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    <journal-meta>
      <journal-title-group>
        <journal-title>S. Ya. Krepych “Modeling and providing of functional
suitability of static systems by methods of analysis of
interval data”, PhD thesis, Lviv</journal-title>
      </journal-title-group>
    </journal-meta>
    <article-meta>
      <title-group>
        <article-title>Intelligent System Analyzing Quality of Land Plots</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Аndrii Bayurskii</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Svitlana Krepych</string-name>
          <email>s.krepych@tneu.edu.ua</email>
        </contrib>
      </contrib-group>
      <pub-date>
        <year>2016</year>
      </pub-date>
      <volume>166</volume>
      <issue>1</issue>
      <fpage>1</fpage>
      <lpage>3</lpage>
      <abstract>
        <p>Products grown on the territory of Ukraine or goods obtained from the processing of the crops concerned are attractive in many countries of the world. It is advisable to focus on improving the cultivation of crops to increase the export of our goods abroad. The development of an appropriate software complex that would combine the interests of the state and farmers to increase the yield of crops and, accordingly, increase the amount of crop, is an integral part of improving the work of the agricultural sector of the state. Introduction a crop rotation is the main idea of developing a software system. This will lessen the drying of the soil and increase yield.</p>
      </abstract>
    </article-meta>
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      <title>-</title>
      <p>Each year the state must sell the tender for the planting of
certain crops for a certain period of time. The most effective
distribution of orders for planting between farmers is the main
issue of study. There is a problem in absence of a database of
agrarians and information’s about tenders at the first stage. In
the work, we will use a simulated bidding scheme based on
input data that is as close as possible to the actual data.</p>
      <p>Only a few hundred species of plants are used in agriculture.
Most of the agricultural products are provided at best twenty
species of plants. For thousands of years, people have been
trying to improve their yields, using the remains of fauna and
flora. However, it was a natural way to improve yields. Today
we see a completely different picture. On the one hand it
increases yields but on the other hand the quality of crops and
also the ecological condition of soils and groundwater
deteriorate [1].</p>
      <p>Considering all the above problems, the creation of an
intelligent system analyzing quality of land plots will be a
major breakthrough in the field of agronomy. It will allow
maximize profits for both the state and agrarians by efficient
cultivation of different crop.
ІІ. MODELING THE PROCESS OF YIELD OF CULTURE</p>
      <p>The main idea of developing a software system for planting
land is to improve soil fertility through such a crop rotation of
crops. This will allow to reduce drying soil, increase the yield
of the crop and will require less use of various types of
herbicides, pesticides, supplements, growth</p>
      <p>stimulants, etc. At the end, it will still have a positive impact
on the environment, because less chemicals will fall into the
soil and, accordingly, to the reservoirs.</p>
      <p>Another positive aspect is that such a system does not exist
in Ukraine today. The main emphasis of the state's provision
of export goods in the field of agrarian industry is focused on
agrarians-monopolists. They conclude with state the main
tendering agreements. Within these agreements, the main
focus is on obtaining a stable yield, resulting in a soil
deterioration. It leads to extensive use of a large amount of
inorganic fertilizers in order to improve soils quality which in
run adversely affects the environmental state or condition.</p>
      <p>The main crops grown in the Ternopil region are
sunflowers, corn, rape, sugar beet and winter crops - wheat and
barley. These crops are an export commodity within our state,
and some of them, including sunflowers and wheat, are part of
the exported goods abroad.</p>
      <p>The average yield index of the described crops for Ternopil
region in 2016 was:
- 3.8 t from 1 ha for wheat;
- 2.4 t from 1 ha for sunflowers;
- 30 t from 1 ha for sugar beet;
- 4.7 t from 1 ha for corn;
- 3.6 t from 1 ha for barley;
- 1.8 t from 1 ha for rape.</p>
      <p>Let's take these indicators as etalon for standard crop yields
to determine which crop on which area is better to plant to
obtain the best possible yield without excess fertilizer. The
planting of a culture will then influence what culture was
planted in this field last year and how many years the proposed
culture was not grown in this area.</p>
      <p>The most depleting for soil, from the crops grown in the
Ternopil region are sunflowers and corn. The land should reset
for seven years to recapture the previous fertilizing power and
inspiration after the sunflowers, after the corn only three years.
This term agricultural producers do not always stand, or do not
stand at all. This is especially true for sunflower. So in the
system is proposed to consider planting a plot sunflower at
least after 4 years.</p>
      <p>Table 1 summarizes the planting rates of crops. It is
including the last year of landing and crop rotation, as well as
the obtained average yield of a crop from 1 ha of land. Let's
enter some variables:
- y – the maximum number of years the culture should not be
grown on the site;
- v pri - average yield of the crop that was last planted on the
plot within the proposed area for the last landing;
- vi - the average yield of a crop that is being prepared for
planting on a plot within the proposed area for the last landing;
- vresi - average yield of cultivated crop.
where ki , i = 1 .. 4 - unknown coefficients, the values of which
need to be evaluated on the basis of the analysis of the data
presented in Table 1.</p>
      <p>According to tabular data we will make a system of linear
algebraic equations in this form:</p>
      <p>It is advisable to construct a model of the dependence of
the yield of the crop from its crop rotation within a specific
area. At the initial stage, we will choose the linear structure of
the model of the species:
vresi = k1 ⋅ yi + k2 ⋅ v pri + k3 ⋅ vi + k4 (1)</p>
      <p>The solution of the system (2) is the region of coefficients
of the model [2,3]. Using the least squares method to find the
estimates of the coefficients of the model from SLR (2), we
obtain the following model:
Obtained value from the formula (3) is reflects the average
yield of the proposed landing in the specified section of the
crop with regard to the history of the planting. However, for a
more adequate construction of the planting strategy, it is
necessary to take into account the risks that can reduce this
indicator.</p>
      <p>Let's establish a 5% deviation from the predicted yield
index for the possibility of taking into account the various risks
of deteriorating crop yields. As a result, the forecast yield of
the crop will be in the range [3]:</p>
      <p>[vr−esi ; vr+esi ] = [vresi − 0,05 ⋅ vresi ; vresi ]</p>
      <p>The order of the state to a certain culture appears in the
interval:</p>
      <p>[Vc−oni ; Vc+oni ]
where Vc−oni - the minimum amount of crop yield required by
the state to cover the domestic needs and export needs of the
overseas; Vc+oni - the maximum amount of crop yield that the
state may buy overtime from agrarians.</p>
      <p>The function of the distribution of planting the culture
between the plots within a single order (2.5) is represented by
the expression:
[ f (Vi )] = ∑ (Si ⋅ [vr−esi ;vr+esi ]) ,</p>
      <p>i=1
where Si - the area of the field selected for planting the
selected culture on the i-th iteration.</p>
      <p>The number of iterations is determined in accordance with
the improvement of the goal function Fi , the value of which
is determined by the formula:</p>
      <p>Fi =
min {mid ([Vc−oni ;Vc+oni ]) − mid ([ f (Vi )])}, (7)
i =1,.., N
where Fi ≥ 0 .</p>
      <p>That is, the choice of the optimal field for planting will be
selected as long as the function Fi will accept positive values
from a set of possible values [4].
(2)
(4)
(5)
(6)
ІII. SOFTWARE REALIZATION
7.2. If there are cultures for which the fields are not yet
selected, then choose the culture that follows the
priority and proceed to step 2.</p>
      <p>Start</p>
      <p>A
Check if the best field is found for</p>
      <p>all cultures
We calculate projected efficiency of</p>
      <p>planting
Get the first priority culture from
the list</p>
      <p>We bind the field to the culture.</p>
      <p>Check field as in use.</p>
      <p>Choose the field with the most
efficiency</p>
      <p>A
End
In order to get started with the system, it is necessary to
form orders. We should choose the culture, their priority and
indicate the minimum and maximum crop yields for the state.
The form of this process is depicted in Fig. 3. [7]</p>
      <p>Once the system has selected the most effective options for
planting fields, you can open the resulting form for viewing
detailed information on the results of calculations, namely:
• description of the data on the agrarian who owns the
field with the planted crop;
• field area;
• a culture that will be planted in the chosen field;
• current year of planting.</p>
      <p>The prototype of the shape is depicted in Fig. 4.
In general, this form depicts a compiled information about
agrarian and field, which will effectively be used when
planting a certain culture. Double-clicking on a culture will
open a dialog box that displays detailed information about the
field and the owner. The prototype of the shape is depicted in
Fig. 5.</p>
      <p>Clicking on the "View yield" button will open a window
that displays information about how much culture of the whole
field was collected, how much was forecasted for collection,
the average yield of actual and average yields is projected in
the range from the minimum to the maximum value. The
prototype of the shape is depicted in Fig. 6.</p>
      <p>IV. CONCLUSION</p>
      <p>In the scientific work the actual scientific research task of
analyzing the quality of land plot planting has been solved. The
following scientific and practical results were obtained.</p>
      <p>During the analysis of the subject area it was discovered
that today the main emphasis of the state's provision of export
goods in the field of agrarian industry is focused on agrarians
of the monopolists. Between them and the state, the main
tendering agreements are concluded. Within these agreements,
the main focus is on obtaining a maximum yield, which leads
to a deterioration of the soil, which is trying to improve with
the use of a large amount of fertilizers of inorganic origin,
which in turn adversely affects the environmental state of the
environment.</p>
      <p>In order to improve crop yields and reduce the amount of
inorganic fertilizers, it is proposed to take into account the
previous crop rotation when planting the crop, which can
significantly improve the yields of the proposed crop.</p>
      <p>In the framework of the proposed approach, a
mathematical model of the dependence of the crop yield from
the previous crop rotation within a specific area is developed.</p>
      <p>The method of planting of plots on the basis of the
developed model of crop rotation is developed, which will
allow covering the minimum amount of crop yield required for
the state for crops and improve the quality of soil application
and, as a result, average yields of crops.</p>
      <p>The program complex of quality of planting of land plots
has been developed, which will improve the connection
between "state-agrarian state". Provide the opportunity for
private entrepreneurs to enter a large market of sales and as a
result, with the correct and lawful application of the software
complex to improve the quality of land and the ecological state
of the country.</p>
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