Application of multiple spectral systems for the tree disease detection: A review

[1]  Cristina E. Davis,et al.  Advanced methods of plant disease detection. A review , 2014, Agronomy for Sustainable Development.

[2]  Wei Zhang,et al.  Development and application of a universal and simplified multiplex RT-PCR assay to detect five potato viruses , 2016, Journal of General Plant Pathology.

[3]  K. Elsayad Optical imaging spectroscopy for plant research: more than a colorful picture. , 2019, Current opinion in plant biology.

[4]  Kai Zhang,et al.  The Plant Pathology Challenge 2020 data set to classify foliar disease of apples , 2020, Applications in plant sciences.

[5]  Alfredo de la Escosura-Muñiz,et al.  Biosensors for plant pathogen detection. , 2017, Biosensors & bioelectronics.

[6]  A. Donoso,et al.  In‐field molecular diagnosis of plant pathogens: recent trends and future perspectives , 2018 .

[7]  A. Docoslis,et al.  Portable surface-enhanced Raman scattering analysis performed with microelectrode-templated silver nanodendrites. , 2020, The Analyst.

[8]  E. Lindberg,et al.  Early detection of forest stress from European spruce bark beetle attack, and a new vegetation index: Normalized distance red & SWIR (NDRS) , 2021 .

[9]  R. Ehsani,et al.  Detection of Laurel Wilt Disease in Avocado Using Low Altitude Aerial Imaging , 2015, PloS one.

[10]  Marian-Daniel Iordache,et al.  A Machine Learning Approach to Detecting Pine Wilt Disease Using Airborne Spectral Imagery , 2020, Remote. Sens..

[11]  Nikrooz Bagheri,et al.  Detection of Fire Blight disease in pear trees by hyperspectral data , 2018 .

[12]  Pablo J. Zarco-Tejada,et al.  Early Detection and Quantification of Verticillium Wilt in Olive Using Hyperspectral and Thermal Imagery over Large Areas , 2015, Remote. Sens..

[13]  Anna O. Conrad,et al.  Fourier-transform infrared (FT-IR) spectroscopy analysis discriminates asymptomatic and symptomatic Norway spruce trees. , 2019, Plant science : an international journal of experimental plant biology.

[14]  Anne-Katrin Mahlein Plant Disease Detection by Imaging Sensors - Parallels and Specific Demands for Precision Agriculture and Plant Phenotyping. , 2016, Plant disease.

[15]  D. Kurouski,et al.  Rapid and noninvasive diagnostics of Huanglongbing and nutrient deficits on citrus trees with a handheld Raman spectrometer , 2019, Analytical and Bioanalytical Chemistry.

[16]  Yannik Rist,et al.  Fine-scale prediction of biomass and leaf nitrogen content in sugarcane using UAV LiDAR and multispectral imaging , 2020, Int. J. Appl. Earth Obs. Geoinformation.

[17]  Lav R. Khot,et al.  Visible-near infrared spectroradiometry-based detection of grapevine leafroll-associated virus 3 in a red-fruited wine grape cultivar , 2019, Comput. Electron. Agric..

[18]  B. Møller,et al.  Label-free Raman hyperspectral imaging analysis localizes the cyanogenic glucoside dhurrin to the cytoplasm in sorghum cells , 2018, Scientific Reports.

[19]  D. Byrne,et al.  Raman spectroscopy as an early detection tool for rose rosette infection , 2019, Planta.

[20]  Jayme Garcia Arnal Barbedo,et al.  Digital image processing techniques for detecting, quantifying and classifying plant diseases. , 2013 .

[21]  Dongrong Xu,et al.  Review of spectral imaging technology in biomedical engineering: achievements and challenges , 2013, Journal of biomedical optics.

[22]  S. Redhead,et al.  Detection and identification of selected cereal rust pathogens by TaqMan® real-time PCR , 2015 .

[23]  P. R. Villas Boas,et al.  Laser-induced fluorescence spectroscopy applied to early diagnosis of citrus Huanglongbing , 2016 .

[24]  Lembe S. Magwaza,et al.  Non-destructive prediction of ‘Marsh’ grapefruit susceptibility to postharvest rind pitting disorder using reflectance Vis/NIR spectroscopy , 2018 .

[25]  P. R. Villas Boas,et al.  Infrared spectroscopy: a potential tool in huanglongbing and citrus variegated chlorosis diagnosis. , 2012, Talanta.

[26]  Reza Ehsani,et al.  Identification of Citrus Greening (HLB) Using a VIS-NIR Spectroscopy Technique , 2012 .

[27]  V. Tomaselli,et al.  A grapevine leaves dataset for early detection and classification of esca disease in vineyards through machine learning , 2021, Data in brief.

[28]  Helmi Zulhaidi Mohd Shafri,et al.  Spectral discrimination of healthy and Ganoderma-infected oil palms from hyperspectral data , 2011 .

[29]  Reza Ehsani,et al.  Detection and Differentiation between Laurel Wilt Disease, Phytophthora Disease, and Salinity Damage Using a Hyperspectral Sensing Technique , 2016 .

[30]  S. Bustin,et al.  How to speed up the polymerase chain reaction , 2017, Biomolecular detection and quantification.

[31]  M Shuaibu,et al.  DETECTION OF APPLE MARSSONIA BLOTCH DISEASE USING PARTICLE SWARM OPTIMIZATION , 2017 .

[32]  Kangkang Wang,et al.  The Early, Rapid, and Non-Destructive Detection of Citrus Huanglongbing (HLB) Based on Microscopic Confocal Raman , 2019, Food Analytical Methods.

[33]  U. Knauer,et al.  Improved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images , 2017, Plant Methods.

[34]  Reza Ehsani,et al.  Evaluating the performance of spectral features and multivariate analysis tools to detect laurel wilt disease and nutritional deficiency in avocado , 2018, Comput. Electron. Agric..

[35]  Huasheng Huang,et al.  Comparison of machine learning methods for citrus greening detection on UAV multispectral images , 2020, Comput. Electron. Agric..

[36]  Michael Fischer,et al.  Evaluating the suitability of hyper- and multispectral imaging to detect foliar symptoms of the grapevine trunk disease Esca in vineyards , 2020, Plant methods.

[37]  Yiannis Ampatzidis,et al.  Finite Difference Analysis and Bivariate Correlation of Hyperspectral Data for Detecting Laurel Wilt Disease and Nutritional Deficiency in Avocado , 2019, Remote. Sens..

[38]  Won Suk Lee,et al.  Comparison of two aerial imaging platforms for identification of Huanglongbing-infected citrus trees , 2013 .

[39]  L. Plümer,et al.  Development of spectral indices for detecting and identifying plant diseases , 2013 .

[40]  Yu Jin,et al.  Recognition of Banana Fusarium Wilt Based on UAV Remote Sensing , 2020, Remote. Sens..

[41]  Farhad Samadzadegan,et al.  UAV-based multispectral imagery for fast Citrus Greening detection , 2019, Journal of Plant Diseases and Protection.

[42]  Jie Ren,et al.  Principles, developments and applications of laser-induced breakdown spectroscopy in agriculture: A review , 2020 .

[43]  M. Irey,et al.  Detection and identification of canker and blight on orange trees using a hand‐held Raman spectrometer , 2019, Journal of Raman Spectroscopy.

[44]  Reza Ehsani,et al.  Visible-near infrared spectroscopy based citrus greening detection: Evaluation of spectral feature extraction techniques , 2011 .

[45]  Gerrit Polder,et al.  Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images , 2019, Front. Plant Sci..

[46]  D. Kurouski,et al.  Confirmatory non-invasive and non-destructive identification of poison ivy using a hand-held Raman spectrometer , 2020, RSC advances.

[47]  Jianbing Yan,et al.  Development of Spectral Disease Indices for Southern Corn Rust Detection and Severity Classification , 2020, Remote. Sens..

[48]  Matthew Maimaitiyiming,et al.  Early Detection of Plant Viral Disease Using Hyperspectral Imaging and Deep Learning , 2021, Sensors.

[49]  H. Shafri,et al.  The development of spectral indices for early detection of Ganoderma disease in oil palm seedlings , 2017 .

[50]  Nikrooz Bagheri,et al.  Application of aerial remote sensing technology for detection of fire blight infected pear trees , 2020, Comput. Electron. Agric..

[51]  Zheng Zheng,et al.  Detection of Citrus Huanglongbing Based on Multi-Input Neural Network Model of UAV Hyperspectral Remote Sensing , 2020, Remote. Sens..

[52]  Joe Mari Maja,et al.  Visible-near infrared spectroscopy for detection of Huanglongbing in citrus orchards , 2011 .

[53]  Christopher Searle,et al.  Quantifying the Severity of Phytophthora Root Rot Disease in Avocado Trees Using Image Analysis , 2018, Remote. Sens..

[54]  Zheng Zheng,et al.  Field detection and classification of citrus Huanglongbing based on hyperspectral reflectance , 2019, Comput. Electron. Agric..

[55]  Yanbo Huang,et al.  Monitoring plant diseases and pests through remote sensing technology: A review , 2019, Comput. Electron. Agric..

[56]  René Hans-Jürgen Heim,et al.  Developing a spectral disease index for myrtle rust (Austropuccinia psidii) , 2019, Plant Pathology.

[57]  Chin Nee Vong,et al.  Detection of Basal Stem Rot (BSR) Infected Oil Palm Tree Using Laser Scanning Data , 2014 .

[58]  Reza Ehsani,et al.  Early detection of basal stem rot disease (Ganoderma) in oil palms based on hyperspectral reflectance data using pattern recognition algorithms , 2014 .

[59]  Teresa Flores,et al.  Rapid identification of Huanlongbing-infected citrus plants using laser-induced breakdown spectroscopy of phloem samples. , 2018, Applied optics.

[60]  Vasilis Valdramidis,et al.  Recent applications of hyperspectral imaging in microbiology. , 2015, Talanta.

[61]  Joe Mari Maja,et al.  Huanglongbing (Citrus Greening) Detection Using Visible, Near Infrared and Thermal Imaging Techniques , 2013, Sensors.

[62]  Daniel S. Falster,et al.  Detecting myrtle rust (Austropuccinia psidii) on lemon myrtle trees using spectral signatures and machine learning , 2018 .

[63]  Reza Ehsani,et al.  Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm , 2014 .

[64]  Yiannis Ampatzidis,et al.  UAV-Based Remote Sensing Technique to Detect Citrus Canker Disease Utilizing Hyperspectral Imaging and Machine Learning , 2019, Remote. Sens..

[65]  Timothy E. Martinson,et al.  Economic Impact of Grapevine Leafroll Disease on Vitis vinifera cv. Cabernet franc in Finger Lakes Vineyards of New York , 2012, American Journal of Enology and Viticulture.

[66]  A. de Vicente,et al.  Detection of White Root Rot in Avocado Trees by Remote Sensing. , 2019, Plant disease.

[67]  Guangzhao Tian,et al.  From hyperspectral imaging to multispectral imaging: Portability and stability of HIS-MIS algorithms for common defect detection , 2018 .

[68]  Yanbo Huang,et al.  Detection of anthracnose in tea plants based on hyperspectral imaging , 2019, Comput. Electron. Agric..

[69]  R. Ramasamy,et al.  Current and Prospective Methods for Plant Disease Detection , 2015, Biosensors.

[70]  Reza Ehsani,et al.  Mid-infrared spectroscopy for detection of Huanglongbing (greening) in citrus leaves. , 2010, Talanta.

[71]  V. Botero-Fernández,et al.  Linking physiological parameters with visible/near-infrared leaf reflectance in the incubation period of vascular wilt disease , 2019, Saudi journal of biological sciences.

[72]  Pablo J. Zarco-Tejada,et al.  High-resolution airborne hyperspectral and thermal imagery for early detection of Verticillium wilt of olive using fluorescence, temperature and narrow-band spectral indices , 2013 .

[73]  Thomas Wöhner,et al.  Apple blotch disease (Marssonina coronaria (Ellis & Davis) Davis) – review and research prospects , 2018, European Journal of Plant Pathology.

[74]  S. Sankaran,et al.  Detection of Anomalies in Citrus Leaves Using Laser-Induced Breakdown Spectroscopy (LIBS) , 2015, Applied spectroscopy.

[75]  Lav R. Khot,et al.  Early detection of grapevine leafroll disease in a red-berried wine grape cultivar using hyperspectral imaging , 2020, Comput. Electron. Agric..

[76]  Andrea Luvisi,et al.  Detection of grapevine yellows symptoms in Vitis vinifera L. with artificial intelligence , 2019, Comput. Electron. Agric..

[77]  S. Delalieux,et al.  Fire Blight Monitoring in Pear Orchards by Unmanned Airborne Vehicles (UAV) Systems Carrying Spectral Sensors , 2020, Agronomy.

[78]  Samsuzana Abd Aziz,et al.  Early detection of diseases in plant tissue using spectroscopy – applications and limitations , 2018 .

[79]  Siva Kumar Balasundram,et al.  A review of neural networks in plant disease detection using hyperspectral data , 2018, Information Processing in Agriculture.

[80]  Application of remote sensing techniques for the identification of biotic stress in plum trees caused by the Plum pox virus , 2015 .

[81]  Fei Liu,et al.  Laser-Induced Breakdown Spectroscopy Coupled with Multivariate Chemometrics for Variety Discrimination of Soil , 2016, Scientific Reports.

[82]  Jean-Michel Roger,et al.  Evaluation of Oil-Palm Fungal Disease Infestation with Canopy Hyperspectral Reflectance Data , 2010, Sensors.

[83]  Stuart Barr,et al.  UAV-BORNE THERMAL IMAGING FOR FOREST HEALTH MONITORING: DETECTION OF DISEASE-INDUCED CANOPY TEMPERATURE INCREASE , 2015 .

[84]  Pablo J. Zarco-Tejada,et al.  Early Detection and Quantification of Almond Red Leaf Blotch Using High-Resolution Hyperspectral and Thermal Imagery , 2016, Remote. Sens..

[85]  Yongsheng Si,et al.  High-Throughput Phenotyping of Fire Blight Disease Symptoms Using Sensing Techniques in Apple , 2019, Front. Plant Sci..

[86]  Daniel Cozzolino,et al.  Use of Infrared Spectroscopy for In-Field Measurement and Phenotyping of Plant Properties: Instrumentation, Data Analysis, and Examples , 2014 .

[87]  P. Zarco-Tejada,et al.  Previsual symptoms of Xylella fastidiosa infection revealed in spectral plant-trait alterations , 2018, Nature Plants.

[88]  Shiyan Fang,et al.  Chemometric development using portable molecular vibrational spectrometers for rapid evaluation of AVC (Valsa mali Miyabe et Yamada) infection of apple trees , 2021 .

[89]  Idris Abu Seman,et al.  Development of classification models for basal stem rot (BSR) disease in oil palm using dielectric spectroscopy , 2018, Industrial Crops and Products.

[90]  G. Antonova,et al.  Seasonal development of phloem in scots pine stems , 2006, Russian Journal of Developmental Biology.

[91]  C. Huck,et al.  Breakthrough Potential in Near-Infrared Spectroscopy: Spectra Simulation. A Review of Recent Developments , 2019, Front. Chem..

[92]  Baofeng Su,et al.  Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications , 2017, J. Sensors.

[93]  JaCinta S. Batson,et al.  Identification of Opioids and Related Substances using Handheld Raman Spectrometers , 2020, Journal of forensic sciences.

[94]  Beth Fallon,et al.  Spectral differentiation of oak wilt from foliar fungal disease and drought is correlated with physiological changes. , 2020, Tree physiology.

[95]  Stuart Barr,et al.  Combined use of spectral and structural characteristics for improved red band needle blight detection in pine plantation stands , 2019, Forest Ecology and Management.

[96]  Yong He,et al.  Hyperspectral reflectance imaging combined with carbohydrate metabolism analysis for diagnosis of citrus Huanglongbing in different seasons and cultivars , 2018, Sensors and Actuators B: Chemical.

[97]  Shattri Mansor,et al.  Early Detection of Ganoderma Basal Stem Rot of Oil Palms Using Artificial Neural Network Spectral Analysis. , 2017, Plant disease.

[98]  Dianpeng Zhang,et al.  Study on terahertz spectrum analysis and recognition modeling of common agricultural diseases. , 2020, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[99]  X. Fan,et al.  High Diversity of Cytospora Associated With Canker and Dieback of Rosaceae in China, With 10 New Species Described , 2020, Frontiers in Plant Science.

[100]  L. Melgarejo,et al.  Leaf spectral reflectance of Hevea brasiliensis in response to Pseudocercospora ulei , 2020, European Journal of Plant Pathology.

[101]  Andrew P French,et al.  Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress , 2017, Plant Methods.

[102]  Amr H. Abd-Elrahman,et al.  A remote sensing technique for detecting laurel wilt disease in avocado in presence of other biotic and abiotic stresses , 2019, Comput. Electron. Agric..

[103]  Samsuzana Abd Aziz,et al.  Spectral features selection and classification of oil palm leaves infected by Basal stem rot (BSR) disease using dielectric spectroscopy , 2018, Comput. Electron. Agric..

[104]  H. Jones,et al.  Multi‐sensor plant imaging: Towards the development of a stress‐catalogue , 2009, Biotechnology journal.

[105]  G. Carter,et al.  Leaf optical properties in higher plants: linking spectral characteristics to stress and chlorophyll concentration. , 2001, American journal of botany.

[106]  Francisco Javier González,et al.  Raman Spectroscopy an Option for the Early Detection of Citrus Huanglongbing , 2016, Applied spectroscopy.