Hand-held Spectrometer Research Articles

Detecting Low Concentrations of Nitrogen-Based Adulterants in Whey Protein Powder Using Benchtop and Handheld NIR Spectrometers and the Feasibility of Scanning through Plastic Bag.

Nitrogen-rich adulterants in protein powders present sensitivity challenges to conventional combustion methods of protein determination which can be overcome by near Infrared spectroscopy (NIRS). NIRS is a rapid analytical method with high sensitivity and non-invasive advantages. This study developed robust models using benchtop and handheld spectrometers to predict low concentrations of urea, glycine, taurine, and melamine in whey protein powder (WPP). Effectiveness of scanning samples through optical glass and polyethylene bags was also tested for the handheld NIRS. WPP was adulterated up to six concentration levels from 0.5% to 3% w/w. The two spectrometers were used to obtain three datasets of 819 diffuse reflectance spectra each that were pretreated before linear discriminant analysis (LDA) and regression (PLSR). Pretreatment was effective and revealed important absorption bands that could be correlated with the chemical properties of the mixtures. Benchtop NIR spectrometer showed the best results in LDA and PLSR but handheld NIR spectrometers showed comparatively good results. There were high prediction accuracies and low errors attesting to the robustness of the developed PLSR models using independent test set validation. Both the plastic bag and optical glass gave good results with accuracies depending on the adulterant of interest and can be used for field applications.

Theae nigrae folium: Comparing the analytical performance of benchtop and handheld near-infrared spectrometers

We investigated caffeine and l-theanine, quality characteristics for camellia sinensis, in milled and ground black tea samples with near-infrared (NIR) spectroscopy giving a direct comparison between the performances of benchtop and handheld NIR spectrometers. The constructed partial least squares regression (PLSR) models for all spectrometers were validated by test-set-validation and according to the obtained root mean square errors of prediction (RMSEP). The performances of the spectrometers were as follows: The benchtop spectrometer NIRFlex N-500 (Büchi, Flawil, Switzerland) showed the best results for milled samples with a RMSEP of 0.14% for caffeine and 0.12% for l-theanine. For the ground samples, a RMSEP of 0.17% for caffeine and 0.12% for l-theanine was gained. While the handheld spectrometers MicroNIR 2200 (Viavi Solutions (former: JDS Uniphase Corporation), Milpitas, USA) and the microPHAZIR (Thermo Fisher Scientific, Waltham, USA) both provided good results for the prediction of caffeine in milled samples (RMSEP of 0.22% and 0.26%), only the microPHAZIR was able to satisfactorily determine the caffeine content in ground samples (RMSEP of 0.28%). The investigation of l-theanine with handheld spectrometers did not lead to convincing results, since R2 was 0.75 for milled samples while ground samples could not be calculated. Decisive differences were concluded in how different NIR instruments capture the chemical information on caffeine vs. l-theanine. The handheld spectrometers manifested limited applicability to l-theanine. Deeper insight was obtained through the detailed NIR band assignments of caffeine and l-theanine derived from quantum mechanical simulation. Narrow working spectral region of handhelds omits the characteristic absorption bands of l-theanine. Therefore, information on l-theanine content measured by the evaluated miniaturized spectrometers is insufficient to enable its effective quantification. In contrast, the most characteristic NIR absorption of caffeine matches the working spectral regions of the handheld NIR spectrometers, hence their performance is comparable with the benchtop device.

UAV-based Multispectral & Thermal dataset for exploring the diurnal variability, radiometric & geometric accuracy for precision agriculture

To explore the diurnal variations, radiometric and geometric accuracy of UAV-based data for precision agriculture, a comprehensive dataset was created in a one-day field campaign (21 June 2017). The multi-sensor data set covers wheat, barley & potato experimental fields, located in Wageningen University and Research (WUR) farm maintained by Unifarm. UAV-based images were collected with several sensors over the experimental area, starting from 7:25am and ending at 20:00pm local solar time. The dataset consists of images collected by 9 flights with senseFly MSP4C, 9 with Parrot Sequoia, 2 with Slant Range P3, 5 with DJI Zenmuse X3 NIR, 4 with the senseFly Thermo-map and 1 with the RGB Sony WX-220. Additionally, validation measurements at radiometric calibration plates and plant sample locations were taken with a Cropscan handheld spectrometer and a tec5 Handyspec spectrometer. The dataset consists of the validation measurements, the raw images and the processed orthomosaics (both with and without geometric correction).

Performance of new low-cost handheld NIR spectrometers for nondestructive analysis of umbu (Spondias tuberosa Arruda) quality

The objective of this study was to evaluate the analytical performance of two new low-cost handheld NIR spectrometers for the determination of umbu fruit (Spondias tuberosa Arruda) quality. A third handheld spectrometer, representing a proven good performance for fruit quality analysis, was used as reference instrument. Multivariate calibration models were built using Partial Least Squares regression to determine dry matter (DM), soluble solids (SS), flesh firmness (FF) and skin color (SC). No significant statistical difference was found among the analytical performances of all three spectrometers. The average of the relative root mean square error of prediction (RMSEPr) obtained with the three spectrometers were 5.2 ± 0.9% for DM, 8.4 ± 1.5% for SS, 27.6 ± 2.0% for FF and 8.0 ± 0.6% for SC. According to these results, the new low-cost handheld NIR spectrometers can be used to monitor umbu fruit quality during ripening with suitable accuracy.

Handheld near-infrared spectrometers: Where are we heading?

During NIR 2019 conference, Gold Coast, Australia, a presentation upon a critical review of instrumentation and applications of handheld spectrometers was delivered during the plenary session held on Thursday morning, 19 September. Following the conference presentation, a vivid discussion flared up among the audience that equally involved academic scholars, industry representatives, as well as professionals who carry out every day in-the-field applications. Various aspects were raised connected with the emerged new generation of near-infrared instrumentation, with many individuals expressing their point-of-view on the merits and pitfalls of the miniaturized spectrometers. This vigorous dispute and exchange of impressions indicated that the community remains concerned about the applicability of such devices. That concern reflects the still relatively shallowly explored miniaturization versus performance factor, which can only be dismissed by focused feasibility studies with comparative analyses carried out on scientific-grade benchtop spectrometers. It is the aim of the present manuscript to summarize the discussed scientific content and to share the developed point-of-view with addition of our remarks.

On-Site Identification of the Material Composition of PV Modules with Mobile Spectroscopic Devices

With the increased development of portable and handheld molecular spectrometers within recent years, new fields of applications have opened up, such as their use (i) for material identification of samples contained in large and non-portable components and (ii) the detection of material degradation effects and failures directly in the plant. The usability and transferability of well-established analytical characterization techniques, such as attenuated total reflection (ATR) Infrared (IR)-, Raman, and Near-Infrared (NIR)-spectroscopy as mobile devices for the in-field characterization of Photovoltaic (PV) modules, are described and discussed. Material identification of the polymeric compounds incorporated in the PV modules (encapsulants, backsheets) is often an important task, especially when degradation and failures occur. Whereas the knowledge of the bill of materials is one challenge, the detection of material degradation effects is another important issue. Both tasks can be solved nondestructively by the application of mobile spectrometers. Raman spectroscopy is the best-suited method for the identification of the encapsulant within the module (measurement through 3-mm glass), while NIR measurements allowed for the nondestructive determination of the composition of the multilayer backsheet. Surface degradation effects (e.g., oxidation, hydrolysis) are best detectable with IR-spectroscopy. The application of mobile devices allows for direct material analysis in the field without dismantling PV modules, transporting them to the lab, cutting them in smaller pieces, and analyzing them in conventional bench-top spectrometers.

Analysis of factors influencing the interpretation of a digitally examined fluvial meanderbelt system: Joggins Formation, Nova Scotia

Clastic reservoir exploration, development, and exploitation are inherently complex with recovery depending largely on the understanding of sand body architecture and interlayered clayey/silty baffles and barriers. Numerous data collection techniques and methods are now widely available for helping to enrich reservoir outcrop analogue data extraction from the well scale to the larger seismic scale. This integrated study uses the inherited, combined data from a localized light detection and ranging survey, measurements taken from a portable handheld spectrometer and air permeameter, in addition to total (or absolute) porosity measurements from thin sections to assist with the analysis of components influencing the interpretation of a digitally analyzed fluvial meanderbelt system outcrop. The purpose is not to perform a detailed reservoir characterization or to model a potential reservoir, but rather to study a section of a reservoir analogue and apply reservoir geology with integrated data collection techniques to highlight potential benefits and shortcomings of this type of approach. A point cloud survey generated from light detection and ranging, coupled with other tools including a portable handheld spectrometer and permeameter, supplements data from the light detection and ranging scan and increases the confidence of interpretations. Spectrometer measurements recorded at the outcrop are used to generate a pseudo-gamma log. Handheld air permeameter measurements give a sense of the permeability of corresponding lithologies, as well as the variability in permeability of the reservoir both laterally and vertically. Light detection and ranging also provides important information regarding rock properties. The high detail of the outcrop images is used for the assessment of reservoir characteristics. The reservoir data leads to an increased understanding of subsurface reservoirs, particularly of the fluvial meanderbelt type. This study shows the importance and drawbacks of a combined digital data collection approach for the analysis of a sedimentary outcrop.

Application of high-throughput plant phenotyping for assessing biophysical traits and drought response in two oak species under controlled environment

Early plant selection for desirable traits is important in tree improvement programs and sustainable forest management. In this study, we demonstrate the use of image based high-throughput plant phenotyping (HTPP, LemnaTec 3D Scanalyzer, Germany), with Red, Green, Blue (RGB), and hyperspectral cameras, to quantify Quercus bicolor and Quercus prinoides seedlings growth and development [plant height, projected leaf area (LA), plant/canopy width, ConvexHull, and plant aspect ratio], and assess their response to a dry-down period, under controlled environment. HTPP images were validated against low throughput measurements, including gas exchange, leaf spectral properties, and morphological traits. Using HTPP, we recorded significant differences in growth dynamic in examined species, with faster initial growth rate early in the growing season, higher photosynthetic rates, larger LA, and seedling dimension, in Q. bicolor, compared to Q. prinoides. This has ecological implications on species responses to shading and timing of drought stress, as well as their competitive relationship with each other and with other species under changing climate. HTTP showed that both growth and leaf expansion ceased under dry-down treatment. Image derived and measured morphological traits were highly and significantly correlated under both well-watered and dry-down conditions for both species. To obtain meaningful physiological information using spectrometry, we calculated 12 vegetation indices (VIs) from both HTPP and handheld spectrometers. Vogelmann and Maccioni indices had the highest correlations across methods, suggesting their potential use for assessing oak seedlings performance and health. Our results emphasized the importance of VIs ground truthing, since VIs performance can vary significantly between species and treatments. HTPP tools can successfully be used to effectively assess forest seedlings of the two Quercus species, important for early plant selection for forest management purposes and tree improvement programs.

Non-invasive diagnostics of Liberibacter disease on tomatoes using a hand-held Raman spectrometer.

Hand-held Raman spectroscopy can be used for confirmatory, non-invasive and non-destructive detection and identification of two haplotypes of Liberibacter disease on tomatoes. Using this spectroscopic approach, structural changes in carotenoids, xylan, cellulose and pectin that are associ-ated with this bacterial disease can be determined. 'Candidatus Liberibacter solanacearum' (Lso) is a phloem-limited Gram-negative bacterium that infects crops worldwide. In North America, two haplotypes of Lso (LsoA and LsoB) are transmitted by the potato psyllid, Bactericera cockerelli (Sulč), and infect many solanaceous crops such as potato and tomato. Infected plants exhibit chlorosis, severe stunting, leaf cupping, and scorching. Polymerase chain reaction (PCR) and potato tuber frying are commonly used methods for diagnostics of the plant disease caused by Lso. However, they are time-consuming, costly, destructive to the sample, and often not sensitive enough to detect the pathogen in the early infection stage. Raman spectroscopy (RS) is a noninvasive, nondestructive, analytical technique, which probes chemical composition of analyzed samples. In this study, we demonstrate that Lso infection can be diagnosed by non-invasive spectroscopic analysis of tomato leaves three weeks following infection, before the development of aerial symptoms. In combination with chemometric analyses, Raman spectroscopy allows for 80% accurate diagnostics of Liberibacter disease caused by each of the two different haplotypes. This diagnostics approach is portable and sample agnostic, suggesting that it could be utilized for other crops and could be conducted autonomously.

Detection of Soil Total Nitrogen, Phosphorus and Potassium Content Based on the Spectral Information of Citrus Canopy

The content of total nitrogen, phosphorus and potassium in the soil is an important basis for calculating the best fertilization amount and realizing the reasonable fertilization of the orange planting soil in time and accurately. In this research, hyper-spectral technology is applied to detect the three soil nutrient elements in the cultivated soil of citrus trees. Four spectral bands with central wavelengths of 660, 780, 870 and 970 nm and width of 20 nm are selected to measure the spectral reflectance of the potted kumquats canopy by hand-held spectrometer. At the same time, the content of total nitrogen, phosphorus and potassium in the cultivated soil of kumquat is determined using traditional methods. The correlation between the spectral information of kumquat canopy and the content of soil nutrient elements is analyzed by correlation coefficient method. The prediction model of soil nutrient element content based on the spectral information is established by multiple linear regression method. The results showed that the total potassium content of soil is significantly correlated with the spectral reflectance at 660 nm wave band and significantly correlated with the spectral indexes of R660/R780, R660/R870 and R660/R970. R2 of the prediction model of total potassium content established on the basis of spectral reflectance and ratio spectral index of the selected band is 0.756 and 0.857 respectively, which shows good prediction effect of the model. There is no significant correlation between the spectral reflectance and ratio spectral index of the selected band towards the total soil nitrogen and phosphorus content and it cannot be used for the rapid measurement of total nitrogen and phosphorus content. Further study is needed to select suitable spectral band and spectral index.

Qualitative Analysis and Phenotyping with Raman Spectroscopy

Currently one of the biggest dilemmas facing the world is the ability of food production to meet the challenges of the ever-increasing world population. Currently there is over a billion people suffering from malnutrition, either from poor quality or lack of food. Nutrient content of food can be determined by a variety of methods which have issues such as slow analysis or sample destruction. Our lab has demonstrated that Raman spectroscopy (RS), a spectroscopic method, can also be used to assess nutrient content of maize (Zea mays), one of the most widely cultivated grain in the world. Using a hand-held Raman spectrometer, we predicted the content of carbohydrates, fibers, carotenoids and proteins in six different varieties of maize. This analysis requires only a single maize kernel and it is fast (1s), portable, non-invasive and non-destructive. Moreover, we showed that RS in combination with chemometric methods can be used for highly accurate (approximately 90%) spectroscopic typing of maize, which is important for plant breeders and farmers. Our next step is to try and build a standard curve for accurate measure of nutrient content using Raman. If this technology can be calibrated, we can further use technology to our advantage by using Raman systems on combines and grain elevators to perform mass scans to determine grain quality.

Facies associations, detrital clay grain coats and mineralogical characterization of the Gironde estuary tidal bars: A modern analogue for deeply buried estuarine sandstone reservoirs

Abstract Estuarine tidal bar sandstones are complex reservoir geobodies commonly exploited by the oil and gas industry. In order to better predict the reservoir potential of these geobodies, this study provides a modern-day reservoir analogue, describing tidal bars in the inner and outer Gironde estuary from the microscopic to the macroscopic scale. The originality of this work lies in the multi-scale study of modern estuarine tidal bars based on numerous piston cores extracted in a high-energy environment. This work demonstrates that these tidal bars are composite sedimentary bodies made up of individual reservoir sand units separated by thick muddy layers. Their vertical facies associations and internal architectures are controlled by local hydrodynamic variations and seasonal river influxes. Detrital clay grain coats are notably characterized using a portable and handheld mineral spectrometer from the base to the top of the tidal bars. X-ray diffraction and electron microscopes reveal that these coats are mainly composed of di-octahedral smectite, illite, chlorite and kaolinite associated with other components such as diatoms or pyrite. The best reservoir geobodies are those with the minimum clay permeability barriers at the macro and mesoscale. An optimum coated grain content and clay fraction volume is also needed for generating authigenic clay coatings and inhibiting quartz overgrowth. These conditions are met within the tidal sand bars of the outer estuary funnel that are expected to be the best reservoir geobodies in deeply buried sandstones.

Effect of scanning samples through polypropylene film on predicting nitrogen content of forage using handheld NIR

This study examined the effect of collecting near infrared (NIR) spectra of forage samples through a transparent polypropylene (PP) plastic film instead of glass cups on calibrating two handheld NIR spectrometers to nitrogen content (N). The first device was a transportable spectrometer (H1) covering 790–2500 nm at 1 nm interval, while the second device was a smartphone spectrometer (H2) covering 900–1700 nm at 4 nm interval. The spectra from each spectrometer were subjected to principal component analysis (PCA) to identify wavebands for PP packaging that would interfere in subsequent partial least squares (PLS) regression modeling to predict N. PCA results showed that the loadings of the first principal component (PC1) of the first derivative of the spectra from H1 and loadings of the second principal component (PC2) of the second derivative of the spectra from H2 were useful in identifying wavebands due to PP film. Regression models for H1 had better prediction performance when spectra were collected through glass than through PP films, in terms of coefficient of determination (r² = 0.958), standard error of prediction (SEP = 0.96 g kg^-1), and ratio of performance to deviation (RPD) = 4.93 vs. (r² = 0.942, SEP = 1.13 g kg^-1, and RPD = 4.17). Similar results were obtained for H2 using spectra collected through glass (r² = 0.821, SEP = 1.73 g kg^-1, and RPD = 2.72) than through PP (r² = 0.499, SEP = 2.99 g kg^-1, and RPD = 1.57). Removing peaks due to PP in the sample spectra improved the PLS models for H1 (r² = 0.959, SEP = 0.94 g kg^-1, and RPD = 5.02), but not for H2 (r² = 0.521, SEP = 3.17 g kg^-1, and RPD = 1.49). Hence, scanning samples through PP films can reduce the accuracy of predicting N, but for some handheld NIR spectrometers, this could be overcome by excluding wavebands due to PP.

Surface-enhanced Raman spectroscopy (SERS) for detection of VX and HD in the gas phase using a hand-held Raman spectrometer

A sensitive surface-enhanced Raman spectroscopy (SERS) substrate was developed to enable hand-held Raman spectrometers to detect gas-phase VX and HD. The substrate comprised Au nanoparticles modified onto quartz fibres. Limits of detection (LOD) of 0.008 μg L-1 and 0.054 μg L-1 were achieved for VX and HD, respectively. Gas-phase experiments were performed using a homemade gas-phase flow system inside a climatic chamber at 25 °C and 50% relative humidity. Preliminary experiments were conducted using VX and HD in solution with Au and Ag nanoparticle colloidal suspensions. We developed and optimized several SERS methods for detection of VX and HD in solution. Gold nanoparticles were optimal for detection of VX and HD and were modified onto quartz fibres for gas-phase detection. The LODs for HD and VX detection in solution were 1.8 × 10-3 μg mL-1 (1.1 × 10-8 M) and 2.5 × 10-3 μg mL-1 (9.3 × 10-9 M), respectively. This study demonstrates that integration of SERS substrates with hand-held Raman spectrometers expands the applicability of Raman technology to homeland security, as reflected by increased sensitivity and gas-phase detection capabilities.

Confirmatory non-invasive and non-destructive differentiation between hemp and cannabis using a hand-held Raman spectrometer

Cannabis is a generic term that is used to denote hemp plants (Cannabis sativa) that produce delta-9-tetrahydrocannabinolic acid (THCA) in amounts higher than industrial hemp. While THCA itself is not considered psychoactive, it is the source of the psychoactive delta-9 tetrahydrocannabinol (THC) that forms from its oxidation. About 147 million people, which is around 2.5% of the world population, consume cannabis. This makes cannabis by far the most widely cultivated and trafficked illicit drug in the world. Such enormous popularity of cannabis requires substantial effort by border control and law enforcement agencies to control illegal trafficking and distribution. Confirmatory diagnostics of cannabis is currently done by high pressure liquid chromatography (HPLC), which requires sample transportation to a certified laboratory, making THC diagnostics extremely time and labor consuming. This catalyzed a push towards development of a portable, confirmatory, non-invasive and non-destructive approach for cannabis diagnostics that could be performed by a police officer directly in the field to verify illicit drug possession or transport. Raman spectroscopy (RS) is a modern analytical technique that meets all these strict expectations. In this manuscript, we show that RS can be used to determine whether plant material is hemp or cannabis with 100% accuracy. We also demonstrate that RS can be used to probe the content of THCA in the analyzed samples. These findings suggest that a hand-held Raman spectrometer can be an ideal tool for police officers and hemp breeders to enable highly accurate diagnostics of THCA content in plants.

Validation of vegetation coverage and NDVI based on UAV remote sensing method and its response to hydrothermal gradient

To verify the accuracy of MODIS-NDVI data products in deserts and provide guidance for scientific management of desert grasslands in the context of climate change, we examined the responses of fractional vegetation cover (FVC) and normalized difference vegetation index (NDVI) to hydrothermal gradient in arid desert areas using unmanned aerial vehicle (UAV) remote sensing. In Alxa desert region of Inner Mongolia, GreenSeeker handheld spectrometer was used to obtain NDVI (NDVIR) of 100 sampling points. NDVI was extracted by MODIS-NDVI data products (NDVIM), and the accuracy of NDVIM was verified by NDVIR. FVC of each sampling point was obtained through unmanned aerial vehicle remote sensing (FVCU), which was used to examine the FVC that was retrieved by the pixel binary model (FVCM). In addition, combining meteorological data, we examined the responses of FVC and NDVI to hydrothermal gradient based on UAV remote sensing method. The results showed that MODIS-NDVI data products reflected the real NDVI in Alxa area with an accuracy of 84.2%, but NDVIM were 15.7% higher than the actual values. FVCM reflected the vegetation coverage of Alxa region with an accuracy of 83.1%, which were 14.8% lower than the real value. Effects of meteorological factors on NDVI was different, depending on the different acquisition methods. NDVI was affected not only by temperature and precipitation, but also by ground temperature, evaporation and the interaction between evaporation and ground temperature. Because of the different degree of atmospheric influence, NDVIM was more affected by ground temperature, evaporation and precipitation than NDVIR, while NDVIR was more affected by temperature than NDVIM. To examine the changes of vegetation coverage across hydrothermal gradient in desert area, we should consider not only precipitation and temperature, but also the interaction between evaporation, ground temperature and meteorological factors. The interaction between temperature and rainfall, evaporation and ground temperature, and between temperature and evaporation had greater impacts on FVCU.

SiC based charged particle strip sensor spectrometer with neutron detection capability

Silicon carbide (SiC) devices have gained much attention owing to their superior characteristics that make them high-temperature and radiation-hard. The advantage of the SiC arises from its unique combination of electronic and physical properties such as a wide band-gap, high breakdown electric field strength, high saturated electron velocity, and high thermal conductivity. The wide band-gap results in a low intrinsic charge carrier concentration and a radiation hardness. The low intrinsic charge carrier concentration leads to low device leakages at high temperature. The high breakdown strength allows SiC devices to operate at much higher voltages. The aim of this publication is to present current status of a charged particle spectrometer based on a SiC strip detector. The sensor is made of a 4H-SiC (α-SiC) hexagonal crystalline structure material which manifests good spectroscopic characteristics for charged particle detection similar to a standard silicon diode (20 keV FWHM with 5,4857 MeV 241Am alpha particle). To obtain sensors for the charged particle detection out of the SiC bulk material we created Schottky contacts on the top and the Ohmic contact on the bottom. Preparation of the contacts will be discussed alongside the electric characterization of the sensor material. Results of the charged particle and the gamma detection and detection of thermal neutron detection (after a neutron converter deposition) will be presented. There will be also a discussion regarding fast neutron detection. The SiC sensor material was attached to a VATA GP8 based 128 strip readout to form the handheld spectrometer which will be demonstrated.

Laser-induced breakdown spectroscopy for rapid accurate analysis of Mg, Ca, and K in edible sea salts.

A compact laser-induced breakdown spectroscopy (LIBS) instrument and a simple sample preparation method were developed for rapid on-site analysis of Mg, Ca, and K in edible sea salt products. The LIBS instrument was assembled using a small diode-pumped solid-state laser and a handheld spectrometer. Aqueous solutions of salts were prepared and sampled by using pieces of filter papers. The dried filter paper was attached on the flat surface of a silicon wafer and then analyzed by LIBS. Calibration curves were obtained using binary mixtures of ${\rm NaCl} {-} {{\rm MgSO}_4}$NaCl-MgSO4, ${\rm NaCl} {-} {{\rm CaCl}_2}$NaCl-CaCl2, and NaCl-KCl and used to estimate the concentrations of Mg, Ca, and K in 13 edible sea salt products. Matrix effects on the results from LIBS were identified in comparison with those from inductively coupled plasma optical emission spectroscopy. This indicates that the matrix of sea salt samples is significantly different from that of the binary mixture standards. The sea salts with known concentrations of Mg, Ca, and K were employed to match the matrices of samples and standards. This improved analysis accuracy remarkably. Furthermore, an alternative indirect method for estimating the concentration of K was suggested on the basis of the strong positive correlations observed between the concentrations of Mg and K in the sea salt samples.

Open-source, handheld, wireless spectrometer for rapid biochemical assays

Translating spectrometers into a field-portable, open-source analytical device offers great potential for clinical and environmental applications. However, current spectrometers lack one or more of the following features that might be necessary for the next-generation spectrometer: open-source engineering, multi-spectral analysis, rapid mixing, and portable, wireless operation. We herein report a handheld spectrometer made from commercially available parts, including a spectrometer sensor and a microcontroller, thus facilitating development of an open-source bioengineering tool. In contrast to the stereotype of conventional spectrometers, this device is designed as a micropipette, which can not only precisely place a liquid sample onto the sensor, but also rapidly mix assay components for homogeneous biochemical reactions by simple pipetting. In addition to the fluidic functionality, the embedded electronics enables continuous, wireless, multi-spectral analysis. We demonstrate these unique capabilities by evaluating the hemolytic potential of a toxic agent for blood, and the degradation kinetics of an organic pollutant catalyzed by gold nanoparticles. Overall, the brand-new spectrometer represents a rapidly evolving, potentially transformative technology that can facilitate unrestricted use, distribution, reproduction, and modification by non-expert users, and further enable diverse usage, even for unanticipated applications.

Hyperspectral analysis of algal biomass in northern lakes, Churchill, MB, Canada

A hyperspectral approach to quantify algal biomass was studied across 30 shallow ponds in the Hudson Bay Lowlands near Churchill, MB. Normalized difference algal indices (NDAI) were calculated based on hyperspectral measurements of the reflectance collected on shore with a hand-held spectrometer in parallel to estimations of biomass with an in vivo fluorometer designed for benthic algae. Algal biomass and coarse assemblages were differentiated through their spectral reflectance as a demonstration of concept for future upscaling that would be necessary for regional monitoring using remote sensing technology. Results indicated strong agreements between the calculated NDAI for measured reflectance from each pond and that of the isolated benthic zone. Cyanobacteria were the dominant component of the algal community for most ponds. As such, measures of reflectance and use of simple NDAIs may be able to characterize the total biomass of northern ponds. However, the distinction between algal groups may require independent validation of algal assemblages for estimations beyond total biomass. Nonetheless, hyperspectral analysis could provide a strong potential for monitoring northern freshwater systems at a regional scale.