Multispectral Reflectance Imaging Research Articles

Reflectance Spectroscopy as a Novel Tool for Thickness Measurements of Paint Layers.

A major challenge in heritage science is the non-invasive cross-sectional analysis of paintings. When low-energy probes are used, the presence of opaque media can significantly hinder the penetration of incident radiation, as well as the collection of the backscattered signal. Currently, no technique is capable of uniquely and noninvasively measuring the micrometric thickness of heterogeneous materials, such as pictorial layers, for any painting material. The aim of this work was to explore the possibility of extracting stratigraphic information from reflectance spectra obtained by diffuse reflectance spectroscopy (DRS). We tested the proposed approach on single layers of ten pure acrylic paints. The chemical composition of each paint was first characterised by micro-Raman and laser-induced breakdown spectroscopies. The spectral behaviour was analysed by both Fibre Optics Reflectance Spectroscopy (FORS) and Vis-NIR multispectral reflectance imaging. We showed that there is a clear correlation between the spectral response of acrylic paint layers and their micrometric thickness, which was previously measured by Optical Coherence Tomography (OCT). Based on significant spectral features, exponential functions of reflectance vs. thickness were obtained for each paint, which can be used as calibration curves for thickness measurements. To the best of our knowledge, similar approaches for cross-sectional measurements of paint layers have never been tested.

Noninvasive Detection of Salt Stress in Cotton Seedlings by Combining Multicolor Fluorescence–Multispectral Reflectance Imaging with EfficientNet-OB2

Salt stress is considered one of the primary threats to cotton production. Although cotton is found to have reasonable salt tolerance, it is sensitive to salt stress during the seedling stage. This research aimed to propose an effective method for rapidly detecting salt stress of cotton seedlings using multicolor fluorescence–multispectral reflectance imaging coupled with deep learning. A prototyping platform that can obtain multicolor fluorescence and multispectral reflectance images synchronously was developed to get different characteristics of each cotton seedling. The experiments revealed that salt stress harmed cotton seedlings with an increase in malondialdehyde and a decrease in chlorophyll content, superoxide dismutase, and catalase after 17 days of salt stress. The Relief algorithm and principal component analysis were introduced to reduce data dimension with the first 9 principal component images (PC1 to PC9) accounting for 95.2% of the original variations. An optimized EfficientNet-B2 (EfficientNet-OB2), purposely used for a fixed resource budget, was established to detect salt stress by optimizing a proportional number of convolution kernels assigned to the first convolution according to the corresponding contributions of PC1 to PC9 images. EfficientNet-OB2 achieved an accuracy of 84.80%, 91.18%, and 95.10% for 5, 10, and 17 days of salt stress, respectively, which outperformed EfficientNet-B2 and EfficientNet-OB4 with higher training speed and fewer parameters. The results demonstrate the potential of combining multicolor fluorescence–multispectral reflectance imaging with the deep learning model EfficientNet-OB2 for salt stress detection of cotton at the seedling stage, which can be further deployed in mobile platforms for high-throughput screening in the field.

Indocyanine Green Angiography Overpredicts Postoperative Necrosis Compared to Multispectral Reflectance Imaging.

Sufficient perfusion is foundational to successful reconstructive surgery. Various technologies have been developed to help determine whether tissue is adequately perfused, or whether it will be prone to necrosis postoperatively. Indocyanine green (ICG) angiography is one such method that uses fluorescence and analyzes tissue perfusion. Multispectral reflectance imaging (MSRI) is an alternative technology that analyzes optical properties of oxygenated and deoxygenated hemoglobin to determine tissue viability. Because tissue in low-perfusion states may still survive because of sufficient oxygenation, the authors hypothesized that compared to MSRI, ICG angiography overpredicts necrosis, potentially resulting in unnecessary resection of viable tissue. This study expands on preliminary work to investigate this hypothesis. This was a prospective cohort of patients undergoing prepectoral direct implant reconstruction at a single institution. Each patient was examined intraoperatively with both ICG angiography and MSRI. Decisions to resect tissue were made in conjunction with MSRI and ICG images collected purely for data analysis. Patients were followed postoperatively for at least 2 months for signs of postoperative necrosis. Fifty-three cases were included. ICG angiography accurately predicted viability in 40 of 40 patients (100%) and incorrectly predicted necrosis in 11 of 13 patients (84.6%). Simultaneously, MSRI predicted necrosis in zero patients and accurately predicted viability in 51 of 53 patients (96.2%). There was no statistically significant difference in demographic data among patients predicted to experience necrosis by means of ICG angiography versus those predicted to have entirely viable tissue. This study suggests that ICG angiography is prone to overpredicting postoperative necrosis in comparison to MSRI. This study suggests that multispectral reflectance imaging may benefit practicing plastic surgeons in determining the likelihood of postoperative necrosis. Diagnostic, II.

Combining multicolor fluorescence imaging with multispectral reflectance imaging for rapid citrus Huanglongbing detection based on lightweight convolutional neural network using a handheld device

Citrus Huanglongbing (HLB) has posed a great challenge to the citrus production. Timely removal of HLB infected trees was considered as one of the most effective strategies for citrus orchard management. Therefore, rapid detection of HLB disease is urgently needed. The study was aimed to propose an effective method for HLB disease detection by developing a handheld device to capture multicolor fluorescence and multispectral reflectance images synchronously. Additionally, the deep learning and transfer learning technologies were introduced for citrus HLB disease detection. The results demonstrated that the lightweight convolutional neural network (MobileNetV3) can achieve an overall accuracy of 92.1% with the false negative rate of 12.1% at epochs of 33 by combining multicolor fluorescence with multispectral reflectance images as the input of MobileNetV3 model using the dataset of Navel orange. It implied that structural and physiological information from reflectance images and multicolor fluorescence images relating to photosynthesis and secondary metabolites were valuable for rapid HLB disease detection. The transfer learning method of fine-tuning model obtained a superior transferring ability than that of reuse-model with the overall accuracy of 96.5% for Ponkan. These results demonstrated the feasibility of developed handheld device based on multicolor fluorescence and multispectral reflectance imaging combined with deep learning and transfer learning technologies for high throughput HLB disease detection in different infected statuses and cultivars.

Improving Urban Impervious Surfaces Mapping through Integrating Statistical Methods and Spectral Mixture Analysis

Impervious surfaces have been widely considered as the key indicator for evaluating urbanization and environmental quality. As one of the most widely applied methods, spectral mixture analysis (SMA) has been commonly used for mapping urban impervious surface fractions. When implementing SMA, the original multispectral remote-sensing reflectance images are served as the foundation and key to successful SMA. However, the limited spectral variances among different land covers from the original reflectance images make it challenging in information extraction and results in unsatisfactory mapping results. To address this issue, a new method has been proposed in this study to improve urban impervious surface mapping through integrating statistical methods and SMA. In particular, two traditional statistical methods, principal component analysis (PCA) and minimum noise fraction rotation (MNF) were applied to highlight the spectral variances among different land covers. Three endmember classes (impervious surface, soil, and vegetation) and corresponding spectra were identified and extracted from the vertices of the 2-D space plots generated by the first three components of each of the statistical analysis methods, PCA and MNF. A new dataset was generated by stacking the first three components of the PCA and MNF (in a total of six components), and a fully constrained linear SMA was implemented to map the fractional impervious surfaces. Results indicate that a promising performance has been achieved by the proposed new method with the systematic error (SE) of −3.45% and mean absolute error (MAE) of 11.52%. Comparative analysis results also show a much better performance achieved by the proposed statistical method-based SMA than the conventional SMA.

Snapshot Multispectral Imaging Is Not Inferior to SPY Laser Fluorescence Imaging When Predicting Murine Flap Necrosis.

Objective assessment of tissue viability is critical to improve outcomes of cosmetic and reconstructive procedures. A widely used method to predict tissue viability is indocyanine green angiography. The authors present an alternative method that determines the relative proportions of oxyhemoglobin to deoxyhemoglobin through multispectral reflectance imaging. This affordable, hand-held device is noninvasive and may be used in clinic settings. The authors hypothesize that multispectral reflectance imaging is not inferior to indocyanine green angiography in predicting flap necrosis in the murine model. Reverse McFarlane skin flaps measuring 10 × 3 cm were raised on 300- to 400-g male Sprague-Dawley rats. Indocyanine green angiography and multispectral reflectance imaging was performed before surgery, immediately after surgery, and 30 minutes after surgery. Clinical outcome images acquired 72 hours after surgery were evaluated by three independent plastic surgeons. Objective data obtained immediately after surgery were compared to postsurgical clinical outcomes to determine which method more accurately predicted flap necrosis. Nine reverse McFarlane skin flaps were evaluated 72 hours after flap elevation. Data analysis demonstrated that the 95 percent confidence intervals for the sensitivity of postoperative multispectral reflectance imaging and indocyanine green angiography imaging to predict 72-hour tissue viability at a fixed specificity of 90 percent for predicting tissue necrosis were 86.3 to 91.0 and 79.1 to 86.9, respectively. In this experimental animal model, multispectral reflectance imaging does not appear to be inferior to indocyanine green angiography in detecting compromised tissue viability. With the advantages of noninvasiveness, portability, affordability, and lack of disposables, multispectral reflectance imaging has an exciting potential for widespread use in cosmetic and reconstructive procedures.

Short-wave infrared light imaging measures tissue moisture and distinguishes superficial from deep burns.

Existing clinical approaches and tools to measure burn tissue destruction are limited resulting in misdiagnosis of injury depth in over 40% of cases. Thus, our objective in this study was to characterize the ability of short-wave infrared (SWIR) imaging to detect moisture levels as a surrogate for tissue viability with resolution to differentiate between burns of various depths. To accomplish our aim, we constructed an imaging system consisting of a broad-band Tungsten light source; 1,200-, 1,650-, 1,940-, and 2,250-nm wavelength filters; and a specialized SWIR camera. We initially used agar slabs to provide a baseline spectrum for SWIR light imaging and demonstrated the differential absorbance at the multiple wavelengths, with 1,940 nm being the highest absorbed wavelength. These spectral bands were then demonstrated to detect levels of moisture in inorganic and in vivo mice models. The multiwavelength SWIR imaging approach was used to diagnose depth of burns using an in vivo porcine burn model. Healthy and injured skin regions were imaged 72 hours after short (20 seconds) and long (60 seconds) burn application, and biopsies were extracted from those regions for histologic analysis. Burn depth analysis based on collagen coagulation histology confirmed the formation of superficial and deep burns. SWIR multispectral reflectance imaging showed enhanced intensity levels in long burned regions, which correlated with histology and distinguished between superficial and deep burns. This SWIR imaging method represents a novel, real-time method to objectively distinguishing superficial from deep burns.

Optical Access to Arteriovenous Cerebral Microcirculation Through a Transparent Cranial Implant.

Microcirculation plays a critical role in physiologic processes and several disease states. Laser speckle imaging (LSI) is a full-field, real-time imaging technique capable of mapping microvessel networks and providing relative flow velocity within the vessels. In this study, we demonstrate that LSI combine with multispectral reflectance imaging (MSRI), which allows for distinction between veins and arteries in the vascular flow maps produced by LSI. We apply this combined technique to mouse cerebral vascular network in vivo, comparing imaging through the skull, to the dura mater and brain directly through a craniectomy, and through a transparent cranial "Window to the Brain" (WttB) implant. The WttB implant used in this study is made of a nanocrystalline Yttria-Stabilized-Zirconia ceramic. MSRI was conducted using white-light illumination and filtering the reflected light for 560, 570, 580, 590, 600, and 610 nm. LSI was conducted using an 810 nm continuous wave near-infrared laser with incident power of 100 mW, and the reflected speckle pattern was captured by a complementary metal-oxide-semiconductor (CMOS) camera. Seven vessel branches were analyzed and comparison was made between imaging through the skull, craniectomy, and WttB implant. Through the skull, MSRI did not detect any vessels, and LSI could not image microvessels. Imaging through the WttB implant, MSRI was able to identify veins versus arteries, and LSI was able to image microvessels with only slightly higher signal-to-noise ratio and lower sharpness than imaging the brain through a craniectomy. This study demonstrates the ability to perform MSRI-LSI across a transparent cranial implant, to allow for cerebral vascular networks to be mapped, including microvessels. These images contain additional information such as vein-artery separation and relative blood flow velocities, information which is of value scientifically and medically. The WttB implant provides substantial improvements over imaging through the murine cranial bone, where microvessels are not visible and MSRI cannot be performed. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc.

Towards real-time multispectral endoscopic imaging for cardiac lesion quality assessment.

Atrial fibrillation (Afib) can lead to life threatening conditions such as heart failure and stroke. During Afib treatment, clinicians aim to repress unusual electrical activity by electrically isolating the pulmonary veins (PV) from the left atrium (LA) using radiofrequency ablation. However, current clinical tools are limited in reliably assessing transmurality of the ablation lesions and detecting the presence of gaps within ablation lines, which can warrant repeat procedures. In this study, we developed an endoscopic multispectral reflectance imaging (eMSI) system for enhanced discrimination of tissue treatment at the PV junction. The system enables direct visualization of cardiac lesions through an endoscope at acquisition rates up to 25 Hz. Five narrowband, high-power LEDs were used to illuminate the sample (450, 530, 625, 810 and 940nm) and combinatory parameters were calculated based on their relative reflectance. A stitching algorithm was employed to generate large field-of-view, multispectral mosaics of the ablated PV junction from individual eMSI images. A total of 79 lesions from 15 swine hearts were imaged, ex vivo. Statistical analysis of the acquired five spectral data sets and ratiometric maps revealed significant differences between transmural lesions, non-transmural lesions around the venoatrial junctions, unablated posterior wall of left atrium tissue, and pulmonary vein (p < 0.0001). A pixel-based quadratic discriminant analysis classifier was applied to distinguish four tissue types: PV, untreated LA, non-transmural and transmural lesions. We demonstrate tissue type classification accuracies of 80.2% and 92.1% for non-transmural and transmural lesions, and 95.0% and 92.8% for PV and untreated LA sites, respectively. These findings showcase the potential of eMSI for lesion validation and may help to improve AFib treatment efficacy.

Quantitative characterization of turbidity by radiative transfer based reflectance imaging.

A new and noncontact approach of multispectral reflectance imaging has been developed to inversely determine the absorption coefficient of μ a , the scattering coefficient of μs and the anisotropy factor g of a turbid target from one measured reflectance image. The incident beam was profiled with a diffuse reflectance standard for deriving both measured and calculated reflectance images. A GPU implemented Monte Carlo code was developed to determine the parameters with a conjugate gradient descent algorithm and the existence of unique solutions was shown. We noninvasively determined embedded region thickness in heterogeneous targets and estimated in vivo optical parameters of nevi from 4 patients between 500 and 950nm for melanoma diagnosis to demonstrate the potentials of quantitative reflectance imaging.

Assessment of multispectral and hyperspectral imaging systems for digitisation of a Russian icon

In a study of multispectral and hyperspectral reflectance imaging, a Round Robin Test assessed the performance of different systems for the spectral digitisation of artworks. A Russian icon, mass-produced in Moscow in 1899, was digitised by ten institutions around Europe. The image quality was assessed by observers, and the reflectance spectra at selected points were reconstructed to characterise the icon’s colourants and to obtain a quantitative estimate of accuracy. The differing spatial resolutions of the systems affected their ability to resolve fine details in the printed pattern. There was a surprisingly wide variation in the quality of imagery, caused by unwanted reflections from both glossy painted and metallic gold areas of the icon’s surface. Specular reflection also degraded the accuracy of the reconstructed reflectance spectrum in some places, indicating the importance of control over the illumination geometry. Some devices that gave excellent results for matte colour charts proved to have poor performance for this demanding test object. There is a need for adoption of standards for digitising cultural heritage objects to achieve greater consistency of system performance and image quality.

Spectral Behavior of White Pigment Mixtures Using Reflectance, Ultraviolet-Fluorescence Spectroscopy, and Multispectral Imaging.

Reflectance spectroscopy, ultraviolet (UV)-fluorescence spectroscopy, and multispectral imaging have been widely employed for pigment identification on paintings. From ancient times to the present, lead white, zinc white, and titanium white have been the most important white pigments used for paintings and they are used as pigment markers for dating a work of art. The spectral behavior of these pigments is reported in several scientific papers and websites, but those of their mixtures are quite unknown. We present a combined nondestructive approach for identifying mixtures of lead white, zinc white, and titanium white as powder and dispersed in two different binder media (egg yolk and linseed oil) by using reflectance spectroscopy, spectrofluorimetry, multispectral reflectance and UV-fluorescence imaging. We propose a novel approach for mapping the presence of white pigments in paintings by false color images obtained from multispectral reflectance and UV-fluorescence images. We found that the presence of lead white mixed with either zinc white or titanium white is highly detectable. Zinc white mixed with lead white or titanium white can be identified due to its UV-fluorescence emission, whereas titanium white in association with lead white or zinc white is distinguishable by its reflectance spectral features. In most cases, the UV-fluorescence analyses also permit the recognition of the binder media in which the pigments are dispersed.

Development of a Multimodal Colposcopy for Characterization of Cervical Intraepithelial Neoplasia

To develop and evaluate the clinical application of a multimodal colposcopy combining multispectral reflectance, autofluorescence, and red, green, blue (RGB) imaging for noninvasive characterization of cervical intraepithelial neoplasia (CIN). We developed a multimodal colposcopy system that combined multispectral reflectance, autofluorescence, and RGB imaging for noninvasive characterization of CIN. We studied the optical properties of cervical tissue first; then the imaging system was designed and tested in a clinical trial where comprehensive datasets were acquired and analyzed to differentiate between squamous normal and high grade types of cervical tissue. The custom-designed multimodal colposcopy is capable of acquiring multispectral reflectance images, autofluorescence images, and RGB images of cervical tissue consecutively. The classification algorithm was employed on both normal and abnormal cases for image segmentation. The performance characteristics of this system were comparable to the gold standard histopathologic measurements with statistical significance. Our pilot study demonstrated the clinical potential of this multimodal colposcopic system for noninvasive characterization of CIN. The proposed system was simple, noninvasive, cost-effective, and portable, making it a suitable device for deployment in developing countries or rural regions of limited resources.

Potential of multispectral imaging for real-time determination of colour change and moisture distribution in carrot slices during hot air dehydration

Colour and moisture content are important indices in quality monitoring of dehydrating carrot slices during dehydration process. This study investigated the potential of using multispectral imaging for real-time and non-destructive determination of colour change and moisture distribution during the hot air dehydration of carrot slices. Multispectral reflectance images, ranging from 405 to 970nm, were acquired and then calibrated based on three chemometrics models of partial least squares (PLS), least squares-support vector machines (LS-SVM), and back propagation neural network (BPNN), respectively. Compared with PLS and LS-SVM, BPNN considerably improved the prediction performance with coefficient of determination in prediction (RP2)=0.991, root-mean-square error of prediction (RMSEP)=1.482% and residual predictive deviation (RPD)=11.378 for moisture content. It was concluded that multispectral imaging has an excellent potential for rapid, non-destructive and simultaneous determination of colour change and moisture distribution of carrot slices during dehydration.

Classification of peacock feather reflectance using principal component analysis similarity factors from multispectral imaging data.

Iridescent structural colors in biology exhibit sophisticated spatially-varying reflectance properties that depend on both the illumination and viewing angles. The classification of such spectral and spatial information in iridescent structurally colored surfaces is important to elucidate the functional role of irregularity and to improve understanding of color pattern formation at different length scales. In this study, we propose a non-invasive method for the spectral classification of spatial reflectance patterns at the micron scale based on the multispectral imaging technique and the principal component analysis similarity factor (PCASF). We demonstrate the effectiveness of this approach and its component methods by detailing its use in the study of the angle-dependent reflectance properties of Pavo cristatus (the common peacock) feathers, a species of peafowl very well known to exhibit bright and saturated iridescent colors. We show that multispectral reflectance imaging and PCASF approaches can be used as effective tools for spectral recognition of iridescent patterns in the visible spectrum and provide meaningful information for spectral classification of the irregularity of the microstructure in iridescent plumage.

Single-trial estimation of the cerebral metabolic rate of oxygen with imaging photoplethysmography and laser speckle contrast imaging.

Cortical cerebral metabolic rate of oxygen (CMRO(2)) could conventionally be measured by combining laser Doppler flowmetry and multispectral reflectance imaging across multiple trials of stimulation, which compromises the real-time capacity. Monitoring transient change of CMRO(2) has been challenging. In this Letter, imaging photoplethysmography (iPPG) and laser speckle contrast imaging were combined into a multi-modal optical imaging system for single-trial estimation of CMRO(2). In a physiologically stable experiment, the iPPG-based method showed a less than 4% variance in comparison with the conventional method over 20 trials, and its temporal stability could be comparable to that by conventional method over 6 trials. While the oxygen supply was decreased deliberately, the new method was able to detect the transient changes of CMRO(2) in real time, which could not be revealed by the conventional method.

Endothelial dysfunction abrogates the efficacy of normobaric hyperoxia in stroke.

Hyperoxia has been uniformly efficacious in experimental focal cerebral ischemia. However, pilot clinical trials have showed mixed results slowing its translation in patient care. To explain the discordance between experimental and clinical outcomes, we tested the impact of endothelial dysfunction, exceedingly common in stroke patients but under-represented in experimental studies, on the neuroprotective efficacy of normobaric hyperoxia. We used hyperlipidemic apolipoprotein E knock-out and endothelial nitric oxide synthase knock-out mice as models of endothelial dysfunction, and examined the effects of normobaric hyperoxia on tissue perfusion and oxygenation using high-resolution combined laser speckle and multispectral reflectance imaging during distal middle cerebral artery occlusion. In normal wild-type mice, normobaric hyperoxia rapidly and significantly improved tissue perfusion and oxygenation, suppressed peri-infarct depolarizations, reduced infarct volumes, and improved neurological function. In contrast, normobaric hyperoxia worsened perfusion in ischemic brain and failed to reduce infarct volumes or improve neurological function in mice with endothelial dysfunction. These data suggest that the beneficial effects of hyperoxia on ischemic tissue oxygenation, perfusion, and outcome are critically dependent on endothelial nitric oxide synthase function. Therefore, vascular risk factors associated with endothelial dysfunction may predict normobaric hyperoxia nonresponders in ischemic stroke. These data may have implications for myocardial and systemic circulation as well.

Fractal dimension of sparkles in automotive metallic coatings by multispectral imaging measurements.

Sparkle in surface coatings is a property of mirror-like pigment particles that consists of remarkable bright spots over a darker surround under unidirectional illumination. We developed a novel nondestructive method to characterize sparkles based on the multispectral imaging technique, and we focused on automotive metallic coatings containing aluminum flake pigments. Multispectral imaging was done in the visible spectrum at different illumination angles around the test sample. Reflectance spectra at different spatial positions were mapped to color coordinates and visualized in different color spaces. Spectral analysis shows that sparkles exhibit higher reflectance spectra and narrower bandwidths. Colorimetric analysis indicates that sparkles present higher lightness values and are far apart from the bulk of color coordinates spanned by the surround. A box-counting procedure was applied to examine the fractal organization of color coordinates in the CIE 1976 L*a*b* color space. A characteristic noninteger exponent was found at each illumination position. The exponent was independent of the illuminant spectra. Together, these results demonstrate that sparkles are extreme deviations relative to the surround and that their spectral properties can be described as fractal patterns within the color space. Multispectral reflectance imaging provides a powerful, noninvasive method for spectral identification and classification of sparkles from metal flake pigments on the micron scale.

Science applications of a multispectral microscopic imager for the astrobiological exploration of Mars.

Future astrobiological missions to Mars are likely to emphasize the use of rovers with in situ petrologic capabilities for selecting the best samples at a site for in situ analysis with onboard lab instruments or for caching for potential return to Earth. Such observations are central to an understanding of the potential for past habitable conditions at a site and for identifying samples most likely to harbor fossil biosignatures. The Multispectral Microscopic Imager (MMI) provides multispectral reflectance images of geological samples at the microscale, where each image pixel is composed of a visible/shortwave infrared spectrum ranging from 0.46 to 1.73 μm. This spectral range enables the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases, and the detection of hydrated minerals. The MMI advances beyond the capabilities of current microimagers on Mars by extending the spectral range into the infrared and increasing the number of spectral bands. The design employs multispectral light-emitting diodes and an uncooled indium gallium arsenide focal plane array to achieve a very low mass and high reliability. To better understand and demonstrate the capabilities of the MMI for future surface missions to Mars, we analyzed samples from Mars-relevant analog environments with the MMI. Results indicate that the MMI images faithfully resolve the fine-scale microtextural features of samples and provide important information to help constrain mineral composition. The use of spectral endmember mapping reveals the distribution of Fe-bearing minerals (including silicates and oxides) with high fidelity, along with the presence of hydrated minerals. MMI-based petrogenetic interpretations compare favorably with laboratory-based analyses, revealing the value of the MMI for future in situ rover-mediated astrobiological exploration of Mars.

Detection Algorithm for Cracks on the Surface of Tomatoes using Multispectral Vis/NIR Reflectance Imagery

Purpose: Tomatoes, an important agricultural product in fresh-cut markets, are sometimes a source of foodborne illness, mainly Salmonella spp. Growth cracks on tomatoes can be a pathway for bacteria, so its detection prior to consumption is important for public health. In this study, multispectral Visib le/Near-Infrared (NIR) reflectance imaging techniques were used to determine optimal wavebands for the classification of defect tomatoes. Methods: Hyperspectral reflectance images were collected from samples of naturally cracked tomatoes. To classify the resulting images, the selected wavelength bands were subjected to two-band permutations, and a supervised classification method was used. Results: The results showed that two optimal wavelengths, 713.8 nm and 718.6 nm, could be used to identify cracked spots on tomato surfaces with a correct classification rate of 91.1%. The result indicates that multispectral reflectance imaging with optimized wavebands from hyperspectral images is an effective technique for the classification of defective tomatoes. Conclusions: Although it can be susceptible to specular interference, the multispectral reflectance imaging is an appropriate method for commercial applications because it is faster and much less expensive than Near-Infrared or fluorescence imaging techniques.