Optical sensing method for screening disease in melon seeds by using optical coherence tomography

Using Optical Coherence Tomography in Plant Biology Research: Review and Prospects

Visualizing the microscopic structure of plants in vivo, non-invasively, and in real-time is the Holy Grail of botany. Optical coherence tomography (OCT) has all the characteristics necessary to achieve this feat. Indeed, OCT provides volumetric images of the internal structure of plants without the need for histological preparation. With its micrometric resolution, OCT is commonly used in medicine, primarily in ophthalmology. But it is seldom used in the field of botany. The aim of the present work is thus to review the latest technical development in the field of OCT and to highlight its current use in botany, in order to promote the technique and further advance research in the field of botany.

Non-Destructive Direct Pericarp Thickness Measurement of Sorghum Kernels Using Extended-Focus Optical Coherence Microscopy

Non-destructive measurements of internal morphological structures in plant materials such as seeds are of high interest in agricultural research. The estimation of pericarp thickness is important to understand the grain quality and storage stability of seeds and can play a crucial role in improving crop yield. In this study, we demonstrate the applicability of fiber-based Bessel beam Fourier domain (FD) optical coherence microscopy (OCM) with a nearly constant high lateral resolution maintained at over ~400 µm for direct non-invasive measurement of the pericarp thickness of two different sorghum genotypes. Whereas measurements based on axial profiles need additional knowledge of the pericarp refractive index, en-face views allow for direct distance measurements. We directly determine pericarp thickness from lateral sections with a 3 µm resolution by taking the width of the signal corresponding to the pericarp at the 1/e threshold. These measurements enable differentiation of the two genotypes with 100% accuracy. We find that trading image resolution for acquisition speed and view size reduces the classification accuracy. Average pericarp thicknesses of 74 µm (thick phenotype) and 43 µm (thin phenotype) are obtained from high-resolution lateral sections, and are in good agreement with previously reported measurements of the same genotypes. Extracting the morphological features of plant seeds using Bessel beam FD-OCM is expected to provide valuable information to the food processing industry and plant breeding programs.

Nondestructive in situ monitoring of pea seeds germination using optical coherence tomography

Seed germination and uniform plant stand in the field are the most critical crop growth stages determining the final yield. Pea (Pisum sativum L.) seeds production is often hampered due to the seed dormancy caused by the hard seed coat. Such effect is mainly attributed to poor or uneven germination and unsynchronised seedling emergence. Understanding the time course of water intake and several critical germination indicators can reveal many features of seed germination such as rate and uniformity. This paper used optical coherence tomography (OCT), a noninvasive and cross-sectional imaging technique, to monitor the inner structural changes throughout the germination process. A sequence of cross-sectional OCT images of pea (P. sativum L.) seeds, together with additional microscopic optical images, was recorded continuously and in situ for over 40 h. OCT and microscopic images revealed the changes in the internal structure and the external shape of the pea seeds during germination, respectively. It was found that the cross-sectional OCT images helped to identify the critical indicators distinguishing the different phases of germination pea seeds. Therefore, the presented OCT approach offers a fast and nondestructive way to precisely measure the structural indicators in different germination phases.

Plant Viral Disease Detection: From Molecular Diagnosis to Optical Sensing Technology—A Multidisciplinary Review

Plant viral diseases result in productivity and economic losses to agriculture, necessitating accurate detection for effective control. Lab-based molecular testing is the gold standard for providing reliable and accurate diagnostics; however, these tests are expensive, time-consuming, and labour-intensive, especially at the field-scale with a large number of samples. Recent advances in optical remote sensing offer tremendous potential for non-destructive diagnostics of plant viral diseases at large spatial scales. This review provides an overview of traditional diagnostic methods followed by a comprehensive description of optical sensing technology, including camera systems, platforms, and spectral data analysis to detect plant viral diseases. The paper is organized along six multidisciplinary sections: (1) Impact of plant viral disease on plant physiology and consequent phenotypic changes, (2) direct diagnostic methods, (3) traditional indirect detection methods, (4) optical sensing technologies, (5) data processing techniques and modelling for disease detection, and (6) comparison of the costs. Finally, the current challenges and novel ideas of optical sensing for detecting plant viruses are discussed.

Early Detection of Mold-Contaminated Peanuts Using Machine Learning and Deep Features Based on Optical Coherence Tomography

Fungal infection is a pre-harvest and post-harvest crisis for farmers of peanuts. In environments with temperatures around 28 °C to 30 °C or relative humidity of approximately 90%, mold-contaminated peanuts have a considerable likelihood to be infected with Aflatoxins. Aflatoxins are known to be highly carcinogenic, posing danger to humans and livestock. In this work, we proposed a new approach for detection of mold-contaminated peanuts at an early stage. The approach employs the optical coherence tomography (OCT) imaging technique and an error-correcting output code (ECOC) based Support Vector Machine (SVM) trained on features extracted using a pre-trained Deep Convolutional Neural Network (DCNN). To this end, mold-contaminated and uncontaminated peanuts were scanned to create a data set of OCT images used for training and evaluation of the ECOC-SVM model. Results showed that the proposed approach is capable of detecting mold-contaminated peanuts with respective accuracies of approximately 85% and 96% after incubation periods of 48 and 96 h.

Remote Sensing of Diseases

Detection, identification, and quantification of plant diseases by sensor techniques are expected to enable a more precise disease control, as sensors are sensitive, objective, and highly available for disease assessment. Recent progress in sensor technology and data processing is very promising; nevertheless, technical constraints and issues inherent to variability in host-pathogen interactions currently limit the use of sensors in various fields of application. The information from spectral [e.g., RGB (red, green, blue)], multispectral, and hyperspectral sensors that measure reflectance, fluorescence, and emission of radiation or from electronic noses that detect volatile organic compounds released from plants or pathogens, as well as the potential of sensors to characterize the health status of crops, is evaluated based on the recent literature. Phytopathological aspects of remote sensing of plant diseases across different scales and for various purposes are discussed, including spatial disease patterns, epidemic spread of pathogens, crop characteristics, and links to disease control. Future challenges in sensor use are identified.

Non-Invasive Morphological Characterization of Rice Leaf Bulliform and Aerenchyma Cellular Regions Using Low Coherence Interferometry

Non-invasive investigation of rice leaf specimens to characterize the morphological formation and particular structural information that is beneficial for agricultural perspective was demonstrated using a low coherence interferometric method called swept source optical coherence tomography (SS-OCT). The acquired results non-invasively revealed morphological properties of rice leaf, such as bulliform cells; aerenchyma, parenchyma, and collenchyma layer; and vascular bundle. Beside aforementioned morphologic characteristics, several leaf characteristics associated with cytological mechanisms of leaf rolling (leaf inclination) were examined for the pre-identification of inevitable necrosis and atrophy of leaf tissues by evaluating acute angle information, such as angular characteristics of the external bi-directional angles between the lower epidermis layer and lower mid-vein, and internal angle of lower mid-vein. To further assist the pre-identification, acquired cross-sections were employed to enumerate the small veins of each leaf specimen. Since mutants enlarge leaf angles due to increased cell division in the adaxial epidermis, healthy and abnormal leaf specimens were morphologically and quantitatively compared. Therefore, the results of the method can be used in agriculture, and SS-OCT shows potential as a rigorous investigation method for selecting mutant infected rice leaf specimens rapidly and non-destructively compared to destructive and time consuming gold-standard methods with a lack of precision.

Biophotonic approach for the characterization of initial bitter-rot progression on apple specimens using optical coherence tomography assessments

The tremendous advances achieved in the biophotonics technologies have intensified the necessity for non-invasive modalities that can characterize diverse biological materials with increased sensitivity and resolution. Optical coherence tomography (OCT) is one of the techniques that has been applied for biological applications in medicine and agriculture to identify structural properties. Herein, we report the successful incorporation of OCT for the identification of morphological changes that occur as a result of the bitter rot disease, through continuous detection of structural changes. Detailed inner morphological structural changes occurring in fruit specimens were precisely analyzed as a function of the disease incubation period using OCT. The conducted histological correlation and quantitative three-dimensional evaluations provide a robust platform for further discoveries related to plant materials. The results highlight the initial identification of bitter rot progression on apple specimens owing to the non-invasive inspection capability of OCT. Therefore, we expect that the proposed method will enable immediate sensitivity improvements in the inspection of plant diseases for postharvest utility.

Non-Destructive Classification of Diversely Stained Capsicum annuum Seed Specimens of Different Cultivars Using Near-Infrared Imaging Based Optical Intensity Detection

The non-destructive classification of plant materials using optical inspection techniques has been gaining much recent attention in the field of agriculture research. Among them, a near-infrared (NIR) imaging method called optical coherence tomography (OCT) has become a well-known agricultural inspection tool since the last decade. Here we investigated the non-destructive identification capability of OCT to classify diversely stained (with various staining agents) Capsicum annuum seed specimens of different cultivars. A swept source (SS-OCT) system with a spectral band of 1310 nm was used to image unstained control C. annuum seeds along with diversely stained Capsicum seeds, belonging to different cultivar varieties, such as C. annuum cv. PR Ppareum, C. annuum cv. PR Yeol, and C. annuum cv. Asia Jeombo. The obtained cross-sectional images were further analyzed for the changes in the intensity of back-scattered light (resulting due to dye pigment material and internal morphological variations) using a depth scan profiling technique to identify the difference among each seed category. The graphically acquired depth scan profiling results revealed that the control specimens exhibit less back-scattered light intensity in depth scan profiles when compared to the stained seed specimens. Furthermore, a significant back-scattered light intensity difference among each different cultivar group can be identified as well. Thus, the potential capability of OCT based depth scan profiling technique for non-destructive classification of diversely stained C. annum seed specimens of different cultivars can be sufficiently confirmed through the proposed scheme. Hence, when compared to conventional seed sorting techniques, OCT can offer multipurpose advantages by performing sorting of seeds in respective to the dye staining and provides internal structural images non-destructively.

In Vivo Non-Destructive Monitoring of Capsicum Annuum Seed Growth with Diverse NaCl Concentrations Using Optical Detection Technique

We demonstrate that optical coherence tomography (OCT) is a plausible optical tool for in vivo detection of plant seeds and its morphological changes during growth. To investigate the direct impact of salt stress on seed germination, the experiment was conducted using Capsicum annuum seeds that were treated with different molar concentrations of NaCl. To determine the optimal concentration for the seed growth, the seeds were monitored for nine consecutive days. In vivo two-dimensional OCT images of the treated seeds were obtained and compared with the images of seeds that were grown using sterile distilled water. The obtained results confirm the feasibility of using OCT for the proposed application. Normalized depth profile analysis was utilized to support the conclusions.

Raman Hyperspectral Imaging for Detection of Watermelon Seeds Infected with Acidovorax citrulli

The bacterial infection of seeds is one of the most important quality factors affecting yield. Conventional detection methods for bacteria-infected seeds, such as biological, serological, and molecular tests, are not feasible since they require expensive equipment, and furthermore, the testing processes are also time-consuming. In this study, we use the Raman hyperspectral imaging technique to distinguish bacteria-infected seeds from healthy seeds as a rapid, accurate, and non-destructive detection tool. We utilize Raman hyperspectral imaging data in the spectral range of 400–1800 cm⁻¹ to determine the optimal band-ratio for the discrimination of watermelon seeds infected by the bacteria Acidovorax citrulli using ANOVA. Two bands at 1076.8 cm⁻¹ and 437 cm⁻¹ are selected as the optimal Raman peaks for the detection of bacteria-infected seeds. The results demonstrate that the Raman hyperspectral imaging technique has a good potential for the detection of bacteria-infected watermelon seeds and that it could form a suitable alternative to conventional methods.

Structural Analysis of Polymer Composites Using Spectral Domain Optical Coherence Tomography

The structural analysis of nylon/graphene oxide (NY/GO) and polyetherblockamide/ trisilinolphenyl-polyhederal oligomeric silsesquioxane (PEBA/t-POSS) composites were performed using high-resolution spectral domain optical coherence tomography (SD-OCT). This optical technology revealed both cross-sectional, as well as sub-layer depth information of sample. The non-destructive real-time imaging demonstrated the nature of defects in the composites. The thickness and location of each defect point in the composites were measured using A-scan analysis on the SD-OCT images. The cross-sectional and volumetric images clearly demonstrate the effectiveness of SD-OCT for composite research, as well as the for industrial quality assurance of polymer materials.

Optical coherence tomography-integrated, wearable (backpack-type), compact diagnostic imaging modality for in situ leaf quality assessment

We developed a compact, wearable diagnostic imaging modality employing optical coherence tomography for in situ plant leaf quality assessments. This system is capable of diagnosing infected leaves at the initial disease stages. Our system is a versatile backpack-type imaging modality with a compact spectrometer, miniature computer, rechargeable power source, and handheld inspection probe. This method enhances real-time in situ specimen inspection through direct implementation of the imaging modality in a plantation. To evaluate the initial performance, field experiments were conducted in apple, pear, and persimmon plantations. Based on the obtained results, we can conclude that the developed imaging modality can be considered as a promising, efficient, convenient, and fast in situ inspection technique for various agricultural fields, which minimizes the limitations of complex tabletop inspection modalities.

Non-destructive evaluation of bacteria-infected watermelon seeds using visible/near-infrared hyperspectral imaging

BACKGROUND

There is a need to minimize economic damage by sorting infected seeds from healthy seeds before seeding. However, current methods of detecting infected seeds, such as seedling grow-out, enzyme-linked immunosorbent assays, the polymerase chain reaction (PCR) and the real-time PCR have a critical drawbacks in that they are time-consuming, labor-intensive and destructive procedures. The present study aimed to evaluate the potential of visible/near-infrared (Vis/NIR) hyperspectral imaging system for detecting bacteria-infected watermelon seeds.

RESULTS

A hyperspectral Vis/NIR reflectance imaging system (spectral region of 400-1000 nm) was constructed to obtain hyperspectral reflectance images for 336 bacteria-infected watermelon seeds, which were then subjected to partial least square discriminant analysis (PLS-DA) and a least-squares support vector machine (LS-SVM) to classify bacteria-infected watermelon seeds from healthy watermelon seeds. The developed system detected bacteria-infected watermelon seeds with an accuracy > 90% (PLS-DA: 91.7%, LS-SVM: 90.5%), suggesting that the Vis/NIR hyperspectral imaging system is effective for quarantining bacteria-infected watermelon seeds.

CONCLUSION

The results of the present study show that it is possible to use the Vis/NIR hyperspectral imaging system for detecting bacteria-infected watermelon seeds. © 2016 Society of Chemical Industry.

Bio-Photonic Detection and Quantitative Evaluation Method for the Progression of Dental Caries Using Optical Frequency-Domain Imaging Method

The initial detection of dental caries is an essential biomedical requirement to barricade the progression of caries and tooth demineralization. The objective of this study is to introduce an optical frequency-domain imaging technique based quantitative evaluation method to calculate the volume and thickness of enamel residual, and a quantification method was developed to evaluate the total intensity fluctuation in depth direction owing to carious lesions, which can be favorable to identify the progression of dental caries in advance. The cross-sectional images of the ex vivo tooth samples were acquired using 1.3 μm spectral domain optical coherence tomography system (SD-OCT). Moreover, the advantages of the proposed method over the conventional dental inspection methods were compared to highlight the potential capability of OCT. As a consequence, the threshold parameters obtained through the developed method can be used as an efficient investigating technique for the initial detection of demineralization.

Full-Field Optical Coherence Tomography Using Galvo Filter-Based Wavelength Swept Laser

We report a wavelength swept laser-based full-field optical coherence tomography for measuring the surfaces and thicknesses of refractive and reflective samples. The system consists of a galvo filter–based wavelength swept laser and a simple Michelson interferometer. Combinations of the reflective and refractive samples are used to demonstrate the performance of the system. By synchronizing the camera with the source, the cross-sectional information of the samples can be seen after each sweep of the swept source. This system can be effective for the thickness measurement of optical thin films as well as for the depth investigation of samples in industrial applications. A resolution target with a glass cover slip and a step height standard target are imaged, showing the cross-sectional and topographical information of the samples.

Two-axis polydimethylsiloxane-based electromagnetic microelectromechanical system scanning mirror for optical coherence tomography

Compact size and fast imaging abilities are key requirements for the clinical implementation of an optical coherence tomography (OCT) system. Among the various small-sized technology, a microelectromechanical system (MEMS) scanning mirror is widely used in a miniaturized OCT system. However, the complexities of conventional MEMS fabrication processes and relatively high costs have restricted fast clinical translation and commercialization of the OCT systems. To resolve these problems, we developed a two-axis polydimethylsiloxane (PDMS)-based MEMS (2A-PDMS-MEMS) scanning mirror through simple processes with low costs. It had a small size of 15×15×15??mm3, was fast, and had a wide scanning range at a low voltage. The AC/DC responses were measured to evaluate the performance of the 2A-PDMS-MEMS scanning mirror. The maximum scanning angles were measured as ±16.6??deg and ±11.6??deg along the X and Y axes, respectively, and the corresponding field of view was 29.8??mm×20.5??mm with an optical focal length of 50 mm. The resonance frequencies were 82 and 57 Hz along the X and Y axes, respectively. Finally, in vivo B-scan and volumetric OCT images of human fingertips and palms were successfully acquired using the developed SD-OCT system based on the 2A-PDMS-MEMS scanning mirror.

Fast Industrial Inspection of Optical Thin Film Using Optical Coherence Tomography

An application of spectral domain optical coherence tomography (SD-OCT) was demonstrated for a fast industrial inspection of an optical thin film panel. An optical thin film sample similar to a liquid crystal display (LCD) panel was examined. Two identical SD-OCT systems were utilized for parallel scanning of a complete sample in half time. Dual OCT inspection heads were utilized for transverse (fast) scanning, while a stable linear motorized translational stage was used for lateral (slow) scanning. The cross-sectional and volumetric images of an optical thin film sample were acquired to detect the defects in glass and other layers that are difficult to observe using visual inspection methods. The rapid inspection enabled by this setup led to the early detection of product defects on the manufacturing line, resulting in a significant improvement in the quality assurance of industrial products.

Optical Inspection and Morphological Analysis of Diospyros kaki Plant Leaves for the Detection of Circular Leaf Spot Disease

The feasibility of using the bio-photonic imaging technique to assess symptoms of circular leaf spot (CLS) disease in Diospyros kaki (persimmon) leaf samples was investigated. Leaf samples were selected from persimmon plantations and were categorized into three groups: healthy leaf samples, infected leaf samples, and healthy-looking leaf samples from infected trees. Visually non-identifiable reduction of the palisade parenchyma cell layer thickness is the main initial symptom, which occurs at the initial stage of the disease. Therefore, we established a non-destructive bio-photonic inspection method using a 1310 nm swept source optical coherence tomography (SS-OCT) system. These results confirm that this method is able to identify morphological differences between healthy leaves from infected trees and leaves from healthy and infected trees. In addition, this method has the potential to generate significant cost savings and good control of CLS disease in persimmon fields.

3-D Imaging Systems for Agricultural Applications-A Review

Efficiency increase of resources through automation of agriculture requires more information about the production process, as well as process and machinery status. Sensors are necessary for monitoring the status and condition of production by recognizing the surrounding structures such as objects, field structures, natural or artificial markers, and obstacles. Currently, three dimensional (3-D) sensors are economically affordable and technologically advanced to a great extent, so a breakthrough is already possible if enough research projects are commercialized. The aim of this review paper is to investigate the state-of-the-art of 3-D vision systems in agriculture, and the role and value that only 3-D data can have to provide information about environmental structures based on the recent progress in optical 3-D sensors. The structure of this research consists of an overview of the different optical 3-D vision techniques, based on the basic principles. Afterwards, their application in agriculture are reviewed. The main focus lays on vehicle navigation, and crop and animal husbandry. The depth dimension brought by 3-D sensors provides key information that greatly facilitates the implementation of automation and robotics in agriculture.

Evaluation of moisture-related attenuation coefficient and water diffusion velocity in human skin using optical coherence tomography

In this study, time-resolved optical coherence tomography (OCT) scanning images of the process of water diffusion in the skin that illustrate the enhancement in the backscattered intensities due to the increased water concentration are presented. In our experiments, the water concentration in the skin was increased by soaking the hand in water, and the same region of the skin was scanned and measured with the OCT system and a commercial moisture monitor every three minutes. To quantitatively analyze the moisture-related optical properties and the velocity of water diffusion in human skin, the attenuation coefficients of the skin, including the epidermis and dermis layers, were evaluated. Furthermore, the evaluated attenuation coefficients were compared with the measurements made using the commercial moisture monitor. The results demonstrate that the attenuation coefficient increases as the water concentration increases. Furthermore, by evaluating the positions of center-of mass of the backscattered intensities from OCT images, the diffusion velocity can be estimated. In contrast to the commercial moisture monitor, OCT can provide three-dimensional structural images of the skin and characterize its optical property, which together can be used to observe morphological changes and quantitatively evaluate the moisture-related attenuation coefficients in different skin layers.