Faculty Opinions recommendation of Image-based phenotyping of plant disease symptoms.

2015 ◽  
Author(s):  
José Dinneny
Keyword(s):  
Plant Disease ◽  
Disease Symptoms

scholarly journals Autonomous Detection of Plant Disease Symptoms Directly from Aerial Imagery

tppj ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Harvey Wu ◽  
Tyr Wiesner‐Hanks ◽  
Ethan L. Stewart ◽  
Chad DeChant ◽  
Nicholas Kaczmar ◽  
...  
Keyword(s):  
Plant Disease ◽  
Aerial Imagery ◽  
Disease Symptoms ◽  
Autonomous Detection

scholarly journals A phytopathometry glossary for the twenty-first century: towards consistency and precision in intra- and inter-disciplinary dialogues

2021 ◽  
Author(s):  
Clive H. Bock ◽  
Sarah J. Pethybridge ◽  
Jayme G. A. Barbedo ◽  
Paul D. Esker ◽  
Anne-Katrin Mahlein ◽  
...  
Keyword(s):  
Plant Pathology ◽  
Disease Severity ◽  
Plant Disease ◽  
Yield Loss ◽  
First Century ◽  
Control Methods ◽  
Visual Estimation ◽  
Disease Symptoms ◽  
Disease Epidemiology ◽  
Measurement Science

AbstractPhytopathometry can be defined as the branch of plant pathology (phytopathology) that is concerned with estimation or measurement of the amount of plant disease expressed by symptoms of disease or signs of a pathogen on a single or group of specimens. Phytopathometry is critical for many reasons, including analyzing yield loss due to disease, breeding for disease resistance, evaluating and comparing disease control methods, understanding coevolution, and studying disease epidemiology and pathogen ecology. Phytopathometry underpins all activities in plant pathology and extends into related disciplines, such as agronomy, horticulture, and plant breeding. Considering this central role, phytopathometry warrants status as a formally recognized branch of plant pathology. The glossary defines terms and concepts used in phytopathometry based on disease symptoms or visible pathogen structures and includes those terms commonly used in the visual estimation of disease severity and sensor-based methods of disease measurement. Relevant terms from the intersecting disciplines of measurement science, statistics, psychophysics, robotics, and artificial intelligence are also included. In particular, a new, broader definition is proposed for “disease severity,” and the terms “disease measurement” and “disease estimate” are specifically defined. It is hoped that the glossary contributes to a more unified cross-discipline approach to research in, and application of the tools available to phytopathometry.

scholarly journals A multiaccess LUCIDtrade; key to common plant pathogenic fungi causing diseases of temperate crops

2003 ◽  
Vol 56 ◽  
pp. 100-102 ◽  
Author(s):  
H.F. Neilson ◽  
T.M. Stewart
Keyword(s):  
Microscopic Examination ◽  
Plant Disease ◽  
Plant Pathogens ◽  
Morphological Characteristics ◽  
Pathogenic Fungi ◽  
Plant Pathogenic Fungi ◽  
Disease Symptoms ◽  
The Public ◽  
Taxonomic Approach ◽  
Common Plant

A LUCIDtrade; multiaccess computerbased key for identifying 175 genera of plant pathogenic fungi of temperate crops is described The key takes a pragmatic rather than a taxonomic approach to identification enabling a nonspecialist to key out many suspected plant pathogens based on microscopic examination of the fungal structures and plant disease symptoms Taxonomic jargon is kept to a minimum and images of morphological characteristics are used frequently Fact sheets on the diseases caused by common pathogens are also included in the programme The key is available in the public domain and should be useful to anyone with a microscope wishing to identify a common fungal disease

scholarly journals DIAGNOSIS LIMA PENYAKIT UTAMA KARENA JAMUR PADA 100 KULTIVAR BIBIT PISANG

2012 ◽  
Vol 12 (1) ◽  
pp. 36-45
Author(s):  
Loekas Soesanto ◽  
Endang Mugiastuti ◽  
Fajarudin Ahmad ◽  
Witjaksono Witjaksono
Keyword(s):  
Fusarium Oxysporum ◽  
Leaf Spot ◽  
Field Data ◽  
Plant Disease ◽  
Pathogenic Fungi ◽  
Curvularia Lunata ◽  
Disease Symptoms ◽  
Descriptive Research ◽  
Laboratory Variables ◽  
Data Result

The research which aimed to identify main pathogenic fungi of 100 banana seedling cultivars and their disease intensity was carried out at the Laboratory of Plant Disease, Faculty of Agriculture, Jenderal Soedirman University with samples and field data taking at Indonesian Insitute of Science  Bogor.  This descriptive research was started by taking samples and field data followed by identification of pathogenic fungi at the laboratory.  Variables observed were disease symptoms, colony and pathogenic morphology, kinds of the pathogen, disease intensity, and physical data.  Result of the research showed that there were five main pathogenic fungi of the banana seedlings, i.e., Fusarium oxysporum Schlecht. f.sp. cubense, causing Fusarium wilt; Mychosphaerella musicola Mulder, causing Mycosphaerella leaf spot or Sigatoka; Cordana musae (Zimm.) Hohn., causing Cordana leaf spot; Curvularia lunata, causing leaf spot; and Cladosporium musae Mason, causing speckle.  From 100 banana seedling cultivars observed, Fusarium oxysporum f.sp. cubense was the most frequently found with the intensity of 1.4-72%, followed by Curvularia lunata, Mychosphaerella musicola, Cladosporium Musae, and Cordana musae with the intensity of 1-32, 2-18, 2-24, and 3-23%, respectively.

scholarly journals Image-based phenotyping of plant disease symptoms

2015 ◽  
Vol 5 ◽  
Author(s):  
Andrew M. Mutka ◽  
Rebecca S. Bart
Keyword(s):  
Plant Disease ◽  
Disease Symptoms

scholarly journals Quantitative, image-based phenotyping methods provide insight into spatial and temporal dimensions of plant disease

2016 ◽  
Author(s):  
Andrew M. Mutka ◽  
Sarah J. Fentress ◽  
Joel W. Sher ◽  
Jeffrey C. Berry ◽  
Chelsea Pretz ◽  
...  
Keyword(s):  
Plant Disease ◽  
In Planta ◽  
Spatial And Temporal Patterns ◽  
Bacterial Populations ◽  
Cassava Bacterial Blight ◽  
Disease Symptoms ◽  
Multiple Imaging ◽  
Host Microbe Interactions ◽  
Temporal Dimensions

AbstractPlant disease symptoms exhibit complex spatial and temporal patterns that are challenging to quantify. Image-based phenotyping approaches enable multi-dimensional characterization of host-microbe interactions and are well suited to capture spatial and temporal data that are key to understanding disease progression. We applied image-based methods to investigate cassava bacterial blight, which is caused by the pathogen Xanthomonas axonopodis pv. manihotis (Xam). We generated Xam strains in which individual predicted type III effector (T3E) genes were mutated and applied multiple imaging approaches to investigate the role of these proteins in bacterial virulence. Specifically, we quantified bacterial populations, water-soaking disease symptoms, and pathogen spread from the site of inoculation over time for strains with mutations in avrBs2, xopX, and xopK as compared to wild-type Xam. ΔavrBs2 and ΔxopX both showed reduced growth in planta and delayed spread through the vasculature system of cassava. ΔavrBs2 exhibited reduced water-soaking symptoms at the site of inoculation. In contrast, ΔxopK exhibited enhanced induction of disease symptoms at the site of inoculation but reduced spread through the vasculature. Our results highlight the importance of adopting a multi-pronged approach to plant disease phenotyping to more fully understand the roles of T3Es in virulence. Finally, we demonstrate that the approaches used in this study can be extended to many host-microbe systems and increase the dimensions of phenotype that can be explored.Summary:Novel, image-based phenotyping methods enhance characterization of plant-pathogen interactions.

scholarly journals First Report of Cephaleuros virescens in Arkansas and Its Occurrence on Cultivated Blackberry in Arkansas and Louisiana

Plant Disease ◽  
1998 ◽  
Vol 82 (2) ◽  
pp. 263-263 ◽  
Author(s):  
G. E. Holcomb ◽  
S. R. Vann ◽  
J. B. Buckley
Keyword(s):  
Plant Disease ◽  
Gulf Coast ◽  
Research Station ◽  
Disease Symptoms ◽  
First Report ◽  
Disease Clinic ◽  
Commercial Grower ◽  
Pathogenicity Tests ◽  
Water Drops ◽  
The U.S

Blackberry (Rubus sp.) cane samples (cultivar Navaho) showing disease symptoms were collected from a commercial grower in Texarkana, AR, and sent for diagnosis to the plant disease clinic in Lonoke in June, 1997. Cane symptoms consisted of stem cracking, tissue discoloration beneath the bark, and the presence of an orange, velvetlike growth that was identified as sporangiophores and sporangia of the parasitic green alga Cephaleuros virescens Kunze. Zoospores were released when sporangia were placed in water drops. The alga was isolated from infected canes on potato dextrose agar, but pathogenicity tests were not attempted because pathogenicity has never been demonstrated successfully, nor have zoospores been produced in culture. C. virescens also was found infecting cultivated blackberry at the Louisiana Calhoun Research Station, where it occurred more commonly on thornless than on thorned type cultivars. This parasitic alga occurs commonly along the U.S. Gulf Coast and has been recorded on 287 plant species and cultivars, including 80 that are subject to stem infections (1,2). The occurrence of C. virescens in Arkansas extends its known northernmost range from 32.5°N to 33.5°N in the U.S. This is the first report on the occurrence of C. virescens in Arkansas and the first report of its occurrence on cultivated, commercially grown blackberry. References: (1) G. E. Holcomb. Plant Dis. 70:1080, 1986. (2) R. B. Marlatt and S. A. Alfieri, Jr. Plant Dis. 65:520, 1981.

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