Fast Detection of Sclerotinia Sclerotiorum on Oilseed Rape Leaves Using Low-Altitude Remote Sensing Technology
暂无分享,去创建一个
Chu Zhang | Yong He | Feng Cao | Han Guo | Wenwen Kong | Fei Liu | Yong He | Han Guo | W. Kong | Fei Liu | Chu Zhang | Feng Cao | Wenwen Kong
[1] Renfu Lu,et al. Hyperspectral and multispectral imaging for evaluating food safety and quality , 2013 .
[2] Onisimo Mutanga,et al. Multispectral mapping of key grassland nutrients in KwaZulu-Natal, South Africa , 2018 .
[3] A. Whitten,et al. Population structure of Sclerotinia sclerotiorum in an Australian canola field at flowering and stem-infection stages of the disease cycle. , 2006, Genome.
[4] Yaxin Bi,et al. KNN Model-Based Approach in Classification , 2003, OTM.
[5] Haiyan Cen,et al. Chlorophyll Fluorescence Imaging Uncovers Photosynthetic Fingerprint of Citrus Huanglongbing , 2017, Front. Plant Sci..
[6] S. Sathiya Keerthi,et al. Evaluation of simple performance measures for tuning SVM hyperparameters , 2003, Neurocomputing.
[7] Rong Song-bai,et al. Distribution of blackleg disease on oilseed rape in China and its pathogen identification , 2013 .
[8] Jun-yan Huang,et al. Electrocatalytic oxidation of phytohormone salicylic acid at copper nanoparticles-modified gold electrode and its detection in oilseed rape infected with fungal pathogen Sclerotinia sclerotiorum. , 2010, Talanta.
[9] Avital Bechar,et al. Robotic Disease Detection in Greenhouses: Combined Detection of Powdery Mildew and Tomato Spotted Wilt Virus , 2016, IEEE Robotics and Automation Letters.
[10] M. Hossain,et al. Neck blast disease influences grain yield and quality traits of aromatic rice. , 2014, Comptes rendus biologies.
[11] D. Huber,et al. The role of magnesium in plant disease , 2012, Plant and Soil.
[12] Zhihao Qin,et al. Detection of rice sheath blight for in-season disease management using multispectral remote sensing , 2005 .
[13] P. Gbolo,et al. Using high-resolution, multispectral imagery to assess the effect of soil properties on vegetation reflectance at an abandoned feedlot , 2015 .
[14] Guihua Zeng,et al. Thermal light ghost imaging based on morphology , 2016 .
[15] Víctor Robles,et al. Feature selection for multi-label naive Bayes classification , 2009, Inf. Sci..
[16] Reza Ehsani,et al. Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm , 2014 .
[17] Da-Wen Sun,et al. Multispectral Imaging for Plant Food Quality Analysis and Visualization. , 2018, Comprehensive reviews in food science and food safety.
[18] Weiyin Ma,et al. Computing the Hausdorff distance between two B-spline curves , 2010, Comput. Aided Des..
[19] E. Oerke,et al. Digital infrared thermography for monitoring canopy health of wheat , 2007, Precision Agriculture.
[20] Gunter Menz,et al. Multi-temporal wheat disease detection by multi-spectral remote sensing , 2007, Precision Agriculture.
[21] O. Mutanga,et al. Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review , 2010, Wetlands Ecology and Management.
[22] D. Roberts,et al. Estimating life-form cover fractions in California sage scrub communities using multispectral remote sensing , 2011 .
[23] Jocelyn Chanussot,et al. Synthesis of Multispectral Images to High Spatial Resolution: A Critical Review of Fusion Methods Based on Remote Sensing Physics , 2008, IEEE Transactions on Geoscience and Remote Sensing.
[24] Ulrike Steiner,et al. Effect of downy mildew development on transpiration of cucumber leaves visualized by digital infrared thermography. , 2005, Phytopathology.
[25] Frank Technow,et al. Use of Crop Growth Models with Whole-Genome Prediction: Application to a Maize Multienvironment Trial , 2016 .
[26] Yong He,et al. Hyperspectral imaging for classification of healthy and gray mold diseased tomato leaves with different infection severities , 2017, Comput. Electron. Agric..
[27] Anne-Katrin Mahlein,et al. Recent advances in sensing plant diseases for precision crop protection , 2012, European Journal of Plant Pathology.
[28] Ingo Grunwald,et al. Identification of guttation fluid proteins: the presence of pathogenesis‐related proteins in non‐infected barley plants , 2003 .
[29] R. Hammerschmidt,et al. Systemic Induction of Salicylic Acid Accumulation in Cucumber after Inoculation with Pseudomonas syringae pv syringae. , 1991, Plant physiology.
[30] Shen Yin,et al. Tuning kernel parameters for SVM based on expected square distance ratio , 2016, Inf. Sci..
[31] Jorge E. Pezoa,et al. Embedded nonuniformity correction in infrared focal plane arrays using the Constant Range algorithm , 2015 .
[32] I. Pavlidis,et al. Thermal image analysis for polygraph testing. , 2002, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.
[33] Hui-Xia Ma,et al. Occurrence and Characterization of Dimethachlon Insensitivity in Sclerotinia sclerotiorum in Jiangsu Province of China. , 2009, Plant disease.
[34] B. Gossen,et al. Impact of Foliar Diseases on Photosynthesis, Protein Content and Seed Yield of Alfalfa and Efficacy of Fungicide Application , 2006, European Journal of Plant Pathology.
[35] Dong Ni,et al. Multispectral Image Alignment With Nonlinear Scale-Invariant Keypoint and Enhanced Local Feature Matrix , 2015, IEEE Geoscience and Remote Sensing Letters.
[36] H. Muhammad Asraf,et al. A Comparative Study in Kernel-Based Support Vector Machine of Oil Palm Leaves Nutrient Disease , 2012 .
[37] HeYong,et al. Hyperspectral imaging for classification of healthy and gray mold diseased tomato leaves with different infection severities , 2017 .
[38] Andreas von Tiedemann,et al. Effects of experimental warming on fungal disease progress in oilseed rape , 2013, Global change biology.
[39] T. Marosevic,et al. The Hausdorff distance between some sets of points , 2018 .
[40] Brian S. Backer,et al. An advanced infrared thermal imaging module for military and commercial applications , 2005, SPIE Defense + Commercial Sensing.
[41] U. Steiner,et al. Thermographic assessment of scab disease on apple leaves , 2011, Precision Agriculture.
[42] Anne-Katrin Mahlein,et al. Fusion of sensor data for the detection and differentiation of plant diseases in cucumber , 2014 .
[43] M. Malin,et al. The Thermal Emission Imaging System (THEMIS) for the Mars 2001 Odyssey Mission , 2004 .
[44] Wolfgang Förstner,et al. The potential of automatic methods of classification to identify leaf diseases from multispectral images , 2011, Precision Agriculture.
[45] Yoshio Inoue,et al. Remote estimation of leaf transpiration rate and stomatal resistance based on infrared thermometry , 1990 .
[46] P. Curran,et al. Technical Note Grass chlorophyll and the reflectance red edge , 1996 .
[47] Cristiane Neri Nobre,et al. Algorithms Analysis in Adjusting the SVM Parameters: An Approach in the Prediction of Protein Function , 2017, Appl. Artif. Intell..
[48] Dong-Gyu Sim,et al. Object matching algorithms using robust Hausdorff distance measures , 1999, IEEE Trans. Image Process..
[49] Hans R. Schultz,et al. Early pathogen detection under different water status and the assessment of spray application in vineyards through the use of thermal imagery , 2008, Precision Agriculture.
[50] Lukasz A. Kurgan,et al. Discretization as the enabling technique for the Naïve Bayes and semi-Naïve Bayes-based classification , 2010, Knowl. Eng. Rev..
[51] Anne-Katrin Mahlein. Plant Disease Detection by Imaging Sensors - Parallels and Specific Demands for Precision Agriculture and Plant Phenotyping. , 2016, Plant disease.