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2019 Vol. 39, No. 04
Published: 2019-04-01

 
997 Development and Application of Spatially Offset Raman Spectroscopy
ZHU Ting1,LIU Yang2, 3*,WU Jun2, 4,WANG En-liang1,XUE Feng5
DOI: 10.3964/j.issn.1000-0593(2019)04-0997-08
The traditional Raman spectroscopy can only detect the surface information of the sample, or can only through the transparent surface detect the inner information of the sample, and it has same problems to get information of multilayer opaque sample or opaque packaging sample, such as searching for hidden explosives, identifying fake medicine with opaque package and non-invasive detection of bone disease, etc.. Spatially offset Raman Spectroscopy (SORS) is a new type of spectral detection technique, which can get information from opaque package non-invasively or gain information through surface layer to inner of the sample directly. This technology solves the problems mentioned above. Firstly, this paper introduced the principle of SORS in detail. The fundamental principle lies in the theory of photon migration. Between the focus point of the incident laser light source and the focus point of the collect lens there is a certain spatial distance offset ΔS from surface of the sample. When the laser light incident into the surface of sample, it will be stimulated or scatter broadband fluorescence by the surface of sample. One part of scattered light will reach to the inner of sample, and the photons of Raman scattered light from inner sample is easier to migrate than the photons of the surface of sample. The photons of Raman scattered light are returned to the surface of sample and collected by optical system after multiple scattering. Scattered light from different depths ΔH have different spatial distance offset ΔS after returning to the surface of sample.When the spatial distance offset ΔS is zero, the focus point of the incident laser light and the focus point of the collect lens are coincided where the density of photons is maximum, and the Raman signal collected by optical system are mostly from the surface of sample, and Raman signal of inner sample is submerged. When the spatial distance offset ΔS is not zero, the Raman signal from the surface of sample collected by optical system is attenuated quickly, but Raman signal of inner sample is attenuated more slowly than that from the sample surface, and this makes the proportion of inner sample more larger, so as to realize the Raman spectral separation. Then optical system will show us the Raman spectral from different depths of inner sample with multivariate data analysis method, and this Raman spectral is the Spatially offset Raman Spectroscopy(SORS). SORS has a good ability to suppress the interference of Raman and fluorescence spectra of surface materials, especially for the extraction of Raman spectra from substances under opaque packaging materials, so as to identify the target components quickly and non-invasively. Secondly, the characteristics of SORS technology are introduced. It is the derivative of Raman spectroscopy. Besides it has all the advantages of Raman spectroscopy, such as simple sample making, less water interference, less sample consumption, high sensitivity, etc.. It also has the special advantages of effectively suppressing the fluorescence, deep detection, non-invasive characteristics of nondestructive detecting and remote detection. These special advantages improved the intensity of Raman spectra effectively, reduced the user’s detection and production costs and also improved the personal safety of the inspectors. At the same time, this paper summarized and compared three existing working methods of SORS technology, standard SORS, inverse SORS and tilted SORS. The standard SORS technology can be used in non-contact remote sensing detection, and inverse SORS compared with the standard SORS has higher sensitivity and potential anti spectral distortion, and the incident light face and the effective spatial distance offset ΔS is controllable, and also avoid the sample overheating. Tilted SORS has a higher detection sensitivity of SORS, and the experimental device is easy to achieve. Then, based on a large number of research papers, the development and application of SORS technology combined with other technologies in chemical production, security inspection, biomedicine, archaeology, food safety, inspection and counterfeiting and national defense safety in recent years were reviewed. Finally, the existing problems of SORS technology are pointed out and the future prospects of the technology are also prospected.
2019 Vol. 39 (04): 997-1004 [Abstract] ( 322 ) RICH HTML PDF (3150 KB)  ( 224 )
1005 Advance in Agricultural Drought Monitoring Using Remote Sensing Data
YAO Yuan1, 2, 3, CHEN Xi1, 4, QIAN Jing1, 2*
DOI: 10.3964/j.issn.1000-0593(2019)04-1005-08
At present, frequent agricultural droughts not only seriously affect regional food security and ecological security, but also threaten social economic stability and sustainable development in the context of global warming. Using remote sensing technology to monitor agricultural drought is an important way to prevent the occurrence and development of agricultural drought, which can provide a strong support for people to develop scientific management measures. Hence, understanding the current progress in studies related to the agricultural drought monitoring based on remote sensing data has importance and practical significance in the quantitative evaluation of agricultural drought and promotion of sustainable social and economic development. In this paper, we first introduced the concepts of the drought and agricultural drought and main research methods. Secondly, we reviewed the progress of research on the agricultural drought monitoring by remote sensing, especially in monitoring indices and its methods. The monitoring indices based on remote sensing were classified into three categories: reflecting rainfall change, reflecting soil moisture change and reflecting crop water balance. Beside this, microwave remote sensing monitoring method, multispectral, near infrared and thermal infrared remote sensing monitoring method and hyperspectral remote sensing monitoring method which are sensitive to moisture change were selected to summarize the advance in monitor agricultural drought research by analyzing the two typical land use types of soil and vegetation. The limitations and applicability of different methods for each category were systematically summarized and described. Thirdly, the existing bottlenecks and difficulties in current research were discussed. Finally, in order to provide a reference for quantitative monitoring and analysis of the agricultural drought, the future research directions were equally proposed.
2019 Vol. 39 (04): 1005-1012 [Abstract] ( 294 ) RICH HTML PDF (934 KB)  ( 309 )
1013 Synthesis and Luminescence Properties of Sr2-x-yAl2SiO7x%Sm3+, y%Li+ Phosphors
WANG Qing-ling, Dilare Halimulati, SHEN Yu-ling, HE Jiu-yang, Aierken Sidike*
DOI: 10.3964/j.issn.1000-0593(2019)04-1013-05
At present, aluminosilicates have attracted extensive attention because of their stable chemical properties and easy availability of raw materials, which have become an effective substrate for luminescent materials. Among them, barium aluminosilicate (Sr2Al2SiO7) belongs to the tetragonal system and has a stable crystal structure. As a commonly used activator, Sm3+ has characteristic peaks distributed in the band of 300~750 nm. Some characteristic excitation peaks are located in the near-ultraviolet region and have strong absorption in the near-ultraviolet region. Therefore, using Sr2Al2SiO7 as a matrix and Sm3+ as an activator, a red phosphor meeting the LED requirements can be prepared. In this work, a series of Sr2-x-yAl2SiO7x%Sm3+, y%Li+ phosphors were synthesized by high temperature solid phase method. The crystal structure, luminescence properties and internal quantum efficiency of the sample were characterized and measured by X-ray diffraction (XRD), photoluminescence spectroscopy (PL), and absolute quantum efficiency measurement system, and the XRD of the sample was refined and the color purity was calculated. The results show that the synthesized samples are all single-phase Sr2Al2SiO7, and do not cause phase transformation after doping with Sm3+ and charge compensator Li+. Relative to the other cations Sm3+(r=1.079 Å), Li+(r=0.920 Å) and the radius of Sr2+(r=1.260 Å) are the closest, so the two ions are more easily substituted for the Sr2+grid. The two ionic radius is smaller than Sr2+ to reduce the crystal structure parameters a, b, c and v of the sample. The best excitation peak of the sample is at 403 nm, which shows a blue shift of 3 nm compared to the excitation peak of Ca3Y2(Si3O9)2∶Sm3+, indicating that the sample has strong absorption under near-ultraviolet light. That is beneficial for applications in the field of lighting. Under the excitation of 403 nm near-ultraviolet light, it can be seen that the emission peak of Sm3+ ions is located at 564 nm (4G5/26H5/2) and 601 nm (4G5/26H7/2) in the range of 500~750 nm. ), 648 nm (4G5/26H9/2) and 713 nm (4G5/26H11/2), of which the intensity of the 601 nm emission peak is the largest, which makes the sample appear strong orange red color. The emission peaks are cleaved at 607 and 618 nm because the interaction of the crystal fields causes energy level splitting. The intensity of the emission spectrum of the single-doped Sm3+ increases first and then decreases with the increase of the concentration, and reaches the strongest when the doping concentration is 2%. Using the energy transfer critical distance formula proposed by Blasse, the critical distance RC≈19.734 Å is calculated, which indicates that the concentration quenching is caused by the multi-level interaction between Sm3+ ions. According to the Dexter theory, the multipole interaction function θ≈6 is calculated, indicating that the concentration quenching mechanism of Sr2-xAl2SiO7x%Sm3+ is an electric dipole-electric dipole (d-d) interaction. In order to further increase the luminescence intensity, the charge compensator Li+ is doped to balance the internal charge of the crystal. The experimental results show that the optimum doping concentration of Li+ is 2%, and the luminescence intensity is increased by 2 times compared with the absence of charge compensator, and the internal quantum efficiency is tested to be 43.6%. Fluorescent pink coordinates are in the vicinity of (0.60, 0.39), located in the orange-red region, with a higher color purity (about 92.2%). The phosphor has potential applications in the red component of trichromatic white LEDs.
2019 Vol. 39 (04): 1013-1017 [Abstract] ( 201 ) RICH HTML PDF (2714 KB)  ( 102 )
1018 The Influence of Deep Trap on the Efficiency Decrease in PhOLEDs Based on Double Dopants Strategy
WANG Hao1, 2, ZHAO Su-ling1, 2*, XU Zheng1, 2, SONG Dan-dan1, 2, QIAO Bo1, 2, WANG Peng1, 2, ZHENG Wei-ye1, 2, WEI Peng1, 2
DOI: 10.3964/j.issn.1000-0593(2019)04-1018-07
In this paper, in order to study the effect of trapped carrierson the efficiency decrease in PhOLEDs based on double dopants strategy, threegroupsof devices, in whichthehostwas 4,4’-bis(N-carbazolyl)-1,1’-biphenyl (CBP) andtheguestswere tris(2-phenylpyridine) iridium(Ⅲ) (Ir(ppy)3),tris(1-phenylisoquinolinato-C2, N)iridium(Ⅲ)(Ir(piq)3)andpoly[[4,8-bis[(2-ethylhexyl)oxy]benzo[1, 2-b:4,5-b′]dithiophene-2, 6-diyl][3-fluoro-2-[(2ethylhexyl)carbonyl]thieno[3, 4-b]thiophenediyl]] (PTB7), with the emitting layer of CBP∶Ir(ppy)3, CBP∶Ir(ppy)3∶Ir(piq)3 or CBP∶Ir(ppy)3: PTB7 were prepared by spin-coating method utilizing the double dopants strategy to realize high performance PhOLEDs. Transient photoluminescence measurement was used to test the lifetime of the films with different doping ratios. Asthe concentration of Ir(piq)3 increased, the lifetime of green emission became shorter which indicated that internal energy transfer between the dopants existedwhen the doping ratioofthe Ir(piq)3 was at a low value. When the concentration of Ir(piq)3 increased to 100∶3 and 100∶5, the luminescence of the dopants became independent, in which the internal energy transfer could be negleted. The devices with PTB7 or Ir(piq)3 performed significantly lower power efficiency compared with Ir(ppy)3 only devices, in which the PTB7 and Ir(piq)3 had become the traps which would influence the perfomance of the devices. Transcient electroluminanscence was investigated to penetrate how the trapped charges work in the double doped devices. When the device was driven by a pulse power, a spike occured when the reverse bias turned on. This was because that the trapped charges were released and then recombined under a high reverse bias. The results showed that the device with more Ir(ppy)3 showed weaker spike which indicated that charges trapped by the Ir(piq)3 reduced, and as the concetration of the Ir(ppy)3 increased, the sipke became weaker. This was mainly because that the Ir(ppy)3 could transmit charges, which would reduce the trapped charges in Ir(piq)3. Through the transicient electrolu minescence mesurement, we also found that the spike would decay faster when suppllied a higher reverse bia which was caused by the deep trapped charges releasing and then excerbate the triplet-polaron quenching (TPQ) effect. Hence, the material with deep energy level would trap a large number of charges and then aggravate the interaction between the triplet exciton and polaron, causing the efficiency decrease and roll-off in the PhOLEDs based on double dopants strategy.
2019 Vol. 39 (04): 1018-1024 [Abstract] ( 182 ) RICH HTML PDF (5044 KB)  ( 70 )
1025 The Research of the Instantaneous Spectral Performance Measurement for a Tunable Semiconductor Laser
AN Ying1, WANG Chun-lei2
DOI: 10.3964/j.issn.1000-0593(2019)04-1025-05
The instantaneous spectral characteristics of semiconductor lasers during the tuning process, such as the instantaneous wavelength, tuning rate, power, line shape, and linewidth, affect the accuracy of optical precision measurements and coherent optical communication systems that use tunable lasers as their light sources. Nevertheless, a method that can measure their performance simultaneously has not yet been reported. The purpose of this paper is to provide a novel method for the measurement of the instantaneous spectral performance of a semiconductor laser using time-frequency analysis. We designed a short-delayed self-heterodyne measuring system, described the time-frequency distributions of a laser’s optical field and the beat signal, determined the relationship between a laser’s instantaneous spectral performance during tuning and the parameters of the beat signal, and obtained the time-varying optical power spectrum of a semiconductor laser under continuous injection current tuning. The proposed short-delayed self-heterodyne measuring system used a Mach-Zehnder interferometer (MZI) with an optical path difference (OPD) of 10 cm. The tunable semiconductor laser (FRL15DDR0A31-18950, Furukawa) was tuned using a sawtooth injection current with an amplitude of 20 to 120 mA and a frequency of 1 kHz. According to the principle of coherent measurement, we considered a beat voltage as a superposed oscillation signal consisting of three components: the DC voltage signal, the noise, and the pure beat signal. The DC signal is directly proportional to the power of the laser. The noise generated from the laser’s phase variation can be used to calculate the linewidth and the line shape of the semiconductor laser. The pure beat signal is a mono-component amplitude and frequency modulation (AM-FM) signal, which can be named the carrier; its frequency is closely related to the wavelength of the laser. Using the trend local mean decomposition method, the instantaneous power, wavelength, tuning rate, and linewidth of a semiconductor laser were confirmed simultaneously during the continuous tuning process. The beat signal cut off the relaxation section is an oscillation with an increasing trend in the voltage as the injection current increases from 60 to 115 mA, in this range of changes, the power grows linearly from 5.16 to 10.6 mW, the wavelength changed linearly from 1 579.2 to 1 579.6 nm during the tuning process, the tuning rate increased from 0.004 8 to 0.011 5 nm·mA-1 and the instantaneous linewidth of the semiconductor laser ranges from 852.55 to 954.95 kHz during the entire duration. The results indicated that the time-varying spectral performance of a semiconductor laser can be obtained more accurately and conveniently. This instantaneous spectral performance measurement method based on the short-delayed self-heterodyne measuring system and time-frequency analysis can help in precisely obtaining the instantaneous characteristics of a semiconductor laser during the tuning process and requires only a simple optical system. This method makes possible a deeper and more fundamental understanding of the dynamic workings of a tunable laser, and we believe it should be widely applied.
2019 Vol. 39 (04): 1025-1029 [Abstract] ( 257 ) RICH HTML PDF (2208 KB)  ( 106 )
1030 Spectroscopic Studies on the Natural Leather and Artificial Leather in Terahertz Band
LONG Sha1, ZHANG Hua2, SONG Zhe-yu2, 3, YAN Shi-han2*, CUI Hong-liang2, 4
DOI: 10.3964/j.issn.1000-0593(2019)04-1030-06
A huge demand and supply gap existed in the market about leather identification. The nondestructive detection method of different kinds of leather, especially different kinds of natural leather, has important application value. The terahertz (THz) transmission spectra of different kinds of natural leather and artificial leather have been systematically investigated and compared by THz time-domain spectroscopy (THz-TDS). In the range of 0.2 to 1.5 THz, the THz absorption coefficient and refractive index of natural leather are generally greater than those of artificial leather, and those of reptile leather, fish leather and mammal leather gradually decreased. There existed a turning point at about 60 ℃ in the amplitude change of THz time-domain spectroscopic curve during the heating process of natural leather from 25 to 80 ℃ with different variation tendency to pigskin, cowhide and sheepskin respectively, while it is absent to artificial leather. Further, the THz spectrum feathers of major components of leather, collagen, Polyvinyl chloride (PVC) and Polyurethane (PU) have been characterized to verify the cause of the difference of leather THz spectrum. The THz absorption coefficient and refractive index of collagen are greater than those of PVC and PU. The inflection point appears to collagen, but not to PVC during the same heating process. The characteristics of the THz spectrum of the composition of leather, collagen, PVC and PU have the similar numerical trends and changes, which indicates that the difference of the THz spectrum between different kinds of leather is mainly due to the difference in its composition. The work illustrates that the THz-TDS could be used to label-free distinguish artificial leather from natural leather and differentiate varieties of natural leathers from reptiles, mammals and fish.
2019 Vol. 39 (04): 1030-1035 [Abstract] ( 196 ) RICH HTML PDF (4180 KB)  ( 91 )
1036 The Study on the Mechanism of Fluorine Transformation between Water and Rock (Soil) in Seawater Intrusion Areas Based on FTIR Spectrum
JIA Cui-ping1, CHEN Qiao2*, WEI Jiu-chuan2*, WANG Hong-mei3, SHI Long-qing2, NING Fang-zhu3, LIU Song-liang3, YANG Meng-yuan1, XUE Xin1, DONG Fang-ying2, JIA Zhi-wen2, JI Yu-han2
DOI: 10.3964/j.issn.1000-0593(2019)04-1036-05
Drinking-water fluorosis and seawater intrusion are common phenomena along coastal zones. The groundwater property variation evoked by seawater intrusion has the potential effect on fluorine transformation of rock (soil), but it lacks the direct simulation experiments, and the mechanism of fluorine transformation is still unclear. The static simulation experiments of fluorine transformation of sediments in the aquifers were performed by simulating the seawater intrusion process with the mixture of fresh water, seawater, brine water and laboratory solutions, and the FTIR spectrum of sediments was compared. By this way, the laws and mechanism of the effect of seawater intrusion on rock (soil) fluorine transformation are expected to be detected. The results are gained as follows: the orders of the fluorine transformation ability are: seawater>1∶1 fresh water and seawater>fresh water, and brine water>1∶1 fresh water and brine water>fresh water. The more fluorine in rock(soil) transforms with the more mixture of seawater or brine water. The sediments show higher ability of fluorine transformation with the higher levels of NaCl and NaHCO3, and with the lower levels of CaCl2. The intensity of Si—O—Si stretching vibration peak increases, that of bending vibration of fluorapatite decreases, and that of O—H adsorption peak doesn’t change with the higher levels of NaCl, but the opposite case occurs with the higher levels of NaHCO3, which indicates the fluorine migration mainly by the OH--F- exchange in NaHCO3 solution and instead by Si substitution of Si—O—Si bond in NaCl solution. The intensity of Si—O—Si stretching vibration peaks is weakened and that of fluorapatite bending vibration increases with the higher levels of CaCl2, indicating that Ca2+ can restrain the rock(soil) fluorine transformation. Meanwhile, the intensity of Si-F bending variation peak decreases and Si—O bending variation peak moves towards the low wavenumber with the increase of NaCl and NaHCO3 concentrations and the decrease of CaCl2 concentration. The 1 460 and 1 420 cm-1 CO2-3 absorption peaks occur when the sediment interacts with 1 mol·L-1 CaCl2 because of the CO2 mixture. The sediment has the higher intensity of 1 460 cm-1 absorption peak and the new 875 cm-1 absorption peak when interacting with 1 mol·L-1 NaHCO3. But the sediment has no CO2-3 absorption peaks when interacting with seawater, brine water and NaCl solution. These facts indicates no fluorite (CaF2) dissolution. Thus, the alkaline, high Na+ and low Ca2+ conditions due to seawater intrusion lead to the high fluorine-leaching ability of rock(soil), which should be the important dynamics of high-fluorine groundwater along coastal zones.
2019 Vol. 39 (04): 1036-1040 [Abstract] ( 244 ) RICH HTML PDF (2227 KB)  ( 79 )
1041 Model Transfer Method of Fresh Jujube Soluble Solids Detection Using Variables Optimization and Correction Algorithms
SUN Hai-xia, ZHANG Shu-juan*, XUE Jian-xin, ZHAO Xu-ting, XING Shu-hai, CHEN Cai-hong, LI Cheng-ji
DOI: 10.3964/j.issn.1000-0593(2019)04-1041-06
The difficulty of sharing detection models built by different instruments is common in the quality inspection and classification of fruits. In the study, the “Huping” jujube was used as the research object, and the transfer method of the soluble solids content (SSC) detection model between instruments was explored using visible/near infrared spectroscopy. First, the spectral information of samples was collected using two instruments produced by American Analytical Spectral Device. Based on the original, Savitzky-Golay first derivative processed and standard normal variable transformed spectrum, SSC detection models were established by least squares-support vector machines (LS-SVM), respectively. The prediction ability of the three methods for the spectra acquired by different instruments was poor. The built model by the original spectrum of the master instrument was optimal in predicting spectra from the same instrument. The determination coefficient (R2p) and the root mean squared error of prediction (RMSEP) were 0.73 and 1.36%, respectively. Next, the Kennard/Stone algorithm was used to select standard samples. The Shenk’s, direct standardization (DS) and slope/bias (S/B) algorithm were used for model transfer, respectively. Then, according to the regression coefficient, the sensitive wavelengths of the master instrument (24) and the slave instrument (28) were extracted. 24 single variables (SV), 23 common variables (CV) and 29 fusion variables (FV) were selected, all of which contained the main absorption bands of SSC. LS-SVM detection models of the master instrument were respectively established by the preferred variables, which (R2p=0.78~0.80, RMSEP=1.07%~1.13%) was better than the model built by the full wavelength for the prediction result of the master instrument. However, the model failed in predicting spectra from different instruments (RMSEP=6.62%~7.88%). Finally, based on the wavelength position shift and the absorbed property of molecular vibration, these algorithms named as common variable-subtraction correction (CV-MC), single variable- subtraction correction, fusion variable-subtraction correction and common variable-wavelength correction (CV-WC) were respectively proposed for model transfer. These methods were compared with SV-Shenk’s, CV-Shenk’s, FV-Shenk’s, SV-DS, CV-DS, FV-DS, SV-S/B, CV-S/B and FV-S/B algorithms. The results showed that the prediction results (R2p=0.03~0.34, RMSEP=2.44%~4.67%) were poor when the model was transferred by the full-band. Using the model built by the preferred variables, the results transferred by SV-Shenk’s, CV-Shenk’s and FV-Shenk’s were poor, and the results transferred by other algorithms (R2p=0.47~0.73, RMSEP=1.30%~1.90%) were better than the full wavelength. The CV got better transfer results than the SV and the FV, and the CV-MC result was the best (R2p=0.73, RMSEP=1.30%). The predicted result after CV-WC transfer (RMSEP=1.62%) was similar to CV-DS and CV-S/B. The research indicates that both CV-MC and CV-WC are effective model transfer algorithms, which are of great significance to establishing a common jujube quality detection model between different instruments.
2019 Vol. 39 (04): 1041-1046 [Abstract] ( 292 ) RICH HTML PDF (1992 KB)  ( 118 )
1047 A Variable Selection Method Based on Ensemble-SISPLS for Near Infrared Spectroscopy
LI Si-hai1, ZHAO Lei2
DOI: 10.3964/j.issn.1000-0593(2019)04-1047-06
Near-infrared spectroscopy has the characteristics of high-dimensional small sample,which means the number of variables is by far larger compared to that of samples. Variable selection is an effective method to improve the robustness and interpretability of quantitative analysis models of near-infrared spectroscopy. Sure Independence Screening (SIS), an effective feature selection method for ultrahigh dimensional space based on marginal correlations between each predictor and response, is widely used for variable selection of gene microarray data. SIS has the ability to reduce the dimensionality of data to the size of the sample, which is comparable to the reduction ability of LASSO. In a fairly general asymptotic framework, the use of SIS with the sure screening property means that all the significant variables remain after employing the variable screening method with probability tending to one. The variable selection method, based on sure independence screening combined with partial least squares regression (SIS-SPLS), is an iterative SIS method. Firstly, the SIS method is used to complete the initial selection of significant variables, then the stepwise forward selection is carried out on the basis of the marginal correlation of selected significant variables: the partial least squares regression model is established, and the final variable selection result is determined according to the Bayesian Information Criterion (BIC). SIS-SPLS implements an incremental screening of important variables in the stepwise forward selection manner. As the number of latent variables increases and the residual decreases gradually, the number of variables selected by SIS-SPLS will stay steady. Whereas, the evaluation of the importance of variables only by the marginal correlation, when the number of spectral variables is much larger than that of samples, will make the selected variable still large in number, or make the robustness of the variable selection results unsatisfactory. To improve the robustness of variable selection results in the case of small samples, a new variable selection method based on ensemble learning, the SIS method and partial least squares regression (Ensemble-SISPLS) was developed in this paper. First, using the bagging ensemble strategy, the bootstrap method was adopted to resample at random on the calibration set. The variable selection was performed by SIS-SPLS on each calibration subset. The variable selection results of all the calibration subsets were aggregated together by the vote rule. The variable whose frequency was greater than the given threshold was selected and the partial least squares regression model was established to calculate the root mean square error of the 5-fold cross validation. The grid search method was utilized to optimize the two key parameters of the frequency threshold and the number of latent variables. Based on the cross-validation root mean square error and number of variables of the sub-models, the sub-model performance was comprehensively evaluated, and the variables included in the optimal sub-model were treated as the final variable selection result. The variable selection experiments were respectively performed on the Corn dataset and the Angelica sinensis dataset, several variable selection methods such as Ensemble-SISPLS, SIS-SPLS and UVE-PLS were compared in selected variable number and model robustness. A total of 77 Angelica sinensis samples were collected from Minxian and Weiyuan Counties in Gansu Province. Near infrared spectra of all samples were obtained through a Nicolet-6700 near-infrared spectrometer for the prediction of ferulic acid content in Angelica sinensis. The number of selected variables, RMSEP and the coefficient of determination of the Ensemble-SISPLS method on the Corn dataset were 22, 0.000 8 and 0.999 8 respectively; the number of selected variables, RMSEP and the coefficient of determination of the SIS-SPLS method on the Corn dataset were 97, 0.007 3 and 0.998 8 respectively. The number of selected variables, RMSEP and the coefficient of determination of the Ensemble-SISPLS method on Angelica sinensis dataset were 24, 0.018 1 and 0.996 3 respectively; the number of selected variables, RMSEP and the coefficient of determination of the SIS-SPLS method on Angelica sinensis dataset were 38, 0.022 6 and 0.994 3. The results showed that the Ensemble-SISPLS method further improved the robustness and predictability of the variable selection result. The Ensemble-SISPLS method which combines the variable selection ability of the SIS-SPLS method and the good generalization capacity of ensemble learning can improve the robustness of variable selection. In addition, the evaluation criteria of sub-models manage to make an optimal compromise between the prediction performance and the number of selected variables, which reduces the number of selected variables to some extent and at the same time improves the interpretability of the model.
2019 Vol. 39 (04): 1047-1052 [Abstract] ( 221 ) RICH HTML PDF (2674 KB)  ( 93 )
1053 Spectral Characteristics of Natural and Heated Blood-Red Ambers
XIAO Rui-hong1, WANG Li-sheng1, CHEN Wen-jun2, SHI Guang-hai2*
DOI: 10.3964/j.issn.1000-0593(2019)04-1053-06
Blood-red amber is the kind of amber with red coloration, which is so popular in jewelry market. Natural blood-red amber is rare and expensive. Anyway, there is so much heat-treated blood-red amber emerges to make consumers confused. So it is an urgent task to distinguish heat-treated amber from the natural one. In this work, natural and heated blood-red amber samples were tested by conventional gemmological methods, infrared spectrometer and UV-Vis spectrophotometer, including 4 natural blood-red amber samples and 9 heat-treated blood-red amber samples. The blood-red amber samples were all tested in Hebei GEO University. The NICOLET is5 Fourier transform infrared spectrometer was used to do the infrared spectrum test. And the UV- visible spectrum was tested by GEM-3000 UV- visible spectrophotometer. The results indicated: The average relative density of the heated blood-red ambers was slightly smaller, for the average relative density of the natural blood-red amber samples was around 1.075 compared to 1.045 for the heated ones. The heated blood-red amber samples have no fluorescence under long wave and short wave ultraviolet light, while the natural ones appear weak blue fluorescence under the long wave ultraviolet lamp. The internal fluid inclusions of heated blood-red amber samples are broken and almost all burst into tree branch shape and disc shape. The surfaces of the heated blood-red ambers are widely developed in turtle cracks, and the red color, with red spots and streaks, is darker in the fissure than anywhere else. And the colorations are attached to the surface of heated blood-red amber samples. The internal fluid inclusions of the natural blood-red ambers are rarely burst. The red color distribution on natural blood-red ambers is uniform and natural, with little cracks for being weathered. Heated and natural ambers have obvious differences in relative density, UV fluorescence and inclusions, etc. The basic molecular skeletons of blood-red amber samples have not been seriously damaged after heated. The differences between heated and natural ambers lie on the aspects of intensities and locations of infrared absorption peaks at 2 930, 1 724,994,1 157 cm-1. The peaks at 2 930 cm-1 in heated blood-red amber samples, which is implication of saturated C—H asymmetric stretching vibration, are less intense than that in natural blood-red amber samples. There is enhancement in the intensity of peaks at 1 724 cm-1, indicating C=O bond, for heated blood-red ambers comparing the natural ones with a larger locations. Peaks at 1 029 and 975 cm-1 are signals for C—O stretching vibrations in infrared spectrum. The peaks of heated blood-red ambers trend to merging to a single one peak at these two points with broad width and high intensity, while the peaks of the natural ones appear thin and short. The peaks at 975 cm-1 of the heated blood-red ambers shift to around 997 cm-1 obviously. Peaks at 1 158, 1 227 and 1 180 cm-1 of natural blood-red ambers can be found, while there are single peaks with no shoulder peaks at 1 160 cm-1 of heated blood-red ambers. From 1 457 to 1 376 cm-1 the absorption peak intensities of natural amber samples are much higher than those of heated ones. And the natural blood-red amber samples showed downward trends in IR-spectrum, while heated amber showed a horizontal or horizontal upward trends. The absorption peaks of heat-treated amber samples from 975 to 1 029 cm-1 merge into wide single peaks, which is the key evidence to identify natural and heated blood-red ambers. The difference of the infrared absorption peaks between heated and natural ambers is speculated to be mainly caused by the breaking of C—H,C=C bond and the increasing of C—O,C=O and other oxygen bond structure. UV-Vis spectra of blood-red amber samples revealed: in the turning region of 660 nm, the turning areas of natural blood-red amber samples are greater than the heated amber samples.
2019 Vol. 39 (04): 1053-1058 [Abstract] ( 309 ) RICH HTML PDF (2753 KB)  ( 77 )
1059 Study on Soil Organic Matter Prediction Model Based on Moisture Correction Algorithm and Near Infrared Spectroscopy
HU Xiao-yan, CUI Xu, HAN Xiao-ping, ZHANG Zhi-yong, QIN Gang, SONG Hai-yan*
DOI: 10.3964/j.issn.1000-0593(2019)04-1059-04
Soil organic matter (SOM) is a necessary nutrient for plant growth and an important parameter for Soil property detection. Rapid and efficient acquisition of soil organic matter information is of great importance to the development of fine agriculture. Near infrared spectrum technology, which has the advantages such as rapidness and low cost, is widely applied to the measurement of soil organic matter, however, the soil moisture in the near infrared spectrum (780~2 500 nm), has a strong absorption properties in detection of soil organic matter formed certain interference. This study analyzed the characteristics of near-infrared absorbance spectra of 50 soil samples at different moisture contents (about 17%, 15%, 10%, 5%, and dry soil), and constructed MDI (Moisture determination index) using moisture sensitive bands 2 210, 1 415, and 1 929 nm. On this basis, soil samples with different moisture contents were reconstructed to eliminate the effect of water on the prediction model of soil organic matter. The results are as follows: (1) the absorbance spectrogram after MDI correction and reconstruction is similar to the corresponding absorbance spectrogram of dry soil samples, which can reflect the characteristics of dry soil samples. (2) By using Partial least square (Partial further squares, PLS) method to establish the dry soil organic matter of soil sample quantitative prediction model, and the reconstruction after the soil samples obtained from different moisture content prediction, the statistical parameters are: prediction correlation coefficient (RP) 0.90, standard error (SEP) 0.802 and the root mean square prediction error (RMSEP) 1.09; Compared with the original prediction results without MDI correction, the correlation coefficient increased by 0.032, the prediction standard error decreased by 0.113, and the prediction root mean square error decreased by 0.25. Results showed that the moisture correction algorithm proposed in this study can reduce the moisture content of soil organic matter prediction of interference, improve the use of dry soil of soil organic matter quantitative prediction model to predict the precision of different moisture content of soil samples, can be based on near infrared spectrum technology spread and provide theoretical basis for real-time measurement of soil organic matter.
2019 Vol. 39 (04): 1059-1062 [Abstract] ( 270 ) RICH HTML PDF (2206 KB)  ( 126 )
1063 A Study on Remote Sensing Inversion of Soil Salt Content in Arid Area Based on Thermal Infrared Spectrum
XIA Jun1, ZHANG Fei2
DOI: 10.3964/j.issn.1000-0593(2019)04-1063-07
The soil salinization has faced a serious threat to the ecological environment in arid areas, and it is of great significance to quantitative inversion of the salt content of soil by remote sensing technology. In this paper, we gathered the farmland soil and salt crystal in Ebinur lake watershed, to prepare into soil samples with different salt content (the proportion of salt and saline soil: 0.3%~30%) in the laboratory. We measured the thermal infrared emissivity spectral of soil samples using 102F FTIR spectrometer, and through the Planck function fitting to obtain soil emissivity data, and then used the Gaussian filter method for smoothing emissivity curve to eliminate the background and noise effects. The saline soil emissivity spectral curve features were as bellow. The emissivity spectrum curve of soil with different salt content was basically consistent in shape and change tendency, and with the increase of salt content, the value of emissivity increased. Soil salinity factors had inhibitory effect on Reststrahlen absorption characteristics, which would be weakened with the increase of salt content, that presented as the depth of the asymmetric absorption valleys decreased, but the position and width changed a little. Based on the correlation analysis of emissivity and salt content, we found that: It was positively correlated between thermal infrared emissivity and salt content of soil, with the maximum correlation coefficient being 0.899, and the corresponding waveband 9.21 μm; 8.2~10.5 μm was the most sensitive wave bands for soil salinity. Using monadic linear regression, multiple stepwise regression and partial least square method to construct the prediction model, the value of R2 were respectively 0.863, 0.879 and 0.958, and RMSE were respectively 3.853%, 3.334% and 1.911%. It was proved that these three kinds of methods had certain prediction ability for salt content of soil, but partial least square was the best method. The thermal infrared wave bands of ASTER, Landsat8 and HJ-1B satellite sensors were chosen for the emissivity spectrum simulation according to the spectral response function of the sensor, and the correlation analysis results showed: ASTER’s B10, B11 and B12 bands are sensitive to the salt factor with thermal infrared spectroscopy and have a high correlation with soil salinity, and their correlation coefficient are up to 0.706, 0.786 and 0.872 respectively. Furthermore, the prediction model of soil salt content based on ASTER thermal infrared wavebands was established through the multiple linear regression method, R2 and RMSE of the predicted model was 0.833 and 3.895%. At last, the results showed that: it is feasible to quantitatively inverse salt content of saline soil by satellite thermal infrared remote sensing, which will provide a new way and reference for the remote sensing monitoring of soil salinization in arid areas.
2019 Vol. 39 (04): 1063-1069 [Abstract] ( 185 ) RICH HTML PDF (1542 KB)  ( 205 )
1070 Influence of Spectral Characteristics on the Accuracy of Concentration Quantitatively Analysis by NIR
ZHAO Zhe1, 2, 3, WANG Hui1, WANG Hui-quan1, 2, 3*, HE Xin-wei1, MIAO Jing-hong1, 2, WANG Jin-hai1, 2*
DOI: 10.3964/j.issn.1000-0593(2019)04-1070-05
In order to solve the problem of measurement blindness caused by the lack of measurable analysis in the the near-infrared spectroscopy, we can roughly estimate the analytical error of the concentration of the tested substances using the spectral characteristics of near-infrared spectroscopy under the known conditions of measurement, sample types, components under analysis and modeling and analysis methods,before a large number of samples were collected by near-infrared spectroscopy and concentration data measured by standard method. In the research, two important parameters, ESNR and OC, were proposed and tested. ESNR reflects the proportion of the component absorbance to the total absorbance, while OC reflects the overlap degree between near-infrared spectral curves of the components. We got the relationship between spectral characteristics and concentration analysis error when using the classical partial least squares regression in spectral analysis to establish quantitative analysis model through theoretical simulation. The relationship between ESNR and OC and the concentration of analyte (RMSE) was calculated respectively, and the independence of the two spectral parameters was also studied. The results of theoretical analysis were used to measure the concentration of aqueous ethanol solution between 8% and 12%, and compared with the actual results of near infrared spectroscopy. The relationship between the spectral characteristics and the concentration analysis errors when using partial least squares regression to establish a quantitative analysis model was obtained through theoretical simulation. ESNR is inversely proportional to RMSE, and OC is in a non-linear monotonic relationship with the measured component analysis error, and the independence of ESNR and OC was verified. The quantitative relationship between ESNR and OC and spectral concentration error was discussed by theoretical calculations and near-infrared spectroscopy of ethanol aqueous solution. The RMSE of ethanol concentration was 0.3% which was estimated by theoretical analysis, and the RMSE of near infrared spectroscopy was 0.32%. The relative error was 6.67%. We have realized the quantitative calculation and experimental verification of the theoretical error of the content of the tested components based on near infrared spectroscopy under the conditions of the measurement conditions, the types of samples, the components to be measured, and the methods of modeling and analysis. This study identified two spectral parameters that have a clear and quantitative relationship with the concentration of the measured component in NIR spectroscopy. The analytical accuracy empirical curve was established when using the classical partial least-squares regression in spectral analysis. In addition,the analysis of the measurable degree of the concentration of the components could also be tested by near infrared spectroscopy. The results showed the effectiveness of the ESNR and OC in this paper, as well as the analytical method of error prediction. This study provided an effective and rapid prediction method for the quantitative analysis of near infrared spectroscopy, and optimized the theory of measurable analysis of near infrared spectroscopy, which has a good guidance for the quantitative analysis of the concentration of near infrared spectroscopy.
2019 Vol. 39 (04): 1070-1074 [Abstract] ( 264 ) RICH HTML PDF (1467 KB)  ( 109 )
1075 An In-Situ Raman Spectroscopic Study of the Phase Transition of Anhydrite under High Pressures
XIONG Xin1, 2, YUAN Xue-yin2*
DOI: 10.3964/j.issn.1000-0593(2019)04-1075-05
Anhydriteis one of the most widely distributed sulfite on the earth. Inorder to investigate the phase transition pressure and transformation mechanism between anhydrite and high pressure anhydrite, and to constrain the p-T area where the anhydrite Raman pressure sensor is applicable, in this paper the phase transition between anhydrite and high pressure anhydrite and the Raman spectra of both polymorphs were investigated by using a hydrothermal diamond anvil cell and laser Raman spectroscopy. Our results showed that the phase transition from anhydrite to a high pressure monazite structure occurred at pressures around 2.3 GPa, and that the phase transition pressure varied during the compressing and decompressing processes, which suggested the transformation between anhydrite and high pressure anhydrite was reconstructive process with significant hysteresis. As reconstructive transformations were controlled not only by pressure and temperature, but also by kinetics and metastability of the structure, hence explaining the discrepancy among the phase transition pressures between anhydrite and high pressure anhydrite. In contrast to those of anhydrite, the Raman vibrations of high pressure anhydrite were characterized by shifting of the ν1 mode from 1 128.28 to 1 024.39 cm-1, and by splitting of the ν2 mode into 441, 459 and 494 cm-1, ν3 into 1 136, 1 148, 1 158 and 1 173 cm-1, and ν4 into 598, 616, 646 and 671 cm-1, which ca be used as identifications for the transformation from anhydrite to high pressure anhydrite. The splitting of the ν2~ν4 vibrations into more bands indicated that the SO4 vibrations in high pressure anhydrite were affected by more nearby atoms, which was consistent with the high pressure anhydrite crystal symmetry (monoclinic) being lower than that of anhydrite (orthorhombic). Within the stability pressure range of anhydrite, All observed Raman bands of the SO4 vibrations, except for the ν2, 416, shifted to higher frequencies with constant ∂ν/∂p rates, mean while the Raman peak intensities and shapes remained stable, which meant that the Raman peak fitting and pressure calibration results could be equally precise under different pressures. In addition, we also verified the reliability of the anhydrite Raman pressure sensor by measuring the shifting rate of the ν1, 1 085 Raman peak position of calcite with pressure, and the phase transition pressures from calcite to CaCO3-Ⅱ and from CaCO3-Ⅱ to CaCO3-Ⅲ.
2019 Vol. 39 (04): 1075-1079 [Abstract] ( 288 ) RICH HTML PDF (1839 KB)  ( 91 )
1080 Method and Application for Raman Spectra SNR Evaluation Based on Extreme Points Statistics
WANG Zi-ru1, LIU Ming-hui2, LIU En-kai1, DONG Zuo-ren2, CAI Sheng-wen1, YIN Lei1, LIU Feng1
DOI: 10.3964/j.issn.1000-0593(2019)04-1080-06
In recent years, portable spectrometer technology has developed rapidly. Compared with the traditional spectrometer, CCD spectrometer in the spectral collection of the way there have been two changes: (1) The signal is superposed and integrated to generate the spectrum, and the traditional SNR estimation method cannot obtain the detector fluctuation by a single detection. (2) For the spectral noise, the detector responses to random fluctuations and scanning repetitive errors are transformed into differences in pixel response of the CCD detector, detector random noise and mode noise related to the resolution of the optical system. Therefore, it is of great practical significance to propose a more adaptive spectral quality assessment method based on the measured spectrum. According to the changes of Raman spectrometer detector, we analyze the components of the collected spectral signal, and put forward the noise model assumptions of CCD spectrometer on the basis of the analysis. According to this assumption, different signal extremum frequencies are used to separate different noise pixels and the noise frequency mode is numerically simulated. The simulation results are consistent with the assumptions. On the basis of this, we propose and experimentally validate the method for evaluating SNR of Raman spectroscopy to estimate spectral line noise through spectral line spacing. The method includes the following two steps: (1) Collecting multiple measured spectra for superposition, counting the number of spectral extreme points corresponding to different frequencies in the superposition process, and obtaining the statistical results to separate the environmental noise and dark noise in the spectrometer; (2)Applying the above separation results, the statistical average of the spectral line extreme points corresponding to the dark noise in the measured spectrum is calculated, and then the SNR is calculated according to the formula in the text. After the preliminary preparation of step (1), the method can evaluate the random noise of the CCD Raman spectrometer through a single spectrum and evaluate the spectral SNR. In this paper, three Raman spectroscopy systems with the same optical structure and different CCD detectors are used to experiment. By using this method, the spectral quality is controlled by setting the SNR threshold, and a uniform spectral curve is obtained. Based on the method proposed in this paper, the SNR is fitted to the synchronization overlapping average algorithm, and the goodness of fit is up to 98%. The method can be used to evaluate the performance of Raman spectrometer and acquire real-time quality control of Raman spectrum. Theoretical and experimental results show that for the CCD detector-based Raman spectrometer, the SNR can be obtained based on this method when determining the sample and the characteristic peak. The method can also be used to compare different configurations of Raman spectroscopy equipment and as a standard to control the quality of spectra.
2019 Vol. 39 (04): 1080-1085 [Abstract] ( 240 ) RICH HTML PDF (3969 KB)  ( 143 )
1086 Optimization of a Near-Concentric Cavity Raman Spectroscopy System for Liquid Sample and Preliminary Results of CO2-3/HCO-3
SI Gan-shang, YANG De-wang, GUO Jin-jia*, LIU Qing-sheng, YE Wang-quan, ZHENG Rong-er
DOI: 10.3964/j.issn.1000-0593(2019)04-1086-06
It is of great significance to study the carbon cycle in the ocean for environmental monitoring and resource detecting. In this field, one of the most important topics is to study carbonate. There is no direct detection method to monitor carbonate in seawater, and most traditional detection methods for carbonate are indirect. For example: with seawater sample acidified by phosphoric acid, the carbonate in the sample can be converted into CO2 and then be detected. Raman spectroscopy can be used in in-situ detection and has great potential to detect the carbonate directly. But it’s sensitivity is still a limitation in the practical use of ocean detection. In the hope of developing an approach to directly detect the carbonate in the seawater, we build a near-concentric cavity Raman spectroscopy system and optimize the main parameters of the cavity (diameter=25.4 mm, reflectivity=99.66%@532 nm) including optical windows thickness of the liquid cell, the optical windows distance at two sides, and the focal length of the mirrors with simulation software. The results are listed as follows: (1)The number of the reflection is at a maximum when the focal length is 25 mm for the mirrors with diameter of 25.4 mm; (2) For the optical windows of the liquid cell, with smaller thickness, the light would be denser in the center of the cell, and the totally luminous intensity in the center plane of the near-concentric cavity would be larger; (3) with smaller distance between the optical windows, the light would be denser in the center of the cell, and the totally luminous intensity in the center plane of the near-concentric cavity would be larger; After optimization, the measurement of CO2-3 and HCO-3 solutions on different concentration levels is carried out using the optimized near-concentric cavity Raman spectroscopy system. The spectral signal was pretreated using second order differential and Gaussian filter, and then calibration curves were established using the peak intensity of the corresponding concentrations. The results showed good linear relationship between concentration of solution and signal intensity of Raman spectrum, with R2 of 0.994 and 0.998 for CO2-3 and HCO-3, respectively. We calculated the LODs using the 3 times signal-to-noise ratio. The results showed that the LOD for CO2-3 and HCO-3 is about 0.06 and 0.38 mmol·L-1 respectively. The LODs are lower than the typical concentrations of CO2-3 and HCO-3 in seawater, which are about 0.2 and 2 mmol·L-1 respectively. Compared to the current reported of the Raman spectroscopy system of in-suit ocean detection, the sensitivity of the system has increased by nearly ten times. So it is hoped to apply the system to the in-situ CO2-3 and HCO-3 detection inseawater.
2019 Vol. 39 (04): 1086-1091 [Abstract] ( 165 ) RICH HTML PDF (2946 KB)  ( 66 )
1092 Study on the Structural Properties and the Detection Performances of Thiacalix[4]arene-Based Micellar Self-Assembled Fluorescent Probe
LI Yuan-yi, WANG Bo, ZHANG Ying, HU Xiao-jun*, ZHANG Zhi, HU Xin-yan
DOI: 10.3964/j.issn.1000-0593(2019)04-1092-05
Heavy metal pollution in water is widely concerned because it threatens the ecological environment and human health. The fluorescent probe has been a research focus in this field due to the rapid and efficient detection for heavy metals. Generally, the fluorescent probe structurally includes a receptor recognizing a desired analyte and a fluorophore generating a signal response. It gradually has formed four kinds of structures, which are intrinsic, conjugate, ensembling and template-assisted self-assembled types. In recent years, micellar self-assembled fluorescent probes based on the self-assembly of acceptor and fluorophore in surfactant micelles have attracted attentions. This is due to their simple structure, easy preparation and direct application to water environment. In this paper, the micellar self-assembled fluorescent probes for the detection of Cu2+ ions were prepared through self-assembly of surfactant micelles. The p-tert-butylthiacalix[4]arene (TCA) was used as acceptor with excellent bonding property to copper ions. And pyrene, fluoranthene, anthracene, phenanthrene, perylene were used as fluorophore. The fluorescence quantum yields of the micellar self-assembled fluorescent probes were measured by the reference method. The micelle aggregation numbers were determined by the steady-state fluorescence method. At the same time, the influences of fluorophore species and compound surfactants were investigated on detection performances of the probes for Cu2+ ions by calculating the fluorescence quenching rate. The experimental results showed that the three surfactants, which are sodium dodecyl sulfate (SDS), Triton X-100 (TX-100) and polyoxyethylene lauryl ether (Brij35), had significant effects on fluorescence quantum yields of the probes. Their fluorescence quantum yields were in the range of 0.25~0.47. And they gradually increased. These indicated that the polarities of the microenvironment inside the micelles were changed by surfactant micelles. And the influences of different types of surfactants on the microenvironment polarity were different. The enhancement of the microenvironment polarity made excited pyrene more stable. The addition of acceptor TCA had little effect on the polarity of the microenvironment in which the fluorophore was located. And it didn’t have a significant influence on the fluorescence quantum yield. However, the micellar aggregation numbers of the probe markedly decreased after the addition of TCA. They were attributed to the fact that the amphiphilic receptor TCA molecules dispersed into the surfactant molecular layer through micelle self-assembly forming co-micelle structure. Thus, the aggregation state of the surfactant molecules was changed. The fluorophore had a significant effect on the detection performance of the probe for Cu2+ ions. Under the same conditions, the fluorescence quenching rates of the probes to detect Cu2+ ions respectively using fluoranthene, anthracene and phenanthrene as fluorophores were much higher than those of pyrene and perylene. This was mainly due to the different energies released by fluorophore radiative transitions from the excited state to the ground state. And the higher the matching degree with the energy required by the acceptor TCA to recognize Cu2+ ions, the greater the fluorescence quenching rate. The compound surfactants could obviously improve the detection performance of the fluorescent probe. When the mole ratios of non-ionic/anionic and non-ionic/cationic surfactants were 7∶3 and 1∶1 respectively, the fluorescence quenching rates were maximum. And the fluorescence quenching rates of the compound surfactants both were higher than those of single surfactant. These showed that the optimal compound ratios of different types of surfactant were quite different. But they both effectively enhanced the dispersibility and self-assembled performance of receptor and fluorophore. Moreover, they improved the detection performance of the probe for Cu2+ ions. The results of the thesis will provide a reference for the design and application of novel micellar self-assembled fluorescent probes.
2019 Vol. 39 (04): 1092-1096 [Abstract] ( 181 ) RICH HTML PDF (1946 KB)  ( 83 )
1097 The Temperature, Turbidity and pH Impact Analysis of Water COD Detected by Fluorescence Spectroscopy
ZHOU Kun-peng1, BAI Xu-fang1, BI Wei-hong2*
DOI: 10.3964/j.issn.1000-0593(2019)04-1097-06
In this paper, the COD standard liquid is used as the research object, and the water COD is detected by the chemometrics algorithm based on the fluorescence emission spectrum data of specific excitation wavelength. During the detection process, the influences of temperature, turbidity and pH on the fluorescence spectrum are analyzed, and the compensation correction is performed on the influence of the related parameters. Firstly, excitation-emission matrix (EEM) spectra of the COD standard solution whose concentration ranges between 1 and 55 mg·L-1 are collected by fluorescence spectrophotometer, after the scattering peaks are removed, the partial least squares based on the ant colony (ACO-iPLS) algorithm is used for extracting feature for the fluorescence emission spectra (Em=275~450 nm) at different excitation wavelengths (Ex=255~285 nm, with the interval 5 nm) and the least squares support vector machine algorithm with particle swarm optimization (PSO-LSSVM) is used to establish the prediction model. The results show that the determination coefficient of the validation set (R2p) of the fluorescence emission spectrum data model at different excitation wavelengths is within the range of 0.961 8~0.998 1, of which the effect of the fluorescence emission spectrum data model at Ex=270 nm is the optimal, and the determination coefficient (R2p) and the root mean square error of prediction (RMSEP) are R2p=0.998 1, RMSEP=0.348 3 mg·L-1, respectively. Secondly, the influences of temperature, turbidity and pH on the water COD detection by fluorescence spectrometry are analyzed, and the corresponding compensation model is obtained. The results demonstrate that the effect of temperature and turbidity on the fluorescence spectrum cannot be ignored, but the compensation model can be established to correct the interference effectively. The mean deviation (Bias) of fluorescence model after temperature compensation is 0.130 6 mg·L-1, and the influence of turbidity change on COD detection by fluorescence spectrometry can be well corrected after turbidity compensation, while the effect of pH range in 4~12.3 on the fluorescence spectrum is relatively small, so it can be ignored. Finally, combined with the analysis results of single influence factors, the effects of various environmental factors (temperature, turbidity and pH) on the detection of water quality COD by fluorescence spectrometry are analyzed. The result shows that after neglecting the influence of pH, the influences of temperature and turbidity on the fluorescence spectrum can be corrected effectively. The results of the paper can serve as reference for water quality parameter optical sensors in suppressing environmental factors during commissioning.
2019 Vol. 39 (04): 1097-1102 [Abstract] ( 344 ) RICH HTML PDF (3837 KB)  ( 112 )
1103 Study on Interaction between Resveratrol and Pepsin by Fluorescence Spectroscopy and Molecular Modeling
REN Guo-yan1, 2, 3, SUN He1, FAN Jin-ling1, NIU Xiao-li3, GUO Jin-ying1, WU Ying1, CUI Guo-ting1
DOI: 10.3964/j.issn.1000-0593(2019)04-1103-06
Resveratrol (RES) is a non-flavonoid polyphenols found in many plants, such as Vitaceae and Liliaceae. It is a natural active substance with variety biological and pharmacological functions and widely used in food and pharmaceutical field. Studies have shown that polyphenols had an interaction with digestive enzymes (such as pepsin, trypsin, etc.) in the process of digestion and absorption of organisms, resulting in changes in the biological activity of polyphenols and digestive enzymes and affecting the digestion and absorption of polyphenols and other nutrients. However, the mechanism of interaction between RES and pepsin (PEP) has rarely been reported. The attempt of this paper was to investigate the binding characteristics between RES and PEP at different temperatures by fluorescence spectroscopy, UV-Vis absorption spectroscopy, infrared spectroscopy (FT-IR) and molecular modeling technique. The experimental results provided important information for elucidating the action mechanism of RES and PEP. Fluorescence data revealed that the fluorescence intensity of PEP decreased regularly with the increase of RES concentration, indicating that RES had a fluorescence quenching effect on PEP. After RES was added, the UV-vis spectra of PEP changed significantly. The Kq value (the minimum quenching rate constant) at different temperatures were all much larger than 2.0×1010 L·mol-1·s-1(the maximum diffusion collision constant of the quenching agent on biological macromolecules). Moreover, Stern-Volmer quenching constant (KSV) gradually decreased with the increase in temperature. These results verified quenching mode between PEP and RES to be static. The value of the stoichiometric binding number approximately equals 1, suggesting that one molecule of RES combined with one molecule of PEP. The thermodynamic parameters indicated that RES could spontaneously bind with pepsin mainly through the hydrogen bonds and Van der Waals forces. Synchronous fluorescence and three-dimensional fluorescence results provided data concerning conformational and some micro-environmental changes of pepsin. According to the results from FTIR analyses of PEP, the content of β-sheet increased accompanying with significantly decrease of α-helix, and no obvious change of β-turn and random coil upon binding with RES. The presence of RES loosened the skeleton of pepsin. These secondary structure changes might lead to changes of the physiological function of pepsin, such as the enzyme activity. Finally, molecular docking further suggested that RES molecule binded within the active pocket of PEP mainly via the van der Waals forces and hydrogen bonds. There were the van der Waals forces between RES and residues Asp-32, Gly-34, Ser-35, Asn-37, Tyr-75, Gly-76, Thr-77, Ile-128, Ala-130 and Gly-217 of PEP, super conjugation between RES and residues Ile-128 and Asp-215 of PEP, and hydrogen bonds between RES and Ser-36, Asn-37, Ile-128 and Thr-218 of PEP. Various forces make RES and PEP form a more stable complex.
2019 Vol. 39 (04): 1103-1108 [Abstract] ( 198 ) RICH HTML PDF (2787 KB)  ( 113 )
1109 Application of Structure-Matched Phthalocyanines Associate as a Red-Emitting Fluorescent Probe in the Determination of Heparin at Nano-Gram Level
ZHOU Tao, DU Guang-xin, ZHENG Xiao, ZHANG Yan, HUANG Ping, DENG Ya-bin, LI Dong-hui*
DOI: 10.3964/j.issn.1000-0593(2019)04-1109-05
Heparin, a polyanionic bio-polysaccharide, has important clinical values. The development of simple, rapid and specific method for the detection of heparin has been being an attractive topic in the last decades. According to the principle of molecular association, a phthalocyanine-based ion-associate fluorescent probe was prepared, followed by the establishment of a novel fluorimetry for the determination of heparin with high specificity at nanogram level. Tetrasulfonated aluminum phthalocyanine (AlS4Pc), which emits strong red fluorescence is negatively charged, was found that its fluorescence could be dramatically quenched by a structure-matched cationic copper phthalocyanie (Alcian blue 8 GX) bearing a same parent structure and oppositely charged. Because of their highly matched molecular structures the two phthalynines, strong association is easy to occur through intermolecular force, leading to the formation of none-fluorescent associate. Based on this founding, a fluorescent probe of AlS4Pc-Alcian blue 8 GX associate was developed in this study. Screening experiments on carbohydrates showed that the fluorescence of AlS4Pc-Alcian blue 8 GX recovered when polyanionic bio-polysaccharide existed. The fluorescence recovery is particularly significant in the presence of heparin. We believe that this phenomenon could be attributed to the presence of a large number of sulfonate anion on the skeleton of heparin. The polyanionic structure leads to strong competitive binding to Alcian blue 8GX with AlS4Pc, resulting in the dissociation of AlS4Pc from the associate, and the fluorescence of the system restored. Based on the above findings, a highly sensitive and specific method for the determination of heparin by fluorescence enhancement was established. The molecular spectra (fluorescence and absorption spectra) of the system were investigated to deduce the mechanism of the formation of associate and the fluorescence recovery. The reaction parameters (including pH, reaction temperature, reaction time, usage of AlS4Pc and Alcian blue 8 GX) were optimized. Under the optimal conditions, the linear range of calibration curve is 6.0~600.0 ng·mL-1, and the detection limit is 5.7 ng·mL-1. A facile pretreatment method employing polar organic solvent as precipitant was developed to avoid the deviation in the detection of practical samples. In addition, the interference behavior of foreign substances on the determination of heparin was investigated comprehensively, which has made up for the deficiency in literatures. The proposed method has been applied to the determination of practical sample (heparin sodium injection) with satisfactory results. This study expends the application of fluorescent phthalocyanines as molecular optical probes in analytical sciences.
2019 Vol. 39 (04): 1109-1113 [Abstract] ( 188 ) RICH HTML PDF (1817 KB)  ( 57 )
1114 Analysis of Lycopene in Different Solvents by Spectrophotometry
LI Zhen-xia1, SHEN Huan-huan1, GAO Miao-miao1, QI Jiao1, LI Qing-yan2*
DOI: 10.3964/j.issn.1000-0593(2019)04-1114-04
In recent years, lycopene has been paid more and more attention due to its strong antioxidant activity and various health care functions. However, lycopene extraction and determination methods are complicated and difficult to be widely applied. In this study, using spectrophotometry, petroleum ether, acetone and methanol as solvent, methylene chloride as co-solvent, starting with the absorption spectrum differences to determine the maximum absorption wavelength, then, the absorbance of lycopene standard liquid with different solubility was determined at the maximum absorption wavelength and the standard curve was established to obtain the regression equation. The effect of the amount of dichloromethane and the extraction time on the lycopene extraction efficiency was investigated, and the simple and rapid determination method of lycopene by spectrophotometry was explored. The experimental results showed that the best method for the determination of lycopene by spectrophotometry is petroleum ether as solvent, wavelength 474 nm, addition of 5 mL of dichloromethane for solubilization and extraction time of 40 min.
2019 Vol. 39 (04): 1114-1117 [Abstract] ( 218 ) RICH HTML PDF (1435 KB)  ( 62 )
1118 A Sparse Constrained Graph Regularized Nonnegative Matrix Factorization Algorithm for Hyperspectral Unmixing
GAN Yu-quan1, 2, LIU Wei-hua1, FENG Xiang-peng1, YU Tao1, HU Bing-liang1, WEN De-sheng1
DOI: 10.3964/j.issn.1000-0593(2019)04-1118-10
The space resolution of hyperspectral image is influenced due to the restriction of sensor platform, which results in more than one material in one pixel. Such kind of pixel is called mixed pixel. The existence of mixed pixels restricts accurate analysis and application of hyperspectral images. Hyperspectralunmixing technique can factorize mixed pixels to pure material signatures (endmembers) and corresponding proportion (abundance), which makes more accurate material signature available. Unmxing is very important to accurate classification and identification, anomaly detection and quantitative analysis for hyperspectral imagery. Based on linear spectral mixing model, this paper develops an endmember and abundance sparse constrained graph regularized nonnegative matrix factorization (EAGLNMF) algorithm for hyperspectral imagery unmixing. The algorithm is based on nonnegative matrix factorization, and integrates graph regularization and both endmember and abundance sparse constraints to the object function. Graph regularization is used to consider the geometrical structure of the hyperspectral image and sparse constraints can demonstrate the inner manifoldstructure. First, the lost function of EAGLNMF is constructed, and VCA-FCLS method is used as initial value. And then, the value of the parameters is set, including weighting matrix of graph regularization, sparse factors for both endmember signature matrix and abundance matrix. At last, the iteration equations for endmember matrix and abundance matrix are both obtained, and stopping criteria is given. The algorithm does not require pure pixel in the hyperspectral image. In fact, there are little pure pixel in real hyperspectral imagerydue to the sensors platform. Thus, EAGLNMF algorithm provides a kind of solution for real hyperspectral imagery. The availability and effect of EAGLNMF are verified by synthetic data via four experiments. The experiments compare EAGLNMF with VCA-FCLS, standard NMF and GLNMF. Two metrics, spectral angle distance (SAD) and abundance angle distance (AAD) are used to compare the four methods. Experiment 1 is total comparison experiment of the four methods. SNR and the number of endmembers are constant, and the value of SAD and AAD are compared. Experiment 2 evaluates the influence of SNR. Different value for SNR and constant value for number of endmembers are given to different runs. Experiment 3 evaluates the influence of number of endmembers. Different value for number of endmembers and constant value for SNR are given to different runs. The experiment result shows that EAGLNMF method obtains more accurate result for both endmebers and abundance. Moreover, experiment 4 evaluates the influence of sparse factor between endmember signature and abundance. The result demonstrates that endmember sparse constraint shows a positive effect to unmixing. And, sparse factor between endmember signature and abundance shows effect to unmixing result. In addition, real AVIRIS hyperspectral image is applied to VCA-FCLS, standard NMF, GLNMF and the proposed EAGLNMF, and compared with the ground truth of USGS, the result shows that EAGLNMF obtains best unmixing result among the four algorithms and the accuracy of the estimated endmembers is good.
2019 Vol. 39 (04): 1118-1127 [Abstract] ( 224 ) RICH HTML PDF (5029 KB)  ( 106 )
1128 Application of Analytical Techniques of Spectroscopy on Cherts in Orogenic Belt and Its Geological Significances
CHEN Shuo1,3,4, SU Zhi-hua2, ZHOU Yong-zhang1,3,4*, YANG Zhi-jun1,3, LI Hong-zhong3,4*, ZHOU Wei-li3,4, ZHANG Yan-long3,4
DOI: 10.3964/j.issn.1000-0593(2019)04-1128-08
The Devonian cherts profile was developed in Lvhe area, Xunyang basin of southern Qinling orogenic belt, and the microfabric features based on spectroscopy characteristics clearly recorded information of diagenesis and later stage evolution of the cherts. Cherts in Lvhe area, Xunyang basin of southern Qinling orogenic belt were taken as object, by means of Raman spectroscopy,Fourier transform infrared spectroscopy and X-ray powder diffraction,and the results of this study showed that:low temperature quartz and a small quantity of carbonate minerals were the two main mineral phases of the cherts, and XRD analysis further proved the carbonate minerals were dolomites. Within the cherts in Lvhe area,Gauss fitting FWHM and Area values of the 463 cm-1 Raman shift of SiO2 texture confirmed that recrystallization had occurred in the SiO2 minerals. Alone with this process, variations of degree of order were triggered by fluid effects as well as the quartz itself. During the recrystallization process of the quartz, degree of order went up. The cherts were altered by later fluids, apart from the intersected late vein, the alteration reflected in that the closer to the edge of the fluids in the quartz, the higher the crystallinity and degree of order. In this study, alteration of cherts made by orogeny mainly reflected in two aspects:on the one hand,tectonic stress destroyed the continuity of the cherts and provides space for migration and intersection of later stage hydrothermal fluids;On the other hand,participation of the late fluids accelerated the recrystallization of quartz. In this study, infrared spectroscopy is capable of identifying mineral structure type systematically, and Raman spectrum analysis can reveal in situ microfabric characteristics, and XRD shows significant advantage in discriminating trace impurity minerals in cherts. These spectroscopy methods provide important demonstrations in studying the diagenetic evolution of the cherts.
2019 Vol. 39 (04): 1128-1135 [Abstract] ( 257 ) RICH HTML PDF (3266 KB)  ( 92 )
1136 Spectral Analysis of Main Mineral Pigments in Thangka
CEN Yi1, ZHANG Lin-shan1,2, SUN Xue-jian1*, ZHANG Li-fu1, LIN Hong-lei1, ZHAO Heng-qian3, WANG Xue-rui4
DOI: 10.3964/j.issn.1000-0593(2019)04-1136-07
As a work of art, Thangka has both high historical value and artistic value. The identification and analysis of the mineral pigments of the Thangka are of great significance to the identification, repair, digital archiving and reproduction of the Thangka. This is the first systematic spectral analysis of five kinds of main Thangka mineral pigment, commonly used in the process. Through an in-depth analysis of the spectral characteristics of mineral pigments, we summarized the spectral features of Thangka’s main mineral pigments. By comparing the spectral characteristics of the same mineral pigment powder, blend bone glue and pigment on the pigment, we found that the reflectance of the powder pigment decreases after the blending of bone glue, and there are two strong absorption peaks near 1 447 and 1 928 nm. When you paint the glue soluble on the cloth, with the reduction of water paste in the paint, the two peaks become weaker, and the absorption peak at 1 447 nm or even disappears. Therefore, the spectra of mineral pigment powder and pigment on the cloth are very close. Mineral pigment powder can be directly used in the analysis of the Thangka pigment spectra match and analysis in the later period. Red mineral pigments on Thangka are cinnabar, whose mineral composition is HgS. The reflectance in the visible band rises after the first drop, and there is a deep absorption valley near 500 nm (430~530 nm). After the rapid rise of red, the reflectance curve near infrared changes slowly, and there are weak absorption valleys in the vicinity of 1 940 and 2 250 nm. There are three main types of Thangka yellow mineral pigments: desert tan(realgar, orpiment), ochre and gold, whose main components are arsenic sulfide, iron oxide and gold. Their spectral characteristics are concentrated in the visible spectrum between 400~500 nm, and the absorption valley position and absorption depth of different pigments are different. Near infrared reflectance Ochre is low, and the 860 nm has appeared near the absorption peak; while desert tan, realgar and orpiment in near infrared and shortwave infrared spectrum show high values and flat curves, with two weak absorptions in the valley near 1 890 and 2 230 nm. The absorption valley of gold in visible band is narrow and shallow, which can be used as the basis to distinguish it. Thangka’s blue mineral pigment is azurite, which has strong absorption characteristics in 500~1 000, 1 500, 2 040, 2 285 nm and near 2 350 nm, and weak absorption characteristics in 1 885 and 1 980 nm. Thangka’s green mineral pigment is malachite, and the spectrum has a strong broad absorption feature in 550~1 000, 2 270 and 2 350 nm. Although the main mineral compositions of malachite and azurite are both copper carbonate, but the reflectance value of malachite in 900~1 900 nm increases slowly, and there is no absorption characteristic at 1500nm, which can be used to distinguish them. Thangka’s white mineral pigments are mainly clay and clam, respectively, calcium carbonate and kaolin-clay. In the visible spectral range, clam has a weak absorption characteristic in 370 nm, and the clay has two obvious absorption characteristics in the 370nm and 730nm, which can be used to distinguish them. In the short wave infrared and near-infrared spectrum, clay has obvious absorption characteristics in 1 425, 1 930 and 2 230 nm, while clam has obvious absorption characteristics in 1 930 and 2 320 nm, plus a weak absorption characteristics in 1 440 nm. As for the same mineral pigment powder, the larger the mineral powder particle is, the darker the color of the pigment will be, and the lower the reflectance of the spectral characteristics will be.
2019 Vol. 39 (04): 1136-1142 [Abstract] ( 193 ) RICH HTML PDF (4376 KB)  ( 87 )
1143 The Relationships between Uranium Polluted Leaf Reflectance Spectral Characteristics of Phytolacca acinosa Roxb. and Uranium Contents
ZHANG Yan, WANG Wei-hong*, ZHANG Wen-jun, LIU Lai
DOI: 10.3964/j.issn.1000-0593(2019)04-1143-05
A pot cultivation experiment was carried out to investigate the relationship between uranium contents in leaves of Phytolacca acinosa Roxb. and original spectral datum and first derivative spectral datum with derivative technique,and to seek out the sensitive wavelengths and spectral characteristics of Phytolacca acinosa Roxb. under uranium pollution. Then by choosing sensitive bands and the best correlated spectrum characteristic parameters, uranium estimation models were constructed. The results showed that when the U contents in leaves were 5.94~71.74 mg·kg-1,they correlated closely with the first derivative reflectance in the range of 749~766 nm. The chosen 14 spectral characteristic parameters were used to calculate the correlation coefficients with uranium contents in leaves, and correlations of the blue edge area, the red edge position, the ratio of red edge area to blue edge area and the normalized values of red edge area and blue edge area were significantat the 0.05 level. The selected wavelengths of 757, 758, 760, 761 nm and the above-mentioned 4 best spectral characteristic parameters were used to establish the uranium estimation models, and precision tests proved that the uranium estimation models established bythe ratio of red edge area to blue edge area, first derivative reflectanceat 757 and 760 nm achieved better test results,among them,the best model was the cubic function model using first derivative reflectance at 757 nm as a variable and the prediction accuracy of it was up to 89.8%.
2019 Vol. 39 (04): 1143-1147 [Abstract] ( 166 ) RICH HTML PDF (1153 KB)  ( 118 )
1148 A Classification Method Based on the Visible Spectrum for Burned and Unburned Gangue Distinguishment
SONG Liang, LIU Shan-jun*, MAO Ya-chun, WANG Dong, YU Mo-li
DOI: 10.3964/j.issn.1000-0593(2019)04-1148-06
A large number of coal mines are widely distributed over China. Bulk coal gangue deposits seriously affect the mining area environment, and some mishandling of coal gangue may cause spontaneous combustion and explosion, which poses a direct threat to mine safety. The comprehensive utilization of coal gangue can effectively alleviate this problem, and it is of significance to the ecological safety and sustainable development of mine. Depending on the burning state, coal gangue is divided into two types - burned and unburned gangue, whose hidden dangers of security and harm to the environment are different, as well as ways of comprehensive utilization. Therefore, it is very important to do the classification, recognition and monitoring of the coal gangue. The current monitoring methods are mainly the field investigation with low efficiency and high cost, almost impossible for meeting the actual demand of coal gangue monitoring.Tiefa mine in Liaoning Province was chosen as the study area. Firstly, a total of 106 typical coal gangue samples were collected from waste dump in mining areas. Then, SVC HR1024 spectrometer was used to test the visible and near infrared spectrum of samples, and a differential spectral index NDGI was constructed to identify the burned and unburned gangue based on the difference of spectral characteristics of the burned and unburned gangue. Finally, the laboratory spectral data and the corresponding satellite remote sensing images were utilized for verifying the index. The random forest classification method was used as a contrast to the results of the laboratory spectrum treatment. The results showed that the slope of the spectral curves of burned gangue samples was higher ranging from 350 to 750 nm, and the reflectance within range of 550~630 nm increased sharply, while the slope of the unburned gangue in the whole visible bands of spectrum was lower. The threshold of the NDGI index was set as 0.25 to distinguish the burned and unburned gangue. The laboratory spectral data showed that the classification accuracy of the NDGI index is up to 99.1%, higher than that of 95.2% of the random forest classification method. The Field results showed burned and unburned areas of waste dump were distinguished and classified in Landsat8 OLI images based on the NDGI index, and the burned and unburned coal gangue areas were in good agreement with the Google Earth on the morphology and size. The overall results showed that the index can effectively distinguish the combustion states of gangue. In addition, burned and unburned gangue samples were taken for mineral identification respectively. By comparing the changes of mineral species before and after combustion, the cause of spectral difference was analyzed between the burned and unburned gangue. The results showed the oxidation from Fe2+ to Fe3+ of gangue in the process of combustion. A large increase in Fe3+ caused the formation of an obvious spectral valley characteristic at 550 nm band, and a highly reflectance appeared at 750 nm band due to the glass quality generated during combustion. The above conditions cause differences in NDGI index between the burned and unburned gangue. In this paper, the results provide a fast, efficient and accurate model and method for burned and unburned gangue distinguishment in coal mine.
2019 Vol. 39 (04): 1148-1153 [Abstract] ( 226 ) RICH HTML PDF (3167 KB)  ( 81 )
1154 Synthesis of Carbon Quantum Dots Based on Gelatin and Study on It’s Optical Property
WANG Xue-chuan1,2, BAI Peng-xia2, LUO Xiao-min1, LI Ji1
DOI: 10.3964/j.issn.1000-0593(2019)04-1154-08
In this article, the blue luminescent carbon quantum dots (CQDs) were prepared by hydrothermal method using pyrolysis of gelatin. The temperature, time of the prepared CQDs were optimized via single-factor experiments to select the optimal conditions for the preparation of CQDs. The results showed that fluorescence of carbon quantum dots was the strongest when the carbonization temperature was 200 ℃, and time was 6 h. At the same time, the obtained carbon quantum dots under the optimal conditions was characterized by transmission electron microscope (TEM), UV-visible spectroscopy, photoluminescence spectroscopy (PL), fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD), the result indicating that the quantum yield of carbon quantum dots prepared by this method is 39.4%, and the quantum yield is relatively higher than that of carbon quantum dots that do not doped, which may be due to the presence of N elements that increase the quantum yield, and the prepared carbon quantum dots not only have rich oxygen-containing functional groups but also have good photobleaching performance, and the morphology of the carbon quantum dots is mainly spherical with uniform dispersion and no obvious lattice fringes, which is consistent with the morphology of the carbon quantum dots reported in related literatures; And the carbon quantum dots had weak absorption at 250~300 nm, but there was no obvious characteristic absorption peak, which may be due to the n—π* transition of the C=O group; In addition, the pH, the Xenon lamp irradiation time, the concentration of carbon quantum dots, the type of solvent, andionic strengthon the fluorescence properties of carbon quantum dots were discussed. The results showed that the irradiation time of the xenon lamp and ionic strength had little effect on the fluorescence performance of the carbon quantum dots. The fluorescence intensity is relatively weak under peracid or overbase conditions, which may be due to protonated or non-protonated effects resulting in decreased fluorescence intensity under peracid or overbase conditions. And as the concentration of the carbon quantum dots increased, the fluorescence intensity increased first and then decreased. For the solvent type, the fluorescence intensity in the polar solvent was greater than the fluorescence intensity in the non-polar solvent which indicated that the carbon quantum dots had good water solubility by this method.
2019 Vol. 39 (04): 1154-1161 [Abstract] ( 309 ) RICH HTML PDF (4617 KB)  ( 110 )
1162 Research on Spectral Reflectance Reconstruction Based on Genetic Algorithm for Selecting Multi-Illuminants
KONG Ling-jun1, ZENG Xi2*, ZHANG Lei-hong2, ZHAN Wen-jie2, ZENG Wen-chao3
DOI: 10.3964/j.issn.1000-0593(2019)04-1162-07
In order to solve the problem that the accuracy of the spectral reflectance reconstruction based on RGB three-channel values is not ideal, an optimized spectral reflectance reconstruction algorithm based on RGB three-channel information was proposed. Firstly we coded to generate individuals with multiple illuminants selected randomly, and RGB three-channel values were used to predict CIE XYZ values under multi-illuminant by polynomial regression algorithm, and the pseudo-inverse method was used to reconstruct the spectral reflectance. Then the reconstruction accuracy of the sample was taken as the fitness evaluation value of the individual, and the individuals were selected, crossed, and mutated based on the principle of survival of the fittest. Finally, the combination of multiple illuminants which were suitable for spectral reconstruction of color samples were obtained, and then used to reconstruct the spectral of color samples. Munsell color set was used as training samples, RC24 chart and SG140 chart were used as test samples, and 8 standard illuminants and 82 LED light sources were used as experimental light sources. The proposed method was used to select the optimal combination from the 90 illumination sources and reconstruct the spectral reflectance of the test samples, and compared with the method based on multi-illuminant selected by exhaustive method proposed by Zhang and the pseudo-inverse method under A light source. The experimental results show that the spectral reflectance reconstruction accuracy is improved as the number of light sources increases, and the increase achieves the most when the number of light sources reach to 3. Among the three reconstruction methods, the average color difference and average root mean square error of the proposed method are 0.332 4 and 0.002 9 respectively for the RC24 chart,while the average color difference of the Zhang and pseudo-inverse methods are 0.429 3 and 3.266 respectively, and their average root mean square error are 0.029 7 and 0.004 8. For the SG140 chart, the average color difference and average root mean square error of the proposed method are 0.486 2 and 0.007 3 respectively, while the average color differences of the Zhang and pseudo-inverse methods are 0.544 8 and 3.821 9 respectively, and the average root mean errors are 0.035 6 and 0.013 3 respectively. The results show that the spectral reconstruction accuracy obtained under multi-illuminant is obviously superior to the one obtained under a single light source, and the results of the multi-illuminant selection method based on genetic algorithm is better than those of the exhaustive method. The genetic algorithm can automatically find the optimal illuminant combination according to the color samples, so as to reconstruct the spectral reflectance of the sample based on the optimal combination improving the accuracy of spectral reconstruction.
2019 Vol. 39 (04): 1162-1168 [Abstract] ( 218 ) RICH HTML PDF (3189 KB)  ( 110 )
1169 Development and Test of On-Line Detection System for Meat Freshness Evaluation Based on Spectroscopy Technology
WANG Wen-xiu, PENG Yan-kun*, SUN Hong-wei, WEI Wen-song, ZHENG Xiao-chun, YANG Qing-hua
DOI: 10.3964/j.issn.1000-0593(2019)04-1169-08
In order to realize real-time, on-line and non-destructive evaluation of main freshness attributes of raw meat, an on-line detection system based on dual-band visible/near-infrared reflectance spectroscopy(350~1100 and 1000~2500 nm) was established in this paper. The hardware which includes the light source unit, the spectrum acquisition unit, the control unit and the driving unit was designed. The light source fixing support and installation angle were optimized, and the corresponding control program was developed. Based on those, two sets of on-line detection systems were developed for laboratory use and to satisfy the demands of different production lines. Firstly, the experimental parameters including the conveyor speed and the distance between sample surface and the entrance of the lens were optimized. By comparing the spectral similarity and the significance analysis, the conveyor speed and the distance were determined as 275 mm·s-1 and 12 cm to obtain stable spectra. Then, based on the experimental parameters, the reflectance spectra of 50 pork samples stored for 1~13 days were collected under static and on-line conditions, respectively. The dual-band spectra were fused by parabolic fitting to obtain a complete spectrum which covered the whole visible and near-infrared region. Subsequently, all spectra were rearranged at 2 nm intervals by means of cubic spline interpolation to make the spectral data points distribute evenly over the two bands. Based on this, the spectrum was smoothed by the moving window polynomial fitting least square method and normalized by standard normal variable transformation. Then the prediction models for L*, a*, b*, pH and total volatile base nitrogen under static and on-line conditions were established and compared to verify the reliability of the constructed system. It was found that the modeling results for on-line detection performed worse than those under static conditions, and the reason may be attributed to the spectrum drift. Therefore, first derivative was further employed to eliminate the baseline drift and enhance the band characteristics. The influence of processing sequence of first derivative and standardization on the modeling results was also discussed. The results showed that the first derivative followed by standardization worked more successfully to eliminate the external interference. Then the prediction models for L*, a*, and b* were established based on the first band, and the models for pH and total volatile basic nitrogen were established based on the dual-band spectrum, with correlation coefficients of 0.955 3, 0.924 7, 0.955 1, 0.961 5 and 0.966 8. Finally, 20 independent samples were detected using the developed on-line inspection system to verify the model applicability, and the correlation coefficients for L*, a*, b*, pH and total volatile basic nitrogen were 0.918 9, 0.914 1, 0.947 7, 0.950 4 and 0.960 6, respectively. The results showed that by the real-time acquisition and fusion of dual-band spectroscopy, more optical signal were collected to reflect the internal information of tested samples. Combined with the designed optical path and other hardware units, the spectral information within a larger area of the sample surface were obtained. Thus, the non-destructive, online, and real-time assessment of the main attributes for raw meat freshness was achieved. The system was easy to assemble and disassemble, which made it possible to satisfy the actual needs of different production lines and had strong practical value and market prospects.
2019 Vol. 39 (04): 1169-1176 [Abstract] ( 185 ) RICH HTML PDF (3041 KB)  ( 72 )
1177 Research on Detection of Beef Freshness Parameters Based on Multi Spectral Diffuse Reflectance Method
WEI Wen-song, PENG Yan-kun*, ZHENG Xiao-chun, WANG Wen-xiu
DOI: 10.3964/j.issn.1000-0593(2019)04-1177-09
In order to meet the development requirement of portable and low cost equipment in the field of non-destructive detection of fresh meat quality parameters, a new method based on multi spectral diffuse reflectance technology for fresh meat quality detection is proposed. Based on the diffusion approximation theory and combined with the sample scattering coefficient, absorption coefficient and refractive index of beef and other parameters, based on Monte Carlo simulation of thin vertical beam on the radio, on a certain divergence angle of LED light source are initialized with correction respectively from the light source position probability distribution and different angles of the irradiation probability distribution, angle, direction angle the probability distribution and different incident light angle sample reflection caused by the energy loss and influence on the photon weight, the LED divergence angle under different source detector diffuse reflectance and depth of detection distance, the optimum distance between the light source and the detector is 15 mm, then according to the distance, to build a multi spectral diffuse reflection detection platform, multi spectral detection platform by 8 groups of 470, 535, 575, 610, 650, 720, 780, 960 nm LED. The source composition corresponds to the quality parameters of fresh beef to be detected. At the same time, according to the 8 LED light source, the light source design layout structure of probe point symmetry, 8 light sources inside the probe to the detector as the center, symmetric distribution, while using LED light source divergence angle, determine the installation position of the light source to the sample surface and the vertical distance of each light source, to ensure the light source to the sample area is uniform. In addition, the probe embedded within the design of signal acquisition, amplification and transmission components, signal acquisition part uses the spectral response range of 400~1 100 nm light intensity detector, sample diffuse intensity after processing to the host computer through the signal acquisition and amplification circuit, and the software finished modeling and analysis. Finally in order to verify the performance of the detection system, with fresh beef freshness in the color parameter (L*, a*, b*) and the pH value as the index was tested using 60 samples, 8 light source under the original light intensity value and corrected reflectance values respectively, and then the beef samples according to 3∶1 the proportion is divided into set and prediction set correction, for the original value of light intensity and reflectivity values, respectively, using multiple linear regression (MLR), Multiple Linear Regression Partial Least Squares Regression partial least squares regression (PLSR) and partial least squares support vector machine regression Partial Least-Squares Support Vector Machine (LS-SVM) three methods, model parameters in the original light intensity and reflectivity data of the two cases, and get the best results. The results show that the results of modeling using reflectivity data are better than those of light intensity data. The MLR modeling results of parameters L*, a* and b* are better than those of PLSR and LS-SVR, and their correlation coefficients of prediction set are 0.983 2, 0.907 2 and 0.935 9, respectively, and the prediction set errors are 1.00, 2.14 and 0.67, respectively. The LS-SVR modeling results of parameter pH value are better than that of PLSR and MLR, and the correlation coefficient of the prediction set is 0.942 0 and the error is 0.19. Finally, using 20 pieces of beef samples which did not participate in the test to validate the model, the color of L*, a*, b* and pH parameters of the prediction value of the correlation coefficient and the measured value is greater than 0.85, the results proved that using multispectral diffuse reflection technology and building the multispectral reflectance detecting system are feasible for the detection of fresh beef the quality parameters, this method can provide reference and basis for the nondestructive testing instrument design of portable or micro fresh beef quality.
2019 Vol. 39 (04): 1177-1185 [Abstract] ( 220 ) RICH HTML PDF (4130 KB)  ( 96 )
1186 Rapid Identification and Enumeration of Common Pathogens in Yogurt Using Hyperspectral Imaging
SHI Ji-yong, WU Sheng-bin, ZOU Xiao-bo*, ZHAO Hao, HU Xue-tao, ZHANG Fang
DOI: 10.3964/j.issn.1000-0593(2019)04-1186-06
Yogurt is a kind of fermented dairy beverage, and it is celebrated for its special functionality and good taste. However, due to the improper operation of the commercial chain, such as the illegal acquisition of milk sources and so on, the pathogenic bacteria in yogurt are widespread, resulting in frequent occurrence of yogurt poisoning. The main pathogenic in yogurt are Escherichia coil, Staphylococcus aureus and Salmonella. Human consumption of these three kinds of bacteria will cause severe digestive tract diseases and destroy the balance of normal flora in the human intestine after reaching a certain number. Therefore, the Chinese National Standard has a clear limit on the number of the three pathogens in dairy products. Because the main object of yogurt consumption is the old and the children, the potential harm of yogurt should not be underestimated. The traditional colony detection method is sample, sensitive and operable, but when different colonies are mixed together, it can not be qualitatively detected at the same time, and there are shortcomings such as high cost, long detection cycle and human factors. Therefore, it is of great practical significance to develop a fast, simple and accurate mixed identification count method to avoid the potential hazards of pathogenic bacteria in yogurt. Hyperspectral technology integrates the spectral information and spatial location information of the sample. It can not only accurately identify according to the tiny change of chemical components (spectral information), but also reflect the multi-level changes of the strain (image information). Therefore, this study adopts pattern recognition method to compare different models established by the image information and spectral information, and selects the best counting model based on the recognition rate of the model. Finally, the identification and counting of common pathogenic bacteria in yogurt were realized by the classification results of the best model. Firstly, the standard strains of lactic bacteria and potentially contaminated pathogenic bacteria in yogurt were cultured, and the colony image information and spectral information after 48 h, culture were extracted. Then, different pre-processing methods (SNV, MC, MSC, 1stDER, 2ndDER) were used to reduce the spectral data, and the genetic algorithm was used to reduce the excess spectral bands. The image of agar background used image processing technology to mask removal, then 3 characteristic wavelengths were selected from each map by principal component analysis, and 18 texture feature based on gray-level co-occurrence matrix texture information were extracted from the strain of characteristic wavelengths. Different discriminant models (LDA, KNN, BP-ANN, LS-SVM) were established by selecting the appropriate principal component, and the best discriminant model was determined by the recognition rate of the final discriminant model. Finally, 30 strains from each standard strain were selected for counting test, and the accuracy of pattern recognition was verified by comparing the results of classification and quantity of pattern recognition with the actual number of strains. The results showed that the spectral data pretreated by SNV were superior to other pre-treating methods. The 745.790 8, 773.098 4 and 779.207 0 nm were the characteristic wavelengths. Through the contrast of image pattern recognition and spectral information rate results, it was found that the spectral characteristics of the differential model were better than those of the image texture feature identification model, and when the number of principal component was 9, the LS-SVM spectral model was the optimal model, and the recognition rate of the correction set is 96.25%, and the recognition rate of the prediction set is 91.88%. The optimal model was applied to recognize and count the strains. The relative error of Escherichia coil count was 3.33%, and the relative error of count of Staphylococcus aureus and Salmonella was 0, which verified the feasibility of applying hyperspectral technology to identify and count common pathogenic bacteria in yogurt.
2019 Vol. 39 (04): 1186-1191 [Abstract] ( 215 ) RICH HTML PDF (2591 KB)  ( 94 )
1192 Comparison between the Effects of Visible Light and Multispectral Sensor Based on Low-Altitude Remote Sensing Platform in the Evaluation of Rice Sheath Blight
ZHAO Xiao-yang1, 2, ZHANG Jian1, 2*, ZHANG Dong-yan3, ZHOU Xin-gen4, LIU Xiao-hui3, XIE Jing5*
DOI: 10.3964/j.issn.1000-0593(2019)04-1192-07
Efficient and non-destructive assessment of crop disease grade is of great significance to the practical agricultural production and research. In this study, the feasibility of low-altitude UAV (Unmanned Aerial Vehicle) remote sensing platform for the disease grade assessment of rice Sheath Blight (ShB) was discussed. Then the spectral response differences of visible light sensor and multispectral sensor and their effects on the spectral reflectance acquisition of rice with ShB were analyzed. And rice ShB monitoring effects of two kinds of sensors were compared quantitively. The study area consisted of 67 rice plots with different varieties, each of which was divided into inoculation zone and infection zone. The drone was Phantom 3 Advanced, a small consumer-grade UAV made by DJI-Innovations company, and the payloads were the self-contained visible light sensor and Micasense RedEdgeTM multispectral sensor to acquire remote sensing images respectively. At the same time, the rice ShB disease grades were investigated by manual expert recognition and measured NDVI was obtained with Trimble's GreenSeeker Handheld Crop Sensor. Remote sensing images were preprocessed by image mosaic, layer stacking and radiometric calibration. A total of 134 plots in inoculation and infection zones of visible light image were used to calculate seven kinds of visible light vegetation indices, namely NDI (Normalized Difference Index), ExG (Excess Green), ExR (Excess Red), ExG-ExR, B*, G* and R*. Besides the above seven kinds of visible light vegetation indices, multispectral image was calculated by three kinds of multispectral vegetation indices additionally, namely NDVI (Normalized Difference Vegetation Index), RVI (Ratio Vegetation Index) and NDWI (Normalized Difference Water Index). The correlation between the image-based vegetation index and ground-based NDVI was analyzed, and the optimal image-based vegetation indices of the visible light and multispectral sensor were selected to establish the disease grade inversion model of rice ShB. The results of correlation analysis showed that the fitting degree of image-based NDVI and ground-based NDVI based on multispectral sensor was the highest, and R2 was 0.914 and RMSE was 0.024 in the inoculation zone, while R2 and RMSE were 0.863 and 0.024 respectively in the infection zone. As for the visible light sensor, the correlation between image-based NDI and measured NDVI was best, and R2 was 0.875 and RMSE was 0.011 in the inoculation zone, while R2 was 0.703 and RMSE was 0.014 in the infection zone. The consistencies of the same image-based vegetation index and ground-based NDVI of two kinds of sensors and two kinds of zones were compared, which revealed that NDI, ExR, ExG-ExR, G*, ExG, R* except B* were mainly highly correlated with the measured NDVI. In the inoculation zones with severe disease, the two kinds of sensors had similar effects on the detection of rice ShB, but the monitoring effect of multispectral sensor was more precise and sensitive in infection zones with relatively lighter disease. The disease grade inversion model of rice ShB established by NDVI based on multispectral sensor was effective, whose R2 reached 0.624, and RMSE was 0.801 and prediction accuracy was 90.04%. The disease grade inversion model established by NDI based on visible light sensor was slightly worse, whose R2 was 0.580, and RMSE was 0.847 and prediction accuracy was 89.45%. The spectral response curves of visible light and multispectral sensor were compared and analyzed. The visible light sensor can obtain three bands of red, green, blue in the range of visible light, and wavelength range overlaps with each other, while the multispectral sensor including five imaging units can independently obtain five narrow-band spectral bands from visible light to near infrared providing subtler spectral information. Through comparing the average reflectance curves of rice in inoculation zone and infection zone, the multispectral sensor not only reflected bigger difference than visible light sensor in the visible light band, but also represented more obvious difference in the red and near infrared band, which demonstrated that the professional narrow-band sensor had an advantage over broad-band consumer-grade sensor in the rice ShB monitoring. In conclusion, it is feasible to evaluate the disease grade of rice ShB based on the low-altitude UAV remote sensing platform with visible light and multispectral sensor. The multispectral sensor is precise and sensitive which can be used for early detection of rice ShB, and the visible light sensor is less accurate but economical and easy to popularize. The results of this study are expected to provide decision support for diseases control and be beneficial to promoting precision agriculture and ensureing food security.
2019 Vol. 39 (04): 1192-1198 [Abstract] ( 388 ) RICH HTML PDF (3786 KB)  ( 221 )
1199 Estimation Method of Wheat Leaf Area Index Based on Hyperspectral Under Late Sowing Conditions
SUN Hua-lin, GENG Shi-ying, WANG Xiao-yan*, XIONG Qin-xue*
DOI: 10.3964/j.issn.1000-0593(2019)04-1199-08
In this study, hyperspectral remote sensing technology was used to measure the changes of leaf and canopy characteristics with leaf area index (LAI) of wheat leaves under late sowing conditions, and the LAI estimation method suitable for late sowing wheat was established. The results show that: (1) Correlation analysis between chlorophyll spectral reflectance vegetation index (CSRVI) is extracted from the red and blue bands (420~663 nm) to analyze the correlation between SPAD value and CSRVI of the leaf mode under normal sowing and late sowing treatment with R2 being 0.963* and 0.997** reached significant and extremely significant level, respectively. (2) It is concluded that the correlation coefficients of LAI and SPAD values for the two sowing dates are 0.847* and 0.813* by using correlation analysis, respectively, and both reaching significant levels. The SPAD value is correlated with LAI and CSRVI indices, and the CSRVI index can be used to establish the LAI estimation model. (3) Analysis of the spectral curves of characteristics of leaf pattern and canopy patter shows that the reflectance of leaf pattern increases sharply at 680~780 nm. There are two distinct absorption troughs at 446 nm, 680 nm in visible light band and 1 440 and 1 925 nm in near-infrared wave band. There is a clear reflection peak at 540-600 nm band. There are two distinct reflective peaks at 1 660 and 2 210 nm, and the spectral reflectance of the three canopy modes is the highest in the three canopy modes. (4) Correlation analysis between the reflectance of each band and the leaf area index shows that the spectral reflectance has a negative correlation with the overall LAI in the visible light range, and there is a peak at 500~600 nm. (5) Correlation analysis of the equivalent vegetation index and LAI in the three canopy modes (the angle of incidence of the instrument with the ground at 30°, 60°, and 90° respectively) is obtained: there was no significant correlation between 8 vegetation indices and the LAI under the late sowing condition of 60° canopy mode. And a significant and extremely significant the 6 vegetation indices (normalized vegetation index (NDVI), enhanced vegetation index (EVI), re-normalized vegetation index (RDVI), Soil-adjusted vegetation index (SAVI) and modified Soil-adjusted vegetation index (MSAVI) ) under the late sowing condition of 60° canopy mode; the CSRVI indices in the 90° canopy mode were significantly correlated with the LAI of the normal sowing date. NDVI index is significantly correlated with LAI in late sowing treatment; the correlation between the 8 vegetation indices in the 30° canopy mode and the LAI in the two sowing dates was not relevant. Comprehensive analysis of the CSRVI index, NDVI index is the most relevant, and these two indices have the most potential to estimate LAI. (6) The LAI model was estimated by the vegetation index calculated by the three canopy models. The results show that under the normal sowing date, the best estimation model is the Linear function model established by the 90° canopy model with CSRVI index Y=Y=-7.873 6+6.223 8X; The best model under late sowing conditions is the power function model Y=30 221 333.33X17.679 1 established by the 60° canopy mode RDVI index, with R2 being 0.950* and 0.974** in the two treatments, respectively. Studies have shown that the CSRVI index extracted from the test can reflect the chlorophyll content of flag leaf. The chlorophyll content of wheat during the growth period can be monitored by the leaf pattern of the spectroscopy instrument; LAI estimation model based on CSRVI index and RDVI index calculated by canopy model can be used to observe wheat LAI without damage.
2019 Vol. 39 (04): 1199-1206 [Abstract] ( 238 ) RICH HTML PDF (2189 KB)  ( 100 )
1207 Analysis of Two Stage Effluent from Sewage Treatment Plant by 3D-EEMs and PARAFAC
LÜ Jing-jing1, 2, DOU Yan-yan1, GONG Wei-jin1, DUAN Xue-jun1, ZHANG Lie-yu3, XI Bei-dou3, YU Shui-li2, HOU Li-an2, 4
DOI: 10.3964/j.issn.1000-0593(2019)04-1207-07
The vertical distribution characteristics of nitrogen, phosphorus and DOM in secondary effluent of soil infiltration WWTP were studied by 3D-EEMs and PARAFAC. The experiment was carried out on a pilot-scale soil infiltration system with a sampling port at 30 cm intervals from top to bottom. The collected samples were identified by PARAFAC model as having 4 fluorescent components at different points in the system, including two humus substances (C1, C2) and two protein substances (C3, C4) respectively. Fmax analysis showed that the tryptophan represented by C4 was more easily degraded than other three kinds of substances, that is, tryptophan was the most easily degraded, followed by fulvic acid, humic acid and protein-like substances. The Fmax variation of the four components was the largest at 0~30 cm, which showed that the biochemical reaction was the most intense and the migration and transformation rate of DOM was the highest. The source of DOM in soil infiltration system and the variation law of DOM in different depths could be revealed by means of PARAFAC, PCA and CA. Soil infiltration system was unfavorable for TN and nitrate removal in treating secondary effluent of sewage treatment plant under 4 L·d-1 low load condition. The subsequent denitrification processes such as denitrification filter could be coupled to enhance denitrification and nitrogen removal rate. The adsorption of phosphorus on soil had not yet reached saturation state, and had maintained a high TP removal efficiency.
2019 Vol. 39 (04): 1207-1213 [Abstract] ( 233 ) RICH HTML PDF (2114 KB)  ( 91 )
1214 Hyperspectral Inversion of Heavy Metal Content in Soils Reconstituted by Mining Wasteland
SHEN Qiang1, ZHANG Shi-wen2*, GE Chang2, LIU Hui-lin2, ZHOU Yan3, CHEN Yuan-peng3, HU Qing-qing2, YE Hui-chun4*, HUANG Yuan-fang5
DOI: 10.3964/j.issn.1000-0593(2019)04-1214-08
Mineral resources play an important role in the development of industry and national economy. However, with the expansion of mining scale, more and more abandoned mining land is formed due to resource depletion and poor management. Due to the prolonged mining impact, a large amount of heavy metal elements are present in the soils of mining wastelands. In such contaminated areas, high levels of heavy metals may have an impact on the environment and the human body. Land reclamation is an important method for remediation of contaminated and degraded soils. The detection of heavy metal content in the reconstructed soils is an important indicator of land reclamation efficiency and requires long-term follow-up and monitoring. The traditional chemical detection methods are inefficient and costly, and can not detect a wide range of heavy metals. Hyperspectral technology is a new technology with great potential for development and has a wide range of applications in environmental protection, resource utilization and regional sustainable development. After the rapid development in recent decades, the accuracy of instruments has been gradually increased, and the detection methods have gradually become mature, so as to realize the high efficiency of soil heavy metals. Easy detection provides a new way. Normal soil heavy metal content is generally relatively lower, and the use of spectral techniques to measure heavy metal content is more difficult, but mining iron ore mining area due to the soil more iron, will make the soil heavy metals in the form of existence and aggregation changes, impact the response of heavy metals to the spectra, and make the correlation between soil spectral reflectance and heavy metal content even more pronounced. The contents of heavy metal (As, Cr, Zn) in soils were obtained by sampling chemical detection method in the study area of reclamation mining area in Daye City, Hubei Province. The soil reflectance was obtained by means of FieldSpec4 spectrophotometer (350~2 500 nm) First-order differential, reciprocal logarithm, and continuous unmixing method were used to preprocess the reflectance curve respectively, and the spectral characteristic bands were extracted. The correlations between the three heavy metal elements and spectral features were analyzed and a stepwise regression model was established. The results showed that compared with the general soil, spectral data preprocessing could make spectral characteristic bands more obvious, of which the first-order differential and continuous removal were the most obvious. The characteristic bands of the three heavy metal elements were 495, 545, 675, 995, 1 425, 1 505, 1 935, 2 165, 2 205, 2 275 and 2 355 nm. Correlation analysis between soil heavy metal content and spectral characteristic bands showed that all the three heavy metals showed correlation with spectral curve, and most of the correlation coefficients reached above 0.5 and the maximum correlation coefficient was 0.663, and different heavy metal species and treatment methods led to significant differences in the correlation coefficients. Three heavy metal inversion models were established based on the characteristic bands with the highest correlation with heavy metals in soil. The optimal inversion model for each heavy metal was selected based on the size of inversion model r. Because of different selection of heavy metal species, Cr, Zn First-order differential step-by-step regression was the best inversion model, and heavy metal As continuous removal method gradually regression was the best inversion model. Through the test, Cr in the three kinds of heavy metals was the best, and RMSE is 2.67, followed by Zn, and As is the worst. Comparing the current different detection methods, we can see that hyperspectral inversion of soil heavy metal content spectrometer based on soil samples and spectral data pretreatment is ideal. The related research results can provide reference for the hyperspectral inversion of heavy metals in mining-abandoned soils.
2019 Vol. 39 (04): 1214-1221 [Abstract] ( 234 ) RICH HTML PDF (2728 KB)  ( 305 )
1222 Study on Prediction of Soil Organic Matter Based on Digital Image Color Extraction
WU Cai-wu1, YANG Hao2, XIA Jian-xin3*, CHANG Jia-ning1, YANG Yue1, ZHANG Yue-cong1, CHENG Fu-wei1
DOI: 10.3964/j.issn.1000-0593(2019)04-1222-07
As an important criterion for determining soil quality, the rapid determination of soil organic matter (SOM) can provide basic data support for the implementation of precision agriculture. Traditional determination method of SOM, through field sampling and laboratory chemical analysis, not only time-consuming and laborious, but also inefficient, cannot meet the large-scale demand for soil information in current social development. Although the prediction model of SOM can be established based upon the characteristics of spectral reflectance of soil affected by SOM to realize the rapid prediction for SOM, the spectrometer is of high price and strict operation environment, which limits its wide application. Then visible-light sensor with RGB is cheap and easy to operate. Therefore it is worth exploring and studying the rapid determination of SOM from the perspective of practicality and economy, with the help of many advantages of visible-light sensor. Therefore, in order to verify the feasibility and applicability of extracting color information of digital images for fast prediction of SOM, the paper uses a digital camera to obtain the soil surface color information, analyses the characteristics of soil surface composition, determines the optimal sampling area, compares the correlation between different sample preparation standards (<1 mm and <0.5 mm) and SOM, selects the high correlation of color variables, and establishes the prediction model of SOM through regression analysis. The results show that the 950×950 pixel as the sampling area can obtain the color of the soil surface more stably and reduce the influence of the edge effect on the sampling result. In the correlation analysis between the soil samples <1 mm and <0.5 mm and SOM, the RGB bands of <1 mm soil samples have a higher correlation with SOM and are suitable as sample preparation standards for soil color acquisition. In the three bands of RGB, the red band showed the highest correlation with SOM, with a correlation coefficient of -0.70. The correlation between color and SOM was enhanced by the mathematical transformation of the RGB band and the excessred (ExR) calculation, in which the ExR index shows the highest correlation with SOM with a correlation coefficient of -0.86. In a single variable modeling process, the best predictive effect is obtained by ExR reciprocal model. In the multivariable modeling, the standard deviations of each color were involved in the modeling, which causes the color information description to be more comprehensive, and the best modeling results are obtained that can better reflect the variation of SOM within the study area, its R2=0.80, RMSE=0.51, the validation result R2val=0.84, RMSEval=0.54. Based on the prediction results of the model for black soil, only the single-variable red band model shows a good prediction effect, and the test results show that the red band is a sensitive band of SOM and has its universality in different soil types. Although the model built in this study cannot be extended to predict other soil types, the prediction of the same soil shows that the digital camera, as a quantitative color imetric tool, has the potential to rapidly predict SOM content.
2019 Vol. 39 (04): 1222-1228 [Abstract] ( 291 ) RICH HTML PDF (1793 KB)  ( 89 )
1229 A Study of Soil Salinity Inversion Based on Multispectral Remote Sensing Index in Ebinur Lake Wetland Nature Reserve
ZHOU Xiao-hong1,2,3, ZHANG Fei1,2,3*, ZHANG Hai-wei1,2,3, ZHANG Xian-long1,2,3, YUAN Jie1,2,3
DOI: 10.3964/j.issn.1000-0593(2019)04-1229-07
Soil salinity is an important factor for measuring soil quality, and it is also a basic condition for the growth of crops. Therefore, it is urgent to find a method that can understand soil salt content quickly. This paper is based on the Landsat8 OLI multispectral remote sensing image for the Ebinur Lake Wetland Nature Reserve, and we use the salt content of 36 soil surface samples in the study area as the data source, and choose several multispectral remote sensing indices which have the superior correlation with soil salinity to analyze the soil salinity distribution in the study area. The linear, logarithmic and quadratic function models were constructed with the measured soil salinity, and optimum inversion model of soil salt content was selected. The result shows that: (1)Among these multispectral remote sensing indices, the enhanced vegetation indices show the closest correlation with soil salinity, and the correlation coefficient range is between -0.67 and -0.70. The second is the traditional vegetation indices, and the correlation coefficient range is between -0.46 and -0.58. The correlation of soil salt index is the farthest t,and its range is between 0.16 and -0.45, and there is no correlation between SI3, SI4 and soil salt content. (2)Comparing and analyzing the salt distribution map inverted by measured soil salinity values and the spatial distribution of Enhanced Vegetation indices, we found that the soil salt content around the Ebinur Lake of the northwest and south direction and tne Yan Chi Bridge in the northeast is higher, but the enhanced vegetation indices are lower. The result shows that the salt distribution map inverted by measured soil salinity values is consistent with the spatial distribution of Enhanced Vegetation indices. It indicates that the enhanced vegetation indices have a higher sensitivity to soil salinity,which can better reverse the spatial distribution of soil salinity in the study area. (3)From the comparison and analysis of those models, which builds the three enhanced vegetation indices and measured soil salt content respectively.We found that the enhanced ratio vegetation index is the best choice to construct the quadratic function model. The determination coefficient of its validation set (R2) is 0.92, and the root mean square error (RMSE) is 2.48, and the relative analysis error (RPD) is 2.09. The data show that this model is more accurate and reliable. In summary, ERVI is more sensitive to soil salinity and predict the soil salinity content, while is more suitable for inversion of soil salinity in this study area. Therefore, the study indicates that it is feasible to invert the soil salinity by the enhanced vegetation index constructed by the b6 and b7 band of Landsat8 multipectral remote sensing imagery. And its inversion effect is better than that of traditional visible light band. Therefore, this study not only provides a theoretical reference for remote sensing inversion, but also has important implications for the quantitative estimation and dynamic monitoring of soil salinity for the study area. Otherwise, it can be used as an alternative offer for prediction of soil salt content in other regions.
2019 Vol. 39 (04): 1229-1235 [Abstract] ( 249 ) RICH HTML PDF (2455 KB)  ( 99 )
1236 Electrical and OES Characters of Nanosecond Pulsed Array Wire-to-Wire SDBD Plasma in Atmospheric Air
ZHAO Zi-lu, YANG De-zheng, WANG Wen-chun*, ZHOU Xiong-feng, YUAN Hao
DOI: 10.3964/j.issn.1000-0593(2019)04-1236-06
In this paper, an array wire-to-wire surface dielectric barrier discharge is reported, and discharge plasma with a relative large area is excited by a high-voltage nanosecond pulse power in atmospheric air. The high-voltage and ground electrodes are made of cylindrical metal, and the discharge structure is composed of 20 groups of alternately arranged array high-voltage and ground electrodes covered with dielectric tubes. The applied voltage and total discharge current are measured by high-voltage and current probes, and displayed on oscilloscope. And the discharge current is calculated. The optical emission spectra within the wavelengths of 300~440 and 766~778 nm are measured by fiber, spectrometer, and CCD, namely, the spectra of N2 (C3Πu→B3Πg) including the bands of Δν=+1, 0, -1, -2, -3, N+2(B2Σ+u→X2Σ+g), N2 (B3Πg→A3Σ+u), and O (3p5P→3s5S2). The emission intensities are calculated, and every peak of N2 (C3Πu→B3Πg) and four active species are compared. The effects of pulse peak voltage on the emission intensities are also investigated. The second and third diffraction spectra are measured and compared with the original spectra of N2 (C3Πu→B3Πg, 0-0) in the aspects of rotational bands and background spectra. The ratios of peak value between the second diffraction and original spectra of N2 (C3Πu→B3Πg, 0-0) are calculated. The rotational and vibrational temperatures are simulated and compared by N2 (C3Πu→B3Πg, Δν=+1, 0, -1, -2) and N+2 (B2Σ+u→X2Σ+g, 0-0), and the effects of pulse peak voltage are investigated. According to the applied voltage and calculated discharge current, the discharge current of array wire-to-wire surface dielectric barrier discharge is about 75 A in both positive and negative directions, when pulse peak voltage is 22 kV and pulse repetition rate is 150 Hz. The optical emission spectra show that the main active species of discharge plasma are N2 (C3Πu→B3Πg), N+2(B2Σ+u→X2Σ+g), N2 (B3Πg→A3Σ+u), and O (3p5P→3s5S2) during measured ranges. During the range of 22~36 kV of pulse peak voltage, the emission intensity of N2 (C3Πu→B3Πg, 0-0) keeps the highest, then it is N2 (B3Πg→A3Σ+u), and those of N+2(B2Σ+u→X2Σ+g) and O (3p5P→3s5S2) are relatively weak. And when the pulse peak voltage increases, the emission intensities of all vibrational peaks of N2 (C3Πu→B3Πg), N+2(B2Σ+u→X2Σ+g), N2 (B3Πg→A3Σ+u), and O (3p5P→3s5S2) increase. Comparing the original, second, and third diffraction spectra of N2 (C3Πu→B3Πg, 0-0), it is found that the rotational bands of the second and third diffraction are clearer than those of original spectra, and the backgrounds of third diffraction are more intense than those of second diffraction, which means that it is more suitable to simulate rotational temperatures by the second diffraction spectra of N2 (C3Πu→B3Πg). Comparing the simulated vibrational temperatures, N2 (C3Πu→B3Πg, Δν=-2) is the most suitable one amongthe four bands of N2 (C3Πu→B3Πg, Δν=+1, 0, -1, -2), and rotational temperatures simulated by N+2 (B2Σ+u→X2Σ+g, 0-0) are higher than those of N2 (C3Πu→B3Πg, Δν=-2) by 10~15 K. Besides, when the pulse peak voltage increases, the rotational temperatures simulated by N+2 (B2Σ+u→X2Σ+g, 0-0) and N2 (C3Πu→B3Πg, Δν=-2) both increase, and the vibrational temperatures simulated by N2 (C3Πu→B3Πg, Δν=-2) decrease.
2019 Vol. 39 (04): 1236-1241 [Abstract] ( 199 ) RICH HTML PDF (3170 KB)  ( 135 )
1242 Characteristics Study and Parameters Diagnosis by Spectral Analysis of Low Pressure Argon Inductively Coupled Plasma
SONG Zhi-jie, XU Hao-jun, WEI Xiao-long, CHEN Zeng-hui, SONG Fei-long, ZHANG Wen-yuan
DOI: 10.3964/j.issn.1000-0593(2019)04-1242-05
The inductively coupled plasma (ICP) has more advantages over other plasma sources in radar stealth, including simple antenna structure, a wide pressure range, large area and high electron density. Compared with the open-type plasma, closed-type plasma is more compatible with the flying environment of aircraft, where the air flows fast and pressure changes fiercely. A newly designed cylindrical closed chamber made of quartz windows inlaid in stainless steel was used to generate planar ICP for the potential application in stealth design of aircraft local. Compared with previous all-quartz chamber, the new structure effectively improved the homogeneity of ICP because of the ground connection. The discharging characteristics and emission spectrum of ICP in the closed chamber was studied. Obvious E-H mode transition was observed when the power came to 150 W in experiment. The spectrum intensity and electron density increased in a huge step at the transition point. Over the whole discharging progress, the spectrum intensity increased with power, but because of the diversity in transition probability and excitation energy of spectral lines, the increasing amplitude was also different. Based on the emission spectrum of ICP, the electron excitation temperature was diagnosed by the Boltzmann slope method. The electron excitation temperature was above 2 000 K and the higher of the power, the lower of the temperature. Because higher power enhanced the thermal motion of electrons and then the collision between particles became fiercer. This kind of collision consumed more energy so the temperature came down. The distribution of electron excitation temperature along the radial direction was approximately homogeneous. And the power had little influence on the distribution. A Voigt convolution function was introduced to solve the problem of big error and cockamamie calculation about spectrum diagnosis of electron density. The interferential broadenings of argon emission spectrum were eliminated by fitting calculation. So the accurate full width at half maximum of Stark broadening was obtained. Then the electron density was calculated by Stark broadening method. The peak electron density came to 7.5×1017 m-3 at the center of chamber. The electron density increased with power because the coupling efficient was enhanced. Power had little influence on the spatial distribution of electron density.
2019 Vol. 39 (04): 1242-1246 [Abstract] ( 229 ) RICH HTML PDF (2352 KB)  ( 123 )
1247 The Effect of Sample Temperature on Characteristic Parameters of the Nanosecond Laser-Induced Cu Plasma
WANG Li, FU Yuan-xia, XU Li,GONG Hao, RONG Chang-chun
DOI: 10.3964/j.issn.1000-0593(2019)04-1247-05
To investigate the influence of sample temperature on the characteristic parameters of laser-induced Cu plasma, brass was used as the study object. A Nd: YAG nanosecond pulsed laser with 532 nm wavelength was adopted under optimized experimental conditions to excite and to induce the breakdown of massive brass under different sample temperatures, and the characteristic spectral line intensity and signal-to-noise ratio of the Cu plasma were measured. The Boltzmann diagonal line and Stark broadening methods were used to analyze and calculate the electron temperature and electron density of the plasma under different sample temperatures. When the laser power was 60 mw, the characteristic spectral line intensity and signal-to-noise ratio of Cu gradually increased as the sample temperature increased and tended to be saturated after reaching maximum values under 130 ℃. The relative intensities of eight spectral lines—Cu Ⅰ 329.05, Cu Ⅰ 427.51, Cu Ⅰ 458.71, Cu Ⅰ 510.55, Cu Ⅰ 515.32, Cu Ⅰ 521.82, Cu Ⅰ 529.25, and Cu Ⅰ 578.21 nm—of Cu in the brass sample increased 11.55, 4.53, 4.72, 3.31, 4.47, 4.60, 4.25, and 4.55 times under 130 ℃ compared with those under room temperature (18 ℃), and the spectral signal-to-noise ratios increased 1.35, 2.29, 1.76, 2.50, 2.45, 2.28, 2.50 and 2.53 times respectively. Elevating the sample temperature would increase the ablation mass of the sample and plasma particle concentration compared with those under relatively low temperature and consequently would enhance the plasma emission spectral intensity. Therefore, appropriately elevating the sample temperature could increase the spectral line intensity and signal-to-noise ratio to enhance the measurement accuracy of LIBS technology in detecting and analyzing weak spectral signals and to improve its detection sensitivity for trace elements. The variation tendency of the electron temperature and electron density with the change of sample temperature was investigated. In the calculation, the electron temperature of the plasma was basically unchanged when it was increased from 4 723 to 7 121 K when the sample temperature increased from room temperature to 130 ℃. This change law was consistent with the variation tendency of the emission line intensity and signal-to-noise ratio. This condition was mainly due to the increase in the laser ablation quantity and internal energy of the plasma at the initial phase of the sample temperature rise, which increased the electron temperature of the plasma. No additional change in the sample quantity under laser ablation was observed after reaching a certain value, and the laser energy was absorbed, scattered, and reflected by excited and sputtered sample evaporants and dust particles; such process reduced the laser energy density. As a result, the electron temperature tended to be saturated, and several dynamic balances were reached. The Stark broadening coefficient of the 324.75 nm Cu atomic spectral line was selected in this study to calculate the electron density of the plasma. The variation tendency of the plasma electron density with the change of sample temperature was evaluated. The plasma electron density that corresponded to Cu Ⅰ 324.75 nm when the sample temperature was 130 ℃ increased by 1.74×1017 cm-3 compared with that under room temperature (18 ℃). This variation tendency was consistent with that of electron temperature. Appropriately elevating the sample temperature increased the electron density and the probability for electron and atom collision, which excited many atoms. This process was one of the reasons for the enhancement of spectral line density. Thus, elevating the sample temperature is a convenient and effective means to improve LIBS detection sensitivity.
2019 Vol. 39 (04): 1247-1251 [Abstract] ( 195 ) RICH HTML PDF (2115 KB)  ( 52 )
1252 Application of Soluuion Cathode Glow Discharge-Atomic Emission Spectrometry in Determination of Lithium in Serum
LIU Feng-kui1, ZU Wen-chuan2*, ZHOU Xiao-ping2, LIU Cong2, LIU Pan-xi1, WANG Yu2*
DOI: 10.3964/j.issn.1000-0593(2019)04-1252-04
The lithium in serum of the patients should be monitored to achieve the regular medical effect and prevent from lithium poisoning when the medicine containing lithium is adopted to treat the manic depression. At present,flame atomic absorption spectrometry and electrochemical methods are commonly used in lithium determination in clinic area. However,for the flame atomic absorption spectrometry method,the instrument can’t be portable as the C2H2 cylinder is necessary,for which the demands for the laboratory are critical. As for the electrochemical technique,the treatment of the electrodes is tedious and the analytical efficiency is somewhat low. The solution cathode glow discharge-atomic emission spectrometry,which has proved to be sensitive for Li determination with simple operation and portable instrument,has never been used in clinic Li test in serum. Therefore,a novel method was established for sensitive determination of lithium in serum based on a home-made portable solution cathode glow discharge- atomic emission spectrometer. The serum samples were pumped into the discharging chamber after dilution and acidification. Lithium in serum was excited by the plasma generated between the solution cathode and the solid metal anode,and the characteristic spectrum came into being in the common atmosphere and the signal collection and analysis were carried out by using a fiber optical spectrometer. The influence of dilution times within 10~100 on matrix interferences was comprehensively investigated and the results showed that no significant matrix interferences were observed when the dilution times were above 20 and the reliability could be basically ensured. The parameters influencing the analytical performances,including the analytical emission line,the acidity of the testing solution,etc,were optimized. The results showed that 671 nm was proved to be the ideal analytical emission line due to the strongest emission intensity and the non-significant spectral interferences while the best analytical performance could be achieved when 1% HNO3V/V)was adopted to keep the acidity of the solution on the premise of the suitable stability. Under the optimized conditions,the equation of the linear calibration curve was as follows:Ie=7 299ρLi+400;R2=0.998 3. The limit of determination for lithium in the serum was 0.2 mg·L-1 when the serum sample was diluted by 20 times. The relative standard deviation for the repeatability test based on 6 times tests of the serum was below 5%. This method was applied to the analysis of serum standard material. The detection result was in favorable agreement with the certified value,which showed that this method can be used in the determination of lithium in real serum samples of clinical tests.
2019 Vol. 39 (04): 1252-1255 [Abstract] ( 277 ) RICH HTML PDF (1748 KB)  ( 185 )
1256 Quantification of Trace Impurities in Graphite by Glow Discharge Mass Spectrometry
WANG Zi-ren, WANG Chang-hua, HU Fang-fei, LI Ji-dong*
DOI: 10.3964/j.issn.1000-0593(2019)04-1256-06
Graphite material is an ideal inorganic non-metallic material with high chemical stability, good conductivity, and good wear resistance. As graphite is a refractory substance, it is difficult to test the trace element contents by using common chemical methods or conventional instrumental analyses. Common problems in the graphite analysis by the Fire-ICP method are as follows: (1) the individual elements are easily lost during the high temperature burning pretreatment process, and (2) the graphite cannot be dissolved completely during the process of adding acid dissolution. Therefore, many scholars began using solid analytical technology to determine the impurity contents in graphite. Glow discharge mass spectrometry (GDMS) is a technology combining glow discharge power supply (GD) with mass spectrometry (MS). It has advantages of simple pretreatment, weak matrix effect, low detection limit and high sensitivity. It has become a division of high pure metal and semiconductor materials at home and abroad. Relative sensitivity factor (RSF) is a coefficient used to correct GDMS analysis results. For GDMS analysis, most elements still have obvious matrix effect in different matrixes. In order to make GDMS analysis as a quantitative analysis method, it is necessary to use the standard material matching the matrix to correct the RSF. However, most of the GDMS analysis is based on the standard relative sensitivity factor (RSFStd) provided by instrument manufacturers and only semi quantitative analysis results can be obtained. This paper describes an analytical method to determine the content of 9 elements in graphite materials using GDMS. Through the optimization of the discharge conditions, the suitable discharge conditions of graphite were determined (current intensity as 55 mA, discharge gas flow rate as 450 mL·min-1). Under optimized analytical conditions, 9 impurities (Mg, Cr, Ni, Ti, Fe, Cu, Al, Si and Ca) were determined. The result of t-test showed that there was significant difference between the results of most elements and the reference value. In order to obtain more accurate results, the corresponding RSFx of each element was required to establish quantitative analysis methods. Through experiments, the effects of different current intensity and discharge gas flow on the RSF value of 9 elements were investigated, and the causes of the influencing factors were discussed. The experimental results showed that the current intensity and discharge gas flow have a great influence on the RSF value of most elements. The discharge gas flow has the greatest influence on the RSF value, and the RSF value of each element varies between 15% and 405%. Under selected conditions, the content of 9 impurity elements, such as Mg, Cr and Ni in graphite materials, was quantitatively analyzed by RSFx value. The t-test sig value of the test results was more than 0.05, indicating that there was no significant difference between the measured results and the reference value, and the accuracy of the method was significantly improved. The relative standard deviations (RSD) were between 3.2% and 9.9%. The method can meet the need for the analysis of high purity graphite materials above 4N purity.
2019 Vol. 39 (04): 1256-1261 [Abstract] ( 315 ) RICH HTML PDF (2366 KB)  ( 103 )
1262 Determination of 21 Inorganic Elements in Urine Samples by ICP-MS Using KED System
LIU Liu1, 2, LIU Zhe1, YANG Yi-bing3, WANG Qin1, XU Dong-qun1*
DOI: 10.3964/j.issn.1000-0593(2019)04-1262-05
The content of elements in blood and urine samples can effectively reflect the internal exposed information by different pathways. Currently, there are many methods for pretreat method, such as digestion and direct dilution. But these methods have their own weak points. In order to obtain the contents of multi-elements in urine, an analytical method was established for accurate determination of Mn, Co, V, Cu and Zn in urine by using inductively coupled plasma-mass spectrometry (ICP-MS) with kinetic energy discrimination system (KED). The method is improved on the basis of direct dilution method, after the pre-preparation, such as water-bath heating and supersonic, and the 21 inorganic elements in urine samples were determined by ICP-MS. The changes of background equivalent concentration (BEC) for multi-elements in KED mode were optimized in detail. Application of kinetic energy discrimination and collisional cleavage between helium atoms and interfering molecules reduces the influence of mass spectrometry interference such as polyatomic interference on the determination. The matrix effects and signal drift were adjusted by the online addition of internal standards and the standard addition method. The flow rate and rejection parameter q (Rpq)in the KED mode were selected by considering the BEC and the best gas flow rate for He was 3.8 mL·min-1, Rpq=0.45, respectively. The detection limit for the 21 inorganic elements were between 0.004~12.08 μg·L-1, under the optimized conditions. The liner correlation coefficient (R2) of analyzes were ≥0.999 in the range 0~200 μg·L-1. The recovery of all elements ranged from 81.8% to 112.6%, and the relative standard deviation (RSD) was under 5%. The method study research indexes were much lower than the “Simultaneous determination of a variety of metals in urine-Inductively coupled plasma mass spectrometry method”(GBZ/T 308—2018). The method is simple, rapid and accurate, which can be used to determine inorganic elements in urine samples directly, providing a scientific basis for public health emergency and clinical examination.
2019 Vol. 39 (04): 1262-1266 [Abstract] ( 278 ) RICH HTML PDF (846 KB)  ( 198 )
1267 Investigation on Experimental Conditions and Quantitative Analysis for Fe and Si Elements in General Aluminum by Laser Induced Breakdown Spectroscopy Technique
LU Hui1,2, HU Xiao-jun1*, CAO Bin2, SUN Lan-xiang3, CONG Zhi-bo3, DONG Wei3
DOI: 10.3964/j.issn.1000-0593(2019)04-1267-07
In order to promote the application of LIBS technology in electrolytic aluminum industry, give full play to its advantages of rapidness, no preparation and multi-element simultaneous detection. The contents of Fe and Si elements in general aluminium procuced from electrolysis process were detected by means of laser induced breakdown for the first time, and the reasonable experimental conditions were explored, the calibration curves were established and the content of Fe and Si in general aluminium were quantitatively analyzed based on reasonable experimental conditions. The accuracy of LIBS measurement results were examined according to national standard GB / T 7999—2015 “optical emission spectrometric analysis method of aluminum and aluminum alloy”. The fundamental frequency 1 064 nm laser produced by Nd∶YAG pulsed laser device as the excitation source producing plasma,the spectral informations were detected and recorded by multi-channel grating spectrometer and ICCD detector. First of all, LIBS spectral line was detected and the spectral line was assigned, the line of Al Ⅰ 266.04 nm, Si Ⅰ 288.15 nm and Fe Ⅰ 259.92 nm were selected for quantitative analysis through comprehensive consideration. The influence of trigger delay time, 1Q delay time, laser setting voltage on the spectral signal intensity and SNR were researched respectively in the paper. The experimental results show that the trigger delay time of 4 μs, 1Q delay time of 170~190 μs, the laser set voltage of 560 V are the reasonable experimental parameters for Si and Fe element quantitative analysis in this paper. According to the relationship between spectral intensity and elemental concentration, the calibration curves were cestablished by the internal standard method. The correlation coefficients were 0.952 11 and 0.919 72, and the relative standard deviation were 6.34% and 7.25% for Fe and Si elements respectively. There was a good linear relationship between concentration and spectral intensity, and the 12 samples were quantitatively analyzed base on the above model. The relative error of Fe content is 0~17.3% and the relative error of Si content is 0~14.3% compared with the results obtained by OES. The measurement results 100% comply with the allowable requirements for Si content in 12 samples, and the results 91.7% meet the allowable difference requirements according to national atandard GB/T 7999—2015 “optical emission spectrometric analysis method of aluminum and aluminum alloy”. The experimental results show that, LIBS technology has a certain value of promotion and using in the electrolytic aluminum industry for Fe and Si elements detection.
2019 Vol. 39 (04): 1267-1273 [Abstract] ( 238 ) RICH HTML PDF (5456 KB)  ( 64 )
1274 The Characterization Study on Quantity of Filled Glass Material in Ruby
XIANG Zi-han1, YIN Zuo-wei1,2*, ZHENG Xiao-hua2
DOI: 10.3964/j.issn.1000-0593(2019)04-1274-06
In this paper, the lead glass filled ruby is the main study object and the characteristics of filling amount were studied. Its conventional gemological parameters were tested, including refractive index, polarization, ultraviolet fluorescence, visible spectrum, etc. At the same time, the characteristics of the filling quantity were studied using the microphotography, X-ray fluorescence spectrometer, and infrared spectrometer. The average results were obtained through multiple tests. Based on analysis, the filled samples’ gemstones parameters were consistent with the natural rubies’. Excepting a few showing all light in polarization tests that associated with fillings focused on mesa distribution. The X-ray fluorescence spectrometer showed that the lead peak was high and shape was stinging, indicating the fillings was large and obvious. At the same time, the internal and external characteristics of the quantity of fillings of all samples were studied by using microscopic magnification, and the comparison research could be made to distinguish the quantity of fillings of some samples. It was found that the internal and external characteristics of the filling were the dotted, linear and reticulate structure and pits; a single or group of bubbles; the filling of a fog-shaped structure formed along the fissure surface; the blue flash effect and filling hole, and the more filling volume is, the more obvious the filling characteristics are. By comparing the size, shape and quantity of surface filling cracks; Bubbles’ size and shape; the obvious degree of the distribution area of the yellow fillings under the diffuse reflection illumination can distinguish the different filling amount of different samples. Infrared spectrum testing shows that the main peaks are 2 920, 3 424, 2 600 and 2 851 cm-1. The 2 920 cm-1 is for diaspora, andthe 2 851 cm-1 is for the other inclusion, and 2 600 and 3424 cm-1 are for typical indicated peaks of the lead glass fillings. Among them, 3 424 cm-1 is the vibration absorption peak of the water molecule, and the 2 600 cm-1 is the absorption peak of Si—OH. If the 2 600 cm-1 is taken as an example, the quantities of the fillings are different, and the intensity of peak shape and height is also different. Meanwhile taking the peak at 2 600 cm-1 as criterion, it is concluded the different values of peak height’ histogram with the value of peak height is proportional to the quantity of fillings, so the histogram can indicate the variable quantity of glass fillings. By comparing the samples, the peak of R-6 is lower than R-3, and R-3 is lower than R-5, and the peak of R-5 is the highest, and illustrating quantities of fillings of R-6 is least, and R-5 is the most. This is in line with most of the results of the microphotography. Through the above research and analysis, lead glass fillings mainly do not affect the ruby gemological parameters, but the distribution of internal and external filling characteristics can basically distinguish the differences of filling quantities, but for samples with very serious fillings, it has limitation. The infrared spectrum makes up for this defect to some extent, and can distinguish the small difference between the filling quantities by the peak height calculation of the filling point peak. This also lays a foundation for the quantitative classification of lead glass filled rubies.
2019 Vol. 39 (04): 1274-1279 [Abstract] ( 180 ) RICH HTML PDF (3405 KB)  ( 81 )
1280 Study on Manufacturing Technique for Glazed Tiles Bodies from Mingzhongdu Site, Fengyang
YANG Gui-mei1, 2, YANG Yu-zhang1*, YAO Zheng-quan2, ZHANG Mao-lin3, WANG Zhi2, ZHANG Ju-zhong1
DOI: 10.3964/j.issn.1000-0593(2019)04-1280-08
In order to explore the manufacturing technique level and characteristic for glazed tiles in early Ming dynasty, Energy Disperse X-Ray Fluorescence(EDXRF) was used to the determination of chemical composition of 69 pieces glazed tiles bodies from Mingzhongdu Site in Fengyang(FMZD), and Minggugong Site in Nanjing(NMGG), thermal expansion instrument, water absorption rate determinator and polarizing microscope were used to analyze the bodies’ firing temperature and the rate of water absorption and apparent porosity, bulk density, microstructure. The results showed that, the sample bodies were divided into three types: high Ca and Fe, low Ca high Fe and low Ca low Fe, which meant that the raw materials of samples were from different areas. The chemical composition of some FMZD’s samples had a great similarity with NMGG, while the two places had obvious difference in chemical composition compared with Beijinggugong’s glazed tiles bodies, which suggested the raw materials for Beijinggugong’s samples were different from the Mingzhongdu and Minggugong’s samples. The results of firing temperature and physical properties, microstructure showed that: firing temperature of porcelain body in FMZD was so high that reached 1 140 ℃, lower in water absorption and porosity, and the porcelain body met the requirement of standards. While firing temperature of the pottery bodies was about 880~1 100 ℃,higher in water absorption and porosity, obvious differences in the samples of the FMZD’s, and it was speculated that the dispersion of the raw materials origin of the FMZD’s tiled glazes caused the differences on the firing temperature, water absorption and porosity. Compared with samples of NMGG and BGGM, absorption and porosity of the FMZD’s samples were higher than that’s, but firing temperature of the pottery bodies of the three places was below 1100℃. The microstructures of the FMZD and NMGG’s samples were rarely different from the pictures of the microstructures, which showed that the bodies raw materials were smashed subtly and elutriated highly, sintered higher, and tiled glazes had the better performance comparison. By studying the firing technology for tiled glazes during Hongwu Period in early Ming Dynasty, it not only enriched the course of the technological development of the tiled glazes, but also offered the gist for understanding the making-technology of tiled glazes and organization form of building Mingzhongdu.
2019 Vol. 39 (04): 1280-1287 [Abstract] ( 242 ) RICH HTML PDF (4289 KB)  ( 78 )
1288 Occurrence of the Impurities in Phosphorus Rock and the Research of Acidolysis Process
LI Xu1, 2, ZHU Gan-yu3, GONG Xiao-kang1, LI Shao-peng3, XU Wei1, LI Hui-quan3, 4*
DOI: 10.3964/j.issn.1000-0593(2019)04-1288-06
In the process of wet-process phosphoric acid, the impurities in the mineral have great effects on the crystallization of calcium sulfate and restrict the utilization of phosphogypsum. Choosing the typical low-grade phosphorus rock in Hubei province of China as the material, the types and contents of main impurities in phosphorus rock and phosphogypsum have been analyzed through X-ray photoelectron spectroscopy, scanning electron microscopy, and EDS. The main changes of the impurities have been evolved in wet-process phosphoric acid. The results show that fluorapatite and quartz are the main phases in phosphorus rock. The highest impurity components are silicon, aluminum, fluorine, and magnesium. Silicon exists in silica and calcium silicate, and fluorine is all in fluorapatite, and aluminum exists in different kinds of aluminosilicate, and most of magnesium exists as MgF2. Calcium reacts with sulfuric acid to form gypsum through acidolysis reaction. Silicon mainly remains in solid phase. Most of aluminum, fluorine, and magnesium decompose into liquid phosphoric acid. Silica still remains in phosphogypsum, and calcium silicate dissolves in acid solution. The compound comprised of aluminum, silicon and phosphorus forms in acidolysis process. Fluorine is mainly in silicofluoride. Most of MgF2 dissolve into solution, and remaining part of Mg in phosphogypsum mainly exists as magnesium silicate. Through the research of occurrence of impurities, the system change may be better acknowledged in the process, and it can provide a basis for the investigation and control of phosphogypsum crystallization.
2019 Vol. 39 (04): 1288-1293 [Abstract] ( 206 ) RICH HTML PDF (4865 KB)  ( 97 )
1294 The Genesis and Geological Implications for Oceanic Redbeds of the South China Sea in U1434 of IODP Expedition 349——the Constraint from Diffuse Reflectance and X-Ray Fluorescence Spectroscopy
JIANG Lian-ting1, SUN Jie1*, HU Li-tian2, 3*, ZHAN Wen-huan1, TANG Qin-qin1, LI Jian1
DOI: 10.3964/j.issn.1000-0593(2019)04-1294-07
We presented a new finding that the occurrences of oceanic redbeds in the South China Sea (SCS) first discovered from Expedition 349 are similar to those in Sulu Sea and Celebes Sea from Expedition 124, as well as to the continental redbeds in Sanshui Basin of China, all directly covering massive magmatic rocks with significance for revealing the connections between oceanic redbeds and magma thermal events. We measured the samples collectted from marine sedimentary with colors ranging from celadon to rufous in U1434 of IODP Expedition 349, and analyzed the influence of oxygen fugacity and geothermal temperature on the formation of pigment in redbeds. By comparing red-nonred sediments and experimental samples, we discussed the redbed genesis and its geological implications. We obtained the red values, the content of goethite, hematite and quantivalent Fe in marine sediments and experiment samples through the analysis of diffuse reflectance and fluorescent spectroscopy and Fe2+ in titration test. The results showed that, (1) Red and non-red marine sediments are formed at high oxygen fugacity environment in U1434 of IODP Expedition 349, and difference in oxidation-deoxidation environment was not the controlling factor on red and non-red sediments; (2) The oceanic redbeds directly covering basalts in U1434 of IODP Expedition 349 originated from high geothermal temperature during sedimentary- diagenesis process; (3) And we found that continental redbeds and Cretaceous oceanic redbeds formed in different geological periods are closely associated with tectonic- magmatic active belts, showing that redbeds have significance in indicating geological thermal events.
2019 Vol. 39 (04): 1294-1300 [Abstract] ( 175 ) RICH HTML PDF (4616 KB)  ( 68 )
1301 Spectral Analysis of Sky Light Based on Trajectory Clustering
CAI Jiang-hui1, YANG Yu-qing1, YANG Hai-feng1*, LUO A-li2, KONG Xiao2, ZHANG Ji-fu1
DOI: 10.3964/j.issn.1000-0593(2019)04-1301-06
Skylight background subtraction is an important part of LAMOST 1D spectral data processing, and constructing ideal super sky spectral models is of great significance since it may directly affect the quality of the spectral products. Generally, the super sky spectral models are composed of the spectra from sky fibres simultaneously observed with target objects, and sky background may be of regular variation along with different observation times. Taking full account of these timing features, the super skylight model can be effectively corrected to improve the skylight reduction effect. Meanwhile, the trajectory clustering method is an effective tool for analyzing the characteristics of the target with temporal and spatial variation. Therefore, a method for analyzing the characteristics of the sky spectra based on the trajectory clustering is provided in this paper orienting to the possible variation laws in the sky spectra of LAMOST. It includes the following 3 parts: (1) the time series description of sky spectra. In fact, LAMOST pipeline uses and provides the instant super sky spectra for each observed target. In order to obtain the light-changing characteristics of the sky background spectra of a specific sky area, the time series of sky spectra are re-described by selecting the sky fiber spectra and background spectra without target component, taking the 5-degree field of view (the Fov of LAMOST) as processing unit, and evenly grouping these spectra by observation date. (2) density-based clustering algorithm (STK-means) for sky spectra. In order to solve the problem that the random parameters may lead to relatively poor convergence and clustering, a density-based similarity measurement formula is studied. The values of this formula are used as the selection basis of the initial parameters, and then a new algorithm named STK-means is proposed after updating the traditional k-means algorithm. (3) experiment analysis. Firstly, by experiment, the correctness and effectiveness of this method is verified, and clustering effect is analyzed by utilizing different initial parameter k. And then, the trajectory characteristics of sky spectral time series are analyzed by selecting the sky spectra from one of complete small sky areas in the first phase of LAMOST survey. The experimental results show that the sky background in particular region is distributed symmetrically around the lunar 15th and 16th of each month, which indicates the influence partly from the moon phase during the observation process in this sky area. These timing characteristics can be quantified to correct the super sky spectral model. Meanwhile, uniform sampling of data during the description of time-series spectra is very important, so this method can be effectively applied to the regions of high celestial number density such as GAC, disk, halo, etc. On the contrary, the longer time survey is necessary for the low number density areas. In addition, this method may also effectively find outlier sky spectra of specific regions, which will provide rare samples for further physical study.
2019 Vol. 39 (04): 1301-1306 [Abstract] ( 292 ) RICH HTML PDF (3650 KB)  ( 102 )
1307 Stellar Spectra Classification by Support Vector Machine with Spectral Distribution Properties
LIU Zhong-bao1, 2, QIN Zhen-tao1, LUO Xue-gang1, ZHOU Fang-xiao1, ZHANG Jing1
DOI: 10.3964/j.issn.1000-0593(2019)04-1307-05
Stellar spectra classification is one of hot spots in astronomy. With hundreds and thousands of spectra obtained by researchers, it is a big challenge to process them manually. It’s urgent to apply the automatic technologies, especially the data mining algorithms, to classify the stellar spectra. Neural networks, self organization mapping, association rules and other data mining algorithms have been utilized to classify the stellar spectra in recent years. In these methods, Support Vector Machine (SVM), as a typical classification method, is widely used in the stellar spectra classification due to its good learning capability and excellent classification performance. The basic idea of standard SVM is to find an optimal separating hyper-plane between the positive and negative samples. Its time complexity is so high that its classification efficiencies can’t be greatly improved. Twin Support Vector Machine (TWSVM) is proposed to deal with the above problem. It aims at generating two non-parallel hyper-planes such that each plane is close to one class and as far as possible from the other one. The learning speed of TWSVM is approximately four times faster than the classical SVM. The limitation of TWSVM is that it doesn’t take spectral distribution properties into consideration, and its efficiencies are prone to be influenced by noise and singular points. In view of this, Fuzzy Twin Support Vector Machine with Spectral Distribution Properties (TWSVM-SDP) is proposed, in which between-class scatter and within-class scatter in Linear Discriminant Analysis (LDA) is introduced to describe the spectral distribution properties and the fuzzy membership function is introduced to decrease the influences of noise and singular points. Comparative experiments on SDSS DR8 stellar spectra datasets verity TWSVM-SDP performs better than SVM and TWSVM. However, some limitations exist in TWSVM-SDP, for example, how to deal with the mass spectra is quite difficult to solve. We will research the adaptability of our proposed method in the big data environment based on big data technologies.
2019 Vol. 39 (04): 1307-1311 [Abstract] ( 189 ) RICH HTML PDF (538 KB)  ( 70 )
1312 Automatic Classification Method of Star Spectra Data Based on Convolutional Neural Network
SHI Chao-jun1, QIU Bo1*, ZHOU Ya-tong1, DUAN Fu-qing2*
DOI: 10.3964/j.issn.1000-0593(2019)04-1312-05
Star spectral automatic classification is the basis for the study of Star Spectral analysis. The fast and accurate automatic identification and classification of the star spectra can improve the search for the speed of the special celestial bodies, which is of great significance to the study of astronomy. At present, LAMOST, a large-scale spacecraft project in China, releases millions of spectral data every year. Fast and accurate automatic identification and classification of massive star spectra has become one of the hot spots in the field of astronomical data analysis and processing. Aiming at the problem of star spectral automatic classification, a new spectral classification method of K, F stellar based on convolutional neural network (CNN) is proposed. Support Vector Machine (SVM) and Back Propagation (BP) neural network algorithms are compared algorithms. The cross-validation method is used to verify the performance of the classifier. Compared with the traditional method, CNN has the advantages of sharing the weight and reducing the learning parameters of the model. It can automatically extract training data features. The experiment uses the Tensorflow depth learning framework and the Python 3.5 programming environment. The K, F stellar spectral dataset uses the LAMOST DR3 data provided by the National astronomical observatory of the Chinese academy of sciences. Spectra with wavelengths in the 3 500 to 7 500 range are sampled evenly to generate data sets. Data sets were normalized using the min-max normalization method. The CNN structure includes an input layer, a convolution layer C1, a pooling layer S1, a convolution layer C2, a pooling layer S2, a convolution layer C3, a pooling layer S3, a full connection layer and an output layer. The input layer is the flow value at 3 700 wavelength points of a group of K and F stars. The C1 layer has 10 convolution kernels in size of 1×3 steps of 1. S1 layer using the maximum pooling method. The size of the sampling window is 1×2, no overlapping sampling. The sampling result produces 10 features, which is the same as the number of the C1 features, and each feature is one-half the size of the C1 feature. The C2 layer has 20 convolution kernels of size 1×2 steps of 1 which outputs 20 feature maps. S2 layer outputs 20 features. The C3 layer has 30 convolution kernels of size 1×3 steps of 1 which outputs 30 feature maps. S3 layer outputs 30 features. The number of fully connected layer neurons is set to 50, and each neuron is connected to all the neurons in the S3 layer. The number of neurons in the output layer is set to 2, and the output classification results are obtained. The activation function of convolution layer uses the ReLU function, and the activation function of output layer uses the softmax function. The contrast algorithm SVM type is C-SVC, and its kernel function uses the radial basis function. The BP algorithm has three hidden layers, each with 20, 40 and 20 neurons. Data set is divided into training data and test data. The training data of 40%, 60%, 80% and 100% are used as training sets and the test data is used as a test set. The training sets are put into the model for training. Each training iteration 8 000 times. Each trained model is validated with a test set. The training data of 100% are used as a training set for comparative experiments. And test data are used as a test set. The accuracy, recall, F-score and accuracy are used to evaluate the performance of the model. The results of experiments are analyzed in detail. Analysis results show that CNN algorithm can quickly and automatically classify and screen K, F star spectra. The greater the amount of data in the training set, the stronger the model generalization ability and the higher the classification accuracy. Contrast experiment results demonstrate that CNN algorithm significantly outperform the competitors SVM and BP algorithms on automatic classification method of K and F star spectra data.
2019 Vol. 39 (04): 1312-1316 [Abstract] ( 254 ) RICH HTML PDF (1677 KB)  ( 111 )
1317 Retrieval of Atmospheric H2O Column Concentration Based on Mid-Infrared Inter-Band Cascade Laser Heterodyne Radiometer
ZHANG Shang-lu1, 2, HUANG Yin-bo1, LU Xing-ji1, 2, CAO Zhen-song1, DAI Cong-ming1*, LIU Qiang1, GAO Xiao-ming1, RAO Rui-zhong1, WANG Ying-jian1
DOI: 10.3964/j.issn.1000-0593(2019)04-1317-06
Water vapor is an important component of the atmosphere. It is also an important factor to balance the radiation budget of the atmosphere system, which has an important influence on weather and climate change. The commonly used equipment for measuring the concentration of water vapor column, such as Radiosonde, Lidar, Microwave Radiometer, Solar Photometer, DOAS instrument and Fourier Transform Infrared Spectrometer are difficult to meet the requirements of high-resolution and portable mobility. Based on a high-sensitivity and high-resolution spectral detection technology, related researches have been carried out around the detection of water vapor column concentration. The main achievements are as follows: (1) Based on the laser heterodyne spectroscopy technology, a set of high-resolution laser heterodyne solar spectrum measuring devices with a narrow-line broadband inter-cascade laser as the local oscillator and the sun tracker is estabished, with a spectral resolution of 0.002 cm-1. (2) The Langley-plot method is used to calibrate the high-resolution heterodyne solar spectrum measuring device. The field measurement is carried out at the Purple Mountain Observatory in Yunnan, and the direct measurement data of the 2 831~2 833 cm-1 band solar spectrum are obtained. The high-resolution total atmospheric spectral transmittance is also obtained. (3) The Line by Line Radiative Transfer Model (LBLRTM) is used to calculate the total atmospheric spectral transmittance, and the nonlinear least square fitting is carried out with the measured spectral transmittance. The inversion of water vapor column concentration is realized. The concentration of water vapor column is also observed by the Microwave Radiometer. The consistency between the inversion results and the measured resultsis is relatively good, where the minimum relative deviation is 16.59%, and the maximum relative deviation is 21.69%. (4) The error of the inversion results and the measured results is mainly caused by the error of the inversion algorithm and the measurement error of the device. Inversion algorithm errors include the calculation error of the radiative transfer model, the actual temperature measurement error, the methane concentration uncertainty into the error, the deviation of HDO abundance and the natural abundance. The device measurement error includes the calibration error of device, the wavelength calibration error, the noise influence, the error caused by the weak fluctuation of the background signal and the DC signal. (5) The 2 831~2 833 cm-1 band selected contains the absorption of water vapor and methane, and the concentration of methane column is also retrieved. With the initial column concentration of methane as the reference value, it is found that the numerical average of the concentration of the methane column after the inversion is 14.41% higher than the initial column concentration. The high-resolution laser heterodyne solar spectrum measurement device combined with its inversion algorithm is an effective integrated equipment for detecting the whole atmospheric transmittance and the concentration of water vapor and methane column. It has a wide application prospect in the detection of multi-component gas concentration.
2019 Vol. 39 (04): 1317-1322 [Abstract] ( 190 ) RICH HTML PDF (2254 KB)  ( 101 )
1323 Comparison of Near-Infrared Spectrum Pretreatment Methods for Jujube Leaf Moisture Content Detection in the Sand and Dust area of Southern Xinjiang
BAI Tie-cheng1,2, WANG Tao2, CHEN You-qi3, MERCATORIS Benoît1*
DOI: 10.3964/j.issn.1000-0593(2019)04-1323-06
Precision irrigation for jujube crop in southern Xinjiang, China, is underlying to optimize the water use in such a drought-affected region. Water stress can be remotely assessed by evaluating the leaf moisture content using spectroscopy. These measurements are however affected by the presence of coarse sand and dust of the leaves induced by dry climates. This paper studied different methods to correct the spectral data in order to reduce the scattering noise with a baseline induced by such a jujube leaf covering. The reflectance of 120 leaf samples were measured by means of a near-infrared spectrometer (1 000~1 800 nm) and their moisture content was obtained by conventional drying method. The original reflectance spectrums were pre-processed by the normalization method, the moving smoothing method, the Savitzky-Golay (SG) convolution smoothing method, the SG first derivative method, the standard normal variables (SNV) method and the multiple scatter correction (MSC) method. The results of these different methods were compared and analyzed by means of partial leastsquares regressions (PLSR) allowing selecting sensitive spectral bands and establishing prediction models. The results showed that a significant reflectance peak related to the water content of the jujube leaves was located at 1 443 nm and that a local minimum of reflectance occurred at 1 661 nm. The predicition model based on the MSC method presented the best scattering noise reduction. The model performances were R2=0.750 4, RMSEP=0.034 3 and RMSEPCV=0.021 5. The five characteristic wavelengths were 1 002, 1 383, 1 411, 1 443 and 1 661 nm. In this experiment, the MSC method had a good ability to reduce the scattering noise generated by sand and dust covering. The preprocessing improved the selection ability of characteristic wavelengths and the accuracy of the prediction model. The results can therefore provide an effective detection method for the jujube leaf water in the sandy and dusty area of Southern Xinjiang, China.
2019 Vol. 39 (04): 1323-1328 [Abstract] ( 267 ) RICH HTML PDF (3071 KB)  ( 136 )