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Conceptual Model of Digital Nitrogen Management in Agricultural Crops.

Authors :
Kalichkin, V. K.
Maksimovich, K. Yu.
Fedorov, D. S.
Garafutdinova, L. V.
Source :
Russian Agricultural Sciences; Apr2024, Vol. 50 Issue 2, p197-206, 10p
Publication Year :
2024

Abstract

The research was aimed at developing a conceptual model of digital nitrogen management in crops. Cognitive analysis of the knowledge structure in this subject area and conceptual modeling of digital nitrogen management in agrophytocenoses using an object-oriented approach and Unified Modeling Language (UML) were used. A detailed system of diagrams was created, encompassing class, process, and interaction diagrams. The model is anchored on three abstract objects: class (seven in total), attribute (32), and interclass relationships (18), which distribute the main concepts, emphasizing the complexity and multifaceted approaches to digital nitrogen management. The central class is "Agrophytocenosis", which directly interacts with five classes and indirectly with one class. Attributes are integral to the classes and reflect their specific characteristics. To depict the interaction between the classes and their attributes, four types of relationships are employed in the model: "dependency," "association," "aggregation," and "inner class." In the process diagram of the digital nitrogen management system, two primary subsystems are highlighted: the analysis and planning subsystem and the adjustment subsystem, as well as tools and sources for data acquisition and processing. A distinctive feature of the developed conceptual model is the application of the temporality principle, integrating static and dynamic processes in the digital nitrogen management system within the agrophytocenosis. Subsystems for analysis, planning, and adjustment of emerging conditions in the management areas allow ensuring more efficient use of nitrogen fertilizers in crops. The conceptual model is aimed at developing a hardware-software complex for diagnostics of nitrogen nutrition of cultivated plants and management of fertilizer application based on modern digital monitoring and data-processing tools. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10683674
Volume :
50
Issue :
2
Database :
Complementary Index
Journal :
Russian Agricultural Sciences
Publication Type :
Academic Journal
Accession number :
178065726
Full Text :
https://doi.org/10.3103/S1068367424700071