Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases.
about
Image-based Analysis to Study Plant Infection with Human PathogensMetro maps of plant disease dynamics--automated mining of differences using hyperspectral imagesPlant Phenotyping using Probabilistic Topic Models: Uncovering the Hyperspectral Language of PlantsHyperspectral Imaging for Presymptomatic Detection of Tobacco Disease with Successive Projections Algorithm and Machine-learning Classifiers.An integrated hyperspectral imaging and genome-wide association analysis platform provides spectral and genetic insights into the natural variation in riceHyperART: non-invasive quantification of leaf traits using hyperspectral absorption-reflectance-transmittance imagingLimits of active laser triangulation as an instrument for high precision plant imaging.Hyperspectral phenotyping on the microscopic scale: towards automated characterization of plant-pathogen interactions.Detection of early blight and late blight diseases on tomato leaves using hyperspectral imaging.External characteristic determination of eggs and cracked eggs identification using spectral signatureSpectrum and Image Texture Features Analysis for Early Blight Disease Detection on Eggplant Leaves.Detection of Fungus Infection on Petals of Rapeseed (Brassica napus L.) Using NIR Hyperspectral Imaging.Image-based phenotyping of plant disease symptoms.High Throughput In vivo Analysis of Plant Leaf Chemical Properties Using Hyperspectral ImagingImproved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images.Glyphosate-resistant and glyphosate-susceptible Palmer amaranth (Amaranthus palmeri S. Wats.): hyperspectral reflectance properties of plants and potential for classification.Non-invasive Presymptomatic Detection of Cercospora beticola Infection and Identification of Early Metabolic Responses in Sugar Beet.Quantitative, Image-Based Phenotyping Methods Provide Insight into Spatial and Temporal Dimensions of Plant Disease.Supplemental blue LED lighting array to improve the signal quality in hyperspectral imaging of plants.Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress.Monitoring wound healing in a 3D wound model by hyperspectral imaging and efficient clustering.SINGLE-CELL ANALYSIS USING HYPERSPECTRAL IMAGING MODALITIES.Development of Spectral Disease Indices for 'Flavescence Dorée' Grapevine Disease Identification.Specim IQ: Evaluation of a New, Miniaturized Handheld Hyperspectral Camera and Its Application for Plant Phenotyping and Disease Detection.Chlorophyll Fluorescence and Reflectance-Based Non-Invasive Quantification of Blast, Bacterial Blight and Drought Stresses in Rice.New Spectral Index for Detecting Wheat Yellow Rust Using Sentinel-2 Multispectral Imagery.Proximal Phenotyping and Machine Learning Methods to Identify Septoria Tritici Blotch Disease Symptoms in Wheat.Quantitative assessment of disease severity and rating of barley cultivars based on hyperspectral imaging in a non-invasive, automated phenotyping platform.Evaluating the Effect of Different Wheat Rust Disease Symptoms on Vegetation Indices Using Hyperspectral MeasurementsDeveloping Two Spectral Disease Indices for Detection of Wheat Leaf Rust (Pucciniatriticina)Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stemsDetection of biotic and abiotic stresses in crops by using hierarchical self organizing classifiersField Phenotyping and Long-Term Platforms to Characterise How Crop Genotypes Interact with Soil Processes and the EnvironmentExploring the potential of PROCOSINE and close-range hyperspectral imaging to study the effects of fungal diseases on leaf physiologyDigital Imaging Combined with Genome-Wide Association Mapping Links Loci to Plant-Pathogen Interaction Traits
P2860
Q27009544-4E646A9D-0299-4623-88E8-87EE68554672Q28543092-2119AC15-7FA2-4B6E-ADCE-B2420B878D2CQ28603081-5BE57C20-102C-4330-874F-6E87C33DFAE6Q33829890-F1D83C25-C42E-4C82-842D-F1652452AA0BQ33860983-6E8AF8F0-EC96-406A-B457-474822F63D29Q34997899-11974A82-1C52-4719-B98C-068778A41613Q35087799-15FEE914-E044-4E6D-A1A2-E557E826E3FEQ35621328-F35C8B7A-7108-43E9-BA59-C5A8126CF976Q36287328-AFEEA32A-77D5-4986-A4A8-A70B934903CEQ36588497-19F49F82-B0BD-451B-916D-2E2F93CBB2D2Q36943264-D039551E-72BC-40E2-8BCE-8A4CA1A142E4Q37497480-28A0F51B-DC40-427F-9EAD-86639190F53BQ38324545-AFC8C940-3B40-4DFA-B988-0C2FFB47811EQ38616661-F51BED62-90AF-48F2-8637-2E5B5C611DF1Q38718227-8833F796-7005-470A-B3A2-A960FF0B0A23Q39256079-B228DBC9-9358-4C9D-B427-FB5A591126B7Q39314670-44286E50-4F7E-4F86-B904-D8CCC1FCF2B9Q39575061-49C0F9FF-9D99-4D8E-8CFA-611324D28EECQ41993643-A435D860-F3CD-43D8-9775-28A6431FA67DQ42374154-13A39977-DB68-476F-99A2-843534E5B653Q47093513-EDA88527-FABE-434B-BD7C-E680ADFCDF0AQ47277859-8C0C0AF1-6710-4876-88B7-B952A409B933Q47326989-F7B005D0-BC95-4E8B-8D8F-00DDAE710724Q48114759-7D6578CB-1BA5-4E42-A87C-AC836AC3DF22Q49691173-2AC011D5-88DD-4E32-A1DB-429E5D293824Q52654057-F0A0EB22-CEF4-40EA-BDB4-4EA0F2FD6C82Q55287451-77F377B7-947D-4650-8751-9063FDEBAAF2Q55403092-77C1C325-46A4-4D45-B731-45196DAE1609Q57192864-5D807D56-F788-486A-912B-8EDFC44FCBA9Q57192869-87945884-3596-4A94-91CE-C1F71F444138Q57298181-43005067-C2BA-4709-B314-291B4B9DF540Q57822199-FDD894A2-7CD4-4C0B-A72C-57F2869B2BC5Q58097336-D8EA8137-526E-425A-A16E-7A044F9D61EDQ58107206-47B9F6C1-CF2B-44C1-888F-4C53E4DF2C62Q59126850-8BDB189C-69BC-4965-A0AB-C870D0F63A7B
P2860
Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases.
description
2012 nî lūn-bûn
@nan
2012年の論文
@ja
2012年学术文章
@wuu
2012年学术文章
@zh-cn
2012年学术文章
@zh-hans
2012年学术文章
@zh-my
2012年学术文章
@zh-sg
2012年學術文章
@yue
2012年學術文章
@zh
2012年學術文章
@zh-hant
name
Hyperspectral imaging for smal ...... different sugar beet diseases.
@en
type
label
Hyperspectral imaging for smal ...... different sugar beet diseases.
@en
prefLabel
Hyperspectral imaging for smal ...... different sugar beet diseases.
@en
P2093
P2860
P356
P1433
P1476
Hyperspectral imaging for smal ...... different sugar beet diseases.
@en
P2093
Anne-Katrin Mahlein
Christian Hillnhütter
Erich-Christian Oerke
Heinz-Wilhelm Dehne
Ulrike Steiner
P2860
P2888
P356
10.1186/1746-4811-8-3
P577
2012-01-24T00:00:00Z
P5875
P6179
1044688578