Acquired Reflectance Spectra Research Articles

Adapting Prediction Models to Bare Soil Fractional Cover for Extending Topsoil Clay Content Mapping Based on AVIRIS-NG Hyperspectral Data

The deployment of remote sensing platforms has facilitated the mapping of soil properties to a great extent. However, the accuracy of these soil property estimates is compromised by the presence of non-soil cover, which introduces interference with the acquired reflectance spectra over pixels. Therefore, current soil property estimation by remote sensing is limited to bare soil pixels, which are identified based on spectral indices of vegetation. Our study proposes a composite mapping approach to extend the soil properties mapping beyond bare soil pixels, associated with an uncertainty map. The proposed approach first classified the pixels based on their bare soil fractional cover by spectral unmixing. Then, a specific regression model was built and applied to each bare soil fractional cover class to estimate clay content. Finally, the clay content maps created for each bare soil fractional cover class were mosaicked to create a composite map of clay content estimations. A bootstrap procedure was used to estimate the standard deviation of clay content predictions per bare soil fractional cover dataset, which represented the uncertainty of estimations. This study used a hyperspectral image acquired by the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor over cultivated fields in South India. The proposed approach provided modest performances in prediction (Rval2 ranging from 0.53 to 0.63) depending on the bare soil fractional cover class and showed a correct spatial pattern, regardless of the bare soil fraction classes. The model’s performance was observed to increase with the adoption of higher bare soil fractional cover thresholds. The mapped area ranged from 10.4% for pixels with bare soil fractional cover >0.7 to 52.7% for pixels with bare soil fractional cover >0.3. The approach thus extended the mapped surface by 42.4%, while maintaining acceptable prediction performances. Finally, the proposed approach could be adopted to extend the mapping capability of planned and current hyperspectral satellite missions.

Can diffuse reflectance spectroscopy identify shuntodynia in pediatric hydrocephalus patients?

Shuntodynia is patient reported pain at the site of the implanted ventriculoperitoneal (VP) shunt. Pediatric hydrocephalus requiring shunt placement is a chronic and prevalent standard of care treatment and requires lifetime management. Shuntodynia is a subjective measure of shunt dysfunction. Quantitative, white-light tissue spectroscopy could be used to objectively identify this condition in the clinic. Pediatric subjects were recruited for optical sensing during routine clinical follow-up visits, post-VP shunt implantations. Acquired optical signals were translated into skin-hemodynamic signatures and were compared between subjects that reported shuntodynia versus those that did not. Diffuse reflectance spectroscopy (DRS) measurements were collected between 450 and 700nm using a single-channel fiber-optical probe from () patients. Multiple reflectance spectra were obtained by the attending physician from regions both proximal and distal to the VP shunt sites and from a matched contralateral site for each subject. Acquired reflectance spectra were processed quantitatively into functional tissue optical endpoints. A two-way, repeated measures analysis of variance was used to assess whether and which of the optical variables were statistically separable, across subjects with shuntodynia versus those without. Analyses indicated that intrapatient differences in vascular oxygen saturation measured between shunt sites relative to that obtained at the scar or contralateral sites was significantly lower in the pain group. We also find that the total hemoglobin concentrations at the shunt site were lowest relative to the other sites for subjects reporting pain. These findings suggest that shuntodynia pain arises in the scalp tissue around the implanted shunts and may be caused due to hypoxia and inflammation. Optically derived hemodynamic variables were statistically significantly different in subjects presenting with shuntodynia relative to those without. DRS could provide a viable mode in routine bedside monitoring of subjects with VP shunts for clinical management and assessment of shuntodynia.

Hyperspectral Reflectance and Chemical Composition of Pre- and Post-Fire Soils from Three 2021 Western USA Megafires

Over the past two decades, wildfire activity in the western USA has increased, especially in California. Wildfires not only affect air quality but also the environment at large, including chemical and physical properties of fire-affected soils, which are of great interest for prediction and mitigation of hydrological consequences. Hyperspectral reflectance can be used to remotely assess the effects of fires on soil and here we use it to characterize soils before and after three 2021 California wildfires (Dixie, Beckwourth Complex, and Caldor fire). We acquired reflectance spectra and compared changes in these spectra with changes in the chemistry of analyzed soils. For all three fires, the results show that 700 nm wavelength reflectance of ash samples collected 1 and 1.5 years after fire decreased between 36% and 76% compared to that of samples collected right after the fires. Additionally, significantly higher visible reflectance has been found for unburned compared to burned soil samples in each region that was studied. Infrared transmission measurements were used to characterize the carbonate content of soil and ash samples demonstrating a mostly positive relationship between carbonate content and visible reflectance, indicating a possible cause and effect between the two.

Application of deep learning and spectral deconvolution for estimating mineral abundances of zeolite, Mg-sulfate and montmorillonite mixtures and its implications for Mars

A technique for estimating clinoptilolite, montmorillonite, and epsomite mineral abundances from a reflectance spectrum of mineral mixtures using spectral deconvolution and a deep neural network is proposed. Sixty-six ternary mineral mixtures were physically prepared with <150 μ m grain size with different weight percentages of minerals. A combination of normal and skewed Gaussian curves was fitted to the absorption bands at 1.4 μ m , 1.9 μ m , and 2.2 μ m of the acquired reflectance spectra of these mineral mixtures. Six Gaussian curve parameters with maximum absorption band depth ∼1.9 μ m , and wavelength at the maximum band depth, were used (along with mineral abundances) to train multilayer perceptron deep neural network (MLP-DNN) models. Forty-eight models with different DNN architectures and different hyperparameters were trained and the results were validated to find the best models. Winning models were tested using twenty-five samples including fourteen library spectra from RELAB and USGS spectral databases, a spectrum from a different sample, five different amounts of noise-added spectra simulating CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) orbital spectral data, and five mixed spectra derived from linear mixtures of laboratory minerals. The best model was able to predict mineral mixture composition with higher accuracies; three of five montmorillonite and four of the five epsomite library spectra were identified with more than 90% accuracy. However, clinoptilolite samples show less than 50% accuracy and always predicted as mixtures of clinoptilolite and epsomite. This shows the difficulties of distinguishing non-analcime zeolites (e.g., clinoptilolite) from Mg-polyhydrated sulfate minerals, as discussed by authors who mapped hydrous minerals on Mars using hyperspectral image data. Also, the presence of at least ∼10% of montmorillonite in a clinoptilolite-montmorillonite mixture can entirely mask the presence of clinoptilolite in SWIR spectral data. Random artifacts introduced by noise sometime lead to predictions of completely different and incorrect mineral abundances. The study also discusses the possible reasons for the incorrect prediction of mineral abundances and how to overcome these difficulties. Overall, the study shows the advantage of spectral deconvolution with deep neural network for calculating mineral abundance from mixed mineral spectra. • Deep neural network estimating mineral abundances from spectroscopy is proposed. • Presence of montmorillonite mask the spectral identification of clinoptilolite. • Montmorillonite will also mask the presence of epsomite in SWIR spectral data.

4D dual-mode staring hyperspectral-depth imager for simultaneous spectral sensing and surface shape measurement.

A 4D dual-mode staring hyperspectral-depth imager (DSHI), which acquire reflectance spectra, fluorescence spectra, and 3D structural information by combining a staring hyperspectral scanner and a binocular line laser stereo vision system, is introduced. A 405 nm laser line generated by a focal laser line generation module is used for both fluorescence excitation and binocular stereo matching of the irradiated line region. Under the configuration, the two kinds of hyperspectral data collected by the hyperspectral scanner can be merged into the corresponding points in the 3D model, forming a dual-mode 4D model. The DSHI shows excellent performance with spectral resolution of 3 nm, depth accuracy of 26.2 µm. Sample experiments on a fluorescent figurine, real and plastic sunflowers and a clam are presented to demonstrate system's with potential within a broad range of applications such as, e.g., digital documentation, plant phenotyping, and biological analysis.

Investigating the Relationship between (3200) Phaethon and (155140) 2005 UD through Telescopic and Laboratory Studies

Abstract The relationship between the near-Earth objects (3200) Phaethon and (155140) 2005 UD is unclear. While both are parents to meteor showers (the Geminids and Daytime Sextantids, respectively) and have similar visible-wavelength reflectance spectra and orbits, dynamical investigations have failed to find any likely method to link the two objects in the recent past. Here we present the first near-infrared reflectance spectrum of 2005 UD, which shows it to be consistently linear and red-sloped, unlike Phaethon’s very blue and concave spectrum. Searching for a process that could alter some common starting material to both of these end states, we hypothesized that the two objects had been heated to different extents, motivated by their near-Sun orbits, the composition of Geminid meteoroids, and previous models of Phaethon’s surface. We thus set about building a new laboratory apparatus to acquire reflectance spectra of meteoritic samples after heating to higher temperatures than available in the literature to test this hypothesis and were loaned a sample of the CI chondrite Orgueil from the Vatican Meteorite Collection for testing. We find that while Phaethon’s spectrum shares many similarities with different CI chondrites, 2005 UD’s does not. We thus conclude that the most likely relationship between the two objects is that their similar properties are only by coincidence as opposed to a parent-fragment scenario, though the ultimate test will be when JAXA’s DESTINY+ mission visits one or both of the objects later this decade. We also discuss possible paths forward to understanding Phaethon’s properties from dynamical and compositional grounds.

Relevance of a near infrared spectral index for assessing tillage and fertilization effects on soil water retention

Agricultural practices are expected to have significant effects on soil physical properties, such as soil structure and soil water retention (SWR) properties are among the relevant properties that can be used to assess these effects. Ex-situ measurements are costly and time-consuming. Visible (vis) and near infrared (NIR) spectroscopy has been widely used as a rapid, cost-effective and nondestructive technique to predict many soil properties, including soil water content (SWC). In this study, we explored the ability of vis-NIR to assess the effects of soil tillage and fertilization on SWR. The study was performed on silty soil samples with 10.4 g kg−1 of organic carbon content and a pH of 5-6.5. Undisturbed soil blocks were collected from an experimental station located in Brittany, France. In 2012, the field was designed as two separate experiments, each with a different tillage system (conventional tillage (CT) and shallow tillage (ST)). For each experiment, two fertilizer types were considered (mineral and organic). Six undisturbed soil blocks were sampled at each of two depths (0–15 cm and 15–25 cm) and from each agricultural practice. Soil was sampled on two dates: before starting the treatment (2012) and after 5 years of agricultural practices (2017). From each soil block, four aggregates 3–4 cm wide and 5–6 cm long were collected. The whole aggregates were set at a number of matric potentials, from saturation to the permanent wilting point (pF = 4.2). At a given pressure head, soil samples were scanned in triplicate to acquire reflectance spectra from 400 to 2500 nm using a handheld spectrometer (ASD Fieldspec®). We focused on the absorption band near 1920 nm and used a new NIR spectral index based on the band’s full width at half maximum, called SWSI. Our results showed a linear relation between SWSI and SWC (R² > 0.99). Moreover, the slope and intercept of this linear relation were significantly correlated with water holding capacity (WHC) and soil quality. Using these parameters, we found that SWR and soil physical quality under CT were significantly greater under cattle manure (CTC) than under mineral fertilizer (CTM) or at T0. This significant effect was more pronounced at 15–25 cm. In ST treatments, SWR properties and soil quality were significantly lower than at T0. More importantly, our results show that the slope and intercept of the linear relation offer a way to summarize and assess the effects of agricultural practices on SWR properties and soil structural quality.

Near-infrared spectroscopy as a tool for in vivo analysis of human muscles

Recent advances in materials and fabrication techniques provided portable, performant, sensing optical spectrometers readily operated by user-friendly cabled or wireless systems. Such systems allow rapid, non-invasive, and not destructive quantitative analysis of human tissues. This proof-of-principle investigation tested whether infrared spectroscopy techniques, currently utilized in a variety of areas, could be applied in living humans to categorize muscles. Using an ASD FieldSpec® 4 Standard-Res Spectroradiometer with a spectral sampling capability of 1.4 nm at 350–1000 nm and 1.1 nm at 1001–2500 nm, we acquired reflectance spectra in visible short-wave infra-red regions (350–2500 nm) from the upper limb muscles (flexors and extensors) of 20 healthy subjects (age 25–89 years, 9 women). Spectra off-line analysis included preliminary preprocessing, Principal Component Analysis, and Partial Least-Squares Discriminant Analysis. Near-infrared (NIR) spectroscopy proved valuable for noninvasive assessment of tissue optical properties in vivo. In addition to the non-invasive detection of tissue oxygenation, NIR spectroscopy provided the spectral signatures (ie, “fingerprints”) of upper limb flexors and extensors, which represent specific, accurate, and reproducible measures of the overall biological status of these muscles. Thus, non-invasive NIR spectroscopy enables more thorough evaluation of the muscular system and optimal monitoring of the effectiveness of therapeutic or rehabilitative interventions.

Active hyperspectral imaging with a supercontinuum laser source in the dark**Project supported by the Opening Foundation of State Key Laboratory of High Performance Computing, China (Grant No. 201601-02), the Open Research Fund of Hunan Provincial Key Laboratory of High Energy Technology, China (Grant No. GNJGJS03), the Opening Foundation of State Key Laboratory of Laser Interaction with Matter, China (Grant No.

An active hyperspectral imaging (HSI) system was built with a supercontinuum (SC) laser illuminator and a visible/near-infrared hyperspectral camera, which was used for object spectrum detection in the dark. It was demonstrated that the Gaussian-like distribution of the SC illuminator can still be used for accurate reflectance spectrum measurement once the illuminator was characterized in advance. The validity of active HSI results was demonstrated by comparison with passive results. Then, the active HSI system was used to acquire reflectance spectra of different objects in just one push-broom measurement successfully. With algorithms of principal component analysis clustering and unsupervised K-means spectral classification, this active HSI system with high spectral and spatial resolutions was demonstrated to be efficient and applicable for specific spectrum detections.

A near infrared index to assess effects of soil texture and organic carbon content on soil water content

SummaryCharacterization of soil hydrodynamic properties is important for assessing the soil water regime. Ex situ measurements are costly and time consuming. Reflectance spectroscopy can rapidly estimate several soil properties, including soil water content (SWC). Here, we evaluated the ability of visible (vis) and near‐infrared (NIR) spectroscopy to assess the effects of soil texture and soil organic carbon (SOC) content on SWC. Thirteen undisturbed soil surface blocks were sampled in 2014 across the Brittany region, western France. Textural classes ranged from sandy loam to sandy clay loam texture, and SOC content ranged from 8.12 g kg−1 to 62.3 g kg−1. Aggregates of 3–4‐cm width and 5–6‐cm height were extracted and set at 10 matric potentials from saturation to permanent wilting point (1585 kPa). At given pressure heads, soil samples were scanned in triplicate to acquire reflectance spectra between 350 and 2500 nm. Spectra were converted into continuum removal and we focused on the absorption band near 1920 nm, which is linked to combination vibrations of water. We defined a new index based on the full width at half maximum (FWHM) of the absorption feature near 1920 nm. Results showed a linear relation between this NIR index and the volumetric SWC (R2 &gt; 0.9) for every soil aggregate. The slope and the intercept of the line were correlated well with soil texture and SOC content. Results indicated that the parameters of this linear relation offer a new way to study SWC and water retention properties of soils in relation to their physical properties.Highlights We used vis–NIR spectroscopy to assess effects of texture and SOC content on soil water content. Formulated a new spectral index based on absorption feature of water near 1920 nm. Linear relation between SWC and NIR index; its parameters are related to texture and SOC content. Vis–NIR spectroscopy can be relevant to assess effects of texture and SOC content on SWC.

Production of an innovative biowaste-derived fertilizer: Rapid monitoring of physical-chemical parameters by hyperspectral imaging

In this work the possibility to apply hyperspectral imaging as a fast and non-destructive technique for the monitoring of the production process at pilot plant scale of an innovative biowaste-derived fertilizer was explored. Different mixtures of urban organic waste, farm organic residues, biochar and vegetable active principles were selected and utilized in two different European countries, Italy and Spain, for the production of the innovative fertilizer. The biowaste-derived fertilizer samples were collected from the pilot plant piles at different curing time and acquired by the hyperspectral imaging device. Spectra have been collected in the near infrared wavelength range (1000–1700 nm). Conventional analyses were carried out on the same samples in order to find correlations between the physical-chemical parameters detected at laboratory scale, and the acquired reflectance spectra. The investigated parameters were: pH, electrical conductivity, soluble total organic carbon and soluble total nitrogen.Hyperspectral data were processed adopting chemometric strategies through the application of principal component analysis, for exploratory purposes, and partial least squares analysis to establish correlations between spectral features and measured physical-chemical parameters. Good correlations, with R2 ranging between 0.85 and 0.96, were obtained for all the investigated parameters. Results showed as the proposed approach, based on hyperspectral imaging, is suitable to be adopted for a rapid and non-destructive monitoring of waste-derived fertilizer production.

Application of Near Infrared Reflectance Spectroscopy for Rapid and Non-Destructive Discrimination of Hulled Barley, Naked Barley, and Wheat Contaminated with Fusarium.

Fusarium is a common fungal disease in grains that reduces the yield of barley and wheat. In this study, a near infrared reflectance spectroscopic technique was used with a statistical prediction model to rapidly and non-destructively discriminate grain samples contaminated with Fusarium. Reflectance spectra were acquired from hulled barley, naked barley, and wheat samples contaminated with Fusarium using near infrared reflectance (NIR) spectroscopy with a wavelength range of 1175–2170 nm. After measurement, the samples were cultured in a medium to discriminate contaminated samples. A partial least square discrimination analysis (PLS-DA) prediction model was developed using the acquired reflectance spectra and the culture results. The correct classification rate (CCR) of Fusarium for the hulled barley, naked barley, and wheat samples developed using raw spectra was 98% or higher. The accuracy of discrimination prediction improved when second and third-order derivative pretreatments were applied. The grains contaminated with Fusarium could be rapidly discriminated using spectroscopy technology and a PLS-DA discrimination model, and the potential of the non-destructive discrimination method could be verified.

SpectraCam® : A new polarized hyperspectral imaging system for repeatable and reproducible in vivo skin quantification of melanin, total hemoglobin, and oxygen saturation.

An accurate way to determine skin pigmentation is to acquire the spectral reflectance of a skin sample and to quantify chromophores by reverse calculation from physical models of light propagation. Therefore, we tested a new hyperspectral imaging device and software suite, the SpectraCam® system, and evaluated its accuracy to quantify skin chromophores. Validation of the SpectraCam® system was performed by, firstly, comparing the known and the acquired reflectance spectra of color phantoms. Repeatability and reproducibility were then evaluated by two operators who performed acquisitions at different time points and compared the acquired reflectance spectra. The specificity of the system was tested by quantitative analysis of single chromophore variation models: lentigo and pressure relief. Finally, we tested the ability of the SpectraCam® system to detect variations in chromophore in the eye region due to the daily application of a new anti-dark circle cosmetic product. The SpectraCam® system faithfully acquires the reflectance spectra of color phantoms (r2 >0.90). The skin reflectance spectra acquired by different operators at different times are highly repeatable (r2 >0.94) and reproducible (r2 >0.99). The SpectraCam® system can also produce qualitative maps that reveal local variations in skin chromophore or underlying structures such as blood vessels. The system is precise enough to detect melanin variation in lentigo or total hemoglobin and oxygen saturation variations upon pressure relief. It is also sensitive enough to detect a decrease in melanin in the eye region due to the application of an anti-dark circle cosmetic product. The SpectraCam® system proves to be rapid and produces high-resolution data encompassing a large field of view. It is a robust hyperspectral imaging system that quantifies melanin, total hemoglobin, and oxygen saturation and is well adapted to cosmetic research.

The Ma_Miss instrument performance, I: Analysis of rocks powders by Martian VNIR spectrometer

The ExoMars/Ma_Miss instrument is a miniaturized spectrometer that will observe the Martian subsoil in the visible and near infrared range (VNIR, 0.4–2.2μm) with high spatial resolution, 120μm. It will be integrated in the Drilling system of the Pasteur Rover of the ExoMars 2018 mission, and will acquire reflectance spectra of the borehole wall performed by the Drill, at various depths down to 2m. The laboratory breadboard instrument consists of the main subsystems: illumination system, optical fibres for illumination and signal collection, and optical elements for light focusing. It has been interfaced with a commercial spectrometer, the FieldSpec Pro©.The primary aim of this work is to compare the VNIR measurements and spectral parameters derived from the spectra acquired with the Ma_Miss breadboard and with a second laboratory setup.Reflectance spectra have been acquired on a set of six rock powder samples representative of Martian soil. Nine different grain size ranges of each sample have been measured with the breadboard and five spectral parameters were used to explore the Ma_Miss spectra. Those data were compared with spectra acquired by the FieldSpec Pro® coupled with a goniometer. The analyses of these spectral parameters evidence the correlation between the VNIR continuum slope and the grain size, and the correlation between the reflectance and the grain size; both the parameters tend to decrease as the grain size increases. The trends observed with Ma_Miss breadboard for NIR and VNIR slopes and for the reflectance are clearly consistent with the trends observed with the spectro-goniometer setup, although small differences are seen that can be explained with the different viewing geometries of the two instruments. Ma_Miss proves to have great capabilities for extracting spectroscopic information to constrain the mineralogy and some physical parameters of the analysed material.

Interpretation of Reflectance Spectra of Clay Mineral-Silica Mixtures: Implications for Martian Clay Mineralogy at Mawrth Vallis

AbstractThe Al-clay-rich rock units at Mawrth Vallis, Mars, have been identified as mixtures of multiple components based on their spectral reflectance properties and the known spectral character of pure clay minerals. In particular, the spectral characteristics associated with the ~2.2 μm feature in Martian reflectance spectra indicate that mixtures of AlOH- and SiOH-bearing minerals are present. The present study investigated the spectral reflectance properties of the following binary mixtures to aid in the interpretation of remotely acquired reflectance spectra of rocks at Mawrth Vallis: kaolinite-opal-A, kaolinite-montmorillonite, montmorillonite-obsidian, montmorillonite-hydrated silica (opal), and glass-illite-smectite (where glass was hydrothermally altered to mixed-layer illite-smectite). The best spectral matches with Martian data from the present study’s laboratory experiments are mixtures of montmorillonite and obsidian having ~50% montmorillonite or mixtures of kaolinite and montmorillonite with ~30% kaolinite. For both of these mixtures the maximum inflection point on the long wavelength side of the 2.21 μm absorption feature is shifted to longer wavelengths, and in the case of the kaolinite-montmorillonite mixtures the 2.17 μm absorption found in kaolinite is of similar relative magnitude to that feature as observed in CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) data. The reflectance spectra of clay mixed with opal and of hydrothermally altered glass-illite-smectite did not represent the Martian spectra observed in this region as well. A spectral comparison of linear vs. intimate mixtures of kaolinite and montmorillonite indicated that for these sieved samples, the intimate mixtures are very similar to the linear mixtures with the exception of the altered glass-illite-smectite samples. However, the 2.17 μm kaolinite absorption is stronger in the intimate mixtures than in the equivalent linear mixture. Modified Gaussian Modeling of absorption features observed in reflectance spectra of the kaolinite-montmorillonite mixtures indicated a strong correlation between percent kaolinite in the mixture and the ratio of the area of the 2.16 μm band found in kaolinite to the area of the 2.20 μm band found in montmorillonite.

Rapid estimation of lycopene concentration in watermelon and tomato puree by fiber optic visible reflectance spectroscopy

Chemometric models were developed for prediction of lycopene concentration in watermelon and tomato puree from their visible reflectance spectra acquired by a fiber optic reflectance probe. A fiber optic spectrometer was used to acquire reflectance spectra from puree samples in the wavelength range of 500–750 nm. Least squares (LS) and partial least squares (PLS) regression were used to correlate spectral data with lycopene concentration measured by hexane extraction and spectrophotometry. An apparent absorbance index (AAI) obtained by subtracting apparent absorbance at 700 nm from that at 565 nm showed linear correlation with lycopene concentration ( R 2 = 0.90 for watermelon puree and 0.62 for tomato puree). A normalized apparent absorbance index (NAAI) obtained by dividing the AAI by the sum of apparent absorbances at 565 and 700 nm, also had linear correlation with lycopene concentration ( R 2 = 0.90 and 0.61 for watermelon and tomato, respectively). The LS linear regression model for watermelon puree could predict lycopene concentration with R 2 of 0.93, and standard error of prediction (SEP) of 5.1 mg kg −1. The LS linear regression model for tomato puree could predict lycopene concentration with R 2 of 0.54 and an SEP of 5.2 mg kg −1. The PLS model for watermelon puree could predict lycopene concentration with an R 2 of 0.97 and an SEP of 3.4 mg kg −1. The PLS model for tomato puree could predict lycopene concentration with an R 2 of 0.88 and an SEP of 2.5 mg kg −1. The high linear correlations between spectral parameters and lycopene concentration of samples (with lycopene concentration between 10 and 80 mg kg −1) suggest that this method can be reliably used for fast and safe quantification of lycopene concentration in watermelon and tomato puree.

In vivomeasurement of skin erythema and pigmentation: new means of implementation of diffuse reflectance spectroscopy with a commercial instrument

Various physical, chemical and biological insults, including exposure to ultraviolet (UV) radiation, cause erythema and change in pigmentation in human skin. These reactions provide an important measure of the cutaneous response to the insult. To present a new implementation of a method for objective in vivo measurement of erythema and pigmentation. The method is based on acquisition of reflectance spectra in the visible range using a commercially available spectrophotometer. The probe of this instrument incorporates an integrating sphere that captures the light remitted from the skin in a wide range of angles. We corrected the acquired reflectance spectra for the contribution of specular reflections by an amount given by the Fresnel equation and verified this correction experimentally. This correction is particularly important when measurements are performed on heavily pigmented skin. The corrected reflectance spectra are then transformed into absorbance spectra. To analyse these spectra, we developed an algorithm which can be used to calculate apparent concentrations of oxyhaemoglobin, deoxyhaemoglobin and melanin. This method was tested in clinical studies of skin reactions induced by exposure to UV radiation. These experiments involved three groups of subjects with progressively darker complexion (constitutive pigmentation). Each group consisted of 10 subjects. Erythema was measured 1 day after UV exposure, and pigmentation (melanin content) 1 week later. Results Distinct apparent absorbance spectra were obtained for dark, intermediate and fair skin. There was good agreement between reconstructed spectra and experimental data at relevant wavelengths. Difference absorption spectra were able to show the dose dependence of UV-induced responses, and erythema and pigmentation values obtained by the spectroscopic method showed good correlation with those derived by subjective visual grading. The results demonstrate that the presented methodology provides an objective noninvasive way of measuring UV-induced reactions independently of the level of constitutive pigmentation.