=Paper=
{{Paper
|id=Vol-3309/paper17
|storemode=property
|title=Analysis and Prediction of Humus Balance in Soils of Ukraine Using Informational Tools
|pdfUrl=https://ceur-ws.org/Vol-3309/paper17.pdf
|volume=Vol-3309
|authors=Viktor Zhukovskyy,Andriy Sverstiuk,Borys Sydoruk,Nataliia Zhukovska,Sofiia Sverstiuk
|dblpUrl=https://dblp.org/rec/conf/ittap/ZhukovskyySSZS22
}}
==Analysis and Prediction of Humus Balance in Soils of Ukraine Using Informational Tools==
https://ceur-ws.org/Vol-3309/paper17.pdf
Analysis and Prediction of Humus Balance in Soils of Ukraine
Using Informational Tools
Viktor Zhukovskyya, Andriy Sverstiukb, Borys Sydorukc , Nataliia Zhukovskaa and Sofiia
Sverstiukd
a
National University of Water and Environmental Engineering, 11 Soborna St., Rivne, 33028, Ukraine
b
I. Horbachevsky Ternopil National Medical University, 12 Rus'ka St., Ternopil, 46001, Ukraine
c
Ternopil State Agricultural Experimental Station of Institute of Feed Research and Agriculture of Podillya of
NAAS, 12 Troleybusna St., Ternopil, 46027, Ukraine
d
Ternopil National Pedagogical University, 2 Maxyma Kryvonosa St., Ternopil, 46027, Ukraine
Abstract
The impact of agricultural activity intensification on soil quality, the relationship between
soil humus content and the dynamics of the technically feasible energy potential of crops
grown in Ukraine in the regional context, and the production of organic fertilizers as a result
of raising livestock are all topics covered in this article. The investigation revealed a
downward trend in the humus content of Ukrainian soils, which is mostly attributable to an
increase in the production of crops that deplete the soil and a decrease in the production of
organic fertilizers, which can be used to restore land fertility. Due to this circumstance,
agricultural land loses its inherent fertility and its monetary value. To further rehabilitate it,
enormous financial resources will be needed. The paper used a wide range of methods of
analysis and mathematical modeling, grouped administrative regions into clusters according
to the study. Research data reveal a high correlation coefficient of the studied indicators
within individual territories. Crop rotation modeling and percentages of organic fertilizer
application will be made possible by the integration of IT technologies, using the example of
a humus balance e-calculator for organic land use, in order to stabilize or improve soil
quality. The research results are expected to be used to plan the necessary measures to
increase the environmental and economic efficiency of the agricultural land use system.
Keywords 1
humus balance, modeling, organic portal, organic fertilizers, soil quality
1. Introduction
Despite the impacts of anthropogenic impact on the state of the soil, the goal of modern
agricultural production is to turn a quick profit. It first appears in the intensification of the crop sector,
which is geared toward expanding the area sown with energy crops. This circumstance, which is
typical of Ukraine as well, strives to boost the energy potential of the crop industry. The
characteristics of growing energy crops used for bioenergy generation and their impact on soil fertility
are therefore the subjects of several scholarly papers. Numerous researchers are looking into how the
development of energy crops affects the state of agricultural land [1].
Methodological approaches to evaluating the potential of energy crops for energy production and
their social and economic implications are the subject of numerous works [2, 3].
The outcomes of this research generally provide the basis for the claim that the growth of the
bioenergy sector is crucial for obtaining a variety of social and economic benefits. However, it is
ITTAP’2022: 2nd International Workshop on Information Technologies: Theoretical and Applied Problems, November 16–18, 2021,
Ternopil, Ukraine
EMAIL: sverstyuk@tdmu.edu.ua, v.v.zhukovskyy@nuwm.edu.ua
ORCID: 0000-0001-8644-0776 (A. Sverstiuk); 0000-0002-7088-6930 (V. Zhukovskyy); 0000-0002-7705-6489 (B. Sydoruk); 0000-0001-
7839-0684 (N. Zhukovska)
2022 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
known that there is a growing negative influence of economic activity on the quality parameters of
land used for agriculture as a result of the growth in seeded areas of soil-depleting crops.
The application of organic fertilizers to feed the soil and replenish its humus content is crucial for
restoring soil fertility. The study of the application of organic fertilizers to increase soil fertility and
acquire other environmental impacts is the focus of the work of many scientists. Accordingly, it was
proven in a study [4] that adding animal dung to the soil encourages plant growth, herbivore
tolerance, and the control of pests. Paper [5] illustrates the significance of the development of the
livestock industry working in tandem with crop production to enhance the quality qualities of land.
The phrase "humus balance" refers to both the model for maximizing soil productivity in arable
land by calculating the demand for organic fertilizers without quantifying the change in SOM or SOC,
as well as simple models for quantifying changes in soil organic matter (SOM) or soil organic carbon
(C) (SOC) in arable soils [6–8]. Several scientists have been working on humus balance modelling,
mass, heat and moisture transfer in soils at the same time. [7–19]. They established the fundamental
terms and guidelines for computing the humus balance.
In turn, predicting humus balance requires the development of compartment-type models of
reaction-diffuse type, the dynamics of which were studied in [20, 21]. A deeper study of the
interaction of counterparts within such type models can be based on recurrent neural networks, the
convergence of which was studied in the general case in [22].
The study [23] extensively covers the use of various methods for obtaining enough organic
fertilizers and maintaining soil fertility, as well as the relationship between nitrogen and carbon
efficiency depending on the development of various novel methods for the treatment of plant residues
and animal waste.
At the same time, the scientific community gives insufficient consideration to a thorough
investigation of the effects of crop intensification (including increased production of crops that
deplete the soil, such as sunflower, soybeans, rapeseed, etc.) and the amount of land fertilized with
organic fertilizers from farm animals (the content of humus in them) [24].
To leverage the identified interdependencies to harmonize environmental and economic interests
in the area of agricultural land use at various levels of government, we predict that there is a close
relationship between these characteristics.
In addition, many scientists have emphasized that an important factor in the effectiveness of
agricultural production development, including organic production, is the introduction of innovative
management approaches based on software complexes and geoinformation systems (GIS) [25–29].
Features of GIS use in the agricultural sector, including organic farming, presented by such scientists
as: Medvedev V. V. [30], Romashchenko M. I.[31], Morozov V. V. [32], Pichura V. I. [1], JaafarH.
H. [33], Montgomery B. [34], Mishra A. K. [35], Pilehforooshha P. [36] and other scientists.
However, as of right now, Ukraine has no expertise in developing websites, portals, or software for
online modelling the humus content change over time.
2. Materials and Methods
The study's methodology is based on a dialectical approach, which enables analysis of the current
state of the agricultural land use system and recommendations for its improvement. This approach
allows for assessing the impact of economic laws in establishing trends and patterns of social and
natural phenomena and processes.
A regionally integrated approach, which demonstrates the interdependence of economic and social
systems, their unbreakable unity with the natural environment, and the balance of relationships with
which the principles of environmental safety and sustainable development of land use in agriculture
are formed, is crucial to the system of land-use efficiency assessment.
In this situation, we believe it is crucial to employ the cluster approach as a tool for the targeted
management of the economic and environmental aspects of the regional land use system in the
agricultural sector. This is essential for increasing the agricultural land use's economic and
environmental efficiency. The goal is to locate regions where specific factors have a noticeable
impact by using clustering's potential. As a result, economic development priorities are established,
taking into account how they will affect the standards of land quality.
A study of the dynamics of the technically feasible energy potential of crops cultivated in Ukraine
in the regional context is necessary to determine the degree of intensification of land use in the
agricultural sector. In this case, it is proposed to use the "Methods of generalized assessment of
technically achievable energy potential of biomass", which was developed by scientists of the
National University of Life and Environmental Sciences of Ukraine, Institute of Technical
Thermophysics NAS of Ukraine, Institute of Renewable Energy NAS of Ukraine [37].
It is advised to look into the creation of organic fertilizers during the process of raising farm
animals in order to assess the possibilities for the fertile layer restoration of soil (humus), which is lost
due to growing crops during the examined period. The calculation is proposed to be carried out by
following the "Methods for calculating the volume of agricultural products at constant prices and the
index of agricultural products", which was approved by the order of the State Statistics Service of
Ukraine from 19.09.2019 №311.
Using the software program Statistica 10.0, the study's findings and the effects of the factors
considered on the amount of humus in Ukraine's soils from 1990 to 2019 were assessed. The
interrelation between the factors considered was evaluated, as well as their influence, the degree of
interconnection among the factors considered, the clustering of the country's regions, and the division
of the regions into four clusters based on the three factors considered.
Materials and reports from the State Statistics Service of Ukraine, the Institute of Soil Protection
of Ukraine, and research guidelines from scientific, educational, and governmental organizations used
as the study's data source.
3. Results and Discussions
An urgent issue in the modern world is the degradation of the ecological condition of land
throughout the process of its agricultural usage. We can see this pattern in Ukraine as well.
The paper demonstrates how identifying environmental hazards and threats paves the way for
modelling countermeasures to eco-destructive forces and creating a framework for their
implementation. The usage of agricultural land will improve as a result of this. Therefore, we propose
to investigate the impact of land use intensification in agriculture on soil quality (by assessing the
technically available energy potential obtained by growing crops in Ukraine), as well as to assess
volumes of production of organic fertilizers in the process of growing farm animals, in order to
identify eco-destructive factors in the system of agricultural land use. You can use the findings to
decide whether it would be possible to increase the humus content of soils.
3.1. Cluster Analysis
According to an analysis of soil quality indicators by organic component (humus content), humus
levels gradually declined between 1990 and 2019 in accordance with the indicators. Cherkasy,
Chernivtsi, Kharkiv, Khmelnitskyi, Luhansk, Mykolaiv, Poltava, Ternopil, Vinnytsia, and Volyn are
some of the administrative regions of Ukraine where the dynamics of diminishing the humus content
on agricultural fields have been observed. So, in Ukraine, the average humus content has fallen by
0.12% over the past 25 years. Due to the fact that it takes 25–30 years to naturally increase it by 0.1
percent in the soil [38].
The effects of agricultural intensification activities are one of the elements that contributed to this
degradation of soil quality. This process is accompanied by a change in the structure of the areas
where crops that can produce bioenergy are seeded. These crops mineralize significantly more humus
in the soil during development than the soil still contains after harvest (it is then used to fertilize land
by its plowing).
The rise in the technically feasible energy potential of cultivated crops is another indicator of the
rise in the proportion of soil-depleting crops per 100 hectares of arable land (check Table 1). The
growth was greater than ten times in some regions (Zaporizhia, Herson, and Chernihiv).
The fact that there was a large decline in the number of farm animals in Ukraine throughout the
studied period further complicates the matter. Due to this, there is less manure being produced, which
you can utilize to replenish the humus in the soil. Thus, in the Luhansk, Mykolaiv, and Zaporizhia
areas, the volume of production of organic fertilizers per 1 hectare of arable land reduced by 9.7 to
16.5 times. We investigated the correlation dependence of the dynamics of these indicators in terms of
regions of Ukraine in order to establish the interdependence between the acquired technically
attainable energy potential of crops per 100 hectares of arable land and the degree of humus in soils.
The study led to the identification of the areas where these indicators are most closely related
(correlation coefficient > 0.8). As a result, the Transcarpathian (0.88) and Kyiv (0.86) regions show
the most direct correlation between the dynamics of indicators of technically possible capacity of
agricultural sowing. We observe the inverse relationship in the Kharkiv (-0.85) and Luhansk (-0.83)
regions. This demonstrates how agricultural operations have become more intensive in different
administrative regions.
The following regions have the highest levels of interdependence between soil humus content and
the kinetics of organic fertilizer production: Khmelnytskyi (0.92), Lviv (0.90), Mykolaiv (0.92),
Poltava (0.97), Vinnytsia (0.88), and Volyn (0.98). Additionally important is how closely these
variables relate to one another across the board in Ukraine (the correlation coefficient is 0.98).
Table 1
Volumes of technologically possible energy potential per 100 hectares of agricultural land that can
be acquired from agricultural raw materials produced in Ukraine in the context of the region for
1990–2019 (tons of conventional fuel per 100 hectares of arable land)
Years
The ratio
Region
1990 2000 2010 2012 2014 2016 2017 2019 of 2019 to
1990,%
Cherkasy 4.2 1.8 6.4 9.9 10.2 9.2 7.8 12.6 300.0
Chernihiv 1.1 0.7 3.6 7.2 8.3 6.6 9.6 11.4 1036.4
Chernivtsi 4.6 2.8 4.6 5.7 8.2 4.1 6.1 6.9 150.0
Dnipro 0.9 0.9 1.9 1.4 3.3 3.3 4.0 7.7 855.6
Donetsk 0.4 0.4 0.5 0.5 1.2 0.6 1.5 2.2 550.0
Herson 0.4 0.3 3.1 0.8 2.4 1.9 3.7 5.3 1325.0
Ivano-Frankivsk 2.6 1.7 3.2 8.0 11.7 8.6 13.1 10.4 400.0
Kharkiv 1.7 0.9 1.0 2.5 3.8 3.4 3.0 2.9 170.6
Khmelnytskyi 3.9 1.6 6.2 8.6 13.1 8.2 10.7 13.6 348.7
Kropyvnytskyi 2.1 1.0 4.7 3.7 6.0 5.4 5.1 7.9 376.2
Kyiv 2.9 1.4 3.8 8.0 9.4 6.7 6.9 11.7 403.4
Luhansk 0.3 0.4 0.3 0.7 0.9 0.8 0.5 0.7 233.3
Lviv 2.9 1.4 6.8 9.3 11.7 8.8 12.2 13.2 455.2
Mykolayiv 0.8 0.3 3.4 1.1 3.2 1.4 2.5 5.8 725.0
Odesa 0.9 0.6 6.3 1.2 6.1 2.5 6.2 8.7 966.7
Poltava 3.3 1.3 4.3 6.5 7.3 8.7 6.5 9.4 284.8
Rivne 3.3 1.1 4.6 6.6 7.7 5.0 7.1 10.9 330.3
Sumy 2.9 0.8 3.1 6.4 8.9 7.0 7.9 9.7 334.5
Ternopil 4.5 2.2 8.0 10.5 14.1 9.8 12.8 15.8 351.1
Transcarpathian 1.6 1.6 2.8 3.2 3.2 4.4 4.2 4.3 268.8
Vinnytsia 4.1 2.3 5.6 7.5 12.4 8.6 10.8 13.4 326.8
Volyn 2.3 1.0 3.6 5.1 7.4 4.8 8.4 12.4 539.1
Zaporizhia 0.3 0.3 1.4 0.4 1.2 1.2 1.5 3.9 1300.0
Zhytomyr 1.2 0.5 2.5 5.6 6.5 4.8 6.4 10.4 866.7
Ukraine 1.9 1.0 3.5 4.2 6.1 4.6 5.7 8.0 421.1
In the Chernihiv region, it is observed that these indicators have an inverse relationship (-0.98).
This could be explained by a considerable increase in the areas of depleting crops (such as sunflower
and soybeans) that are sown alongside a significant decrease in the use of organic fertilizers to
improve the condition of the soil (in this region, they are characterized by low humus content).
Applying the software Statistica 10.0, the regions of Ukraine were exposed to cluster analysis. The
volume of the technically attainable energy potential of cultivated crops, the volume of production of
organic fertilizers, and the content of humus in the soil were taken into consideration in each cluster
during the period 1990–2019 (data for 1990, 2000, 2010, and 2019 were utilized for the study). The
table below lists the findings of the cluster analysis used to divide Ukraine's regions into 4 clusters
(Tables 3, 4).
Table 2
Volumes of organic fertilizers produced by farm animals per 1 ha of arable land in each area of
Ukraine, measured in t per ha of agricultural land
Years
Region The ratio of 2019 to
1990 2000 2010 2012 2014 2016 2017 2019
1990,%
Cherkasy 7.7 3.5 2.4 2.4 2.2 2.0 1.9 1.8 23.4
Chernihiv 9.9 3.6 1.9 1.9 1.6 1.5 1.4 1.2 12.1
Chernivtsi 13.5 6.1 4.2 4.1 3.5 3.2 3.1 3.0 22.2
Dnipro 6.2 1.8 1.1 1.1 1.1 1.0 0.9 0.9 14.5
Donetsk 6.7 2.1 1.4 1.4 1.0 0.7 0.8 0.8 11.9
Herson 5.4 1.4 0.8 0.9 0.9 0.8 0.7 0.6 11.1
Ivano-Frankivsk 14.1 8.1 5.5 5.6 5.2 4.8 4.5 4.2 29.8
Kharkiv 6.6 2.4 1.2 1.2 1.2 1.1 1.1 1.0 15.2
Khmelnytskyi 9.0 4.5 2.4 2.4 2.2 2.1 2.1 2.0 22.2
Kropyvnytskyi 5.1 1.5 0.9 0.9 0.8 0.7 0.7 0.6 11.8
Kyiv 9.5 3.4 1.9 2.0 1.9 1.8 1.8 1.8 18.9
Luhansk 6.6 1.8 1.1 1.0 0.6 0.4 0.4 0.4 6.1
Lviv 13.7 7.5 4.0 4.0 3.6 3.4 3.3 2.9 21.2
Mykolayiv 4.9 1.4 0.9 0.9 0.8 0.8 0.9 0.5 10.2
Odesa 5.6 2.3 1.3 1.3 1.3 1.1 1.0 0.9 16.1
Poltava 7.3 2.8 1.6 1.7 1.6 1.5 1.4 1.3 17.8
Rivne 12.2 5.8 3.7 3.8 3.3 3.0 2.9 2.4 19.7
Sumy 7.8 3.4 1.5 1.5 1.3 1.3 1.3 1.2 15.4
Ternopil 10.3 4.6 2.6 2.8 2.5 2.4 2.2 2.1 20.4
Transcarpathian 18.9 10.3 9.0 9.2 8.6 8.0 7.7 8.0 42.3
Vinnytsia 7.4 3.4 2.1 2.2 2.1 2.2 2.1 1.8 24.3
Volyn 13.7 6.1 4.0 4.1 3.6 3.4 3.2 2.8 20.4
Zaporizhia 5.8 1.5 0.8 0.8 0.8 0.7 0.7 0.6 10.3
Zhytomyr 10.0 4.8 2.3 2.3 1.9 1.9 1.9 1.9 19.0
Ukraine 7.4 2.9 1.7 1.7 1.5 1.5 1.4 1.3 17.6
Table 3
The results of the Ukraine regions cluster analysis for 1990, 2000, 2010, and 2019 based on the
studied indicators grouping that affects the quality of soils
Years Cluster characteristics (administrative areas)
First Second Third Fourth
1990 Chernivtsi, Ivano-Frankivsk, Cherkasy, Chernihiv, Dnipro, Donetsk, Herson,
Lviv, Rivne, Transcarpathian, Khmelnytskyi, Kyiv, Poltava, Kharkiv, Luhansk Kirovohrad,
Volyn Sumy, Ternopil, Vinnytsia, Mykolayiv, Odesa,
Zhytomyr Zaporizhia,
2000 Cherkasy, Chernihiv, Chernivtsi, Ivano-Frankivsk, Lviv, Herson, Kirovohrad, Dnipropetrovsk,
Khmelnytskyi, Kyiv, Poltava, Rivne, Transcarpathian, Mykolayiv, Odesa, Donetsk, Kharkiv,
Sumy, Ternopil, Volyn Zaporizhia Luhansk
Vinnytsia, Zhytomyr
2010 Chernihiv, Herson, Dnipropetrovsk, Donetsk, Cherkasy, Lviv, Chernivtsi, Ivano-
Kirovohrad, Kyiv, Mykolayiv, Kharkiv, Luhansk, Zaporizhia Khmelnytskyi, Odesa, Frankivsk, Rivne,
Poltava, Sumy, Zhytomyr Ternopil, Vinnytsia Transcarpathian,
Volyn
2019 Chernivtsi, Dnipropetrovsk, Cherkasy, Chernihiv, Ivano- Transcarpathian Donetsk, Kharkiv,
Herson, Kropyvnytskyi, Frankivsk, Khmelnytskyi, Kyiv, Luhansk,
Mykolayiv, Odessa, Poltava, Lviv, Rivne, Ternopil, Vinnytsia, Zaporizhia
Sumy Volyn, Zhytomyr
Analysis of variance shows that the number of clusters was correctly chosen because there are
differences between the groups we obtained at a significance level p 0.05.
The findings of cluster analysis (k-means clustering) for various years between 1990 and 2019 are
represented in Fig. 1-4 as the split of regions into four clusters by three components (the amount of
technically achievable energy potential of crops, the number of organic fertilizers and the level of
humus in soils).
Based on the presented figures, we observe the relationship between the studied groups of
indicators. Thus, during the analyzed period in all clusters the highest average indicators for the
production of organic fertilizers (manure) and technically achievable energy potential of crops
correspond to one of the lowest average indicators of humus content in soils, and vice versa. This may
indicate limited use of organic matter to improve soil quality, as well as an increased intensification of
agricultural activities. The consequence is the depletion of agricultural land. Additionally, we observe
a notable rise in the amount of technically feasible energy potential in the third and second clusters
between 2010 and 2019. It implies a rise in the production of agricultural goods that require a lot of
energy, particularly in the administrative regions of Ukraine's west, north, and centre. This has an
impact on the humus content of the soils in these areas.
Table 4
Average values of quantitative indicators of the volume of the technically achievable energy
potential of crops, organic fertilizers, and humus content were determined based on the grouping of
studied indicators that affect the quality status of soils, according to the study results of a Ukraine
regions cluster analysis in 1990, 2000, 2010, and 2019
Name Numerical characteristics of clusters (average values of quantitative indicators (standard
quantitative deviations))
indicators First Second Third Fourth
1990 year
Organics 14.35 (2.32) 8.77 (1.22) 6.53 (0.22) 5.36 (0.36)
Potential 2.88 (1.02) 3.12 (1.25) 0.83 (0.64) 0.9 (0.72)
Humus 2.34 (0.42) 2.92 (0.53) 4.18 (0.29) 3.33 (0.73)
2000 year
Organics 3.78 (0.68) 7.32 (1.72) 1.65 (0.44) 1.92 (0.34)
Potential 1.40 (0.64) 1.60 (0.65) 0.38 (0.15) 0.72 (0.29)
Humus 2.84 (0.49) 2.38 (0.58) 3.01 (0.58) 4.14 (0.21)
2010 year
Organics 1.48 (0.56) 1.12 (0.22) 2.47 (0.88) 5.28 (2.19)
Potential 3.56 (0.70) 1.02 (0.65) 6.55 (0.81) 3.76 (0.82)
Humus 2.97 (0.70) 3.99 (0.37) 2.98 (0.29) 2.33 (0.54)
2019 year
Organics 1.13 (0.81) 2.26 (0.80) 8.00 (0.00) 0.7 (0.26)
Potential 7.68 (1.60) 12.35 (1.62) 4.30 (0.00) 2.43 (1.35)
Humus 3.32 (0.70) 2.68 (0.53) 2.56 (0.00) 3.69 (0.32)
The study's findings indicate that there is, in the majority of Ukraine's regions, a negative
relationship between soil humus content and the expansion of agricultural land use. This establishes
the necessity of further balancing the effects of human activity on the state of the land and identifying
the future directions for agricultural land use. They will be designed to optimize the layout of crop-
sown regions and the creation of a suitable system of organic fertilizers while taking into
consideration the dynamics of humus content in soils. The creation of an appropriate legislative
framework that will guarantee the application of suitable administrative influence on land users is also
crucial for the construction of a system of balanced agricultural land use at the national level.
As a result, creating a comprehensive system of balanced land use is essential for raising the
quality of agricultural land while also increasing its economic and environmental effectiveness.
a) year 1990 b) year 2000
c) year 2010 d) year 2019
Figure 1: Cluster analysis results (K-means method) for the period 1990-2019 for each cluster: blue
line – first cluster, orange line – second cluster, green line – third cluster, red line – fourth cluster
3.2. Mathematical Modeling
In order to predict the change in soil organic matter (SOM) levels over a long period, the
dynamics of organic matter are simulated. The first published model of OPE decomposition based on
differential equations was proposed by S. Genin and his colleagues [39]. One of the most popular
SOM dynamics models today is Rothamsted (RothC), which emits 4 active pools and 1 stable pool
(inert organic matter) [39]. In the post-Soviet space, the widespread model of ORU dynamics
(ROMUL) involves the allocation of three major pools - detritus (prehumus fraction), labile humus,
and stable humus [40].
The following paragraph explains the mathematical model of the change in humus concentration
in some soil volume [41]:
Let y (t ) be the amount of humus at time t (t / ha); y (t t ) – s the amount of humus at time
t t ; at the initial time y(0) y0 , where y0 – is the amount of humus at the initial time; f ( R, ) –
is some function of the humus balance and the type of crop (t / ha); R – type of culture for planting,
– balance of humus.
Then the humus change is proportional to the amount of humus at a given time and the function
of the humus balance and the type of culture
y (t t ) y (t )
V V k ( y (t ) f ( R, )) ,
t
where k– some proportionality factor.
dy dy
At t 0 , we will get k ( y (t ) f ( R, )) . Then: kdt
dt y (t ) f ( R, )
From which ln y(t ) f ( R, ) kt c , where c const .
Then: y (t ) c1 e k t f ( R, ) , where c1 ec .
From the initial condition y(0) y0 we will get c1 y0 f (R, ) .
Therefore, the humus content at time t is equal to
y (t ) ( y0 f ( R, )) e k t f ( R, ) .
By using certain input data as input for this mathematical model, we obtain a graph of the
humus content versus time. (Fig. 2).
Figure 2: Modeling the dynamics of soil humus content using a mathematical model
3.3. Information-Analytical System
As part of the software implementation work, the aforementioned computer simulation method for
affecting the humus condition at a predefined time interval was implemented, accounting for the costs
of applying organic fertilizer in the form of an e-calculator. Integration of the newly designed module
into the current information-analytical system of organic agriculture was a crucial next step.
The e-calculator module is divided into two sections: the Frontend section and the Backend
section, which includes ASP.NET MVC code, average crop fertility statistics, agrochemical soil
indicators, etc (html, css, java script). According to the GET and POST requests from the Frontend
portion, the Backend part implements the Web API method for numerical calculations. On the client's
end, crop rotation, desired crops, and fertilizer opportunities are developed in accordance with the
client's needs. The humus state change can be modeled in two different ways: "Individual plan" and
"Rationale for all scenarios". By toggling the desired tab in the GUI dialog box for the GUI module,
the desired mode can be chosen.
The user selects the crops and the amount of fertilizer for each year in the "Individual plan" mode
(Fig. 3). The system will then produce a humus status change report for this specific circumstance
utilizing a server-side numerical computation in accordance with the aforementioned mathematical
model when the user clicks the "Get Recommendations" button. Instead, the "Rationale for all
scenarios" mode includes an automated computation to support any conceivable situation involving
fertilizer in various years (Fig. 4). The user can set the amount of funds available for the cost of
organic fertilizer and the number of years to examine. Then, using the "Calculate all choices" button,
the e-calculator launches the proper algorithm for computer simulation and eco-economic
calculations. The user will then be able to select the option that best suits him in terms of cost and
environmental impact.
Figure 3: Dialog box for humus change simulation initialization in an individual plan scenario
Figure 4: Dialog box for justification different scenarios involving fertilizer in various years
4. Conclusions
The study's findings support the notion that it is prudent to consider the impact on the status of
land characteristics of the operation of the two subsystems of natural and economic in order to ensure
the balanced use of land resources by the agricultural sector. The results of the investigation showed a
connection between the intensification of agricultural operations, the volume of organic fertilizer
production, and the quality of the land (humus content in soils).
An important degree of dependency and grouping of the regions of Ukraine between 1990 and
2019 was discovered using the statistical processing data method of the researched indicators in the
program Statistica 10.0. Also, we demonstrated the method of mathematical and computer modelling
for the prediction of humus content change in the soils of Ukraine.
The geoinformation-analytical system of organic agriculture incorporates the proposed method of
humus balance calculation as an e-calculator module. The e-humus balance calculator allows the user
to independently set the order of crops to be grown in rotation and the amount of organic fertilizer
(biohumus) to be applied. As a result, the user can receive potential variations of the total humus
content in the soil for various volumes of organic fertilizer application (biohumus) siderates.
It will be possible to develop effective ways to increase soil fertility and lessen the influence of
harmful anthropogenic elements on the quality parameters of agricultural land with more research into
the regulatory effects of a balanced natural economic system.
Acknowledgements
This research work contains the results carried out within the project “Information-analytical
system of organic farming and ensuring environmental sustainability of soils” (project number
0120U000235) and funded by the national budget of Ukraine. Thanks to the brave Ukrainian Air
Forces this research has become possible.
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