Detection and Discrimination of Tea Plant Stresses Based on Hyperspectral Imaging Technique at a Canopy Level

Tea plant stresses threaten the quality of tea seriously. The technology corresponding to the fast detection and differentiation of stresses is of great significance for plant protection in tea plantation. In recent years, hyperspectral imaging technology has shown great potential in detecting and differentiating plant diseases, pests and some other stresses at the leaf level. However, the lack of studies at canopy level hampers the detection of tea plant stresses at a larger scale. In this study, based on the canopy-level hyperspectral imaging data, the methods for identifying and differentiating the three commonly occurred tea stresses (i.e., the tea leafhopper, anthrax and sun burn) were studied. To account for the complexity of the canopy scenario, a stepwise detecting strategy was proposed that includes the process of background removal, identification of damaged areas and discrimination of stresses. Firstly, combining the successive projection algorithm (SPA) spectral analysis and K-means cluster analysis, the background and overexposed non-plant regions were removed from the image. Then, a rigorous sensitivity analysis and optimization were performed on various forms of spectral features, which yielded optimal features for detecting damaged areas (i.e., YSV, Area, GI, CARI and NBNDVI) and optimal features for stresses discrimination (i.e., MCARI, CI, LCI, RARS, TCI and VOG). Based on this information, the models for identifying damaged areas and those models for discriminating different stresses were established using K-nearest neighbor (KNN), Random Forest (RF) and Fisher discriminant analysis. The identification model achieved an accuracy over 95%, and the discrimination model achieved an accuracy over 93% for all stresses. The results suggested the feasibility of stress detection and differentiation using canopy-level hyperspectral imaging techniques, and indicated the potential for its extension over large areas.     

Imaging techniques for the detection of stored product pests

Stored grains are subject to deterioration and losses through various factors, but mainly insects and fungi. Various techniques are employed to detect stored product pests; however, there is an urgent need for an industrial-scale on-line detection technique. Near-infrared hyperspectroscopic imaging and soft X-rays have shown the potential for real-time application. These techniques are particularly effective for detecting internal infestations of stored grains. The digital images of the scanned objects are analyzed for various spectral and image features using statistical techniques such as complex multivariate tools. Classification accuracies as high as 80–100 % have been achieved for various pest and grain combinations. Dual-energy X-rays have been shown to detect the concealed eggs of stored product insect pests. The main threats to stored cereals come from Aspergillus spp., Penicillium spp., and Fusarium spp., which may produce mycotoxins. These imaging techniques have shown good results in the detection of fungal infections of stored grain.     

树木病虫害缺陷精准检测方法的综述和展望

我国疆土辽阔,有着丰富的森林资源。近年来,随着外来昆虫的入侵,全国树木病虫害的暴发率逐年上升,对我国生态经济造成了巨大的影响,但是树木病虫害的监测只能在局部地区,因而只能在已经暴发了较严重的病虫害后才能够发现和治理。树木病虫害如在早期未被发现和处理,可能会造成暴发的严重形势,且预防和治理将变得被动,因此,进行树木内部病虫害缺陷精准检测尤为重要。为更早和更加准确预报树木病虫害的发生,需要进行定期的检测和监控。针对早期传统方法如目测法、敲击辩声法和解剖观测法等方法的准确性低、时效性差和易对树木造成不可逆损害等缺点,近些年研究出了新的检测方法,包括指向性好、能量大的超声波检测法,低成本、穿透性强的应力波检测法,以及成像准确、适用于不同环境的电磁波检测法等。不同的检测方法分别有着相对应的成像算法,如走时法、频域分析法和Born近似法等。这些成像算法在分辨率、准确度、精度和计算速度上各有优势。通过对这3种检测方法的发展现状进行总结,了解各类检测方法的优缺点,有助于更好地针对不同情况下的树木病虫害做出精准检测,能够把树木病虫害暴发后的被动治理变成暴发前的主动预防,以提早做出应对方案。     

Discrimination between Weaned and Unweaned Atlantic Cod (Gadus morhua) in Capture-Based Aquaculture (CBA) by X-Ray Imaging and Radio-Frequency Metal Detector

The aim of this study was to investigate the feasibility of two detection methods for use in discrimination and sorting of adult Atlantic cod (about 2 kg) in the small scale capture-based aquaculture (CBA). Presently, there is no established method for discrimination of weaned and unweaned cod in CBA. Generally, 60–70% of the wild-caught cod in the CBA are weaned into commercial dry feed. To increase profitability for the fish farmers, unweaned cod must be separated from the stock, meaning the fish must be sorted into two groups – unweaned and weaned from moist feed. The challenges with handling of large numbers of fish in cages, defined the limits of the applied technology. As a result, a working model was established, focusing on implementing different marking materials added to the fish feed, and different technology for detecting the feed presence in the fish gut. X-ray imaging in two modes (planar and dual energy band) and sensitive radio-frequency metal detection were the detection methods that were chosen for the investigations. Both methods were tested in laboratory conditions using dead fish with marked feed inserted into the gut cavity. In particular, the sensitive radio-frequency metal detection method with carbonyl powder showed very promising results in detection of marked feed. Results show also that Dual energy band X-ray imaging may have potential for prediction of fat content in the feed. Based on the investigations it can be concluded that both X-ray imaging and sensitive radio-frequency metal detector technology have the potential for detecting cod having consumed marked feed. These are all technologies that may be adapted to large scale handling of fish from fish cages. Thus, it may be possible to discriminate between unweaned and weaned cod in a large scale grading situation. Based on the results of this study, a suggestion for evaluation of concept for in-situ sorting system is presented.     

Direct chemiluminescent imaging detection of human serum proteins in two-dimensional polyacrylamide gel electrophoresis

A novel chemiluminescence (CL)-based imaging method capable of directly detecting proteins in polyacrylamide gels after electrophoresis is proposed. Human serum proteins are presently detected by a direct CL imaging method after native 2-D PAGE. As a consequence, some proteins, including haptoglobin (Hp), Hp precursor, hemopexin (Hpx) precursor, Ig alpha-1 chain C region, and Complement C3 precursor can be detected and identified by MS and MS/MS techniques. These proteins are all acute phase proteins, which have been defined as biomarkers for certain diseases. Moreover, serum proteins from healthy people and cirrhotic patients were analyzed. A decrease in Hp spots for cirrhotic patients could be confirmed. The CL imaging conditions were optimized, including the concentrations of H(2)O(2) and luminol. The process of CL detection of proteins is simple, and there is no need for specialized equipment. In comparison with the traditional CBB-R250 staining method, the detection sensitivity was improved and the detection period decreased about 70 times. Hence, this technique possesses potentials as a rapid, convenient, and inexpensive analytical technique for protein detection and for the diagnosis of diseases.     

小麦叶面积指数与冠层反射光谱的定量关系

在分析不同氮素水平下小麦叶面积指数（LAI）和冠层光谱反射率随生育期变化模式的基础上,确立了LAI与冠层光谱反射率及光谱参数的相关关系,提出了小麦LAI的敏感光谱参数及预测方程.结果表明,小麦LAI和近红外短波段（760～1 220 nm）反射率都随施氮量的增加呈上升趋势,可见光波段反射率则相反;从拔节期到成熟期,LAI和近红外短波段反射率均表现为先上升后下降的趋势,而可见光波段（460～710 nm）反射率随生育期的推进先降低后升高,以孕穗期反射率最低,近红外长波段区域（1 480～1 650 nm）反射率的变化与可见光部分相同.LAI与可见光波段反射率呈负相关,与近红外短波段反射率呈极显著正相关,其中以810 nm相关性最好.可以选择RVI(810,510)和DVI(810,560)作为反演小麦LAI的光谱参数.另外,在证明垂直植被指数PVI和转换型土壤调整指数TSAVI对LAI预测能力的同时,发现利用RVI(810,510)、DVI(810,560)和PVI 3个植被指数共同推算小麦LAI的准确度更高.     

翘嘴鳜病原嗜水气单胞菌分子特征及LAMP检测方法的建立

嗜水气单胞菌(Aeromonas hydrophila)是一种危害鳜鱼养殖生产的重要病原细菌, 为进一步明确该病原菌的分子特征及建立快速检测技术, 实验对引起翘嘴鳜(Siniperca chuatsi)暴发性死亡的病原嗜水气单胞菌进行了致病性、菌株毒力特征研究, 同时以嗜水气单胞菌气溶素基因aerA为分子靶标设计引物, 利用环介导等温扩增技术(Loop-mediated isothermal amplification, LAMP)建立了病原嗜水气单胞菌的快速检测方法。结果表明, 本次引起翘嘴鳜暴发性死亡的病原嗜水气单胞菌半致死浓度为1.6×106 CFU/mL, 携带aerA等14种毒力基因, 此14种毒力基因可用于其致病性分析及分子检测。以气溶素基因aerA设计引物进行的环介导恒温扩增, 结果显示可扩增出阶梯状条带, 加入SYBR Green I染色后呈现绿色的阳性反应, 而对照组均未出现任何扩增条带且反应体系呈现橙色, 表明LAMP检测方法对于嗜水气单胞菌检测具有很好的特异性; 灵敏度检测的最低检测限为4.6×101 CFU/mL; 10种经人工感染的淡水养殖鱼虾组织匀浆增菌液, 提取DNA后进行LAMP方法检测, 结果均可获得阳性扩增结果, 而对照未染菌组呈阴性, 表明该方法具有较好的应用性, 可应用于嗜水气单胞菌引起的水生动物疾病的检测。     

Quantification of protein interaction in living cells by two-photon spectral imaging with fluorescent protein fluorescence resonance energy transfer pair devoid of acceptor bleed-through

Fluorescence resonance energy transfer (FRET) between fluorescent proteins (FPs) is a powerful method to visualize and quantify protein-protein interaction in living cells. Unfortunately, the emission bleed-through of FPs limits the usage of this complex technique. To circumvent undesirable excitation of the acceptor fluorophore, using two-photon excitation, we searched for FRET pairs that show selective excitation of the donor but not of the acceptor fluorescent molecule. We found this property in the fluorescent cyan fluorescent protein (CFP)/yellow fluorescent protein (YFP) and YFP/mCherry FRET pairs and performed two-photon excited FRET spectral imaging to quantify protein interactions on the later pair that shows better spectral discrimination. Applying non-negative matrix factorization to unmix two-photon excited spectral imaging data, we were able to eliminate the donor bleed-through as well as the autofluorescence. As a result, we achieved FRET quantification by means of a single spectral acquisition, making the FRET approach not only easy and straightforward but also less prone to calculation artifacts. As an application of our approach, the intermolecular interaction of amyloid precursor protein and the adaptor protein Fe65 associated with Alzheimer's disease was quantified. We believe that the FRET approach using two-photon and fluorescent YFP/mCherry pair is a promising method to monitor protein interaction in living cells.     

Multicolor banding technique, spectral color banding (SCAN): new development and applications

Conventional banding techniques can characterize chromosomal aberrations associated with tumors and congenital diseases with considerable precision. However, chromosomal aberrations that have been overlooked or are difficult to analyze even by skilled cytogeneticists were also often noted. Following the introduction of multicolor karyotyping such as spectral karyotyping (SKY) and multiplex-fluorescence in situ hybridization (M-FISH), it is possible to identify this kind of cryptic or complex aberration comprehensively by a single analysis. To date, multicolor karyotyping techniques have been established as useful tools for cytogenetic analysis. However, since this technique depends on whole chromosome painting probes, it involves limitations in that the origin of aberrant segments can be identified only in units of chromosomes. To overcome these limitations, we have recently developed spectral color banding (SCAN) as a new multicolor banding technique based on the SKY methodology. This new technique may be deemed as an ideal chromosome banding technique since it allows representation of a multicolor banding pattern matching the corresponding G-banding pattern. We applied this technique to the analysis of chromosomal aberrations in tumors that had not been fully characterized by G-banding or SKY and found it capable of (1) detecting intrachromosomal aberrations; (2) identifying the origin of aberrant segments in units of bands; and (3) precisely determining the breakpoints of complex rearrangements. We also demonstrated that SCAN is expected to allow cytogenetic analysis with a constant adequate resolution close to the 400-band level regardless of the degree of chromosome condensation. As compared to the conventional SKY analysis, SCAN has remarkably higher accuracy for a particular chromosome, allowing analysis in units of bands instead of in units of chromosomes and is hence promising as a means of cytogenetic analysis.     

Color standardization method and system for whole slide imaging based on spectral sensing

In the field of whole slide imaging, the imaging device or staining process cause color variations for each slide that affect the result of image analysis made by pathologist. In order to stabilize the analysis, we developed a color standardization method and system as described below. (1) Color standardization method based on RGB imaging and multi spectral sensing, which utilize less band (16 bands) than conventional method (60 bands). (2) High speed spectral sensing module. As a result, we confirmed the following effect. (1) We confirmed the performance improvement of nucleus detection by the color standardization. And we can conduct without training data set which is needed in conventional method. (2) We can get detection performance of H&E component equivalent to conventional method (60 bands). And measurement process is more than 255 times faster.     

Identifying plants under natural gas micro-leakage stress using hyperspectral remote sensing

Natural gas is an important clean energy source. The demand for, and consumption of, natural gas have been increasing in recent years. Slight natural gas leakage can occur during transportation, which can have a negative impact on the environment, economy, and safety. However, it is relatively difficult to directly detect natural gas microleakage. Hyperspectral remote sensing technology is useful for analyzing the spectral characteristics of vegetation near leakage areas, thereby indirectly obtaining leakage information. In this study, a field experiment was designed to simulate natural gas leakage from an underground pipeline and gas stress on three plant species. The canopy spectral reflectance of the vegetation throughout the growth period of the plants was collected and analyzed. Variational mode decomposition was then used to decompose the spectra. Based on the stress distance (SD) and intrinsic mode functions, it was found that the second intrinsic mode function, with a decomposition scale of 32, was sensitive to gas stress. According to the results of SD, the bands (616 and 829 nm) sensitive to natural gas stress for the three plant species were extracted, and the variational mode decomposition index (VMDI) was constructed. The Jeffries–Matusita distance (JMD) was used to quantitatively evaluate the VMDI index and three indices were used to evaluate the ability to recognize stress. It was found that the index proposed in this study could identify stressed wheat and grass one week earlier than other indices and could better identify stressed vegetation throughout the phenological cycle (JMD > 1.8). The results show that the proposed index can be used as a reliable method to identify natural gas-stressed plants, and that hyperspectral technology is promising for detecting the location of natural gas leaks from underground pipelines.     

Identification of Sunn-pest affected (Eurygaster Integriceps put.) wheat plants and their distribution in wheat fields using aerial imaging

Sunn pest (Eurygaster integriceps put.) causes severe damage to wheat fields annually, reducing production by up to 50%. Rapid identification of pest concentration points and estimation of infestation levels in fields can be useful for production management and reducing the use of chemical sprays. Because of the limited ability to detect pests on the ground and access to high-resolution satellite imagery, aerial photography was considered for crop pest and disease detection. In this study, the feasibility of soft computing approaches and image processing to identify areas infected with sunn pest using near-infrared and visible light aerial imagery was investigated. An irrigated winter wheat field was surveyed for five consecutive months, from February to June. The spectral vegetation features (SVI), were extracted and analysed for both near infrared and visible light images. To detect infected spikes, Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel was used. The Red and near-infrared (NIR) bands reflectance and, the Ratio Vegetation Index (RVI) for near-infrared images as well as Red and Green bands reflectance and normalised green blue difference index (NGBDI) for visible light images had the greatest impact on the performance of the SVM classifiers. The SVM classifiers were validated using the confusion matrix method. The best accuracy and performance of the detection system was achieved in February and March when the healthy wheat plant was still green. The mean accuracy for these two months was 0.97 and 0.93 for the SVM classifiers for NIR and visible light, respectively.     

Multispectral fluorescence and reflectance imaging at the leaf level and its possible applications

Images taken at different spectral bands are increasingly used for characterizing plants and their health status. In contrast to conventional point measurements, imaging detects the distribution and quantity of signals and thus improves the interpretation of fluorescence and reflectance signatures. In multispectral fluorescence and reflectance set-ups, images are separately acquired for the fluorescence in the blue, green, red, and far red, as well as for the reflectance in the green and in the near infrared regions. In addition, 'reference' colour images are taken with an RGB (red, green, blue) camera. Examples of imaging for the detection of photosynthetic activity, UV screening caused by UV-absorbing substances, fruit quality, leaf tissue structure, and disease symptoms are introduced. Subsequently, the different instrumentations used for multispectral fluorescence and reflectance imaging of leaves and fruits are discussed. Various types of irradiation and excitation light sources, detectors, and components for image acquisition and image processing are outlined. The acquired images (or image sequences) can be analysed either directly for each spectral range (wherein they were captured) or after calculating ratios of the different spectral bands. This analysis can be carried out for different regions of interest selected manually or (semi)-automatically. Fluorescence and reflectance imaging in different spectral bands represents a promising tool for non-destructive plant monitoring and a 'road' to a broad range of identification tasks.     

Goldfish color vision sensitivity is high under light-adapted conditions

The wavelength discrimination threshold of three goldfish was examined in a series of behavioral experiments. Using an auto-shaping technique, detection thresholds were established for 531 and 648 nm spectral increments presented on a 6.6 cd m^–2 white background. Next, discrimination between the wavelengths was established at equal, suprathreshold, intensities. Finally, the intensities of the two stimuli were reduced to establish the intensity threshold for the wavelength discrimination. The results indicate that goldfish, like several mammalian species, can discriminate wavelength at detection threshold intensity. This finding suggests that high color sensitivity is not confined to mammals or dependent upon a very high percentage of wavelength opponent ganglion cells. Rather, high color vision sensitivity may be based upon an inherent sensitivity advantage of wavelength opponent receptive fields compared to non-wavelength opponent receptive fields and be an important selective advantage of wavelength opponency and color vision.     

Localization of water-soluble carbohydrates in wheat stems using imaging matrix-assisted laser desorption ionization mass spectrometry

The pool of endogenous water-soluble oligosaccharides found in the stems of wheat (Triticum aestivum) is being investigated as a potential indicator of grain yield. Techniques such as liquid chromatography with mass spectrometry (LC-MS) can profile these analytes but provide no spatial information regarding their distribution in the wheat stem. The imaging matrix-assisted laser desorption ionization (MALDI) mass spectrometry technique has not been utilized for the analysis of oligosaccharides in plant systems previously. Imaging MALDI mass spectrometry was used to analyse cross and longitudinal sections from the stems of Triticum aestivum. A range of oligosaccharides up to Hex(11) were observed. Water-soluble oligosaccharides were ionized as potassiated molecules, and found to be located in the stem pith that is retained predominantly around the inner stem wall. Imaging MALDI analyses provided spatial information on endogenous oligosaccharides present in wheat stems. The technique was found to offer comparable sensitivities for oligosaccharide detection to those of our established LC-MS method, and has potential for broad application in studying the in situ localization of other compound types in plant material.     

Engineering antibodies and proteins for molecular in vivo imaging

The rapid and ongoing discovery of new disease related biomarkers leads to a dramatic paradigm change in human healthcare and constitutes the basis for a truly personalized medicine. Molecular imaging enables early detection and classification of human diseases and provides valuable data for optimized, target-oriented therapies. By now, the biochemical and physiological properties of antibody derivatives or alternative protein scaffolds can be engineered for the detection of a wide range of target structures. The successful application of these reagents in animals, xenograft models and cells in preclinical research clearly demonstrate their utility for molecular imaging. Despite these promising perspectives, only a few antibodies and recombinant proteins are used yet for molecular imaging in human medicine. Especially the high safety demands and the need to eliminate off target effects in humans require extensive research and development efforts.     

地中海实蝇及其近缘种基因芯片检测研究

本研究选择线粒体DNA (mtDNA) 细胞色素氧化酶Ⅰ基因（COⅠ）为分子标记基因,以双翅目实蝇科昆虫DNA序列为目标,建立了我国进境植物检疫害虫地中海实蝇Ceratitis capitata、芒果小条实蝇C. cosyra和纳塔尔小条实蝇C. rosa等生物芯片检测方法。地中海实蝇及其近缘种检测芯片由检测探针（实蝇科通用探针1条,小条实蝇属通用探针1条,地中海实蝇、芒果小条实蝇和纳塔尔小条实蝇近缘种探针2条和种特异探针4条）、质控探针（定位点探针、阳性质控、阴性质控和空白对照探针各1条）组成。芯片检测结果表明,检测探针特异性强,能实现上述3种实蝇的种类快速区分和准确鉴定; 检测方法稳定性好,地中海实蝇不同虫态（卵、幼虫、蛹和成虫）和不同地理种群检测结果完全一致。地中海实蝇生物芯片检测技术将为我国进口果蔬中检疫性实蝇快速筛查和种类鉴定提供检测方法,同时,还可应用到其他属的实蝇以及相关害虫的检疫中,为有害生物的快速鉴定提供了新方法。     

DNA‐Functionalized Plasmonic Nanomaterials for Optical Biosensing

Plasmonic nanomaterials, especially Au and Ag nanomaterials, have shown attractive physicochemical properties, such as easy functionalization and tunable optical bands. The development of this active subfield paves the way to the fascinating biosensing platforms. In recent years, plasmonic nanomaterials–based sensors have been extensively investigated because they are useful for genetic diseases, biological processes, devices, and cell imaging. In this account, a brief introduction of the development of optical biosensors based on DNA‐functionalized plasmonic nanomaterials is presented. Then the common strategies for the application of the optical sensors are summarized, including colorimetry, fluorescence, localized surface plasmon resonance, and surface‐enhanced resonance scattering detection. The focus is on the fundamental aspect of detection methods, and then a few examples of each method are highlighted. Finally, the opportunities and challenges for the plasmonic nanomaterials–based biosensing are discussed with the development of modern technologies.     

Multiband Terahertz Metamaterial Absorber Based on Multipolar Plasmonic Resonances

Terahertz metamaterial absorbers (MMA) have found wide scope of research prospective, remarkably in the development of multiband absorbers. Considerable applications are established using these multiband absorbers in THz imaging, wireless communication and bolometric detectors. The MMA was built on a GaAs substrate of 30 µm thickness and the hexagonal metallic pattern was etched out on a gold layer of 0.4 µm thickness on the top surface. The underlying ground layer is metallic backed. This design realizes the multiband (9-bands) of absorption in the spectral region from 0.56 to 0.92 THz. The multiband absorption mechanism of the absorber was examined by electric field dispersion analysis and impedance matching concept. From the established results, the absorber exhibits nine bands within a narrow frequency range and secures promising applications in hyperspectral imaging, clinical sensing and detection.

     

功能与分子影像在头颈部肿瘤放射治疗计划和疗效评价中的应用

目前临床普遍采用功能与分子影像检测手段能来评价头颈部肿瘤的放射治疗计划和疗效,可指导个体化治疗从而提高疗效。文章概述了功能与分子影像技术CT,MRI,PET-CT,超声检测技术在头颈部肿瘤放射治疗计划制定和疗效评价中的应用进展。结果显示,不同分子影像检测方法如在检查时机的选择、诊断和鉴别诊断的价值、观察放射治疗后肿瘤的残存和复发、预测放射治疗效果、指导后续治疗等方面均可起到重要作用。采用图像融合技术进行联合应用,如PET-CT和MRI-CT等,可提高检测的准确率。临床医生需在常规影像学手段的基础上,根据头颈部肿瘤患者病情和治疗方法的不同选用正确的功能和分子影像检测手段,更好地指导制定放射治疗计划及综合评价放射治疗后的疗效。