Resonate frequency and cell constant of photoacoustic spectrum system are usually calibrated by using standard gas in laboratory, whereas the resonate frequency and cell constant will be changed in-situ, leading to measurement accuracy errors, caused by uncertainties of standard gas, differences between standard and measured gas components and changes in environmental condition, such as temperature and humidity. As to overcome the above problems, we have proposed an on-line atmospheric oxygen-based calibration technology for photoacoustic spectrum system and used in measurement of concentration of carbon dioxide in atmosphere. As the concentration of atmospheric oxygen is kept as constant as 20.96%, the on-line calibration for the photoacoustic spectrum system can be realized by detecting the swept-frequency and peak signal at 763.73 nm. The cell of the PAS has a cavity with length of 100 mm and an inner diameter of 6 mm, and worked in a first longitudinal resonant mode. The influence of environmental temperature and humidity, gas components on the photoacoustic cell’s performance has been theoretically analyzed, and meanwhile the resonant frequencies and cell constants were calibrated and acquired respectively using standard gas, indoor air and outdoor air. Compared with calibrated gas analyzer, concentration of carbon dioxide is more accurate by using the resonant frequency and cell constant calculated by oxygen in tested air, of which the relative error is less than 1%, much smaller than that calculated by the standard gas in laboratory. The innovation of this paper is that using atmospheric oxygen as photoacoustic spectrum system’s calibration gas effectively reduces the error caused by using standard gas and environmental condition changes, and thus improves the on-line measuring accuracy and reliability of the photoacoustic spectrum system.

All-trans-β-carotene has important functions of light collection and light protection, and it is also an important electro-optical material. The Raman spectra of polyenes are a result of the modulation effect of the π electron energy gap on the vibration of CC bonds, which associate with the external field. So it has higher theoretical significance and practical value to study the molecular structure and properties change under the external field. Ultraviolet-visible absorption spectra and resonant Raman spectra of all-trans-β-carotene in cyclohexanol were measured from 341 to 275 K. The liquid-solid phase transition of the sample appears at 295 K. The characteristic energy describes the conformational change of all-trans-β-carotene molecule. After the solution phase transition, the characteristic energy ε of all-trans-β-carotene molecule becomes bigger. And when temperature decreasing, the rate of change of the Huang-Rhys, the wavelength of UV absorption peak, electron-phonon Parameter, RSCSs of the CC bond increase. the Huang-Rhys in solid phase is an order of magnitude higher then liquid phase. The characteristic energy of liquid is 0.206 7 eV. The characteristic energy of liquid is 0.559 6 eV. The increasing of the characteristic energy ε makes the rate of increasing of the effectively conjugated length becomes bigger. The decreasing of the π electric energy gap quickens. The function of moderation from electron energy gap to all-trans-β-carotene molecule enhances. Electron-phonon Parameter increases. RSCSs of the CC bond substantially increases.

By using three monochromator!detecting systems, the light emissions of excited-state OH*, CH* and C*2 radicals during the transient combustion of methylcyclohexane at high temperatures behind the reflected shock wave have been measured. The dependence of the time-history and the relative intensity of excited radicals on the temperature have been obtained. The reflected shock temperatures are 1 200～1 700 K, the shock pressure is 1.5 atm, the mole fraction of methylcyclohexane is 0.1% and the equivalence ratio is 1.0. At the beginning of the combustion process, these three radicals were produced at the same time. The durations of these radicals became shorter when the temperature increases. At the same ignition temperature, the durations of CH* and OH* are longer than that of C*2. The C*2 signal disappears below 1 400 K. The emission intensities of OH* and CH* are not sensitive to the temperature at T1 400 K), the peak intensity of CH* increases rapidly as temperature increases, while C*2 and OH* increase slowly. Current results were compared to the simulation results of corresponding chemical reaction mechanism. The obtained time-history of OH* radical matches well with the prediction of mechanism at low temperatures, but shows difference at high temperatures. The time-history of CH* radical matches well between experimental and simulated results at high temperatures, however, the simulated durations of CH* are longer than the experimental results at low temperatures. Current work provides experimental data to validate and optimize corresponding chemical reaction mechanism containing excited-state species.

The shielding gas plays an important role in the laser welding process and the variation of the protecting conditions has an obvious effect on the welding quality. This paper studied the influence of the change of protecting conditions on the parameters of laser-induced plasma such as electron temperature and electron density during the laser welding process by designing some experiments of reducing the shielding gas flow rate step by step and simulating the adverse conditions possibly occurring in the actual Nd∶YAG laser welding process. The laser-induced plasma was detected by a fiber spectrometer to get the spectral data. So the electron temperature of laser-induced plasma was calculated by using the method of relative spectral intensity and the electron density by the Stark Broadening. The results indicated that the variation of protecting conditions had an important effect on the electron temperature and the electron density in the laser welding. When the protecting conditions were changed, the average electron temperature and the average electron density of the laser-induced plasma would change, so did their fluctuation range. When the weld was in a good protecting condition, the electron temperature, the electron density and their fluctuation were all low. Otherwise, the values would be high. These characteristics would have contribution to monitoring the process of laser welding.

A methane (CH4) detection system based on tunable diode laser absorption spectroscopy (TDLAS) technique was experimentally demonstrated. A distributed feedback (DFB) laser around 1 654 nm, an open reflective sensing probe and two InGaAs photodiodes were adopted in the system. The electrical part of the system mainly includes the laser temperature control & modulation module and the orthogonal lock-in amplifier module. Temperature and spectrum tests on the DFB laser indicate that, the laser temperature fluctuation can be limited to the range of -0.02~0.02 ℃, the laser’s emitting wavelength varies linearly with the temperature and injection current, and also good operation stability of the laser was observed through experiments. Under a constant working temperature, the center wavelength of the laser is varied linearly by adjusting the driving current. Meanwhile, a 5 kHz sine wave signal and a 10 Hz saw wave signal were provided by the driving circuit for the harmonic extraction purpose. The developed orthogonal lock-in amplifier can extract the 1f and 2f harmonic signals with the extraction error of 3.5% and 5% respectively. By using the open optical probe, the effective optical pass length was doubled to 40 cm. Gas detection experiment was performed to derive the relation between the harmonic amplitude and the gas concentration. As the concentration increases from 1% to 5%, the amplitudes of the 1f harmonic and the 2f harmonic signal were obtained, and good linear ration between the concentration and the amplitude ratio was observed, which proves the normal function of the developed detection system. This system is capable to detect other trace gases by using relevant DFB lasers.

The ZnO films were deposited by atomic layer deposition method using water and diethylzinc as precursors at different temperatures (110 and 190 ℃). X-ray photoelectron spectroscopy, spectroscopic ellipsometry and photoluminescence spectra (PL) were used to investigate the elemental composition and optical properties of ZnO films. Our results showed that with the increasing of the growth temperature, the amount of —OH groups in the ZnO film decreased, which indicated that the reactions went to completion at high processing temperatures. The PL spectra of the ZnO film deposited at 110 ℃ exhibited two emission bands, one in the UV region and the other in the visible region. When the deposition temperature increased to 190 ℃, the emission bands in the visible region disappeared, which indicated that the deep level defect in ZnO became less. The carrier mobility improved from 25 to 32 cm2·(V·S)-1 with the reduction of the defects in the ZnO film. The refractive index of the ZnO films decreased from 2.33 to 1.9 in the 375～800 nm region. The optical absorption edge (Eg) values of the ZnO films deposited at different temperature were about 3.27 eV.

Particulate backscattering coefficient is a main inherent optical properties (IOPs) of water, which is also a determining factor of ocean color and a basic parameter for inversion of satellite ocean color remote sensing. In-situ measurement with optical instruments is currently the main method for obtaining the particulate backscattering coefficient of water. Due to reflection and refraction by the mirrors in the instrument optical path, the emergent light source from the instrument may be partly polarized, thus to impact the measurement accuracy of water backscattering coefficient. At present, the light polarization of measuring instruments and its impact on the measurement accuracy of particulate backscattering coefficient are still poorly known. For this reason, taking a widely used backscattering coefficient measuring instrument HydroScat6 (HS-6) as an example in this paper, the polarization characteristic of the emergent light from the instrument was systematically measured, and further experimental study on the impact of the light polarization on the measurement accuracy of the particulate backscattering coefficient of water was carried out. The results show that the degree of polarization(DOP) of the central wavelength of emergent light ranges from 20% to 30% for all of the six channels of the HS-6, except the 590 nm channel from which the DOP of the emergent light is slightly low (~15%). Therefore, the emergent light from the HS-6 has significant polarization. Light polarization has non-neglectable impact on the measurement of particulate backscattering coefficient, and the impact degree varies with the wave band, linear polarization angle and suspended particulate matter(SPM) concentration. At different SPM concentrations, the mean difference caused by light polarization can reach 15.49%, 11.27%, 12.79%, 14.43%, 13.76%, and 12.46% in six bands, 420, 442, 470, 510, 590, and 670 nm, respectively. Consequently, the impact of light polarization on the measurement of particulate backscattering coefficient with an optical instrument should be taken into account, and the DOP of the emergent light should be reduced as much as possible.

A new method for temperature measurement is established based on the gray-body radiation, which can not only determine the real-time temperature of thermal source, but also conduct non-contacted temperature measurement with high precision. First, a wide-band emission spectrum of the given radiation source is measured precisely with a multi-channel CCD image spectrometer, which is served as its spectral fingerprints for establishing a gray-body radiation model; Secondly, the coefficients introduced in the gray-body radiation model are determined by fitting the measured emission spectrum; Finally, a combination of spectroscopic technique and the gray-body radiation model is employed to measure any temperature of the given radiation source. Having tested on both types of radiation sources, with and without a flame, the present work has demonstrated that the imaged spectral approach mentioned above can be utilized as a real-time, high precision and non-contacted technique for temperature measurement.

Under the conditions of the polarized light, The reflective surface of the object is affected by many factors, refractive index, surface roughness, and so the angle of incidence. For the rough surface in the different wavelengths of light exhibit different reflection characteristics of polarization, a spectral polarimetric BRDF based on Kirchhof theory is proposee. The spectral model of complex refraction index is combined with refraction index and extinction coefficient spectral model which were got by using the known complex refraction index at different value. Then get the spectral model of surface roughness derived from the classical surface roughness measuring method combined with the Fresnel reflection function. Take the spectral model of refraction index and roughness into the BRDF model, then the spectral polarimetirc BRDF model is proposed. Compare the simulation results of the refractive index varies with wavelength, roughness is constant, the refraction index and roughness both vary with wavelength and origin model with other papers, it shows that, the spectral polarimetric BRDF model can show the polarization characteristics of the surface accurately, and can provide a reliable basis for the application of polarization remote sensing, and other aspects of the classification of substances.

Achiral molecules with conjugated structures can form chiral supramolecules through interfacial self-assembly. These spontaneous symmetry breaking processes may help elucidate the origin of life and are thus of great importance. So far, the mechanism of interfaciam self-assembly has been discussed in detail. However, dynamics of the chiral assemblies was rarely investigated. In order to clarify whether the chiral structures are stable or dynamic, we employed second harmonic generation linear dichroism (SHG-LD) to investigate the supramolecular chirality of PARC18 at air/aqueous interface. It was shown that PARC18 formed chiral structures with stable chiral state at air/water interface. While at air/NaOH solution interface, the chiral state changed with time. In addition, on NaOH solution subphase, contributions of magnetic dipole to second harmonic signals were dominant. We suggest that this is due to isomerization of PARC18 molecules on NaOH solution subphase. As a result, the two chromophores coupled with each other and the magnetic dipole contribution was enhanced.

In order to achieve the rapid monitoring of process state of solid state fermentation (SSF), this study attempted to qualitative identification of process state of SSF of feed protein by use of Fourier transform near infrared (FT-NIR) spectroscopy analysis technique. Even more specifically, the FT-NIR spectroscopy combined with Adaboost-SRDA-NN integrated learning algorithm as an ideal analysis tool was used to accurately and rapidly monitor chemical and physical changes in SSF of feed protein without the need for chemical analysis. Firstly, the raw spectra of all the 140 fermentation samples obtained were collected by use of Fourier transform near infrared spectrometer (Antaris Ⅱ), and the raw spectra obtained were preprocessed by use of standard normal variate transformation (SNV) spectral preprocessing algorithm. Thereafter, the characteristic information of the preprocessed spectra was extracted by use of spectral regression discriminant analysis (SRDA). Finally, nearest neighbors (NN) algorithm as a basic classifier was selected and building state recognition model to identify different fermentation samples in the validation set. Experimental results showed as follows: the SRDA-NN model revealed its superior performance by compared with other two different NN models, which were developed by use of the feature information form principal component analysis (PCA) and linear discriminant analysis (LDA), and the correct recognition rate of SRDA-NN model achieved 94.28% in the validation set. In this work, in order to further improve the recognition accuracy of the final model, Adaboost-SRDA-NN ensemble learning algorithm was proposed by integrated the Adaboost and SRDA-NN methods, and the presented algorithm was used to construct the online monitoring model of process state of SSF of feed protein. Experimental results showed as follows: the prediction performance of SRDA-NN model has been further enhanced by use of Adaboost lifting algorithm, and the correct recognition rate of the Adaboost-SRDA-NN model achieved 100% in the validation set. The overall results demonstrate that SRDA algorithm can effectively achieve the spectral feature information extraction to the spectral dimension reduction in model calibration process of qualitative analysis of NIR spectroscopy. In addition, the Adaboost lifting algorithm can improve the classification accuracy of the final model. The results obtained in this work can provide research foundation for developing online monitoring instruments for the monitoring of SSF process.

The biomass to plastic ratio in wood plastic composites (WPCs) greatly affects the physical and mechanical properties and price. Fast and accurate evaluation of the biomass to plastic ratio is important for the further development of WPCs. Quantitative analysis of the WPC main composition currently relies primarily on thermo-analytical methods. However, these methods have some inherent disadvantages, including time-consuming, high analytical errors and sophisticated, which severely limits the applications of these techniques. Therefore, in this study, Fourier Transform Infrared (FTIR) spectroscopy in combination with partial least square (PLS) has been used for rapid prediction of bamboo and polypropylene (PP) content in bamboo/PP composites. The bamboo powders were used as filler after being dried at 105 ℃ for 24 h. PP was used as matrix materials, and some chemical regents were used as additives. Then 42 WPC samples with different ratios of bamboo and PP were prepared by the methods of extrusion. FTIR spectral data of 42 WPC samples were collected by means of KBr pellets technique. The model for bamboo and PP content prediction was developed by PLS-2 and full cross validation. Results of internal cross validation showed that the first derivative spectra in the range of 1 800～800 cm-1 corrected by standard normal variate (SNV) yielded the optimal model. For both bamboo and PP calibration, the coefficients of determination (R2) were 0.955. The standard errors of calibration (SEC) were 1.872 for bamboo content and 1.848 for PP content, respectively. For both bamboo and PP validation, the R2 values were 0.950. The standard errors of cross validation (SECV) were 1.927 for bamboo content and 1.950 for PP content, respectively. And the ratios of performance to deviation (RPD) were 4.45 for both biomass and PP examinations. The results of external validation showed that the relative prediction deviations for both biomass and PP contents were lower than ±6%. FTIR combined with PLS can be used for rapid and accurate determination of bamboo and PP content in bamboo/PP composites.

Infrared spectroscopy is an important source of information for the identification of the compounds structure and it is great significant for biological activity research of natural and organic drug molecules. With the theoretical calculation method is more reasonable and calculation accuracy continues to improve, Theoretical calculate advantage is more obvious in the infrared spectrum simulation and vibration modes attributable identified. And it has important reference value for experimental study of infrared spectral analysis. Using density functional theory, geometry optimizations and frequencies calculation of 7-Hydroxycoumarin were performed at the level of B3LYP/6-311G(d,p), the stable structure and all vibration modes of 7-Hydroxycoumarin were attained. The results show that the infrared absorption peak of 7-hydroxycoumarin is mainly distributed in the several regions in wave number of 3 700～3 500, 3 150～3 000, 1 750～1 400, 1 400～1 000, 1 000～50 cm-1. In addition to the vibration in a wave number range of 3 700～3 500, 3 150～3 000 cm-1 is relatively independent, and were attributed to OH stretching vibration and benzene ring CH stretching vibration, the other several vibration regions are more complex, the different degree of spectral peaks is composed of multiple vibration modes. Finally, based on the theoretical analysis of the vibration mode, the vibration modes of 7-Hydroxycoumarin molecule were assigned, and in order to discuss the reliability of theoretical calculation method, the correlation diagram of the main absorption peak of 7-hydroxyl group was drawn from the theoretical value of X axis and the experimental value of Y axis, the correlation between experimental IR data and calculated IR data of 7-Hydroxycoumarin was analyzed through the linear regression method. Results show that they have good correlation, correlation coefficient values “r” equals 0.998 5, and the theory calculation of 7-Hydroxycoumarin IR by density functional theory at the base set level is reliable.

Biomass energy is being industrialized rapidly in China in recent years, whereas, research on energy grass is still in primary stage. Only if near-infrared spectroscopy mode was constructed which was used to predict the lignin, cellulose and hemicellulose contents in energy crop, the varieties screening, performance evaluation and on-line control of industrialization would be facilitated. In this study, the prediction model for quality indices (cellulose, hemicellulose, lignin and ash) of four energy grass (Miscanthus) was built using Fourier transform near-infrared (FT-NIR) spectroscopy combined with partial least squares regression (PLSR) , and the impacts exerted by particle size on the model were also revealed. The results showed that (1) the root mean error of cross validation (RMSECV) of cellulose, hemicelluloses and lignin contents were 1.35% (R2=0.88), 0.39% (R2=0.91) and 0.35 (R2=0.80), respectively in stalk and 0.72% (R2=0.88), 0.85% (R2=0.85) and 0.44 (R2=0.87), respectively in leaf. The model showed good performance in prediction of corresponding contents in unknown samples, however, no satisfying performance in ash content. (2) Both 2 mm and 0.5 mm grades of particle size can meet accuracy requirements of the model. But considering the time and labor cost, 2 mm grade was suggested for model building.

A new method using reflection NIR technology was developed to determine the alcoholysis degree and volatile matter of Poly-vinyl alcohol (PVA). 120 samples were used in this research. NIR spectra of the sample were scanned by the spectrometer from 1 000 to 1 800 nm. The alcoholysis degree and volatile matter were determined by the national standard method of volumetric and gravimetric method respectivily. Partial least squares (PLS1) was used to establish the quantitative correction model of alcoholysis degree and volatile matter of PVA. The corrected relationship(RC) of alcoholysis degree and volatile matter was 0.976 and 0.981 respectively. The corrected standard deviation(SEC) was 0.176 and 0.197. The predicted relationship(RP) was 0.967 and 0.969. The predicted deviation(SEP) was 0.202 and 0.193. The test for actual samples showed that the NIR method was fitted for the requirement of PVA analysis.

At present, the identification and classification of the microalgae and its biochemical analysis have become one of the hot spots on marine biology research. Four microalgae species, including Chlorella vulgaris, Chlorella pyrenoidosa, Nannochloropsis oculata, Chlamydomonas reinhardtii, were chosen as the experimental materials. Using an established spectral acquisition system,which consists of a portable USB 4000 spectrometer having transmitting and receiving fiber bundles connected by a fiber optic probe, a halogen light source, and a computer, the Vis/NIR transmission spectral data of 120 different samples of the microalgae with different concentration gradients were collected, and the spectral curves of fourmicroalgae species were pre-processed by different pre-treatment methods (baseline filtering, convolution smoothing, etc.). Based on the pre-treated effects, SPA was applied to select effective wavelengths (EWs), and the selected EWs were introduced as inputs to develop and compare PLS, Least Square Support Vector Machines (LS-SVM), Extreme Learning Machine (ELM)models, so as to explore the feasibility of using Vis/NIR transmission spectroscopy technology for the rapid identification of four microalgae species in situ. The results showed that: the effect of Savitzky-Golay smoothing was much better than the other pre-treatment methods. Six EWs selected in the spectraby SPA were possibly relevant to the content of carotenoids, chlorophyll in the microalgae. Moreover, the SPA-PLS model obtained better performance than the Full-Spectral-PLS model. The average prediction accuracy of three methods including SPA-LV-SVM, SPA-ELM, and SPA-PLS were 80%, 85% and 65%. The established method in this study may identify four microalgae species effectively, which provides a new way for the identification and classification of the microalgae species. The methodology using Vis/NIR spectroscopy with a portable optic probe would be applicable to a diverse range of microalgae species and proves to be a rapid, real-time, non-destructive, precise method for the physiological and biochemical detection for microalgae.

The inspection and classification for blood products are important but complicated in import-export ports or inspection and quarantine departments. For the inspection of whole blood products, open sampling can cause pollution and virulence factors in bloods samples may even endanger inspectors. Thus non-contact classification and identification methods for whole bloods of animals are needed. Spectroscopic techniques adopted in the flowcytometry need sampling blood cells during the detection; therefore they can not meet the demand of non-contact identification and classification for whole bloods of animals. Infrared absorption spectroscopy is a technique that can be used to analyze the molecular structure and chemical bonds of detected samples under the condition of non-contact. To find a feasible spectroscopic approach of non-contact detection for the species variation in whole blood samples, a near infrared transmitted spectra (NITS, 4 497.669～7 506.4 cm-1) experiment of whole blood samples of three common animals including chickens, dogs and cats has been conducted. During the experiment, the spectroscopic resolution is 5 cm-1, and each spectrogram is an average of 5 measured spectral data. Experimental results show that all samples have a sharp absorption peak between 5 184 and 5 215 cm-1, and a gentle absorption peak near 7 000 cm-1. Besides, the NITS curves of different samples of same animals are similar, and only have slight differences in the whole transmittance. A correlation coefficient (CC) is induced to distinguish the differences of the three animals’ whole bloods in NITS curves, and the computed CCs between NITS curves of different samples of the same animals, are greater than 0.99, whereas CCs between NITS curves of the whole bloods of different animals are from 0.509 48 to 0.916 13. Among which CCs between NITS curves of the whole bloods of chickens and cats are from 0.857 23 to 0.912 44, CCs between NITS curves of the whole bloods of chickens and dogs are from 0.509 48 to 0.664 82, and CCs between NITS curves of the whole bloods of cats and dogs are from 0.872 75 to 0.916 13. The cat and the dog belong to the class of mammal, and the CCs between their whole bloods NITS curves are greater than those between chickens and cats, or chickens and dogs, which are hetero-class animals. Namely, the whole bloods NITS curves of the cat and the dog have higher similarity. These results of NITS provide a feasible method of non-contact identification of animal whole bloods.

In order to improve the technical level of the rapid detection of liquor fermented grains, in this paper, use near infrared spectroscopy technology to quantitative analysis moisture, starch, acidity and alcohol of liquor fermented grains. Using CARS, iPLS and no information variable elimination method (UVE), realize the characteristics of spectral band selection. And use the multiple scattering correction (MSC), derivative and standard normal variable transformation (SNV) pretreatment method to optimize the models. Establish models of quantitative analysis of fermented grains by PLS, and in order to select the best modeling method, using R2, RMSEP and optimal number of main factors to evaluate models. The results showed that the band selection is vital to optimize the model and CARS is the best optimization of the most significant effect. The calculation results showed that R2 of moisture, starch, acidity and alcohol were 0.885, 0.915, 0.951, 0.885 respectively and RMSEP of moisture, starch, acidity and alcohol were 0.630, 0.519, 0.228, 0.234 respectively. After optimization, the model prediction effect is good, the models can satisfy the requirement of the rapid detection of liquor fermented grains, which has certain reference value in the practical.

Near infrared spectroscopy analysis as a reliable, rapid, little sample preparation requirement, low-cost, convenient, nondestructive and green technique becomes more and more important in the area of soil nutrition measurement. Near infrared spectroscopy are highly sensitive to C—H, O—H and N—H bonds of soil components such as total nitrogen (TN) making their use in the agricultural and environmental sciences particularly appropriate. The analytical abilities of near infrared spectroscopy depend on the repetitive and broad absorption of light by C—H, O—H and N—H bonds. A total of 243 soil samples were collected from wencheng, Zhejiang province. Raw spectra and wavelength-reduced spectra with 3 different pretreatment methods (Savitzky-Golay smoothing (SG), Reduce (RD), and Wavelet Transform (WT)) were compared to determine the optimal wavelength range and pretreatment method for analysis. Spectral variable selection is an important strategy in spectrum modeling analysis, because it tends to parsimonious data representation and can lead to multivariate models with better performance. In order to simply calibration models, the preprocessed spectra were then used to select sensitive wavelengths by competitive adaptive reweighted sampling (CARS), Random frog and Successive Projections Algorithm (SPA) methods. Different numbers of sensitive wavelengths were selected by different variable selection methods with Wavelet Transform (WT) preprocessing method. Partial least squares (PLS) was used to build models with the full spectra, and Extreme Learning Machine (ELM) and LS-SVM were applied to build models with the selected wavelength variables. The overall results showed that PLS and LS-SVM models performed better than ELM models, and the LS-SVM models with the selected wavelengths based on SPA obtained the best results with the determination coefficient (R2), RMSEP and RPD were 0.63, 0.007 9 and 1.58 for prediction set. The results indicated that it was feasible to use portable short wave near-infrared spectral technology to predict soil total nitrogen and wavelengths selection could be very useful to reduce redundancy of spectra.

Raman spectroscopy has been widely used for gas detection due to the advantages of simultaneous multiple species recognition, rapid analysis, and no sample preparation, etc. Low sensitivity is still a great limitation for Raman application. In this work a Raman system based on a hollow core optical fiber (HCOF) was built and the detection sensitivity for the gas was significantly improved. Also a comparison was carried out between the HCOF Raman system and back-scattering Raman system. The obtained results indicated that the HCOF Raman system could well enhance the signal while also for the background and noise. Using HCOF system, 60 folds signal enhancement was achieved with SNR improvement of 6 times for the N2 and O2 in air when comparing to the back-scattering system. While for the same signal intensity, with HCOF system the exposure time was well shortened to 1/60 and the noise was decreased to 1/2 than the back-scattering system.

A series of ultra-uniform gold spherical nanoparticles with different sizes were synthesized using gold chloride acid as precursor, ascorbic acid as reductant and sodium citrate hydrate as surfactant. The prepared Au nanoparticles were characterized by scanning electron microscope (SEM) and UV-visible spectroscopy. The results showed that the absorption peak of UV-Vis spectroscopy red-shifted along with size increasing of the nanoparticles and finally appeared a quadrupole peak. To further explore the mechanism of surface enhanced Raman spectroscopy (SERS) effect and optimize the sensitivity, SERS on Au nanoparticles with different sizes were measured using Rhodamine 6G (R6G) as probe molecule. We found the SERS signals of R6G on the Au nanoaprtciles were highly size dependent. When the particles sizes are close to ～120 nm, it will generate the highest enhancement, the enhancement factor is about 1.1×107. The 3D-FDTD simulation results correlated with the experimental data very well.

CH4/C2H6/N2 mixed hydrate formation experiments were performed at 2 ℃ and 5 MPa for three different mine gas concentrations (CH4/C2H6/N2, G1=54∶36∶10, G2=67.5∶22.5∶10, G3=81∶9∶10). Raman spectra for hydration products were obtained by using Microscopic Raman Spectrometer. Hydrate structure is determined by the Raman shift of symmetric C—C stretching vibration mode of C2H6 in the hydrate phase. This work is focused on the cage occupancies and hydration numbers, calculated by the fitting methods of Raman peaks. The results show that structure Ⅰ (sⅠ) hydrate forms in the G1 and G2 gas systems, while structure Ⅱ (sⅡ) hydrate forms in the G3 gas system, concentration variation of C2H6 in the gas samples leads to a change in hydrate structure from sⅠ to sⅡ; the percentages of CH4 and C2H6 in sⅠ hydrate phase are less affected by the concentration of gas samples, the percentages of CH4 are respectively 34.4% and 35.7%, C2H6 are respectively 64.6% and 63.9% for gas systems of G1 and G2, the percentages of CH4 and C2H6 are respectively 73.5% and 22.8% for gas systems of G3, the proportions of object molecules largely depend on the hydrate structure; CH4 and C2H6 molecules occupy 98%, 98% and 92% of the large cages and CH4 molecules occupy 80%, 60% and 84% of the small cages for gas systems of G1, G2 and G3, respectively; additionally, N2 molecules occupy less than 5% of the small cages is due to its weak adsorption ability and the lower partial pressure.

Aiming at the shortage of the Raman spectra of drugs and the current situation of drug testing, we have applied Raman spectroscopic technique to several kinds of medicine, such as antibiotics, antihistamine, hemocoagulase and antiemetics. The spectral properties for the samples with high Raman activity are investigated by observing their Raman spectra to yield the shift, intensity, and line width of the Raman peaks, as well as the line shape of Raman envelope. For those samples with weak Raman activity or complex structures that are hard to be identified, we have also made some tentative measurements or raise some suggestions for future measurement. Comparing the similarities or differences among many Raman spectra of drugs, it is evident that drugs with small molecule have apparent spectral characteristics, by which to recognize them is very feasible, while those with large molecule usually have weak peaks or complex envelope in their spectra, leading to a difficult recognition and uncertain peak positions. This work not only proposes to identify chemical ingredients of drugs by observing and analyzing their Raman spectra, but also provides experimental evidences for medical workers doing so. The present results lay the foundation for establish the database of Raman spectra for drugs, and point out the prospect for rapid identification and detection of drugs, promoting the application of Raman spectroscopy technology on drug detection to a certain extent.

Raman spectrometry was employed to study the characteristics of Raman spectra of polyethylene terephthalate (PET), which were treated with sodium hydroxide, sulfuric acid and copper sulfate, respectively. Raman spectra under different conditions were obtained and the characteristics of the Raman spectra were analyzed. The morphology structures were observed under different conditions using Atomic Force Microscope. The results show that the spectral intensity of PET treated with sodium hydroxide is higher than that untreated between 200～1 750 cm-1, while the intensity of PET treated with sodium hydroxide is lower than that untreated beyond 1 750 cm-1 and the fluorescence background of Raman spectra is decreased. The spectral intensity of PET treated with sulfuric acid is remarkably reduced than that untreated, and the intensity of PET treated with copper sulphate is much higher than that untreated. The research results obtained by Atomic Force Microscopy show that the variations of the Raman spectra of PET fibers are closely related to the chemical bonds and molecular structures of PET fibers. The surface of the PET treated with sodium hydroxide is rougher than that untreated, the surface roughness of the PET treated with sulfuric acid is reduced as compared to that untreated, while the surface roughness of the PET treated with copper sulphate is increased. The results obtained by Raman spectroscopy are consistent with those by Atomic Force Microscopy, indicating that the combination of Raman spectroscopy and Atomic Force Microscopy is expected to be a promising characterization technology for polymer characteristics.

Chitin is an important structural polysaccharide of fungal cell wall. In this paper, aerial hyphae of Colletotrichum camelliae Massee was first studied by confocal Raman microscopy in vivo. Firstly, the optimal experimental parameters of hyphae for collecting the Raman spectra were determined, and the typical Raman spectra of hyphae, chitin standard and background were acquired. By comparing analysis, characteristic peaks of chitin were found in hyphae. Then, a region of interesting on hyphae was selected for Raman scanning. Through principal component analysis, the Raman signal of hyphae and background in the scanning area can be separated clearly. Combined with loading weight plot, two main characteristic peaks of hyphae were obtained, 1 622 cm-1was belong to chitin and 1 368 cm-1 was assigned to pectic polysaccharide. Finally, two and three dimension chemical images of fungal hyphae were realized based on Raman fingerprint spectra of chitin in a nondestructive way.

Different breeds of cows affect the form of fat exist in dairy products and the final functionality, which depended mainly on the composition of the milk fat globules(MFG). However, the relationship between the composition and breeds has not been illuminated. In our study, differences in the lipid content and fatty acid composition of native bovine, buffalo and yak MFG were investigated by confocal Raman spectroscopy. The research offers the possibility of acquisition and analysis of the Raman signal without disruption of the structure of fat globule. The results showed that yak MFG had a higher ratio of band intensities at 2 885/2 850 cm-1, indicating yak MFG tend to have a triglyceride core in a fluid state with a milk fat globule membrane in a crystalline state. The buffalo and yak MFG had a higher level of unsaturation compared to bovine MFG, shown by a higher ratio of band intensities at 1 655/1 744 cm-1. The results indicate that small MFG of buffalo is more unsaturated than yak, while the large MFG of buffalo is less unsaturated than the yak. Thus, selective use of cream with yak MFG would allow a harder and more costly churning process but lead to a softer butter. Buffalo milk which contains larger MFG is more suitable for cream and MFG membrane separation.

Strontium borate doping with different lanthanide bivalent ions and concentration (SrB4O7∶Re2+) were synthesized by the high-temperature solid state method. The fluorescent spectral characteristics of SrB4O7∶Re2+ were investigated by the non-polarization con-foucus fluorescence/raman measurement system built by us. The results indicate that the fluorescent spectral characteristics of SrB4O7∶Re2+ is very similar to that of SrB4O7∶Sm2+. The most strong fluorescence line (0-0 line) arises from 5D0-7F0 electron transition and the wavelength is 685.41 nm. In addition, two fluorescent bands coming from 5D0-7F1 and 5D0-7F2 electron transition are observed near 700 and 730 nm, respectively. The intensity of 0-0 line of SrB4O7∶Re2+ is at least a magnitude smaller than that of SrB4O7∶Sm2+. A further study on the fluorescent spectrums of SrB4O7∶Re2+ shows that the doping elements and concentration both are the key points that affect the intensity of the fluorescent peaks, which directly decide the amount of Re2+ concerned with irradiance.

As a kind of coenzyme of one-carbon enzymes in vivo, folic acid belongs to B vitamins, which can interact with other vitamins and has great significance for converting among amino acids, dividing growth of cells and protein synthesis reactions. Half-life, concentration and reaction rate constant of drugs are important parameters in pharmacokinetic study. In this paper, by utilizing fluorescence spectrophotometer and stopped-flow spectrum analyzer, reaction kinetic parameters between bovine serum albumin(BSA) and folic acid in a bionic system have been investigated, which provide references for parameters of drug metabolism related to folic acid. By using Stern-Volmer equation dealing with fluorescence quenching experiments data, we concluded that under 25, 30, and 37 ℃, the static quenching constants of folic acid to intrinsic fluorescence from bovine serum albumin were 2.455×1010, 4.900×1010 and 6.427×1010 L·mol-1·s-1 respectively; The results of kinetic reaction rate have shown that the reaction rate of BSA and folic acid are greater than 100 mol·L-1·s-1 at different temperatures, pH and buffering media, illustrating that the quenching mechanism between BSA and folic acid is to form composite static quenching process. Reaction concentration of bovine serum albumin and its initial concentration were equal to the secondary reaction formula, and the correlation coefficient was 0.998 7, while the half-life (t1/2) was 0.059 s at physiological temperature. With the increase of folic acid concentration, the apparent rate constant of this reaction had a linear increasing trend, the BSA fluorescence quenching rate constant catalyzed by folic acid was 3.174×105 mol·L-1·s-1. Furthermore, with different buffer, the apparent rate constant and reaction rate constant of BSA interacting with folic acid were detected to explore the influence on the reaction under physiological medium, which is of great significance to determine the clinical regimen, forecast the efficacy and toxicity of drugs and rational drug.

Based on traditional fluorescence spectroscopy and metal nanoparticles-enhanced fluorescence technology, this research explores a method of improving the accuracy and resolution of cholesterol detected by fluorescence spectroscopy in human whole blood solution. In experiment, an adult blood with silver nanoparticles is radiated by a laser pulse with wavelength of 407 nm, the fluorescence enhancement effect of cholesterol in blood is studied. The results show that, colloidal silver nanoparticles can enhance the fluorescence intensity of cholesterol in human blood with low concentration significantly. With the increase of the amount of silver colloids, the enhanced efficiency of fluorescence peaks at different positions increases first, and then decreases. However, the strongest enhanced efficiency of fluorescence peaks is different corresponding to different amount of silver colloids. According to the experimental results and the distribution of cholesterol molecules and silver nanoparticles in solution, molecular spatial distribution model is established by theoretical analyses, and the optimal distance for efficient fluorescence enhancement between cholesterol molecules and silver nanoparticles is calculated, the range is 12.19～25 nm, and the result is in good agreement with the theoretical values in other literatures. In summary, the fluorescence intensity of cholesterol in human blood can be enhanced by colloidal silver nanoparticles, and the results also provide a valuable reference on improving the sensitivity and accuracy of cholesterol detection.

Ca(1-x)Al2Si2O8∶Eux(x=0, 0.01, 0.05, 0.15) were synthesized by solid-state reaction respectively at 1 150, 1 250 1 350 and 1 450 ℃. With X-ray diffraction(XRD), Raman spectroscopy(Raman), photoluminescence spectroscopy(PL) and X-ray fluorescence spectrometer(XRF), the relationship between surface structure and fluorescence intensity of Ca(1-x)Al2Si2O8∶Eux were studied. XRD and Raman results show that, CaAl2Si2O8 anorthite single-phase has formed gradually along with the temperature rising in the process of synthesis.Raman spectroscopy is clear that when the Eu doping amount is the same, Si—O amorphous phase disappear gradually and the CaAl2Si2O8 phase form gradually with the temperature increases. As the temperature increases, vibration peaks position silicon oxygen tetrahedron shift to lower wave number. When 1 450 ℃, the temperature is too high to destroy the structure of silicon oxygen tetrahedron.At the same time, there is a broadening amorphous peak appears in Raman spectroscopy.The procedure of Al to replace Si is hindered with Eu doped in. It is the result that the peak at 1 620 cm-1 decreases after the first increases. The change of surface structure associated with the scattering amount of Eu. PL and XRF results show that: as the temperature increases, the amount of Eu atom scattering on the material surface increases gradually, this change lead to the fluorescence intensity raise. Therefore, there is proportional relationship between the fluorescence intensity of the samples and the number of samples per unit surface area of Eu atoms.

Due to the intrinsic fluorescence characteristic of tyrosine (Tyr) and phenylalanine (Phe), synchronization fluorescence spectrum technology which adopted the constant wavelength difference (Δλ=15 nm) was selected to investigate the effects of collagen-based surfactant (CBS) concentration, pH, NaCl concentration and temperature on the aggregation state of CBS molecules in aqueous solutions. Meanwhile, temperature-dependent two-dimensional (2D) synchronization fluorescence correlation analyses was used to investigate the variation order of Tyr and Phe residues in CBS molecules with the change of temperature. The results showed that the characteristic absorption peaks located at 261 and 282 nm were attributed to Phe and Tyr, respectively. With the increase of CBS concentration, the amount of Phe and Tyr residues increased gradually which resulted in the increase of aggregate degree of CBS molecules and then led to the increase of fluorescence intensity. When the pH value (pH 5.0) of CBS solutions was close to the isoelectric point of CBS, the aggregate degree of CBS molecules increased due to the increase of the hydrophobic interaction and the formation ability of hydrogen bond. Additionally, with the increase of NaCl concentration, the repulsion force for inter/intra-molecules of CBS decreased, which helped to improve the aggregation behavior of CBS molecules. However, with the increase of temperature, the aggregation state of CBS was changed to be monomolecular state, and then resulted in the decrease of the fluorescence intensity gradually due to the quenching, the denaturation and the decrease of hydrogen bond formation ability. Furthermore, temperature-dependent 2D synchronization fluorescence correlation spectroscopy demonstrated that at lower temperature (10～40 ℃), the aggregate state of CBS changed to be loose state and then Phe residues located in the inside of the aggregate varied before Tyr residues; while in the heating process of 45～70 ℃, the monomolecular state of CBS changed to be random coil conformation, the separation distance between Tyr residues increased and the hydrogen bond formation ability reduced strongly, which led to Tyr residues changed before Phe residues.

A disubstituted phthalimide-based thiacalix arene derivative (probe s1) was synthesized from cone 1,3-thiacalix arene and hydroxyethyl phthalimide, with benzyl appended the lower edge of thiacalix-arene by triazole ring in the 2,4 position. The relative fluorescence quantum yield of probe s1 is 0.43 in CH3CN solvent. The strong fluorescence emission of probe s1 at 390 nm wavelength can be selectively quenched by Fe3+ in DMF/H2O solution. Similarly, the presence of I- also induced a significant fluorescence quenching of probe s1 at 310 nm wavelength in CH3CN solution. Spectral titration and isothermal titration calorimetry were showed that probe s1 with Fe3+ or I- both form 1∶1 complexes, the binding constants up to 105 and coordinate process were spontaneous. The linear ranges of fluorescence detect Fe3+ or I- were 1.0×10-7～1.6×10-4 mol·L-1 and 1.0×10-7～8.5×10-5 mol·L-1, detection limits were up to 2.30×10-8 mol·L-1 and 1.17×10-8 mol·L-1, respectively. Meanwhile, take advantage of identification and coordination action, a logic circuit constructed at the molecular level by controlling two input signals of Fe3+ and F-, which causing probe s1 cycling of fluorescence emission or quenching. IR spectrum speculated that the nitrogen atoms of triazole groups are involved in the complexation with Fe3+, while the hydrogen atoms of triazole groups were complexed with I- by hydrogen bonding.

In order to clarify the interaction mechanism of the formation of the resveratrol-hordein nanoparticle, the fluorescence, UV-Vis spectroscopic, FTIR and DSCwere used to study the binding reaction between resveratrol and hordein. The fluorescent emission of hordein was inhibited by resveratrol in a dose dependent manner. Fluorescence spectroscopy and DSC indicated that resveratrol interacted with hordein and formed a new complex by a static process. The binding constant(KA(298 K)=2.21×105 L·mol-1, KA(310 K)=1.53×104 L·mol-1) and the number of binding sites(n298 K=1.23, n310 K=0.94)were calculated based on the quenching effect of resveratrol on hordein. Thermodynamic parameter and FTIR indicated that the interaction force between resveratrol and hordein was mainly hydrogen binding and van der Waals force. The binding distance(r0=3.25 nm)between resveratrol and hordein and the energy transfer efficiency (E=0.227) were obtained according to non-radiative energy transfer theory. The effect of resveratrol on the conformation of hordein was further analyzed by using synchronous fluorescence spectrometry. The results indicated that resveratrol changed the hydrophobicity of tryptophan residue, which caused an obvious influence on the conformation of hordein.

Spectral indices (SIs) method has been widely applied in the prediction of vegetation biochemical parameters. Take the diversity of spectral response of different sensors into consideration, this study aimed at researching spectral scale effect of SIs for estimating vegetation chlorophyll content (VCC). The 5 nm leaf reflectance data under 16 levels of chlorophyll content was got by the radiation transfer model PROSPECT and then simulated to multiple bandwidths spectrum (10～35 nm), using Gaussian spectral response function. Firstly, the correlation between SIs and VCC was studied. And then the sensitivity of SIs to VCC and bandwidth were analyzed and compared. Lastly, 112 samples were selected to verify the results above mentioned. The results show that Vegetation Index Based on Universal Pattern Decomposition Method (VIUPD) is the best spectral index due to its high sensitivity to VCC but low sensitivity to bandwidth, and can be successfully used to estimate VCC with coefficient of determination R2 of 0.99 and RMSE of 3.52 μg·cm-2. Followed by VIUPD, Normalized Difference Vegetation Index (NDVI) and Simple Ratio Index (SRI) presented a comparatively good performance for VCC estimation (R2>0.89) with their prediction value of chlorophyll content was lower than the true value. The worse accuracy of other indices were also tested. Results demonstrate that spectral scale effect must be well-considered when estimating chlorophyll content, using SIs method. VIUPD introduced in the present study has the best performance, which reaffirms its special feature of comparatively sensor-independent and illustrates its potential ability in the area of estimating vegetation biochemical parameters based on multiple satellite data.

Ultraviolet/visible (UV/Vis) spectroscopy technology was used to measure water COD. A total of 135 water samples were collected from Zhejiang province. Raw spectra with 3 different pretreatment methods (Multiplicative Scatter Correction (MSC), Standard Normal Variate (SNV) and 1 st Derivatives were compared to determine the optimal pretreatment method for analysis. Spectral variable selection is an important strategy in spectrum modeling analysis, because it tends to parsimonious data representation and can lead to multivariate models with better performance. In order to simply calibration models, the preprocessed spectra were then used to select sensitive wavelengths by competitive adaptive reweighted sampling (CARS), Random frog and Successive Genetic Algorithm (GA) methods. Different numbers of sensitive wavelengths were selected by different variable selection methods with SNV preprocessing method. Partial least squares (PLS) was used to build models with the full spectra, and Extreme Learning Machine (ELM) was applied to build models with the selected wavelength variables. The overall results showed that ELM model performed better than PLS model, and the ELM model with the selected wavelengths based on CARS obtained the best results with the determination coefficient (R2), RMSEP and RPD were 0.82, 14.48 and 2.34 for prediction set. The results indicated that it was feasible to use UV/Vis with characteristic wavelengths which were obtained by CARS variable selection method, combined with ELM calibration could apply for the rapid and accurate determination of COD in aquaculture water. Moreover, this study laid the foundation for further implementation of online analysis of aquaculture water and rapid determination of other water quality parameters.

The secondary geological disasters triggered by the Lushan earthquake on April 20, 2013, such as landslides, collapses, debris flows, etc., had caused great casualties and losses. We monitored the number and spatial distribution of the secondary geological disasters in the earthquake-hit area from airborne remote sensing images, which covered areas about 3 100 km2. The results showed that Lushan County, Baoxing County and Tianquan County were most severely affected; there were 164, 126 and 71 secondary geological disasters in these regions. Moreover, we analyzed the relationship between the distribution of the secondary geological disasters, geological structure and intensity. The results indicate that there were 4 high-hazard zones in the monitored area, one focused within six kilometers from the epicenter, and others are distributed along the two main fault zones of the Longmen Mountain. More than 97% secondary geological disasters occurred in zones with a seismic intensity of VII to IX degrees, a slope between 25 A degrees and 50 A degrees, and an altitude of between 800 and 2 000 m. At last, preliminary suggestions were proposed for the rehabilitation and reconstruction planning of Lushan earthquake. According to the analysis result, airborne and space borne remote sensing can be used accurately and effectively in almost real-time to monitor and assess secondary geological disasters, providing a scientific basis and decision making support for government emergency command and post-disaster reconstruction.

High precision retrieval of atmospheric CH4 is influenced by a variety of factors. The uncertainties of ground properties and atmospheric conditions are important factors, such as surface reflectance, temperature profile, humidity profile and pressure profile. Surface reflectance is affected by many factors so that it is difficult to get the precise value. The uncertainty of surface reflectance will cause large error to retrieval result. The uncertainties of temperature profile, humidity profile and pressure profile are also important sources of retrieval error and they will cause unavoidable systematic error. This error is hard to eliminate only using CH4 band. In this paper, ratio spectrometry method and CO2 band correction method are proposed to reduce the error caused by these factors. Ratio spectrometry method can decrease the effect of surface reflectance in CH4 retrieval by converting absolute radiance spectrometry into ratio spectrometry. CO2 band correction method converts column amounts of CH4 into column averaged mixing ratio by using CO2 1.61 μm band and it can correct the systematic error caused by temperature profile, humidity profile and pressure profile. The combination of these two correction methods will decrease the effect caused by surface reflectance, temperature profile, humidity profile and pressure profile at the same time and reduce the retrieval error. GOSAT data were used to retrieve atmospheric CH4 to test and validate the two correction methods. The results showed that CH4 column averaged mixing ratio retrieved after correction was close to GOSAT Level2 product and the retrieval precision was up to -0.24%. The studies suggest that the error of CH4 retrieval caused by the uncertainties of ground properties and atmospheric conditions can be significantly reduced and the retrieval precision can be highly improved by using ratio spectrometry method and CO2 band correction method.

In this research, protein micro/nanotubes were fabricated by alternate layer-by-layer (LbL) assembly of human serum albumin (HSA) and polyethyleneimine (PEI) into polycarbonate (PC) membranes. The experimental conditions of pH values, ionic strength, the depositions cycles and the diameter of porous membrane were discussed. The morphology and composition of tubes were characterized by scanning electron microscope (SEM), transmission electron microscope (TEM), fourier transform infrared spectroscopy (FTIR) and energy dispersive spectroscopy (EDS). The results show that pH and ionic strength of the solution are the key factors that influence the effect of assembly. Micro/nanotubes with good opening hollow tubular structure were obtained when pH 7.4 HSA solution and pH 10.3 PEI solution without NaCl were used in synthesis procedure. The outer diameter of tube was dependent on the PC template, thus the micro/nanotubes size was controlled by the wall thickness, which can be adjusted by the number of layers of the HSA and PEI deposited along the pore walls. To avoid the thin wall being damaged in dissolving the template and vacuum drying, the PEI/HSA bilayer number should not be less than 3. The polar solvent N,N-dimethylformamide (DMF) can dissolve PC template to release the micro/nanotubes.

The traditional method of measuring arterial oxygen saturation is that R value, the ratio of alternating component of the logarithmic photoplethysmography, is firstly computed and then the linear regression model is established by experiment. The R value computation is a dimension reduction process based on Lambert-beer law, which aims at eliminating the influence of optical path andminimizing the impact of individual differences. When taking scattering into consideration, the dimension reduction process loses information, introduces the system error and limits the precision of measurement. In order to reduce the measurement error resulting from the scattering effects, this paper presents a new method that the peak and valley values of dual-wavelength logarithmic photoplethysmography waves are used as the independent variables to develop a linear regression model to predict the arterial oxygen saturation. During the experiment, the in-vivo measurements were carried out on 23 healthy volunteer and 133 samples of photoplethysmography waves and the reference value of oxygen saturation were recorded. To compare the predictive performance between the new method and the R value method, 90 samples were randomly selected as modeling sets and the remaining 43 samples were used as prediction sets. Random selection of modeling sets and prediction are executed 10 times. The average related coefficients of the prediction sets of the new method and the R value method are 0.890 6 and 0.846 8, and the average root mean square errors are 0.889 6% and 1.037 3% respectively. Results indicate that the performance of the new method is better than the one of the R value method, and the predictivemodel based on 4 parameters can improve the stability and accuracy of measurement. And the new method has guiding significance to the measurement of human body’s blood physiological information based on limited wavelength spectrum data.

Reflective spectra in a multispectral image can objectively and originally represent color information due to their high dimensionality, illuminant independent and device independent. Aiming to the problem of loss of spectral information when the spectral data reconstructed from three-dimensional colorimetric data in the trichromatic camera-based spectral image acquisition system and its subsequent problem of loss of color information, this work proposes an iterated Tikhonov regularization to reconstruct the reflectance spectra. First of all, according to relationship between the colorimetric value and the reflective spectra in the colorimetric theory, this work constructs a spectral reconstruction equation which can reconstruct high dimensional spectral data from three dimensional colorimetric data acquired by the trichromatic camera. Then, the iterated Tikhonov regularization, inspired by the idea of the pseudo inverse Moore-Penrose, is used to cope with the linear ill-posed inverse problem during solving the equation of reconstructing reflectance spectra. Meanwhile, the work also uses the L-curve method to obtain an optimal regularized parameter of the iterated Tikhonov regularization by training a set of samples. Through these methods, the ill condition of the spectral reconstruction equation can be effectively controlled and improved, and subsequently loss of spectral information of the reconstructed spectral data can be reduced. The verification experiment is performed under another set of training samples. The experimental results show that the proposed method reconstructs the reflective spectra with less spectral information loss in the trichromatic camera-based spectral image acquisition system, which reflects in obvious decreases of spectral errors and colorimetric errors compared with the previous method.

The evolution of water DOC and COD, and the source, chemical structure, humification degree and redox of dissolved organic matter (DOM) in a constructed wetland of Xiao River, Hebei, was investigated by 3D excitation–emission matrix fluorescence spectroscopy coupled with ultraviolet spectroscopy and chemical reduction, in order to explore the geochemical processes and environmental effects of DOM. Although DOC contributes at least 60% to COD, its decrease in the constructed wetland is mainly caused by the more extensive degradation of elements N, H, S, and P than C in DOM, and 65% is contributed from the former. DOM is mainly consisted of microbial products based on proxies f470/520 and BIX, indicating that DOM in water is apparently affected by microbial degradation. The result based on PARAFAC model shows that DOM in the constructed wetland contains protein-like and humus-like components, and Fulvic- and humic-like components are relatively easier to degrade than protein-like components. Fulvic- and humic-like components undergo similar decomposition in the constructed wetland. A common source of chromophoric dissolved organic matter (CDOM) and fluorescent dissolved organic matter (FDOM) exists; both CDOM and FDOM are mainly composed of a humus-like material and do not exhibit selective degradation in the constructed wetland. The proxies E2/E3, A240～400, r(A, C) and HIX in water have no changes after flowing into the constructed wetland, implying that the humification degree of DOM in water is hardly affected by wet constructed wetland. However, the constructed wetland environment is not only beneficial in forming the reduced state of DOM, but also facilitates the reduction of ferric. It can also improve the capability of DOM to function as an electron shuttle. This result may be related to the condition that the aromatic carbon of DOM can be stabilized well in the constructed wetland.

In order to precisely acquire leaf reflectance spectra (400～1 000 nm), influence of background on leaf reflectance spectra was studied. Experiment was conducted to discriminate the characteristics of wheat leaves based on 8 background materials and leaf chlorophyll concentration. BPLT (Background Plate) model, based on the Plate model, was promoted and applied to remove the influence of leave background. The BPLT model needed “2-3-1”variables, which were input variables R0(reflectance of the interaction of leaves and background), σ(reflectance of background alone), intermediate variables R12(reflectance of interacting interface from air to a compact leaf), R21 (reflectance of interacting interface from a compact leaf to air), τ (the transmissivity of the plate), and ultimate variable R (reflectance of a compact leaf alone). To verify this model, Analysis of Variance (ANOVA) was conducted to compare ten vegetation indices under different background influences. The results indicated that percent of variation in background reflectance associated with spectral vegetation indices was 5% lower after using the BPLT model. Meanwhile, wheat leaf chlorophyll concentration at different levels could be effectively estimated by the means of BPLT model with determined coefficients (DC) greater than 0.9 and residual sum of squares (SSE) less than 1. As with the ANOVA, vegetation indices NDI and MCARI were better than the other 8 ones. The slope of NDI&MCARI plotted as a function of mean wheat leaf chlorophyll concentration. R2 ranged from 0.847 8 to 0.977 8 with the applied method of BPLT model. The BPLT model is a powerful and accurate method for the acquisition of wheat leaf reflectance information.

By using Ultraviolet-visible Spectrometry, Fourier Transform Infrared Spectrometer and Elemental Analyzer, spectrum and chemical characteristics of soil DOM affected by long-term different fertilizations were investigated in irrigation-desert soil in North-western China based on an experiment started from 1988. Four different fertilization treatments were included, i.e., organic fertilizer (OF), green manure (GM), chemical fertilizer (CF) and a control of no fertilization (CK). The results showed that fertilization could increase the contents of DOM. Compared to CK, the treatments of OF, GM, CF increased the dissolved organic carbon (DOC) by 37%, 29%, 16%; increased the dissolved nitrogen (DON) by 334%, 257%, 182%; increased the total carbohydrate (TCs) by 90%, 25%, 2%; and increased the total organic acids (TOAs) by 195%, 116%, 58%; respectively. Furthermore, DOC, DON, TCs, and TOAs in the OF treatment were significantly higher than those in CK, they were also significantly higher in the GM and CF treatments except for TCs. The ultraviolet-visible analysis showed that fertilizations enhanced the SUVA254, SUVA260, SUVA272 and SUVA280 of DOM, indicating that fertilizations increased the aromatic and hydrophobic percentage, humification degree, and average molecular weight, and thus resulting in more stability of DOM. Same trends were showed for all the 4 ultraviolet spectrum absorption values in different fertilizations, i.e., the strongest effect was found in the OF treatment, and then was the GM treatment and CF treatment successively. From the results by the Fourier Transform Infrared Spectrometry, the characteristic peak of aromatic in the OF treatment was observed shifting from 1 625 to 1 649 cm-1, which was close to the characteristic peak of humin, suggesting that the aromaticity of DOM in the OF treatment was higher than the other treatments. The characteristic peaks of C—O at 1 260～1 000 cm-1 belonging to sugar, alcohol, and carboxylic acid were highest in the GM treatment, showing that the green manure could increase rich oxygen radicals. The highest characteristic peaks of N—H at 3 559, 3 419 and 1 456 cm-1 were observed in the CF treatment, indicating that the chemical fertilizer could increase amine substances. The contents of C, O and N in the OF, GM, CF treatments were also increased respectively according to the elemental analysis.

The feasibility of Fourier transform near infrared (FT-NIR) spectroscopy with spectral range between 833 and 2 500 nm to detect the moldy corn kernels with different levels of mildew was verified in this paper. Firstly, to avoid the influence of noise, moving average smoothing was used for spectral data preprocessing after four common pretreatment methods were compared. Then to improve the prediction performance of the model, SPXY (sample set partitioning based on joint x-y distance) was selected and used for sample set partition. Furthermore, in order to reduce the dimensions of the original spectral data, successive projection algorithm (SPA) was adopted and ultimately 7 characteristic wavelengths were extracted, the characteristic wavelengths were 833, 927, 1 208, 1 337, 1 454, 1 861, 2 280 nm. The experimental results showed when the spectrum data of the 7 characteristic wavelengths were taken as the input of SVM, the radial basic function (RBF) used as the kernel function, and kernel parameter C=7 760 469, γ=0.017 003, the classification accuracies of the established SVM model were 97.78% and 93.33% for the training and testing sets respectively. In addition, the independent validation set was selected in the same standard, and used to verify the model. At last, the classification accuracy of 91.11% for the independent validation set was achieved. The result indicated that it is feasible to identify and classify different degree of moldy corn grain kernels using SPA and SVM, and characteristic wavelengths selected by SPA in this paper also lay a foundation for the online NIR detection of mildew corn kernels.

In order to explore a non-destructive monitoring technique, the use of digital photo pixels canopy cover (CC) diagnosis and prediction on maize growth and its nitrogen nutrition status. This study through maize canopy digital photo images on relationship between color index in the photo and the leaf area index (LAI), shoot dry matter weight (DM), leaf nitrogen content percentage (N%). The test conducted in the Chinese Academy of Agricultural Science from 2012 to 2013, based on Maize canopy Visual Image Analysis System developed by Visual Basic Version 6. 0, analyzed the correlation of CC, color indices, LAI, DM, N% on maize varieties (Zhongdan909, ZD 909) under three nitrogen levels treatments, furthermore the indicators significantly correlated were fitted with modeling, The results showed that CC had a highly significant correlation with LAI (r=0.93, p<0.01), DM (r=0.94, p<0.01), N% (r=0.82, p<0.01). Estimating the model of LAI, DM and N% by CC were all power function, and the equation respectively were y=3.281 2x0.763 9, y=283.658 1x0.553 6 and y=3.064 5x0.932 9; using independent data from modeling for model validation indicated that R2, RMSE and RE based on 1∶1 line relationship between measured values and simulated values in the model of CC estimating LAI were 0.996, 0.035 and 1.46%; R2, RMSE and RE in the model of CC estimating DM were 0.978, 5.408 g and 2.43%; R2, RMSE and RE in the model of CC estimating N% were 0.990, 0.054 and 2.62%. In summary, the model can comparatively accurately estimate the LAI, DM and N% by CC under different nitrogen levels at maize grain filling stage, indicating that it is feasible to apply digital camera on real-time undamaged rapid monitoring and prediction for maize growth conditions and its nitrogen nutrition status. This research finding is to be verified in the field experiment, and further analyze the applicability throughout the growing period in other maize varieties and different planting density.

The components of ancient mortars have always been an important research field in historic building conservation. It has been well known that using traditional mortars in conservation projects have many advantages, such as compatibility and stability. So, developing new binding materials based on traditional mortar has become an international study hotspot. With China’s economic development, the protection of ancient buildings also began to put on the agenda, but the understanding on Chinese traditional mortar is limited, and rare literatures are reported. In the present work, the authors investigate seven ancient city wall sites in Zhejiang Province in situ, and subsequently laboratory analysis were carried out on collected mortar samples. The characterizations of mortar samples were made by multi-density gauge, XRD, FTIR, TG-DSC and wet chemical analysis. The experimental results showed that: the main component of masonry mortars is calcium carbonate, the content between 75%～90%, and they should be made from relatively pure lime mortar. The raw materials of mortar samples were mainly calcareous quick lime, and sample from Taizhou city also contained magnesium quick lime. There are four city walls were built by sticky-rice mortars. It suggests that the technology of adding the sticky rice soup into mortar was universal in the Ming Dynasties. These mortars have lower density between 1.2 and 1.9 g·cm-3; this outcome should be the result of long-term natural erosion. We have also analyzed other chemical and physical characteristics of these masonry mortars. The results can afford the basic data for the future repairmen programs, development of new protective materials, and comparative study of mortars.

Rapid source identification of mine water inrush is of great significance for early warning and prevention in mine water hazard. According to the problem that traditional chemical methods to identify source takes a long time, put forward a method for rapid source identification of mine water inrush with laser induced fluorescence (LIF) technology and soft independent modeling of class analogy (SIMCA) algorithm. Laser induced fluorescence technology has the characteristics of fast analysis, high sensitivity and so on. With the laser assisted, fluorescence spectrums can be collected real-time by the fluorescence spectrometer. According to the fluorescence spectrums, the type of water samples can be identified. If the database is completed, it takes a few seconds for coal mine water source identification, so it is of great significance for early warning and post-disaster relief in coal mine water disaster. The experiment uses 405 nm laser emission laser into the 5 kinds of water inrush samples and get 100 groups of fluorescence spectrum, and then put all fluorescence spectrums into preprocessing. Use 15 group spectrums of each water inrush samples, a total of 75 group spectrums, as the prediction set, the rest of 25 groups spectrums as the test set. Using principal component analysis (PCA) to modeling the 5 kinds of water samples respectively, and then classify the water samples with SIMCA on the basis of the PCA model. It was found that the fluorescence spectrum are obvious different of different water inrush samples. The fluorescence spectrums after preprocessing of Gaussian-Filter, under the condition of the principal component number is 2 and the significant level α＝5%, the accuracy of prediction set and testing set are all 100% with the SIMCA to classify the water inrush samples.

This study chooses the core demonstration area of ‘Bohai Barn’ project as the study area, which is located in Wudi, Shandong Province. We first collected near-ground and multispectral images and surface soil salinity data using ADC portable multispectral camera and EC110 portable salinometer. Then three vegetation indices, namely NDVI, SAVI and GNDVI, were used to build 18 models respectively with the actual measured soil salinity. These models include linear function, exponential function, logarithmic function, exponentiation function, quadratic function and cubic function, from which the best estimation model for soil salinity estimation was selected and used for inverting and analyzing soil salinity status of the study area. Results indicated that all models mentioned above could effectively estimate soil salinity and models using SAVI as the dependent variable were more effective than the others. Among SAVI models, the linear model(Y=-0.524x+0.663, n=70) is the best, under which the test value of F is the highest as 141.347 at significance test level, estimated R2 0.797 with a 93.36% accuracy. Soil salinity of the study area is mainly around 2.5‰～3.5‰, which gradually increases from southwest to northeast. This study has probed into soil salinity estimation methods based on near-ground and multispectral data, and will provide a quick and effective technical soil salinity estimation approach for coastal saline soil of the study area and the whole Yellow River Delta.

As the special imaging principle of the interference hyperspectral image data, there are lots of vertical interference stripes in every frames. The stripes’ positions are fixed, and their pixel values are very high. Horizontal displacements also exist in the background between the frames. This special characteristics will destroy the regular structure of the original interference hyperspectral image data, which will also lead to the direct application of compressive sensing theory and traditional compression algorithms can’t get the ideal effect. As the interference stripes signals and the background signals have different characteristics themselves, the orthogonal bases which can sparse represent them will also be different. According to this thought, in this paper the morphological component analysis (MCA) is adopted to separate the interference stripes signals and background signals. As the huge amount of interference hyperspectral image will lead to slow iterative convergence speed and low computational efficiency of the traditional MCA algorithm, an improved MCA algorithm is also proposed according to the characteristics of the interference hyperspectral image data, the conditions of iterative convergence is improved, the iteration will be terminated when the error of the separated image signals and the original image signals are almost unchanged. And according to the thought that the orthogonal basis can sparse represent the corresponding signals but cannot sparse represent other signals, an adaptive update mode of the threshold is also proposed in order to accelerate the computational speed of the traditional MCA algorithm, in the proposed algorithm, the projected coefficients of image signals at the different orthogonal bases are calculated and compared in order to get the minimum value and the maximum value of threshold, and the average value of them is chosen as an optimal threshold value for the adaptive update mode. The experimental results prove that whether LASIS and LAMIS image data, the traditional MCA algorithm can separate the interference stripes signals and background signals very well, and make the interference hyperspectral image decomposition perfectly, and the improved MCA algorithm not only keep the perfect results of the traditional MCA algorithm, but also can reduce the times of iteration and meet the iterative convergence conditions much faster than the traditional MCA algorithm, which will also provide a very good solution for the new theory of compressive sensing.

Spectroscopic sensor is becoming an important issue for the deep-sea exploration due to the advantages of multi-specie, multi-phases and stand-off detection. Different approach have been developing in recent years based on LIBS (Laser Induced Breakdown Spectroscopy) and Raman spectroscopy since Raman-LIBS are complementary techniques with the similar components and the capability of molecular and elementary analysis. In this work, we built a LIBS-Raman system and detected Na2SO4 in aqueous solution to evaluate the potential ocean application. With the same laser, spectrometer and detector, a hybrid of Raman and LIBS system was developed to realize the detection of anions and cations in the seawater. The optics was composed by two parts: Raman channel and LIBS channel, and the signal was collected by a Y type optical fiber bundle. The signal from two channels was separated by imaging on different arrays of the CCD detector. The Raman spectra of SO2-4 and LIBS spectra of Na was successfully detected simultaneously when the pulse energy was above 3.6 mJ. However, due to the strong bremsstrahlung radiation of LIBS, the signal to noise ratio of Raman was significantly decreased as the laser energy increasing. The results manifested the great potential of Raman-LIBS combination for the underwater detection.

By adopting inductively coupled plasma mass spectrometry (ICP-MS) combined with chemometric analysis technology, 23 kinds of minerals in four kinds of characteristic honey derived from Yunnan province were analyzed. The result showed that 21 kinds of mineral elements, namely Na, Mg, K, Ca, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Sr, Mo, Cd, Sb, Ba, Tl and Pb, have significant differences among different varieties of honey. The results of principal component analysis (PCA) showed that the cumulative variance contribution rate of the first four main components reached 77.74%, seven kinds of elements (Mg, Ca, Mn, Co, Sr, Cd, Ba) from the first main component contained most of the honey information. Through the stepwise discriminant analysis, seven kinds of elements (Mg, K, Ca, Cr, Mn, Sr, Pb) were filtered out and used to establish the discriminant function model, and the correct classification rates of the proposed model reached 90% and 86.7%, respectively, which showed elements contents could be effectively indicators to discriminate the four kinds characteristic honey in southern Yunnan Province. In view of all the honey samples were harvested from apiaries located at south Yunnan Province where have similar climate, soil and other environment conditions, the differences of the mineral elements contents for the honey samples mainly due to their corresponding nectariferous plant. Therefore, it is feasible to identify honey botanical source through the differences of mineral elements.

The technology of computational spectral imaging changes the traditional imaging modalities by introducing a coded aperture in the optical path to achieve transformation of the targets spectral imformation, then we can get the spectral data cube by reverse transform. This paper introduces the principle of a push-broom imaging coded aperture computational spectral imager. In practical applications, the matching error between the push speed and the frame rate can affect the accuracy of the spectral data reconstruction. The error terms are deduced based on the model of pushroom, the influences of matching errors to the spectral data reconstruction are anlyzed. And the second spectra derivative and strehl ratio are introduced as the evaluation parameters to, respectively, evaluate the reconstructed spectral and spatial image in the data simulation analysis. It showed that, when the accumulated error of a complete set of data is more than one pixel, the shading dramaticly area’s reconstructed results are relatively poor, but the relatively homogeneous regions are affected small; when cumulative error does not exceed half pixel, strehlretio of each channel were above 0.9, and the lower of the spectral energy, the channels strehl ratio smaller, so the more the ranks of the coding template, the higher the platform’s stability required.

Monochromator is the necessary equipment for spectral imager to calibrate the spectrum continuously. In order to calibrate the hyperspectral imaging spectrometer continuously, a small-type and high-spectral-resolution grating monochromator is designed. The grating monochromator with horizontal Czerny-Turner structure is designed with high-spectral-resolution as a starting point, and the design idea is discussed in detail from choosing the grating, calculating the focal length, the sizes of entrance slit and exit slit, among others. Using this method, the necessary structure parameters are determined, and the impact of the necessary structure parameters for spectral resolution and volume is given. According to the optical characteristics of the grating monochromator, the mechanical structures of the instrument are designed for small and handy from the components of the entrance slit, the collimator lens and imaging objective lens, the scanning structures, the fuselage and so on. The relationship of the sine mechanism parameters for output wavelength and wavelength scanning accuracy is given. The design and adjustment of the instrument are completed. The visible spectrums of mercury lamp are used as calibration lines, and the calibration curve is acquired by using least square method. This paper gives a method that combining the limit error of the step number and the calibration curve to evaluate the wavelength repeatability and wavelength precision. The datum of experiment shows that the spectral resolution of the instrument is better than 0.1 nm in the wavelength band from 400 to 800 nm. Simultaneously the wavelength repeatability reach to ±0.096 6 nm and the precision reach to ±0.096 9 nm.

Methane is a colorless, odorless, flammable and explosive gas, which not only is the cause to induce significant security risk in coal mining operation, but also one of the important greenhouse gases, so the monitoring of methane is extremely critical. A trace methane gas sensor is designed and developed using the combination of tunable diode laser absorption spectroscopy (TDLAS) and wavelength modulation spectroscopy (WMS) detection technology, which is based on the methane R(3) absorption branch in 2v3 second harmonic band. Through tuning parameters -0.591 cm-1·K-1, using the method that change the working temperature of distributed feedback (DFB) laser to obtain the best absorption wavelength of methane at 1.654 μm. When the mid-wavelength of DFB laser is selected, the appropriate emitting intension can be obtained via adjusting the amplitude of inject current of DFB laser. Meanwhile, combining the frequency modulation technology to move the bandwidth of detection signal from low frequency to high frequency to reduce the 1/f noise. With aspect to the optical structure, utilizing herriott cell with 76 m effective optical path to guarantee the detection of trace methane is successful. Utilizing the proposed trace methane sensor to extract the second harmonic signal of detected methane in the range of 50 to 5 000 μmol·mol-1, and adopting minimum mean square error criterion to fit the relationship between methane concentration and signal noise ratio, harmonic peak signal and methane concentration, respectively. In addition, the minimum detection limit is 1.4 μmol·mol-1. The experiment results show the symmetry of harmonic waveform is good, no intensity modulation, and the factor of intensity-modulated impacts on harmonic detection is eliminated.

Traditional temperature detection system based on Fiber Bragg Grating is suitable for large-scale, real-time multi-point temperature detection field. But its stability of temperature response is poor, shift amount of Bragg grating center wavelength is poor linearity with temperature variation. In order to improve the stability for system and temperature detection accuracy of the system, an improved temperature detection system based on Fiber Bragg Grating was designed. The method of dual fiber parallel acquisition for temperature data was used on the same point, and then center wavelength data was differentially processed. It was realized that the random errors of the system were effectively real-time eliminated in the process temperature. The function relationships of center wavelength shift amount of Fiber Bragg Grating and temperature variation was derived in this mode, and the new structure of the probes for Fiber Bragg Grating was designed. In the experiments, measurement data of Improved temperature detection system based on Fiber Bragg Grating was compared with the data of traditional system. Experimental results show that temperature measurement accuracy of improved system was up to 0.5 ℃, and its accuracy has been improved compared to conventional systems. Meanwhile, the measurement error was significantly better than traditional systems. It proved that the design can improve the stability of temperature detection for the system.

According to the spectral absorption characteristics of polluting gases and fluorescence characteristics, a time-division multiplexing detection system is designed. Through this system we can detect Methane (CH4) and sulfur dioxide (SO2) by using spectral absorption method and the SO2 can be detected by using UV fluorescence method. The system consists of four parts: a combination of a light source which could be switched, the common optical path, the air chamber and the signal processing section. The spectral absorption characteristics and fluorescence characteristics are measured first. Then the experiment of detecting CH4 and SO2 through spectral absorption method and the experiment of detecting SO2 through UV fluorescence method are conducted, respectively. Through measuring characteristics of spectral absorption and fluorescence, we get excitation wavelengths of SO2 and CH4 measured by spectral absorption method at the absorption peak are 280 nm and 1.64 μm, respectively, and the optimal excitation wavelength of SO2 measured by UV fluorescence method is 220 nm. we acquire the linear relation between the concentration of CH4 and relative intensity and the linear relation between the concentration of SO2 and output voltage after conducting the experiment of spectral absorption method, and the linearity are 98.7%, 99.2% respectively. Through the experiment of UV fluorescence method we acquire that the relation between the concentration of SO2 and the voltage is linear, and the linearity is 99.5%. Research shows that the system is able to be applied to detect the polluted gas by absorption spectrum method and UV fluorescence method. Combing these two measurement methods decreases the costing and the volume, and this system can also be used to measure the other gases. Such system has a certain value of application.

The spectra measurements mode that suitable for haploid maize kernel identification was explored using MicroNIR-1700 series of miniature near infrared spectrometer by JDSU company. Based on Near Infrared Spectroscopy (NIRS) qualitative analysis techniques, we conducted a comparative study using reflectance and transmittance spectra to identify haploid maize kernels. Partial least squares-discriminant analysis(PLS-OLDA) was used to compress the pretreated spectral data, and then the identification models were built based on Support Vector Machine (SVM). The measured data were recorded in reflectance and transmittance modes and the recognition correct rates were calculated. For measurements taken in reflectance mode, the average recognition rate was less than 60% regardless of embryo side positions. In transmittance mode, however, the average recognition rate reached 93.2%. The experiment results show that diffuse reflection spectrum could only obtain corn grain surface information, so embryo side positions severely affect haploid maize kernel identification effect when reflectance measurements mode have been employed, but they have far less impact on transmittance mode. The near infrared diffuse transmittance spectra analyzes non-uniform samples can achieve the analysis of optical path depth information accumulation, all information of the sample interior can be obtained, so transmittance spectra could identify haploid maize effectively and be desensitized to kernel positions. NIRS qualitative analysis techniques with features of rapid, nondestructive could identify the haploid and Micro-NIR spectrometer scan fast and cost less, which have utility for automatically selecting haploid maize kernels from hybrid kernels.

Edible blend oil market is confused at present. It has some problems such as confusing concepts, randomly named, shoddy and especially the fuzzy standard of compositions and ratios in blend oil. The national standard fails to come on time after eight years. The basic reason is the lack of qualitative and quantitative detection of vegetable oils in blend oil. Edible blend oil is mixed by different vegetable oils according to a certain proportion. Its nutrition is rich. Blend oil is eaten frequently in daily life. Different vegetable oil contains a certain components. The mixed vegetable oil can make full use of their nutrients and make the nutrients more balanced in blend oil. It is conducive to people’s health. It is an effectively way to monitor blend oil market by the accurate determination of single vegetable oil content in blend oil. The types of blend oil are known, so we only need for accurate determination of its content. Three dimensional fluorescence spectra are used for the contents in blend oil. A new method of data processing is proposed with calculation of characteristics peak value integration in chosen characteristic area based on Quasi-Monte Carlo method, combined with Neural network method to solve nonlinear equations to obtain single vegetable oil content in blend oil. Peanut oil, soybean oil and sunflower oil are used as research object to reconcile into edible blend oil, with single oil regarded whole, not considered each oil’s components. Recovery rates of 10 configurations of edible harmonic oil is measured to verify the validity of the method of characteristics peak value integration. An effective method is provided to detect components content of complex mixture in high sensitivity. Accuracy of recovery rats is increased, compared the common method of solution of linear equations used to detect components content of mixture. It can be used in the testing of kinds and content of edible vegetable oil in blend oil for the food quality detection, and provide an effective reference for the creation of national standards.