Discrimination of Transgenic Rice Based on Near Infrared Reflectance Spectroscopy and Partial Least Squares Regression Discriminant Analysis

Near infrared reflectance spectroscopy （NIRS）, a non-destructive measurement technique, was combined with partial least squares regression discrimiant analysis （PLS-DA） to discriminate the transgenic （TCTP and mi166） and wild type （Zhonghua 11） rice. Furthermore, rice lines transformed with protein gene （OsTCTP） and regulation gene （Osmi166） were also discriminated by the NIRS method. The performances of PLS-DA in spectral ranges of 4 000-8 000 cm-1 and 4 000-10 000 cm-1 were compared to obtain the optimal spectral range. As a result, the transgenic and wild type rice were distinguished from each other in the range of 4 000-10 000 cm-1, and the correct classification rate was 100.0% in the validation test. The transgenic rice TCTP and mi166 were also distinguished from each other in the range of 4 000-10 000 cm-1, and the correct classification rate was also 100.0%. In conclusion, NIRS combined with PLS-DA can be used for the discrimination of transgenic rice.

Application of Near Infrared Diffuse Reflectance Spectroscopy with Radial Basis Function Neural Network to Determination of Rifampincin Isoniazid and Pyrazinamide Tablets

Partial least squares（PLS）,back-propagation neural network（BPNN）and radial basis function neural network（RBFNN）were respectively used for estalishing quantative analysis models with near infrared（NIR）diffuse reflectance spectra for determining the contents of rifampincin（RMP）,isoniazid（INH）and pyrazinamide（PZA）in rifampicin isoniazid and pyrazinamide tablets.Savitzky-Golay smoothing,first derivative,second derivative,fast Fourier transform（FFT）and standard normal variate（SNV）transformation methods were applied to pretreating raw NIR diffuse reflectance spectra.The raw and pretreated spectra were divided into several regions,depending on the average spectrum and RSD spectrum.Principal component analysis（PCA）method was used for analyzing the raw and pretreated spectra in different regions in order to reduce the dimensions of input data.The optimum spectral regions and the models＇ parameters were chosen by comparing the root mean square error of cross-validation（RMSECV）values which were obtained by leave-one-out cross-validation method.The RMSECV values of the RBFNN models for determining the contents of RMP,INH and PZA were 0.00288,0.00226 and 0.00341,respectively.Using these models for predicting the contents of INH,RMP and PZA in prediction set,the RMSEP values were 0.00266,0.00227 and 0.00411,respectively.These results are better than those obtained from PLS models and BPNN models.With additional advantages of fast calculation speed and less dependence on the initial conditions,RBFNN is a suitable tool to model complex systems.

Determination of Protein and Starch Content in Whole Maize Kernel by Near Infrared Reflectance Spectroscopy

Using 128 bulk-kernel samples of inbred lines and hybrids, a study was conducted toinvestigate the feasibility and method of measuring protein and starch contents inintact seeds of maize by near infrared reflectance spectroscopy (NIRS). The chemometricalgorithms of partial least square (PLS) regression was used. The results indicated thatthe calibration models developed by the spectral data pretreatment of firstderivative+multivariate scattering correction within the spectral region of 10000-4000cm-1, and first derivative + straight line subtraction in 9000-4000cm-1 were thebest for protein and starch, respectively. All these models yielded coefficients ofdetermination of calibration (R2cal) above 0.97, while R2cv and R2val of cross and externalvalidation ranged from 0.92 to 0.95, respectively; however, the root of mean squareerrors of calibration, cross and external validation (RMSEE, RMSECV and RMSEP) werebelow 1(ranged 0.3-0.7),respectively. This study demonstrated that it is feasible touse NIRS as a rapid, accurate, and none-destructive technique to predict protein andstarch contents of whole kernel in the maize quality improvement program.

Characterization on the Exfoliation Degree of Graphite Oxide into Graphene Oxide by UV-visible Spectroscopy

The exfoliation degree of graphite oxide into graphene oxide plays an important role in the massive production method of reduced graphene oxide. It is significant to find a simple and feasible method to analyze the exfoliation degree of graphite oxide. In the present work, graphite oxide was synthesized by a modified Hummers method, and then graphene oxide colloids were obtained by exfoliation of graphite oxide dispersed in de-ionized water. UV-visible spectroscopy was used to characterize the absorption of the graphene oxide colloids, and the concentration of graphene oxide colloids indicated by absorption area of UV-visible spectra was studied. Results show that there is a relatively stable relationship between them, indicating that UV- visible spectroscopy is a potential method for analyzing the exfoliation degree of graphite oxide into graphene oxide.

Sensitivity Enhancement in Uranium Determination by UV-Visible Spectroscopy Using Ion Imprinted Polymer

There is need to determination of uranium concentration at ppb level in environmental matrices.Due to low sensitivity of FAAS,UV-Visible Spectroscopy is generally used as measurement technique.In this study,ion-imprinted polymers(IIP)were prepared for uranyl ion(imprint ion)by formation of ternary(salicylaldoxime and 4-vinylpyridine)complex in 2-methoxy ethanol(porogen)following copolymerization with methacrylic acid(MAA)as a functional monomer and ethylene glycol dimethacrylate(EGDMA)as crosslinking monomer using 2,2-azobisisobutyronitrile as initiator.The synthesized polymers were characterized by FTIR and TGA analysis.ArsenazoⅢin 3M HClO_4 was used as complexing agent in the measurement step.The optimal pH for preconcentration was found to be between 3.5~6.5values.The developed method was applied to uranium(Ⅵ)determination in natural water samples.

Thermal maturity evaluation using Raman spectroscopy for oil shale samples of USA:comparisons with vitrinite reflectance and pyrolysis methods

Thermal maturity is commonly assessed by various geochemical screening methods(e.g.,pyrolysis and organic petrology).In this contribution,we attempt to establish an alternative approach to estimating thermal maturity with Raman spectroscopy,using 24 North American oil shale samples with thermal maturity data generated by vitrinite reflectance(VRo%)and pyrolysis(Tmax)-based maturity calculation(VRe%).The representative shale samples are from the Haynesville(East Texas),Woodford(West Texas),Eagle Ford and Pearsall(South Texas)Formations,as well as Gothic,Mancos,and Niobrara Formation shales(all from Colorado).The Raman spectra of disordered carbonaceous matter(D1 and G bands separation)of these samples were directly obtained from the rock chips without prior sample preparation.Using the Gaussian and Lorentzian distribution approach,thermal maturities from VR were correlated with carbon G and D1.We found that the Raman band separation(RBS)displayed a better correlation for equivalent VRe%than vitrinite reflectance VRo%.The RBS(D1–G)distance versus total organic carbon,free hydrocarbons from thermal extraction(S1),and the remaining hydrocarbon generating potential(S2)indicate that the RBS(D1–G)distance is also related to kerogen type.Data presented here from three methods of maturity determination of shale demonstrate that Raman spectroscopy is a quick and valid approach to thermal maturity assessment.

Use of near-infrared reflectance spectroscopy for the rapid determination of the digestible energy and metabolizable energy content of corn fed to growing pigs

Background： The ability of near-infrared reflectance spectroscopy（NIRS） to determine the digestible energy（DE）and metabolizable energy（ME） content of corn fed to growing pigs was tested. One hundred and seventeen corn samples, comprising different planting regions and varieties were collected from all over China in a three-year period. The samples were randomly split into a calibration set（n = 88） and a validation set（n = 29）. The actual and calculated DE and ME content of the corn samples was determined by digestion-metabolism experiments and the prediction equations of Noblet and Perez（J Anim Sci. 71：3389–98,1993）. The samples were then subjected to NIRS scanning and calibrations were performed by the modified partial least square（MPLS） regression method based on77 different spectral pre-treatments. The NIRS equations based on the actually determined and calculated DE and ME were built separately and then validated using validation samples.Results： The NIRS equations obtained from actually determined DE, the coefficient of determination for calibration（RSQcal）, cross-validation（R^2CV）, and validation（RSQv） were 0.89, 0.87 and 0.86, and these values for determined ME were 0.87, 0.86 and 0.86. For the NIRS equations built from calculated DE, the RSQcal, R^2CV, and RSQvvalues were 0.88, 0.85 and 0.84, and these values for calculated ME were 0.86, 0.84 and 0.82. Except for the equation based on calculated ME（RPD_v= 2.38, 〈 2.50）, the other three equations built from actually determined energy and calculated DE produced good prediction performance（RPD_vranging from 2.53 to 2.69, 〉 2.50） when applied to validation samples.Conclusion： These results indicate that NIRS can be used as a quantitative method for the rapid determination of the available energy in corn fed to growing pigs, and the NIRS equations based on the actually determined energy produced better predictive performance than those built from calculated energy values.

Geographic Classification of Chinese Grape Wines by Near-Infrared Reflectance Spectroscopy

Near-infrared reflectance spectroscopy (NIRS) was applied to classify grape wines of different geographical origins (Changli, Huailai, and Yantai, China). Near infrared (NIR) spectra were collected in transmission mode in the wavelength range of 800-2500 nm. Wines (n=90) were randomly split into two sets, calibration set (n=54) and validation set (n=36). Discriminant analysis models were developed using BP neural network and discriminant partial least-squares discriminant analysis (PLS-DA). The prediction performance of calibration models in different wavelength range was also investigated. BP neural network models and PLS-DA models correctly classified 100% of the wines in calibration set. When used to predict wines in validation set, BP neural network models correctly classified 100%, 81.8%, and 90.9% of the wines from Changli, Huailai, and Yantai respectively, and PLS-DA models correctly classified 100% of all samples. The results demonstrated that NIRS could be used to discriminate Chinese grape wines as a rapid and reliable method.

Application of NIR Reflectance Spectroscopy on Rapid Determination of Moisture Content of Wood Pellets

NIR spectroscopy was used to measure the moisture concentration of wood pellets. Pellets were conditioned to various moisture levels between 0.63% and 14.16% (wet basis) and the moisture concentration was verified using a standard oven method. Samples from various moisture levels were separated into two groups, as calibration and validation sets. NIR absorption spectral data from 400 nm to 2500 nm with 0.5 nm intervals were collected using pellets within the calibration and validation sample sets. Spectral wavelength ranges were taken as independent variables and the MC of the pellets as the dependent variable for the analysis. Measurements were obtained on 30 replicates within each moisture level. Partial Least Square (PLS) analysis was performed on both raw and preprocessed spectral data of calibration set to determine the best calibration model based on Standard Error of Calibration (SEC) and coefficient of multiple determinations (R2). The PLS model that yielded the best fit was used to predict the moisture concentration of validation group pellets. Relative Percent Deviation (RPD) and Standard Error of Prediction (SEP) were calculated to validate goodness of fit of the prediction model. Baseline and Multiple Scatter Corrected (MSC) reflectance spectra with 1st derivative model gave the highest RPD value of 4.46 and R2 of 0.95. Also it’s SEP (0.670) and RMSEP (0.782) were less than the other models those had RPD value more than 3.0 with less number of factors. Therefore, this model was selected as the best model for moisture content prediction of wood pellets.

THE VARIATIONS OF WATER IN HUMAN TISSUE UNDER CERTAIN COMPRESSION:STUDIED WITH DIFFUSE REFLECTANCE SPECTROSCOPY

The reflectance spectrun has been widely adopted to extract diagnosis information of human tissue because it possesses the advantages of noninvasive and rapidity.The external pressure brought by fiber optic probe may influence the accuracy of measurement.In this paper,a sys-tematic study is focused on the effects of probe pressure on intrinsic changes of water and scattering particles in tissue.According to the biphasic nonlinear mixture model,the pressure modulated reflectance spectrum of both in vitro and in vivo tissue is measured and processed with second-derivation.The results indicate that the variations of bulk and bonded water in tissue have a nonlinear relationship with the pressure.Diferences in tissue structure and morphology contribute to site specific probe pressure effects.Then the finite element(FEM)and Monte Carlo(MC)method is employed to simulate the deformation and reflectance spectrum variations of tissue before and after compression.The simulation results show that as the pressure of fiber optic probe applied to the detected skin increased to 80kPa,the effective photon proportion form dermis decreases significantly from 86%to 76%.Future designs might benefit from the research of change of water volume inside the tissue to mitigate the pressure applied to skin.

Monitoring real time polymorphic transformation of sulfanilamide by diffuse reflectance visible spectroscopy

This study investigated the development of a novel approach to surface characterization of drug poly- morphism and the extension of the capabilities of this method to perform ＇real time＇ in situ measure- ments. This was achieved using diffuse reflectance visible （DRV） spectroscopy and dye deposition, using the pH sensitive dye, thymol blue （TB）. Two polymorphs, SFN-β and SFN-γ, of the drug substance sulfanilamide （SFN） were examined. The interaction of adsorbed dye with polymorphs showed different behavior, and thus reported different DRV spectra. Consideration of the acid/base properties of the morphological forms of the drug molecule provided a rationalization of the mechanism of differential coloration by indicator dyes. The kinetics of the polymorphic transformation of SFN polymorphs was monitored using treatment with TB dye and DRV spectroscopy. The thermally-induced transformation fitted a first-order solid-state kinetic model （R2=0.992）, giving a rate constant of 2.43 × 10^- 2 s 1.

Changes in diffuse reflectance spectroscopy properties of hematite in sediments from the North Pacific Ocean and implications for eolian dust evolution history

Eolian dust preserved in deep-sea sediments of the North Pacific Ocean(NPO) is an important recorder of paleoclimatic and paleoenvironmental changes in the Asian inland. To better understand changes in the dust provenances, in this study diffuse reflectance spectroscopy(DRS) was used to extract the eolian signal recorded in sediments of ODP Hole 885 A recovered from the NPO. First, we systematically investigated sieving effects on the DRS data; then band positions of hematite(obtained from the second order derivative curves of the K-M remission function spectrum derived from the DRS) were used to distinguish different provenances of the eolian dust preserved in the pelagic sediments of this hole. Our results show that the sieving(38 μm) process can suppress effectively the experimental errors. Eolian signatures from Chinese Loess Plateau(CLP) sources and non-CLP-sources have been identified in the pelagic sediments of ODP Hole 885 A from the late Pliocene to the early Pleistocene. The provenance differences account for the discrepancies in the eolian records recovered from the pelagic sediments in the NPO and profiles in the CLP. Temporal changes in dust provenances are caused by the latitudinal movement of the westerly jet mainstream. The hematite DRS band position is a useful tool to distinguish the provenance of eolian components preserved in pelagic sediments.

A practical and effective method for reducing differential reflectance spectroscopy noise

Differential reflectance spectroscopy(DRS)is a powerful tool to study processes during thin-film growth,especially that of transition metal dichalcogenides and organic thin films.To satisfy the requirements for in situ and real-time monitoring of film growth,including spectral resolution and sensitivity at the level of monolayers and even sub-monolayers,the most challenging technical task in DRS is to reduce noise to an extremely low level so that the best possible signal-to-noise ratio can be achieved.In this paper,we present a simplified and cost-effective DRS apparatus,with which we show that the measurement noise is mainly composed of thermal drift noise and explore the temperature-dependence of the DRS signal.Based on the results obtained,we propose an easily realized and effective scheme aiming to reduce the noise.Experimental results demonstrate that this scheme is effective in stabilizing reliable signals for a long period of several hours.Significant noise reduction is achieved,with the typical average noise of the DRS system being decreased to 0.05%over several hours.The improved DRS system is applied to study the growth of an organic semiconductor layer for an organic field-effect transistor device.The results indicate that the apparatus proposed in this paper has potential applications in fabrication of devices on the nanoscale and even the sub-nanoscale.

Interaction between DNA with Complex of Eu^(3+)-Rutin by UV-Visible Spectroscopy and Electrochemistry

The interaction of Eu^3＋-rutin with CT DNA was studied by UV-visible spectroscopy and electrochemistry. All experimental results indicate that the complex binds to DNA by the electrostatic mode and the groove binding mode. Information such as intrinsic binding costant （ k = 1. 426 × 104 mol·L^-1 ）, and binding numbers （ n = 2）, were determined by cyclic vohammetry and differential pulse vohammetry at glass carbon electrode. Interaction between Eu^3＋ with rutin was also studied by UV-visible spectroscopy.

Feasibility of using reflectance spectroscopy for the analysis of bio-element concentrations in Antarctic ornithogenic sediments

Compared with traditional chemical analysis methods,reflectance spectroscopy has the advantages of speed,minimal or no sample preparation,non-destruction,and low cost.The present study explored the application of the reflectance spectroscopy within near ultraviolet-visible-near infrared region to predict bio-element compositions in the ornithogenic sediments from the maritime Antarctic.A total of 106 samples were taken from four ornithogenic sediment cores on the Ardley Island of Antarctica,68 samples were used for building calibration equation,and 38 for prediction of nine bio-elements including P,Ca,Cu,Zn,Se, Sr,Ba,F and S.Three multivariate statistical analysis techniques,including stepwise multiple linear regression（Stepwise-MLR）,principal component regression（PCR） and partial least squares regression（PLS） were used to develop mathematical relationships between the spectral data and the chemical reference data.The results showed that the regression models constructed by PCR and PLS models have no significant differences,and obviously supervisor to Stepwise-MLR.The correlations between spectra-predicted and chemically analyzed concentrations of nine bio-elements are statistically significant,and the concentration-versusdepth profiles predicted from reflectance spectra using PLS calibration model are consistent with those from actual chemical analysis.These results demonstrated the feasibility of using reflectance spectroscopy to infer bio-element concentrations in the ornithogenic sediments,and thus it is suggested that the reflectance spectroscopy could provide a rapid and valuable technique to indirectly identify whether the sediments were influenced by penguin droppings in the Antarctic region.

In vivo percutaneous reflectance spectroscopy of fatty liver development in rats suggests that the elevation of the scattering power is an early indicator of hepatic steatosis

This study assessed whether there was a scat tering spectral mar ker quantifiable by reflectance measurements that could indicate early development of hepatic steatosis in rats for potential applications to pre procurement organ evaluation.Sixteen rats were fed a methionine choline-deficient(MCD)diet and eight rats were fed a normal diet.Direct assessment of the liver parenchyma of rats in vivo was performed by percut aneous reflect ance spectroscopy using a single fiber probe at the beginning of diet-intake and arbitrary post-diet-intake times up to 11 weeks to render longitudinal comparison.Histological sampling of the liver over the duration of diet adm inistration was performed on two MCD diet treated rats and one control rat eutha-nized after reflectance spectroscopy measurement.The images of hematoxylin/eosin-stained liver specimens were analyzed morphometrically to evahuate the lipid size changes associated with the level of steatosis.The MCD-diet-treated group(n=16)had mild steatosis in seven rats,moderate in three rats,severe in six rats,and no other significant pathology.No control rats(n=8)developed hepatic steatosis.Among the parameters retrieved from per-SfS,only the scat tering power(can be either positive or negative)appeared to be statist ically diferent between MCD-treated and control livers.The scattering power for the 16 MCD-diet-treated livers at the time of euthanasia and presenting various levels of steatosis was 033±0.21,in comparison to 0.036±0.25 of the eight control livers(p=0.0189).When evaluated at days 12 and 13 combined,the scattering power of the 16 MCD-diet-treated livers was 032±0.17,in comparison to 0.10±0.11 of the eight control livers(p=0.0017).All of four MCD-treated livers harvested at days 12 and 13 presented mild steatosis with sub-micron size lipid droplets,even though none of the MCD-treated livers were sonogr aphically remarkable for fatty changes.The elevation of the scattering power may be a valuable marker indicating early hepatic steatosis before the steatosis is sonographically detectable.

RAPID DETERMINATION OF PROTEIN IN MILLET BY FOURIER TRANSFORM NEAR-INFRARED(FTNIR)DIFFUSE REFLECTANCE SPECTROSCOPY

In this paper,the Fourier transform near-infrared(FTNIR)diffuse reflectance spectroscopy is applied for the rapid determination of protein in millet.The partial least-squares(PLS)regression is successfully used as an effective multivariate calibration technique.The calibration set is composed of 20 standard millet samples that the protein contents were determined by the traditional Kjeldahl method.The optimal model dimension is found to be 5 by cross-validation.22 millet samples were determined by the proposed FTNIR-PLS method.The correlation coefficient between the concentration values obtained by the FTNIR-PLS method and the traditional Kjeldahl method is 0.9805.The standard error of prediction(SEP)is 0.28% and the mean recovery is 100.2%.The proposed method has been successfully applied for the routine analysis of protein in about 10,000 grain samples.

Determination of the Biodiesel Content in Petrodiesel/Biodiesel Blends: A Method Based on Uv-Visible Spectroscopy and Chemometrics Tools

In this work, we developed an analytical method based on UV-visible spectroscopy to determine the concentration of biodiesel from African palm in blends of petrodiesel. Seventy-five samples with biodiesel concentrations between 0-100 wt% were prepared. The spectral fingerprints that were obtained from the analysis of the samples by UV-visible spectroscopy were used to build predictive model using PLS regression. The predictive ability of the models was evaluated through statistical parameters: the standard error of calibration (SEC), the standard error of validation (SEV), the correlation coefficient of calibration (r Cal) and validation (r Val), the ratio (SEC/SEV), the coefficient of determination R2, the paired data Student’s t-test, cross-validation and external validation. The results indicate that the PLS model predicts the concentration of biodiesel from African palm with high precision in mixtures with petrodiesel. The method developed in this study can be applied to determine the concentration of biodiesel African palm in mixtures of petrodiesel in a more rapid and economical way. Moreover, this method has less analytical errors and is more environmentally friendly than the conventional methods.

Determination of the Deep Optical Properties of Healthy and Diseased Skin Using Diffuse Reflectance Spectroscopy

In this study, we focused on diffuse reflectance spectroscopy, a rapid and noninvasive spectroscopy technique that has considerable potential for medical diagnosis. In order to better understand and analyze the signals induced by this method, we performed a series of in vivo measurements on healthy and diseased skin. Measurement sites on a human hand and feet were chosen. Some preliminary results obtained on these sites show the feasibility of this technique in clinics.