Elements of the Decision Support System in the Agricultural Production Processes

Riksen, Vera; Maksimovich, Kirill; Kizimova, Tatyana; Galimov, R. R.; Fedorov, Dmitry

doi:10.1007/978-981-19-7780-0_34

Cited by 2 publications

(1 citation statement)

References 6 publications

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“…The set of logical rules allows evaluating stable or most productive crop rotation types under different moisture variations (Figure 4). This model will enable more efficient planning of technological resources according to the prevailing moisture conditions during various vegetation periods and can become an integral part of decision support systems [31][32][33].…”

Section: Fig 2 Graphical Analysis Of Crop Rotation Productivity Varia...mentioning

confidence: 99%

Application of machine learning methods for crop rotation selection in organic farming system

Maksimovich,

Kalichkin,

Fedorov

et al. 2024

E3S Web Conf.

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This study demonstrates the possibility of crop rotation selection based on the assessment of productivity and sustainability of crop production under different atmospheric moisture conditions. The study considers 8 crop rotations oriented to grain production. The data obtained in long-term field experiments in the forest-steppe of the Novosibirsk region were used. As a result of the implementation of the decision tree (CART) and the use of ensemble algorithm (Random Forest) the construction of a model characterized by a fairly high predictive ability was performed. Standardized Precipitation Index was chosen as the main predictor characterizing atmospheric moistening in different periods of vegetation. The most stable from the point of view of stability of crop yield – grain-fallow with winter rye, grain-fallow with legumes (vetch-oats), in conditions of manifestation of atmospheric drought of different severity were selected. The possibility of using machine learning methods (CART, Random Forest) as effective tools in the selection of crop rotation for sustainable grain production without the use of chemicalization in soil and climatic conditions of Siberia, as well as the assessment of possible risks in the transition of crop production to organic technologies were scientifically substantiated.

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Section: Fig 2 Graphical Analysis Of Crop Rotation Productivity Varia...mentioning

confidence: 99%

Application of machine learning methods for crop rotation selection in organic farming system

Maksimovich,

Kalichkin,

Fedorov

et al. 2024

E3S Web Conf.

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Optimizing Work Planning for Grain Crop Cultivation: Software Components

Alt,

Isakova

2023

S-h. maš. tehnol.

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The paper considers modernization of the agricultural sector with the aim of enhancing its efficiency and competitiveness through the implementation of digital technologies. Additionally, it analyzes the methods and software employed for the selection of technologies and technical tools. (Research purpose) The research aims to develop software modules for managing the production of crop products. This involves the selection of appropriate agricultural technologies and the optimal utilization of the machine and tractor fleet. The software designed is expected to take into account the farm agroclimatic and production conditions. (Materials and methods) The development of software components for a web-based software package aimed to facilitate the annual work planning in grain crop cultivation, is based on a method rooted in the evaluation of natural, climatic, and production conditions. (Results and discussion) The findings support the feasibility of developing software components for a web-based software package by selecting agricultural technologies and determining optimal utilization options for technical means. The research resulted in the development of a structural scheme for the software package designed as a web-based application, encompassing such software modules as «Selection of technologies» and «Selection of technical means». These modules share a unified interface and operate on a common database. The operation of software modules for selecting technologies was tested in the northern forest-steppe zone of the Novosibirsk region in 2022.The tests examined the cultivation technologies for wheat at a standard intensification level across four working areas with varying predecessors. (Conclusions) The developed software components will be subsequently integrated into the software package in the form of a web application. This application can serve as a support system for making informed managerial decisions in the realm of machine-based agricultural technologies. The software package facilitates the automation of technology selection, the creation of an annual work plan, and the computation of economic indicators.

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Elements of the Decision Support System in the Agricultural Production Processes

Cited by 2 publications

References 6 publications

Application of machine learning methods for crop rotation selection in organic farming system

Application of machine learning methods for crop rotation selection in organic farming system

Optimizing Work Planning for Grain Crop Cultivation: Software Components

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