Anatolii Tryhuba
Lviv National Agrarian University, Ukraine
E-mail: atryguba55@gmail.com
Inna Tryhuba
Lviv National Agrarian University, Ukraine
E-mail: trinle@ukr.net
Larysa Mykhalchyshyna
National University of Life and Environmental Sciences
of Ukraine, Ukraine
E-mail: larysamykhalchyshyna@ukr.net
Iryna Mushenyk
State Agrarian and Engineering University in Podilya, Ukraine
E-mail: mushenik77@ukr.net
Nonna Koval
State Agrarian and Engineering University in Podilya,
Ukraine
E-mail: koval_nona89@i.ua
Yuliia Haybura
State Agrarian and Engineering University in Podilya, Ukraine
E-mail:
hayburay@gmail.com
Submission:
8/28/2021
Accept: 9/23/2021
ABSTRACT
The approach, algorithm, and intelligent system of support of decision-making of management for forecasting of time fund for the performance of the mechanized chemical protection of plants are offered. They are based on the formation of a database and knowledge of the weather from the Open Weather Map service for individual countries and their regions. They provide the formation of databases and knowledge for a given country or its region, taking into account the characteristics of natural, climatic, and industrial conditions based on computer modelling. Also, the proposed intelligent management decision support system provides a systematically accountable set of variable agrometeorological components of the
mechanized chemical plant protection system and their impact on the projected time fund of the relevant work. Based on the use of the developed intelligent system of support of acceptance of administrative decisions forecasting of time fund for the performance of the mechanized chemical protection of plants and the set natural-climatic and industrial conditions is executed. The climatically admissible time fund model for mechanized chemical protection of plants during the day for May, which is described by Weibull distribution, is substantiated. The obtained research results can be used by managers of agricultural enterprises during the management processes of forecasting the time fund for the implementation of mechanized chemical plant protection. The developed intelligent decision support system provides further research on forecasting the time fund for the implementation of mechanized chemical plant protection and substantiation of its models for different countries and their regions.
Keywords: forecasting, time fund, agrometeorological conditions, chemical protection, plants, intelligent system, management decisions.
1.
INTRODUCTION
Agricultural enterprises engaged in crop production
suffer annual losses and lose significant crop yields from weeds, pests, and
diseases. According to the FAO (Food and Agriculture Organization), more than
40% of the world's crop is lost each year due to pests, including about 37%
before harvest and 9% during storage. These losses from crop losses are
estimated at $ 30 billion. At the same time, due to diseases of agricultural
plants, the losses amount to $ 25 billion (Tryhuba et al., 2021a; Tryhuba et
al., 2019a). To prevent and prevent crop losses from pests perform mechanized
chemical plant protection. At the same time, the content and time of
performance of works on mechanized chemical protection of plants are planned.
Qualitative planning of these processes can be performed
only with a known time fund for the implementation of mechanized chemical plant
protection (Tryhuba et al., 2021a; Tryhuba et al., 2019b). Forecasting the time
fund for the implementation of mechanized chemical plant protection is a
complex management task. This is due to the influence of many variables of the
agrometeorological component on the performance of mechanized chemical
protection of plants, which leads to time-consuming calculations based on the
theory of probability and mathematical statistics (Tryhuba et al., 2021b;
Ratushny et al., 2019). The above indicates a need to substantiate the
peculiarities of forecasting the time fund for mechanized chemical plant
protection, as well as due to the time-consuming calculations of application
software based on computer simulation of agrometeorological component
mechanized chemical plant protection.
There is a need to develop an intelligent system to support management
decisions. The main requirements for users of this system include: reliability,
clear user interface, ensuring high-quality forecasting of the time for
mechanized chemical protection of plants, taking into account the climatic and
production conditions of a particular region.
2.
LITERATURE REVIEW
Many works are devoted to the solution of problems of
forecasting of time fund for the performance of works in various applied spheres
taking into account their features (Tryhuba et al., 2021c; Hulida et al., 2019;
Ratushny et al., 2018; Pavlikha et al., 2019; Bashynsky, 2019). They are based
on the developed mathematical models and methods, which partially idealize and
take into account the peculiarities of the production conditions of the subject
area.
Some of the scientific publications (Fraisse et al.,
2006; Roy et al., 2019; Boyarchuk et al., 2020; Syrotiuk et al., 2020)
substantiate the need to develop universal tools for forecasting the time for
work without taking into account the specifics of applications spheres. The
authors of these scientific works propose to use models and methods that are
based on traditional forecasting approaches that do not fully take into account
the features of the agrometeorological component of the system of mechanized
chemical plant protection.
Of particular note are existing publications (Tryhuba et
al., 2021c; Bashynsky, 2019; Tryhuba et al., 2020a; Tryhuba et al., 2020b;
Boyarchuk et al., 2019a; Boyarchuk et al., 2019b), which relate to forecasting
in agricultural production. Some of them relate to crop production and take
into account the specifics of this industry. However, it is impossible to use
them in full to forecast the time fund for the implementation of mechanized
chemical plant protection, as they do not take into account the features of the
agrometeorological component of the system of mechanized chemical plant
protection.
There are several scientific papers (Boyarchuk et al., 2019a;
Ljaskovska et al., 2018; Boychenko et al., 2007), in which their authors take
into account the peculiarities of the agrometeorological component for
different systems of agricultural production. They are used in intelligent
management decision support systems. However, as for taking into account the
peculiarities of the agrometeorological component in intelligent decision
support systems, they are absent for mechanized chemical plant protection. In
particular, the existing intelligent decision support systems are designed for
strategic and tactical planning of work (Bashynsky et al., 2019; Serrano et
al., 2004; Sokulskyi et al., 2020).
The task of operational forecasting of the time fund for the
implementation of mechanized chemical plant protection requires consideration
of natural, climatic, and production conditions of individual countries and
their regions and appropriate research to ensure an adequate database and
knowledge underlying the intelligent decision support system for fund
forecasting time to perform mechanized chemical protection of plants under
given conditions.
Thus, the existing approaches and intelligent decision
support systems for planning in crop production do not fully take into account
the changing climatic and production conditions of individual countries and
their regions, which determine the time to implement mechanized chemical plant
protection. This is one of the main reasons for making incorrect management
decisions during the operational planning of mechanized chemical plant
protection, as well as losses of cultivated agricultural products due to
untimely reduction of pests and plant diseases.
Currently, there is a scientific and applied problem to
substantiate the approach to forecasting the time fund for mechanized chemical
plant protection, as well as due to the need for time-consuming calculations,
development of application software based on computer modelling of
agrometeorological component of mechanized chemical plant protection countries
and their regions. The article confirming its scientific and practical value is
devoted to the solution of this scientific and applied problem.
The aim of the work is to
substantiate the approach to forecasting the time fund for mechanized chemical
plant protection and on its basis to develop an algorithm and intelligent
management support system based on computer simulation and provide high-quality
forecasting of time fund for mechanized chemical plant protection. taking into
account the peculiarities of the agrometeorological component of individual
countries and their regions.
To achieve this goal should solve the following tasks:
· to
propose an approach, algorithm, and intelligent support system for making
management decisions to forecast the time fund for the implementation of
mechanized chemical plant protection;
· on
the basis of using the developed intelligent support system for making
management decisions to forecast the time fund for mechanized chemical plant
protection and given climatic and production conditions to justify the model of
climatically acceptable time fund for mechanized chemical plant protection
during the day.
3.
RESULTS AND DISCUSSIONS
During the season of action of harmful objects on crops
of separate crops, there are intervals of time during which it is possible or
impossible to carry out mechanized chemical protection of plants. In view of
this, the naturally determined time fund for the implementation of mechanized
chemical protection of plants is the time (in hours) during which you can
perform the technological operation of spraying crops.
The formation of a naturally acceptable time fund for the
implementation of mechanized chemical plant protection is based on a number of
climatic factors that reflect the meteorological conditions of a particular
region:
, (1)
where О – the presence
of precipitation, R – the presence of dew; V – the wind speed; Т – the
air temperature; І – the time of day (light or dark).
Equation (1) is presented in an implicit form, since
its disclosure is possible only on the basis of computer modeling of the
implementation of mechanized chemical plant protection, taking into account the
climatic and production conditions of a particular region. At the same time,
the features of the implementation of mechanized chemical plant protection in
certain regions are being revealed.
A feature of mechanized chemical protection of plants by
spraying is their high sensitivity to weather conditions and the state of the
surface layer of the atmosphere (Bazzaz et al., 1996; Lobell et al., 2007).
Thus, rainy weather, fog, rising heat fluxes, wind are among the unfavorable
conditions that can completely neutralize the efficiency of cultivation and
cause negative environmental consequences. Adverse weather conditions
significantly affect the rate of pesticide use and environmental friendliness
of chemical plant protection processes.
When the wind speed is more than 4 m/s, the sprayed
mixture of boom sprayers will wear out of the field, polluting the environment.
At air temperatures above +25°C, the droplets of the working liquid evaporate
quickly. With excessive humidity and precipitation, the working fluid is washed
away from the plants, reducing the efficiency of cultivation and contaminating
the soil.
It is known that in some countries there is a
continuously changing state of the atmosphere, which is determined by the
stochastic sequence of alternation of naturally acceptable and unacceptable
time intervals for mechanized chemical plant protection in terms of a single
calendar day and a specific
calendar period (plant development phase) (Tryhuba et al., 2021a; Islam et al.,
2017).
Determination of the natural allowable time fund for
mechanized chemical protection of plants is performed depending
on the weather conditions and it can be graphically displayed on the calendar
time axis of the time of onset and duration of individual agrometeorological
factors both singly and in combination.
Obviously, the main role in the formation of a
naturally acceptable time fund for mechanized chemical plant protection is played by rainfall
(short-term or long-term and its intensity), which determines the waiting time after its completion
(time for drying soil and plants).
Figure 1: Dependence
of the probability of occurrence of certain agrometeorological factors during
the mechanized chemical protection from the calendar term (during April-August)
for the conditions of the Western Forest-Steppe of Ukraine: 1 – the presence of
precipitation; 2 – excessive wind speed; 3 – above-average daily air
temperature; 4 – the presence of dew
The effect of agrometeorological factors during the
period of cultivation of crops (April-August) characterizes the probability
(Boyarchuk et al., 2019):
(2)
де – the total number of
cases studied; – - the number of
cases corresponding to a particular event.
According to the statistics of the reporting period
(April-August (Tryhuba et al., 2021a)) determined the number of events that met
a certain condition (occurrence of excessive values of limiting factors) in a
single calendar day to the total number of studied days. In nature, there are
certain patterns, for example, if the dew falls, there is no rain, and vice
versa, the time with excessive air temperature is monitored only in the middle
of the day (when the sun is at its highest point relative to the horizon).
As the probability of the appearance of the maximum
average daily air temperature due to the increase in the height of the sun
above the horizon increases, the probability of occurrence of excessive
permissible values of wind gusts decreases, although the probability of dew
increases. On the other hand, it can be argued that precipitation slightly
depends on other agrometeorological factors (average daily air temperature,
dew, excessive wind gusts), as evidenced by the correlation coefficient (Table 1).
Table 1: Equations and
correlation coefficients of the probability of occurrence of individual
agrometeorological factors during the implementation of mechanized chemical
protection of plants from the calendar term (April-August)
Indicator |
Equation |
Correlation
coefficient |
Wind |
|
0,98 |
Dew |
|
-0,88 |
Average
daily air temperature |
|
-0,93 |
Precipitation |
|
-0,5 |
Thus,
the simultaneous consideration of many agrometeorological factors is quite
difficult. However, without it, it is impossible to objectively justify an
effective set of machines for chemical plant protection by spraying. The
obtained regularities are the first step in the way of modelling the action of
these factors and probabilistic estimation of the naturally allowed time fund
for spraying plants.
The established patterns of occurrence and course in a
time of certain agrometeorological factors are the first step towards the
reflection of naturally determined time funds for the implementation of
mechanized chemical protection of plants by spraying. It is hypothesized that
such agrometeorological factors as the average daily air temperature
(correlation coefficient – 0.93), excessive allowable wind speed (correlation
coefficient – 0.98), and dew (correlation coefficient – 0.88) are dependent on
the calendar time. Taking into account the peculiarities of agrometeorological
conditions for a given region in the simulation model will allow us to
objectively justify the need for technical means for the chemical protection of
plants by spraying.
To forecast the time fund for the implementation of
mechanized chemical plant protection, during which favorable weather conditions
for the implementation of mechanized chemical plant protection by spraying
perform the collection of weather statistics from the OpenWeatherMap service
for individual countries or their regions.
Based on the above, the following conditions were
considered favorable for the technological processes of chemical plant
protection: air temperature + 5°.. + 25°C; no precipitation and fog; wind speed
0 ... 4 m/s; absence of thermal ascending currents in the surface layer of the
atmosphere.
The block diagram and algorithm for forecasting the
climatically acceptable time fund for mechanized chemical protection of plants
by spraying on a single day were developed on the basis of sound methods and
models of characteristics of climatic and industrial conditions (Tryhuba et
al., 2021a).
The block diagram consists of 19 blocks (Figure 2).
The first block is designed to store in the PC`s memory
the initial data: the length of daylight; the presence of dew; air temperature;
wind speed and precipitation.
Blocks 2-9 are designed to form agrometeorological
numerical series and check the compliance of their values.
Figure 2: Block diagram of
the algorithm of computer modelling of agrometeorological component and forecasting
of climatically admissible fund of time for performance of the mechanized
chemical protection of plants by spraying in a separate day
Blocks 10-13 are designed to determine the climatically
acceptable time fund for the implementation of mechanized chemical protection
of plants by spraying on a particular day, respectively, the length of
daylight; the presence of dew; air temperature; wind speed, and precipitation.
Blocks 14-17 are designed to verify compliance with the
values of the climatically acceptable time fund for the
implementation of mechanized chemical protection of plants by spraying on a
single day.
Block 18 is designed to check the condition of
completeness of the implemented implementations and determine the climatically
acceptable time fund for the implementation of mechanized chemical protection
of plants by spraying on a single day.
Block 19 is designed to display the results of
calculations.
Based on the disclosure of the content of the blocks
depicted in the block diagram, an algorithm for computer modelling of
agrometeorological component and forecasting the climatic time fund for
mechanized chemical protection of plants by spraying on a single day and an
intelligent management decision support system for forecasting the time fund
mechanized chemical plant protection in Python 3.9, the working window of which
is shown in Figure 3.
Figure
3: The working window of the intelligent system of support of decision-making
of management during forecasting of time fund for the performance of the
mechanized chemical protection of plants in a separate day
The probability of favorable conditions for chemical
plant protection is greatest in the morning and evening. In view of this, it is
advisable to divide the work into half shifts (3 hours in the morning and 3
hours in the evening). The half-shift duration is set in hours (the default
half-shift duration is 3 hours).
Developed intelligent management decision support system
for forecasting the time fund for mechanized chemical plant protection performs
the necessary calculations and provides determination and visualization of
climatically acceptable time fund for mechanized chemical plant protection by
spraying on a single day for a given country and its region. The proposed
intelligent management decision support system was tested for adequacy
according to the Mann-Whitney test for the conditions of the Lviv United
Territorial Community (Ukraine). The deviation of the values of the projected
time fund for the implementation of mechanized chemical protection of plants
from the actual values did not exceed 4%, which confirms the adequacy.
Based on the use of the developed intelligent management
decision support system for forecasting the time fund, computer modeling of the
agrometeorological component for different days of the mechanized chemical
plant protection season for the conditions of the Western Forest-Steppe of
Ukraine was carried out.
The conducted researches provided construction of the
histogram and a theoretical curve of distribution of the climatically
admissible fund of time for the mechanized chemical protection of plants during
days for May.
Statistical processing of the obtained data on the
climatically acceptable time fund for mechanized chemical protection of plants
during the day allowed to determine
the numerical characteristics, as well as to substantiate the model (Fig. 3),
which is described by the Weibull distribution with differential function
. (3)
Figure 4: Model of
climatically acceptable time fund for mechanized chemical protection of plants
during the day in May
The main statistical characteristics of the distribution
of climatically acceptable time fund for mechanized chemical protection of plants
during the day in May are as follows: estimation of mathematical expectation –
8.9 hours; dispersion – 11.0 hours; estimation of the standard deviation – 3.33
hours.
The
test for the adequacy of the theoretical distribution of the climatically
permissible fund of time for mechanized chemical plant protection with
empirical data was carried out according to the -Pearson
criterion.
A well-grounded approach to forecasting the time fund for
mechanized chemical plant protection and based on it developed algorithm and
intelligent management decision support system provide quality forecasting of
time fund for mechanized chemical plant protection taking into account the
agrometeorological component of individual countries and their regions.
4.
CONCLUSIONS
The proposed approach, algorithm, and intelligent
management decision support system for forecasting the time fund for mechanized
chemical plant protection are based on the formation of a database and
knowledge of weather from the OpenWeatherMap service for individual countries
and their regions. The main feature of the proposed approach is that the
formation of databases and knowledge is performed for a given country or
region, taking into account the characteristics of climatic and industrial
conditions based on computer modelling, which provides systematically
considered many variable agrometeorological components of mechanized chemical plant
protection and their impact on the projected time fund of the relevant works.
This fully takes into account the specifics of the subject area, provides
quality database and knowledge, as well as the creation of an intelligent
system that provides rapid and high-quality management decisions on forecasting
the time to perform mechanized chemical plant protection.
On the basis of the use of the developed intelligent
system of support of acceptance of administrative decisions forecasting of time
fund for the performance of the mechanized chemical protection of plants and
the set natural-climatic and industrial conditions is executed. This provided
substantiation of the model of climatically acceptable time fund for mechanized
chemical protection of plants during the day in May, which is described by the
Weibull distribution with the main statistical characteristics: estimation of
mathematical expectation – 8.9 hours; dispersion – 11.0 hours; estimation of
the standard deviation – 3.33 hours. The obtained research results can be used
by managers of agricultural enterprises during the management processes of
forecasting the time fund for the implementation of mechanized chemical plant
protection.
REFERENCES
Bashynsky, O. (2019).
Coordination of dairy workshops projects on the community territory and their
project environment. In: 14-th
International Scientific and Technical Conference on Computer Sciences and
Information Technologies. Lviv
Polytechnic National University, 17–20 September.
Lviv, 51–54.
Bazzaz, F., & Sombroek, W. (1996). Global climate change and
agricultural production: direct and indirect effects of changing hydrological
soil and plant physiological processes. FAO,
Rome, Italy. Available at:
http://www.fao.org/docrep/w5183e/w5183e00.htm#Contents.
Boyarchuk, V.,
Boyarchuk, V. & Ftoma, O. (2019). Evaluation of risk value of
investors of projects for the creation of crop protection of family dairy
farms. Acta Universitatis
Agriculturae et Silviculturae Mendelianae Brunensis, 67(5), 1357–1367.
Boyarchuk, V. & Ftoma, O. (2019). Forecasting of a lifecycle of the projects of production of biofuel raw
materials with consideration of risks. International
Conference on Advanced Trends in Information Theory (ATIT), pp. 420-425.
Boyarchuk, V., Ftoma, O., Francik, S., &
Rudynets, M. (2020). Method and software of planning of the substantial
risks in the projects of production of raw material for biofuel. In: International Workshop IT Project Management. Ukrainian
Project Management Association “UKRNET” & Lviv Polytechnic National
University, 18–20 February. Slavsko,
pp. 116–129.
Boychenko, S., & Voloshchuk, V. (2007). The stochastic
semi-empirical model of space-temporal transformation of the modern climate of
Ukraine. National Academy of Science of
Ukraine, 1,105-109.
Fraisse, C. W., Breuer, N. E., Zierden, D., Bellow, J. G., Paz, J., Cabrera, V. E., …
O'brien, J. J. (2006). AgClimate: a climate forecast information
system for agricultural risk management in the southeastern USA. Computers and Electronics in Agriculture,
53(1), 13–27.
Hulida, E., Pasnak I., & Koval, O. (2019). Determination of the Critical Time of Fire in the Building and Ensure
Successful Evacuation of People. Periodica
Polytechnica Civil Engineering, 63(1), 308-316.
Islam, S., & Mandal, W. A. (2017). A fuzzy inventory model (EOQ
model) with unit production cost, time depended holding cost, without shortages
under a space constraint: a fuzzy parametric geometric programming (FPGP)
approach. Independent Journal of
Management & Production, 8(2), 299-318. DOI:
10.14807/ijmp.v8i2.535.
Ljaskovska, S., Martyn, Y., Malets, I., &
Prydatko, O. (2018). Information technology of process modeling in the
multiparameter systems. In: II
International Conference on Data Stream Mining and Processing. Lviv
Polytechnic National University, 21–25 August.
Lviv, pp. 177–182.
Lobell, D., & Field, C. (2007). Global scale climate–crop yield
relationships and the impacts of recent warming. Environ. Res. Lett., 2, 1-7.
Nuzhna O., Tluchkevych N., Semenyshena N., Nahirska K., & Sadovska I. (2019). Making managerial decisions in the
agrarian management through the use of ABC-Analysis tool. Independent Journal of Management & Production, 10(7), 798-816.
DOI: http://dx.doi.org/10.14807/ijmp.v10i7.901.
Pavlikha, N., Rudynets, M., Grabovets, V., Skalyga, M., Tsymbaliuk, I., Khomiuk, N., & Fedorchuk-Moroz, V. (2019). Studying the influence of production
conditions on the content of operations in logistic systems of milk collection.
Eastern-European Journal of Enterprise
Technologies: Control processes, 99(3/3), 50–63.
Ratushny, R., Bashynsky, O., & Ptashnyk, V. (2019).
Development and usage of a computer model of evaluating the scenarios of
projects for the creation of firefighting systems of rural communities. In: XI-th International Scientific and
Practical Conference on Electronics and Information Technologies. Ivan Franko National University
of Lviv, 16–18 September. Lviv, 34–39.
Ratushny, R., Bashynsky, O. & Shcherbachenko, O. (2018).
Identification of firefighting system configuration of rural settlements Fire
and Environmental Safety Engineering. MATEC
Web Conf (FESE 2018), 247. DOI: https://doi.org/10.1051/matecconf/201824700035.
Ratushnyi, R., Khmel, P., Martyn, E., &
Prydatko, O. (2019). Substantiating the effectiveness of projects for the
construction of dual systems of fire suppression. Eastern-European Journal of Enterprise Technologies: Control processes,
100(4/3), 46–53.
Roy, P. C., Guber, A., Abouali, M., Pouyan
Nejadhashemi, A., Deb, K., & Smucker, A. (2019). Crop yield
simulation optimization using precision irrigation and subsurface water
retention technology. Environmental Modelling & Software, 119, 433–444.
Serrano,
I. V., Gonzalez–Hidalgo, S. M., De Luis, J. C., & Raventos, M. J. (2004).
Drought patterns in the Mediterranean area:
the Valencia region (eastern Spain). Climate
Research, 26, 5-15.
Sokulskyi, O., Hilevska, K., Chumakevych, V., Ptashnyk,
V., & Sachenko, A. (2020). The Internet of Things Solutions in the
Investigation of Urban Passenger Traffic and Passenger Service Quality. IEEE European Technology and Engineering
Management Summit (E-TEMS). DOI: 10.1109/E-TEMS46250.2020.9111658.
Syrotiuk, V., Syrotiuk, S., Ptashnyk, V., Baranovych, S., Gielzecki, J., & Jakubowski, T. (2020). A hybrid system with intelligent control for the processes of resource
and energy supply of a greenhouse complex with application of energy renewable
sources. Przegląd elektrotechniczny,
96(7), 149-152.
Тryhuba, A., Bashynskyi, O., Medvediev, Y., Slobodian, S., & Skorobogatov, D. (2019). Justification of models of changing project environment for harvesting
grain, oilseed and legume crops. Independent Journal of Management & Production, 10(7), 658-672.
Tryhuba, A., Boyarchuk, V., Tryhuba, I., Ftoma, O.,
Padyuka, R., & Rudynets, M. (2019). Forecasting the Risk of the Resource
Demand for Dairy Farms Basing on Machine Learning. Proceedings of the 2nd International Workshop on Modern Machine
Learning Technologies and Data Science (MoMLeT+DS 2020), I, 327-340.
Тryhuba, A., Hridin, O., Slavina, N., Mushenyk, I., & Dobrovolska, E. (2020). Managerial
decisions in logistic systems of milk provision on variable production
conditions. Independent Journal
of Management & Production, 11(8), 783-800.
Тryhuba, A., Hutsol, T., Glowacki, S., Tryhuba, I., Tabor, S., Kwaśniewski, D., Sorokin, D., & Yermakov, S. (2021). Forecasting Quantitative Risk Indicators of Investors in Projects of
Biohydrogen Production from Agricultural Raw Materials. Processes, 9(2), 258. DOI: https://doi.org/10.3390/pr9020258.
Тryhuba, A., Ivanyshyn, V., Chaban, V., Mushenyk, I., &
Zharikova, O. (2021). Influence of agrometeorological component of the project
environment on the duration of works in chemical protection projects of
agricultural crops. Independent Journal of Management & Production (Special Edition
ISE, S&P), 12(3), 138-149. DOI: https://doi.org/10.14807/ijmp.v12i3.1531.
Тryhuba, A., Тryhuba, І., Mushenyk, І., Pashсhenko, О., & Likhter, М. (2020). Computer model of resource
demand planning for dairy farms. Independent Journal
of Management &
Production, 11(9), 658-672. DOI: https://doi.org/10.14807/ijmp.v11i9.1410.