Hyperspectral imaging for quantifying Magnaporthe oryzae sporulation on rice genotypes.

BACKGROUND: Precise evaluation of fungal conidia production may facilitate studies on resistance mechanisms and plant breeding for disease resistance. In this study, hyperspectral imaging (HSI) was used to quantify the sporulation of Magnaporthe oryzae on the leaves of rice cultivars grown under controlled conditions. Three rice genotypes (CO 39, Nipponbare, IR64) differing in susceptibility to blast were inoculated with M. oryzae isolates Guy 11 and Li1497. Spectral information (450-850 nm, 140 wavebands) of typical leaf blast symptoms was recorded before and after induction of sporulation of the pathogen. RESULTS: M. oryzae produced more conidia on the highly susceptible genotype than on the moderately susceptible genotype, whereas the resistant genotype resulted in no sporulation. Changes in reflectance spectra recorded before and after induction of sporulation were significantly higher in genotype CO 39 than in Nipponbare. The spectral angle mapper algorithm for supervised classification allowed for the classification of blast symptom subareas and the quantification of lesion areas with M. oryzae sporulation. The correlation between the area under the difference spectrum (viz. spectral difference without and with sporulation) and the number of conidia per lesion and the number of conidia per lesion area was positive and count-based differences in rice - M. oryzae interaction could be reproduced in the spectral data. CONCLUSIONS: HSI provided a precise and objective method of assessing M. oryzae conidia production on infected rice plants, revealing differences that could not be detected visually.

Hyperspectral imaging reveals small-scale water gradients in apple leaves due to minimal cuticle perforation by Venturia inaequalis conidiophores.

Effects of Venturia inaequalis on water relations of apple leaves were studied under controlled conditions without limitation of water supply to elucidate their impact on the non-haustorial biotrophy of this pathogen. Leaf water relations, namely leaf water content and transpiration, were spatially resolved by hyperspectral imaging and thermography; non-imaging techniques-gravimetry, a pressure chamber, and porometry-were used for calibration and validation. Reduced stomatal transpiration 3-4 d after inoculation coincided with a transient increase of water potential. Perforation of the plant cuticle by protruding conidiophores subsequently increased cuticular transpiration even before visible symptoms occurred. With sufficient water supply, cuticular transpiration remained at elevated levels for several weeks. Infections did not affect the leaf water content before scab lesions became visible. Only hyperspectral imaging was suitable to demonstrate that a decreased leaf water content was strictly limited to sites of emerging conidiophores and that cuticle porosity increased with sporulation. Microscopy confirmed marginal cuticle injury; although perforated, it tightly surrounded the base of conidiophores throughout sporulation and restricted water loss. The role of sustained redirection of water flow to the pathogen's hyphae in the subcuticular space above epidermal cells, to facilitate the acquisition and uptake of nutrients by V. inaequalis, is discussed.

Characterization of Rice-Magnaporthe oryzae Interactions by Hyperspectral Imaging.

Hyperspectral imaging has the potential to detect, characterize, and quantify plant diseases objectively and nondestructively to improve phenotyping in breeding for disease resistance. In this study, leaf spectral reflectance characteristics of five rice genotypes diseased with blast caused by three Magnaporthe oryzae isolates differing in virulence were compared with visual disease ratings under greenhouse conditions. Spectral information (140 wavebands, range 450 to 850 nm) of infected leaves was recorded with a hyperspectral imaging microscope at 3, 5, and 7 days postinoculation to examine differences in symptom phenotypes and to characterize the compatibility of host-pathogen interactions. Depending on the rice genotype × M. oryzae genotype interaction, blast symptoms varied from tiny necrosis to enlarged lesions with symptom subareas differing in tissue coloration and indicated gene-for-gene-specific interactions. The blast symptom types were differentiated based on their spectral characteristics in the visible/near-infrared range. Symptom-specific spectral signatures and differences in the composition of leaf blast symptom type(s) resulted in unique spectral and spatial patterns of the rice × M. oryzae interactions based on the size, shape, and color of the symptom subareas. Spectral angle mapper classification of spectra enabled (i) discrimination between healthy (green) and diseased tissue of rice genotypes, (ii) classification and quantification of different blast symptom subareas, and (iii) grading of the host-pathogen compatibility (low - intermediate - high). Hyperspectral imaging was more sensitive to small changes in disease resistance than visual disease assessments and enabled the characterization of various types of resistance/susceptibility reactions of tissue subjected to M. oryzae infection.

Hyperspectral mapping of the response of grapevine cultivars to Plasmopara viticola infection at the tissue scale.

Resistance of grapevine to Plasmopara viticola is associated with the hypersensitive reaction, accumulation of stilbenoids, and formation of callose depositions. Spectral characterization of infected leaf tissue of cvs 'Regent' and 'Solaris' with resistance genes Rpv 3-1 and Rpv 10 and Rpv 3-3, respectively, suggested that resistance is not dependent on large-scale necrotization of host tissue. Reactions of the resistant cultivars and a reference susceptible to P. viticola were studied using hyperspectral imaging (range 400-1000 nm) at the tissue level and microscopic techniques. Resistance of both cultivars was incomplete and allowed pathogen reproduction. Spectral vegetation indices characterized the host response to pathogen invasion; the vitality of infected and necrotic leaf tissue differed significantly. Resistance depended on local accumulation of polyphenols in response to haustorium formation and was more effective for cv. 'Solaris'. Although hypersensitive reaction of some cells prevented colonization of palisade parenchyma, resistance was not associated with extensive necrotization of tissue, and the biotrophic pathogen survived localized death of penetrated host cells. Hyperspectral imaging was suitable to characterize and differentiate the resistance reactions of grapevine cultivars by mapping of the cellular response to pathogen attack on the tissue level and yields useful information on host-pathogen interactions.

Pathogenesis of Plasmopara viticola Depending on Resistance Mediated by Rpv3_1, and Rpv10 and Rpv3_3, and by the Vitality of Leaf Tissue.

Grapevine cultivars vary in their resistance to Plasmopara viticola, causal agent of downy mildew. Genes from various Vitis species confer pathogen resistance (Rpv), resulting in reduced compatibility of the host-pathogen interaction and partial disease resistance that may become apparent at different stages of pathogenesis. This study describes the pathogenesis of P. viticola on the partially resistant cultivars Regent (Rpv3-1) and Solaris (Rpv3-3, Rpv10) as compared with the susceptible cultivar Mueller-Thurgau using various microscopic techniques, visual disease rating as well as qPCR. Host plant resistance had no effect on the initial steps of pathogenesis outside the host plant cells (zoospore attachment, formation of substomatal vesicle) and became detectable only after the formation of primary haustoria. The restricted compatibility resulted in reductions in haustorium size and in the number of secondary haustoria and was associated with callose depositions around haustoria and stomatal guard cells, collapsed mesophyll cells (hypersensitive reaction), and additional production of an amorphous substance in the intercellular space of cultivar Solaris. Resistance mechanisms reduced the efficiency of P. viticola haustoria and largely restricted tissue colonization to the spongy parenchyma; resistance of cultivar Solaris having thicker leaves was more effective than that of cultivar Regent. Despite of the effects of resistance genes, P. viticola was able to complete its life cycle by forming sporangiophores with sporangia through the stomata on both resistant cultivars indicating partial resistance. Differences in the pathogenesis on detached and attached grapevine leaves highlighted the impact of host tissue vitality on both resistance and susceptibility to the biotrophic pathogen.

A Melanin-Deficient Isolate of Venturia inaequalis Reveals Various Roles of Melanin in Pathogen Life Cycle and Fitness.

Venturia inaequalis is the ascomycetous pathogen causing apple scabs and forms dark-pigmented spores and partially melanised infection structures. Although melanin is considered to be essential for the infection of host tissue, a spontaneously occurring melanin-deficient mutant was isolated from an abaxial side of an apple leaf and can be cultivated in vitro as well as in vivo. The morphology and development of the melanin-deficient-isolate SW01 on leaves of susceptible apple plants were compared to that of the corresponding wild-type isolate HS1. White conidia of SW01 were often wrinkled when dry and significantly increased their volume in suspension. Germination and formation of germtubes and appressoria were not impaired; however, the lack of melanisation of the appressorial ring structure at the interface with the plant cuticle significantly reduced the infection success of SW01. The colonisation of leaf tissue by non-melanised subcuticular hyphae was not affected until the initiation of conidiogenesis. Non-melanised conidiophores penetrated the plant cuticle from inside less successfully than the wild type, and the release of white conidia from less solid conidiophores above the cuticle was less frequent. Melanin in the outer cell wall of V. inaequalis was not required for the survival of conidia under ambient temperature or at -20 °C storage conditions, however, promoted the tolerance of the pathogen to copper and synthetic fungicides affecting the stability and function of the fungal cell wall, plasma membrane, respiration (QoIs) and enzyme secretion, but had no effect on the sensitivity to sulphur and SDHIs. The roles of melanin in different steps of the V. inaequalis life cycle and the epidemiology of apple scabs are discussed.

Lr21 diversity unveils footprints of wheat evolution and its new role in broad-spectrum leaf rust resistance.

Aegilops tauschii, the progenitor of the wheat D genome, contains extensive diversity for biotic and abiotic resistance. Lr21 is a leaf rust resistance gene, which did not enter the initial gene flow from Ae. tauschii into hexaploid wheat due to restrictive hybridization events. Here, we used population genetics and high-resolution comparative genomics to study evolutionary and functional divergence of Lr21 in diploid and hexaploid wheats. Population genetics identified the original Lr21, lr21-1 and lr21-2 alleles and their evolutionary history among Ae. tauschii accessions. Comparative genetics of Lr21 variants between Ae. tauschii and cultivated genotypes suggested at least two independent polyploidization events in bread wheat evolution. Further, a recent re-birth of a unique Lr21-tbk allele and its neofunctionalization was discovered in the hexaploid wheat cv. Tobak. Altogether, four independent alleles were investigated and validated for leaf rust resistance in diploid, synthetic hexaploid and cultivated wheat backgrounds. Besides seedling resistance, we uncover a new role of the Lr21 gene in conferring an adult plant field resistance. Seedling and adult plant resistance turned out to be correlated with developmentally dependent variation in Lr21 expression. Our results contribute to understand Lr21 evolution and its role in establishing a broad-spectrum leaf rust resistance in wheat.

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.

Sensory assessment of Cercospora beticola sporulation for phenotyping the partial disease resistance of sugar beet genotypes.

BACKGROUND: Due to its high damaging potential, Cercospora leaf spot (CLS) caused by Cercospora beticola is a continuous threat to sugar beet production worldwide. Breeding for disease resistance is hampered by the quantitative nature of resistance which may result from differences in penetration, colonization, and sporulation of the pathogen on sugar beet genotypes. In particular, problems in the quantitative assessment of C. beticola sporulation have resulted in the common practice to assess field resistance late in the growth period as quantitative resistance parameter. Recently, hyperspectral sensors have shown potential to assess differences in CLS severity. Hyperspectral microscopy was used for the quantification of C. beticola sporulation on sugar beet leaves in order to characterize the host plant suitability / resistance of genotypes for decision-making in breeding for CLS resistance. RESULTS: Assays with attached and detached leaves demonstrated that vital plant tissue is essential for the full potential of genotypic mechanisms of disease resistance and susceptibility. Spectral information (400 to 900 nm, 160 wavebands) of CLSs recorded before and after induction of C. beticola sporulation allowed the identification of sporulating leaf spot sub-areas. A supervised classification and quantification of sporulation structures was possible, but the necessity of genotype-specific reference spectra restricts the general applicability of this approach. Fungal sporulation could be quantified independent of the host plant genotype by calculating the area under the difference reflection spectrum from hyperspectral imaging before and with sporulation. The overall relationship between sensor-based and visual quantification of C. beticola sporulation on five genotypes differing in CLS resistance was R2 = 0.81; count-based differences among genotypes could be reproduced spectrally. CONCLUSIONS: For the first time, hyperspectral imaging was successfully tested for the quantification of sporulation as a fungal activity depending on host plant suitability. The potential of this non-invasive and non-destructive approach for the quantification of fungal sporulation in other host-pathogen systems and for the phenotyping of crop traits complex as sporulation resistance is discussed.

Comparison and Combination of Thermal, Fluorescence, and Hyperspectral Imaging for Monitoring Fusarium Head Blight of Wheat on Spikelet Scale.

Optical sensors have shown high capabilities to improve the detection and monitoring of plant disease development. This study was designed to compare the feasibility of different sensors to characterize Fusarium head blight (FHB) caused by Fusarium graminearum and Fusarium culmorum. Under controlled conditions, time-series measurements were performed with infrared thermography (IRT), chlorophyll fluorescence imaging (CFI), and hyperspectral imaging (HSI) starting 3 days after inoculation (dai). IRT allowed the visualization of temperature differences within the infected spikelets beginning 5 dai. At the same time, a disorder of the photosynthetic activity was confirmed by CFI via maximal fluorescence yields of spikelets (Fm) 5 dai. Pigment-specific simple ratio PSSRa and PSSRb derived from HSI allowed discrimination between Fusarium-infected and non-inoculated spikelets 3 dai. This effect on assimilation started earlier and was more pronounced with F. graminearum. Except the maximum temperature difference (MTD), all parameters derived from different sensors were significantly correlated with each other and with disease severity (DS). A support vector machine (SVM) classification of parameters derived from IRT, CFI, or HSI allowed the differentiation between non-inoculated and infected spikelets 3 dai with an accuracy of 78, 56 and 78%, respectively. Combining the IRT-HSI or CFI-HSI parameters improved the accuracy to 89% 30 dai.

Discovering coherency of specific gene expression and optical reflectance properties of barley genotypes differing for resistance reactions against powdery mildew.

Hyperspectral imaging has proved its potential for evaluating complex plant-pathogen interactions. However, a closer link of the spectral signatures and genotypic characteristics remains elusive. Here, we show relation between gene expression profiles and specific wavebands from reflectance during three barley-powdery mildew interactions. Significant synergistic effects between the hyperspectral signal and the corresponding gene activities has been shown using the linear discriminant analysis (LDA). Combining the data sets of hyperspectral signatures and gene expression profiles allowed a more precise differentiation of the three investigated barley-Bgh interactions independent from the time after inoculation. This shows significant synergistic effects between the hyperspectral signal and the corresponding gene activities. To analyze this coherency between spectral reflectance and seven different gene expression profiles, relevant wavelength bands and reflectance intensities for each gene were computed using the Relief algorithm. Instancing, xylanase activity was indicated by relevant wavelengths around 710 nm, which are characterized by leaf and cell structures. HvRuBisCO activity underlines relevant wavebands in the green and red range, elucidating the coherency of RuBisCO to the photosynthesis apparatus and in the NIR range due to the influence of RuBisCO on barley leaf cell development. These findings provide the first insights to links between gene expression and spectral reflectance that can be used for an efficient non-invasive phenotyping of plant resistance and enables new insights into plant-pathogen interactions.

Spectral Patterns Reveal Early Resistance Reactions of Barley Against Blumeria graminis f. sp. hordei.

Differences in early plant-pathogen interactions are mainly characterized by using destructive methods. Optical sensors are advanced techniques for phenotyping host-pathogen interactions on different scales and for detecting subtle plant resistance responses against pathogens. A microscope with a hyperspectral camera was used to study interactions between Blumeria graminis f. sp. hordei and barley (Hordeum vulgare) genotypes with high susceptibility or resistance due to hypersensitive response (HR) and papilla formation. Qualitative and quantitative assessment of pathogen development was used to explain changes in hyperspectral signatures. Within 48 h after inoculation, genotype-specific changes in the green and red range (500 to 690 nm) and a blue shift of the red-edge inflection point were observed. Manual analysis indicated resistance-specific reflectance patterns from 1 to 3 days after inoculation. These changes could be linked to host plant modifications depending on individual host-pathogen interactions. Retrospective analysis of hyperspectral images revealed spectral characteristics of HR against B. graminis f. sp. hordei. For early HR detection, an advanced data mining approach localized HR spots before they became visible on the RGB images derived from hyperspectral imaging. The link among processes during pathogenesis and host resistance to changes in hyperspectral signatures provide evidence that sensor-based phenotyping is suitable to advance time-consuming and cost-expensive visual rating of plant disease resistances.

Hyperspectral phenotyping of the reaction of grapevine genotypes to Plasmopara viticola.

A major aim in grapevine breeding is the provision of cultivars resistant to downy mildew. As Plasmopara viticola produces sporangia on the abaxial surface of susceptible cultivars, disease symptoms on both leaf sides may be detected and quantified by technical sensors. The response of cultivars 'Mueller-Thurgau', 'Regent', and 'Solaris', which differ in resistance to P. viticola, was characterized under controlled conditions by using hyperspectral sensors. Spectral reflectance was suitable to differentiate between non-infected cultivars and leaf sides of the bicolored grapevine. Brown discoloration of tissue became visible on both leaf sides of resistant cultivars 2 days before downy mildew symptoms appeared on the susceptible 'Mueller-Thurgau' cultivar. Infection of this cultivar resulted in significant (P<0.05) reflectance changes 1-2 days prior to abaxial sporulation induced by high relative humidity, or the formation of adaxial oil spots. Hyperspectral imaging was more sensitive in disease detection than non-imaging and provided spatial information on the leaf level. Spectral indices provided information on the variability of chlorophyll content, photosynthetic activity, and relative water content of leaf tissue in time and space. On 'Mueller-Thurgau' downy mildew translated reflectance to higher values as detectable by the index DMI_3=(R470+R682+R800)/(R800/R682) and affected reflectance at 1450nm. Tissue discoloration on 'Regent' and 'Solaris' cultivars was associated with lower reflectance between 750 and 900nm; blue and red reflectance demonstrated differences from leaf necroses. With high inoculum densities, P. viticola sporulated on even resistant cultivars. Hyperspectral characterization at the tissue level proved suitable for phenotyping plant resistance to pathogens and provided information on resistance mechanisms.

Plant Phenotyping using Probabilistic Topic Models: Uncovering the Hyperspectral Language of Plants.

Modern phenotyping and plant disease detection methods, based on optical sensors and information technology, provide promising approaches to plant research and precision farming. In particular, hyperspectral imaging have been found to reveal physiological and structural characteristics in plants and to allow for tracking physiological dynamics due to environmental effects. In this work, we present an approach to plant phenotyping that integrates non-invasive sensors, computer vision, as well as data mining techniques and allows for monitoring how plants respond to stress. To uncover latent hyperspectral characteristics of diseased plants reliably and in an easy-to-understand way, we "wordify" the hyperspectral images, i.e., we turn the images into a corpus of text documents. Then, we apply probabilistic topic models, a well-established natural language processing technique that identifies content and topics of documents. Based on recent regularized topic models, we demonstrate that one can track automatically the development of three foliar diseases of barley. We also present a visualization of the topics that provides plant scientists an intuitive tool for hyperspectral imaging. In short, our analysis and visualization of characteristic topics found during symptom development and disease progress reveal the hyperspectral language of plant diseases.

Improvement of Lesion Phenotyping in Cercospora beticola-Sugar Beet Interaction by Hyperspectral Imaging.

Cercospora leaf spot (CLS) caused by Cercospora beticola is the most destructive leaf disease of sugar beet and may cause high losses in yield and quality. Breeding and cultivation of disease-resistant varieties is an important strategy to control this economically relevant plant disease. Reliable and robust resistance parameters are required to promote breeding progress. CLS lesions on five different sugar beet genotypes incubated under controlled conditions were analyzed for phenotypic differences related to field resistance to C. beticola. Lesions of CLS were rated by classical quantitative and qualitative methods in combination with noninvasive hyperspectral imaging. Calculating the ratio of lesion center to lesion margin, four CLS phenotypes were identified that vary in size and spatial composition. Lesions could be differentiated into subareas based on their spectral characteristics in the range of 400 to 900 nm. Sugar beet genotypes with lower disease severity typically had lesions with smaller centers compared with highly susceptible genotypes. Accordingly, the number of conidia per diseased leaf area on resistant plants was lower. The assessment of lesion phenotypes by hyperspectral imaging with regard to sporulation may be an appropriate method to identify subtle differences in disease resistance. The spectral and spatial analysis of the lesions has the potential to improve the screening process in breeding for CLS resistance.

Hyperspectral imaging reveals the effect of sugar beet quantitative trait loci on Cercospora leaf spot resistance.

The quantitative resistance of sugar beet (Beta vulgaris L.) against Cercospora leaf spot (CLS) caused by Cercospora beticola (Sacc.) was characterised by hyperspectral imaging. Two closely related inbred lines, differing in two quantitative trait loci (QTL), which made a difference in disease severity of 1.1-1.7 on the standard scoring scale (1-9), were investigated under controlled conditions. The temporal and spatial development of CLS lesions on the two genotypes were monitored using a hyperspectral microscope. The lesion development on the QTL-carrying, resistant genotype was characterised by a fast and abrupt change in spectral reflectance, whereas it was slower and ultimately more severe on the genotype lacking the QTL. An efficient approach for clustering of hyperspectral signatures was adapted in order to reveal resistance characteristics automatically. The presented method allowed a fast and reliable differentiation of CLS dynamics and lesion composition providing a promising tool to improve resistance breeding by objective and precise plant phenotyping.

Osmotic adjustment of young sugar beets (Beta vulgaris) under progressive drought stress and subsequent rewatering assessed by metabolite analysis and infrared thermography.

The main objective of this work was to provide the chronology of physiological and metabolic alterations occurring under drought and demonstrate how these relate to a phenotypic approach (infrared thermal imaging, IRT). This should provide tools to tailor phenotyping approaches for drought tolerance and underlying metabolic alterations. In the present study, destructive analysis of growth and cell morphology, water status, osmotic adjustment, metabolic changes and membrane damage were combined with non-destructive determination of leaf temperature using infrared thermography (IRT) in 6-week-old sugar beets subjected to progressive drought stress and subsequent rewatering. Different methods were suitable for the characterisation of the dynamic development of distinct stress phases: although IRT allowed detection of initial impairment of transpiration within 1 day of drought stress, destructive methods allowed us to distinguish a phase of metabolic adjustment including redirection of carbon flow into protective mechanisms and a subsequent phase of membrane destabilisation and cellular damage. Only the combination of invasive and non-invasive methods allowed for the differentiation of the complete sequence of physiological changes induced by drought stress. This could be especially beneficial for the selection of phenotypes that are adapted to early drought. During rewatering, sugar beet shoots rapidly re-established water relations, but membrane damage and partial stomatal closure persisted longer, which could have an impact on subsequent stress events. During the onset of secondary growth, taproots required more time to recover the water status and to readjust primary metabolites than shoots.

Supplemental blue LED lighting array to improve the signal quality in hyperspectral imaging of plants.

Hyperspectral imaging systems used in plant science or agriculture often have suboptimal signal-to-noise ratio in the blue region (400-500 nm) of the electromagnetic spectrum. Typically there are two principal reasons for this effect, the low sensitivity of the imaging sensor and the low amount of light available from the illuminating source. In plant science, the blue region contains relevant information about the physiology and the health status of a plant. We report on the improvement in sensitivity of a hyperspectral imaging system in the blue region of the spectrum by using supplemental illumination provided by an array of high brightness light emitting diodes (LEDs) with an emission peak at 470 nm.

Hyperspectral phenotyping on the microscopic scale: towards automated characterization of plant-pathogen interactions.

BACKGROUND: The detection and characterization of resistance reactions of crop plants against fungal pathogens are essential to select resistant genotypes. In breeding practice phenotyping of plant genotypes is realized by time consuming and expensive visual rating. In this context hyperspectral imaging (HSI) is a promising non-invasive sensor technique in order to accelerate and to automate classical phenotyping methods. A hyperspectral microscope was established to determine spectral changes on the leaf and cellular level of barley (Hordeum vulgare) during resistance reactions against powdery mildew (Blumeria graminis f.sp. hordei, isolate K1). Experiments were conducted with near isogenic barley lines of cv. Ingrid, including the susceptible wild type (WT), mildew locus a 12 (Mla12 based resistance) and the resistant mildew locus o 3 (mlo3 based resistance), respectively. The reflection of inoculated and non-inoculated leaves was recorded daily with a hyperspectral linescanner in the visual (400 - 700 nm) and near infrared (700 - 1000 nm) range 3 to 14 days after inoculation. RESULTS: Data analysis showed no significant differences in spectral signatures between non-inoculated genotypes. Barley leaves of the near-isogenic genotypes, inoculated with B. graminis f.sp. hordei differed in the spectral reflectance over time, respectively. The susceptible genotypes (WT, Mla12) showed an increase in reflectance in the visible range according to symptom development. However, the spectral signature of the resistant mlo-genotype did not show significant changes over the experimental period. In addition, a recent data driven approach for automated discovery of disease specific signatures, which is based on a new representation of the data using Simplex Volume Maximization (SiVM) was applied. The automated approach - evaluated in only a fraction of time revealed results similar to the time and labor intensive manually assessed hyperspectral signatures. The new representation determined by SiVM was also used to generate intuitive and easy to interpretable summaries, e.g. fingerprints or traces of hyperspectral dynamics of the different genotypes. CONCLUSION: With this HSI based and data driven phenotyping approach an evaluation of host-pathogen interactions over time and a discrimination of barley genotypes differing in susceptibility to powdery mildew is possible.

Metro maps of plant disease dynamics--automated mining of differences using hyperspectral images.

Understanding the response dynamics of plants to biotic stress is essential to improve management practices and breeding strategies of crops and thus to proceed towards a more sustainable agriculture in the coming decades. In this context, hyperspectral imaging offers a particularly promising approach since it provides non-destructive measurements of plants correlated with internal structure and biochemical compounds. In this paper, we present a cascade of data mining techniques for fast and reliable data-driven sketching of complex hyperspectral dynamics in plant science and plant phenotyping. To achieve this, we build on top of a recent linear time matrix factorization technique, called Simplex Volume Maximization, in order to automatically discover archetypal hyperspectral signatures that are characteristic for particular diseases. The methods were applied on a data set of barley leaves (Hordeum vulgare) diseased with foliar plant pathogens Pyrenophora teres, Puccinia hordei and Blumeria graminis hordei. Towards more intuitive visualizations of plant disease dynamics, we use the archetypal signatures to create structured summaries that are inspired by metro maps, i.e. schematic diagrams of public transport networks. Metro maps of plant disease dynamics produced on several real-world data sets conform to plant physiological knowledge and explicitly illustrate the interaction between diseases and plants. Most importantly, they provide an abstract and interpretable view on plant disease progression.