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INFORMATIC SIMULATION OF PLANTS BIOLOGICAL PROCESSES

Nicolae Marian

First published: 2018-06-20https://doi.org/10.5593/sgem2018/2.1/s07.060View metrics

Abstract

Simulation of biological processes with the aid of computing techniques helps to model physiological processes, to create mathematical models with the computer support. Starting from experimental data difficult to be obtained, we can do calculation algorithms to identify the variation functions of the processes that are to be simulated, then to interpolate in order to fill them in the missing data collection. Having the variation parameters (input data): time, temperature, dry substance, a software product (output data) can be create to simulate reality, plant growth and fruit formation. You can then design a friendly, easy-to-use graphical user interface that can process the database and exploit computing facilities. Having the functions that approximate physiological processes (degree of similarity over 95% - 98%) can be used to produce predictions of growth, to anticipate results and to intervene in the biological processes depending on the environment disturbing factors. The final platform or model is based on a collection of discrete experimental data, and in the end it completes with the missing data through the numerical simulation done computerized. If applicable, the functions could be a variable or multiple variables.

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Publication details

Title
INFORMATIC SIMULATION OF PLANTS BIOLOGICAL PROCESSES
Authors
Nicolae Marian
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 18th International Multidisciplinary Scientific GeoConference SGEM2018, Informatics, Geoinformatics and Remote Sensing
Publisher
STEF92 Technology
Year
2018
Pages
477-484
SWS Citekey
Nicolae20187477484
ISSN
1314-2704
ISBN
978-619-7408-39-3
Language
en
Publication type
Conference Paper
Keywords
References4
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  2. Larionescu, D., Numerical calculation elements. Applications, Polytechnic University of Bucharest, ISBN: 973-755-025-0, 2018.

  3. Matthes, E., Python Crash Course: A Hands-On, Project-Based Introduction to Programming, ISBN-13: 978-1593276034, 2018.

  4. NICOLAE M., Doctorate Thesis, U.S.A.M.V Bucharest, 2006.

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