Hybrid spatial-temporal Mueller matrix imaging spectropolarimeter for high throughput plant phenotyping.

Many correlations exist between spectral reflectance or transmission with various phenotypic responses from plants. Of interest to us are metabolic characteristics, namely, how the various polarimetric components of plants may correlate to underlying environmental, metabolic, and genotypic differences among different varieties within a given species, as conducted during large field experimental trials. In this paper, we overview a portable Mueller matrix imaging spectropolarimeter, optimized for field use, by combining a temporal and spatial modulation scheme. Key aspects of the design include minimizing the measurement time while maximizing the signal-to-noise ratio by mitigating systematic error. This was achieved while maintaining an imaging capability across multiple measurement wavelengths, spanning the blue to near-infrared spectral region (405-730 nm). To this end, we present our optimization procedure, simulations, and calibration methods. Validation results, which were taken in redundant and non-redundant measurement configurations, indicated that the polarimeter provides average absolute errors of (5.3±2.2)×10-3 and (7.1±3.1)×10-3, respectively. Finally, we provide preliminary field data (depolarization, retardance, and diattenuation) to establish baselines of barren and non-barren Zea maize hybrids (G90 variety), as captured from various leaf and canopy positions during our summer 2022 field experiments. Results indicate that subtle variations in retardance and diattenuation versus leaf canopy position may be present before they are clearly visible in the spectral transmission.

Flexible sensor patch for continuous carbon dioxide monitoring.

Monitoring and measurement of carbon dioxide (CO2) is critical for many fields. The gold standard CO2 sensor, the Severinghaus electrode, has remained unchanged for decades. In recent years, many other CO2 sensor formats, such as detection based upon pH-sensitive dyes, have been demonstrated, opening the door for relatively simple optical detection schemes. However, a majority of these optochemical sensors require complex sensor preparation steps and are difficult to control and repeatably execute. Here, we report a facile CO2 sensor generation method that suffers from none of the typical fabrication issues. The method described here utilizes polydimethylsiloxane (PDMS) as the flexible sensor matrix and 1-hydroxypyrene-3,6,8-trisulfonate (HPTS), a pH-sensitive dye, as the sensing material. HPTS, a base (NaOH), and glycerol are loaded as dense droplets into a thin PDMS layer which is subsequently cured around the droplet. The fabrication process does not require prior knowledge in chemistry or device fabrication and can be completed as quickly as PDMS cures (∼2 h). We demonstrate the application of this thin-patch sensor for in-line CO2 quantification in cell culture media. To this end, we optimized the sensing composition and quantified CO2 in the range of 0-20 kPa. A standard curve was generated with high fidelity (R 2 = 0.998) along with an analytical resolution of 0.5 kPa (3.7 mm Hg). Additionally, the sensor is fully autoclavable for applications requiring sterility and has a long working lifetime. This flexible, simple-to-manufacture sensor has a myriad of potential applications and represents a new, straightforward means for optical carbon dioxide measurement.

Practical spectral photography II: snapshot spectral imaging using linear retarders and microgrid polarization cameras.

Despite recent advances, customized multispectral cameras can be challenging or costly to deploy in some use cases. Complexities span electronic synchronization, multi-camera calibration, parallax and spatial co-registration, and data acquisition from multiple cameras, all of which can hamper their ease of use. This paper discusses a generalized procedure for multispectral sensing using a pixelated polarization camera and anisotropic polymer film retarders to create multivariate optical filters. We then describe the calibration procedure, which leverages neural networks to convert measured data into calibrated spectra (intensity versus wavelength). Experimental results are presented for a multivariate and channeled optical filter. Finally, imaging results taken using a red, green, and blue microgrid polarization camera and the channeled optical filter are presented. Imaging experiments indicated that the calculated spectra's root mean square error is highest in the region where the camera's red, green, and blue filter responses overlap. The average error of the spectral reflectance, measured of our spectralon tiles, was 6.5% for wavelengths spanning 425-675 nm. This technique demonstrates that 12 spectral channels can be obtained with a relatively simple and robust optical setup, and at minimal cost beyond the purchase of the camera.

Multistatic fiber-based system for measuring the Mueller matrix bidirectional reflectance distribution function.

Bidirectionality effects can be a significant confounding factor when measuring hyperspectral reflectance data. The bidirectional reflectance distribution function (BRDF) can effectively characterize the reflectivity of surfaces to correct remote sensing measurements. However, measuring BRDFs can be time-consuming, especially when collecting Mueller matrix BRDF (mmBRDF) measurements of a surface via conventional goniometric techniques. In this paper, we present a system for collecting mmBRDF measurements using static optical fiber detectors that sample the hemisphere surrounding an object. The entrance to each fiber contains a polarization state analyzer configuration, allowing for the simultaneous acquisition of the Stokes vector intensity components at many altitudinal and azimuthal viewing positions. We describe the setup, calibration, and data processing used for this system and present its performance as applied to mmBRDF measurements of a ground glass diffuser.

Computer vision for detecting field-evolved lepidopteran resistance to Bt maize.

BACKGROUND: Resistance evolution of lepidopteran pests to Bacillus thuringiensis (Bt) toxins produced in maize and cotton is a significant issue worldwide. Effective toxin stewardship requires reliable detection of field-evolved resistance to enable the implementation of mitigation strategies. Currently, visual estimates of maize injury are used to document changing susceptibility. In this study, we evaluated an existing maize injury monitoring protocol used to estimate Bt resistance levels in Helicoverpa zea (Lepidoptera: Noctuidae). RESULTS: We detected high interobserver variability across multiple injury metrics, suggesting that the precision and accuracy of maize injury detection could be improved. To do this, we developed a computer vision-based algorithm to measure H. zea injury. Algorithm estimates were more accurate and precise than a sample of human observers. Moreover, observer estimates tended to overpredict H. zea injury, which may increase the false-positive rate, leading to prophylactic insecticide application and unnecessary regulatory action. CONCLUSIONS: Automated detection and tracking of lepidopteran resistance evolution to Bt toxins are critical for genetically engineered crop stewardship to prevent the use of additional insecticides to combat resistant pests. Advantages of this computerized screening are: (i) standardized Bt injury metrics in space and time, (ii) preservation of digital data for cross-referencing when thresholds are reached, and (iii) the ability to increase sample sizes significantly. This technological solution represents a significant step toward improving confidence in resistance monitoring efforts among researchers, regulators and the agricultural biotechnology industry.

Organic-based photodetectors for multiband spectral imaging.

Using organic photodetectors for multispectral sensing is attractive due to their unique capabilities to tune spectral response, transmittance, and polarization sensitivity. Existing methods lack tandem multicolor detection and exhibit high spectral cross talk. We exploit the polarization sensitivity of organic photodetectors, together with birefringent optical filters to design single-pixel multispectral detectors that achieve high spectral selectivity and good radiometric performance. Two different architectures are explored and optimized, including the Solc-based and multitwist-retarder-based organic photodetectors. Although the former demonstrated a higher spectral resolution, the latter enables a more compact sensor as well as greater flexibility in device fabrication.

Quantification of gray mold infection in lettuce using a bispectral imaging system under laboratory conditions.

Gray mold disease caused by the fungus Botrytis cinerea damages many crop hosts worldwide and is responsible for heavy economic losses. Early diagnosis and detection of the disease would allow for more effective crop management practices to prevent outbreaks in field or greenhouse settings. Furthermore, having a simple, non-invasive way to quantify the extent of gray mold disease is important for plant pathologists interested in measuring infection rates. In this paper, we design and build a bispectral imaging system for discriminating between leaf regions infected with gray mold and those that remain unharmed on a lettuce (Lactuca spp.) host. First, we describe a method to select two optimal (high contrast) spectral bands from continuous hyperspectral imagery (450-800 nm). We then explain the process of building a system based on these two spectral bands, located at 540 and 670 nm. The resultant system uses two cameras, with a narrow band-pass spectral filter mounted on each, to measure the bispectral reflectance of a lettuce leaf. The two resulting images are combined using a normalized difference calculation that produces a single image with high contrast between the leaves' infected and healthy regions. A classifier was then created based on the thresholding of single pixel values. We demonstrate that this simple classification produces a true-positive rate of 95.25% with a false-positive rate of 9.316% in laboratory conditions.

Internal defect scanning of sweetpotatoes using interactance spectroscopy.

While standard visible-light imaging offers a fast and inexpensive means of quality analysis of horticultural products, it is generally limited to measuring superficial (surface) defects. Using light at longer (near-infrared) or shorter (X-ray) wavelengths enables the detection of superficial tissue bruising and density defects, respectively; however, it does not enable the optical absorption and scattering properties of sub-dermal tissue to be quantified. This paper applies visible and near-infrared interactance spectroscopy to detect internal necrosis in sweetpotatoes and develops a Zemax scattering simulation that models the measured optical signatures for both healthy and necrotic tissue. This study demonstrates that interactance spectroscopy can detect the unique near-infrared optical signatures of necrotic tissues in sweetpotatoes down to a depth of approximately 5±0.5 mm. We anticipate that light scattering measurement methods will represent a significant improvement over the current destructive analysis methods used to assay for internal defects in sweetpotatoes.

Dual-beam potassium Voigt filter for atomic line imaging.

Spectrally narrowband imaging in remote sensing applications can be advantageous for detecting atomic emission features. This is especially useful in detecting specific constituents within rocket plumes, which are challenging to discern from naturally occurring sunglints. In this paper, we demonstrate a dual-beam technique, implemented with a Wollaston prism, for calibrating a Voigt magneto-optical filter for a linear polarizer's finite extinction ratio, as well as optical misalignment between the linear polarizers' transmission axes. Such a strategy would be key towards expanding the filter's field of view while maintaining its classification capabilities. Validation of the potassium Voigt filter is demonstrated using the simulation tool ElecSus in combination with a potassium hollow cathode lamp. RMS error between the filter's temperature response and that of the simulation was approximately 2%. We then demonstrate the detection of a potassium model rocket motor outdoors alongside a sunglint. Results indicate a 20-fold increase in contrast when using our dual-beam calibration strategy.

Optical crosstalk and off-axis modeling of an intrinsic coincident polarimeter.

Polarimeters have broad applications in remote sensing, astronomy, and biomedical imaging to measure the emitted, reflected, or transmitted state of polarization. An intrinsic coincident (IC) full-Stokes polarimeter was previously demonstrated by our group, in a free space configuration, by using stain-aligned polymer-based organic photovoltaics. To minimize the model's complexity, these were tilted to avoid crosstalk from back-reflections. We present a theoretical model of a monolithic IC polarimeter that considers the back-reflection's influence for on-axis light. The model was validated using a monolithic four-detector polarimeter, which achieved an error of less than 3%. Additionally, an off-axis model was produced and validated for a simpler two detector polarimeter, demonstrating an error between the TM and TE polarized components of less than 3% for angles spanning an 18° incidence cone.

Dual-beam cross-correlation spectrometer for radial velocity measurements.

Measuring the radial velocity of an object can be achieved by quantifying the Doppler shift of Fraunhofer lines. Measurements are typically made using high-resolution conventional spectroscopy, in which the Doppler shift is calculated numerically on a computer. An alternative technique includes cross-correlation spectroscopy, which performs an optical correlation of the incident spectrum against a reference spectrum embedded in the instrument. Many existing correlation spectrometers leverage a chrome mask and obtain a single beam measurement, making the sensors more sensitive to atmospheric turbulence without moving parts. In this paper, we present a static dual-beam polarization-based technique for acquiring cross-correlation spectra that is insensitive to atmospheric turbulence and contains no moving parts. The instrument is based on acquiring light both inside and outside of the solar Fraunhofer lines using a twisted nematic liquid-crystal spatial light modulator. Correlation spectra can be calculated as a ratio of these two components. A model of the dual-beam cross-correlation spectrometer is presented and subsequently validated with experimental observations of Venus. Radial velocity accuracies, as calculated against reference ephemerides, yielded an absolute error less than 0.24%.

Microbolometer with a multi-aperture polymer thin-film array for neural-network-basedtarget identification.

Infrared imaging spectrometers are frequently used for detecting chemicals at standoff distances. Cost, size, and sensitivity are common tradeoffs in this regime, particularly when deploying infrared imaging arrays. In this work, we develop and characterize an infrared snapshot computational imaging spectrometer that leverages a multi-aperture filtered design. A theoretical model is developed, describing the multiplexed encoding technique. The experimental system is then described, including filter optimization and fabrication. Finally, the performance of the system is tested, leveraging a neural-network-based calibration approach, for various indoor and outdoor detection scenarios involving liquid contaminants. The results of our testing demonstrate that the system can detect room-temperature liquid contaminants under cold sky downwelling radiance conditions. We achieve a false positive rate (FPR) of 0.12% at a true positive rate (TPR) of 95% for silicon oil on sand at 18°C and a FPR of 2% at a TPR of 95% for silicon oil on various substrates at 23°C. Results support the efficacy of using uncooled polymer absorption filters for infrared imaging liquid contaminant detectors.

Snapshot channeled imaging spectrometer using geometric phase holograms.

In this paper, we present the design and experimental demonstration of a snapshot imaging spectrometer based on channeled imaging spectrometry (CIS) and channeled imaging polarimetry (CIP). Using a geometric phase microlens array (GPMLA) with multiple focal lengths, the proposed spectrometer selects wavelength components within its designed operating waveband of 450-700 nm. Compared to other snapshot spectral imagers, its key components are especially suitable for roll-to-roll (R2R) rapid fabrication, which gives the spectrometer potential for low-cost mass production. The principles and proof-of-concept experimental system of the sensor are described in detail, followed by lab validation and outdoor measurement results which demonstrate the sensor's ability to resolve spectral and spatial contents under both experimental and natural illumination conditions.

Shear-Enhanced Transfer Printing of Conducting Polymer Thin Films.

Polymer conductors that are solution-processable provide an opportunity to realize low-cost organic electronics. However, coating sequential layers can be hindered by poor surface wetting or dissolution of underlying layers. This has led to the use of transfer printing where solid film inks are transferred from a donor substrate to partially fabricated devices using a stamp. This approach typically requires favorable adhesion differences between the stamp, ink, and receiving substrate. Here, we present a shear-assisted organic printing (SHARP) technique that employs a shear load on a post-less polydimethylsiloxane (PDMS) elastomer stamp to print large-area polymer films that can overcome large unfavorable adhesion differences between the stamp and receiving substrate. We explore the limits of this process by transfer printing poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) films with varied formulation that tune the adhesive fracture energy. Using this platform, we show that the SHARP process is able to overcome a 10-fold unfavorable adhesion differential without the use of a patterned PDMS stamp, enabling large-area printing. The SHARP approach is then used to print PEDOT:PSS films in the fabrication of high-performance semitransparent organic solar cells.

Imaging linear and circular polarization features in leaves with complete Mueller matrix polarimetry.

Spectropolarimetry of intact plant leaves allows to probe the molecular architecture of vegetation photosynthesis in a non-invasive and non-destructive way and, as such, can offer a wealth of physiological information. In addition to the molecular signals due to the photosynthetic machinery, the cell structure and its arrangement within a leaf can create and modify polarization signals. Using Mueller matrix polarimetry with rotating retarder modulation, we have visualized spatial variations in polarization in transmission around the chlorophyll a absorbance band from 650 nm to 710 nm. We show linear and circular polarization measurements of maple leaves and cultivated maize leaves and discuss the corresponding Mueller matrices and the Mueller matrix decompositions, which show distinct features in diattenuation, polarizance, retardance and depolarization. Importantly, while normal leaf tissue shows a typical split signal with both a negative and a positive peak in the induced fractional circular polarization and circular dichroism, the signals close to the veins only display a negative band. The results are similar to the negative band as reported earlier for single macrodomains. We discuss the possible role of the chloroplast orientation around the veins as a cause of this phenomenon. Systematic artefacts are ruled out as three independent measurements by different instruments gave similar results. These results provide better insight into circular polarization measurements on whole leaves and options for vegetation remote sensing using circular polarization.

Mueller matrix polarimetry on plasma sprayed thermal barrier coatings for porosity measurement.

Yttria-stabilized zirconia (YSZ) is the most widely used material for thermal plasma sprayed thermal barrier coatings (TBCs) used to protect gas turbine engine parts in demanding operation environments. The superior material properties of YSZ coatings are related to their internal porosity level. By quantifying the porosity level, tighter control on the spraying process can be achieved to produce reliable coatings. Currently, destructive measurement methods are widely used to measure the porosity level. In this paper, we describe a novel nondestructive approach that is applicable to classify the porosity level of plasma sprayed YSZ TBCs via Mueller matrix polarimetry. A rotating retarder Mueller matrix polarimeter was used to measure the polarization properties of the plasma sprayed YSZ coatings with different porosity levels. From these measurements, it was determined that a sample's measured depolarization ratio is dependent on the sample's surface roughness and porosity level. To this end, we correlate the depolarization ratio with the samples' surface roughness, as measured by a contact profilometer, as well as the total porosity level, in percentage measured using a micrograph and stereological analysis. With the use of this technique, a full-field and rapid measurement of porosity level can be achieved.

Spatially heterodyned snapshot imaging spectrometer.

Snapshot hyperspectral imaging Fourier transform (SHIFT) spectrometers are a promising technology in optical detection and target identification. For any imaging spectrometer, spatial, spectral, and temporal resolution, along with form factor, power consumption, and computational complexity are often the design considerations for a desired application. Motivated by the need for high spectral resolution systems, capable of real-time implementation, we demonstrate improvements to the spectral resolution and computation trade-space. In this paper, we discuss the implementation of spatial heterodyning, using polarization gratings, to improve the spectral resolution trade space of a SHIFT spectrometer. Additionally, we employ neural networks to reduce the computational complexity required for data reduction, as appropriate for real-time imaging applications. Ultimately, with this method we demonstrate an 87% decrease in processing steps when compared to Fourier techniques. Additionally, we show an 80% reduction in spectral reconstruction error and a 30% increase in spatial fidelity when compared to linear operator techniques.

Achromatic Wollaston prism beam splitter using polarization gratings.

We describe a method to achromatize a Wollaston prism beam splitter by combining it with a polarization grating. The advantage of this technique, compared to refractive methods of correction, is that only one type of birefringent crystal is needed. Additionally, the assembly can be made thinner while remaining achromatized. In this Letter, a model for the achromatized grating prism is formulated. Experimental validation is conducted by achromatizing a calcite Wollaston prism (apex angle of 5.35°) using a polarization grating with a spatial period of 253 µm. We found that the primary dispersion was reduced by approximately 6.5 times for wavelengths spanning the conventional F, d, and C Fraunhofer lines (486 to 656 nm).

Imaging of in vitro parenteral drug precipitation.

Solid particulate matter introduced into the bloodstream as a result of parenteral drug administration can produce serious pathological conditions. Particulate matter that cannot be eliminated by pre-infusion filtration is often the result of drug precipitation that occurs when certain parenteral formulations are mixed with blood. A new device is designed to model the mixing of drug formulations with flowing blood utilizing a uniquely designed flow cell and a CCD camera to view the formulation as it is mixed with a blood surrogate in real time. The performance of the proposed device is measured using 3 commercially available parenteral formulations previously tested using a validated in vitro model.

Neural network calibration of a snapshot birefringent Fourier transform spectrometer with periodic phase errors.

Systematic phase errors in Fourier transform spectroscopy can severely degrade the calculated spectra. Compensation of these errors is typically accomplished using post-processing techniques, such as Fourier deconvolution, linear unmixing, or iterative solvers. This results in increased computational complexity when reconstructing and calibrating many parallel interference patterns. In this paper, we describe a new method of calibrating a Fourier transform spectrometer based on the use of artificial neural networks (ANNs). In this way, it is demonstrated that a simpler and more straightforward reconstruction process can be achieved at the cost of additional calibration equipment. To this end, we provide a theoretical model for general systematic phase errors in a polarization birefringent interferometer. This is followed by a discussion of our experimental setup and a demonstration of our technique, as applied to data with and without phase error. The technique's utility is then supported by comparison to alternative reconstruction techniques using fast Fourier transforms (FFTs) and linear unmixing.