Laboratory Spectrometer Research Articles

X‐Ray Absorption and X‐Ray Emission Spectroscopy Study of a Molybdenum Disulfide Anode in a Sodium‐Ion Half‐Cell

The development of efficient anodes for sodium‐ion batteries requires a deep understanding of the electrochemical processes involved. Herein, X‐ray spectroscopy is used to study changes in the electronic structure of MoS2 nanosheets coupled with few‐layered graphene at early stages of battery life. Working electrode is combined with a sodium plate and a solution of NaClO4 in ethyl carbonate/dimethyl carbonate in a homemade cell having an X‐ray transparent window. X‐ray absorption spectra at the S K‐edge and Mo L3‐edge are recorded using a synchrotron source, X‐ray emission S Kα and Mo Lα spectra are obtained on a laboratory spectrometer for initial powder and electrode material at different potentials of the cell. Analysis of the spectra shows the occupation of the initially empty orbitals of MoS2 by sodium electrons as a result of the interaction of the components of the sodium‐ion half‐cell. Ex situ X‐ray photoelectron spectroscopy measurements of a fully discharged electrode material reveal partial transformation of hexagonal MoS2 to disordered tetragonal MoS2 coated with a surface electrolyte interphase layer. The obtained results indicate that coupling MoS2 to graphene prevents the breaking of Mo–S bonds when Na+ ions are first introduced, which may promote stable battery performance.

Laboratory-based X-ray spectrometer for actinide science.

X-ray absorption and emission spectroscopies nowadays are advanced characterization methods for fundamental and applied actinide research. One of the advantages of these methods is to reveal slight changes in the structural and electronic properties of radionuclides. The experiments are generally carried out at synchrotrons. However, considerable progress has been made to construct laboratory-based X-ray spectrometers for X-ray absorption and emission spectroscopies. Laboratory spectrometers are reliable, effective and accessible alternatives to synchrotrons, especially for actinide research, which allow dispensing with high costs of the radioactive sample transport and synchrotron time. Moreover, data from laboratory spectrometers, obtained within a reasonable time, are comparable with synchrotron results. Thereby, laboratory spectrometers can complement synchrotrons or can be used for preliminary experiments to find perspective samples for synchrotron experiments with better resolution. Here, the construction and implementation of an X-ray spectrometer (LomonosovXAS) in Johann-geometry at a radiochemistry laboratory is reported. Examples are given of the application of LomonosovXAS to actinide systems relevant to the chemistry of f-elements, the physical chemistry of nuclear power engineering and the long-term disposal of spent nuclear fuel.

Smartphone-based spectroscopy as a tool to estimate soil attributes for the citizen science concept

This study explores the potential of using smartphone cameras to estimate soil attributes as a field-based alternative to traditional sampling and lab analyses that are time-consuming, expensive, and non-friendly to the environment. It aims to investigate whether the color information captured by smartphone cameras could provide spectral information that can be utilized for soil attribute estimation using regression techniques. The DN values from smartphone camera photos were transformed into reflectance using colored plastic plated marker (PPM) reference panels. The spectral information of the PPM keys, obtained using a laboratory spectrometer, was convolved into 3 RGB smartphone bands. Using the legacy soil spectral library (SSL) of Israel on the 3-reflectance calibrated RGB smartphone bands, a good agreement with the reflectance of the laboratory spectrometer was obtained. The soil properties were modeled with the converted reflectance using the multiple linear regression (MLR), partial least square regression (PLSR), and ridge regression (RR) algorithms. The models created using the smartphone data (RGB and 6 synthetic bands) predicted six soil properties: i.e., soil organic matter (OM%), CaCO3, free iron oxides (Fe-dithionite), Al2O3, soil surface area (SSA), and hygroscopic moisture with the coefficient of determination (R2) values of 0.58, 0.54, 0.60, 0.55, 0.55 and 0.64, respectively. The quality of predictions was also evaluated using root mean square error (RMSE) and the ratio of prediction to interquartile distance (RPIQ). This research provides the results of an experiment to convert a personal smartphone camera to a spectrometer with the help of SSL. Despite the low spectral resolution of smartphone cameras, the models achieved fair results in predicting six soil properties. These findings could promote the adoption of citizen science methodologies for sustainable soil management as smartphone devices that are available to all can be simply calibrated to reflectance and used for proximal sensing of soils.

Study on the rapid measurement of carbon content in marine sediments based on the model transfer of hyperspectral imaging camera and spectrometer

Laboratory spectrometer and hyperspectral imaging camera are two instruments for obtaining spectral information of substances. Both instruments have advantages in practical applications. In this paper, a total of 164 sediment samples were collected from two locations in the marine intertidal zone of Qingdao Aoshan Bay. The total carbon content (TC) concentration in marine sediments was obtained by chemical method. The spectral data of sediments were obtained by the spectrometer and the hyperspectral data were obtained by a hyperspectral imaging camera. With a spectrometer as the main instrument and a hyperspectral imaging camera as the slave instrument, the rapid measurement of carbon content in marine sediments was realized through the model transfer. Two model transfer algorithms were used: piecewise direct standardization, deviation model updating, and slope/bias correction method (PDS-DMP-S/B), and piecewise direct standardization, model updating, and slope/bias correction method (PDS-MP-S/B). Different modeling results were obtained by changing the proportion of the calibration set and test set and adding preprocessing. Compared with the single model transfer algorithm, PDS-MP-S/B and PDS-DMP-S/B were more effective. Standard normal variable transform (SNV) preprocessing had little effect on the modeling results in the model transfer between the spectrometer and hyperspectral imaging camera. After the data normalization of spectral data, all models were improved. When the ratio of the calibration set to the test set was 3:1, the PDS-DMP-S/B algorithm was used for the model transfer, the RP2 value of the modeling result was 0.693, the RMSEP value was 2.332, and the RPD value was 1.615, which achieved a relatively ideal modeling result. This study provides a new and fast method for predicting the carbon content in marine sediments.

Hydrocarbon Spectra Slope (HYSS): A Spectra Index for Quantifying and Characterizing Hydrocarbon oil on Different Substrates Using Spectra Data

Many sensors in Optical domain allow for detection of hydrocarbons in oil spills study. However, high resolution laboratory and airborne imaging spectrometers have shown potential for quantification and characterization of hydrocarbon. Available methods in literature for quantifying and characterizing hydrocarbons on these data relies mainly on shapes and positions of hydrocarbon key absorption features, mainly at 1.73 µm and 2.30 µm. Shapes formed by these absorption features are often influenced by spectral features of background substrates, thereby limiting the quality of results. Furthermore, multispectral sensors cannot resolve the shapes of key absorption features, a strong limitation for methods used in previous works. In this study, we present Hydrocarbon Spectra Slope (HYSS), a new spectra index that offers predictive quantification and characterization of common hydrocarbon oils. Slope values for the studied hydrocarbon oils enable clear discrimination for relative quantitative analysis of oil abundance classes and qualitative discrimination for common hydrocarbons on common background substrates. Data from ground-based spectrometers and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) are resampled to AVIRIS, Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) and LANDSAT 7 Enhanced Thematic Mapper’s (ETM+) Full Width at Half Maximum (FWHM), in order to compute spectra slope values for hydrocarbon abundance /hydrocarbon-substrate characterization. Despite limitations of nonconformity of central wavelengths and/or band widths of multispectral sensors to key hydrocarbon band, statistical significance for both quantitative and qualitative analysis at 95% confidence level (P-value ˂0.01) suggests strong potential of the use of HYSS, multispectral and hyperspectral sensors as emergency response tools for hydrocarbon mapping.

Portuino-A Novel Portable Low-Cost Arduino-Based Photo- and Fluorimeter.

A novel portable low-cost Arduino-controlled photo- and fluorimeter for on-site measurements has been developed. The device uses LEDs as a light source and a phototransistor as a light sensor. The circuit is based on the discharge of a capacitor with the photocurrent from the phototransistor. Validation experiments for absorbance measurements were performed by measuring protein concentration using the Bradford method and measuring phosphate ions in water using a commercial test kit. The emission light of the excited fluorescent dyes rhodamine 6G and calcofluor white was measured to validate the usability of the device as a fluorescence photometer. In all validation experiments, similar correlation coefficients and limit of detection could be achieved with the portable photo- and fluorimeter and a laboratory spectrometer and fluorimeter. Real sample analysis was performed, measuring phosphate concentration in freshwater and concentration of green fluorescent protein, extracted from Escherichia coli.

Miniaturized NIR Spectroscopy in Food Analysis and Quality Control: Promises, Challenges, and Perspectives.

The ongoing miniaturization of spectrometers creates a perfect synergy with the common advantages of near-infrared (NIR) spectroscopy, which together provide particularly significant benefits in the field of food analysis. The combination of portability and direct onsite application with high throughput and a noninvasive way of analysis is a decisive advantage in the food industry, which features a diverse production and supply chain. A miniaturized NIR analytical framework is readily applicable to combat various food safety risks, where compromised quality may result from an accidental or intentional (i.e., food fraud) origin. In this review, the characteristics of miniaturized NIR sensors are discussed in comparison to benchtop laboratory spectrometers regarding their performance, applicability, and optimization of methodology. Miniaturized NIR spectrometers remarkably increase the flexibility of analysis; however, various factors affect the performance of these devices in different analytical scenarios. Currently, it is a focused research direction to perform systematic evaluation studies of the accuracy and reliability of various miniaturized spectrometers that are based on different technologies; e.g., Fourier transform (FT)-NIR, micro-optoelectro-mechanical system (MOEMS)-based Hadamard mask, or linear variable filter (LVF) coupled with an array detector, among others. Progressing technology has been accompanied by innovative data-analysis methods integrated into the package of a micro-NIR analytical framework to improve its accuracy, reliability, and applicability. Advanced calibration methods (e.g., artificial neural networks (ANN) and nonlinear regression) directly improve the performance of miniaturized instruments in challenging analyses, and balance the accuracy of these instruments toward laboratory spectrometers. The quantum-mechanical simulation of NIR spectra reveals the wavenumber regions where the best-correlated spectral information resides and unveils the interactions of the target analyte with the surrounding matrix, ultimately enhancing the information gathered from the NIR spectra. A data-fusion framework offers a combination of spectral information from sensors that operate in different wavelength regions and enables parallelization of spectral pretreatments. This set of methods enables the intelligent design of future NIR analyses using miniaturized instruments, which is critically important for samples with a complex matrix typical of food raw material and shelf products.

Evaluation of a combination of NIR micro-spectrometers to predict chemical properties of sugarcane forage using a multi-block approach

Forage quality is essential in livestock farming and has an important role in the functioning of agricultural farms. Access to biochemical variables provides an estimation of the feed value of crop for animal feed at harvest. Near infrared (NIR) spectroscopy provides measurements indirectly related to biochemical variables. In recent years, several micro-spectrometers have been developed that offer the opportunity to predict such biochemical variables at low cost. In this study, the potential of a combination of micro-spectrometers is evaluated to predict crude protein (CP) and total sugar content (TS) of sugarcane. First, each micro-spectrometer with optimal pretreatments was individually compared to a reference laboratory spectrometer. Then, a combination of micro-spectrometers is proposed and prediction models were established by a multi-block method from data fusion called Sequential and Orthogonalised - Partial Least Squares (SO-PLS). For CP, the combination of micro-spectrometers provides model (sep = 0.69%; bias = 0.15%; R t e s t 2 = 0.910) close to those obtained with the reference spectrometer (sep = 0.56%; bias = −0.13%; R t e s t 2 = 0.935). For TS, the results obtained with this combination of micro-spectrometers (sep = 2.38%; bias = −0.52%; R t e s t 2 = 0.983) are better than those obtained with the reference spectrometer (sep = 2.59%; bias = 0.41%; R t e s t 2 = 0.978). For both chemical variables, the combination of the micro-spectrometers significantly increases the performance of the predictive models compared to the models obtained with the micro-spectrometers independently. Using several low-cost micro-spectrometers, combined with a multi-block method would give results as good as a single laboratory spectrometer with a lower cost. • A combination of micro-spectrometers is proposed as a low-cost solution. • The combination significantly increases prediction quality. • The case used is for the prediction of crude protein and sugar content of sugarcane. • A multi-block regression method called SO-PLS is used. • Application to predict chemical properties of sugarcane forage from NIRS.

Assessment of Radioactive Materials in Albite Granites from Abu Rusheid and Um Naggat, Central Eastern Desert, Egypt

The present study aims to assess Abu Rusheid and Um Naggat albite granite’s natural radioactivity in the Central Eastern Desert, Egypt, using an HPGe laboratory spectrometer. A total of 17 albite granite samples were detected for this study. The activity concentrations were estimated for 238U (range from 204 to 1127 Bq/kg), 226Ra (range from 215 to 1300 Bq/kg), 232Th (from 130 to 1424 Bq/kg) and 40K (from 1108 to 2167 Bq/kg) for Abu Rusheid area. Furthermore 238U (range from 80 to 800 Bq/kg), 226Ra (range from 118 to 1017 Bq/kg), 232Th (from 58 to 674 Bq/kg) and 40K (from 567 to 2329 Bq/kg) for the Um Naggat area. The absorbed dose rates in the outdoor air were measured with average values of 740 nGy/h for Abu Rusheid albite granite and 429 nGy/h for Um Naggat albite granite. The activity concentration and gamma-ray exposure dose rates of the radioactive elements 238U, 226Ra, 232Th and 40K at Abu Rusheid and Um Naggat exceeded the worldwide average values that recommend the necessity of radiation protection regulation. Moreover, the corresponding outdoor annual effective dose (AEDout) was calculated to be 0.9 and 0.5 mSv y−1 for Abu Rusheid and Um Naggat albite granite, respectively, which are lower than the permissible level (1 mSv y−1). By contrast, the indoor annual effective dose (AEDin) exceeded the recommended limit (3.6 and 2.1 for Abu Rusheid and Um Naggat, respectively). Therefore, the two areas are slightly saving for development projects concerning the use of the studied rocks. The statistical analysis displays that the effects of the radiological hazard are associated with the uranium and thorium activity concentrations in Abu Rusheid and Um Naggat albite granites.

Quantification routines for full 3D elemental distributions of homogeneous and layered samples obtained with laboratory confocal micro XRF spectrometers

Confocal micro-X-ray fluorescence spectroscopy can be performed with laboratory spectrometers for elemental imaging and quantification with 3D resolution.

The Identification of Cu-O-C Bond in Cu/MWCNTs Hybrid Nanocomposite by XPS and NEXAFS Spectroscopy.

The results of the research of a composite based on multi-walled carbon nanotubes (MWCNTs) decorated with CuO/Cu2O/Cu nanoparticles deposited by the cupric formate pyrolysis are discussed. The study used a complementary set of methods, including scanning and transmission electron microscopy, X-ray diffractometry, Raman, and ultrasoft X-ray spectroscopy. The investigation results show the good adhesion between the copper nanoparticles coating and the MWCNT surface through the oxygen atom bridge formation between the carbon atoms of the MWCNT outer graphene layer and the oxygen atoms of CuO and Cu2O oxides. The formation of the Cu–O–C bond between the coating layer and the outer nanotube surface is clearly confirmed by the results of the O 1s near edge X-ray absorption fine structure (NEXAFS) and X-ray photoelectron spectroscopy (XPS) of the Cu/MWCNTs nanocomposite. The XPS measurements were performed using a laboratory spectrometer with sample charge compensation, and the NEXAFS studies were carried out using the synchrotron radiation of the Russian–German dipole beamline at BESSY-II (Berlin, Germany) and the NanoPES station at the Kurchatov Center for Synchrotron Radiation and Nanotechnology (Moscow, Russia).

All-in-one: A spectral imaging laboratory system for standardised automated image acquisition and real-time spectral model deployment

Spectral imaging (SI) in analytical chemistry is widely used for the assessment of spatially distributed physicochemical properties of samples. Although massive development in instrument and chemometrics modelling has taken place in the recent years, the main challenge with SI is that available sensors require extensive system integration and calibration modelling before their use for routine analysis. Further, the models developed during one experiment are rarely useful once the system is reintegrated for a new experiment. To avoid system reintegration and reuse calibrated models, this study presents an intelligent All-In-One SI (ASI) laboratory system allowing standardised automated data acquisition and real-time spectral model deployment. The ASI system supplies a controlled standardised illumination environment, an in-built computing system, embedded software for automated image acquisition, and model deployment to predict the spatial distribution of sample properties in real-time. To show the capability of the ASI framework, exemplary cases of fruit property prediction in different fruits are presented. Furthermore, ASI is also benchmarked in performance against the current commercially available portable as well as high-end laboratory spectrometers.

Research on estimation models of the spectral characteristics of soil organic matter based on the soil particle size

Soil organic matter (SOM) is an important part of soil fertility and the main nutrient source for crop growth. The establishment of an effective SOM content estimation model can provide technical support for the improvement of saline soil and the implementation of precision agriculture. In this paper, a laboratory spectrometer was used to measure the spectral reflectance of saline soils with particle sizes of 1 mm, 0.50 mm, 0.25 mm and 0.15 mm collected from Kenli County. After spectral preprocessing and spectral transformation, the characteristic bands of the SOM spectrum were extracted by the successive projections algorithm (SPA). Finally, stepwise multiple linear regression (SMLR), principal component regression (PCR) and partial least squares regression (PLSR) were used to establish SOM content estimation models based on soil particle size. The results showed the following. (i) Soil particle size had a significant impact on soil spectral reflectance. The smaller the soil particle size was, the greater the soil spectral reflectance. (ii) The sensitive bands for SOM were mainly concentrated in the visible light region (400–760 nm). First derivative (FD) transformation can effectively improve the characteristic spectral information obtained from SOM. (iii) Among the three models established with the characteristic bands, the estimation ability of the PLSR model was better than that of the PCR and SMLR models. (iv) The FD of the original spectral reflectance of the 0.25 mm particles combined with the PLSR model gave the best estimation of the SOM content. When the soil particle size was less than 0.25 mm, the estimation results of the model were not improved. These results provide a basis for effective estimation of the SOM content and improvement of saline-alkali soil in Kenli County in the Yellow River Delta.

Fast at-line characterization of solid organic waste: Comparing analytical performance of different compact near infrared spectroscopic systems with different measurement configurations

Fast characterization of solid organic waste using near infrared spectroscopy has been successfully developed in the last decade. However, its adoption in biogas plants for monitoring the feeding substrates remains limited due to the lack of applicability and high costs. Recent evolutions in the technology have given rise to both more compact and more modular low-cost near infrared systems which could allow a larger scale deployment. The current study investigates the relevance of these new systems by evaluating four different Fourier transform near-infrared spectroscopic systems with different compactness (laboratory, portable, micro spectrometer) but also different measurement configurations (polarized light, at distance, in contact). Though the conventional laboratory spectrometer showed the best performance on the various biochemical parameters tested (carbohydrates, lipids, nitrogen, chemical oxygen demand, biochemical methane potential), the compact systems provided very close results. Prediction of the biochemical methane potential was possible using a low-cost micro spectrometer with an independent validation set error of only 91 NmL(CH4).gTS-1 compared to 60 NmL(CH4).gTS-1 for a laboratory spectrometer. The differences in performance were shown to result mainly from poorer spectral sampling; and not from instrument characteristics such as spectral resolution. Regarding the measurement configurations, none of the evaluated systems allowed a significant gain in robustness. In particular, the polarized light system provided better results when using its multi-scattered signal which brings further evidence of the importance of physical light-scattering properties in the success of models built on solid organic waste.

Calibration Transfer for LED-Based Optical Multisensor Systems.

Multivariate calibration transfer is widely used to expand the applicability of the existing regression model to new analytical devices of the same or similar type. The present research proves the feasibility of calibration model transfer between a full-scale laboratory spectrometer and an optical multisensor system based on only four light-emitting diodes with different wavelengths. The model transfer between two multisensor systems of this kind has also been studied. Both possibilities were successfully performed without any significant loss of precision using a designed set of training and transfer samples. Direct standardization and slope and bias correction protocols for model transfer were tested and compared. The best model transfer between two optical multisensor systems was obtained using direct standardization.

Studies of Buried Layers and Interfaces of Tungsten Carbide Coatings on the MWCNT Surface by XPS and NEXAFS Spectroscopy

Currently, X-ray photoelectron spectroscopy (XPS) is widely used to characterize the nanostructured material surface. The ability to determine the atom distribution and chemical state with depth without the sample destruction is important for studying the internal structure of the coating layer several nanometers thick, and makes XPS the preferable tool for the non-destructive testing of nanostructured systems. In this work, ultra-soft X-ray spectroscopy methods are used to study hidden layers and interfaces of pyrolytic tungsten carbide nanoscale coatings on the multi-walled carbon nanotube (MWCNT) surfaces. XPS measurements were performed using laboratory spectrometers with sample charge compensation, and Near Edge X-ray Absorption Fine Structure (NEXAFS) studies using the Russian–German dipole beamline (RGBL) synchrotron radiation at BESSY-II. The studied samples were tested by scanning and transmission electron microscopy, X-ray diffractometry, Raman scattering and NEXAFS spectroscopy. It was shown that the interface between MWCNT and the pyrolytic coating of tungsten carbide has a three-layer structure: (i) an interface layer consisting of the outer graphene layer carbon atoms, forming bonds with oxygen atoms from the oxides adsorbed on the MWCNT surface, and tungsten atoms from the coating layer; (ii) a non-stoichiometric tungsten carbide WC1-x nanoscale particles layer; (iii) a 3.3 nm thick non-stoichiometric tungsten oxide WO3-x layer on the WC1-x/MWCNT nanocomposite outer surface, formed in air. The tungsten carbide nanosized particle’s adhesion to the nanotube outer surface is ensured by the formation of a chemical bond between the carbon atoms from the MWCNT upper layer and the tungsten atoms from the coating layer.

A Performance Comparison of Low-Cost Near-Infrared (NIR) Spectrometers to a Conventional Laboratory Spectrometer for Rapid Biomass Compositional Analysis

The performance of a conventional laboratory near-infrared (NIR) spectrometer and two NIR spectrometer prototypes (a Texas Instruments NIRSCAN Nano evaluation model (EVM) and an InnoSpectra NIR-M-R2 spectrometer) are compared by collecting reflectance spectra of 270 well-characterized herbaceous biomass samples, building calibration models using the partial least squares (PLS-2) algorithm to predict five constituents of the samples from the reflectance spectra, and comparing the resulting model statistics. The prediction models developed using spectra from the Foss XDS spectrometer were slightly better than the prediction models developed using spectra from either the TI NIRSCAN Nano EVM and the InnoSpectra NIR-M-R2 as measured by the root mean square error (RMSECV) and the correlation coefficient (R2_cv) for “leave-one-out” cross-validation (CV). The models built from the two prototype units were not statistically significantly different from each other (p = 0.05). The Foss spectrometer has a larger wavelength range (400–2500 nm) compared with the two prototypes (900–1700 nm). When the spectra from the Foss XDS spectrometer were truncated so their wavelength range matched the wavelength range of the two prototype units, the resulting model was not statistically significantly different from the models from either prototype.

Testing edible oil authenticity by using smartphone based spectrometer

In recent years, there has been an increasing interest in the classification of edible vegetable oils, examining authenticity and in detecting possible adulteration of high quality, expensive extra virgin olive oils with low-cost edible oils. Classical methods such as gas chromatography, liquid chromatography, Fourier transform infrared and nuclear magnetic resonance, mass spectrometry, and Raman spectroscopy have been widely applied to examine the authenticity of edible oils. De-spite of their high sensitivity and accuracy, these methods are significantly expensive for daily life testing, especially in resource-poor regions. Furthermore, they are time-consuming as samples have to be analyzed in dedicated laboratories. In this paper, we propose a compact, low-cost, port-able smartphone-based spectrometer for testing edible oil authenticity. Using simple laboratory op-tical components and a smartphone, we developed a compact spectrometer which can function in the wavelength range of 400–700 nm with the spectrum/pixel resolution of 0.334 nm / pixel. The images captured by the smartphone were converted into intensity distribution plots versus wave-length. As a proof of concept, the smartphone based spectrometer was utilized to measure the variations in fluorescent intensity of the mixed oils of expensive extra virgin olive oil and low-cost rice oil with different percentages. The results obtained the spectrometer were in good agreement with that from a laboratory spectrometer, thus, confirmed its adequate sensitivity and accuracy. Due to the cost effectiveness, the adequate sensitivity, and the portability, the smartphone based spectrometer can be applied in numerous applications such as in-field testing, lifestyle monitoring, and home diagnostics.

Hand-Held Near-Infrared Spectroscopy for Authentication of Fengdous and Quantitative Analysis of Mulberry Fruits.

Recently, miniaturization of Raman, mid-infrared (MIR) and near-infrared (NIR) spectrometers have made substantial progress, and marketing companies predict this segment of instrumentation a significant growth rate within the next few years. This increase will be based on a more frequent implementation for industrial quality and process control and a broader adoption of spectrometers for in-the-field testing, on-site measurements, and every-day-life consumer applications. The reduction in size, however, must not lead to compromises in measurement performance and the hand-held instrumentation will only have a real impact if spectra of comparable quality to laboratory spectrometers can be obtained. The present communication will, on the one hand, explain the instrumental reasons why NIR spectroscopy is presently the most advanced technique regarding miniaturization and on the other hand, it will emphasize the impact of NIR spectroscopy for plant analysis by discussing in some detail a qualitative and a quantitative application example.

Radioactivity Levels of Some Natural Stones in Burdur, Turkey

Radionuclides such as uranium, thorium and potassium have existed in the environment since the world's existence. It is important to know the distribution of these radionuclides in terms of human health and environmental protection. For this reason, the measurements of these natural radionuclides were made for the 6 stone samples extracted in the province of Burdur. To measure the natural activity concentrations of potassium-40, radium-226 and thorium-232 radionuclides, a gamma spectrometry method was used with a NaI (T1) detector which is a multichannel analytical detector in the gamma spectrometer laboratory of Suleyman Demirel University. The average activity concentrations of 40K, 226Ra and 232Th were 290.53 Bq/kg, 35.49 Bq/kg and 42.88 Bq/kg, respectively. To evaluate the radiological hazard of natural radioactivity to humans and the environment, radium equivalent activity, absorbed dose ratio, annual effective dose ratio, internal and external hazard indices were calculated. These calculated values were found to be suitable with the standard limit values.