EPWS 310 - PLANT PATHOLOGY

 

LECTURE: ABIOTIC DISEASES AND PLANT DISEASE EPIDEMIOLOGY

Readings: Chapter 7, 8, 10

 

Plants grow best within a specified range of environmental conditions.  Growing plants outside their optima may cause problems.  Environmental conditions that are important include:

Temperature, soil moisture, soil nutrition, light, pollutants, humidity, soil structure, pH

Problems due to the environment are not transmissible and may affect all stages of plant growth.  Symptoms vary from mild to severe, with the severity dependant on the distance from the optima.  Symptoms are often similar to those cause by viruses, phytoplasmas, and root pathogens, so diagnosis is difficult.

Nutrient deficiencies and toxicities cause disease and induce susceptibility to pathogenic diseases. PH plays a major role, because as pH increases some elements become less available, while others can become toxic.  In high pH soils, iron and zinc become deficient.

When mobile elements such as N, P, K, Na, Mg, Cl, S become deficient, the symptoms show up in older leaves, while deficiencies of immobile elements such as boron, iron, and Ca show up in younger leaves.

Nutrient problems can be diagnosed by soil testing, tissue testing, and symptoms.

 

The environment has pronounced effects on plants disease by effecting pathogens and plants.  Plants grown outside of their optimum are more susceptible to disease.  A pathogens ability to cause disease depends on its optimum environmental conditions.  Some fungi grow better at cooler temperatures, others at hot temperatures.  A pathogen can repeat its life cycle (disease cycle) more rapidly at its optimum temperature. 

Moisture has a significant effect on the germination and penetration of fungal spores and a role in dissemination of pathogens.  It influences disease development, ex. anthracnose, downy mildew, rust, and powdery mildew.  Some pathogens prefer higher moisture, others lower moisture.

Other factors effecting disease include, wind, light, soil pH, herbicides, and pollution.  Plant nutrition effects disease also.  Obligate parasites are more active on vigorously growing plants, while non-obligates prefer weakened tissue and wounds. N, P, K, Ca levels significantly effect disease.

What is epidemiology?

The study of epidemics or epiphytotics. An epidemic is the outbreak of a disease (plant, animal or human) which affects many individuals over a large area in a short space of time.

Epidemiology is the study of the reasons behind these outbreaks so that they may me stopped completely or at least reduced in frequency and duration. In human medicine epidemiologists study things like diet, living conditions, social behavior as well as the weather, movement of infected individuals, dispersal of new strains of pathogens etc.

Plant pathologists study the same type of things but concentrate much more on weather and dispersal.

Some epidemics have become out-of-control such as the Irish Potato Famine, southern corn leaf blight, wheat rust etc.

All epidemics have a set of common elements represented by the disease triangle -susceptible host, virulent pathogen, and conducive environment.

1. susceptible host. Genetic uniformity makes it worse. Type of crop has influence also. Diseases in perennials are slower than in annuals. Age of host influences susceptibility to disease (FIG 8-5).

 

2. virulent pathogen

* Amount of inoculum.

Pathogen life cycle - Length of reproductive parts of life cycle of pathogen (short or long).

Type - asexual or sexual

* Mechanism of dispersal of pathogen (Air, Soil, wind etc).

3. Environmental factors - Water and Temperature.

 

4. * Cultural practices, including site preparation, propagative material, sanitation, plant nutrition, monoculture

 

5. * Introduction of new pathogens or new races or into new areas.

Epidemics must be quantifiable in order to be studied. Hence there are three major parameters used to measure plant disease in a quantitative way.

1) Disease incidence - proportion of plants, leaves stems etc showing disease. (discrete variable)

2) Disease Severity - The proportion of the total AMOUNT of plant matter (dry weight leaf area etc) which is diseased. Includes severity on diseased plant + disease free plants (continuous variable) can use disease assessment scales

3) Yield loss - The yield reduction DIRECTLY attributable to the disease. It is difficult to isolate amount attributable to disease since plants can compensate. Economic threshold or damage threshold.

These can be plotted against time to provide a DISEASE PROGRESS CURVE to provide a way to visualize quantitatively the structure of an epidemic.

Figures 8-14 and 8-16

Y axis = disease (severity, percentage, incidence)

X axis = time

Note that the DPC depends upon the interplay between host, pathogen and environment and these are constantly changing in many ways. The DPC is an integrated view of the disease.

There are two basic types of epidemics:

1) Monocyclic

2) Polycyclic

These may be bimodal indicating two distinct phases of the disease. Affecting two different plant organs at different times.

Monocyclic diseases are those which have one generation of infective propagules per year. Usually with a large overwintering inoculum load at the beginning of the season and just keep pace with the growing crop. Curve has a distinct rise, then levels off. Examples are Verticillium wilt of cotton, and Fusarium root rots.

Polycyclic diseases are those with multiple cycles. Often with a small overwintering load but lots of secondary or summer cycles which cause geometric increases in inoculum in a short time during the season. Examples include rusts and late blight of potato.

Both cycles reflect infectivity of overwintering inoculum and number of generations involved in the epidemic.

Disease gradient curves show one-dimensional spatial patterns of disease from a source.

Note these have all been developed for foliar diseases and there has been little attention paid to soilborne diseases until recently but these same techniques are applied to them as foliar diseases so they don't work all that well.

Disease progress curves used to compare epidemics around the world and to evaluate cultural practices and fungicidal treatments.

The comparison of different DPC's under different treatments of cultural practices is tricky because the curve may change quantitatively as well as qualitatively. Hence curves are often transformed mathematically to a straight line then two comparisons are possible.

1 - determine if the same transformation works as well for both epidemics if not then there is a qualitative difference.

2 - determine if the slope and intercept of the transformed line is the same for both to quantify difference.

The strict comparison of different epidemics involves modeling where parameters may be varied and quantified in as many dimensions as the modeler desires.

This is beyond this class but modeling does lead to one very practical benefit and that is disease forecasters or computer-based disease prediction systems.

These are usually based on weather (temperature, humidity, rainfall - ex. Phytophthora infestans - polycyclic with large load early and throughout the season)

initial inoculum - especially for monocyclic diseases like Fusarium oxysporum - where the microconidia are spread inside the plant

and host and pathogen characteristics.

There are many, many examples of commercial successes with these models.

E.g.:

Apple Scab in the NE USA- initial inoculum + weather

Late Blight of Potato - weather (temperature + relative humidity)

Early blight of potato and tomato - weather (moisture + temperature)

Chrysanthemum blight

Southern corn leaf blight (temperature + relative humidity +spore count)

Leaf spot of peanuts (moisture + temperature)

Septoria blotch of wheat and many others - weather

The detail mechanics of each forecast depends on the disease. Nearly all depend on the weather, many depend on the host developmental stage and if the disease is monoyclic then they also need the initial inoculum load.

Hence diseases like soilborne root rots and bacteria which overwinter in an insect vector. Must be forecast based on the amount of initial inoculum. This requires some type of bioassay or monitoring during the winter or in the spring. For Verticillium, this would mean counting the number of sclerotia per gram of soil.

Diseases which depend on the development of secondary inoculum. Many important diseases are like this. Leaf spots, the late blight pathogen of potato etc. They have low initial inoculum but can build up quickly. These can be predicted almost entirely by a few weather parameters e.g. Temperature, humidity and rainfall.

Some diseases need to be forecast on BOTH of the above criteria and this is difficult but still worth it e.g. Apple Scab, rusts - need to know inoculum load and weather data

Apple Scab Figure 11-90.

Need to know overwintering inoculum because the ascospores can be released over 1-2months during bud break, then conidia kick into secondary phase and many more infections can occur.

Farmer Warning systems e.g. BLITECAST for late blight are used to warn farmers by news bulletins on radio or newspaper of by telephone, in many states.

Also the Neogen Envirocaster which is placed in each field and gives real time advisories to the farmer for Apple Scab.