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2018 Vol. 38, No. 08 Published: 2018-08-01

	2325	Research Progress of High-Voltage LED Chip
		WANG Jia-lu, GUO Wei-ling^*, LI Song-yu, YANG Xin, SUN Jie
		DOI: 10.3964/j.issn.1000-0593(2018)08-2325-07
		High-voltage light-emitting diode has the characteristics of high working voltage, small drive current, high efficiency, high reliability and low energy consumption, which has been widely studied and applied. This paper first introduces the basic principle of high-voltage LED, classification and structure; Then, the latest research progress of the key fabrication technology of high-voltage LED is described, from the point of optimizing the photoelectric characteristics of the devices; The reliability of high-voltage LED are discussed from the aspect of failure mechanism and thermal characteristics as well; Finally, its development and application prospects are prospected.
		2018 Vol. 38 (08): 2325-2331 [Abstract] ( 204 ) RICH HTML PDF (4264 KB) ( 124 )

	2332	The Influence of Noise on Ranging Accuracy of the Frequency Modulation Continuous Wave Laser Radar Based on Equal Frequency Sampling Method and Experimental Verification
		XIONG Xing-ting, QU Xing-hua^*, ZHANG Fu-min
		DOI: 10.3964/j.issn.1000-0593(2018)08-2332-05
		Because of the advantages such as the large measurement range, high accuracy and not needing cooperation target, frequency modulation continuous wave (FMCW) laser radar plays an important role in metrology and industrial measurement. This paper briefly introduces the basic structure and ranging principle of frequency modulation continuous wave laser radar, which was based on equal frequency sampling method. The main noises that exist in the auxiliary interference signal and the measurement interference signal and their characteristics were analyzed. When the auxiliary interference signal of the system was existed with noise, part of the extreme points was incorrect and the measurement error will be brought into the result. Subsequently, the Cramer-Rao lower bound was adopted to evaluate the influence of the noise that existed in the measurement interference signal. To improve the accuracy and stability of the measurement, the adaptive filtering methods of wavelet threshold filter based on EMD and Hanning band-pass filter based on wavelet filtering were used to reduce the noise existing in auxiliary interference signal and the measuring interference signal, respectively. In the experiments, a flat mirror and a variety of roughness blocks were measured very times and the correctness was verified by comparing the measured results of the system with a precision guide. Experimental results showed that：when the measured object was located at stand-off distance of about 3.9 m, the adaptive filtering methods can effectively remove the noise and the measurement uncertainty of the mirror and the roughness blocks was 20 μm anti>tainty of the wavelet filtering method (120 μm and hundred microns). At the same time, by comparing the displacement value of the precise guide rail and the measurement results of the system, it proves that the proposed method in this paper can effectively improve the measurement accuracy of the system.
		2018 Vol. 38 (08): 2332-2336 [Abstract] ( 193 ) RICH HTML PDF (2439 KB) ( 184 )

	2337	Preparation and Spectral Properties of White Light Emitting LED Based on Layered Remote Phosphor Film
		ZHUO Ning-ze^{1, 2, 3}, ZHANG Na^{1, 2}, CHEN Yong-hao⁴, JIANG Peng⁴, CHENG Shao-wen⁵, ZHU Yue-hua^{1, 2}, WANG Hai-bo^2*
		DOI: 10.3964/j.issn.1000-0593(2018)08-2337-07
		Based on layered phosphor and remote phosphor packaging technology, double layer remote phosphor film were prepared by hot pressing method, and the films then were packaged into white LED. Fluorescence spectrophotometer and the visible spectrum analysis system were used to study the influence on the white LED spectral properties of the layer order of green and red remote phosphor films and emission wavelength. Results showed that the luminescent efficiency of radiation of blue-green-red type package structure compared to the blue-red-green type package structure was improved by 31.69%, and the color fidelity and color gamut index increased with the increasing of red remote phosphor film wavelength. With emission wavelength 660nm, the color fidelity and color gamut index of prepared white LED reached the highest value 91 and 104 respectively. In contrast, luminescent efficiency of radiation was inversely proportional to the wavelength; color fidelity decreased with the increasing of green remote phosphor film wavelength, and color gamut index raised first, then decreased, when emission wavelength was 530 nm, with the luminescent efficiency of radiation of prepared white LED reaching the highest value 300.7 lm·W^-1. Finally, the related conclusions of present study had a certain reference value for the actual application.
		2018 Vol. 38 (08): 2337-2343 [Abstract] ( 183 ) RICH HTML PDF (5074 KB) ( 75 )

	2344	Bimolecular Excited States Based on 3DTAPBP: Electromer and Exciplex
		ZHU Wei-yi¹, JIN Min-feng¹, TU Xie-hao¹, ZHANG Ye-feng¹, YIN Yue-hong², Lü Zhao-yue^1*
		DOI: 10.3964/j.issn.1000-0593(2018)08-2344-06
		The emission of bimolecular excited states was investigated in 3DTAPBP (2,2’-bis(3-(N,N-di-p-tolylamino) phenyl) biphenyl), which is one of aniline compounds. The emission of both monomer excitons (blue light centered at 420 nm) and electromer (yellow light peaked at 578 nm) was observed in the organic light emitting diode (OLED) fabricated with 3DTAPBP monolayer (ITO/MoO₃/3DTAPBP/LiF/Al). A white OLED can be fulfilled by using the monomer exciton emission and the electromer emission, which is a very simple approach for achieving white OLED. For instance, a white light can be attained at 7.0 V in the device of ITO/MoO₃/3DTAPBP/LiF/Al, with a Commission Internationale de l’clairage (CIE) color coordinates of (0.36, 0.31). However, the brightness and efficiency were extremely poor because of the serious imbalance of carrier injection and transport in the single layer device. In addition, a bilayer device (ITO/MoO₃/3DTAPBP/TPBi/LiF/Al) were fabricated with 3DTAPBP and the electron transport material TPBi (1,3,5-tris(1-phenyl-1H-benzimidazol-2-yl) benzene). The emission peaked at around 490 nm, originating from exciplex formed at 3DTAPBP/TPBi interface, which was observed due to the accumulation of carriers at the interface. The energy of the photons is generally in agreement with the energy difference between HOMO (the highest occupied molecular orbital) of 3DTAPBP and LUMO (the lowest unoccupied molecular orbital) of TPBi. The decomposition of electroluminescent spectra with Lorentzian fitting exhibited found that the intensity of exciplex emission decreased with the increase of voltage. The reason is that more carriers tunnel cross the interface barrier of 3DTAPBP/TPBi, resulting in the increase of monomer emission of 3DTAPBP. Under the application of voltages at 4, 6, and 8 V, the color coordinates were respectively (0.28, 0.35), (0.24, 0.29), and (0.27, 0.28). And the luminous color was within the range of white at a voltage of 8 V. The highest brightness and maximum current efficiency of bilayer devices were 1 349.2 cd·m^-2 and 1.22 cd·A^-1, respectively.
		2018 Vol. 38 (08): 2344-2349 [Abstract] ( 190 ) RICH HTML PDF (4137 KB) ( 160 )

	2350	Study on Moisture Content of Soybean Canopy Leaves under Drought Stress Using Terahertz Technology
		ZHAO Xu-ting^{1, 2, 3}, ZHANG Shu-juan¹, LI Bin^{2, 3, 4*}, LI Yin-kun⁵
		DOI: 10.3964/j.issn.1000-0593(2018)08-2350-05
		With the increasingly serious situation of water resources shortage, the shortage of agricultural irrigation water in some areas has resulted in reduction of crop and damages the farmers’ interests. Soybean is kind of crop with high water requirement. Once the water deficiency will directly affect the morphology and growth, the quality and the yield will be reduced. Because water status of soybean leaves can truly reflect the degree of soil water deficit, a tool for water content measurements is in great need. The strong attenuation of terahertz radiation in water makes it a contactless probe, which can be used to detect the water status of leaves quickly. As a result, terahertz spectroscopy technology was studied to rapidly and conveniently estimate water content in soybean canopy leaf, so as to monitor the health status in real time. Zhong-huang 13 soybean cultivars were cultivated in our experiment. In order to simulate the drought stress of different degrees in the field, 5 different gradients of flowering soybean were carried out: normal watering, mild drought stress and moderate drought, severe drought, more severe drought stress (accounted for 80%, 65%, 50%, 35%, 20% of the maximum water holding capacity in the field, respectively) and 3 repetitions were set per gradient. The artificial weighing method combined with the portable soil moisture measuring instrument was used to regulate soil moisture content to meet the requirements of the various water gradients . Then, the experimental soybean were transported to the laboratory, and the samples were scanned by terahertz time domain spectrometer. 18 canopy leaves for each gradient, a total of 90 samples were collected. It was divided into calibration set and prediction set at 2∶1 ratio. After obtaining the time domain spectral data of each sample, the absorption coefficient spectrum and the refractive index spectrum of each sample were calculated by the data processing method of Dorney and Duvillaret. The changes of time domain spectroscopy, absorption coefficient and refractive index with water drought stress were qualitatively analyzed. It was found that the peak value of time domain spectrum was decreasing with the degree of water stress decreasing, which was lower than the reference value. At the same time, there was a significant time delay. The number of absorption coefficient gradually decreased with the aggravation of drought stress, and the refractive index value the same decreased. Moreover, partial least squares (PLS) and multiple linear regression (MLR) were used to quantitatively study the correlation between time domain spectrum, absorption coefficient, refractive index spectrum data and leaf water content, respectively. The results showed that, terahertz was sensitive to differences of leaf water content. And the MLR model based on maximum and minimum values in time domain spectral performed the best, in which correlation coefficient (r_P) and root mean square error of prediction set (RMSEP) were -0.939 3 and 0.049 5, respectively. This study showed that the application of terahertz technology in leaf water content estimation has good feasibility. It will provide a new detection tool and experimental basis for rapid monitoring of water content in soybean canopy and scientific water-saving irrigation management.
		2018 Vol. 38 (08): 2350-2354 [Abstract] ( 171 ) RICH HTML PDF (1458 KB) ( 113 )

	2355	Study on Rapid Screening of Ignitable Liquid by Attenuated Total Reflection Infrared Spectroscopy
		CHENG Fang-bin¹, SUN Zhen-wen^2, LIU Zhan-fang², ZHANG Guan-nan², XU Jing-yang³, QIAO Ting², ZHU Jun², CHEN Ling-xin⁴, LIU Yao^1,2
		DOI: 10.3964/j.issn.1000-0593(2018)08-2355-07
		As a destructive criminal behavior, arson has brought serious losses to public safety and social stability. Subject to the destruction of fire and fire fighting behavior, most evidence has become beyond recognition. It brings a great difficulty in determining the direction of investigation and a fair trial of criminal suspect. The ignitable liquids at fire scenes are important evidence to judge the case nature. And the types determination is the key point of criminal identification. In this paper, the rapid screening method of common Ignitable Liquid was established by attenuating total reflection infrared (ATR-FTIR) spectroscopy combined with PCA, HCA and DA. The IR spectra of gasoline, diesel oil, vegetable oil and oxygenated organic solvents were significant different and by virtue of this, mutual distinction can be achieved. But there was no significant difference in IR spectra of diesel, kerosene, aviation kerosene, solvent oil and turbine oil and only by direct comparison can not achieve mutual distinction. Next, the IR absorption range (1 136~976 cm^-1) combined with chemometric tools (PCA，PCA-HCA，PCA-DA) was used for separating aviation kerosene from the remaining four types of ILs. Finally, the infrared absorption peaks in the range of 837~400 cm^-1 were selected, and the other four kinds of ILs were distinguished by PCA, PCA-HCA and PCA-DA chemometrics methods. Our experimental results showed that ATR-FTIR can provide sufficient information on ignitable liquids. Combined with some chemometrics methods, ATR-FTIR successfully completed the qualitative analysis of common ILs. Once the model is established, this method becomes convenient and accurate, and can be applied to rapid screening of ILs types.
		2018 Vol. 38 (08): 2355-2361 [Abstract] ( 164 ) RICH HTML PDF (1892 KB) ( 196 )

	2362	Measurement of Tomato Quality Attributes Based on Wavelength Ratio and Near-Infrared Spectroscopy
		HUANG Yu-ping¹, Renfu Lu², QI Chao³, CHEN Kun-jie^3*
		DOI: 10.3964/j.issn.1000-0593(2018)08-2362-07
		The soluble solids content (SSC), pH and firmness (Firmness) of tomato are the key factors that determine the taste and post harvest quality of tomato. A new method for detecting tomato SSC, pH and firmness based on wavelength ratio and near infrared spectroscopy is proposed in this paper. Thespectra of six hundreds tomato samples with different maturity were collected with the portable Vis/NIR spectrometer (wavelength: 400～1 100 nm) and the portablenear infrared spectrometer (wavelength: 900～1 683 nm) in the interaction mode, respectively. After these spectra were pretreated with the wavelength ratio method are as follows：automatic scaling one and the wavelength ratio+automatic scaling one, the prediction models for SSC, pH and firmness of tomatowere developed, respectively, and then the prediction results of the four methods: are as follows automatic scaling, wavelength ratio, wavelength ratio + automatic scaling and no preprocessing were compared and analyzed. The experimental results showed that the prediction accuracy of the visible/near infrared spectra for SSC, pH and firmnesscouldbe visibly improvedby the wavelength ratio combined with the automatic scaling pretreatment, with r_p=0.779, 0.796 and 0.917, respectively. The wavelength ratio combined with the automatic scaling also could enhance the prediction ability of the Near infrared spectroscopy for SSC with r_p=0.818, which suggests that the proposed wavelength ratio method in this paper had considerable potential in optimizing and processing the spectral information of tomato.
		2018 Vol. 38 (08): 2362-2368 [Abstract] ( 193 ) RICH HTML PDF (4522 KB) ( 176 )

	2369	Qualitative Identification of Adulterated Huajiao Powder Using Near Infrared Spectroscopy Based on DPLS and SVM
		WU Xi-yu^{1, 3}, ZHU Shi-ping^1*, WANG Qian², LONG Ying-kai², XU Dan³, TANG Chao¹
		DOI: 10.3964/j.issn.1000-0593(2018)08-2369-05
		Huajiao is one of the “eight famous condiments” in China. Some cheaper adulterants were found to be added into Huajiao powder and in order to identify adulterated Huajiao powder qualitatively and quickly, a direct detecting method using near infrared (NIR) spectroscopy coupled with discriminant partial least squares (DPLS) and support vector machine (SVM) had been developed in this study. Wheat bran, rice bran, corn flour and rosin powder with 1 Wt/Wt.% incremental concentration gradient were mixed with red Huajiao powder and green Huajiao powder separately and the adulterated Huajiao powder with range of 1~54 Wt/Wt.% were prepared. Diffuse NIR spectra (800~2 500 nm) of pure and adulterated Huajiao powder were acquired. Principal component analysis (PCA) on the spectral data of all 462 samples was used and the first three principal components accounted for 98.72% of total variation. It was effective for clustering different adulterated Huajiao powder from the main composition PC1, PC2 and PC3 score plot. 347 samples as a calibration set and with the characteristic band spectrum 2 000~2 200 nm as input, kinds of qualitative models with different spectra pretreatment were established using DPLS and SVM analysis, which were for predicting the rest 115 samples. Results showed that, using different pretreatment methods, and the qualitative identification accuracy of the validation set were between 97.39%~100%, in which adulterated Huajiao powder could be identified totally. NIRS based on DPLS and SVM is a rapid and nondestructive tool for the qualitative analysis of adulterated Huajiao powder.
		2018 Vol. 38 (08): 2369-2373 [Abstract] ( 204 ) RICH HTML PDF (2798 KB) ( 167 )

	2374	A Photometric Redshift Estimation Algorithm Based on the BP Neural Network Optimized by Genetic Algorithm
		FAN Xiao-dong¹, QIU Bo^1, LIU Yuan-yuan¹, WEI Shi-ya¹, DUAN Fu-qing^2
		DOI: 10.3964/j.issn.1000-0593(2018)08-2374-05
		In addition to the spectral redshift of galaxies, the photometric redshift estimation of galaxies has important implications for the study of large-scale structures and evolution of the universe. In this paper, it chose about 150 000 galaxies’ photometric and spectral data in the latest SDSS DR13 of the Sloan survey project within the spectral redshift range of Z<0.8. The SOM self organizing neural networks were used to cluster galaxies in early type galaxies and late type galaxies. And then the photometric redshift of the galaxies was predicted by the BP neural network optimized by genetic algorithm. The prediction results were compared with the spectral redshift of galaxies. The mean square error of the redshift estimation of early type galaxies was about 0.001 3, and it for the late type galaxies was about 0.001 7. Experimental results showed that the BP algorithm optimized by genetic algorithm was more accurate than the BP neural network algorithm, and was more efficient than K nearest neighbor and kernel regression algorithms.
		2018 Vol. 38 (08): 2374-2378 [Abstract] ( 187 ) RICH HTML PDF (2115 KB) ( 73 )

	2379	SIMCA Discrimination of Ring Rot Potatoes Based on Near Infrared Spectroscopy
		ZHANG Xiao-yan, YANG Bing-nan, CAO You-fu, LI Shao-ping, ZHAO Qing-liang, XING Li^*
		DOI: 10.3964/j.issn.1000-0593(2018)08-2379-07
		China is one of the world’s largest countries in potato production and consumption. In 2015, the Chinese government put forward a staple-potato development strategy aimed to change the Chinese traditional diet habit of vegetable-potato and promote potato’s status in safeguarding food security. Potato ring rot is a common disease which has restricted the development of potato industry. With the ring rot potato as the seed, it would cause unhealthy plants; with the ring rot potato as the raw materials for processing, it would cause lower efficiency and worse product quality. Visual inspection, machinevisiontechnology and hyperspectral imaging are the traditional methodsto detect potato diseases. However, it is destructive testing when visual inspection and machinevisiontechnology are used to detect ring rot potatoes; and hyperspectral imaging is at a significant cost. There are some limitations of application on these traditional methods. Internal quality changesof potatoes is caused by ring rot diseases. Near infrared spectroscopy (NIRS) could be used to reflect the quality change of the whole potato. Therefore, NIRS can be used to distinguishring rot potatoes from healthy potatoes. It’s feasible and practical to detect potato ring rot nondestructively with near infrared spectroscopy. Combined with NIRS and soft independent modeling of class analogy (SIMCA), this experiment was aimed to identify ring rot potatoes from healthy potatoes. The results showed that, SIMCA mode based on principal component analysis (PCA) was effective to identify ring rot potatoes. In calibration set, the recognition rate and rejection rate of ring rot potatoes and healthy potatoes were both 100%. In validation set, the recognition rate and rejection rate of ring rot potatoes were 99.00% and 100%. The recognition rate and rejection rate of healthy potatoes were 94.12% and 100%. For external validation, the recognition rate of ring rot potatoes and healthy potatoes were 87.50% and 80.00% respectively without misjudge. The SIMCA model was accurate in prediction and suitable to practical application, but the precision would be improved in further research. The pathogenic site of ring rot potatoes was close to epidermis for about 0.5 cm; and there was transmission and diffuse reflection when NIRS Penetrating potatoes. So that it is possible to collect the NIRS information of potato tuber flesh near to potato epidermis. Combined with pathogenic mechanism of potato ring rot disease and characteristics of near-infrared diffuse reflectance spectra, it is innovative and practical to use NIRS to distinguish ring rot potatoes from healthy potatoes.
		2018 Vol. 38 (08): 2379-2385 [Abstract] ( 365 ) RICH HTML PDF (4312 KB) ( 88 )

	2386	Analysis of Acylation Modification of Black Rice Anthocyanins Using Fourier Transform Infrared Spectroscopy (FTIR)
		XIE Feng-ying¹, LI Feng-feng¹, ZHANG Shuang¹, BI Wei-wei², ZHANG Xiu-ling^1*, ZHANG Xiao-nan¹
		DOI: 10.3964/j.issn.1000-0593(2018)08-2386-04
		The black rice anthocyanins are vulnerable to degradation due to the external environment, resulting in the destruction of local molecular structure, which reduces the nutritional value and health function. The stability of anthocyanin structure was improved by modifying anthocyanins with acyl groups provided by organic acids. The structural changes of anthocyanins modified by caffeic acid acylation were analyzed with Fourier transform infrared spectroscopy (FTIR). The results showed that the absorption peaks of functional group in 3 650~3 200 and 1 680~1 620 cm^-1 were the same between both before and after anthocyanins modified, the phenolic hydroxyl absorption peak appeared in the fingerprint area of 1 282.68, 1 277.51 cm^-1, and the alcoholic hydroxyl absorption peak appeared at 1 056.07, 1 054.03 cm^-1, the absorption peak of C—H surface bending vibration in benzene ring appeared at 719.90 and 719.71 cm^-1. It can be seen that the major structural framework of acylated black rice anthocyanins is still the aromatic ring structure of anthocyanins. In addition, the characteristic absorption peaks of conjugated carbonyl all appeared at 1 714.28 and 1 728.13 cm^-1 in the area of 1 900～1 450 cm^-1 both before and after the modification of anthocyanins, which corresponded to α-carbonyl structure in benzene ring, thus indicating the presence of acyl groups in the structure of the black rice anthocyanins. The new absorption peaks of modified anthocyanin appeared at 1 517.20 cm^-1 in the infrared spectrum, which is right located in the stretching vibration zone of 1 800~900 cm^-1 double bond (no hydrogen), the absorption peak of C—H surface bending vibration in benzene ring appeared at 876.65 cm^-1 in the fingerprint region. At the same time, new fluctuations were observed at 2 500～2 000 cm^-1 in the infrared spectrum after the second derivative treatment, which is the cumulative double bond stretching vibration region. The absorption peak of functional group at 3 370.20 cm^-1 between 3 650~3 200 cm^-1 is located in the multimolecular association region. It can be seen that when caffeic acid is used as acyl donor, the acylated modified black rice anthocyanins present a double acylated spatial structure due to the re-association of the molecules with the Introduction of new acyl groups in the structure. The organic acid was linked to the sugar chain in the structure of black rice anthocyanin, and it was placed on the surface of 2-phenyl benzo pyran skeleton. This stacking model can resist water nucleophilic attack and other degradation reactions, which can improve the stability of black rice anthocyanin structure.
		2018 Vol. 38 (08): 2386-2389 [Abstract] ( 159 ) RICH HTML PDF (1384 KB) ( 161 )

	2390	Identification of Gentiana Macrophylla by FTIR Technology and Sparse Linear Discriminant Analysis
		LI Si-hai¹, YU Xiao-hui², ZHAO Lei², JIN Ling^2*
		DOI: 10.3964/j.issn.1000-0593(2018)08-2390-05
		Fourier transform infrared(FTIR) spectrum usually includes a large number of wavelength variables and the qualitative analysis of FTIR spectrum needs to establish a stable and interpretable classification model. Sparse linear discriminant analysis (SLDA), a relatively new and effective machine learning algorithm, is commonly used for variable selection and discriminant analysis of high-dimensional settings, in which the number of wavelength variable is very large and the number of observations is limited. By introducing regularization items into linear discriminant analysis, the classifier training and variable selection are performed simultaneously in SLDA, and the sparsity of load coefficients in different discriminant directions increases the interpretability of the model. A total of 94 samples of Gentiana macrophylla, including 30 Gentiana straminea Maxims, 28 Gentiana officinalis and 36 Gentiana macropylla Pall, were collected. FTIR spectrum of all samples was obtained by Fourier transform infrared spectroscopy method. 70 of the samples were selected as the training set, the remaining as the test set. Based on the training set, the SLDA model was established through the grid optimization of the number of non-zero loading coefficients in the two discriminant directions, and the optimal parameter space was obtained. According to the model parameters, the prediction accuracy of the test set was 100%, and thus the rapid and accurate identification of the three kinds of Gentiana macrophylla was realized. The experimental results showed that the SLDA model was superior to PLS-DA method in terms of classification accuracy, sparseness and interpretability. SLDA will be a novel and effective method for spectroscopy qualitative analysis.
		2018 Vol. 38 (08): 2390-2394 [Abstract] ( 266 ) RICH HTML PDF (2448 KB) ( 82 )

	2395	*Discrimination of Oleoresins from Pinus msssoniana* and Pinus elliottii by Near Infrared Spectroscopy**
		YAN Jun¹, HUANG Xiao-ping¹, HUANG Yin-ning¹, WU Ye-yu¹, LIANG Zhong-yun², LEI Fu-hou^1*, TAN Xue-cai¹
		DOI: 10.3964/j.issn.1000-0593(2018)08-2395-05
		It is crucial to ensure the quality stability of rosin material since the different chemical constituents of various kinds of rosins will obviously influence the quality of down-stream product. Herein, a method based on near infrared spectroscopy and partial least squares discriminant analysis was proposed to discriminate oleoresins from Pinus msssoniana and Pinus elliottii, which could be helpful to identify the species of oleoresins during the purchasing process. Eighty-two oleoresin samples from six different producing areas of Guangxi, i. e. Wuming, Fangcheng, Fuchuan, Wuzhou, Baise and Leye, were collected to develop classification model. These collected samples were consisted of 51 Pinus msssoniana and 31 Pinus elliottii. Diffuse reflection modes were applied to obtain near infrared spectrum range from 900～1 700 nm. Then, several chemometrics techniques such as sub-window permutation analysis and repeated double cross validation were used to select optimal variables and the number of principal component. Finally, 300 variables were extracted from the original variable pool and the optimal number of principal component was set to 8. Results showed that the obtained model can accurately discriminate oleoresins from Pinus msssoniana and Pinus elliottii, and the classification accuracy of external test is 96.30%, which can meet the need of quality control. The proposed method is less time-consuming, easy to operate and low-cost, and it is suitable for the quality control of purchasing process.
		2018 Vol. 38 (08): 2395-2399 [Abstract] ( 225 ) RICH HTML PDF (2330 KB) ( 139 )

	2400	Analysis of Poplar-Eucalyptus Mixed Pulp Raw Materials Based on Near-Infrared Spectroscopy
		WU Ting¹, FANG Gui-gan^{1, 2*}, LIANG Long¹, DENG Yong-jun¹, XIONG Zhi-xin^{2, 3}
		DOI: 10.3964/j.issn.1000-0593(2018)08-2400-07
		In recent years, with the advance of forest and paper integration strategy, we often use mixed raw materials pulping. It is difficult to realize the rapid analysis of mixing degree and chemical composition content of raw materials, which has become the bottleneck constraints of pulping industry development. In order to solve this problem, the research chose the widely used poplar-eucalyptus wood mixed raw materials as study object, the near infrared spectrums of 131 poplar-eucalyptus wood samples which poplar content was artificially controlled and 30 single poplar and eucalyptus wood samples were collected with Fourier near infrared spectrometer, then the content of holocellulose, pentosan and Klason lignin was measured by chemical methods. The near-infrared spectra of these major chemical components are concentrated in the 7 600~4 000 cm^-1 interval. The model of poplar content and the model of pentosan content were established by LASSO(the least absolute shrinkage and selection operator) algorithm combined with spectral data of 7 600~4 000 cm^-1 which was pretreated by smoothing, standard normal variate and first derivative. The holocellulose content model was established with LASSO algorithm combined with same range of spectral data which was pretreated by smoothing, standard normal variate and second derivative. The Klason lignin content model was developed with the same algorithm , the same range of spectral data with the pretreatment of smoothing, multipicative scatter correction and second derivative. Poplar content, holocellulose, pentosan and Klason lignin models have root mean square error of prediction of 1.82%, 0.52%, 0.67% and 0.59% respectively. Absolute deviation (AD) range were -3.01%~2.94%, -0.91%~0.83%, -0.91%~1.07%, -0.79%~0.92%. The models have good performance better than the traditional partial least squares models that can be applied in actual industrial production.
		2018 Vol. 38 (08): 2400-2406 [Abstract] ( 171 ) RICH HTML PDF (2200 KB) ( 143 )

	2407	Analyzing the Similarity of Different Growing Areas in Red Sun-Cured Tobacco by Using Near Infrared Spectroscopy or Chemical Data
		MA Li¹, LI Xue-ying², DU Guo-rong¹, DING Rui³, WANG Yun-bai³, MA Yan-jun^1, LI Jun-hui^2
		DOI: 10.3964/j.issn.1000-0593(2018)08-2407-05
		Near infrared spectroscopy is a comprehensive information collection material, composite information of various substances, but the specific feature is not obvious; the chemical index can reflect the specific characteristics of the material, but the material information is not comprehensive enough. In this paper, total of 115 red sun-cured tobacco samples in 2012 and 2013 were tested, which were from Guizhou, Hunan, Jilin, Jiangxi, Shandong, Sichuan. After near infrared spectroscopy was processed by the first derivative and SG smooth and 26 items of chemical data and 26 items of calculated data (for example, ratio of sugar to nicotine, etc.) were normalized, the PPF (Projection of Basing on Principal Component and Fisher Criterion) projection method was used to analyze the similarity and substitution of growing areas in red sun-cured tobacco. Combined with the analysis of near infrared spectroscopy and chemical indicators, the results showed that the similarity analysis result by using near infrared spectroscopy is in basic agreement with the result by using chemical data, which means two methods can both analyze the similarity of growing areas. Nitrosamines would determine the growing areas as an important indicator by analyzing the variance contribution rate of 52 test data. The similarity of small areas was analyzed by used near infrared spectroscopy and the result was that the part of different small areas can be replaced. Application of near infrared spectroscopy technology can quickly and accurately analyze the similarity and substitution of different growing areas. Combining chemical data can be used to analyze its intrinsic characteristics, which can play an important role in the scientific exploitation of tobacco raw materials.
		2018 Vol. 38 (08): 2407-2411 [Abstract] ( 160 ) RICH HTML PDF (1365 KB) ( 155 )

	2412	The Identification Method of Blood by Applying Hilbert Transform to Extract Phase Information of Raman Spectra
		WANG Ning^{1, 2}, WANG Chi¹, BIAN Hai-yi², WANG Jun³, WANG Peng², BAI Peng-li³, YIN Huan-cai³, TIAN Yu-bing², GAO Jing^2*
		DOI: 10.3964/j.issn.1000-0593(2018)08-2412-07
		A novel method is reported to discriminate human and animal blood by using Raman chemometric analysis. The phase information of Raman spectra was extracted with Hilbert transform and then analyzed with PCA and PLS to improve the accuracy of identification of human and animal blood compared with original spectra. The cluster analysis was made according to the principal component scores scatter plots of blood spectra data or its corresponding phase information. And the appropriate threshold value was set in the PLS-DA model in order to discriminate human and animal blood. The results show that the PCA model of the phase information can identify animal blood and human blood obviously and it exhibits higher recognition rate compared with PCA of original Raman spectra. The PLS-DA indicates that the optimal number of principal components for the phase information is 3, RMSEP and R² are 0.044 3, 0.993 2, respectively. However, in the PLS model established with the original spectra, the optimal number of principal components is 6, RMSEP and R² are 0.053 7, 0.990 1, respectively. This indicates that the PLS-DA model of the phase information can make less error by using less principal components. The RMSEP of PLS-DA model built by the phase information of Raman spectra is lower than that of the blood Raman spectra when taking the same number of fitting principal components. In conclusion, the complexity of the PCA and PLS models can be reduced and the recognition accuracy can be improved by extracting the phase information of Raman spectroscopy.
		2018 Vol. 38 (08): 2412-2418 [Abstract] ( 301 ) RICH HTML PDF (4021 KB) ( 84 )

	2419	Study on the Determination of Basic Orange Ⅱ and Acid Orange Ⅱ in Food by TLC-SERS
		FU Yun-peng, QI Ying, HU Xiao-peng, TONG Rui, FANG Guo-zhen^*, WANG Shuo
		DOI: 10.3964/j.issn.1000-0593(2018)08-2419-06
		A method for the rapid detection of illegally added basic orange Ⅱ and acid orange Ⅱ in food was established by the combination of thin layer chromatography (TLC) and surface enhanced Raman spectroscopy (SERS). TLC was used for the separation of sample extracts tentatively and the conditions were optimized. Two kinds of silver sols, aqueous phase and organic phase, were synthesized and used as the substrate to enhance Raman signal for basic orange Ⅱ and acid orange Ⅱ. SERS was used to detect isolated micro-substances and the time was investigated. The detection limits of basic orange Ⅱ and acid orange Ⅱ were 1 and 2.5 mg·L^-1. Then, the method has been successfully used for rapid detection of basic orange and orange Ⅱ in the complex food matrix. The method has the advantages of simplicity, rapidity, economic and specificity, and will provide a new scheme for the simultaneous detection of basic orange Ⅱ and acid orange Ⅱ in food.
		2018 Vol. 38 (08): 2419-2424 [Abstract] ( 193 ) RICH HTML PDF (3175 KB) ( 59 )

	2425	Articular Cartilage Optical Clearing Research by Raman Spectroscopy
		GAO Hao, ZHAI Ming-yang, SHANG Lin-wei, ZHAO Yuan, XU Hao, WANG Xiao, YIN Jian-hua^*
		DOI: 10.3964/j.issn.1000-0593(2018)08-2425-05
		To investigate deeper microscopic information of articular cartilage and subchondral bone components in situ, Raman spectroscopy combined with tissue optical clearing technique was used to study the clearing effect of articular cartilage. Raman spectra of the cartilage adhered on femur ends in canine knees were collected after they were impregnated at different time and different concentrations of clearing agents, glycerol and iohexol. The integrated Raman intensity ratio of phosphate group (920~960 cm^-1) to the amide Ⅰ band (1 595~1 700 cm^-1) was obtained to seek the rule of tissue optical clearing at different impregnating time (10～60 min) and different concentrations of clearing agents (40%, 60%, 80% and 100% for glycerol, 50, 150, 250, 350 mg·mL^-1 for iohexol), which is to get the optimum concentration and time. It was found that the both agents could enhance the Raman signal compared to the case of no clearing agent. With equal time for impregnating, glycerol and iohexol were able to obtain good results at 60% and 150 mg·mL^-1, respectively. Under different concentrations, the clearing effect of glycerol was the strongest in 20 min, while that of iohexol was enhanced after 50-min impregnation in general. In conclusion, the Raman scattering information of subchondral bone can be directly detected when the clearing agents penetrating through cartilage, which will provide a novel way and a potential solution into study on osteoarthritis etiology in depth.
		2018 Vol. 38 (08): 2425-2429 [Abstract] ( 195 ) RICH HTML PDF (1586 KB) ( 99 )

	2430	Detection of Nasopharyngeal Carcinoma Based on Human Saliva Surface-Enhanced Raman Spectroscopy
		LIN Xue-liang¹, LIN Duo^{1, 2}, QIU Su-fang³, GE Xiao-song¹, PAN Jian-ji³, WU Qiong¹, LIN Hui-jing¹, HUANG Hao^2*
		DOI: 10.3964/j.issn.1000-0593(2018)08-2430-05
		Surface Enhanced Raman Spectroscopy (SERS) technique is a fast, convenient and nondestructive optical diagnose method that can provide specific fingerprints of biomolecular compositions and structures. Human saliva contains many biomarkers that can reflect health condition. In this paper, we employed SERS methods based on nanometer silver colloid to obtain high quality SERS of 208 saliva samples from 46 patients with nasopharyngeal carcinoma (NPC), 30 patients with rhinitis and 48 healthy volunteers. The results showed there were great differences in SERS pattern among these three subjects. Principal component analysis-linear discriminant analysis (PCA-LDA) was utilized to analyze and classify the saliva spectra from NPC, rhinitis and healthy subjects. The diagnostic sensitivity was 89.5%, 93.0% and 100% respectively, and meanwhile the specificity was 94.6%, 96.7% and 97.7% respectively. The research showed that saliva SERS combined with PCA-LDA can rapidly and effectively distinguish three saliva groups, and this technique has great potential to be a non-destructive and clinical screening method for nasopharyngeal carcinoma detection.
		2018 Vol. 38 (08): 2430-2434 [Abstract] ( 227 ) RICH HTML PDF (2545 KB) ( 76 )

	2435	Corrosion Resistance of Gold Surface Investigated by Surface Enhanced Raman Spectroscopy
		ZHONG Hang, XU Jin-song, TAO Ran, DU Xiao-qing, CHEN Jun^, LIAO Jun-sheng^
		DOI: 10.3964/j.issn.1000-0593(2018)08-2435-06
		The corrosion resistance of metals is closely related to their surface microstructure. This work focuses on the surfaces of gold plates which were prepared through a polishing process with different sizes of α-Al₂O₃. With SEM and AFM characterizations, the surface microstructures of the gold plates are distinct, indicating that the polished gold plates have surface microstructures similar to those of real work-pieces. The effects of the gold surface scratches on surface enhanced Raman scattering (SERS) and corrosion resistance were investigated. SERS on the gold surface scratches with different average feature sizes were tested using Rhodamine B (RhB) as a probe molecule. A relationship between the SERS intensity of the adsorbed Rhodamine B and the average feature size of surface scratch was obtained. By changing the angle between the polarization direction of Raman laser and the direction of scratches, it is found that the SERS signals are mainly ascribed to the transverse plasmon generated from interaction between incident light and scratches. The transverse plasmon intensity reached the maximum when the average feature size of the surface scratches is close to 50 nm. With the increase of the average feature sizes, the transverse plasmon intensity shows a gradual decrease. On the other hand, electrochemical polarization tests of the gold plates with different sizes scratches were measured. The free corrosion potential of samples is obtained. The free corrosion potential of gold plates decrease with increasing the average feature sizes. It is found that, when the average feature size of the surface scratch is more than 50 nm, a ideal coherence exists between the SERS intensity and the free corrosion potential for the gold plates. These results suggest that SERS technique could be applied for the corrosion resistance analysis of the work-pieces. By the means of smearing probe molecules and using a handheld Raman spectrometer, quick analysis of the work-pieces corrosion resistance is proven to be promising.
		2018 Vol. 38 (08): 2435-2440 [Abstract] ( 283 ) RICH HTML PDF (2928 KB) ( 81 )

	2441	Three-Dimensional Fluorescence Spectroscopy Combined with Wavelet Compression and Alternate Penalty Quad Linear Decomposition for Environmental Analysis: Determination of Polycyclic Aromatic Hydrocarbons
		WANG Shu-tao, LIU Ting-ting^*, SHANG Feng-kai, CUI Yao-yao, YANG Zhe, WANG Yu-tian
		DOI: 10.3964/j.issn.1000-0593(2018)08-2441-10
		The quantitative and quantitative analysis of trace polycyclic aromatic hydrocarbons (PAHs) was carried out based on three-dimensional fluorescence spectroscopy combined with alternating penalty four linear decomposition (APQLD). The experiment was carried out with acenaphthene (ANP) and naphthalene (ANA). First, in order to solve the redundant information of the three-dimensional fluorescence spectral data, the experimental spectral data was compressed by wavelet transform. The four-dimensional data were constructed by using the combination of excitation and emission spectra of PAHs in ethanol solvent and methanol solvent and ultrapure water respectively. The four-dimensional spectral data were analyzed by APQLD and compared with PAHs under three solvent conditions The respective recovery rate. The experimental results showed that the higher order data can be used to determine the concentration of PAHs more accurately under the three solvent conditions, and the recovery rate was higher. Compared with the second-order correction and other four-dimensional correction algorithms, APQLD can better reflect the superiority of the four-dimensional algorithm The recovery rate of ANA was 96.5%~103.3% and the predicted root mean square error was 0.04 μg·L^-1. The recovery rate of NAP was 93.3%~110.0%, and the predicted root mean square error was 0.08 μg·L^-1.
		2018 Vol. 38 (08): 2441-2450 [Abstract] ( 207 ) RICH HTML PDF (8817 KB) ( 67 )

	2451	Detection the Concentration of L-Tryptophan by Fluorescence Correlation Spectroscopy
		GU Song^{1, 2}, ZHU Zhuo-wei^{1, 2}, MA Chao-qun^{1, 2}, CHEN Guo-qing^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2018)08-2451-05
		The three-dimensional fluorescence spectrum of the L-tryptophan solution was measured in a fluorescence spectrometer. The result showed that the fluorescence peak of L-tryptophan located at 270 nm/350 nm (excitation wavelength/emission wavelength). As the emission wavelength was fixed at 350 nm, an excitation spectrum can be measured. It can be found from the excitation spectrum that the curve has a high slope and good linearity in the range of 250~260 nm. Thus, the excitation wavelengths of 250, 255 and 260 nm were chosen to excite the sample, and three fluorescence emission spectra were measured. Based on the three spectra, the auto correlation spectra with disturbance variable of wavelength were constructed. In addition, the emission spectra of the ultrapure water under different excitation wavelength were measured and averaged to be reference spectrum. The auto-correlation spectra with disturbance variable of concentration were constructed by correlation calculation between the reference spectrum and the averaged spectrum of the samples. Combined the correlation spectral data with partial least squares regression (PLSR) and radial basis function neural network (RBFNN), the prediction models of the concentration of L-tryptophan were measured, respectively. The prediction results showed that the correlation spectrum constructed with disturbance variable of concentration had a better signal-to-noise ratio and better prediction performance. Furthermore, with the same disturbance variable, the model based on RBFNN was more precise than that based on PLSR. Among all the models, the model based on RBFNN with disturbance variable of concentration had the best prediction performance with correlation coefficient of 99.91% and root-mean-square error of 0.033 μg·mL^-1. This method can provide helps in the food safety supervision for the accurate determination of substances.
		2018 Vol. 38 (08): 2451-2455 [Abstract] ( 163 ) RICH HTML PDF (1513 KB) ( 76 )

	2456	3D Fluorescence Spectra Combined with Zernike Image Moments for Rapid Identification of Doping Sesame Oil
		WU Xi-jun, CUI Yao-yao, PAN Zhao^*, LIU Ting-ting, YUAN Yuan-yuan
		DOI: 10.3964/j.issn.1000-0593(2018)08-2456-06
		In order to realize the rapid identification of dopingsesame oil, the three-dimensional fluorescence spectra of the samples were measured by FS920 fluorescence spectrometer.The three-dimensional fluorescence spectrum was regarded as the gray scale graph,and the characteristic information of three-dimensional spectral grayscale was extracted directly by Zernike image moment without any pretreatment.Then, the characteristic information was clustered and analyzed by using the class mean method to identify the doping sesame oil and its constituent components. Finally, the generalized regression neural network (GRNN) was used to quantitatively analyze the components of the dopingsesame oil. Clustering analysis can identify adulterated sesame oil and its composition. The average relative error of the two groups was 2.23%, 8.00%, 9.70% and 9.70%, respectively. The results showed that the Zernike moments can effectively extract the characteristic information of the spectra. The proposed method of Zernike moments combined with clustering analysis and GRNN model can obtain satisfactory qualitative and quantitative analysis results, which will provide a new method for the identification of doping sesame oil.
		2018 Vol. 38 (08): 2456-2461 [Abstract] ( 178 ) RICH HTML PDF (4488 KB) ( 127 )

	2462	Effects of External Fields on CC Atomic Vibrations Modulated by Electron Band Gap
		GONG Nan¹, CAO Xian-wen¹, SUN Cheng-lin¹, FANG Wen-hui³, YUAN Ju-hui², GAO Shu-qin¹, LI Zuo-wei¹, CHEN Wei^2, FU Hao-yang^1
		DOI: 10.3964/j.issn.1000-0593(2018)08-2462-06
		As an important technique to study the linear polyene molecules, Resonance Raman spectroscopy perfectly characterizes the CC vibrations modulated by the π-electron band gap. This modulation generated by electron-phonon coupling is significantly influenced by external fields. In this paper, we illustrate the dependence of CC vibration modulated by π-electron in different environments such as temperature, pressure, phase and solvent. The results show that the decrease of system energy and the narrowing of π-electron band gap lead to enhancements of the vibrational modulation. Thus, there are enhances of electron-phonon coupling as well as Raman intensity, result of which the spectra red shift. This research is of great significance for a better interpretation on the structural dependence of linear polyene's spectral properties and physical process of its resonance Raman scattering. The results also serve as an important reference for developing high quality photoelectric devices.
		2018 Vol. 38 (08): 2462-2467 [Abstract] ( 250 ) RICH HTML PDF (4261 KB) ( 75 )

	2468	Study on the Interaction between Tetracycline Hydrochloride and Bovine Serum Albumin by Multispectral and Molecular Docking
		WANG Xiao-xia¹, NIE Zhi-hua², LI Song-bo¹, MA Li-tong¹, LIU Jin-yan¹, WANG Zheng-de¹, YAN Hui¹
		DOI: 10.3964/j.issn.1000-0593(2018)08-2468-09
		Tetracycline HCl is a new member of the class of antibiotics. Therefore, its effects on the secondary structural of Bovine Serum Albumin, and the mechanism of action are poorly understood. The interaction between Tetracycline HCL and BSA were investigated with fluorescence spectroscopy, three-dimensional fluorescence spectroscopy, ultraviolet spectroscopy, circular dichroism (CD), infrared spectroscopy and molecular docking under imitated physiological conditions. The analysis of fluorescence spectra showed that Tetracycline HCl could strongly quenching the fluorescence of BSA and the quenching process is a static process. The effective binding constants (Ka) were calculated to be 2.813×10⁵ L·mol^-1(298 K) by stern-volmer equation. According to the Vant’s Hoff equation, the thermodynamic parameters were calculated to be ΔS=-151.1 J·mol^-1·K^-1 ，ΔH=-76.09 kJ·mol^-1，indicating that the predominant forces in the complex were hydrogen bonding and Van der Waals forces. The results of synchronous fluorescence, UV spectrum , FT-IR , CD spectrum and three dimensional fluorescence spectrum, futher demonstrated that the secondary conformation and micro-environment of BSA has been changed after interaction with Tetracycline HCL. Based on the Föster’s theory of non-radiation energy transfer, and the specific binding distance between Tetracycline HCL-BSA system was 0.49 nm. Hill’s coefficients (n_H<1) proved that a negative cooperativity was found when Tetracycline HCLbound to BSA. The alteration of the protein secondary structure were quantitatively calculated from circular dichrosim (CD) spectroscopy with increase of α-helix content about 9.16%(1:1). The result of molecular docking simulation revealed that Tetracycline HCL was located in sudlow’s site I corresponding to subdomain IIA through multiple interactions-hydrogen bond, hydrophobic and vander waals, etc. This research will provide valuable information for understanding the action mechanism of Tetracycline HCl with BSA, and is helpful for understanding its effect on protein function during the storage and transport process.
		2018 Vol. 38 (08): 2468-2476 [Abstract] ( 237 ) RICH HTML PDF (6440 KB) ( 103 )

	2477	Existence of Pressure-Insensitive Radial Position in Diffuse Reflection Contact Measurement
		WANG Zhi-mao, LIU Rong^*, XU Ke-xin
		DOI: 10.3964/j.issn.1000-0593(2018)08-2477-06
		The variation of probe-tissue contact pressure will lead to poor measurement accuracy and stability in the near-infrared noninvasive diffuse reflection measurement. In this paper, the pressure-insensitive radial position was proposed to collect the diffuse reflection signal to minimize the measurement error caused by contact pressure, and the existence of pressure-insensitive radial position was verified by Monte Carlo simulation and in vivo experiment. First, Combined with human skin structure model and mechanical properties, the quantitative relationship between contact pressure and skin tissue parameters were established, and the distribution change of diffuse light intensity along radial distance within the wavelength of 1 000～1 320 nm under different contact pressure was simulated by the Monte Carlo program. Then the diffuse reflection detection system configured with the super-luminescence diodes and customized optical fibers were built, where multiple detector fibers surrounded the source fiber. And in vivo experiments were performed where the diffuse reflection signals in the wavelength of 1 050, 1 219 and 1 314 nm of three volunteers were collected under different pressure. Last, the stability of signal received from pressure-insensitive radial position and other radial position was evaluated. Simulation results showed that, the diffuse reflection signals received within the radial distance from 1.3 to 1.5 mm were not changed with the contact pressure, which means there were the pressure-insensitive radial positions. The experiment results of in vivo showed that, the pressure-insensitive radial positions could be found in all the volunteers, and they were located within the radial distance of 0.78～1.0 mm for the all wavelengths investigated. Compared with other radial positions, the signal-to-noise ratio of the signal collected under the pressure-insensitive radial position was higher. Therefore, the measurement method based on the pressure-insensitive radial position can effectively reduce the influence of the contact-pressure variation on the spectral information, and it is expected to improve the accuracy of the near-infrared noninvasive diffuse reflection measurement.
		2018 Vol. 38 (08): 2477-2482 [Abstract] ( 230 ) RICH HTML PDF (2160 KB) ( 80 )

	2483	Spectral Detection Technique of Blood Species Based on Data Driven Model
		LI Hong-xiao¹, SUN Mei-xiu¹, XIANG Zhi-guang², WANG Yi³, LIN Ling³, QIN Chuan², LI Ying-xin^1*
		DOI: 10.3964/j.issn.1000-0593(2018)08-2483-05
		This paper proposed a non-contact blood species recognition technique based on spectral detection and data driven model. A total of 649 blood samples were selected from 4 species (monkey 144, rat 203, dog 133, and human 169) as the original samples. The wavelength range of the super continuum laser source was 450～2 400 nm. The backward scattered visible spectrum (294～1 160 nm) and the forward scattered near-infrared spectra of ten different spatial sites were collected from each blood sample contained in anticoagulant tubes. Then the eleven spectra were sequentially connected into one-dimensional data as the original data of each sample. The principal component analysis was used to extract the feature information of the dataset, which retained 99.99% of the original variance information, while compressing the data amount to 1.5% of the original data volume, such to improve the computational efficiency of classification and recognition. Experiments on different numbers of training sets and verification sets showed that the recognition error rate of ten-fold cross-validation decreases with the increase of the number of samples, and the increase of sample bank size can improve the recognition accuracy. Because the data driven model is a data stream processing model based on machine learning algorithms, in which a variety of different classification algorithms can be used to realize this model. By comparing the recognition effects of six algorithms (artificial neural network, support vector machine, partial least-squares regression, multiple linear regression, random forest and Naïve Bayes), it was found that the recognition effects of different algorithms have the category differences, that is, the sort of these algorithms in terms of their correct recognition rate are different for different species. Therefore, when choosing the data driven model as a solution, in addition to considering the overall recognition rate of the algorithm, the scheme should also consider the category differences of the algorithm if there are additional requirements on the recognition effect of some certain categories.
		2018 Vol. 38 (08): 2483-2487 [Abstract] ( 205 ) RICH HTML PDF (2283 KB) ( 111 )

	2488	All Spectral Yarn Color Matching Algorithm Based on Stearns-Noechel Model
		MA Chong-qi^{1, 2}, CHENG Lu¹, JIN Xiao³, MAI Wei^{1, 2*}, LIU Jian-yong^{1, 2}, ZHU Bao-ji¹
		DOI: 10.3964/j.issn.1000-0593(2018)08-2488-05
		At present, computer color matching is difficult to predict the exact formulation of the problem when color difference formula hours large deviations, so the algorithm is optimized based on the Stearns-Noechel model of the optical model. Using the spectral reflectance data of the two samples were equal and the two samples necessarily colored，and then the discriminant conditions in the computer color matching algorithm program were improved. We Calculated by MATLB, in the interval [0 1], every interval of 0.001, the cycle of unknown parameters M value, and selected the full spectrum of the reflectance data when the minimum deviation of the parameter M value to calculate the fit ratio, instead of the minimum color parameters M. The fitting ratio wascalculated and the relative formula deviation of the fitting sample was calculated. The results showed that the average deviation of the average color of the primary color was 0.560 and the secondary color was 0.346 when the deviation of the parameter M was the minimum of the total spectral reflectance data. The minimum deviation of the parameter M was the corresponding formula, the relative deviation of the primary color was 0.723, and the secondary color was 0.383. Compared with the two methods, it can be seen that the relative deviation of the formula after fitting the sample and the standard sample was smaller than the relative formula deviation when the chromatic aberration was minimum. That is, after the optimization of the formula was more close to the real formula, and color accuracy has been significantly improved, helping to reduce the number of late proofing as well as improving color efficiency.
		2018 Vol. 38 (08): 2488-2492 [Abstract] ( 199 ) RICH HTML PDF (1223 KB) ( 58 )

	2493	*Non-Destructive Determination of Growth Quality Indicators of Spirulina sp.* Using Vis/NIR Spectroscopy**
		JIANG Lu-lu¹, WEI Xuan², XIE Chuan-qi^3, HE Yong^4
		DOI: 10.3964/j.issn.1000-0593(2018)08-2493-05
		In order to detect the growth quality indicators of Spirulina sp. using a fast and on-destructive method, this study was carried out to predict chlorophyll a and protein content under different red and bule light combinations (100% red light, 90% red light+10% blue light, 70% red light+30% blue light and 50% red light+50% blue light) using Vis/NIR spectroscopy (325～1 075 nm). The chlorophyll a and protein content were predicted using partial least squares (PLS) models. Then successive projections algorithm (SPA) was used to identify effective wavelengths for chlorophyll a and protein, resulting in five (404, 440, 518, 662 and 875 nm) and four (411, 531, 602 and 1 047 nm) wavelengths, respectively. Based on the selected wavelengths, multiple linear regression (MLR) models were established, which obtained the r_p of 0.949 and 0.974, RMSEP of 0.018 8 and 0.006 74, respectively. The results demonstrated that Vis/NIR spectroscopy has the potential to be used for determination of chlorophyll a and protein content in Spirulina sp., and the growth condition can be monitored by the MLR equation and the corresponding spectral reflectance information.
		2018 Vol. 38 (08): 2493-2497 [Abstract] ( 225 ) RICH HTML PDF (1517 KB) ( 180 )

	2498	Study on Detection of Chilled Mutton Freshness Based on Hyperspectral Imaging Technique and Sparse Kernel Canonical Correlation Analysis
		JIANG Xin-hua¹, XUE He-ru^1*, GAO Xiao-jing¹, ZHANG Li-na², ZHOU Yan-qing¹, DU Ya-juan^{1, 3}
		DOI: 10.3964/j.issn.1000-0593(2018)08-2498-07
		The mutton freshness is affected by many factors, which is usually evaluated by a number of indicators, and its routine detection is complicated and not suitable for online detection. Hyperspectral imaging data can reflect the changes of components in the process of mutton freshness changing, but the establishment of spectral feature extraction and evaluation model has a great influence on the final result. In order to study the feasibility of rapid detection of mutton freshness with hyperspectral imaging technique and multi-parameter indicators, this paper proposed a sparse kernel canonical correlation analysis method, and researches comprehensive evaluation of mutton freshness on multi-parameter using laboratory standard values. In this study, 400~1 000 nm hyperspectral images were collected from 70 mutton samples, and the standard values of total volatile basic nitrogen (TVB-N) and total aerobic plate count (TAC) were determined with laboratory methods. The representative spectra of mutton samples were extracted and obtained after selection of the region of interests (ROIs). The spectral feature information is extracted by using the feature extraction method proposed in this paper. The samples of calibration set and the prediction set are divided at the ratio of 3:1. The experiment of classification and recognition using three layer neural network shows that the overall accuracy (OA) is 0.939 3, the Kappa coefficient is 0.906 0, and the root mean square error (RMSEC) is 0.297. The research shows that the multi-parameter spectral feature extraction method proposed in this paper can be used to detect the freshness of mutton quickly and nondestructively. This paper provides a basis for improving the applicability and robustness of the evaluation model due to the single detection indicator by using the hyperspectral imaging technique to synthesize the spectral information of several freshness indexes.
		2018 Vol. 38 (08): 2498-2504 [Abstract] ( 211 ) RICH HTML PDF (2065 KB) ( 77 )

	2505	Spectroscopic Analysis of Effect of Sodium Citrate on the Properties of Transglutaminase Goat’s Milk Gels
		FENG Cai-ping¹, SUI Xiao-feng¹, CHEN Chong², GUO Hui-yuan², WANG Peng-jie^2*
		DOI: 10.3964/j.issn.1000-0593(2018)08-2505-06
		In this study, the effect of sodium citrate (TSC) on the characteristics of transglutaminase (TGase) goat milk gels was analyzed using multiple light scattering, multiple speckle diffusion wave spectroscopy, and dynamic light scattering spectroscopy. TSC was added to skimmed goat milk to concentrations of 0, 20, 40, 60, and 80 mmol·L^-1, and the milk was acidified by gluconolactone (GDL) after TG enzyme treatment. Dynamic light scattering spectra indicated that on increasing the TSC concentrations in the range of 0 to 80 mmol·L^-1, the diameter of casein micelles decreased from (142.0±11.2) to (24.4±2.1) nm; The intensity of the backscattered light was increased from 41.9%±0.3%, 35.8%±0.4%, 25.3%±0.5%, 10.6%±0.3%, and 5.3%±0.4% to 55.8%±0.6%, 49.5%±0.5%, 41.9%±0.4%, 37.8%±0.4% and 30.8%±0.3%, respectively, indicating that the higher the concentration of TSC, the smaller the size of the particles in the gel system, and the smaller the gel building units formed; At the same time, the mean square displacement curves of the multi-speckle diffuse wave spectrum showed that the gel mutation time was 31, 74, 98, 151 and 226 min, respectively, indicating that the higher the concentration of TSC, the longer gelation time. The water holding capacity and hardness values of the resulted gels was negatively related to the TSC concentrations.
		2018 Vol. 38 (08): 2505-2510 [Abstract] ( 154 ) RICH HTML PDF (6036 KB) ( 51 )

	2511	Classification and Year Prediction of Chinese Liquors Based on Wavelet Decomposition and Factor Analysis
		GU Jiao^{1, 2}, CHEN Guo-qing^{1, 2*}, ZHANG Xiao-he^{1, 2}, LIU Huai-bo^{1, 2}, MA Chao-qun^{1, 2}, ZHU Chun^{1, 2}, LIAO Cui-cui^{1, 2}
		DOI: 10.3964/j.issn.1000-0593(2018)08-2511-05
		In this paper, a method to identify the flavor and year of Chinese liquors was proposed based on continuous wavelet decomposition and factor model on analyzing the fluorescence spectra of liquor. The three-dimensional fluorescence spectrum of liquor contained the information of the fluorescent substance, and its decomposition factor was related to the intensity of the characteristic peak. The decomposition of the three-dimensional fluorescence spectrum by Gaussian wavelet can avoid the problem of selecting the specific excitation wavelength when decomposing the two-dimensional fluorescence spectrum. After the wavelet decomposition of the three-dimensional fluorescence spectrum of the sample, the orthogonal factor model was constructed by the fourth layer approximation coefficient, and the liquor was discriminated by the factor loading. The results showed that the factors with small contribution contain unique information of the sample, which can not be neglected in the comparison of similar samples. In the classification of liquor flavor, the three-dimensional fluorescence spectra of the samples were decomposed by Gaussian wavelet, and the fourth-layer approximation coefficients were used for factor analysis to obtain multiple factors with large and small contribution rates. According to the factor of the factor loading, the cluster analysis was carried out. The results showed that the factor with a small contribution rate can increase the correct rate to 90%. By analyzing the correlation between the factor loading and the year of liquors, the contribution rate of the first six factors was larger than that of the liquor, and the correlation between the factors and the year of liquor was small, so the first six factor can be used to predict the year of Chinese liquors. By selecting the factors with different contribution rates to predict the year of liquor, the average error can be reduced to 0.9 years.
		2018 Vol. 38 (08): 2511-2515 [Abstract] ( 204 ) RICH HTML PDF (1589 KB) ( 127 )

	2516	Hybrid Seed Recognition of Maize Based on Probability Clustering Model Using Visible Light Color Features
		LIU Shuang-xi¹, ZHANG Hong-jian¹, WANG Jin-xing^2*, WANG Zhen¹, ZHANG Chun-qing³, LI Yan³
		DOI: 10.3964/j.issn.1000-0593(2018)08-2516-08
		Because the grain size of the same kind of hybrid maize seed is different and the maize color changes as the storage time varies, it is difficult to identify the species only by the machine vision method with its shape and color in a single region. Besides, the existing recognition algorithm mostly uses the hyper-spectral feature as the basis for classification, so for different periods, different types of hybrid maize seeds need to be trained by the classification equipment, and a lot of training is required before the identification. In order to improve the applicability of identification method for maize seed variety, a multi-model probabilistic clustering method was established based on the multi-regional wavelet color characteristics of maize seed in the visible light band as the recognition parameter. This method used a special equipment to extract the non-germinal and the topside color information of the single-grain maize seed, including the color information of RGB, HIS and Lab. Then the color information was enhanced, the feature selection was optimized and the 21-dimensional detail recognition vector was perfected by wavelet packet decomposition. Secondly, the clustering recognition of the optimized color feature was carried out by different clustering models. Three clustering models based on SOM, K-means and two-step method were thus established. Finally, based on the results of multiple clustering models, the maize seed variety identification via probability model was set up. Through the experiments on Zheng Dan 958, Xian Yu 335, Zheng 58 (Zheng Dan 958 female), Chang 7-2 (Zheng Dan 958 male), PH6WC (Xian Yu 335 female), PH4CV (Xian Yu 335 male), it was shown that the method was able to effectively identify maize seeds with non-genetic relationship and parental relationship, with the recognition rate reaching over 98%; While the recognition rate of female parent was 75%. This can provide scientific basis for on-line identification of hybrid seed purity. The method of probability clustering model can provide scientific basis for the identification of maize hybrid seed purity by using visible light multi-regional color characteristics.
		2018 Vol. 38 (08): 2516-2523 [Abstract] ( 169 ) RICH HTML PDF (3595 KB) ( 64 )

	2524	Estimation of Chlorophyll Content by Reflectance Spectra of the Positive and Negative Blades
		WANG Xin, WANG Zi-tong, YOU Wen-qiang, LU Fan, ZHAO Yun-sheng, LU Shan^*
		DOI: 10.3964/j.issn.1000-0593(2018)08-2524-05
		The rapid and nondestructive estimation of leaf chlorophyll content is significance of the monitoring of vegetation growth and environmental stress. The traditional method of chlorophyll estimation is mostly based on the spectral information of upper leaf side. However, in the actual remote sensing observation, the sensor not only receives the adaxial spectral information of leaves, but also receives the spectral information from the abaxial surface of leaf. The main purpose of this study is to find an accurate method to estimate the chlorophyll content of leaves when considering both the adaxial and abaxial spectral information of the blade. This paper compared the simple difference vegetation index (SD), simple ratio vegetation index (SR), normalized difference vegetation index (ND) and partial least squares (PLS) regression modeling method. It was found that PLS regression modeling method had the highest precision in all of the methods to estimate leaf chlorophyll content of two species with two surfaces reflectance. The R² was 0.91 and the RMSE was 5.21 g·cm^-2 Therefore, it can be concluded that the PLS method is more accurate in estimating leaf chlorophyll content when considering both adaxial and abaxial leaf spectral information.
		2018 Vol. 38 (08): 2524-2528 [Abstract] ( 168 ) RICH HTML PDF (2445 KB) ( 126 )

	2529	*Study on the Geographical Traceability of Boletus Tomentipes* Using Multi-Spectra Data Fusion**
		ZHANG Yu^{1, 2}, LI Jie-qing¹, LI Tao³, LIU Hong-gao^1, WANG Yuan-zhong^2
		DOI: 10.3964/j.issn.1000-0593(2018)08-2529-07
		Currently, since the domestic and international food marketing on the safety supervision and traceability system is defective, as well as false labels used by agency，situation on the food safety is becoming more and more serious. In order to enhance food safety, it’s essential to establish a fast and efficient geographical traceability method to protect the agricultural brand of Yunnan plateau. A total of 77 fruit bodies of Boletus tomentipes were collected from 8 geographical origins. Raw of ultraviolet-visible (UV-Vis) and Fourier transform infrared (FTIR) spectra were preprocessed by multiplicative scatter correction (MSC), standard normal variate (SNV), second derivative (2D), Savitzky-Golay (SG) smoothing. Based on pretreatment of UV and FTIR spectra, low-level and mid-level data fusion strategy combined with partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM) were used to identify Boletus in different regions. The results indicated that: (1) that the best pretreatment, was SNV+2D with highest R²Y (61.58%) and Q² (95.09%) for UV-Vis spectra, and MSC+2D with highest R²Y (50.85%) and Q² (82.16%) for FTIR spectra; (2) For UV-Vis, FTIR spectra, low-level and mid-level data fusion, the number of error samples in the classification of PLS-DA and SVM analysis were 24, 6, 2, 2, and 6, 1, 1, 0, respectively; (3) In the mid-level data fusion, the best classification of SVM with none error sample was better than that of the PLS-DA with 2 error samples; (4) The classification of HCA analysis in the mid-level data fusion with 4 error samples had the better performance than that in the low-level data fusion with 1 error sample. In addition, HCA analysis of mid-level data fusion showed that the distance of samples collected from same area were longer than that collected from different sites. It indicated that the differences of samples collected from different sites in the same area were less than that collected from different regions. Those results indicated that mid-level data fusion combined with SVM model using UV-Vis and FTIR spectroscopy can accurately identify Boletus collected from different geographical origins. It will provide a new strategy on the research of geographical traceability of wild edible fungus.
		2018 Vol. 38 (08): 2529-2535 [Abstract] ( 194 ) RICH HTML PDF (4072 KB) ( 67 )

	2536	Piecewise Linear Retrieval Suspended Particulate Matter for the Yellow River Estuary Based on Landsat8 OLI
		LIU Zhen-yu^{1, 3}, CUI Ting-wei², ZHANG Sheng-hua¹, ZHAO Wen-jing⁴
		DOI: 10.3964/j.issn.1000-0593(2018)08-2536-06
		Much sediment is transported into Bohai by Yellow River every year. Therefore the study on suspended matter concentration(SPM) in Yellow River estuary is significant to the environmental monitoring and sediment transport of surrounding ocean. The piecewise linear retrieval model was proposed based on the remote sensing reflectance and suspended matter concentration synchronous sampled in summer and winter in 2011. The results showed: the sensitive bands combination for suspended matter concentration inversion was different under different concentration ranges, (600~700 nm) /(400~600 nm) and (750~900 nm)/(420~720 nm) respectively to the concentration range below and above 50 mg·L^-1, and the corresponding bands for Landsat 8 OLI were B4/B2 and B5/B3 respectively. The R², RMSE and APD of the Piecewise model were 0.873 5，4.08 mg·L^-1 and 22.81%(SPM≤50 mg·L^-1)，0.969 3, 102.96 mg·L^-1, and 17.51%(SPM＞50 mg·L^-1) respectively, and 0.975 3，67.03 mg·L^-1and 20.45% for the overall concentration, which were better than parameters of common single model under entire concentration range. In summary, the piecewise linear retrieval model is more suitable for suspended matter concentration inversion of the Yellow River estuary with large variation of concentration.
		2018 Vol. 38 (08): 2536-2541 [Abstract] ( 206 ) RICH HTML PDF (4999 KB) ( 70 )

	2542	The Spectral Prediction Method of Primary Ink for Prints Manuscript Based on Non-Negative Matrix Factorization
		LI Yu-mei^1,2, HE Song-hua^1*, CHEN Hao-jie², CHEN Qiao¹
		DOI: 10.3964/j.issn.1000-0593(2018)08-2542-07
		In the spectral prediction technology of the primary ink of halftone prints manuscript, the representative vector number obtained by principal component analysis will be greater than the actual number of primary inks used in the reflectance space. The space is not suitable for spectral prediction, and the based vectors obtained by PCA will appear negative. There is no physical meaning. Aiming at the above problems, a subtractive linear experimental space model and space conversion model were created. And the factors influencing the linearity degree of the space n value were explored. Through experiments and optimization algorithms, the methods for determining the best n value were found innovatively. Then the prediction experiments of the primary ink of halftone prints manuscript were carried out in the space. The experimental results showed that, under different n values, the n value corresponding to the minimum square value of the f norm was effective for determining the best n value to establishing the linear empirical space. Finally, the n value was determined to be 3.5. In the space, the number of representative base vectors obtained by the method of number prediction was exactly equal to 4, which was the actual primary ink number. In spectral prediction, in addition to K color, other CMY color compared to the actual primary ink spectrum, the fitting degree of GFC was greater than 99.9%. That was to establish a new method for the optimization of n proposed in this paper. The value of color space was an effective linear empirical linear space which can be used as a halftone color ink number prediction and spectral prediction. That is to say, the space created by the new method is an effective linear space that can be used to predict the number of primary ink and the spectrum of halftone prints manuscript.
		2018 Vol. 38 (08): 2542-2548 [Abstract] ( 143 ) RICH HTML PDF (2453 KB) ( 67 )

	2549	Vertical Distribution Characteristics of DOM in Soil Infiltration System Based on 3D-EEMs and PARAFAC
		LÜ Jing-jing^{1, 2, 3}, YU Shui-li¹, ZHANG Lie-yu³, XI Bei-dou³, DOU Yan-yan², HOU Li-an^{1, 4}
		DOI: 10.3964/j.issn.1000-0593(2018)08-2549-07
		The vertical distribution characteristics of dissolved organic matter(DOM), which were treated by soil infiltration system with simulated high ammonia nitrogen wastewater, were studied by using three-dimensional excitation emission matrix (3D-EEMs)fluorescence spectroscopy and PARAFAC model. 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 with 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. Correlation analysis showed that there was a significant positive correlation among the four kinds of fluorescence components and most of the physical and chemical indexes. The fluorescence component concentration could indirectly characterize the removal efficiency of nitrogen, phosphorus and other nutrients. The analysis of Fmax showed that tyrosine was the most easily degradable in soil infiltration system, followed by fulvic acid, humic acid and the most difficult to degrade protein.
		2018 Vol. 38 (08): 2549-2555 [Abstract] ( 225 ) RICH HTML PDF (2899 KB) ( 142 )

	2556	Prediction of Soil Organic Matter Based PCA-MLR and PCA-BPN Algorithm Using Field VNIR Spectroscopy in Coastal Soils of Southern Laizhou Bay
		XU Xi-bo¹, LÜ Jian-shu^1，2, WU Quan-yuan^1, YU Qing¹, ZHOU Xu¹, CAO Jian-fei¹
		DOI: 10.3964/j.issn.1000-0593(2018)08-2556-07
		Soil organic matter (SOM) content is an important indicator of soil quality, which could be predicted using hyper spectral data rapidly. A total of 111 soil samples and hyperspectral data (325~1 075 nm) were collected from the coastal plain on the southern of Laizhou Bay. In previous study, most prediction model is based on the characteristic band and the linear empirical model, ignoring the information redundancy and collinearity between bands, the prediction accuracy is not high and it is difficult to be extended to other regions. In order to maximize the elimination of band information noise and improve the model prediction accuracy,the organic matter content of soil samples was measured as dependent variable. Through principal component analysis (PCA), the measured spectral is reduced to 6 principal components, and water and vegetation spectral characteristic indices are extracted as the independent variables. At last, we analyzed the prediction effect of different model on soil organic matter with MLR and BPN models. The results show: (1) the six principal components extracted from PCA on spectral information could be used to characterize the spectral characteristics of chlorophyll, salt, humic acid, materialized slag and micro- Landform. (2) The prediction accuracy of BPN model based on 6 principal components as independent variable is better than that of MLR model with R² of 0.704 and 0.643 respectively. After adding water and vegetation spectral characteristic index as an independent variable to prediction models, the prediction accuracy of MLR and BPN increased by 6.1% and 5.2%, and R² reached 0.712 and 0.764, respectively; (3) BPN model based spectral principal components and spectral characteristic indices as independent variables could predict soil organic matter with the highest accuracy, which has a potential application in soil organic matter prediction and mapping.
		2018 Vol. 38 (08): 2556-2562 [Abstract] ( 220 ) RICH HTML PDF (3831 KB) ( 134 )

	2563	Study on Soil Moisture Mechanism and Establishment of Model Based on Hyperspectral Imaging Technique
		WU Long-guo¹, WANG Song-lei^{1, 2}, HE Jian-guo^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2018)08-2563-08
		This article summarizes a near-infrared hyperspectral imaging technique was investigated for non-destructive determination of soil moisture content. A total of 208 soil samples were collected by hyperspectral imaging system. The differences of soil water content and spectral change, and the spectra of different water contents were compared. Different spectral preprocessing methods were analyzed and the characteristic wavelengths were extracted by different methods. MLR, PCR and PLSR modeling were used to optimize the best model. The results show that the reflectivity of the spectral curve decreases with the increase of soil water content, and the reflectivity of the spectral curve increases with the increase of soil moisture content when it increases beyond the field water holding capacity. With the increase of soil moisture content, the spectral reflectance of soil showed a decrease at first before increasing. When the soil moisture content is 30%, the reflectivity of soil spectrum increases. It is mainly because the soil moisture content exceeds the amount of soil surface water layer,form a double structure the soil can accommodate . The method of different pretreatment is analyzed, and the pretreatment method of normalization of unit vector is proposed. The number of characteristic wavelengths extracted by UVE, CARS, β coefficient, SPA were 49, 30, 5, 7, respectively. In order to reduce the data redundancy, the characteristic wavelengths of UVE and CARS were further extracted by SPA method. The number of characteristic wavelengths of UVE+SPA and CARS+SPA were 5, 8. On the basis of this, the MLS, PCR and PLSR methods were used to model the characteristic wavelengths of the range of 400~1 000 nm. The MLR model of the characteristic wavelengths extracted by β coefficient was obtained by comparing the different modeling results.The optimal characteristic wavelength is 411, 440, 622, 713, 790 nm. The prediction coefficient R_p=0.979 is the best model, and the RMSEP is 0.763.Therefore, the soil moisture content can be quantitatively analyzed in different bands in the future.
		2018 Vol. 38 (08): 2563-2570 [Abstract] ( 193 ) RICH HTML PDF (4028 KB) ( 116 )

	2571	Quantitative Inversion of Organic Matter Content Based on Interconnection Traditional Spectral Transform and Continuous Wavelet Transform
		WANG Yan-cang^{1, 3}, JIN Yong-tao^{1, 3}, WANG Xiao-ning^{1, 3}, LIAO Qin-hong⁵, GU Xiao-he^{2, 4*}, ZHAO Zi-hui^{1, 3}, YANG Xiu-feng^1,3
		DOI: 10.3964/j.issn.1000-0593(2018)08-2571-07
		In this study, the soil organic matter content of 96 alluvial soil collected from Beijing area was taken as the object of study; Compared with the traditional spectral transform technology, this paper studied on the analysis of the traditional spectral transform and continuous wavelet technology coupling in the feasibility of estimating soil organic matter content. Firstly, the traditional spectral transform technique and the continuous wavelet transform were used to deal with the soil spectral data. Then The correlation between the spectral data and the soil organic matter content was analyzed, and the sensitive bands were extracted. Finally the estimation model of soil organic matter content was constructed by partial least square method. The results showed that the coupling of traditional spectral transform and continuous wavelet technology can greatly improve the spectral sensitivity of organic matter content, and the correlation coefficient (R²) was up to 0.714, which indicate that the coupling of the traditional spectral transform and continuous wavelet technology can dig the useful signal of the spectral information; Compared with the traditional spectral transform technology, the accuracy of the model based on the interconnection of traditional technique and continuous wavelet transform was higher and better stability; Among of the model based on the interconnection of traditional technique and continuous wavelet transform, the model construct by the differential transform was the Optimal model; Its coefficient of decision and root mean square error were 0.774 and 0.223 respectively, which indicated that the interconnection of traditional technique and continuous wavelet transform spectral technique can effectively suppress noise, improving the spectral stability.
		2018 Vol. 38 (08): 2571-2577 [Abstract] ( 173 ) RICH HTML PDF (4241 KB) ( 160 )

	2578	Investigation on the Properties of Laser Induced Ni Plasma
		ZHANG Gui-yin¹, SONG Huan¹, LIU Yang¹, REN Zhi¹, ZHENG Hai-ming²
		DOI: 10.3964/j.issn.1000-0593(2018)08-2578-05
		With the harmonic output 532 nm of a pulsed Nd·YAG laser as radiation source, the emission spectrum of laser induced nickel sample plasma was investigated. Most emission peaks of the spectrum were assigned to NiⅠand NiⅡ. The electronic excitation temperature and electron density in the plasma was measured. They were 3 714 K and 4.67×10¹⁶ cm^-3 respectively. The spatial distribution of the temperature and electron density were measured by moving the detection head of a fiber along the direction parallel and vertical to the laser beam. It showed that the emission intensity of the plasma in the centre was most strong. With the measurement points moving apart from the center along the direction vertical to the laser beam, the emission intensity decreases, but both of the line profile and width of the emission spectral was almost invariable. So the electronic excitation temperature and electron density in the plasma was uniform along this direction. While along the direction parallel to the laser beam, the temperature and electron density were not uniform. They took the maximum value at the position about 1.5mm apart from the sample. We ought to collect the emission spectrum of this position when perform relative investigation with the technique of LIBS. This can ensure higher detection sensitivity.
		2018 Vol. 38 (08): 2578-2582 [Abstract] ( 196 ) RICH HTML PDF (1658 KB) ( 48 )

	2583	Influence of Temperature on Laser Induced Fluorescence Spectroscopy of Mine Goaf Water
		HU Feng, ZHOU Meng-ran^*, YAN Peng-cheng, ZHANG Jie-wei, WU Lei-ming, ZHOU Yue-chen
		DOI: 10.3964/j.issn.1000-0593(2018)08-2583-05
		Rapid identification of coal mine inrush water source is of great significance to coal mine safety production, therefore，laser induced fluorescence technology is used in the rapid identification of coal mine inrush water, which broke the insufficiency of a long time spent on traditional chemistry method. Mine goaf water is the most common and the most harmful type of water source, and the temperature is one of the most important factors that affect the physical properties. Studying the temperature characteristics of laser induced fluorescence detection of the goaf water can help to quickly and accurately identify mine inrush sources, which has important academic significance and practical value. In this paper, 405 nm blue-violet semiconductor laser as a light source, the laser power is set to 120 mW, the generating laser light is supposed to go by the UV/Vis quartz fiber and expose the water sample by fluorescence probe before the tested water samples are activated by laser to generate the fluorescence which is collected by a fluorescence probe. Finally it is transmitted to the spectrometer through quartz fiber.Taking the goaf water collected from Zhangji Coal Mine in Huainan in March 2017 as the research object, the suspended particles in the water sample is filtered out before placing it in the beaker and reducing the sample temperature to 5 ℃ with ice cubes to. Then it is put into a constant temperature bath pot, using the iron stand fixed fluorescent probe to deposite it at a place 1 cm under the liquid surface. In the process of fluorescence spectrum acquisition, the sample is always placed in a constant temperature water bath, and the fluorescence spectra were obtained by controlling the temperature of the sample in the water bath over the temperature range of 10.0～60.0 ℃, and discusses the effects of temperature variation on the laser induced fluorescence spectra, peak position, peaks, temperature coefficients and spectral area of the goaf water. The results show that, with the increase of temperature, the molecular motion is accelerated, the probability of collision between the molecules is increased. As a result, the non-radiative transition increases, the fluorescence efficiency of the goaf water decreases, the fluorescence intensity is weakened, and the overall attenuation of the fluorescence spectra is mainly concentrated in the 400～700 nm band. The wavelength of the two peaks in the fluorescent spectra of the goaf water remains unchanged, which did not drift with temperature. The fluorescence intensity of two peaks (472 and 493 nm) is where it is weakened the most. Besides, there is a good linear relationship between the decrease of fluorescence intensity and the temperature rise, the correlation coefficient r² is 0.91 at 472 nm, and the fitting correlation coefficient r² is 0.963 36 at 293 nm. The temperature coefficient at 472 nm reached a minimum of 0.34% at 20.0 ℃, 493 nm temperature coefficient at 20 ℃ when the minimum value of 0.81%, both temperature coefficients in 20 ℃ to achieve the lowest value that fluorescence spectra in the vicinity of 20 ℃ the most stable. When the temperature increases, the area of the old air water in the 400～700 nm band and the temperature axis is gradually reduced, the correlation coefficient r² of the area and the temperature of the 400～700 nm band spectrum is 0.975 39, i.e. the decrease of the area and the temperature rise has a good linear relation. By studying the temperature characteristics of the mine goaf water, the laser induced fluorescence spectrum of the mine goaf water is the most stable at 20 ℃, and under this temperature condition, the laser induced fluorescence technique is the most effective to identify the mine water source. At the same time, the temperature compensation by using the linear relation of the goaf wave peak and the area to the temperature can further enhance the sensitivity and accuracy of the identification of mine water inrush by using LIF technology. The study is of great significance to realize fast and accurate discrimination of mine goaf water.
		2018 Vol. 38 (08): 2583-2587 [Abstract] ( 225 ) RICH HTML PDF (2251 KB) ( 170 )

	2588	Analysis of Ultra-Trace Impurities in High Purity Molybdenum Powder through Inductively Coupled Plasma Tandem Mass Spectrometry
		FU Liang^{1, 2}, SHI Shu-yun^2*, TANG You-gen², WANG Hai-yan²
		DOI: 10.3964/j.issn.1000-0593(2018)08-2588-07
		An analytical method for the determination of ultra-trace impurities in high purity molybdenum was established by inductively coupled plasma tandem mass spectrometry (ICP-MS/MS). In MS/MS mode, H₂ was used as the reaction gas to measure Si and Ca through the H₂ on-mass method. O₂ was employed as the reaction gas to measure the Cd via the O₂ on-mass method, and P, As, Se, Ta, Sn, Sb, Ba, and W were measured by the O₂ mass-shift method. NH₃/He was adopted as the reaction gas, so that Na, Mg, Al, K, and V could be measured by NH₃/He on-mass method, and Ti, Cr, Mn, Fe, Co, Ni, Cu, and Zn could be measured by the NH₃/He mass- shift method. Pb, Bi, Th, and U were measured in single quadropole (SQ) mode without gas. Compared with conventional collision/reaction cell (CRC) inductively coupled plasma mass spectrometry (ICP-MS), the background equivalent concentration (BEC) and detection limit of analyte in this method were lower, and the mass spectrum interference could be eliminated more thoroughly. Under optimized working conditions, the calibration curves of analytes showed good linearity with linear correlation coefficient (R²)≥0.999 7. The detection limit was 0.04～50.1 ng·L^-1, the spike recoveries were 92.2%～107.4% and the relative standard deviation (RSD) was ≤4.3%, indicating that the proposal method has excellent accuracy and precision. The results of the sample analysis showed that the method can be used for the determination of 28 impurity elements in high purity molybdenum powder with purity of 5N (≥99.999%).
		2018 Vol. 38 (08): 2588-2594 [Abstract] ( 199 ) RICH HTML PDF (2384 KB) ( 85 )

	2595	Determination of Manganese in Water Samples by Cloud Point Extraction with MN-CCA-CPC Flame Atomic Absorption Spectrometry
		CHEN Zhuo¹, SU Yu-qing², SONG Shan¹, YAO Jun-xue^1*
		DOI: 10.3964/j.issn.1000-0593(2018)08-2595-05
		In this work, a simple and novel cloud point extraction (CPE) method for the separation and preconcentration of manganese in aquatic environment was developed and combined with flame atomic absorption spectrometry (FAAS). Manganese was formed a complex with Calcon carboxylic acid (CCA) in the presence of Cetyl pyridinium chloride (CPC) and Triton X-114. The main factors affected the CPE, such as pH, the dosage of Triton X-114, CCA, CPC, NaCl, coexisting ions, and the heating time and heating temperature. After optimization of the experimental conditions, the system of Mn-CCA-CPC was able to overcome the matrix interference and showed the significant effect of separation of enrichment. The precision of the method was 0.39% and the limit of detection was 0.27 μg·L^-1 of Mn. The results of the determination of manganese content in tap water and groundwater were 33.5 and 64.5 μg·L^-1, which was in line with the international standards, so the method can be successfully applied for the determination of manganese in the water environment.
		2018 Vol. 38 (08): 2595-2599 [Abstract] ( 144 ) RICH HTML PDF (1913 KB) ( 50 )

	2600	The Rapid Detection of Cadmium in Soil Based on Energy Dispersive X-Ray Flourescence
		CHEN Ji-wen^1,2, NI Zi-yue¹, CHENG Da-wei², LIU Ming-bo², LIAO Xue-liang², YANG Bo-zan², YUE Yuan-bo², HAN Bing², LI Xiao-jia^1,2
		DOI: 10.3964/j.issn.1000-0593(2018)08-2600-06
		For the detection of heavy metals in soil, conventional methods of chemical analysis are of many deficiencies, such as long time consuming, complex pretreatment process, and the strong acid used will cause secondary pollution to environment. However，energy dispersive X-Ray fluorescence spectrometry have many advantages, such as non-destruction, fast test, simple pretreatment, easy to carry etc., which make it especially suitable on rapid on-site monitoring. When using this method to detect cadmium, the energy of K series characteristic line is larger, making the limit of the detection relatively high for general EDXRF. Based on the energy dispersive X-Ray fluorescence spectroscopy, the rapid detection of trace cadmium in soil was studied. Appropriate devices were chosen to constructing the instrument platform, and the instrument structures and test conditions were optimized considering peak intensity and relative intensity of determined element.Research showed that the peak intensity increased linearly with the increase of tube current, while relative intensity had no obvious change. Hence, for the detection of cadmium, tube current chosen were as large as possible with the permission of X-Ray tube. Afterwards, considering peak intensity and relative intensity of cadmium with different thickness of filter and tube voltage, the optimized conditions could be ascertained by using theoretical relative deviation. And the optimal conditions were as follows: the tube voltage was 55 kV, tube current was 48 μA, the filter was molybdenum with the thickness of 1.25 mm. The measurement time had an influence on relative standard deviation of results. When measuring times were less than 500 seconds, the relative standard deviation of peak intensity decreased with time increasing, while having no more obvious change after measuring times longer than 500 seconds. And the relative standard deviation was smaller, the short-term precision of results better, which made repetition appropriate for the detection. So 500 seconds was chosen as measuring time. At the same time, test conditions of samples also had an influence on the results. Since both the peak intensity and relative intensity decreased with increasing thickness of film, the thickness of 12.5 μm of polyester film was chosen to be used. And both peak intensity and relative intensity of cadmium increased with increasing weight of samples at first, but when the weight was more than 3g, as the weight increased, the peak intensity of cadmium changed slowly and relative intensity had no obvious change. So the weight of samples should be more than 3 g. The peak intensity and relative intensity decreased as water content increased in soil, which meant that soil moisture would affect test results, and soil samples should be air drying or oven drying. Adopting the optimized conditions above, the linear correlation coefficient was 0.993 of samples when using national standard samples or samples determined by inductively coupled plasma mass spectrometry. A national standard sample was tested 11 times in which the concentration was 1.12 mg·kg^-1, and the standard deviation of the results was 0.09, and the relative standard deviation was 8.22%. The limit of detection of this method was 0.16 mg·kg^-1 detected by high purity silicon dioxide for 11 times, which was below the limit of the first grade soil. Compared with inductively coupled plasma mass spectrometry, the test results had significant consistency. After optimizing instrument structure and test conditions of samples, the limit of detection was lower for trace cadmium in soil based on energy dispersive fluorescence spectrometry, which will play an important part in the rapidly screening of pollution area and the measurement in large area of cadmium.
		2018 Vol. 38 (08): 2600-2605 [Abstract] ( 205 ) RICH HTML PDF (1660 KB) ( 112 )

	2606	Quantitative Analysis, Distribution and Speciation of Elements as Pb, As, Cd in Human Hair from Inhabitants in a Lead-Zinc Mining Area
		FU Chen-fei^{1, 2}, LUO Li-qiang^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2018)08-2606-06
		Hair is one of the excretion organs in human body, so the element content in hair can reflect human body exposure to the toxic elements in the vicinity of the mining area in a period. Pb, As, Cd, Ca, Mg, Fe, Zn, Cu, Mn and Sr in hair sampels collected from a lead-zinc mine were analyzed quantitatively with Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-OES). Micro X-ray fluorescence(Micro-XRF) and X-ray absorption near edge structure(XANES) were used to determine element distribution of Pb, As and speciation of Pb, respectively. The study revealed that (1) The average contents Pb, Zn, Fe, Ca(female) and Mn(male) in the hair sampels were 1.2 times, 1.3 times, 3.9 times, 1.6 times and 1.2 times higher than the normal values, respectively. (2) It was confirmed that The toxic elements in the mining area can be transferred to human beings through the food chain and may causeeventually serious health problems. In addition, different physiological features and living habits were main factors that determined the metal distribution in the different gender groups. Those restuls in that Pb, Cd, Ca, Mg, Zn, Cu and Sr in female were significantly higher than those in male while Fe was in male higher than that in femail. (3) As a result of elements properties, sources and absorption mechanismthere was a positive correlation between Ca-Mg-Sr-Zn, Pb-Cd-Cu-Mn and Fe-Mn respectively. (3) Micro-XRF mapping showed that Pb and As were mainly distributed along the hair axis. Horizontally, the concentration gradient of Pb and As plunge from inside to outside. Because daily cleaning and wearing will lead to peeling of Pb and As which were not closely tied. Longitudinally, there was an increasing trend of Pb and As from hair root to hair tip. We speculated that Pb and As unite with cysteine of keratin in cortex. The vertical distribution characteristics of Pb and As reflected the change of external environment which residents exposed to. (4) On the basis fo XANES analysis, lead in the collected hair sample was composed of 54.7% lead phosphate, 36.8% Pb-glutathione and 8.4% lead sulfide. (5) The main lead speciation in hair were insolubility lead phosphate and sulfur-bounding speciation like Pb-cysteine, suggesting that hair is one of the main way to metabolise lead. To our knowledge, this is the first report on the speciation of Pb in the human hair from lead-zinc mining area.
		2018 Vol. 38 (08): 2606-2611 [Abstract] ( 238 ) RICH HTML PDF (1813 KB) ( 128 )

	2612	Preliminary Study in Spectral Mixing Model of Mineral Pigments on Chinese Ancient Paintings-Take Azurite and Malachite for Example
		LI Da-peng¹, ZHAO Heng-qian^1,2, ZHANG Li-fu^2, ZHAO Xue-sheng¹
		DOI: 10.3964/j.issn.1000-0593(2018)08-2612-05
		Hyperspectral remote sensing technology is completely non-invasive for cultural relics, and suitable for identification and analysis of pigments of Chinese ancient paintings and other cultural relics, but the quantitative analysis of the mixed pigments composition in the ancient paintings is still a difficulty. For the mixed pigments phenomenon which often appears in Chinese ancient paintings, taking an example of azurite and malachite, two typical mineral pigments, we choose the two kinds of mineral pigment powder with the same size, precisely compound these two kinds of pigments to obtain pigment samples, and then obtain their spectra understrict control of experimental conditions . For mixed spectra, we use fully constrained least square method for spectral unmixing with full bands and use derivative of ratio spectroscopy for spectral unmixing with single band, then evaluate the unmixing accuracy, compare and analyze the unmixing results, and finally discuss the spectral mixing model of these two kinds of mineral pigments. Experimental results show that the spectral mixtures of azurite and malachite display strong nonlinear mixing characteristics overall, but are in accordance with linear mixing model in some strong linear bands. Using derivative of ratio method for spectral unmixing at these bands, we can achieve much higher unmixing accuracy than spectral unmixing with full bands.
		2018 Vol. 38 (08): 2612-2616 [Abstract] ( 230 ) RICH HTML PDF (2222 KB) ( 91 )

	2617	Investigation of Degradation of Endocrine Disrupting Compounds by Ozone as Indicated by Ultraviolet and Fluorescence Spectroscopy
		SI Xiu-rong^1,2, JIN Jie³, FU Xu¹, WU Xiao-fang¹
		DOI: 10.3964/j.issn.1000-0593(2018)08-2617-07
		Wastewater treatment and reclamation are effective approaches to alleviate the serious water pollution and water shortage in China. Because of its large and stable quantity and excellent quality, secondary effluent is an excellent water source for the reclamation of wastewater. However, the widespread presence of the endocrine disrupting compounds (EDCs) in secondary effluent poses potential safety risks to its reclamation. Ozonation is an effective method to remove EDCs. However, because of the presence of many organic substances in secondary effluent, ozone also reacts with the active groups in organic mattersduring the ozonationdegradation process of EDCs, causing a certain degree of ozone attenuation, and thus, affecting the ozonation of EDCs. The change in active groups of organic matters that react with ozone is reflected in the change of their UV and fluorescence spectra. Therefore, changesin the characteristic UV and fluorescence spectra can be used to indicate the degradation effect of EDCs by ozone. In this study, we investigated the effect of three main organic matters (humic acid (HA), bovine serum albumin (BSA), and sodium alginate (SA)) present in secondary effluent on the kinetics of ozone attenuation and further analyzed the effect of organic matters on the ozonation degradation of 5 typical EDCs. Based on these results, we further investigated the relationship between the characteristic UV and fluorescence spectra and the degradation effect of EDCs by ozone, with the hope of selecting indicator parameters for the ozone-degradation of secondary effluent EDCs and establishing a quantitative relationship between these parameters and the degradation efficiency towards EDCs. Accordingly, these indicator parameters can be used to predict the ozonation degradation of EDCs, thereby simplifying the detection of EDCs. In this study, 5 target EDCs (estrone (E1), estradiol (E2), estriol (E3), 17α-ethinylestradiol (EE2), and bisphenol A (BPA)) were analyzed and quantified using ultraperformance liquid chromatography-mass spectrometry (UPLC/MS/MS). It was found through the investigation of the impact of different organic matters in secondary effluent on the kinetics of ozone attenuation and EDCs degradation that three organic matters promotedozone attenuation and inhibited the ozonation degradation of EDCs with the following descending effect: HA>BSA>SA. The characteristic spectra of these organic matters indicated that the active groups of these organic matters that could react with ozone exhibitedspecific response characteristics in the UV-Vis region. The three-dimensional excitation-emission matrix (EEM) fluorescence spectra of the three organic matters indicated that the fulvic acid-type humic acids and quinoline-type structures contributed significantly to ozone attenuation; the UV absorbance at 254, 258 and 280 nm and the fluorescence absorbance at the excitation/emission wavelengths of (Ex/Em)=240/396 nm and Ex/Em=345/436 nm were significantly correlated with the dosage of ozone. Among those, the characteristic UV absorbance (UVA₂₈₀) and fluorescence absorbance (Ex/Em=240/396 nm) could be used as indicator parameters for the ozonation degradation of EDCs; specifically, as shown when the UVA₂₈₀ removal efficiency was greater than 18% or the Ex/Em=240/396 nm removal efficiency was greater than 35%, 1 μmol·L^-1 of the five EDCs was nearly completely degraded. The results in this study can be used to guide the optimization of ozone dosage in the removal of EDCs in wastewater plants and the removal efficiency of EDCs. In addition, the complicated detection of EDCs can be avoided.
		2018 Vol. 38 (08): 2617-2623 [Abstract] ( 198 ) RICH HTML PDF (2689 KB) ( 67 )

	2624	*Biomimetic Synthesis of Silver Nanoparticle Using Leaf Extract of Mangifera Indica* and Their Antibacterial Efficacy**
		Vikas Sarsar¹, Manjit K. Selwal¹, Krishan K. Selwal^{1, 2*}
		DOI: 10.3964/j.issn.1000-0593(2018)08-2624-06
		The aim of this study to focused on bioinspired synthesis of silver nanoparticles (AgNPs) as a viable alternative to eradicate the existing physicochemical processes. In this context, the bioinspired AgNPs were synthesized using leaf extract of M. indica. Optimization of the experimental conditions for the rapid and high yield of AgNPs in minimum investment of time and expense have been carried out along with their antibacterial efficacy evaluated. For this reason, the variation of parameters like the concentration of the silver precursors, reducing agent, time, pH, and temperature of synthesis were realized. Synthesized AgNPs were characterized by UV-Visible spectroscopy, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and transmission electron microscopy (TEM) techniques. UV-Visible spectra gave surface plasmon resonance (SPR) at 440 nm for AgNPs. Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) techniques were further confirmed the synthesis and crystalline nature of AgNPs respectively. Transmission electron microscopy (TEM) observed spherical shapes of synthesized AgNPs within range 5～20 nm. The results of the current study indicate that optimization process play a pivotal role in the AgNPs synthesis and biogenic synthesized AgNPs might be used against bacterial pathogens.
		2018 Vol. 38 (08): 2624-2629 [Abstract] ( 146 ) RICH HTML PDF (2996 KB) ( 67 )

	2630	Chemical Effect Analyses of 3d Elements by Study of X-Ray Fluorescence Spectra
		Sevil(Porikli) DURDAĞI
		DOI: 10.3964/j.issn.1000-0593(2018)08-2630-08
		Spectra of K X-rays emitted from pure 3d transition metals and their oxide and sulfate compounds were measured using a single crystal wavelength dispersive X-ray spectroscopy (WDXRF). The measurements were performed using a ZSX-100e sequential spectrometer equipped with an Rh X-ray tube operated. An accurate analytical representation of each line was obtained by a fit to a Lorentz function. The spectra were analyzed in order to examine the K X-ray peak parameters such as asymmetry index, peak energy and relative intensity ratios. The energy shifts and relative intensities weredetermined tobetter understand the chemical effect.
		2018 Vol. 38 (08): 2630-2637 [Abstract] ( 140 ) RICH HTML PDF (1641 KB) ( 75 )

	2638	Development a Spectrophotometric of Fe(Ⅲ), Al(Ⅲ) and Cu(Ⅱ) Using Eriochrome Cyanine R Ligand and Assessment of the Obtained Data by Partial Least-Squares and Artificial Neural Network Method—Application to Natural Waters
		A. Hakan AKTAŞ
		DOI: 10.3964/j.issn.1000-0593(2018)08-2638-07
		Simultaneous determination of heavy metal cations and accurate quantitative prediction of them are of great interest in analytical chemistry. This work has focused on a comprehensive comparison of partial least squares (PLS-1) and artificial neural networks (ANN) as two types of chemometric methods. For this purpose, aluminum, iron and copper were studied as three analytes whose UV-Vis absorption spectra highly overlap each other. Accordance with determined parameters (ligand concentration, pH, waiting times, the relationship between absorbance and concentration of metal ion effect and foreign ions) are provided and the optimum conditions. After establishing the optimum conditions for Fe³⁺, Al³⁺ and Cu²⁺ containing mixtures spectrophotometric determinations and the data calibration method of least squares (PLS-1) regression, and artificial neural network (ANN) methods were used. Chemometric methods are applied in a fast, simple, and the results are applicable.
		2018 Vol. 38 (08): 2638-2644 [Abstract] ( 146 ) RICH HTML PDF (1203 KB) ( 69 )

	2645	Chemical Analysis of Hydroxyapatite Artificial Bone Powders by Energy Dispersive X-Ray Fluorescence Spectrometry (EDXRF)
		O. K. Koksal^1,2*, G. Apaydin¹, E. Cengiz¹, L. Samek², .H. Karahan³, A. Tozar³, M. Lankosz²
		DOI: 10.3964/j.issn.1000-0593(2018)08-2645-05
		Stoichiometric hydroxyapatite (HA) nanoparticles were synthesized by a wet chemical method. Calcium nitrate tetra hydrate used as calcium source and dibasic ammonium phosphate used as phosphorous source. Calcium nitrate tetra hydrate and dibasic ammonium phosphate solutions were prepared by dissolving the salts in distilled water. Stoichiometric hydroxyapatite nanoparticles used by artificial bone powders and synthesized by a wet chemical method were analyzed using EDXRF method.The concentrations of K, Ca, Ti, V, Cr, Fe, Ni, Cu, Sr and Pb for artificial bone powders have been determined. Besides, Calcium contents were evaluated according to the agitation time and temperature in the production process.
		2018 Vol. 38 (08): 2645-2649 [Abstract] ( 184 ) RICH HTML PDF (1188 KB) ( 86 )

	2650	Quercetin-Functionalized Core-Shell Ag@SiO₂ Nanoparticles for Detection of Copper Ions
		JIANG Wei-na^1,2, YANG Shi-long^1,3, LU Wen⁴, XU Li^2,3,4, TANG Ying^2,3,5, XUE Hua-yu¹, GAO Bu-hong³, DU Li-ting³, SUN Hai-jun³, MA Meng-tao⁴, XU Hai-jun^1, CAO Fu-liang^2,5
		DOI: 10.3964/j.issn.1000-0593(2018)08-2650-07
		A novel fluorescent sensor based on natural quercetin and core-shell Ag@SiO₂ nanoparticles for highly sensitive and selective detection of copper ions has been studied. The Ag@SiO₂@Quercetin fluorescent sensor after binding to Cu²⁺ ions showed a quenching of fluorescence emission intensity. The sensor can be applied to the quantification of Cu²⁺ ions with a linear range of 3.0×10^-7～4.8×10^-6 mol·L^-1 and a detection limit of 1.0×10^-7 mol·L^-1. The sensor showed high selectivity toward Cu²⁺. As a result, the proposed fluorescent nanosensor was successfully applied for determination of Cu²⁺ in water samples with good recovery.
		2018 Vol. 38 (08): 2650-2656 [Abstract] ( 290 ) RICH HTML PDF (2859 KB) ( 66 )

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