[Rapid Quantitative Detection of Bacterial in Water Based on Multi-Wavelength Scattering Spectra].

The structures of bacterial cells are analyzed in this paper. The scattering components of individual cell were divided into two parts including external structure and internal structure. The interpretation model of bacteria about scattering light is established. The model is used to analyze the scattering light of Escherichia coli in the region of 400~900 nm. The average size of external structure and the internal structure can be obtained, and the ratio of the two parts is also obtained. According to the relationship of the optical density of single cell and the overall measurement, the concentration of bacterial can be obtained quickly. The maximum difference in all the concentrations of the bacteria repeated measurements is 1.83%; compared with the plate culture method, the measurement results were in the same order of magnitude, with relative error of 3.43%. The scattering light of Escherichia coli and Klebsiella pneumoniae are analyzed in different growth stages, the curves of the concentration and the size of the two species bacteria over time are obtained. The results can provide a quick way for the study of bacterial growth and technical support for rapid detection of bacteria in the water.

[Comparative Study on Laser Induced Breakdown Spectroscopy Based on Single Pulse and Re-Heating Orthogonal Dual Pulse].

In order to improve the detection sensitivity and spectral characteristic of laser-induced breakdown spectroscopy (LIBS), re-heating orthogonal dual-pulse configuration is adopted to analyze Fe, Pb, Ca and Mg contained in the sample and soil sample contained different concentrations of heavy mental Cr. Variation relationship between spectral intensity, signal-to-background(SBR) of four characteristic spectral lines FeⅠ：404.581 nm，PbⅠ：405.78 nm，CaⅠ：422.67 nm and MgⅠ：518.361 nm and time interval of two laser pulses is discussed, the best time interval of two laser pulses is obtained 1.0 µs. In the condition of single pulse and dual-pulse, the enhancement factor of spectral intensity of four characteristic spectral lines FeⅠ：404.581 nm，PbⅠ：405.78 nm，CaⅠ：422.67 nm and MgⅠ：518.361 nm is respectively 2.23，2.31，2.42 and 2.10; The time evolution characteristic of spectral intensity of characteristic spectral lines FeⅠ：404.581 nm and CaⅠ：422.67 nm is considered, and also the variation relationship between spectral acquisition delay time and SBR of four characteristic spectral lines, dual-pulse can prolong decay time of spectral intensity and improve the SBR of characteristic spectral lines; time evolution characteristic of plasma temperature and electron density is compared in the condition of single pulse and dual-pulse, maximum elevation of plasma temperature is found to be 730 K, and the maximum increase of electron density is 1.8×1016 cm-3. The limits of detection of heavy mental Cr are obtained 38 and 20 µg·g-1 respectively in condition of single and double pulse, limit of detection of Cr is reduced approximately 2 times by the condition of re-heating orthogonal dual pulse. Results above indicate that re-heating orthogonal dual-pulse can improve detection sensibility and spectral characteristic of LIBS technique, which provides an effective method for decreasing the limit of detection of elements.

[Rapid Soil Classification with Laser Induced Breakdown Spectroscopy].

Soil classification is an important research content in soil science field. It is the basis of soil survey and resource evaluation which is important to agricultural production. There are many soil classification standards all over the world. China has two kinds of classifications including soil genetic classification and soil system classification. There are great differences between different types of soil elements, so it is feasible for soil classification to use laser induced breakdown spectroscopy. Laser induced breakdown spectroscopy (LIBS) is a new element analysis technology which uses a laser pulse with high energy density to ablate samples. LIBS has been used in many fields including environmental protection and industrial production control. It can directly reflect the difference of element content in different soils. The experimental setup including an Nd: YAG laser, a spectrometer, a computer and a rotating platform. In the experiment 7 kinds of soil (red soil, brick red soil, lateritic red soil, paddy soil, cinnamon, alluvial soil and alpine meadow soil) including 25 samples were used. All soil samples were grinded and sieved before the experiment. Under the same experimental condition, the temperatures of the plasma created by the laser pulses on the surface of the different soil samples have great differences. The lateritic red soil had the highest temperature, and the alpine meadow soil had the lowest. But it was not enough to form the basis for classification. Therefore six constant elements including Si, Fe, Al, Mg, Ca and Ti were selected and their spectral line intensity were treated as classification index. Principal component analysis (PCA) was used to simplify the classification process. The PCA method could simplify the 6 indexes to few independent indexes which could also reflect the spectral information of the 6 elements. The original spectral data was processed by Matlab. The process consisted of spectral background removal, characteristic spectrum identify and extraction. The classification results showed a three--dimensional figure. Except alpine meadow soil which varied in element concentrations 6 kinds of soils achieved good classification. The brick red soil and lateritic red soil varied in PC1, but their PC2s and PC3s were the same. The two kinds of soil overlapped with each other and they couldn't be separated. Back-propagation artificial network was also used to achieve soil classification. The classification results were the same with the PCA. Some brick red soil and lateritic red soil samples were identified inaccurately. When the PC1, 2, 3 were used as the input of the BP-neural network, the classification had much better accuracy because less input improved the performance of the BP-neural network. Only one alpine meadow soil sample was identified to cinnamon soil. When the plasma temperature was also taken into account, all the soil samples could be distinguished. The results showed that LIBS could be used to classify soils based on their element content differences. The PCA, soil plasma temperature and BP-neural network were useful tools to achieve soil classification. The LIBS provides a useful tool for general detailed soil survey and rational utilization of soil.

Study on Detection Sensitivity of Heavy Metal in Water Based on LIBS Combined with Electrode Enrichment Method.

In order to improve the detection sensitivity of laser-induced breakdown spectroscopy (LIBS) and lower the limit of the detection of elements, LIBS combined with Aluminum electrode enrichment method is adopted to analyze heavy metals such as Pb,Cdand Ni in the water. The relationship between the characteristic spectral intensity and the key parameters-voltage of electrode method is discussed, the spectral intensity increases first and then decreases with the increase of voltage. The spectral intensity reaches the maximum value when the enrichment voltage is 1.2 V while the optimal enrichment voltage value is 1.2 V. The stability of characteristic spectral lines of heavy metals is studied, and the relative standard deviation(RSD) of spectral intensity of Pb, Cd and Ni is 5.98％，4.25 ％ and 5.27％ respectively, the result shows that the spectral line obtained by this method has high stability. A series of samples in the range of 0~0.13 mg·L-1 are prepared and quantitatively analyzed, the limit of detection of Pb, Cd and Ni is obtained 1.2，3.1 and 1.7 ppb respectively. The above result shows that LIBS combined with aluminum electrode enrichment method can effectively improve the stability of characteristic spectral lines and lower the limit of detection of Pb,Cd and Ni. This research also provides a method to further improve detection sensitivity of LIBS and analysis ability of heavy metal in the water.

[Quantitative Analysis of Cr in Soil with Laser Induced Breakdown Spectroscopy Combined With Multivariate Calibration].

Laser-induced breakdown spectroscopy (LIBS) was used to calibrate the concentration of Cr in soils combined with Support Vector Machine. The Nd:YAG pulse laser with the wavelength of 1 064 nm was used as the excitation source. The grating spectrometer and the charge couple device were used as spectral separation device and the spectral detection device. The multiple linear regression and support vector machine were adopted to make quantitative analysis on Cr in soils respectively. The result indicate that the multiple linear regression can get more accurate informination of the spectral lines: the correlation coefficient is increased from 0.689 to 0.980 compared with conventional quantitative method. Thereofre, the the accuracy of quantitative analysis is increased. The slope about calibration curve with support vector machine of test set is nearly about 1 and the correlation coefficient is 0.998, the relative errors for the test set all are lower than 2.57%, the quantitative analysis results about support vector machine are better than the results combined with the conventional quantitative method and the multiple linear regression. The support vector machine can correct the matrix effect and improve the accuracy of prediction on the concentration of Cr in soil.

[Study of Rapid Species Identification of Bacteria in Water].

Multi-wavelength ultraviolet visible (UV-Vis) transmission spectra of bacteria combined the forward scattering and absorption properties of microbes, contains substantial information on size, shape, and the other chemical, physiological character of bacterial cells, has the bacterial species specificity, which can be applied to rapid species identification of bacterial microbes. Four different kinds of bacteria including Escherichia coli, Staphylococcus aureus, Salmonella typhimurium and Klebsiella pneumonia which were commonly existed in water were researched in this paper. Their multi-wavelength UV-Vis transmission spectra were measured and analyzed. The rapid identification method and model of bacteria were built which were based on support vector machine (SVM) and multi-wavelength UV-Vis transmission spectra of the bacteria. Using the internal cross validation based on grid search method of the training set for obtaining the best penalty factor C and the kernel parameter g, which the model needed. Established the bacteria fast identification model according to the optimal parameters and one-against-one classification method included in LibSVM. Using different experimental bacteria strains of transmission spectra as a test set of classification accuracy verification of the model, the analysis results showed that the bacterial rapid identification model built in this paper can identification the four kinds bacterial which chosen in this paper as the accuracy was 100%, and the model also can identified different subspecies of E. coli test set as the accuracy was 100%, proved the model had a good stability in identification bacterial species. In this paper, the research results of this study not only can provide a method for rapid identification and early warning of bacterial microbial in drinking water sources, but also can be used as the microbes identified in biomedical a simple, rapid and accurate means.

[The research on separating and extracting overlapping spectral feature lines in LIBS using damped least squares method].

In recent years, the technology of laser induced breakdown spectroscopy has been developed rapidly. As one kind of new material composition detection technology, laser induced breakdown spectroscopy can simultaneously detect multi elements fast and simply without any complex sample preparation and realize field, in-situ material composition detection of the sample to be tested. This kind of technology is very promising in many fields. It is very important to separate, fit and extract spectral feature lines in laser induced breakdown spectroscopy, which is the cornerstone of spectral feature recognition and subsequent elements concentrations inversion research. In order to realize effective separation, fitting and extraction of spectral feature lines in laser induced breakdown spectroscopy, the original parameters for spectral lines fitting before iteration were analyzed and determined. The spectral feature line of' chromium (Cr I : 427.480 nm) in fly ash gathered from a coal-fired power station, which was overlapped with another line(FeI: 427.176 nm), was separated from the other one and extracted by using damped least squares method. Based on Gauss-Newton iteration, damped least squares method adds damping factor to step and adjust step length dynamically according to the feedback information after each iteration, in order to prevent the iteration from diverging and make sure that the iteration could converge fast. Damped least squares method helps to obtain better results of separating, fitting and extracting spectral feature lines and give more accurate intensity values of these spectral feature lines: The spectral feature lines of chromium in samples which contain different concentrations of chromium were separated and extracted. And then, the intensity values of corresponding spectral lines were given by using damped least squares method and least squares method separately. The calibration curves were plotted, which showed the relationship between spectral line intensity values and chromium concentrations in different samples. And then their respective linear correlations were compared. The experimental results showed that the linear correlation of the intensity values of spectral feature lines and the concentrations of chromium in different samples, which was obtained by damped least squares method, was better than that one obtained by least squares method. And therefore, damped least squares method was stable, reliable and suitable for separating, fitting and extracting spectral feature lines in laser induced breakdown spectroscopy.

[Analysis of lead in unknown samples based on the standard addition method using laser induced breakdown spectroscopy].

The standard addition method with laser induced breakdown spectroscopy was used to analyze an unknown sample taken from a lead battery factory. the matrix influence on the results was effectively avoided when the external or internal standard method was used, and the pretreatment of samples was simple and quick. The Nd ' YAG pulse laser with wavelength 1 064 nm was used as the excitation source. The echelle spectroscopy with high resolution and wide spectral range was used as the spectral separation device, and the intensified charge coupled device (ICCD) as the spectral detection device in the experiment. The characteristic line at 405. 78 nrn was chosen as the analysis line to measure Pb concentration. Fe I : 404. 58 line was chosen as the internal standard. Pre-experiment was carried out to confirm the appropriate condition. Under the laser energy of 128. 5 mJ, the delay time of 2. 5 tps, and the gate width of 3 ps, it was determined that with the addition of Pb to the sample in the range of 0 and 25 000 mg . kg-1, there wasn't self-absorption. There was a good linear relationship between the intensity of the spectral line of 405. 78 nm and the addition of Pb. The appropriate concentration of Pb added into the sample for analysis was determined by this series of samples. On this basis, four samples were prepared with three parallel samples for each sample in order to verify the repeatability and reliability of the method, i. e. 5 000, 10 000, 15 000, 20 000 mg . kg-1 Pb was added into the original sample. The results were compared with the result of ICP-MS. The twelve samples' relative errors were between -24. 6% and 17. 6%. The average result was 43 069 mg . kg-1 with the relative error -2. 44%.

[Quantitative Analysis of Heavy Metals in Water with LIBS Based on Signal-to-Background Ratio].

There are many influence factors in the precision and accuracy of the quantitative analysis with LIBS technology. According to approximately the same characteristics trend of background spectrum and characteristic spectrum along with the change of temperature through in-depth analysis, signal-to-background ratio (S/B) measurement and regression analysis could compensate the spectral line intensity changes caused by system parameters such as laser power, spectral efficiency of receiving. Because the measurement dates were limited and nonlinear, we used support vector machine (SVM) for regression algorithm. The experimental results showed that the method could improve the stability and the accuracy of quantitative analysis of LIBS, and the relative standard deviation and average relative error of test set respectively were 4.7% and 9.5%. Data fitting method based on signal-to-background ratio(S/B) is Less susceptible to matrix elements and background spectrum etc, and provides data processing reference for real-time online LIBS quantitative analysis technology.

[Analysis of heavy metals distribution characteristics and pollution assessment in agricultural region soils of Huaihe basin].

By means of field sampling and laboratory analysis, the content distribution characteristics of Cd, Cr, Cu, Ni, Pb and Zn in agricultural region soils of Huaihe basin in Anhui province were analyzed. Assessment of heavy metal pollutions was conducted using enrichment factor, geoaccumulation index and potential ecological risk index. The results showed that the average mass fraction of Cd and Cu was 0.113 5 and 22.09 mg x kg(-1) respectively in the study area soil, which were above the background values 0.097 and 20.4 mg x kg(-1) in Anhui Province. The average mass fraction of other four heavy metals did not exceed the average values of Anhui Province. The results of the evaluations from geoaccumulation index and ecological risk assessment discovered that Cd is the strongest pollution metal among six heavy metals in the study area soil. For some samples of the study soil, Cd was slight risk for the ecosystem. The ecosystem risks caused by the other five heavy metals were not obviously for the sampling points. The entire study area soils were mid integrated potential ecological risk.

[Research on parameter optimization of LIBS used for multi-element measurements in water].

The one of the advantages about Laser Induced Breakdown Spectroscopy (LIBS) is multielement detection at the same time. In order to obtain the optimum signal in the multi-element measurements of water with LIBS, the present paper firstly models the numerical relationship between the signal-to-background ratio of characteristic spectral lines and the delay time and gate width time with BP neural network, using DM design experiment data as the checking sample to ensure the generalization ability of the BP neural network model. Based on the above model, genetic algorithm is used to optimize measurement parameters and the fitness function phi is defined. When the optimum delay time and gate width time is (15.5 micros, 21.5 micros), the minimum value of psi is 0.102 4. The optimization results of genetic algorithm are further confirmed with experimental results. So the method of parameters optimization overall improves S/B of multi-element measurements in water with LBS, and provides the reference for parameter optimization of other experiments.