Abstract:
In the article, the authors present the results of the development and research of methods for creating 3D models of plants grown in vitro, which provide the ability to accurately record the morphometric indicators of the growth of individual parts, organs of plants and plants as a whole, cultivated on different nutrient media. The presented methods and algorithms in a complex solve the problems arising in the process of studying plants in a test tube, related to the complexity of the plant structure, the occurrence of distortions at the borders of the test tube, its possible fogging, as well as the influence of the human factor. A bank of 792 3D models for plants of 6 species has been created, which allows conducting simulation experiments to identify cause-and-effect relationships, forecasting and gaining new knowledge. The developed methods were checked for adequacy, an example of use for a specific plant was presented. The presented methods and algorithms can become the basis for the implementation of the process of digital phenotyping of plants.
Keywords:
in vitro conditions, methods, algorithms, 3D modeling, segmentation, digital phenotyping.
Citation:
O. A. Ivashchuk, V. A. Berezhnoy, Y. N. Maslakov, V. I. Fedorov, “Creation and research of 3D models for digital plant phenotyping”, Artificial Intelligence and Decision Making, 2022, no. 4, 78–87; Scientific and Technical Information Processing, 50:5 (2023), 422–429
\Bibitem{IvaBerMas22}
\by O.~A.~Ivashchuk, V.~A.~Berezhnoy, Y.~N.~Maslakov, V.~I.~Fedorov
\paper Creation and research of 3D models for digital plant phenotyping
\jour Artificial Intelligence and Decision Making
\yr 2022
\issue 4
\pages 78--87
\mathnet{http://mi.mathnet.ru/iipr83}
\crossref{https://doi.org/10.14357/20718594220408}
\elib{https://elibrary.ru/item.asp?id=50271697}
\transl
\jour Scientific and Technical Information Processing
\yr 2023
\vol 50
\issue 5
\pages 422--429
\crossref{https://doi.org/10.3103/S0147688223050088}
Linking options:
https://www.mathnet.ru/eng/iipr83
https://www.mathnet.ru/eng/iipr/y2022/i4/p78
This publication is cited in the following 1 articles: