To quantify the pore characteristics of various macerals in Chang 7 lacustrine shales,macerals were effectively identified according to their optical and morphological characteristics,and the nanoscale pore structure ...To quantify the pore characteristics of various macerals in Chang 7 lacustrine shales,macerals were effectively identified according to their optical and morphological characteristics,and the nanoscale pore structure of macerals was observed by scanning electron microscope.Meanwhile,the reflectances of different positions in the same pieces of vitrinite or solid bitumen with heterogeneous pores development were measured.The results showed that the average contents of sapropelinite,liptinite,vitrinite,inertinite and solid bitumen are 42.7%,8.7%,13.6%,13.8% and 21.2%,respectively,which suggests that the source of the organic matter of the Chang 7 shales is a mixed source input.The organic pores of Chang 7 shales are enriched,and the pore shapes are mostly round or elliptical.The pore size of organic pores has a wide distribution,mainly concentrate in the range of 100-400 nm,and the average plane porosity of organic pores is 10.13%.The size order of the organic pores in various macerals is:solid bitumen<bituminite<alginite<vitrinite<fusinite<liptinite.The abundance order of organic matter pores of each maceral is as follows:alginite>fusinite>bituminite>solid bitumen>vitrinite>liptinite.OM pores are mainly contributed by bituminite,solid bitumen and fusinite.The plane porosity of bituminite increases with maturity.In the process of thermal evolution,the plane porosity of fusinite is distributed in the two ranges of 20%-28% and 1%-7%.The former is mainly the primary pores of the fusinite itself,and the latter is the secondary pores formed in the thermal evolution.As for the organic pores of other macerals,no obvious thermal evolution law was found.Meanwhile,the surface imperfections of vitrinite or solid bitumen is enhanced by the enrichment of organic pores(an increase in pore size or pore number),which may result in the underestimation of their reflectances.展开更多
The process of wound healing is routinely evaluated by histological evaluation in the clinic,which may cause scarring and secondary injury.Reflectance confocal microscopy(RCM)represents a noninvasive,real-time imaging...The process of wound healing is routinely evaluated by histological evaluation in the clinic,which may cause scarring and secondary injury.Reflectance confocal microscopy(RCM)represents a noninvasive,real-time imaging technique that allows in vivo evaluation of the skin.Traditional RCM was wide-probe-based,which limited its application on uneven and covered skin.In this study,we report the development of a portable reflectance confocal microscope(PRCM)in which all components were assembled in a handheld shell.Although the size and weight of the PRCM were reduced based on the use of a microelectromechanical system,the resolution was kept at 0.91μm,and the field of view of the system was 343μm×532μm.When used in vivo,the PRCM was able to visualize cellular and nuclear morphology for both mouse and human skin.PRCM evaluations were then performed on wounds after topically applied mesenchymal stem cells(MSCs)or saline treatment.The PRCM allowed visualization of the formation of collagen bundles,re-epithelization from the wound edge to the wound bed,and hair follicle regeneration,which were consistent with histological evaluations.Therefore,we offer new insights into monitoring the effects of topically applied MSCs on the process of wound healing by using PRCM.This study illustrates that the newly developed PRCM represents a promising device for real-time,noninvasive monitoring of the dynamic process of wound healing,which demonstrates its potential to diagnose,monitor,or predict disease in clinical wound therapy.展开更多
Rice yellow mottle is considered the most destructive disease threatening rice production in Africa. Early detection of this infection in rice is essential to limit its expansion and proliferation. However, there is n...Rice yellow mottle is considered the most destructive disease threatening rice production in Africa. Early detection of this infection in rice is essential to limit its expansion and proliferation. However, there is no research devoted to the spectral detection of rice yellow mottle virus (RYMV) infection, especially in the asymptomatic or early stages. This work proposes the use of hyperspectral fluorescence and reflectance data at leaf level for the detection of this disease in asymptomatic stages. A greenhouse experiment was therefore conducted to collect hyperspectral fluorescence and reflectance data at different stages of infection. These data allowed to calculate nine vegetation indices: one from fluorescence spectra and eight from reflectance spectra. A t-test made it possible to identify, from the second day after infection, four relevant reflectance vegetation indices to discriminate healthy leaves from those infected: these are Photochemical Reflectance Index (PRI), Transformed Chlorophyll Absorption in Reflectance Index (TCARI), Structure Intensive Pigment Index (SIPI) and Simple Ratio Pigment Index (SRPI). The fluorescence index was less sensitive in detecting infection. The four significant vegetation indices for the detection of RYMV were then used to build and evaluate models for discriminating plants according to their health status by the supervised classification of support vector machine (SVM) at different stages of infection. The maximum overall accuracy is 92.5% six days after inoculation (6 DAI). The sixth day after inoculation would be the adequate day to detect RYMV. This plants discrimination was validated by the mean reflectance spectra and by the histograms showing the differences between the average reflectance vegetation indices values of the two types of plants. Our results demonstrate the feasibility of differentiating RYMV-infected samples. They suggest that support vector machine learning models could be developed to diagnose RYMV-infected plants based on vegetation indices derived from spectral profiles at early stages of disease development.展开更多
A spectral reflectance sensor(SRS)fixed on the near-surface ground was developed to support the continuous monitoring of vegetation indices such as the normalized difference vegetation index(NDVI)and photochemical ref...A spectral reflectance sensor(SRS)fixed on the near-surface ground was developed to support the continuous monitoring of vegetation indices such as the normalized difference vegetation index(NDVI)and photochemical reflectance index(PRI).NDVI is useful for indicating crop growth/phenology,whereas PRI was developed for observing physiological conditions.Thus,the seasonal change patterns of NDVI and PRI are two valuable pieces of information in a crop-monitoring system.However,capturing the seasonal patterns is considered challenging because the vegetation index values estimated by the reflection from vegetation are often governed by meteorological conditions,such as solar irradiance and precipitation.Further,unlike growth/phenology,the physiological condition has diurnal changes as well as seasonal characteristics.This study proposed a novel filtering method for extracting the seasonal signals of SRS-based NDVI and PRI in paddy rice,barley,and garlic.First,the measurement accuracy of SRSs was compared with handheld spectrometers,and the R^(2)values between the two devices were 0.96 and 0.81 for NDVI and PRI,respectively.Second,the experimental study of threshold criteria with respect to meteorological variables(i.e.,insolation,cloudiness,sunshine duration,and precipitation)was conducted,and sunshine duration was the most useful one for excluding distorted values of the vegetation indices.After data processing based on sunshine duration,the R^(2)values between the measured vegetation indices and the extracted seasonal signals of vegetation indices increased by approximately 0.002–0.004(NDVI)and 0.065–0.298(PRI)on the three crops,and the seasonal signals of vegetation indices became noticeably improved.This method will contribute to an agricultural monitoring system by identifying the seasonal changes in crop growth and physiological conditions.展开更多
The resource of the gas from coal and coal measures deep in Songliao Basin hasbeen drawing more and more attention to.It is necessary to find out the evolution regulari-ty of the geothermal field of the basin in addit...The resource of the gas from coal and coal measures deep in Songliao Basin hasbeen drawing more and more attention to.It is necessary to find out the evolution regulari-ty of the geothermal field of the basin in addition to a series of geological studies in orderto predict its resources because the ancient geothermal field of the basin is one of themain factors controlling the generation,evolution and disappearance of oil and gas.Inthe recent twenty years,it is generally believed that vitrinite reflectance is the best quanti-tative marker for the ancient geothermal field.In the present paper,a systematic studyof the vitrinite reflectance value of Songliao Basin and its influence factors is made by mul-tiple statistical analysis so as to reconstruct the evolutional process of the Moho and thecorresponding geothermal field.Then,an overall prediction is made of the vitrinitereflectance and the distribution of J<sub>3</sub>-K<sub>1</sub> fault basin group at the bottom of SongliaoBasin,which provides the evidence for the展开更多
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...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(RSQ_(cal)), cross-validation(R^2_(CV)), and validation(RSQ_v) 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 RSQ_(cal), R^2_(CV), 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.展开更多
Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced tech...Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced technologies are used to efficiently and accurately assess the status of salinization processes. Case studies to determine the relations between particular types of salinization and their spectral reflectances are essential because of the distinctive characteristics of the reflectance spectra of particular salts. During April 2015 we collected surface soil samples(0–10 cm depth) at 64 field sites in the downstream area of Minqin Oasis in Northwest China, an area that is undergoing serious salinization. We developed a linear model for determination of salt content in soil from hyperspectral data as follows. First, we undertook chemical analysis of the soil samples to determine their soluble salt contents. We then measured the reflectance spectra of the soil samples, which we post-processed using a continuum-removed reflectance algorithm to enhance the absorption features and better discriminate subtle differences in spectral features. We applied a normalized difference salinity index to the continuum-removed hyperspectral data to obtain all possible waveband pairs. Correlation of the indices obtained for all of the waveband pairs with the wavebands corresponding to measured soil salinities showed that two wavebands centred at wavelengths of 1358 and 2382 nm had the highest sensitivity to salinity. We then applied the linear regression modelling to the data from half of the soil samples to develop a soil salinity index for the relationships between wavebands and laboratory measured soluble salt content. We used the hyperspectral data from the remaining samples to validate the model. The salt content in soil from Minqin Oasis were well produced by the model. Our results indicate that wavelengths at 1358 and 2382 nm are the optimal wavebands for monitoring the concentrations of chlorine and sulphate compounds, the predominant salts at Minqin Oasis. Our modelling provides a reference for future case studies on the use of hyperspectral data for predictive quantitative estimation of salt content in soils in arid regions. Further research is warranted on the application of this method to remotely sensed hyperspectral data to investigate its potential use for large-scale mapping of the extent and severity of soil salinity.展开更多
Based on studies of the reflectance of Ordovician and Silurian zooclasts from 11 sections around the Huangling Anticline, Hubei, China, combined with determination of the conodont colour alteration indices (CAI) and o...Based on studies of the reflectance of Ordovician and Silurian zooclasts from 11 sections around the Huangling Anticline, Hubei, China, combined with determination of the conodont colour alteration indices (CAI) and of infrared spectroscopy of dispersed organic matter from the same or adjacent horizons, it is further proved that reflectances of graptolites, chitinozoans and scolecldonts, like vitrinite and natural bitumen, increase with increasing maturation, but follow different reflectance paths. They may be used, therefore, as thermal maturation indicators. Graptolites display optically strong anisotropy. The maximum reflectance measured from graptolite on polished section cut parallel to the bedding plane is the most suitable for determination of maturation of their host rocks. In polished section chitinozoan and scolecodont show reflectance, but no bireflectance owing to their isotropy. The random reflectance of chitinozoans is higher than that of scolecodonts in the case of the same maturity. By analysing the distribution trends of graptolite, chitionzoan and scolecodont reflectances, the Ordovician and Silurian strata can be subdivided into three areas of maturation in the present region. The potential of oil or gas generation is discussed for each area. The result is basically coincident with the distribution pattern of regional organic maturation presented by CAI and infrared spectroscopic determination of organic matter.展开更多
This research developed estimates of plant crown transpiration and water-use-efficiency using reflectance and derivative indices extracted from remotely sensed chlorophyll fluorescence measurements under natural condi...This research developed estimates of plant crown transpiration and water-use-efficiency using reflectance and derivative indices extracted from remotely sensed chlorophyll fluorescence measurements under natural conditions. Diurnal changes of leaf-level gas exchange (carbon assimilation rate (A), stomatal conductance (gs), transpiration rate (E)), chlorophyll fluorescence and canopy-scale remote sensing were measured on top crown of valley oak (Quercus lobata) in the foothills of central California, USA. The results indicated Q. lobata experienced saturating irradiance (PAR), which induced photoinhibition indicated by a decrease in the quantum efficiency of photosystem II (r2 = 0.648 with Fv ′/Fm′ and r2 = 0.73 with FPSII) and open reaction centers (qP;r2 = 0.699). The excess absorbed quantum energy was dissipated as heat through the Xanthophyll cycle and other processes (photorespiration and the water-water cycle) rather than energy emission as steady state chlorophyll fluorescence (Fs). An increase in leaf temperature caused by the activity of Xanthophyll cycle was correlated to a decrease in Fs (r2 = 0.381) and an increase in evaporative cooling through E (r2 = 0.800) and water use efficiency (WUE;r2 = 0.872).展开更多
Based on the models developed by Lerche et al. (1984) and Pang et al. (1993), an improved model for calculating paleoheat flow into basins is investigated. The new model is an optimization problem with the state varia...Based on the models developed by Lerche et al. (1984) and Pang et al. (1993), an improved model for calculating paleoheat flow into basins is investigated. The new model is an optimization problem with the state variables governed by a thermal conduction equation. A genetic algorithm is used to solve the highly nonlinear optimization problem. As an application, the model is applied to the research into the history of heat flow in the Pearl River Mouth basin located in the South China Sea. The numerical analysis shows that the simulation results are in good agreement with the measured data and indicates that the basin may have undergone three rifting and thermal events. It is also demonstrated that a high R0 gradient reflects a response to high paleoheat flow during the early, rapid subsidence stage, while a low R0 gradient is a result of the thermal decay during the thermal subsidence because of thermal contraction of a cooling lithosphere.展开更多
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 ...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.展开更多
Assessing canopy nitrogen content(CNC) and canopy carbon content(CCC) of maize by hyperspectral remote sensing data permits estimating cropland productivity, protecting farmland ecology, and investigating the nitrogen...Assessing canopy nitrogen content(CNC) and canopy carbon content(CCC) of maize by hyperspectral remote sensing data permits estimating cropland productivity, protecting farmland ecology, and investigating the nitrogen and carbon cycles in the atmosphere. This study aimed to assess maize CNC and CCC using canopy hyperspectral information and uninformative variable elimination(UVE). Vegetation indices(VIs) and wavelet functions were adopted for estimating CNC and CCC under varying water and nitrogen regimes. Linear, nonlinear, and partial least squares(PLS) regression models were fitted to VIs and wavelet functions to estimate CNC and CCC, and were evaluated for their prediction accuracy.UVE was used to eliminate uninformative variables, improve the prediction accuracy of the models, and simplify the PLS regression models(UVE-PLS). For estimating CNC and CCC, the normalized difference vegetation index(NDVI, based on red edge and NIR wavebands) yielded the highest correlation coefficients(r > 0.88). PLS regression models showed the lowest root mean square error(RMSE) among all models. However, PLS regression models required nine VIs and four wavelet functions, increasing their complexity. UVE was used to retain valid spectral parameters and optimize the PLS regression models.UVE-PLS regression models improved validation accuracy and resulted in more accurate CNC and CCC than the PLS regression models. Thus, canopy spectral reflectance integrated with UVE-PLS can accurately reflect maize leaf nitrogen and carbon status.展开更多
Ultraviolet-visible UV-Vis diffuse reflectance measurements of irradiated lithium tetra-borate glass have been acquired using. Evolution 600 Spectrophotometer equipped with praying Mantis Diffuse Reflectance Accessory...Ultraviolet-visible UV-Vis diffuse reflectance measurements of irradiated lithium tetra-borate glass have been acquired using. Evolution 600 Spectrophotometer equipped with praying Mantis Diffuse Reflectance Accessory DRA base upon the onset of the diffuse reflectance spectra of the powdered or bulk materials. Also the absorption edge and band gap energies of the prepared glass were determined. The optical energy gap is calculated and found to be (3.0 - 3.5) eV. Which is in close agreement to the one calculated for r = 1/2, i.e. the transition mechanism, is accordingly direct allowed transition. The density increases from 3.1 to 3.9 gm/cm3 for the undoped and doped glass.展开更多
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 mod...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.展开更多
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 usi...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.展开更多
Rapid assessment of foliar chlorophyll content in tobacco is critical for assessment of growth and precise management to improve quality and yield while minimizing adverse environmental impact. Our objective is to dev...Rapid assessment of foliar chlorophyll content in tobacco is critical for assessment of growth and precise management to improve quality and yield while minimizing adverse environmental impact. Our objective is to develop a precise agricultural practice predicting tobacco-leaf chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> content. Reflectance experiments have been conducted on flue-cured tobacco over 3 consecutive years under different light quality. Leaf hyperspectral reflectance and chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> content data have been collected at 15-day intervals from 30 days after transplant until harvesting. We identified the central band that is sensitive to tobacco-leaf chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> content and the optimum wavelength combinations for establishing new spectral indices (simple ratio index, RVI;normalized difference vegetation index, NDVI;and simple difference vegetation index, DVI). We then established linear and BackPropagation (BP) neural network models to estimate chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> content. The central bands for leaf chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> content are concentrated in the visible range (410 - 680 nm) in combination with the shortwave infrared range (1900 - 2400 nm). The optimum spectral range for the spectral band combinations</span><span style="font-family:Verdana;"> RVI, NDVI, and DVI</span><span style="font-family:Verdana;"> are 440 and 470 nm, 440 and 470 nm, and 440 and 460 nm, respectively. The linear RVI, NDVI, and DVI models, SMLR model and the BP neural network model have respective R</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> values of 0.76, 0.77, 0.69, 0.78 and 0.86, and root mean square error values of 0.63, 1.60, 1.59, 2.04 and 0.05 mg chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;">/g (fresh weight), respectively. Our results identified chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> sensitive spectral regions and new indices facilitate a rapid, non-destructive field estimation of leaf chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> content for tobacco.展开更多
Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the ...Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the time at the 95% confidence level (p = 0.05 significance level). In the present study, cotton and silk had a 62% and 24% chance, respectively, of being classified with their own group and also with rayon. SIMCA correctly identified a counterfeit “silk” sample as polyester. When coupled with diffuse NIR reflectance spectroscopy and a large sample library, SIMCA shows considerable promise as a quick, non-destructive, multivariate method for fiber identification. A major advantage is simplicity. No sample pretreatment of any kind was required, and no adjust-ments were made for fiber origin, manufacturing process residues, topical finishes, weave pattern, or dye content. Increasing the sample library should make the models more robust and improve identification rates over those reported in this paper.展开更多
Emerald is a green(Cr-bearing)variety of beryl.It has also been one of the highest value and highly demanded gemstones in the world.For this reason,the methods for synthesis emerald(i.e.,hydrothermal,flux grown)have b...Emerald is a green(Cr-bearing)variety of beryl.It has also been one of the highest value and highly demanded gemstones in the world.For this reason,the methods for synthesis emerald(i.e.,hydrothermal,flux grown)have been constantly developed.In many cases,it is hard to distinguish the natural emerald from the synthetic one using the basic instruments.Therefore,with the advantage of non-destructive technique,the infrared spectroscopy has been efficiently applied for the task.In this study,to find the potential technique in FTIR spectroscopy for classifying between natural and synthetic emerald(hydrothermal and flux-grown),the observed spectra from the Attenuated Total Reflectance Radiation(ATR),Diffuse Reflectance(DRIFT),transflectance,and specular reflection techniques were compared.The result showed that the spectra obtained from the transflectance and the DRIFT techniques were similar with equal spectral qualities.Unlike the diffuse reflectance spectra,the transflectance spectra were not affected by the sample orientations.The spectral features associated with water molecule in the crystal structure were clearly observed in both the DRIFT and transflectance spectra.Although the spectral features associated with weak absorption bands of water were not observed in both the DRIFT and transflectance spectra,the position of strong absorption band at 3 800-3 500 cm^(-1) and 1 635 cm^(-1) could be detected in the ATR spectra.In addition,the lack of absorption of water between 4 000 and 3 400 cm^(-1) in flux-grown emerald samples is the clue to separate it from the natural and hydrothermal one.In the meantime,the absence of the strong absorption peaks between 2 300 and 1 400 cm^(-1) in hydrothermal emerald can differentiate it from the natural one.展开更多
基金This project was funded by the National Natural Science Foundation of China(41972161)the 2021 American Association of Petroleum Geologists Foundation Grants-in-Aid Program and Science and Technology Cooperation Project of the CNPC-SWPU Innovation Alliance(2020CX050103).
文摘To quantify the pore characteristics of various macerals in Chang 7 lacustrine shales,macerals were effectively identified according to their optical and morphological characteristics,and the nanoscale pore structure of macerals was observed by scanning electron microscope.Meanwhile,the reflectances of different positions in the same pieces of vitrinite or solid bitumen with heterogeneous pores development were measured.The results showed that the average contents of sapropelinite,liptinite,vitrinite,inertinite and solid bitumen are 42.7%,8.7%,13.6%,13.8% and 21.2%,respectively,which suggests that the source of the organic matter of the Chang 7 shales is a mixed source input.The organic pores of Chang 7 shales are enriched,and the pore shapes are mostly round or elliptical.The pore size of organic pores has a wide distribution,mainly concentrate in the range of 100-400 nm,and the average plane porosity of organic pores is 10.13%.The size order of the organic pores in various macerals is:solid bitumen<bituminite<alginite<vitrinite<fusinite<liptinite.The abundance order of organic matter pores of each maceral is as follows:alginite>fusinite>bituminite>solid bitumen>vitrinite>liptinite.OM pores are mainly contributed by bituminite,solid bitumen and fusinite.The plane porosity of bituminite increases with maturity.In the process of thermal evolution,the plane porosity of fusinite is distributed in the two ranges of 20%-28% and 1%-7%.The former is mainly the primary pores of the fusinite itself,and the latter is the secondary pores formed in the thermal evolution.As for the organic pores of other macerals,no obvious thermal evolution law was found.Meanwhile,the surface imperfections of vitrinite or solid bitumen is enhanced by the enrichment of organic pores(an increase in pore size or pore number),which may result in the underestimation of their reflectances.
基金the National Key Research andDevelopment Program of China(No.2021YFA1101100)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA16020807)+3 种基金the Major Innovative Research Team of Suzhou,China(No.ZXT2019007)Suzhou Institute of Biomedical Engineering and Technology(SIBET)Jilin City Science and Technology Cooperation Project(No.E0550104)Science and Technology Innovation Talents in Universities of Henan Province and Doctor of Entrepreneurship and Innovation Program of Jiangsu Province in the year of 2020.
文摘The process of wound healing is routinely evaluated by histological evaluation in the clinic,which may cause scarring and secondary injury.Reflectance confocal microscopy(RCM)represents a noninvasive,real-time imaging technique that allows in vivo evaluation of the skin.Traditional RCM was wide-probe-based,which limited its application on uneven and covered skin.In this study,we report the development of a portable reflectance confocal microscope(PRCM)in which all components were assembled in a handheld shell.Although the size and weight of the PRCM were reduced based on the use of a microelectromechanical system,the resolution was kept at 0.91μm,and the field of view of the system was 343μm×532μm.When used in vivo,the PRCM was able to visualize cellular and nuclear morphology for both mouse and human skin.PRCM evaluations were then performed on wounds after topically applied mesenchymal stem cells(MSCs)or saline treatment.The PRCM allowed visualization of the formation of collagen bundles,re-epithelization from the wound edge to the wound bed,and hair follicle regeneration,which were consistent with histological evaluations.Therefore,we offer new insights into monitoring the effects of topically applied MSCs on the process of wound healing by using PRCM.This study illustrates that the newly developed PRCM represents a promising device for real-time,noninvasive monitoring of the dynamic process of wound healing,which demonstrates its potential to diagnose,monitor,or predict disease in clinical wound therapy.
文摘Rice yellow mottle is considered the most destructive disease threatening rice production in Africa. Early detection of this infection in rice is essential to limit its expansion and proliferation. However, there is no research devoted to the spectral detection of rice yellow mottle virus (RYMV) infection, especially in the asymptomatic or early stages. This work proposes the use of hyperspectral fluorescence and reflectance data at leaf level for the detection of this disease in asymptomatic stages. A greenhouse experiment was therefore conducted to collect hyperspectral fluorescence and reflectance data at different stages of infection. These data allowed to calculate nine vegetation indices: one from fluorescence spectra and eight from reflectance spectra. A t-test made it possible to identify, from the second day after infection, four relevant reflectance vegetation indices to discriminate healthy leaves from those infected: these are Photochemical Reflectance Index (PRI), Transformed Chlorophyll Absorption in Reflectance Index (TCARI), Structure Intensive Pigment Index (SIPI) and Simple Ratio Pigment Index (SRPI). The fluorescence index was less sensitive in detecting infection. The four significant vegetation indices for the detection of RYMV were then used to build and evaluate models for discriminating plants according to their health status by the supervised classification of support vector machine (SVM) at different stages of infection. The maximum overall accuracy is 92.5% six days after inoculation (6 DAI). The sixth day after inoculation would be the adequate day to detect RYMV. This plants discrimination was validated by the mean reflectance spectra and by the histograms showing the differences between the average reflectance vegetation indices values of the two types of plants. Our results demonstrate the feasibility of differentiating RYMV-infected samples. They suggest that support vector machine learning models could be developed to diagnose RYMV-infected plants based on vegetation indices derived from spectral profiles at early stages of disease development.
基金supported by the Rural Development Administration(PJ013821032020),Republic of Korea。
文摘A spectral reflectance sensor(SRS)fixed on the near-surface ground was developed to support the continuous monitoring of vegetation indices such as the normalized difference vegetation index(NDVI)and photochemical reflectance index(PRI).NDVI is useful for indicating crop growth/phenology,whereas PRI was developed for observing physiological conditions.Thus,the seasonal change patterns of NDVI and PRI are two valuable pieces of information in a crop-monitoring system.However,capturing the seasonal patterns is considered challenging because the vegetation index values estimated by the reflection from vegetation are often governed by meteorological conditions,such as solar irradiance and precipitation.Further,unlike growth/phenology,the physiological condition has diurnal changes as well as seasonal characteristics.This study proposed a novel filtering method for extracting the seasonal signals of SRS-based NDVI and PRI in paddy rice,barley,and garlic.First,the measurement accuracy of SRSs was compared with handheld spectrometers,and the R^(2)values between the two devices were 0.96 and 0.81 for NDVI and PRI,respectively.Second,the experimental study of threshold criteria with respect to meteorological variables(i.e.,insolation,cloudiness,sunshine duration,and precipitation)was conducted,and sunshine duration was the most useful one for excluding distorted values of the vegetation indices.After data processing based on sunshine duration,the R^(2)values between the measured vegetation indices and the extracted seasonal signals of vegetation indices increased by approximately 0.002–0.004(NDVI)and 0.065–0.298(PRI)on the three crops,and the seasonal signals of vegetation indices became noticeably improved.This method will contribute to an agricultural monitoring system by identifying the seasonal changes in crop growth and physiological conditions.
文摘The resource of the gas from coal and coal measures deep in Songliao Basin hasbeen drawing more and more attention to.It is necessary to find out the evolution regulari-ty of the geothermal field of the basin in addition to a series of geological studies in orderto predict its resources because the ancient geothermal field of the basin is one of themain factors controlling the generation,evolution and disappearance of oil and gas.Inthe recent twenty years,it is generally believed that vitrinite reflectance is the best quanti-tative marker for the ancient geothermal field.In the present paper,a systematic studyof the vitrinite reflectance value of Songliao Basin and its influence factors is made by mul-tiple statistical analysis so as to reconstruct the evolutional process of the Moho and thecorresponding geothermal field.Then,an overall prediction is made of the vitrinitereflectance and the distribution of J<sub>3</sub>-K<sub>1</sub> fault basin group at the bottom of SongliaoBasin,which provides the evidence for the
基金financially supported by China Special Public Sector Fund in Agriculture(200903006)The collection of data and analysis were funded by National Key Technology Research and Development Program(2011BAD26B0404)The interpretation of data and writing of the manuscript were supported by 111 Project(B16044)
文摘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(RSQ_(cal)), cross-validation(R^2_(CV)), and validation(RSQ_v) 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 RSQ_(cal), R^2_(CV), 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.
基金supported by the International Platform for Dryland Research and Education, Tottori University and the National Key R&D Program of China (2016YFC0500909)
文摘Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced technologies are used to efficiently and accurately assess the status of salinization processes. Case studies to determine the relations between particular types of salinization and their spectral reflectances are essential because of the distinctive characteristics of the reflectance spectra of particular salts. During April 2015 we collected surface soil samples(0–10 cm depth) at 64 field sites in the downstream area of Minqin Oasis in Northwest China, an area that is undergoing serious salinization. We developed a linear model for determination of salt content in soil from hyperspectral data as follows. First, we undertook chemical analysis of the soil samples to determine their soluble salt contents. We then measured the reflectance spectra of the soil samples, which we post-processed using a continuum-removed reflectance algorithm to enhance the absorption features and better discriminate subtle differences in spectral features. We applied a normalized difference salinity index to the continuum-removed hyperspectral data to obtain all possible waveband pairs. Correlation of the indices obtained for all of the waveband pairs with the wavebands corresponding to measured soil salinities showed that two wavebands centred at wavelengths of 1358 and 2382 nm had the highest sensitivity to salinity. We then applied the linear regression modelling to the data from half of the soil samples to develop a soil salinity index for the relationships between wavebands and laboratory measured soluble salt content. We used the hyperspectral data from the remaining samples to validate the model. The salt content in soil from Minqin Oasis were well produced by the model. Our results indicate that wavelengths at 1358 and 2382 nm are the optimal wavebands for monitoring the concentrations of chlorine and sulphate compounds, the predominant salts at Minqin Oasis. Our modelling provides a reference for future case studies on the use of hyperspectral data for predictive quantitative estimation of salt content in soils in arid regions. Further research is warranted on the application of this method to remotely sensed hyperspectral data to investigate its potential use for large-scale mapping of the extent and severity of soil salinity.
文摘Based on studies of the reflectance of Ordovician and Silurian zooclasts from 11 sections around the Huangling Anticline, Hubei, China, combined with determination of the conodont colour alteration indices (CAI) and of infrared spectroscopy of dispersed organic matter from the same or adjacent horizons, it is further proved that reflectances of graptolites, chitinozoans and scolecldonts, like vitrinite and natural bitumen, increase with increasing maturation, but follow different reflectance paths. They may be used, therefore, as thermal maturation indicators. Graptolites display optically strong anisotropy. The maximum reflectance measured from graptolite on polished section cut parallel to the bedding plane is the most suitable for determination of maturation of their host rocks. In polished section chitinozoan and scolecodont show reflectance, but no bireflectance owing to their isotropy. The random reflectance of chitinozoans is higher than that of scolecodonts in the case of the same maturity. By analysing the distribution trends of graptolite, chitionzoan and scolecodont reflectances, the Ordovician and Silurian strata can be subdivided into three areas of maturation in the present region. The potential of oil or gas generation is discussed for each area. The result is basically coincident with the distribution pattern of regional organic maturation presented by CAI and infrared spectroscopic determination of organic matter.
文摘This research developed estimates of plant crown transpiration and water-use-efficiency using reflectance and derivative indices extracted from remotely sensed chlorophyll fluorescence measurements under natural conditions. Diurnal changes of leaf-level gas exchange (carbon assimilation rate (A), stomatal conductance (gs), transpiration rate (E)), chlorophyll fluorescence and canopy-scale remote sensing were measured on top crown of valley oak (Quercus lobata) in the foothills of central California, USA. The results indicated Q. lobata experienced saturating irradiance (PAR), which induced photoinhibition indicated by a decrease in the quantum efficiency of photosystem II (r2 = 0.648 with Fv ′/Fm′ and r2 = 0.73 with FPSII) and open reaction centers (qP;r2 = 0.699). The excess absorbed quantum energy was dissipated as heat through the Xanthophyll cycle and other processes (photorespiration and the water-water cycle) rather than energy emission as steady state chlorophyll fluorescence (Fs). An increase in leaf temperature caused by the activity of Xanthophyll cycle was correlated to a decrease in Fs (r2 = 0.381) and an increase in evaporative cooling through E (r2 = 0.800) and water use efficiency (WUE;r2 = 0.872).
基金This paper is supported by China Offshore Petroleum Exploration Development Corporation.
文摘Based on the models developed by Lerche et al. (1984) and Pang et al. (1993), an improved model for calculating paleoheat flow into basins is investigated. The new model is an optimization problem with the state variables governed by a thermal conduction equation. A genetic algorithm is used to solve the highly nonlinear optimization problem. As an application, the model is applied to the research into the history of heat flow in the Pearl River Mouth basin located in the South China Sea. The numerical analysis shows that the simulation results are in good agreement with the measured data and indicates that the basin may have undergone three rifting and thermal events. It is also demonstrated that a high R0 gradient reflects a response to high paleoheat flow during the early, rapid subsidence stage, while a low R0 gradient is a result of the thermal decay during the thermal subsidence because of thermal contraction of a cooling lithosphere.
基金partially supported by the Graduate Student Research Grants from the Gulf Coast Association of Geological Societies (GCAGS)American Association of Petroleum Geologist (AAPG)by the University of Texas at Arlington and by the Pioneer Natural Resources
文摘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.
基金supported by the National Key Research and Development Program of China (2016YFD0300602)China Agricultural Research System (CARS-04-PS19)Chengdu Science and Technology Project (2020-YF09-00033-SN)。
文摘Assessing canopy nitrogen content(CNC) and canopy carbon content(CCC) of maize by hyperspectral remote sensing data permits estimating cropland productivity, protecting farmland ecology, and investigating the nitrogen and carbon cycles in the atmosphere. This study aimed to assess maize CNC and CCC using canopy hyperspectral information and uninformative variable elimination(UVE). Vegetation indices(VIs) and wavelet functions were adopted for estimating CNC and CCC under varying water and nitrogen regimes. Linear, nonlinear, and partial least squares(PLS) regression models were fitted to VIs and wavelet functions to estimate CNC and CCC, and were evaluated for their prediction accuracy.UVE was used to eliminate uninformative variables, improve the prediction accuracy of the models, and simplify the PLS regression models(UVE-PLS). For estimating CNC and CCC, the normalized difference vegetation index(NDVI, based on red edge and NIR wavebands) yielded the highest correlation coefficients(r > 0.88). PLS regression models showed the lowest root mean square error(RMSE) among all models. However, PLS regression models required nine VIs and four wavelet functions, increasing their complexity. UVE was used to retain valid spectral parameters and optimize the PLS regression models.UVE-PLS regression models improved validation accuracy and resulted in more accurate CNC and CCC than the PLS regression models. Thus, canopy spectral reflectance integrated with UVE-PLS can accurately reflect maize leaf nitrogen and carbon status.
文摘Ultraviolet-visible UV-Vis diffuse reflectance measurements of irradiated lithium tetra-borate glass have been acquired using. Evolution 600 Spectrophotometer equipped with praying Mantis Diffuse Reflectance Accessory DRA base upon the onset of the diffuse reflectance spectra of the powdered or bulk materials. Also the absorption edge and band gap energies of the prepared glass were determined. The optical energy gap is calculated and found to be (3.0 - 3.5) eV. Which is in close agreement to the one calculated for r = 1/2, i.e. the transition mechanism, is accordingly direct allowed transition. The density increases from 3.1 to 3.9 gm/cm3 for the undoped and doped glass.
文摘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.
文摘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.
文摘Rapid assessment of foliar chlorophyll content in tobacco is critical for assessment of growth and precise management to improve quality and yield while minimizing adverse environmental impact. Our objective is to develop a precise agricultural practice predicting tobacco-leaf chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> content. Reflectance experiments have been conducted on flue-cured tobacco over 3 consecutive years under different light quality. Leaf hyperspectral reflectance and chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> content data have been collected at 15-day intervals from 30 days after transplant until harvesting. We identified the central band that is sensitive to tobacco-leaf chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> content and the optimum wavelength combinations for establishing new spectral indices (simple ratio index, RVI;normalized difference vegetation index, NDVI;and simple difference vegetation index, DVI). We then established linear and BackPropagation (BP) neural network models to estimate chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> content. The central bands for leaf chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> content are concentrated in the visible range (410 - 680 nm) in combination with the shortwave infrared range (1900 - 2400 nm). The optimum spectral range for the spectral band combinations</span><span style="font-family:Verdana;"> RVI, NDVI, and DVI</span><span style="font-family:Verdana;"> are 440 and 470 nm, 440 and 470 nm, and 440 and 460 nm, respectively. The linear RVI, NDVI, and DVI models, SMLR model and the BP neural network model have respective R</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> values of 0.76, 0.77, 0.69, 0.78 and 0.86, and root mean square error values of 0.63, 1.60, 1.59, 2.04 and 0.05 mg chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;">/g (fresh weight), respectively. Our results identified chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> sensitive spectral regions and new indices facilitate a rapid, non-destructive field estimation of leaf chlorophyll-</span><i><span style="font-family:Verdana;">a</span></i><span style="font-family:Verdana;"> content for tobacco.
文摘Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the time at the 95% confidence level (p = 0.05 significance level). In the present study, cotton and silk had a 62% and 24% chance, respectively, of being classified with their own group and also with rayon. SIMCA correctly identified a counterfeit “silk” sample as polyester. When coupled with diffuse NIR reflectance spectroscopy and a large sample library, SIMCA shows considerable promise as a quick, non-destructive, multivariate method for fiber identification. A major advantage is simplicity. No sample pretreatment of any kind was required, and no adjust-ments were made for fiber origin, manufacturing process residues, topical finishes, weave pattern, or dye content. Increasing the sample library should make the models more robust and improve identification rates over those reported in this paper.
文摘Emerald is a green(Cr-bearing)variety of beryl.It has also been one of the highest value and highly demanded gemstones in the world.For this reason,the methods for synthesis emerald(i.e.,hydrothermal,flux grown)have been constantly developed.In many cases,it is hard to distinguish the natural emerald from the synthetic one using the basic instruments.Therefore,with the advantage of non-destructive technique,the infrared spectroscopy has been efficiently applied for the task.In this study,to find the potential technique in FTIR spectroscopy for classifying between natural and synthetic emerald(hydrothermal and flux-grown),the observed spectra from the Attenuated Total Reflectance Radiation(ATR),Diffuse Reflectance(DRIFT),transflectance,and specular reflection techniques were compared.The result showed that the spectra obtained from the transflectance and the DRIFT techniques were similar with equal spectral qualities.Unlike the diffuse reflectance spectra,the transflectance spectra were not affected by the sample orientations.The spectral features associated with water molecule in the crystal structure were clearly observed in both the DRIFT and transflectance spectra.Although the spectral features associated with weak absorption bands of water were not observed in both the DRIFT and transflectance spectra,the position of strong absorption band at 3 800-3 500 cm^(-1) and 1 635 cm^(-1) could be detected in the ATR spectra.In addition,the lack of absorption of water between 4 000 and 3 400 cm^(-1) in flux-grown emerald samples is the clue to separate it from the natural and hydrothermal one.In the meantime,the absence of the strong absorption peaks between 2 300 and 1 400 cm^(-1) in hydrothermal emerald can differentiate it from the natural one.
