=Paper=
{{Paper
|id=Vol-3930/paper12
|storemode=property
|title=The impact of data, information and knowledge from precision agriculture on the economy and business management
|pdfUrl=https://ceur-ws.org/Vol-3930/paper12.pdf
|volume=Vol-3930
|authors=Edita Šilerová,Jiří Vaněk,Lukáš Poláček
|dblpUrl=https://dblp.org/rec/conf/haicta/SilerovaVP24
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==The impact of data, information and knowledge from precision agriculture on the economy and business management==
https://ceur-ws.org/Vol-3930/paper12.pdf
The impact of data, information and knowledge from
precision agriculture on the economy and business
management⋆
Edita Šilerová1,†, Jiří Vaněk1,† and Lukáš Poláček1, ∗,†
1
Czech University of Live Sciences, Kamýcká 129, Prague, 165 21, Czech Republic
Abstract
The principles of precision agriculture are gradually becoming a trend in the entire agricultural sector –
crop production, animal production, the use of technology, but it is necessary to incorporate the principles
into the economy and management of agricultural enterprises. Precision agriculture enables efficient and
economical management in the mentioned agricultural companies. Precision agriculture is therefore
oriented towards the maximum use of the potential of soil, plants, machines, animals and, of course, also
the human factor. In order to maintain the competitiveness of enterprises, it is necessary to address the use
of data obtained from plant production, animal production and the use of technology in a complex manner
in connection with the economy and management of the agricultural enterprise. The aim of the contribution
is to propose a structure of data usage for improving the economic situation of the company and for its
management.
Keywords
Precision agriculture, economics, information, data, knowledge, management 1
1. Introduction
Precision agriculture has become a trend of the 21st century. Precision agriculture gradually
enables efficient and economical management in agricultural enterprises. The development of
precision systems is globally supported for the innovative divide in the agricultural sector. Precision
agriculture is a key part of the third wave of modern agricultural revolutions. [1]
Traditional record-sorting software is gradually being replaced by expert systems. The automation
of procedures and the robotization of activities facilitate daily decision-making and eliminate the
disadvantages resulting from the dependence of production on the human factor. A precise approach
in agricultural production also ensures the efficient use of all resources, thereby significantly
contributing to the sustainability of farming.
Precision agriculture is a management concept that relies on intensive data collection and processing
to guide targeted actions that improve the efficiency, productivity and sustainability of agricultural
operations. The rate of adoption of precision agriculture technologies on field crop farms in
developed countries was evaluated, in America it is approximately 20% higher than in Europe [4].
The possibility of using the principles of precision agriculture and their economic benefits are also
discussed by Gerhards and Sökefeld. [2] The issue of the use of data and information is also dealt
with in [8], [10], [13], [14].
The amount of data obtained with regular monitoring of individual activities in plant and animal
production, when using technology, technology, data from the economy, management is rapidly
⋆ Short Paper Proceedings, Volume I of the 11th International Conference on Information and Communication Technologies in
Agriculture, Food & Environment (HAICTA 2024), Karlovasi, Samos, Greece, 17-20 October 2024.
∗
Corresponding author.
†
These authors contributed equally.
silerova@pef.czu.cz (E. Šilerová); vanek@pef.czu.cz (J. Vaněk); polacekl@pef.czu.cz (L. Poláček)
0000-0001-7289-4961 (E. Šilerová); 0000-0002-4573-5348 (J. Vaněk); 0000-0003-2648-5790 (L. Poláček)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
ceur-ws.org 71
ISSN 1613-0073
Proceedings
increasing and it is necessary to work with them further and use them to increase the effective
processing of individual resources. The data obtained on the basis of the activities of the principles
of precision agriculture will significantly affect the competitiveness of the company. It is very
important to address security and the method of data processing, which is also addressed by Benda
et al. [12]
Sgroi carried out research activities on vineyards to prove the economic viability of carrying out
mechanical harvesting using the principles of precision agriculture. [3] If a farmer concentrates a
large amount of data and information about the entire agricultural production, he is not yet
practicing precision farming. They must be able to continue to work with this amount of information,
which is stored for the entire monitored period. The stored data must be given meaning, the data
must be converted into a specific operational solution. Nowadays, only those who cannot only
produce economically, but also sell very efficiently are successful. It is therefore important to work
with all the data created in the agricultural enterprise. For this, it is possible to use the right and
high-quality software, which will create conditions for, among other things, monitoring of financial
flows in the company, processing of economic evaluations, comparing product prices. The use of
well-processed company data has a high influence on quality management decisions. Currently, the
principle of using precision agriculture plays an important role in agricultural enterprises, which
leads to a reduction in costs, and thus the possibility of increasing profit and the quality of work with
data, which must be monitored in agricultural enterprises. The issues of company management,
economic management and the use of data and information to increase competitiveness are
addressed in publications [7], [9], [11].
2. Materials and Methods
Objective: the objective of the contribution is to propose a data model usable for precision
agriculture in the field of economics and management based on the analysis carried out in
agricultural enterprises. Farmers need to know whether management methods have been successful
and how to proceed next year to evaluate the year's results and for further planning. The main goal
is to propose the integration of the obtained data from all parts of the agricultural enterprise and the
possibility of using them for the assessment of reality and other predictions.
Methodology: The article was prepared based on scientific methods - using holistic methodology,
analysis, synthesis, induction and deduction. The theoretical part was prepared based on the study
of secondary literary sources, the study of scientific and professional literature. The authors will use
their long-term knowledge and experience and cooperation with practice to process the contribution.
Based on investigations carried out in selected agricultural enterprises, a methodology for the
usability of data warehouses for use in business management will be proposed. Farmers will be able
to use data to create simulations, planning, predictions and farm development.
3. Results and Discussion
However, the economic benefit from precision agriculture is still not well known. The positive
effects of precision agriculture can be caused by precisely specifying the costs of the entire
production process. Sgroi [3] deals with the positive benefits in his research, which deals with the
economic efficiency of using the principles of precision agriculture when harvesting wine grapes.
Figure 1 shows that precision agriculture requires accurate information, highly skilled human
capital and local application – these are factors that will create ideal resources for further processing
and evaluation of economic efficiency. This means guaranteeing that the amount of input used
exactly matches the cost incurred.
72
Precision farming data of the
given activity
information human capital application - software
Figure 1: Use of data from precision agriculture
The principles of precision agriculture are already very well developed for the use of the potential
of individual plots of land. The obtained data, which are stored in data warehouses, are the source of
further qualitative shifts in the use of land - it is possible to use this data directly in the design of a
solution to the sowing procedure, to find out how the use of the principle of precision agriculture
has affected the entire efficiency of the enterprise. Cultivation interventions should be converted
into graphic form for a better comparison and aligned with the proposed cultivation measures. The
situation of use in the Czech Republic is mainly influenced by the amount of expenses associated
with the acquisition of technologies necessary to introduce the principles of precision agriculture.
Precision agriculture is a management concept that relies on intensive data collection and processing
to guide targeted actions that improve the efficiency, productivity and sustainability of agricultural
operations. [3] Agriculture and food production have entered an era of digitally supported processes
where data can be generated during various agricultural activities. [6] Koliapka solves the problem
of the predictive problem of precision agriculture, which is important for precision agriculture. [5]
Based on the investigations carried out (September, October, November 2023) in agricultural
enterprises implementing the principles of precision agriculture, the following results can be stated.
The investigation was carried out in 76 agricultural enterprises, the method of direct questioning
was chosen.
Table 1
Use of data and information
Unit Yes No
Use for plant production 48% 52%
Use for livestock production 36% 64%
Use for economy 12% 88%
Use for management 9% 91%
Respondents who answered the question Use for business management positively, i.e. that they
use the data for other activities, they use it precisely to implement the principles of precision
agriculture and work with the data to create model situations. Very often, they only use data stored
in individual databases for this, and they process the data stored in this way manually on paper or
in Excel tables.
Unfortunately, companies do not have the software that would allow them to use the data. Nor
has an integrated data structure been created, which would have to be used and further worked with.
In many cases, they use the capabilities of an available spreadsheet (Excel) and often acquire data
again, they do not have the opportunity to use saved data.
Current information and communication technologies make it possible to process large volumes
of data. Companies often have atomized databases and connecting them is difficult and often
impractical. Especially in agricultural enterprises, there are applications that are often used by only
one worker, and it is he who works with the data of the given application, and it is not possible to
perform analyzes that use all the data in the company. It is necessary to design integrated databases
and then be able to work with this data within the entire company. Appropriate data sharing leads
73
to a qualitatively higher use of all resources, the result is a reduction in costs, an increase in yields
and, in the case of precision agriculture, also an improvement in the quality of the environment.
Figure No. 2 shows a proposal for an integrated database that would make it possible to use all
the data generated in the agricultural enterprise. Individual plots, crops grown on the given plots
will be compared. Comparisons will be possible according to individual types of machines, workers
performing the given operations, costs for the given plot of land, for cultivated plants and realized
prices of cultivated crops. Data from individual processes taking place in the company are stored in
a unified database or individual databases connected to each other. It will be possible to further use
the stored data through the corresponding software tools. The knowledge of managers in the given
field (in our case, agriculture) and also their knowledge of working with stored data will make it
possible to create a long-term competitive advantage. You can use software that will be created
directly to work with the designed data - this option will be more financially demanding, but easier
for many users. You can use software that will be created directly to work with the designed data -
this option will be more financially demanding, but easier for many users. The user will only learn
to use these queries (functions) and create usage models according to his knowledge. The second
option is a solution with the use of software such as a database environment or a spreadsheet.
Land condi-
tion – nutrient Fertilizer
Human Resources supply, type, quantity per plot,
use modeling their price
Purchase Integrated Seeds
database applied to the
plot
Economics - Amount of
crops, land, land harvest,
modeling Sale - realized costs, revenuest
price
Figure 2: Data integration
The advantage of the created integrated database is the possibility of access, according to the
user's request and his access rights, to the necessary data for his activity. Models can be created (Fig.
3) when we make predictions in crop production - we use company data (internal) and process it
with external data (e.g. expected market prices, sales volumes, etc.) to create the best efficiency
models. In the current economic environment, an important element for increasing competitiveness
is not only to use the latest scientific knowledge, but also to gradually get involved in this activity.
74
Plant production - sowing
methods, used machines, costs, Economics - current
yields state, modeling, forecasts
Integrated
database
External data –
purchase and sale
options (fertilizers,
seeds, implementation,
production, govern-
ment) Personnel – Research, development -
performance for the possibilities of using data
given land and crop (machines, crops, land,
modelling)
Figure 3: Data usage proposal
4. Conclusions
Data and information have become one of the most valuable business resources. Their use,
importance, influence on the further development of the company is fully influenced by the ability
of managers to use all data and information (internal and external). The quality of the information
strategy is determined by the team's ability to define information needs. When creating a database
that will be used by individual modules of the information system, its individual elements must be
clearly defined. When creating a database, the team must include a representative of each company
department in order to create a high-quality database that will become the basic starting point for
the creation of reports for further decision-making. Agriculture is becoming a knowledge industry
where what employees will know (what data and information they will get) is a key factor in
profitability.
An important element is the involvement of precision agriculture tools in the entire business
chain of production - sales - employees - economy - management. Precision agriculture will fully
support business development if all parts of the business are connected, and this is only possible if
we model stored data from all ongoing business activities.
Acknowledgements
The results and knowledge included herein have been obtained owing to support from the
following institutional grant: Internal grant agency of the Faculty of Economics and Management,
Czech University of Life Sciences Prague, grant no. 2022B0006 – “Life Sciences 4.0. Plus”.
Declaration on Generative AI
The author(s) have not employed any Generative AI tools.
References
[1] Digital agriculture: Helping to feed a growing world". 15 April 2024. Archived from the original
on 15 October 2018. Retrieved 3 April 2018
[2] R. Gerhards, M. Sökefeld, Precision farming in weed control -: system components and economic
benefits. Precision Agriculture, 4th European Conference on Precision Agriculture, pp. 229 –
234, 2003, ISBN 90-76998-21-3
75
[3] F. Sgroi: Precision agriculture and competitive advantage: Economic efficiency of the
mechanized harvesting of Chardonnay and Nero d'Avola grapes. Journal information Journal of
Agriculture and Food Research. 2023, vol. 14. DOI 10.1016/j.jafr.2023.100774
[4] B. Nowak:Precision Agriculture: Where do We Stand? A Review of the Adoption of Precision
Agriculture Technologies on Field Crops Farms in Developed Countries. Agricultural Research,
Vol. 10, Iss. 4, pp. 515-522, DOI 10.1007/s40003-021-00539-x
[5] V. R. R. Kolipaka: Predictive analytics using cross media features in precision farming.
IntternationalJoSpeech Technology, 2020. Vol. 23, Iss. 1, pp. 57-69, DOI 10.1007/s10772-020-
09669-z
[6] M. Medici, M. Mattetti, M. Canavari: A conceptual framework for telemetry data use in
agriculture. Precision Agriculture’21, 2021.Pp. 935 – 940, DOI 10.3920/978-90-8686-916-9_112
[7] T. E. Fiez, C. Baird, W.L. Pan. "Assessment of Spatially Variable Nitrogen Fertilizer Management
in Winter Wheat." Journal of Production Agriculture. 7(January-March 1994): 17- 18, 86- 93.
[8] T. Brukner, J. Voříšek: Outsourcing informačních systémů. Praha:Ekopress, 1998 ISBN 80-86119-
07-6
[9] J. Dohnal, J. Pour: Řízení podniku a řízení IS/IT v informační společnosti. Praha: VŠE, 1999 118
s. ISBN 80-7079-023-7
[10] P. F. Drucker: To nejdůležitější z Druckera v jednom svazku. Praha: Management Press, 2002.
ISBN 80-7261-066-X
[11] Tanure, S.; Nabinger, C.; Becker, J.L.: Bioeconomic model of decision support system for farm
management. Part I: Systemic conceptual modeling. Agricultural Systém, 115(2013), p. 104-116.
doi: 10.1016/j.agsy.2012.08.008
[12] P. Benda, M. Šmejkalová, P. Šimek: Usability Analysis of Agricultural Portal eAGRI in Terms of
the General Public, AGRIS on-line Papers in Economics and Informatics, (2016). Vol. 8, No. 4,
pp. 15-23. ISSN 1804-1930. DOI 10.7160/aol.2016.080402.
[13] L. Pánková, R. Aulová, J. Jarolímek: Economic Aspects of Precision Agriculture Systems, AGRIS
on-line Papers in Economics and Informatics, (2020) Vol. 12, No. 3, pp. 59-67. ISSN 1804-1930.
DOI 10.7160/aol.2020.120306.
[14] R. Nelson, R. Coe, B. Haussmann: Farmer Research Networks as a Strategy for Matching Diverse
Options and Contexts in Smallholder Agriculture, EXPERIMENTAL AGRICULTURE, (2019) pp.
125 – 144, DOI: 10.1017/S0014479716000454
76