Plant disease forecasting

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The plant disease triangle represents the factors necessary for disease to occur Plant Disease Triangle.png
The plant disease triangle represents the factors necessary for disease to occur

Plant disease forecasting is a management system used to predict the occurrence or change in severity of plant diseases. At the field scale, these systems are used by growers to make economic decisions about disease treatments for control. Often the systems ask the grower a series of questions about the susceptibility of the host crop, and incorporate current and forecast weather conditions to make a recommendation. Typically a recommendation is made about whether disease treatment is necessary or not. Usually treatment is a pesticide application.

Contents

Forecasting systems are based on assumptions about the pathogen's interactions with the host and environment, the disease triangle. [1] The objective is to accurately predict when the three factors – host, environment, and pathogen – all interact in such a fashion that disease can occur and cause economic losses.

In most cases the host can be suitably defined as resistant or susceptible, and the presence of the pathogen may often be reasonably ascertained based on previous cropping history or perhaps survey data. The environment is usually the factor that controls whether disease develops or not. Environmental conditions may determine the presence of the pathogen in a particular season through their effects on processes such as overwintering. Environmental conditions also affect the ability of the pathogen to cause disease, e.g. a minimum leaf wetness duration is required for grey leaf spot of corn to occur. In these cases a disease forecasting system attempts to define when the environment will be conducive to disease development.

Good disease forecasting systems must be reliable, simple, cost-effective and applicable to many diseases. As such they are normally only designed for diseases that are irregular enough to warrant a prediction system, rather than diseases that occur every year for which regular treatment should be employed. [2] Forecasting systems can only be designed if there is also an understanding on the actual disease triangle parameters.

Features

Models may predict dispersal – see Parry et al 2014 and Soubeyrand et al 2008 for especially successful estimations of patterns and speeds of spread; optimal strategy by goal, either epidemiological level or economic impact level – see Cunniffe et al 2015 for challenges in creating these models, and Papaïx et al 2014 specifically for implementation of these in ddal ; and time to eradication – see Glasa et al 2004 for an example in aphid transmission of Plum pox virus. [3]

Model quality has benefited both from improvements in the technology being supplied from the computer industry, and from improvements in statistical techniques. [3]

Examples of disease forecasting systems

Forecasting systems may use one of several parameters in order to work out disease risk, or a combination of factors. [4] One of the first forecasting systems designed was for Stewart's wilt and based on winter temperature index as low temperatures would kill the vector of the disease so there would be no outbreak. [5] An example of a multiple disease/pest forecasting system is the EPIdemiology, PREdiction, and PREvention (EPIPRE) system developed in the Netherlands for winter wheat that focused on multiple pathogens. [6] USPEST.org graphs risks of various plants diseases based on weather forecasts with hourly resolution of leaf wetness. Forecasting models are often based on a relationship like simple linear regression where x is used to predict y. Other relationships can be modelled using population growth curves. [4] The growth curve that is used will depend on the nature of the epidemic. Polycyclic epidemics such as potato late blight are usually best modelled by using the logistic model, whereas monocyclic epidemics may be best modelled using the monomolecular model. [7] Correct choice of a model is essential for a disease forecasting system to be useful.

Plant disease forecasting models must be thoroughly tested and validated after being developed. Interest has arisen lately in model validation through the quantification of the economic costs of false positives and false negatives, where disease prevention measures may be used when unnecessary or not applied when needed respectively. [4] The costs of these two types of errors need to be weighed carefully before deciding to use a disease forecasting system.

Future developments

In the future, disease forecasting systems may become more useful as computing power increases and the amount of data that is available to plant pathologists to construct models increases. Good forecasting systems also may become increasingly important with climate change. It will be important to be able to accurately predict where disease outbreaks may occur, since they may not be in the historically known areas.

Related Research Articles

Plant pathology Scientific study of plant diseases

Plant pathology is the scientific study of diseases in plants caused by pathogens and environmental conditions. Organisms that cause infectious disease include fungi, oomycetes, bacteria, viruses, viroids, virus-like organisms, phytoplasmas, protozoa, nematodes and parasitic plants. Not included are ectoparasites like insects, mites, vertebrate, or other pests that affect plant health by eating plant tissues. Plant pathology also involves the study of pathogen identification, disease etiology, disease cycles, economic impact, plant disease epidemiology, plant disease resistance, how plant diseases affect humans and animals, pathosystem genetics, and management of plant diseases.

Texas root rot Species of fungus

Texas root rot is a disease that is fairly common in Mexico and the southwestern United States resulting in sudden wilt and death of affected plants, usually during the warmer months. It is caused by a soil-borne fungus named Phymatotrichopsis omnivora that attacks the roots of susceptible plants. It was first discovered in 1888 by Pammel and later named by Duggar in 1916.

Fusarium wilt Fungal plant disease

Fusarium wilt is a common vascular wilt fungal disease, exhibiting symptoms similar to Verticillium wilt. This disease has been investigated extensively since the early years of this century. The pathogen that causes Fusarium wilt is Fusarium oxysporum. The species is further divided into formae speciales based on host plant.

<i>Uncinula necator</i> Species of fungus

Uncinula necator is a fungus that causes powdery mildew of grape. It is a common pathogen of Vitis species, including the wine grape, Vitis vinifera. The fungus is believed to have originated in North America. European varieties of Vitis vinifera are more or less susceptible to this fungus. Uncinula necator infects all green tissue on the grapevine, including leaves and young berries. It can cause crop loss and poor wine quality if untreated. The sexual stage of this pathogen requires free moisture to release ascospores from its cleistothecia in the spring. However, free moisture is not needed for secondary spread via conidia; high atmospheric humidity is sufficient. Its anamorph is called Oidium tuckeri.

<i>Dickeya dadantii</i> Species of flowering plant

Dickeya dadantii is a gram-negative bacillus that belongs to the family Pectobacteriaceae. It was formerly known as Erwinia chrysanthemi but was reassigned as Dickeya dadantii in 2005. Members of this family are facultative anaerobes, able to ferment sugars to lactic acid, have nitrate reductase, but lack oxidases. Even though many clinical pathogens are part of the order Enterobacterales, most members of this family are plant pathogens. D. dadantii is a motile, nonsporing, straight rod-shaped cell with rounded ends. Cells range in size from 0.8 to 3.2 μm by 0.5 to 0.8 μm and are surrounded by numerous flagella (peritrichous).

<i>Clavibacter michiganensis</i> Species of bacterium

Clavibacter michiganensis is an aerobic non-sporulating Gram-positive plant pathogenic actinomycete of the genus Clavibacter. Clavibacter michiganensis has several subspecies. Clavibacter michiganensis subsp. michiganensis causes substantial economic losses worldwide by damaging tomatoes and potatoes.

<i>Podosphaera leucotricha</i> Species of fungus

Podosphaera leucotricha is a plant pathogen that can cause powdery mildew of apples and pears.

<i>Verticillium dahliae</i> Species of fungus

Verticillium dahliae is a fungal plant pathogen. It causes verticillium wilt in many plant species, causing leaves to curl and discolor. It may cause death in some plants. Over 400 plant species are affected by Verticillium complex.

<i>Corynespora cassiicola</i> Species of fungus

Corynespora cassiicola is a species of fungus well known as a plant pathogen. It is a sac fungus in the family Corynesporascaceae. It is the type species of the genus Corynespora.

<i>Gibberella fujikuroi</i> Species of fungus

Gibberella fujikuroi is a fungal plant pathogen. It causes bakanae disease in rice seedlings.

<i>Meloidogyne javanica</i>

Meloidogyne javanica is a species of plant-pathogenic nematodes. It is one of the tropical root-knot nematodes and a major agricultural pest in many countries. It has many hosts. Meloidogyne javanica reproduces by obligatory mitotic parthenogenesis (apomixis).

<i>Pseudoperonospora cubensis</i> Species of single-celled organism

Pseudoperonospora cubensis is a species of water mould known for causing downy mildew on cucurbits such as cantaloupe, cucumber, pumpkin, squash and watermelon. This water mould is an important pathogen of all these crops, especially in areas with high humidity and rainfall, such as the eastern United States. In most years the disease is an annual, late-season problem on squash and pumpkin in the eastern and central United States, however, since 2004 it has become one of the most important diseases in cucumber production. Considered a highly destructive foliar disease of cucurbits, successful breeding in the mid-twentieth century provided adequate control of downy mildew in cucumber without the use of fungicides. The resurgence in virulence has caused growers great concern and substantial economic losses, while downy mildew in other cucurbit crops continues to be a yearly hindrance.

Plant disease epidemiology is the study of disease in plant populations. Much like diseases of humans and other animals, plant diseases occur due to pathogens such as bacteria, viruses, fungi, oomycetes, nematodes, phytoplasmas, protozoa, and parasitic plants. Plant disease epidemiologists strive for an understanding of the cause and effects of disease and develop strategies to intervene in situations where crop losses may occur. Destructive and non-destructive methods are used to detect diseases in plants. Additionally, understanding the responses of the immune system in plants will further benefit and limit the loss of crops. Typically successful intervention will lead to a low enough level of disease to be acceptable, depending upon the value of the crop.

This article summarizes different crops, what common fungal problems they have, and how fungicide should be used in order to mitigate damage and crop loss. This page also covers how specific fungal infections affect crops present in the United States.

Black rot, caused by the bacterium Xanthomonas campestris pv. campestris (Xcc), is considered the most important and most destructive disease of crucifers, infecting all cultivated varieties of brassicas worldwide. This disease was first described by botanist and entomologist Harrison Garman in Lexington, Kentucky, US in 1889. Since then, it has been found in nearly every country in which vegetable brassicas are commercially cultivated.

Southern corn leaf blight

Southern corn leaf blight (SCLB) is a fungal disease of maize caused by the plant pathogen Bipolaris maydis.

Common spot of strawberry Plant fungal disease


Common spot of strawberry is one of the most common and widespread diseases afflicting the strawberry. Common spot of strawberry is caused by the fungus Mycosphaerella fragariae. Symptoms of this disease first appear as circular, dark purple spots on the leaf surface. Mycosphaerella fragariae is very host-specific and only infects strawberry.

Bacterial wilt of carnation

Bacterial Wilt of Carnations is a bacterial disease caused by the plant pathogen Paraburkholderia caryophylli. Previously, named Pseudomonas caryophilli, the pathogen is an aerobic gram negative bacteria known for only being capable of entering its host through wounds. Once inside the host, it colonizes the vascular system and roots causing symptoms such as, internal stem cracking, yellowing of the leaves, wilting, and the development of cankers. As a bacterial disease, Bacterial Wilt of Carnations can also be characterized by signs such as bacterial streaming, and bacterial ooze.

<i>Xanthomonas oryzae</i> pv. <i>oryzae</i> Variety of bacteria

Xanthomonas oryzae pv. oryzae is a bacterial pathovar which causes a serious blight of rice, other grasses and sedges.

Coffee wilt disease (tracheomycosis) is a common wilt that results in complete death of coffee trees it infects. This vascular disease is induced by the fungal pathogen known by its teleomorph Gibberella xylarioides. In 1927, coffee wilt disease (CWD) was first observed in the Central African Republic where it developed slowly and went on to cause two epidemics between the 1930s and the 1960s. Coffee wilt disease was first seen in Coffea excelsa.

References

  1. ↑ Agrios, George (2005). Plant Pathology. Academic Press. ISBN   978-0-12-044565-3.
  2. ↑ Campbell, C. L.; Madden, L. V. (1990). Introduction to Plant Disease Epidemiology. New York: Wiley and Sons. ISBN   0-471-83236-7.
  3. 1 2 Rimbaud, Loup; Dallot, Sylvie; Gottwald, Tim; Decroocq, Véronique; Jacquot, Emmanuel; Soubeyrand, Samuel; Thébaud, Gaël (2015-08-04). "Sharka Epidemiology and Worldwide Management Strategies: Learning Lessons to Optimize Disease Control in Perennial Plants". Annual Review of Phytopathology . Annual Reviews. 53 (1): 357–378. doi:10.1146/annurev-phyto-080614-120140. ISSN   0066-4286.
  4. 1 2 3 Esker, P. D.; A.H. Sparks; L. Campbell; Z. Guo; M. Rouse; S.D. Silwal; S. Tolos; B. Van Allen; K.A. Garrett. "Ecology and Epidemiology in R: Disease Forecasting". The Plant Health Instructor. APS Press. doi:10.1094/PHI-A-2008-01. Archived from the original on 2008-04-11.
  5. ↑ "APS Education Centre - Stewart's wilt of corn". Archived from the original on 2008-05-16. Retrieved 2008-03-23.
  6. ↑ Reinink, K (1986). "Experimental verification and development of EPIPRE, a supervised disease and pest management system for wheat". European Journal of Plant Pathology. SpringerLink. 92 (1): 3–14. doi:10.1007/BF01976371.
  7. ↑ Madden, Laurence; Gareth Hughes; Frank Van Den Bosch (2007). Study of Plant Disease Epidemics. American Phytopathological Society. ISBN   978-0-89054-354-2.
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