Visible Near-infrared Spectrometer Research Articles

Daily Monitoring of Ripening Processes of a Tomato Using an Original Handheld Visible–Near-Infrared Spectrometer

A handheld visible- and shortwave near-infrared spectrometer has been developed for monitoring daily changes in fruits and vegetables. The ripening processes of a mini tomato sample have been monitored daily for about 100 days by this instrument and color values L*a*b* and Brix were measured. Obtained reflection spectra in the 400–1050 nm range were converted to absorption spectra and daily changes of band areas of chlorophyll a (Ch1 a; 640–710 nm), carotenoids (460–520 nm), lycopene (545–600 nm), and water + sugar (920–1050 nm) were determined. The band area of lycopene increased rapidly from 36 to 44 days associated with the increase in a* value, indicating that the increase in the reddish color originated from the increase of lycopene. On the other hand, the band area of Chl a decreased exponentially over 100 days. This Chl a decrease could be well fitted by the first-order reaction giving the rate constant k = 4.07 × 10–7 s–1. These quantitative daily changes of pigments in fruits and vegetables are expected to provide comprehensive bases for their cultivation and harvest.

Visible-Near-Infrared Spectroscopy and Chemometrics for Authentication Detection of Organic Soybean Flour

Organic and non-organic soybean flours, although visually indifferent, have a significant difference in price and nutrition content. Therefore, the accurate authentication detection of organic soybean flour is necessary. Visible-near-infrared (Vis-NIR) spectroscopy coupled with chemometric methods is a non-destructive technique applied to detect authentic or adulterated organic soybean flour. The spectra of organic, adulterated organic, and non-organic soybean flours were captured using a Vis-NIR spectrometer at 350–1000 nm. The spectra were analyzed using partial least squares (PLS), principal component analysis (PCA), and the combination of these two with discriminant analysis (DA). The results showed that PCA using PC1 and PC2 could differentiate organic and non-organic soybean flours, whereas PC1 and PC4 can detect pure and adulterated organic soybean flours. The PCA–linear DA models showed 98.5% accuracy (Acc) for predicting pure organic and adulterated soybean flours and 100% Acc for predicting organic and non-organic flours. Moreover, PLS regression models resulted in a high R² of >95% for predicting organic and non-organic flours and pure and adulterated soybean flours. In addition, the PLS-DA models can differentiate organic from non-organic soybean flour and distinguish pure and adulterated soybean flours with 100% Acc and reliability.

Necessity of Log(1/R) and Kubelka-Munk transformation in chemometrics analysis to predict white rice flour adulteration in brown rice flour using visible-near-infrared spectroscopy

This study compared the calibration model performance of reflectance to absorbance transformation spectra combined with pre-processing spectra to find the best model to predict white rice flour adulteration in brown rice flour using the visible and near-infrared spectrometer. Partial least squares regression (PLSR) and principal component regression (PCR) were compared using reflectance, Kubelka-Munk (KM), and Log(1/R) spectra. Area normalization (AN) and Savitsky-smoothing Golay's (SGS) were pre-processing methods. The sample was white rice flour mixed with brown rice flour at 0%, 5%, 10%, 15%, 20%, and 25%. Reflectance spectra outperformed KM and log (1/R) spectra in this study. Reflectance spectra provided the best model for PLSR and PCR. Pre-processed SGS spectra were best for PLSR, while raw reflectance spectra were best for PCR. PLSR and PCR both had an R2 of prediction of 0.96, while the overall average R2 of prediction favors PLSR over PCR. The present study led to the discovery of a simple novel method for developing adulteration flour and showed that a visible near-infrared spectrometer combined with PLSR, or PCR, could predict white rice flour adulteration in brown rice flour.

Predicting sugarcane quality using a portable visible near infrared spectrometer and a benchtop near infrared spectrometer

Sugar quality (Brix and Pol) is the key index to evaluate the value of sugarcane. Hence, a rapid, accurate, and time-efficient method is needed to determine the sugar quality. This study develops a two-point sugarcane quality model that uses a benchtop near infrared (NIR) spectrometer and a portable visible–near infrared (Vis-NIR) spectrometer to measure the sugarcane juice and stalk spectra, respectively. GT two experiments for developing a two-point sugarcane quality model. In the first, a model to calibrate the sugar quality as measured by a polarimeter and refractometer, and also by the benchtop NIR spectrometer. In the second, we developed a model to calibrate the sugar quality predicted from the calibration model developed in the first experiment, by measuring the sugarcane stalk absorption spectra using a portable Vis-NIR spectrometer. The results of the first experiment showed that the standard normal variate (SNV) spectral pretreatment was the most effective method for Brix calibration, with a coefficient of determination of prediction ([Formula: see text]) of 0.99 and root mean square error of prediction (RMSEP) of 0.2%. In the case of Pol, second derivatives were the best spectral pretreatment for effective calibration (r2 = 0.99, RMSEP = 0.3%). The results of the second experiment showed that the multiple linear regression model developed using the stalk spectra with the second derivative was the best model for Brix calibration (r2 = 0.70, RMSEP = 1.4%). The second derivative with the SNV pretreatment was best for Pol calibration (r2 = 0.70, RMSEP = 1.4%). Our study showed that a sugar quality regression model can be developed for a portable Vis-NIR spectrometer using the data from the sugar quality predicted by a benchtop NIR spectrometer.

Segregation of ‘Hayward’ kiwifruit for storage potential using Vis-NIR spectroscopy

Kiwifruit are often harvested unripe and kept in local coolstores for extended periods of time before being marketed. Many pre-harvest factors contribute to variation in fruit quality at harvest and during coolstorage, resulting in the difficulty in segregating fruit for their storage potential. The ability to forecast storage potential, both within and between populations of fruit, could enable segregation systems to be implemented at harvest to assist with inventory decision making and improve profitability. Visible-near infrared (Vis-NIR) spectroscopy is one of the most commonly used non-destructive techniques for estimation of internal quality of kiwifruit. Whilst many previous attempts focused on instantaneous quantification of quality attributes, the objective of this work was to investigate the use of Vis-NIR spectroscopy utilised at harvest to qualitatively forecast storage potential of individual or batches of kiwifruit. Commercially sourced ‘Hayward’ kiwifruit capturing large variability of storability were measured non-destructively at harvest using Vis-NIR spectrometer, and then assessed at 75, 100, 125 and 150 days after coolstorage at 0 °C. Machine learning classification models were developed using at-harvest Vis-NIR spectral data, to segregate storability of kiwifruit into two groups based on the export FF criterion of 9.8 N. The best prediction was obtained for fruit stored at 0 °C for 125 days: approximately 54% of the soft fruit (short storability) and 79% of the good fruit (long storability) could be predicted. Further novelty of this work lies within an independent external validation using data collected from a new season. Kiwifruit were repacked at harvest based on their potential storability predicted by the developed model, with the actual post-storage performance of the same fruit assessed to evaluate model robustness. Segregation between grower lines at harvest achieved 30% reduction in soft fruit after storage. Should the model be applied in the industry to enable sequential marketing, significant costs could be saved because of reduced fruit loss, repacking and condition checking costs.

Determination of Acid Level (pH) and Moisture Content of Cocoa Beans at Various Fermentation Level Using Visible Near-Infrared (Vis-NIR) Spectroscopy

Fermentation is critical in cacao processing which breakdowns sugar compounds in the pulp into organic acids. The produced organic acids stimulate enzymatic reactions in the beans which affect the flavor, taste, and color of the cacao beans. Acidity (pH) and moisture content of cacao beans influence the quality of cacao during fermentation. Those parameters are commonly measured using pH meter and gravimetric methods which are time-consuming and destructive.Therefore, the objective of this study was to develop non-destructive calibration models to predict the pH and moisture content of cacao beans at various fermentation levels using a visible near-infrared spectrometer and chemometric methods. The samples consisted of 315 cacao beans obtained from 3 regions (Lampung, Makasar, and Kulon Progo) at 3 levels of fermentation (non, half, full). The calibration and prediction models were performed by PLS regression which involves X variables (Vis/NIR measurement results) and Y variable (pH and moisture content). Smoothing, normalization baseline correction, standard normal variate (SNV), and multiplicative scattered correction (MSC) were used for spectra pre-processing. The research showed that the MSC method resulted in the best model for pH with the correlation coefficient of calibration and prediction were 0.76 and 0.68, respectively. Original and MSC methods resulted in the best model for moisture content with the same value of of 0.55 and of 0.41. The results showed the capability of Vis/NIR spectroscopy and the important role of chemometrics in developing models for predicting cacao bean quality parameters during fermentation.

Two Different Portables Visible-Near Infrared and Shortwave Infrared Region for On-Tree Measurement of Soluble Solid Content of Marian Plum Fruit

The goal of this study was to predict the soluble solid content (SSC) of on-tree Marian plum fruit using two different wavelength range and algorithm. One of these was the commercial dispersion NIR spectrometer (MicroNIR 1700), providing shortwave infrared (SWIR), while the other was a making diode array spectrometer giving visible-near infrared (Vis-NIR). To search optimal model, the analytical ability of the two wavelength ranges spectrometers coupled with two algorithms: i.e. partial least squares regression (PLSR) and support vector machine regression (SVR), were investigated. Different spectral pre-processing methods were tested. The model providing the lowest root mean square errors of prediction (RMSEP) was selected. Overall, the proposed outcome was that the performance of SWIR was more accurate than Vis-NIR spectrometer, and that both SWIR and Vis-NIR coupled with PLSR algorithm had a higher accuracy than SVR algorithm. The best model for on-tree evaluation SSC was the SWIR constructed using the PLSR algorithm with the spectral pre-processing of the 2nd derivative, providing a coefficient of determination of calibration set (R2) of 0.81, a coefficient of determination of validation set (r2) of 0.76, RMSEP of 0.69 °Brix, and a relative standard error of prediction (RSEP) of 4.43%. The outcome showed that a portable SWIR spectrometer developed with PLSR could be used for monitoring the SSC of individual Marian plum fruit on-tree for quality assurance.

A novel polyaniline (PANI)/ paraffin wax nano composite phase change material: Superior transition heat storage capacity, thermal conductivity and thermal reliability

An energy source is required that has potential to reduce global warming, energy cost and create environmental sustainability. Solar energy is a viable candidate with 120 petajoules of energy on earth per second. To utilize this energy the present research explores the effect of the addition of conducting polyaniline (PANI) and cupric (II) oxide (CuO) nanoparticles within the matrix of paraffin wax. The Fourier Transform Infrared Spectroscopy (FTIR), Thermogravimetric Analyzer (TGA), Differential Scanning Calorimetry (DSC), Ultraviolet–Visible-Near Infrared Spectrometer (UV–VIS) and thermal conductivity characterization of the prepared composite were performed. An enhancement of latent heat capacity of paraffin/PANI nanocomposite by 8.20% and paraffin/CuO composite by 7.81% was observed. Thermal conductivity of Paraffin/PANI was increased by ~46.8% for a 1% weight concentration of PANI in paraffin wax the same concentration as maximum latent heat capacity. In the case of paraffin/CuO composite, the maximum increment of thermal conductivity was found to be ~63.6%. To check the thermal reliability of the formulated nanocomposite, the base paraffin and nanocomposites were subjected to thermal cycling of 200 cycles. The DSC results showed that paraffin/PANI nanocomposite outperformed both base paraffin wax and paraffin/CuO composite. With comparable thermal conductivity to Paraffin/CuO composite, better latent heat capacity and improved thermal reliability Paraffin/PANI composite results are encouraging for the application in solar application area.

Effects of Sb doping on the structure and properties of SnO2 films

Transparent heat-insulating SnO2 films were prepared on the glass substrate with sol-gel. The effects of Sb doping on the structure and photoelectric properties of the films were investigated. The films were characterized by scanning electron microscope (SEM), X-ray diffractometer (XRD), X-ray photoelectron spectroscopy (XPS), Ultraviolet–Visible-Near Infrared Spectrometer (UV-VIS-NIR) and Hall Effect tester. The results show that the doping of Sb did not change the basic crystal structure of the SnO2 film, but reduced the crystallinity of the film. With the increase of Sb doping, the grain size decreases first and then maintains basically invariable. The sheet resistance of the film decreases first and then increases. The transmittance of the substrate glass coated with this film (hereinafter referred to as the film's transmittance) in the near-infrared region (780–2500 nm) decreases from 92.55% to 60.48%, and increases a little when the doping amount exceeded 11 mol%. And its transmittance of visible light (380–780 nm) fluctuated slightly between about 81% and 86%.

Prediction of meat quality traits in the abattoir using portable and hand-held near-infrared spectrometers

The use of near-infrared spectrometers (NIRS) for predicting meat quality traits directly in the abattoir was tested with three trials. For the calibration trial, spectra were acquired from the cross-cut surface of the Longissimus thoracis muscle on 1166 carcasses of Piemontese young bulls with a portable visible-near-infrared spectrometer (Vis-NIRS) and with a small hand-held instrument (Micro-NIRS). A sample of the same muscle was analyzed to provide the reference. Validation statistics of the two instruments were similar. Predictabilities of meat color and purge loss were good, whereas for the other traits they were less promising. The repeatability trial showed that post-slaughter factors, not predictable by NIR spectra collected in the abattoir, affect reference meat quality values. A trial under operative conditions showed that both spectrometers were able to capture the major sources of variation in most of the meat quality traits. Overall, NIRS could be used to predict the animals' “native” characteristics exploitable for genetic improvement of meat quality traits.

Evaluating low-cost portable near infrared sensors for rapid analysis of soils from South Eastern Australia

Near infrared spectroscopy has been proposed as a rapid and cost-effective method for soil analysis. Full-range visible near infrared (Vis-NIR) spectrometers working in the 350–2500 nm wavelength are commonly used for research purposes, but now miniaturized spectrometers with limited NIR ranges have become available. This study aims to compare the accuracy of near infrared reflectance (NIR) instruments with different sizes and wavelength ranges on the prediction of soil properties. Soil samples were taken from southern New South Wales and northern Victoria, comprised of Chromosols, Dermosols, Kandosols, and Sodosols. In total, the dataset consists of 392 soil samples from the top 1 m. The study compared two research-grade Vis-NIR spectrometers (350–2500 nm) and two miniaturized NIR spectrometers with limited wavelengths (NeoSpectra operating at 1250–2500 nm and NIRVascan operating at 900–1700 nm). Cubist regression tree and Partial Least Squares Regression (PLSR) were used to build calibration models. The results showed that both modelling procedures are reliable for estimating soil properties. Cubist models gave greater validation r2 values for ten soil properties investigated for all four instruments. Based on the Cubist model, promising results were found in predictions of clay, sand, total carbon, CEC, pH, exchangeable Mg and Ca (r2: 0.43–0.81). The results are also comparable to published studies for all instruments. As expected, the research-grade spectrometers provided the best prediction accuracies (r2: 0.56–0.81). Results from NeoSpectra provided a comparable accuracy with the Vis-NIR spectrometers in prediction of soil pH, CEC and exchangeable Ca and Mg (r2 > 0.63–0.78). NeoSpectra produced a slightly less accurate prediction of total carbon, sand, and clay. While NIRVascan showed the lowest accuracy, it still can be used in prediction of soil texture and total carbon with reasonable accuracy (r2 clay: 0.73; sand: 0.63; total carbon: 0.73). This study demonstrates the potential of miniaturized spectrometers with reduced wavelength ranges as cheaper instruments in soil analysis.

Non-destructive assessment of chloride in persimmon leaves using a miniature visible near-infrared spectrometer

New methods for the non-destructive, rapid and reliable assessment of leaf chloride (Cl−) are needed in many agricultural salt-threatened areas throughout the World. Although portable visible near-infrared spectrometers could be useful for this task, accompanying models for leaf Cl− assessment on basis their visible near-infrared (Vis-NIR) spectra had yet to be developed. To study the feasibility of such models, a persimmon orchard was grown in E Spain and irrigated with eight waters ranging in Cl− concentration from 70 to 350 mg/L. Then, six times throughout the growing season the Vis-NIR foliar reflectance spectra of various representative leaves per Cl− treatment were recorded with a portable miniature Vis-NIR spectrometer. The leaf Cl− was subsequently determined in the same leaves with a laboratory reference method. Next, both the Cl− and spectral data were analyzed using descriptive statistics, mathematical data transformations, principal components analysis (PCA) and partial least squares regression (PLSR). A wide, sufficiently normal-distributed and representative range of leaf Cl− content from 0.17 to 3.14%Cl− was obtained. With correlation coefficients exceeding +0.65 between 390 and 472 nm and between 690 and 692 nm, the foliar reflectance was the spectral data correlated the most with the leaf Cl−. Remarkably, both wavelengths intervals are where chlorophyll a has its two absorbance maxima in the visible region. A PLSR model including all the wavelengths in the Vis-NIR reflectance spectra plus the day of the year, attained values of R2 = 0.78, RMSE = 0.34%Cl− and RPD = 2.18 in the external validation. However, for leaf Cl− below 1.5%Cl−, i.e., when Cl− assessment is most needed, this model presented R2 = 0.55, but RMSE = 0.08%Cl− and RPD = 5.5, in addition to a bias of +0.04%Cl− and a standard error of 0.05%Cl−. These results show that portable Vis-NIR spectrometers can be useful for the non-destructive, rapid and even reliable assessment of leaf Cl−. The potential of this methodology for other crop plants and inorganic ions should be tested.

Space weathering of the Moon from in situ detection**A contributed paper of the International Symposium on Lunar and Planetary Science (ISLPS) on 2018 June 12–15 at Macau University of Science and Technology.

Space weathering is an important surface process that occurs on the Moon and other airless bodies, especially those that have no magnetic field. The optical effects of the Moon’s space weathering have largely been investigated in the laboratory for lunar samples and lunar analogues. However, duplication of pristine regolith on Earth is not possible. Here we report on space weathering from the unique perspective of the “Yutu” rover, which was part of theChang’e-3 (CE-3) mission, building on our previous work. Measurement of the visually undisturbed uppermost regolith as well as locations that have been affected by rocket exhaust from the spacecraft by the Visible-Near Infrared Spectrometer (VNIS) revealed that the returned samples provide biased information about the pristine lunar regolith. The uppermost surficial regolith is much more weathered than the regolith immediately below, and the finest fraction is rich in space weathered products. These materials are very dark and attenuated throughout the visible and near-infrared (VNIR) wavelengths, hence reducing the reflectance and masking the absorption features. The effects on the spectral slope caused by space weathering are wavelength-dependent: the visible and near-infrared continuum slope (VNCS) increases while the visible slope (VS) decreases. In the visible wavelengths, the optical effects of space weathering and TiO2 are identical: both reduce albedo and blue the spectra. This suggests that a new TiO2 abundance algorithm is needed. Optical maturity indices are related to composition and hence only locally meaningful. Since optical remote sensing can only sense the uppermost few microns of regolith and since this surface tends to be very weathered, the interpretation of surface composition using optical remote sensing data needs to be carefully evaluated. Sampling the uppermost surface is suggested.

NU-Spidercam: A large-scale, cable-driven, integrated sensing and robotic system for advanced phenotyping, remote sensing, and agronomic research

Field-based high throughput plant phenotyping has recently gained increased interest in the efforts to bridge the genotyping and phenotyping gap and accelerate plant breeding for crop improvement. In this paper, we introduce a large-scale, integrated robotic cable-driven sensing system developed at University of Nebraska for field phenotyping research. It is constructed to collect data from a 0.4 ha field. The system has a sensor payload of 30 kg and offers the flexibility to integrate user defined sensing modules. Currently it integrates a four-band multispectral camera, a thermal infrared camera, a 3D scanning LiDAR, and a portable visible near-infrared spectrometer for plant measurements. Software is designed and developed for instrument control, task planning, and motion control, which enables precise and flexible phenotypic data collection at the plot level. The system also includes a variable-rate subsurface drip irrigation to control water application rates, and an automated weather station to log environmental variables. The system has been in operation for the 2017 and 2018 growing seasons. We demonstrate that the system is reliable and robust, and that fully automated data collection is feasible. Sensor and image data are of high quality in comparison to the ground truth measurements, and capture various aspects of plant traits such as height, ground cover and spectral reflectance. We present two novel datasets enabled by the system, including a plot-level thermal infrared image time-series during a day, and the signal of solar induced chlorophyll fluorescence from canopy reflectance. It is anticipated that the availability of this automated phenotyping system will benefit research in field phenotyping, remote sensing, agronomy, and related disciplines.

The Absolute Reflectance and New Calibration Site of the Moon

Abstract How bright the Moon is forms a simple but fundamental and important question. Although numerous efforts have been made to answer this question such as use of sophisticated electro-optical measurements and suggestions for calibration sites, the answer is still debated. An in situ measurement with a calibration panel on the surface of the Moon is crucial for obtaining the accurate absolute reflectance and resolving the debate. China’s Chang’E-3 (CE-3) “Yutu” rover accomplished this type of measurement using the Visible-Near Infrared Spectrometer (VNIS). The measurements of the VNIS, which were at large emission and phase angles, complement existing measurements for the range of photometric geometry. The in situ reflectance shows that the CE-3 landing site is very dark with an average reflectance of 3.86% in the visible bands. The results are compared with recent mission instruments: the Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC), the Spectral Profiler (SP) on board the SELENE, the Moon Mineralogy Mapper (M3) on board the Chandrayaan-1, and the Chang’E-1 Interference Imaging Spectrometer (IIM). The differences in the measurements of these instruments are very large and indicate inherent differences in their absolute calibration. The M3 and IIM measurements are smaller than LROC WAC and SP, and the VNIS measurement falls between these two pairs. When using the Moon as a radiance source for the on-orbit calibration of spacecraft instruments, one should be cautious about the data. We propose that the CE-3 landing site, a young and homogeneous surface, should serve as the new calibration site.

Spectroscopic observations of the Moon at the lunar surface

The Moon's reflectance spectrum records many of its important properties. However, prior to Chang'E-3 (CE-3), no spectra had previously been measured on the lunar surface. Here we show the in situ reflectance spectra of the Moon acquired on the lunar surface by the Visible-Near Infrared Spectrometer (VNIS) onboard the CE-3 rover. The VNIS detected thermal radiation from the lunar regolith, though with much shorter wavelength range than typical thermal radiometer. The measured temperatures are higher than expected from theoretical model, indicating low thermal inertia of the lunar soil and the effects of grain facet on soil temperature in submillimeter scale. The in situ spectra also reveal that 1) brightness changes visible from orbit are related to the reduction in maturity due to the removal of the fine and weathered particles by the lander's rocket exhaust, not the smoothing of the surface and 2) the spectra of the uppermost soil detected by remote sensing exhibit substantial differences with that immediately beneath, which has important implications for the remote compositional analysis. The reflectance spectra measured by VNIS not only reveal the thermal, compositional, and space-weathering properties of the Moon but also provide a means for the calibration of optical instruments that view the surface remotely.

Submicroscopic metallic iron in lunar soils estimated from the in situ spectra of the Chang'E‐3 mission

AbstractSubmicroscopic metallic iron (SMFe) created by space weathering has strong effects on the optical properties of the lunar surface. Spectra measured in situ by the visible‐near‐infrared spectrometer (VNIS) on board the Chang'E‐3 Yutu rover were used to investigate optical maturity differences at the CE‐3 landing site caused by lander exhaust. SMFe abundances were estimated using Hapke's radiative transfer model. Analysis of the spectrum for a minimally disturbed soil indicates that it contains 0.368 wt % SMFe, corresponding to an Is/FeO maturity index of ~53 and indicating that the landing site is submature. The soil at a location that was more disturbed contains 0.217 wt % SMFe, suggesting that the material removed by the rocket blast is more weathered than the regolith that remained behind. We conclude that maturity differences related to removal of the finest, highly mature particles play a major role in the observed reflectance changes associated with rocket blast.

Visible and near-infrared spectral survey of lunar meteorites recovered by the National Institute of Polar Research

Lunar meteorite chip samples recovered by the National Institute of Polar Research (NIPR) have been studied by a UV–visible–near-infrared spectrometer, targeting small areas of about 3 × 2 mm in size. Rock types and approximate mineral compositions of studied meteorites have been identified or obtained through this spectral survey with no sample preparation required. A linear deconvolution method was used to derive end-member mineral spectra from spectra of multiple clasts whenever possible. In addition, the modified Gaussian model was used in an attempt of deriving their major pyroxene compositions. This study demonstrates that a visible-near-infrared spectrometer on a lunar rover would be useful for identifying these kinds of unaltered (non-space-weathered) lunar rocks. In order to prepare for such a future mission, further studies which utilize a smaller spot size are desired for improving the accuracy of identifying the clasts and mineral phases of the rocks.

Analysis on the cooling effect of a heat-reflective coating for asphalt pavement

A type of self-made heat-reflective coating was applied on the surface of different types of asphalt concrete. The temperature of the asphalt mixture specimens with coatings that have different application rates was measured. By calculating the temperature difference between the specimen with and without the coating, the results show that the cooling value first increases and then becomes flat as the application rate of the coating increases. With the same coating application rate, dense-graded asphalt mixture has the best cooling effect, followed by the stone matrix asphalt (SMA) mixture, and finally, the open-graded friction course (OGFC) asphalt mixture has the lowest cooling effect of the tested specimens. The reason is that the OGFC asphalt mixture has a high per cent of air voids and part of the coating will penetrate into the air voids, so less coating is available to reduce the temperature. The SMA mixture has a higher texture depth than the dense-graded asphalt mixture, which compromises the cooling effect of the coating. The cooling mechanism was analysed through microscopic analysis methods, and the reflective spectrum was measured by ultraviolet–visible–near-infrared spectrometer. Results show that the coating has a high reflectivity due to the addition of fillers, which reduces the heat absorption of pavement. The Infrared spectra of the coating and fillers in the middle infrared region were tested by the Fourier transform infrared spectrometer. It indicates that the fillers have good thermal radiation ability in the atmospheric window. Accordingly, the coating presents a good cooling ability in this region, which can further reduce the temperature of the pavement. Pictures from the scanning electron microscope prove that there are many fillers scattered on the surface of the coating, which can bring about a good cooling effect.

The determination of some physical characteristics of different particle sizes in soils with reflection spectroscopy

The main objective of this study is to evaluate the ability of visible near-infrared reflectance spectroscopy (VNIRS) to predict diverse soil properties in grinding different particular size effect. In this study, 60 soil samples were collected from the fields include different soil ordo (Entisols, Inceptisols, Vertisols and Mollisols) in Isparta (Atabey) district Crushed samples were subjected into five different mesh sizes (4.76-2.00, 2.00-1.00, 1.00-0.50, 0.5-0.25 and <0.25 mm, respectively). Each soil samples were scanned with a visible near-infrared spectrometer, with a spectral range of 350 to 2500 nm, at five different particular sizes. The spectral reflectances were used to predict some physical properties of the soil (texture, field capacity and wilting point) using partial least squares (PLS) regression. PLS analysis was used to develop calibration models between smoothed-first derivative 6-nm-spaced spectral reflectance data and soil physical analysis measured clay, silt, sand, field capacity and wilting point. The results showed that while soils need to be crushed to pass through 0.25 mm sieve in order to determine wilting point and amount of clay, mesh size was found non-significant in determining sand, silt and field capacaity and the results obtained from the reflectance values taken from field samplings proved to be satisfactory. Key words: Texture, field capacity, wilting point, visible near-infrared reflectance spectroscopy (VNIRS).