Spectral Sorting Research Articles

Multispectral Sorting Based on Visibly High-Risk Kernels Sourced from Another Country Reduces Fumonisin and Toxigenic Fusarium on Maize Kernels

Fusarium species infect maize crops leading to the production of fumonisin by their toxigenic members. Elimination of microbes is critical in mitigating further postharvest spoilage and toxin accumulation. The current study investigates the efficacy of a previously described multispectral sorting technique to analyze the reduction of fumonisin and toxigenic Fusarium species found contaminating maize kernels in Kenya. Maize samples (n = 99) were collected from six mycotoxin hotspot counties in Kenya (Embu, Meru, Tharaka Nithi, Machakos, Makueni, and Kitui County) and analyzed for aflatoxin and fumonisin using commercial ELISA kits. Aflatoxin levels in majority (91%) of the samples were below the 10 ng/g threshold set by the Kenya Bureau of Standards and therefore not studied further. The 23/99 samples that had >2,000 ng/g of fumonisin were selected for sorting. The sorter was calibrated using kernels sourced from Ghana to reject visibly high-risk kernels for fumonisin contamination using reflectance at nine distinct wavelengths (470–1,550 nm). Accepted and rejected streams were tested for fumonisin using ELISA, and the presence of toxigenic Fusarium using qPCR. After sorting, there was a significant (p < 0.001) reduction of fumonisin, by an average of 1.8 log ng/g (98%) and ranging between 0.14 and 2.7 log ng/g reduction (28–99.8%) with a median mass rejection rate of 1.9% (ranged 0% to 48%). The fumonisin rejection rate ranged between 0 and 99.8% with a median of 77%. There was also a significant reduction (p = 0.005) in the proportion of DNA represented by toxigenic Fusarium, from a mean of 30–1.4%. This study demonstrates the use of multispectral sorting as a potential postharvest intervention tool for the reduction of Fusarium species and preformed fumonisin. The spectral sorting approach of this study suggests that classification algorithms based on high-risk visual features associated with mycotoxin can be applied across different sources of maize to reduce fumonisin.

Machine learning-based aerosol characterization using OCO-2 O2 A-band observations

Aerosol scattering influences the retrieval of the column-averaged dry-air mole fraction of CO2 (XCO2) from the Orbiting Carbon Observatory-2 (OCO-2). This is especially true for surfaces with reflectance close to a critical value where there is very low sensitivity to aerosol loading. A spectral sorting approach was introduced to improve the characterization of aerosols over coastal regions. Here, we generalize this procedure to land surfaces and use a two-step neural network to retrieve aerosol parameters from OCO-2 measurements. We show that, by using a combination of radiance measurements in the continuum and inside the absorption band, both the aerosol optical depth and layer height, as well as their uncertainties, can be accurately predicted. Using the improved aerosol estimates as a priori, we demonstrate that the accuracy of the XCO2 retrieval can be significantly improved compared to the OCO-2 Level-2 Standard product. Furthermore, using simulated observations, we obtain estimates of the error in the retrieved XCO2. These simulations indicate that the bias-corrected OCO-2 Lite data, which is used for flux inversions, may have remaining biases due to interference of aerosol effects.

Mycotoxins contamination of market maize and the potential of density sorting in reducing exposure in unregulated food systems in Kenya

Aflatoxins and fumonisins commonly contaminate key food staples in tropical countries, causing recurring acute and chronic public health problems. The present study was conducted to assess the potential of a simple device designed for density-based sorting of maize for its potential to reduce aflatoxins and fumonisins in diverse samples of naturally contaminated maize. A cross sectional survey was conducted, analysing market maize samples (n=204) from eight counties in Western Kenya. A quarter (25%) of the maize samples were contaminated with aflatoxin B1 above the legal limit of 5 μg/kg and nearly half (48%) were contaminated with fumonisins at levels above the legal limit of 2 μg/g. Analysis of additional samples (n=24) from Meru County showed that contamination of maize with the two toxins was also common in Eastern Kenya. A simple density sorter was used to separate grain samples into heavy and light fractions. With an out-sort rate of 31%, density sorting was effective in separating maize by bulk density and 100-kernel weight (P&lt;0.001). Bulk density was negatively correlated with aflatoxins in unsorted (r=-0.20,P&lt;0.01) and heavy fractions (r=-0.32,P&lt;0.01). Density sorting was effective at reducing fumonisins; for maize samples with &gt;1 μg/g, the heavy (accepted) fraction had 66% lower fumonisins than the unsorted maize. After density sorting, the light and heavy fractions fumonisin levels differed by an average of 8.38 μg/g (P&lt;0.001). However, sorting was not effective at significantly reducing aflatoxin levels in maize that was highly contaminated. A simple density sorting equipment that could be adopted by local small-scale millers has potential to reduce fumonisins in maize. Additional and complementary sorting technologies, such as size screening and spectral sorting might improve the effectiveness of reducing aflatoxins in maize.

Subwavelength, polarimetric color sorting by densely interleaved nano-resonators

Sorting light by spectrum in subwavelength scale emerges as important research due to its potential applications in nanoscale optical devices. Diverse research activities are explored to achieve efficient spectral sorting based on nanostructured metasurfaces by leveraging plasmonic and dielectric resonances. While they show many advantages of controlling light in nanoscale with compact form factor, practical realization of the efficient sorting of light in visible spectrum is still elusive due to the strong optical coupling and crosstalk between nanostructures that are arranged in subwavelength scale. Here, we demonstrate silicon-based ultrathin metasurfaces composed of densely interleaved one-dimensional nano-resonators (meta atoms) with three different widths that function both as efficient spectral sorter and light absorber in the visible regime. We find that the geometric aspect ratio of meta atoms and specific mode of resonance play a crucial role in realizing efficient subwavelength spectral splitting with significantly suppressed crosstalk. The sorting efficiency up to 78% is reported by optimally designing the metasurface. We believe that suggested designing scheme paves an important way to realize ultrathin, subwavelength spectral sorters and to develop nano-scale optical sensors.

Rapid counting and spectral sorting of live coral larvae using large-particle flow cytometry

Research with coral embryos and larvae often requires laborious manual counting and sorting of individual specimens, usually via microscopy. Because many coral species spawn only once per year during a narrow temporal window, sample processing is a time-limiting step for research on the early life-history stages of corals. Flow cytometry, an automated technique for measuring and sorting particles, cells, and cell-clusters, is a potential solution to this bottleneck. Yet most flow cytometers do not accommodate live organisms of the size of most coral embryos (> 250 µm), and sample processing is often destructive. Here we tested the ability of a large-particle flow cytometer with a gentle pneumatic sorting mechanism to process and spectrally sort live and preserved Montipora capitata coral embryos and larvae. Average survival rates of mechanically-sorted larvae were over 90% and were comparable to those achieved by careful hand-sorting. Preserved eggs and embryos remained intact throughout the sorting process and were successfully sorted based on real-time size and fluorescence detection. In-line bright-field microscopy images were captured for each sample object as it passed through the flow-cell, enabling the identification of early-stage embryos (2-cell to morula stage). Samples were counted and sorted at an average rate of 4 s larva−1 and as high as 0.2 s larva−1 for high-density samples. Results presented here suggest that large-particle flow cytometry has the potential to significantly increase efficiency and accuracy of data collection and sample processing during time-limited coral spawning events, facilitating larger-scale and higher-replication studies with an expanded number of species.

Design of infrared microspectrometer based on phase-modulated axilenses

We design and characterize a novel axilens-based diffractive optics platform that flexibly combines efficient point focusing and grating selectivity and is compatible with scalable top-down fabrication based on a four-level phase mask configuration. This is achieved using phase-modulated compact axilens devices that simultaneously focus incident radiation of selected wavelengths at predefined locations with larger focal depths compared with traditional Fresnel lenses. In addition, the proposed devices are polarization-insensitive and maintain a large focusing efficiency over a broad spectral band. Specifically, here we discuss and characterize modulated axilens configurations designed for long-wavelength infrared (LWIR) in the 6 µm–12 µm wavelength range and in the 4 µm–6 µm midwavelength infrared (MWIR) range. These devices are ideally suited for monolithic integration atop the substrate layers of infrared focal plane arrays and for use as compact microspectrometers. We systematically study their focusing efficiency, spectral response, and cross-talk ratio; further, we demonstrate linear control of multiwavelength focusing on a single plane. Our design method leverages Rayleigh–Sommerfeld diffraction theory and is validated numerically using the finite element method. Finally, we demonstrate the application of spatially modulated axilenses to the realization of a compact, single-lens spectrometer. By optimizing our devices, we achieve a minimum distinguishable wavelength interval of Δ λ = 240 n m at λ c = 8 µ m and Δ λ = 165 n m at λ c = 5 µ m . The proposed devices add fundamental spectroscopic capabilities to compact imaging devices for a number of applications ranging from spectral sorting to LWIR and MWIR phase contrast imaging and detection.

Shannon Entropy as an Indicator for Sorting Processes in Hydrothermal Systems.

Hydrothermal processes modify the chemical and mineralogical composition of rock. We studied and quantified the effects of hydrothermal processes on the composition of volcanic rocks by a novel application of the Shannon entropy, which is a measure of uncertainty and commonly applied in information theory. We show here that the Shannon entropies calculated on major elemental chemical composition data and short-wave infrared (SWIR) reflectance spectra of hydrothermally altered rocks are lower than unaltered rocks with a comparable primary composition. The lowering of the Shannon entropy indicates chemical and spectral sorting during hydrothermal alteration of rocks. The hydrothermal processes described in this study present a natural mechanism for transforming energy from heat to increased order in rock. The increased order is manifest as the increased sorting of chemical elements and SWIR absorption features of the rock, and can be measured and quantified by the Shannon entropy. The results are useful for the study of hydrothermal mineral deposits, early life environments and the effects of hydrothermal processes on rocks.

Single plasmon spatial and spectral sorting on a crystalline two-dimensional plasmonic platform

In the context of the emerging field of quantum plasmonics, we demonstrate in this manuscript the wavelength-dependent propagation and sorting of single plasmons launched in a two-dimensional crystalline gold flake by a broadband quantum nanoemitter. The stream of single plasmons in the visible is produced by a nanodiamond hosting a single nitrogen-vacancy color center positioned in the near field of the mesoscopic metallic microplatelet. Spatially and spectrally resolved images of the single plasmon propagation in the pristine hexagonal flake, and then in the same structure after insertion of a Bragg mirror, are obtained by filtered image-plane acquisitions on a leakage-radiation microscope. Our work on two-dimensional crystalline structures paves the way to future fundamental studies and applications in quantum plasmonics.

Constraining the vertical distribution of coastal dust aerosol using OCO-2 O2 A-band measurements

Quantifying the vertical distribution of atmospheric aerosols is crucial for estimating their impact on the Earth's energy budget and climate, improving forecast of air pollution in cities, and reducing biases in the retrieval of greenhouse gases (GHGs) from space. However, to date, passive remote sensing measurements have provided limited information about aerosol extinction profiles. In this study, we propose the use of a spectral sorting approach to constrain the aerosol vertical structure using spectra of reflected sunlight absorption within the molecular oxygen (O2) A-band collected by the Orbiting Carbon Observatory-2 (OCO-2). The effectiveness of the approach is evaluated using spectra acquired over the western Sahara coast by comparing the aerosol profile retrievals with lidar measurements from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Using a radiative transfer model to simulate OCO-2 measurements, we found that high-resolution O2 A-band measurements have high sensitivity to aerosol optical depth (AOD) and aerosol layer height (ALH). Retrieved estimates of AOD and ALH based on a look up table technique show good agreement with CALIPSO measurements, with correlation coefficients of 0.65 and 0.53, respectively. The strength of the proposed spectral sorting technique lies in its ability to identify spectral channels with high sensitivity to AOD and ALH and extract the associated information from the observed radiance in a straightforward manner. The proposed approach has the potential to enable future passive remote sensing missions to map the aerosol vertical distribution on a global scale.

Constraining Aerosol Vertical Profile in the Boundary Layer Using Hyperspectral Measurements of Oxygen Absorption

AbstractThis study attempts to infer aerosol vertical structure in the urban boundary layer using passive hyperspectral measurements. A spectral sorting technique is developed to retrieve total aerosol optical depth (AOD) and effective aerosol layer height (ALH) from hyperspectral measurements in the 1.27‐μm oxygen absorption band by the mountaintop Fourier Transform Spectrometer at the California Laboratory for Atmospheric Remote Sensing instrument (1,673 m above sea level) overlooking the LA basin. Comparison to AOD measurements from Aerosol Robotic Network and aerosol backscatter profile measurements from a Mini MicroPulse Lidar shows agreement, with coefficients of determination (r2) of 0.74 for AOD and 0.57 for effective ALH. On average, the AOD retrieval has an error of 24.9% and root‐mean‐square error of 0.013, while the effective ALH retrieval has an error of 7.8% and root‐mean‐square error of 67.01 m. The proposed method can potentially be applied to existing and future satellite missions with hyperspectral oxygen measurements to constrain aerosol vertical distribution on a global scale.

Spectral sorting of visible light using dielectric gratings

We present the concept of spectral sorting using normalized optical efficiency and systematically study the dielectric based multilayer structure for spectral sorting of visible light with silicon as the absorbing material. We show that by using grating structures, the spectral sorter structures are more efficient when the detector size is less than 1µm, enabling the shrinking of the detector size to the wavelength scale. A comprehensive design strategy is derived that could be used as a design guideline to achieve the sorting of visible light. We show that for pixel size as small as 0.5µm, optical efficiency as high as 80% could be achieved using dielectric based sorting structures.

Plasmonic Multibowtie Aperture Antenna with Fano Resonance for Nanoscale Spectral Sorting

In this work we report a new type of nanostructure, the plasmonic multibowtie aperture antenna with Fano resonance for spectral sorting at the nanoscale. Redistribution of surface current in our device plays a critical role in mode coupling to generate Fano resonance, which has never been carefully discussed before. Numerical analyses show that interactions of the electric field, the surface current, and the resulting magnetic field are all important for achieving the desired spectral sorting. Depending on the constructive or destructive interference between the broadband dipole mode and the narrow band multipole mode, electric near-field amplitude and phase distributions switch dramatically across the Fano resonance, which are observed in real space using transmission-type s-SNOM. Based on the Fano interference, photons ranging from visible to infrared spectrum can be sorted through different channels at the nanoscale according to their wavelengths, which shows apparent advantages over other existing nan...

Two-dimensional analytical modeling of a linear variable filter for spectral order sorting.

A two-dimensional thin film thickness model based on the geometry of a commercial coater which can calculate more effectively the profiles of linear variable filters (LVFs) has been developed. This is done by isolating the substrate plane as an independent coordinate (local coordinate), while the rotation and translation matrices are used to establish the coordinate transformation and combine the characteristic vector with the step function to build a borderline which can conclude whether the local mask will block the deposition or not. The height of the local mask has been increased up to 40 mm in the proposed model, and two-dimensional simulations are developed to obtain a thin film profile deposition on the substrate inside the evaporation chamber to achieve the specific request of producing a LVF zone width in a more economical way than previously reported [Opt. Express23, 5102 (2015)OPEXFF1094-408710.1364/OE.23.005102].

Manufacturing of a Linear Variable Filter for Spectral Order Sorting

An analytical thin film thickness model based on the geometry of a commercial vacuum coating system is proposed. This model can calculate the profiles of linear variable filters (LVFs), which are used to eliminate overlapping orders of spectra due to the use of a diffraction grating and which are fabricated using a local mask, producing a linearly variable thickness. While the filter transmits the first-order wavelength and blocks the second-order wavelength. The 75% and 25% relative thicknesses deviation between the evaporated film and the theoretical model is less than 5%, indicating good suitability for LVF design and fabrication.

Analytical modeling and tolerance analysis of a linear variable filter for spectral order sorting.

This paper proposes an innovative method to overcome the low production rate of current linear variable filter (LVF) fabrication. During the fabrication process, a commercial coater is combined with a local mask on a substrate. The proposed analytical thin film thickness model, which is based on the geometry of the commercial coater, is developed to more effectively calculate the profiles of LVFs. Thickness tolerance, LVF zone width, thin film layer structure, transmission spectrum and the effects of variations in critical parameters of the coater are analyzed. Profile measurements demonstrate the efficacy of local mask theory in the prediction of evaporation profiles with a high degree of accuracy.

Semantic Wordification of Document Collections

AbstractWord clouds have become one of the most widely accepted visual resources for document analysis and visualization, motivating the development of several methods for building layouts of keywords extracted from textual data. Existing methods are effective to demonstrate content, but are not capable of preserving semantic relationships among keywords while still linking the word cloud to the underlying document groups that generated them. Such representation is highly desirable for exploratory analysis of document collections. In this paper we present a novel approach to build document clouds, named ProjCloud that aim at solving both semantical layouts and linking with document sets. ProjCloud generates a semantically consistent layout from a set of documents. Through a multidimensional projection, it is possible to visualize the neighborhood relationship between highly related documents and their corresponding word clouds simultaneously. Additionally, we propose a new algorithm for building word clouds inside polygons, which employs spectral sorting to maintain the semantic relationship among words. The effectiveness and flexibility of our methodology is confirmed when comparisons are made to existing methods. The technique automatically constructs projection based layouts the user may choose to examine in the form of the point clouds or corresponding word clouds, allowing a high degree of control over the exploratory process.

Subwavelength optical absorber with an integrated photon sorter

We provide the experimental and theoretical evidence that several nano-patch antennas assembled within a wavelength-scale region may constitute an efficient and easily tunable multi-band photodetector. The system uses highly confined localization states of light and exhibits a robust spectral sorting capability, paving the way to highly integrated hyperspectral imaging.

Sample Classification Algorithm Based on Spectral Similarity Calculation

According to the field geological sample classification, a spectral similarity the cluster analysis algorithm (SSCA) has been put forward. This algorithm expands and improves the spectra sort encoding algorithm on the spectral sorting and similarity computation, and adds similarity clustering analysis method. Testing on 100 field geological samples using SSCA algorithm, we get the results showing that this algorithm can make further classification for field geological samples to some extent.

4917 Identifying dysplasia within barrett's esophagus using raman spectroscopy.

The detailed histochemical information provided by RS makes it a promising complementary technique for BE surveillance. Aim: To assess the diagnostic potential of RS in identifying dysplasia within BE. Methods: A recently developed near-infrared RS system was used to collect spectra on ex vivobiopsy samples of BE patients undergoing endoscopic surveillance. Spectra were correlated with their corresponding histologic diagnoses and spectral sorting techniques such as neural networks (NN) were evaluated to determine optimal diagnostic algorithm(s) for tissue differentiation. Results: So far, 206 biopsies-spectra from 17 patients have been collected. Results obtained from one type of NN are shown (Table). Dysplasia was identified with sensitivity of 75% and specificity of 92%. Additional work is being performed to see if refined algorithms will improve these results and distinguish between grades of dysplasia. For the first time, the feasibility of obtaining in vivospectra with good signal-to-noise ratio in

Chromium determination in NIST standard urine by resonance ionization mass spectrometry

The technique of resonance ionization mass spectrometry (RIMS) has been applied to elemental chromium determination in standard (NIST) human urine samples. RIMS combines multistep photoionization with mass spectral sorting and detection of the resultant ions to provide high sensitivity and selectivity. The Cr concentration in a NIST standard urine sample has been determined using RIMS/isotope dilution techniques to be 0.093 ± 0.008 μg ml in good agreement with the 0.085 ± 0.006 μg/ml certified value. The results indicate the utility and selectivity of RIMS in isotope dilution analysis of biological samples of complex matrix and history.