Thursday, July 18, 2024
General Agriculture

Determination of Plant Disease Incidence and Severity

Plant disease is any abnormal condition that damages a plant and reduces its productivity or usefulness to man. A diseased plant or group of diseased plants is often recognized easily once symptoms or signs become visible; however, it is the quantification of the disease that presents the challenge.

The assessment of disease incidence (i.e., the number or proportion of diseased plants in a population) is an apparently simple counting task, but is subject to the usual limitations of interpretation related to sample size.

The accurate and precise estimation or measurement of disease severity (i.e., the area or proportion of plant tissue that is symptomatic) can be a formidable task.

Plant disease incidence is the proportion or amount of diseased plants or parts in a population. Disease severity is the proportion of plant area that is affected.

Often, disease has to exceed a certain threshold before it reduces the yield of a crop, but it is usually difficult to accurately estimate the yield reduction caused by a specific disease.

For example, many diseases occur on senescing tissue that would not have contributed to the yield anyway. Easier diseases to assess are those that kill whole trees in orchards or plantations, and those that destroy the actual harvested product, such as fruit or grain.

Steps to Take in Plant Disease Incidence and Severity

Determination of Plant Disease Incidence and Severity

Assessment of the effect of disease (incidence/severity) on crop yield normally involves five steps;

  • Developing a descriptive growth stage key for the particular crop species.
  • Developing methods to assess the incidence and severity of disease.
  • Developing statistically sound methods of sampling crop populations for assessment of the amount of disease.
  • Estimating the negative impact of particular levels of the disease on crop yield and quality.
  • Evaluating the economic benefit from various methods available for reducing the amount of disease.

1. Developing a descriptive growth stage key for the particular crop species

The first step to quantify the effect of disease is to develop a key that describes the growth and development of healthy plants during the growing season.

It should describe development, either from sowing to harvest, in the case of annual plants, or from season to season in perennial plants.

Detail drawings or photographs, showing characteristics of the various stages of development, including leaf formation, flowering, fruiting and senescence are needed.

Standardized growth keys have been developed for a number of crop plants, enabling comparison between different countries and different conditions.

2. Developing methods to assess the incidence and severity of disease

The disease incidence for biotrophic pathogens can be measured by counting the number of plants, leaves, flowers etc. that are infected, but the disease severity is assessed by estimating the proportion of total photosynthetic area that is diseased.

Whether it is disease incidence, or disease severity, or both, that are measured, depends on the nature of the disease. Because judging the proportion of diseased leaf by eye is unreliable, disease assessment keys, showing different disease severities as blackened areas, have been devised for various crops.

3. Developing statistically sound methods of sampling crop populations for assessment of the amount of disease

Once the amount of disease has been determined, the next step is to assess, either experimentally or statistically, the effect of different levels of disease on the crop yield.

The statistical approach to assessing disease involves statistical analysis of crop yields under different levels of disease that occur naturally in the field.

The levels of disease and the crop yields are monitored, but not manipulated, and then yields from different seasons or areas with different levels of disease can be compared to determine the effect of disease on crop yield.

An alternative statistical approach to crop loss assessment is the use of questionnaires, filled in by the farmers that allow disease and pest incidence and severity to be related to the yields they produce.

Read Also : Photosynthesis, Plant Growth and Partitioning of Assimilate

4. Estimating the negative impact of particular levels of the disease on crop yield and quality

The growth of the crop, its yield potential, the development of the disease and its impact on yield all have to be measured to predict the impact on yield of particular levels of disease.

This information can be combined with predictions of likely disease levels to determine whether preventative treatments are worthwhile.

5. Evaluating the economic benefit from various methods available for reducing the amount of disease

Disease and crop loss assessments are necessary for evaluating the economic impact of a disease and the benefit of particular control strategies. There is no point in implementing a control measure if it will cost more that the increased crop yield will return.

Advantages

Determination of Plant Disease Incidence and Severity

The method is the use of outcomes of real cropping situations in the field, not experimentally manipulated crops.

Used to predict and forecast crop losses under different environmental situations

Used to determine whether it is economically feasible to embark on a particular control measure

Development of a standardized crop key has helped to have an ideal crop situation. This in effect will give the optimal yields of crops under ideal conditions.

Disadvantages

In the past, most crop loss assessment has been qualitative, producing vague, inaccurate and sometimes misleading data. One major problem with this is the complex nature of disease development.

Rarely can disease be attributed to just one factor. Assessment of the effect of disease (incidence/severity) on crop yield normally complex.

The accurate and precise estimation or measurement of disease severity can be a formidable task because of visual and measurement errors and the need for samples to be representative of the area considered and to be of adequate number.

Statistical tools used are subject to the usual limitations of interpretation related to sample size.

In conclusion, plant disease reduces the productivity or usefulness of plants to man. Symptoms are outward expression of the disease condition which when it becomes visible should be quantified and assessed.

The accurate and precise estimation or measurement of disease severity (i.e., the area or proportion of plant tissue that is symptomatic) can be a formidable task.

Assignment

Select a crop like maize and plant 100 stands under an ideal condition i.e. under green house effect. Monitor the growth and development from planting to harvesting.

Outside the green house, plant 100 seeds of maize and follow all the agronomic practices from planting to harvesting. Then answer the following questions

At which age of the plant did you notice disease(s)?

Where were the symptoms located? Stem, leaf, root, ear, cob?

What is the extent of coverage of the disease?

Is it worth embarking on a control measure?

Make comments with respect to the greenhouse effect on the maize crop.

Read Also : How to start up an E-waste Recycling Business

Agric4Profits

Benadine Nonye is an agricultural consultant and a writer with several years of professional experience in the agriculture industry. - National Diploma in Agricultural Technology - Bachelor's Degree in Agricultural Science - Master's Degree in Science Education - PhD Student in Agricultural Economics and Environmental Policy... Visit My Websites On: 1. Agric4Profits.com - Your Comprehensive Practical Agricultural Knowledge and Farmer’s Guide Website! 2. WealthinWastes.com - For Effective Environmental Management through Proper Waste Management and Recycling Practices! Join Me On: Twitter: @benadinenonye - Instagram: benadinenonye - LinkedIn: benadinenonye - YouTube: Agric4Profits TV and WealthInWastes TV - Pinterest: BenadineNonye4u - Facebook: BenadineNonye

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