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 Considerations for Verticillium Wilt Resistance Evaluation in Potato

Plant Disease ◽  
2007 ◽  
Vol 91 (4) ◽  
pp. 360-367 ◽  
Author(s):  
K. E. Frost ◽  
D. I. Rouse ◽  
S. H. Jansky
Keyword(s):  
Disease Severity ◽  
Verticillium Wilt ◽  
Yield Loss ◽  
Control Culture ◽  
In Planta ◽  
Disease Symptoms ◽  
Accuracy And Precision ◽  
Population Sizes ◽  
Pathogen Colonization ◽  
Time Accuracy

Verticillium wilt (Vw), caused by the soilborne fungi Verticillium dahliae and V. albo-atrum, is an important disease of potato (Solanum tuberosum). Host plant resistance is a promising method of Vw control. Culture-based methods that quantify the pathogen in host tissue often are used for Vw resistance screening. To evaluate the processing time, accuracy, and precision of these methods, 46 clones were planted in a field naturally infested with V. dahliae to collect data on visual disease symptoms, pathogen colonization, and yield. In 2002, disease severity explained 4.34% of the variability of yield loss, but the linear relationship between stem colonization and yield loss was not significant. In 2003, stem colonization explained 57.5% of the variability of yield loss, whereas disease severity explained 1.7% of the variability of yield loss. Correlations comparing clone ranks from repeated pathogen measurements indicated that culturing sap from individual stems or bulked stems generated more repeatable clone rankings than culturing dried stems. Clone rankings were more repeatable between years if pathogen measurements were made earlier in the growing season. The results indicate a need to characterize the effect of the environment on the relationship among pathogen population sizes in planta, disease symptoms, and yield loss.

Inoculation of seeds with Bipolaris sorokiniana and soil fumigation methods to determine wheat and barley tolerance and yield losses caused by common root rot

1997 ◽  
Vol 77 (4) ◽  
pp. 691-698 ◽  
Author(s):  
K. L. Bailey ◽  
L. J. Duczek ◽  
D. A. Potts
Keyword(s):  
Disease Severity ◽  
Root Rot ◽  
Yield Loss ◽  
Bipolaris Sorokiniana ◽  
Soil Fumigation ◽  
Common Root ◽  
Disease Symptoms ◽  
Common Root Rot ◽  
Plot Yield ◽  
Healthy Seed

Wheat and barley plants that are severely infected with common root rot yield less than uninfected ones. Resistant cultivars usually have fewer diseased plants but some cultivars show tolerance as no yield loss occurs even though many plants display disease symptoms. This study assessed disease severity and yield loss due to common root rot in cultivars of wheat and barley by two techniques: i) sowing infested seed in soils with low inoculum levels of Bipolaris sorokiniana (Sacc. in Sorok.) Shoem., and ii) planting healthy seed in soil treated with the fumigants, metam and basamid. Infested seed exhibited reduced emergence, increased disease severity, but plot yield was not significantly affected compared with uninfested seed. The average yield loss or gain from seed treatment amongst all selections of wheat and barley was not significantly different. Losses were of the same magnitude (11.1% in barley, 6.2% in wheat) as reported in other studies. Soil fumigation reduced levels of B. sorokiniana in soil and disease severity. It also led to increased nutrient levels in soil and plant tissues, plant height, and plot yields by 16–29% compared with untreated areas. Tolerance to common root rot was exhibited by BW632, Virden, and Melvin. These losses are higher than reported in other studies which suggests yield loss may be underestimated or that common root rot is only one component of a root problem complex being affected by fumigants. Key words: Common root rot, loss, tolerance, seed inoculation, fumigation

scholarly journals E-Triage Systems for COVID-19 Outbreak: Review and Recommendations

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2845
Author(s):  
Fahd Alhaidari ◽  
Abdullah Almuhaideb ◽  
Shikah Alsunaidi ◽  
Nehad Ibrahim ◽  
Nida Aslam ◽  
...  
Keyword(s):  
Population Growth ◽  
Disease Severity ◽  
Waiting Time ◽  
Transmission Rate ◽  
Waiting Times ◽  
Triage System ◽  
Disease Symptoms ◽  
Comprehensive Review ◽  
Severity Levels ◽  
Growth And Aging

With population growth and aging, the emergence of new diseases and immunodeficiency, the demand for emergency departments (EDs) increases, making overcrowding in these departments a global problem. Due to the disease severity and transmission rate of COVID-19, it is necessary to provide an accurate and automated triage system to classify and isolate the suspected cases. Different triage methods for COVID-19 patients have been proposed as disease symptoms vary by country. Still, several problems with triage systems remain unresolved, most notably overcrowding in EDs, lengthy waiting times and difficulty adjusting static triage systems when the nature and symptoms of a disease changes. In this paper, we conduct a comprehensive review of general ED triage systems as well as COVID-19 triage systems. We identified important parameters that we recommend considering when designing an e-Triage (electronic triage) system for EDs, namely waiting time, simplicity, reliability, validity, scalability, and adaptability. Moreover, the study proposes a scoring-based e-Triage system for COVID-19 along with several recommended solutions to enhance the overall outcome of e-Triage systems during the outbreak. The recommended solutions aim to reduce overcrowding and overheads in EDs by remotely assessing patients’ conditions and identifying their severity levels.

scholarly journals Agro-Nanotechnology as an Emerging Field: A Novel Sustainable Approach for Improving Plant Growth by Reducing Biotic Stress

2021 ◽  
Vol 11 (5) ◽  
pp. 2282
Author(s):  
Masudulla Khan ◽  
Azhar U. Khan ◽  
Mohd Abul Hasan ◽  
Krishna Kumar Yadav ◽  
Marina M. C. Pinto ◽  
...  
Keyword(s):  
Plant Growth ◽  
Crop Yield ◽  
Biotic Stress ◽  
Crop Production ◽  
Plant Disease ◽  
Yield Loss ◽  
Growth Parameters ◽  
Plant Diseases ◽  
High Yield ◽  
Plant Disease Management

In the present era, the global need for food is increasing rapidly; nanomaterials are a useful tool for improving crop production and yield. The application of nanomaterials can improve plant growth parameters. Biotic stress is induced by many microbes in crops and causes disease and high yield loss. Every year, approximately 20–40% of crop yield is lost due to plant diseases caused by various pests and pathogens. Current plant disease or biotic stress management mainly relies on toxic fungicides and pesticides that are potentially harmful to the environment. Nanotechnology emerged as an alternative for the sustainable and eco-friendly management of biotic stress induced by pests and pathogens on crops. In this review article, we assess the role and impact of different nanoparticles in plant disease management, and this review explores the direction in which nanoparticles can be utilized for improving plant growth and crop yield.

scholarly journals Extension Plant Pathology: Strengthening Resources to Continue Serving the Public Interest

2012 ◽  
Vol 102 (7) ◽  
pp. 652-655 ◽  
Author(s):  
K. L. Everts ◽  
L. Osborne ◽  
A. J. Gevens ◽  
S. J. Vasquez ◽  
B. K. Gugino ◽  
...  
Keyword(s):  
Plant Pathology ◽  
Plant Disease ◽  
Crop Yields ◽  
Economic Value ◽  
The United States ◽  
Emerging Diseases ◽  
Plant Diseases ◽  
Economic Losses ◽  
Global Competitiveness ◽  
Horticultural Crops

Extension plant pathologists deliver science-based information that protects the economic value of agricultural and horticultural crops in the United States by educating growers and the general public about plant diseases. Extension plant pathologists diagnose plant diseases and disorders, provide advice, and conduct applied research on local and regional plant disease problems. During the last century, extension plant pathology programs have adjusted to demographic shifts in the U.S. population and to changes in program funding. Extension programs are now more collaborative and more specialized in response to a highly educated clientele. Changes in federal and state budgets and policies have also reduced funding and shifted the source of funding of extension plant pathologists from formula funds towards specialized competitive grants. These competitive grants often favor national over local and regional plant disease issues and typically require a long lead time to secure funding. These changes coupled with a reduction in personnel pose a threat to extension plant pathology programs. Increasing demand for high-quality, unbiased information and the continued reduction in local, state, and federal funds is unsustainable and, if not abated, will lead to a delay in response to emerging diseases, reduce crop yields, increase economic losses, and place U.S. agriculture at a global competitive disadvantage. In this letter, we outline four recommendations to strengthen the role and resources of extension plant pathologists as they guide our nation's food, feed, fuel, fiber, and ornamental producers into an era of increasing technological complexity and global competitiveness.

scholarly journals Brown spot disease severity, yield and yield loss relationships in pigmented upland rice cultivars from East Nusa Tenggara, Indonesia

2020 ◽  
Vol 21 (4) ◽  
Author(s):  
Yosep S. Mau ◽  
Antonius Ndiwa ◽  
Shirly Oematan
Keyword(s):  
Disease Severity ◽  
Yield Loss ◽  
Upland Rice ◽  
Brown Spot ◽  
Yield Reduction ◽  
Rice Cultivars ◽  
Rice Varieties ◽  
Resistance Level ◽  
Spot Disease ◽  
Brown Spot Disease

Abstract. Mau YS, Ndiwa ASS, Oematan SS. 2020. Brown spot disease severity, yield and yield loss relationships in pigmented upland rice cultivars from East Nusa Tenggara, Indonesia. Biodiversitas 21: 1625-1634. Brown spot is one of the most devastating diseases of rice, which could lead to total yield loss. The disease has a worldwide distribution, more specifically in areas where water supply is scarce, most specifically in the dry upland areas. Almost all stages of rice are affected by the disease, where leaves and grains are mostly affected. Considerable differences exist in susceptibility to brown spot among rice varieties, which may cause a large variation in yield loss caused by the disease. Therefore, the resistance level of rice varieties and their yield reduction has to be regularly evaluated and updated. There are only a few reports on the relationship between brown spot severity with yield and yield loss of upland rice, and is even lacking in pigmented upland rice. The objectives of the present study were to assess the brown spot severity and resistance level in pigmented upland rice cultivars from East Nusa Tenggara Province, Indonesia, and to elucidate their relationships with yield and yield reduction. Twenty four pigmented upland rice genotypes were evaluated in the field during May to October 2019, and their disease responses and yields were recorded. Disease severity was observed weekly and used to calculate Area Under the Disease Progress Curve (AUDPC) for comparison among the genotypes. The relationships between disease severity and AUDPC with yield and yield loss were also examined. The results showed significant variation in brown spot severity and AUDPC, ranging from, respectively, 11.11% to 40.70% and 398.42%-days to 1081.30%-days. Yields and yield losses of test genotypes also varied substantially. Yields under diseased-free and diseased plots ranged from, respectively, 2.34 t ha-1 to 6.13 t ha-1 and 1.68 t ha-1 to 3.74 t ha-1 while yield loss was between 10.46% and 56.15%. Six genotypes were moderately resistant, four genotypes were moderately susceptible and 14 genotypes were susceptible to brown spot. Neither disease severity nor AUDPC had a linear relationship with yield but both exhibited positive and linear relationships with yield loss.

Image Segmentation for Feature Extraction

2018 ◽  
pp. 232-257 ◽  
Author(s):  
C. Deisy ◽  
Mercelin Francis
Keyword(s):  
Plant Pathology ◽  
Feature Extraction ◽  
Disease Diagnosis ◽  
Target Object ◽  
Literature Survey ◽  
Remedial Measures ◽  
Disease Symptoms ◽  
Segmentation Methods ◽  
Agricultural Plants ◽  
Object Features

This chapter explores the prevailing segmentation methods to extract the target object features, in the field of plant pathology for disease diagnosis. The digital images of different plant leaves are taken for analysis as most of the disease symptoms are visible on leaves apart from other vital parts. Among the different phases of processing a digital image, the substantive focus of the study concentrates mainly on the methodology or algorithms deployed on image acquisition, preprocessing, segmentation, and feature extraction. The chapter collects the existing literature survey related to disease diagnosis methods in agricultural plants and prominently highlights the performance of each algorithm by comparing with its counterparts. The main aim is to provide an insight of creativeness to the researchers and experts to develop a less expensive, accurate, fast and an instant system for the timely detection of plant disease, so that appropriate remedial measures can be taken.

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