca2+ compensators and provided abundant free Ca2+, which could effectively promote the healing process of the cracks underwater environment. Calcium carbonate gradually dissolved in the water environment and produced Ca2+, CO2-3 and HCO-3, the generated CO2-3 and HCO-3 could reacted with abundant Ca2+ to produce calcium carbonate crystal, which combined with C—S—H gel to blocked the crack structure of CCCW.
2021 Vol. 41 (12): 3909-3914 [Abstract] ( 158 ) RICH HTML PDF (3866 KB)  ( 43 )
3915 Study on Diffuse Reflection and Absorption Spectra of Organic and Inorganic Chinese Painting Pigments
XU Zhao-jin, LI Dong-liang, SHEN Li*
DOI: 10.3964/j.issn.1000-0593(2021)12-3915-07
The unmixing of traditional Chinese painting pigments has always been an essential content in the study of ancient painting pigments, and the fiber optics reflectance spectra (FORS) is a standard method for nondestructive detection of pigment category. In this paper, through the CCD (charge-coupled device) optical fiber spectroscopy system, the classification of traditional Chinese painting pigments in terms of spectral lines was discussed. The diffuse reflectance and absorption spectra of two kinds of organic plant pigments gamboge and rouge in different mass ratios were detected, and the diffuse reflectance spectra of inorganic mineral pigments in different color series were obtained. The characteristic spectral peaks of a single pigment and different mixed pigments were analyzed, and the mass ratio of each pigment was obtained by the linear unmixing method of the whole band using multiple linear regression (MLR) and first derivative spectroscopy (FDS). Through experimental and theoretical analysis, the diffuse reflection spectra of gamboge and rouge are all S-type. The first derivative spectra of the mixed pigment have two characteristic peaks at 536 and 649 nm. MLR is suitable for unmixing the mixed pigment diffuse reflectance spectrum and shows a certain linear rule, but it cannot be precisely dis mixed. However, the absorption spectrum of the mixed pigment has a utterly linear relationship with the monochromatic spectrum, and the unmixing error is about 5%. The diffuse reflectance spectra of inorganic mineral pigments are S-type (mineral yellow and ochre) and bell-type (malachite and azurite). Firstly, for the diffuse reflection spectrum of S-type (mineral yellow) and S-type (ochre), the first derivative spectrum of ochre presents an obvious phenomenon of “triple-peak”. Meanwhile, the first derivative spectrum of mixed pigments presents a new characteristic peak at 534 nm. However, it cannot form a more accurate linear model due to the different weight factors of unmixing of different pigments. Secondly, for the mixed spectrum of S-type (ochre) and bell-type (malachite), it is necessary to use multiple linear regression and derivative spectroscopy to determine the basic trend of their mixing ratio jointly. Because of different lines, the reflection spectrum of mixed pigments has only one crossing point in the range of 400~800 nm. Finally, through the characteristic the peak positions of bell-type (malachite) and bell-type (azurite) pigment mixing spectra, the characteristics of pigment mixing ratio can be acquired. With the change of the mixing ratio, the characteristic peak position of the reflection spectrum showed a significant lateral movement at 457~524 nm, and the peak intensity of the mixed pigment spectrum decreased significantly.
2021 Vol. 41 (12): 3915-3921 [Abstract] ( 147 ) RICH HTML PDF (4619 KB)  ( 40 )
3922 Nonlinear Full-Spectrum Quantitative Analysis Algorithm of Complex Water Based on IERT
LIU Jia-cheng1, 2, HU Bing-liang1, YU Tao1*, WANG Xue-ji1, DU Jian1, LIU Hong1, LIU Xiao1, HUANG Qi-xing3
DOI: 10.3964/j.issn.1000-0593(2021)12-3922-09
Water is a finite resource, essential for agriculture, industry and even human existence. A good water environment is an important guarantee for sustainable development. The scientific monitoring of water quality information is the basis for optimal allocation and efficient use of water resources. The United Nations Environment Program (UNEP) and the World Health Organization (WHO) pointed out that national water quality monitoring networks in developing countries should be strengthened, including improving analytical capabilities and data quality assurance. As an emerging water quality analysis method, spectral method has the characteristics of “fast response, synchronization of multiple parameters, environmental protection and pollution-free” compared with traditional chemical water quality monitoring methods. The traditional single-band, multi-band linear model, relies on the absorption characteristics of water at specific bands, and it cannot be used for multi-component mixed solutions and has poor universality. Therefore, this paper proposes a non-linear full-spectrum quantitative analysis algorithm based on IERT. The concentration prediction model suitable for multi-component mixed solution is established to use full spectrum information to predict concentration information. We use the COD, BOD5, TOC multi-component mixed solution and NO3-N, turbidity, chroma multi-component mixed solution configured in the laboratory as the experimental sample, use the spectrometer to collect the spectral curve of the sample, and conduct the concentration prediction experiment through the full spectrum data. The experimental results show that for COD, BOD5, TOC multi-component mixed solutions, the determination coefficients (R2) of this algorithm for the three components are 0.999 3, 0.991 4 and 0.999 3. The root means square error (RMSE) is 0.024 4, 0.057 7 and 0.000 4. For the multi-component mixed solution of NO3-N, turbidity, and colority, the coefficient of determination (R2) is 0.983 4, 0.868 4 and 0.981 0. The root means square error (RMSE) is 0.100 5, 0.326 4 and 0.120 2. By comparing the experimental results of this algorithm with partial least squares (PLS), support vector regression (SVR), decision tree (DT), and extreme random tree (ERT) for the same set of data, the results show that in the experiment of mixed solution, this algorithm is the best alternative to the coefficient of determination (R2) of each component.The root means square error (RMSE) has been greatly reduced compared with other comparison algorithms. This algorithm can use spectral information to analyze the multi-component mixed solution quantitatively. It can effectively improve the concentration prediction accuracy and reduce the root-mean-square error of the quantitative analysis in the case of equivalent calculation time. Moreover, this algorithm can provide a theoretical basis for spectral methods on water quality monitoring.
2021 Vol. 41 (12): 3922-3930 [Abstract] ( 180 ) RICH HTML PDF (4859 KB)  ( 83 )
3931 Influence of AEO-9 on Ultraviolet Absorbance Spectrum of TDBAC Reduced by β-CD
XU Hui-hua, SHI Dong-po*, WU Hao, YIN Xian-qing, ZHENG Yan-cheng, CHEN Wu, LI Geng
DOI: 10.3964/j.issn.1000-0593(2021)12-3931-05
The interaction between tetradecyl dimethyl benzyl ammonium chloride (TDBAC) and fatty alcohol polyoxyethylene ether (AEO-9) could significantly interfere with the ultraviolet absorption intensity of TDBAC in an aqueous solution. The results showed that AEO-9 can improve the ultraviolet absorption intensity of TDBAC and can greatly decrease the apparent critical micelle concentration (cmc) of TDBAC. When the concentration of AEO-9 increased from 0 to 0.150 and 0.300 mmol·L-1, the apparent cmc of TDBAC decreased from 1.901 to 1.739 mmol·L-1 and 1.584 mmol·L-1, respectively. In TDBAC/AEO-9 aqueous solution, the ultraviolet absorption intensity of TDBAC was enhanced by adding 1∶1 β-cyclodextrin (β-CD) according to the molar amount of TDBAC, with the addition of 0.800 mmol·L-1 β-CD, the ultraviolet absorption intensity of TDBAC increased from 0.259 to 0.270. When the concentrations of AEO-9 increased from 0 to 0.150 or 0.300 mmol·L-1, TDBAC micelles could not be formed in the range of 0.600~2.800 mmol·L-1 in aqueous solutionby adding 1∶1 β-CD. What is more, the interference of AEO-9 on UV Spectrum of TDBAC could be greatly reduced, and the recovery rate of TDBAC in TDBAC/AEO-9 aqueous solution changed from 86.3%~107.5% to 101.9%~103.9%, which showed that the detection accuracy of TDBAC was significantly improved. The results of Job’s experiments showed that TDBAC/AEO-9 inclusion should be formed with the molar ratio of 1∶1 in an aqueous solution. The results of FTIR andTG-DSC showed that TDBAC molecules were more likely to form inclusion complexes with β-CD rather than micelles in aqueous solution, which exhibited that the interference of AEO-9 on quantitative determination of TDBAC could be significantly reduced because of the formation of TDBAC/β-CD inclusion in TDBAC/AEO-9 aqueous solutions.
2021 Vol. 41 (12): 3931-3935 [Abstract] ( 132 ) RICH HTML PDF (2593 KB)  ( 34 )
3936 Gemological and Spectroscopic Characteristics of Natural White Sodalite With Tenebrescence
YAN Xiao-xu1, YUE Su-wei1, 2*, SU Lü-man1, WANG Zhi-wen1
DOI: 10.3964/j.issn.1000-0593(2021)12-3936-06
Sodalite is a member of the feldspathoids, which is widely applied in the field of construction, illumination, and dosimetry. High-quality sodalite is known mainly as its tenebrescence under ultraviolet (UV) irradiation. This attracting optical phenomenon has been recognized by consumers, leading the price of sodalite soaring. For the lack of systematic research on gemstone sodalite, its gemological characteristics and mechanism of tenebrescence are investigated in this study. Photochromic white sodalites were selected in the research of tenebrescence under UV irradiation, respectively exposed to UVA (365 nm) and UVC (254 nm). The mechanism of tenebrescence was investigated by FTIR, UV-Vis, and EPR. The UV irradiation research showed: (1) natural white sodalite has an orangish-pink to orangish-red fluorescence, which might change into purplish-red for 1~2 min when exposed to UVA in 5 min, however, it could be removed by visible-light (700~400 nm) quickly; (2) the purplish-red color got continuous enhanced and became steady even exposed to visible-light; (3) the fluorescence of natural samples was stronger than their photochromic state. FTIR spectra of natural samples showed: (1) 5 250 cm-1 strong absorption attributed to stretching and bending vibration of H2O, demonstrating the existence of hydrate; (2) 4 698 and 4 555 cm-1 weak absorption were induced by the out-of-plane bending vibration (γ) between metallic cations (M) and hydroxyl radicals (O—H); (3) 1 002 cm-1 strong absorption moved 20 cm-1 towards high wave-number direction compared to the standard spectrum for substitution of Mn2+ and Ti3+ in Al—O, which could be demonstrated by the EPR signals of several hyperfine lines around 3 511G (g=2.002) and a single line at 3 573 G (g=1.967). UV-Vis and EPR spectra indicated that, the main cause of tenebrescence in white sodalite was associated with Cl vacancy generated by the substitution between S2-2 and Cl-. For the balance of charge valence, S2-2 was excited by UV irradiation and generated free electron(S2-2→S-2+e-). The free electron then jumped into subduction band and traped by VCl, which formed color center and led to wide absorption band around 539 nm along with strengthen absorption towards ultraviolet region and finally generate purplish-red. By the way, single EPR line at 3 480 G(g=2.02) might be the proof to capability of tenebrescence.
2021 Vol. 41 (12): 3936-3941 [Abstract] ( 190 ) RICH HTML PDF (2769 KB)  ( 63 )
3942 A New Method for Inflection Point Temperature Calculation of Large-Area High-Temperature Fixed-Point Blackbody Used in Spectral Irradiance Scale Realization
XIE Yi-hang, DAI Cai-hong*, WANG Yan-fei, WU Zhi-feng, LI Ling, HE Shu-fang
DOI: 10.3964/j.issn.1000-0593(2021)12-3942-07
The theoretical basis of the national primary standard apparatus of spectral irradiance in China is Planck’s law revealing a real quantitative relationship between wavelength, temperature and spectral irradiance. The spectral irradiance comparison method is used to preserve and transfer the spectral irradiance standard by halogen tungsten lamp. Moreover the temperature measurement of a blackbody is the main source of uncertainty in the realization of spectral irradiance. For a long time in the past, a variable high-temperature blackbody was used as the primary radiation source for realization of spectral irradiance scale, and the temperature measurement of the blackbody was realized by a pyrometer traceable to the fixed-point temperature scale blackbodies of NIM. In order to meet the needs of high accuracy measurement of spectral irradiance in the fields of earth observation, meteorological remote sensing, climate change monitoring and ocean color detection in China, National Institute of Metrology (NIM) established a 14 mm diameter WC-C high-temperature fixed-point blackbody (HTFP) system, which was used as the primary radiation source to realize spectral irradiance scale directly. This method can shorten the traceability chain and reduce the temperature measurement error. In the experiment, the data obtained by a pyrometer are only the relative distribution of the blackbody temperature rather than the absolute value. In order to obtain the absolute temperature of a WC-C HTFP blackbody which can be used for the realization of spectral irradiance, it is necessary to use the point of inflection (POI) temperature of the melting temperature plateau curve for comparison calibration. So it is important to calculate and evaluate the POI temperature reasonably. Unlike a small-area WC-C HTFP, the melting temperature plateau curve of a large-area WC-C HTFP has a longer duration and has greater temperature variation, so traditional POI calculation methods, which are widely used in small-area HTFPs, are no longer applicable. So this paper proposed a selective multiple fit methods calculating the POI of a large-area WC-C HTFP with a 14 mm inner diameter. The influences of selective criterion, data smoothing and fitting range on the calculation results of POI were investigated. The maximum discrepancy between the new and traditional methods was 0.001 and 0.633 K, introducing 0.000 3% and 0.20% spectral irradiance measurement errors at 500 nm respectively. Using small-area WC-C and Re-C fixed-points with 3 mm inner diameters to investigate the validity of the new method. The results showed that the maximum discrepancy between the new method and the average value of the three traditional methods was -0.007 and -0.001 K, introducing 0.002 2% and 0.000 3% spectral irradiance measurement errors at 500 nm respectively. Compared with the three traditional methods, the new method can effectively reduce the temperature error and improve the realization accuracy of spectral irradiance. It is more suitable to calculate the POI temperature of a large-area WC-C HTFP blackbody.
2021 Vol. 41 (12): 3942-3948 [Abstract] ( 144 ) RICH HTML PDF (3324 KB)  ( 66 )
3949 Research on Large-Scale Monitoring of Spider Mite Infestation in Xinjiang Cotton Field Based on Multi-Source Data
YANG Li-li, WANG Zhen-peng, WU Cai-cong*
DOI: 10.3964/j.issn.1000-0593(2021)12-3949-08
Xinjiang’s traditional cotton field spider mite monitoring method is time-consuming and inefficient. The paper proposes combining ground hyperspectral, UAV multi-spectrum, environmental data and field survey for dynamic monitoring of large-scale spider mite damage. Firstly, cotton canopy hyperspectral data and low-altitude-scale UAV multi-spectral data in different cotton periods are collected separately by analyzing the original hyperspectral spectrum and first-order differential spectral characteristics, four sensitive bands of spider mite damage are extracted as below: green light band near 553 nm, red light band near 680 nm, red side band of 680~750 nm, and near infrared band of 760~1 350 nm, which are also included in the multi-spectrum carried by UAV. Secondly, the correlation analysis among 23 vegetation indices, 13 field environmental data, and the occurrence of spider mites surveyed on the ground is done. SAVI, OSAVI, TVI, NDGI, average humidity, temperature-humidity coefficient and average soil temperature of 10 cm are all significantly correlated with spider mite occurrence (sig≤0.01); RDVI, RVI, MSR, maximum temperature, average temperature, accumulated temperature, the highest temperature of 10 cm soil and the average humidity of 10 cm soil all reach a significant correlation level with the occurrence of spider mite damage (sig≤0.05). 15 characteristic values with sig values below 0.05 were selected; cotton field mite monitoring models based on single environmental data, single vegetation indices, and a combination of environmental data and vegetation indices are established respectively using support vector machine (SVM). Finally, from the optimum model, we can draw the spatial distribution map of spider mite damage in different periods and calculate the proportion of spider mite damage are based on the number of spider mite damage and healthy pixels in the statistical distribution map. Then the field environmental data is analyzed for correlation, the environmental factors most closely related to the spider mite area value are determined by multiple stepwise regression analysis, and the cotton field spider mite area prediction model is established. The results show that the accuracy rate of the cotton field spider mite monitoring model based on a single environmental data is 62.22%, while the accuracy rate of the cotton field mite monitoring model based on a single vegetation index is 75.56%. Moreover, the most effective model is based on the combination of environmental data and vegetation indices with an accuracy rate of 80%. The coefficient of determination of the spider mite area prediction model is R2=0.848. In this study, based on multi-source data, the cotton field spider mite occurrence monitoring model and spider mite area prediction model can provide a reference for the large-scale monitoring and trend warning of cotton field mite damage in Xinjiang.
2021 Vol. 41 (12): 3949-3956 [Abstract] ( 159 ) RICH HTML PDF (5152 KB)  ( 55 )
3957 Modification of Ternary Layered Hydroxide and Removing for Orange Ⅱ With Spectroscopy
JIANG Shuang-cheng1, FAN Dan-yang2, LIU Yue2, WANG Jia-bin3, LÜ Hai-xia2*
DOI: 10.3964/j.issn.1000-0593(2021)12-3957-06
The adsorption method has become one of the most common wastewater treatment methods because of its high efficiency, low cost, non-toxicity, simple operation and so on. The key to the adsorption method is the selection and preparation of adsorbents. As a new type of adsorbent, the layered hydroxide (LDH) has attracted much attention due to its special layered structure, adjustable lamellar elements and exchangeable anions between layers. However, the improvement of LDH adsorption capacity is still an urgent problem. In this work, a novel pyromellitic acid modified layered hydroxide (PA-LDH) was prepared by intercalation modification of ternary Ca-Mg-Al-LDH with pyromellitic acid (PA), and its calcination product (PA-LDO) was obtained by calcining. UV Vis was applied to study their adsorption performance for Orange II. FTIR and BET were used to characterize the morphology and structure of the modified adsorbents. Comparing the FT-IR spectra of LDH and PA-LDH, a new peak of PA-LDH appeared at 1 717 cm-1, which may be attributed to the C═O group in PA. Moreover, the peak moved towards the high frequency, which may be due to the destruction of the polymer formed between PA, indicating that PA was successfully intercalated into the interlayer of LDH. Compared with the FT-IR spectra of PA-LDH, it could be found that the weak peak of PA-LDO near 3 000 cm-1 disappeared, implying that the interlayer anion was destroyed during the calcination process. However, the peaks corresponding to the vibration of M—O and M—OH (M=Ca, Mg and Al) at 875 and 723 cm-1 still existed, indicating that the similar structure was still maintained after calcination. The specific surface areas of PA-LDH and PA-LDO measured by nitrogen adsorption-desorption experiments were 15.934 1 and 119.401 0 m2·g-1, respectively, indicating that the specific surface area increased after calcination, so that PA-LDO may have a better adsorption effect. With anionic dye, Orange Ⅱ as the target pollutant, the effects of adsorption time, initial dye concentration and other factors on PA-LDH,PA-LDO adsorption performance were investigated by UV Vis under pH conditions 7.0, adsorbent dosage of 5 mg and wavelength of 484 nm. The Qmax of PA-LDH and PA-LDO for Orange Ⅱ were 561.322 and 1 401.639 mg·g-1, respectively, which were relatively higher than those reported in the literature. Through isothermal adsorption experiments, it was found that the adsorption of Orange Ⅱ by PA-LDH and PA-LDO basically accorded with the Langmuir model, which showed monolayer adsorption was the dominant process of the adsorption process, the theoretical maximum adsorption capacities were 588.235 and 1 428.571 mg·g-1 respectively, which were close to the experimental values mentioned above. This indicated that the layered hydroxide modified by aromatic acid anions had good adsorption performance for anionic dyes and a certain application prospect in the treatment of dye wastewater.
2021 Vol. 41 (12): 3957-3962 [Abstract] ( 130 ) RICH HTML PDF (2616 KB)  ( 41 )
3963 《光谱学与光谱分析》2021年(第41卷)总目次(第1~12期)
《光谱学与光谱分析》编辑部
2021 Vol. 41 (12): 3963-3984 [Abstract] ( 139 ) PDF (1112 KB)  ( 254 )