З PLANT DISEASES IN POPULATIONS (FOUNDATIONS OF EPIPHYTHETIOLOGY)...

Z PLANT DISEASES IN POPULATIONS (FOUNDATIONS OF EPIPHYTHETIOLOGY)

The individuals composing each species of organisms usually form more or less isolated groups, called populations.

A population is a group of individuals of the same species, between which a gene flow occurs as a result of crosses and which are genetically relatively isolated from other groups of individuals of this species.

Typically, populations occupy a certain territory, so that genetic isolation of populations is due, first of all, to the ease of genetic exchanges within populations as compared to exchanges between them. Populations of wild plant species are usually an integral part of more or less complex multi-species phytocenosis. Cenoses of agricultural plants, especially with careful control of weeds, are close to single-species, which imposes special features on the structure and behavior of their populations.

The study of the development of plant diseases in populations involves the most important branch of phytopathology - epiphytotiology (mass disease in human populations is called an epidemic , in animal populations - an epizooty , in plant populations - epiphytoty). As American phytopathologist C. S. Chester wrote, "the main goal of the medical sciences about man is how to preserve the individual; the goal of phytopathology is different, least of all it is the thought of the individual, and mainly of the population, the set. The physician is mainly engaged in therapy, the phytopathologist - with the prevention .

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Methods for estimating the number of diseases

Population biology is one of the most mathematized and precise sections of biology, for a population researcher deals with the number of individuals, their genetic or phenotypic composition, dynamics over time and in space. And for a phytopathologist, their practical interests are added to this, since the number of pathogens is often the most important factor that must be taken into account when deciding whether to choose one or another method of plant protection. There are records of the number of the disease and the number of its pathogen.

Disease counting

The problem taken is the sample - the first, associated with taking into account illnesses. Agronomists usually have to count on a large field, and more often - on a few zeros, and to view all the growing plants on the field is impossible. Therefore, usually take an average sample, which, on the one hand, should not be very large, accessible for detailed study, and on the other - reflect the state of the entire field. Plants for registration are taken in different places of the field in order to cover possible disparity of the lesions at different sites. It is advisable to collect groups of plants on a uniformly spaced zeros, and to keep records of each group within each group separately. This will make it possible to apply the variance analysis of the estimation of the reliability of the results of accounting, with the help of which it is possible to reduce the size of the necessary sample while maintaining a sufficient degree of reliability of the obtained indicators.

Separation of plant diseases into local and general - the second problem of accounting. With local diseases, the plant can carry the symptoms of several or many individual infections, while in common diseases there may be a single act of infection leading to the death or weakening of the whole plant or its crop. For example, rust of wheat - is a local disease, because every single act of infection causes the formation of a separate pustule on the leaf, and these pustules can be many. A hard and dusty bunt of wheat is, on the contrary, a common disease, since infection of seedlings with the first disease or flowers - at the second one, will lead to a complete loss of the seed yield. Bacterial spot of beans is a local disease, and root rot is common, as damage to the root system can cause weakening or even death of the whole plant. Common are viral diseases.

Taking into account local diseases is faced with the need to solve another important problem - counting prevalence (number of affected plants) and intensity (degree of injury). A situation is possible when all or almost all the plants are infected in the studied area, there are only one or two spots of the disease on each plant. In another case, a small percentage of plants in the nil may be affected, but on each plant there are dozens or even hundreds of spots. How can you compare such situations, what is worse for plants and what is more important?

To calculate the prevalence is simple - to put in two heaps of plants that have symptoms of disease and are free from them. It is much more difficult to determine the intensity of the lesion. Recalculation of all spots on the plant is as complex as recalculation of all plants in the field. Therefore, two approaches are proposed for obtaining adequate indicators of the intensity of the disease.

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1. In the first approach, which is used most often, it is suggested to express the intensity of the lesion not in absolute figures (the number of spots) but in relative (points). For different diseases, scales have been created, on which the parts of the leaves depicted on paper are covered with a different number of spots. The sheet of the considered plant is compared with the scale and a figure is chosen whose score coincides with the intensity of the lesion of the leaf. Scales for the account of various plant diseases are given in a number of manuals. As an example, let us cite the Petersen scale, designed to take into account the damage of leaves of cereals with leaf rusts (Figure 3.1), and also the Sari and Prescott scales for taking into account the damage of cereals to spotting (Figure 3.2).

Fig. 3.1. Petersen's scale for determining the score of wheat affected by stem rust:

the numbers of the upper row reflect the absolute percentage of coverage of the leaf blade with disease spots: the lower-row digits are the relative score of the lesion

Fig. 3.2. The scale of Sari and Prescott to account for the damage to cereals caused by powdery mildew and leaf spots :

the numbers show the score of defeat

2. Since the scoring is not absolute, but relative, the important question is the objectivity of the intervals between scores proposed by the authors of the scales. Due to the fact that, according to researches of physiologists, the eye of a man perceives external objects in accordance with the logarithm of their illumination (Weber-Hoffner's law), according to the famous American phytopathologist J. Horsfall, the scoring (or class) gaps should be arithmetical, and logarithmic . Here is how, for example, the scale of accounting for the intensity of the lesion, proposed by Horsfall and R. Barrath (Table 3.1) looks.

Table 3.1

Intensity score scale

Disability, score

Covering the surface of the sheet with spots,%

1

0

2

0-3

3

3-6

4

6-12

5

12-25

6

25-50

7

50-75

8

75-87

9

87-94

10

94-97

11

97-100

12

100

On this scale, except for the extreme dates (0 and 100%), the others mark the same intervals on the log a -scale. If the lesion is below 50%, the interval corresponds to the value of log a , and for lesions above 50%

where a - % of the injury.

German mathematician J. Krantz, based on special studies, considers the 8-point scale optimal (figure 3.3).

Krantz has revealed the following patterns:

- Class gradations should be distinguished not by arithmetic indicators, but by logarithmic ones, so the class gaps along the edges of the scale (with a strong or weak lesion) are shorter than with an average lesion

- The number of classes is limited by the fact that the eye distinguishes gradations between 0.1 and 8% of the coverage of the sheet with spots only after a large workout. Therefore, despite the epidemiological importance of accounting for weak infection, more than two classes in this interval should not be introduced.

Fig. 3.3. J. Krantz's scale of recording leaf damage by disease causing spotting :

the top row of digits in the bottom line indicates the average span of the class; lower number of digits - class boundaries

To use injury assessment tables similar to the ones above, a certain training is necessary, because the basis for establishing the injury class is not a comparison with the figure, but an estimate of the percentage of coverage of the leaf with spots that is as close as possible to the true. Therefore, naturally, for the worker, the average coverage percentage of the sheet (the upper row of digits) is more important, and the class gap, the limits of which are much easier to establish.

It should be noted that logarithmic gaps between classes of damage are established on the basis of the theory (Weber-Hoffner's law). Their empirical verification in a number of cases showed that the arithmetic gradations of the class intervals more adequately reflect the actual state of the intensity of the damage to the plants than the logarithmic ones.

Finally, in order to establish the average lesion of the field, use the disease index - an integrated indicator that takes into account both the prevalence and the intensity of the disease. It is calculated by the following formula:

where R - disease index (mean score of disease); r - score of defeat; b - the number of plants affected by this score; n - total number of counted plants.

Example

100 plants are taken into account, of which 0-10 points are scored, 1 point is 20 points, 2 is 30 points, 3 is 30 points, and 4-10 points.

R = (20 + 60 + 90 + 40)/100 = 2.1.

Another integral indicator is the area under the development curve of the disease. He describes the degree of plant damage not instantaneously, like the index of the disease, but in dynamics, which is sometimes more important. For his

The calculations are carried out to survey the percentage of contamination of the investigated site or variety several times (at least four) and calculate the total index by the formula

5 = 1/2 {(a + b) t 1 + (b + c) t 2 (c + d) t 3 ...},

where a , b, c, d - the intensity of the disease in the first, second, third and fourth accounts; t 1 , t 2 , t 3 - the gap (in the days) between the previous and subsequent accounting.

In contrast to the local, in common diseases it is relatively easy to establish the prevalence (percentage of diseased plants), but much more difficult - the intensity. Of course, when assessing the affection of wheat, it is sufficient to calculate the percentage of diseased ears, but in diseases such as root rot, plants can die completely, but they can turn yellow, burn, fall behind, etc. This is not the number of spots on the leaf or percentage of its coverage by stains; indicators of the intensity of the disease when taking into account root rot are much less objective. Therefore, the scales proposed for their evaluation by different researchers can be very different. For example, E. Gojman gives a very simple scale for assessing the involvement of cereals with fusarium root rot by the appearance of plants (Table 3.2).

Table 3.2

The scale of accounting for the intensity of damage to crops by root rot (according to E. Gojman)

Intensity of defeat, score

Symptom of disease

0

The plant is healthy

1

Yellowish color of affected organs and parts

2

Color from yellowish to brownish, single brown streaks and spots

3

Strong ripening, partial crumbling

4

Dying of tissues and organs

According to MF Grigoriev, it is necessary to excavate the plants under consideration, wash them from the soil and assess the damage to the separately primary roots, underground interstice, secondary roots, root neck and stem base on a four-point scale, and then calculate the mean index of injury.

Uneven , often focal , spread of the disease on the field - the next important accounting problem. In ecology it is common to divide all possible cases of mutual finding of objects into three groups: regular , uniform and contagious (focal ) distribution (Figure 3.4).

Fig. Z.4. Types of distributions of objects in space:

From left to right - regular, uniform, contagious

With a regular distribution, each object is at an equal distance from its neighbors. In nature, such a distribution of plants on the area does not happen, it is typical for artificial planting and planting (regular gardens, square-nesting crops). But even in regular orchards the distribution of diseased plants can not be regular.

Uniform distribution provides an equal probability of the presence or absence of an object at any point of the site. So, for example, wheat plants are distributed on the field. It is described by the Poisson equation

1 - x = e

where x - the number of infected plants (prevalence); m is the average percentage of damage (intensity).

With a contagious (focal) distribution, the distance between individual objects in the outbreaks is less than the distance between objects outside the foci. It occurs most often and is described by the equation

1 - x = (1 + m/k) , where k - is the aggregation coefficient.

Focal distribution of diseases at the site is very frequent and can be the cause of errors that occur when taking an average sample for analysis (if there are few foci, plants from them may not fall into the middle sample). For example, the main source of the emergence of late blight of potatoes planting infected tubers. If 1000 tubers were planted in the field, five of which were infected, and an infected plant grew from each infected tuber, then in the field among 1000 potato bushes there will be five foci of the disease. Under favorable conditions, the spores that form on the infected plants will infect adjacent ones, and the foci will gradually expand, so that eventually the foci will merge and the spread of the disease will become uniform, but at the first counts, which are very important, diseased plants may fall out field of view of the observer. An equation that takes into account the average lesion of zero in the focal distribution of the disease was suggested by AV Filippov. For calculations, the following metrics are needed:

- number of foci;

- the average area of ​​the source;

- the average lesion of the focus.

Example

The average number of foci per 10 000 m (ha) - five; the average area of ​​the outbreak is 80 m; the average degree of affection in the outbreak is 10%. With these indicators, the average field severity is calculated as follows:

[(5-80) 10%]/10 000 = 0.04%.

Now estimates of the damage to agricultural and forest tracts from aircraft and satellites are becoming increasingly popular. A variety of methods have been developed that take into account the discoloration of plants, their reflectivity, etc. For example, when cotton wilt is damaged, the spectral, angular, and polarization structure of crop brightness changes, which can be detected using spectrometers.

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