Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)

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Plant Growth Prediction Model of Red Chili (Capsicum annuum L.) by Different Manipulation Environment

Authors
GMD Putra1, 2, L Sutiarso1, *, AP Nugroho1, Ngadisih1, MSI Chaer1
1Department of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia
2Department of Agricultural Engineering, Faculty of Food and Agroindustrial Technology, Universitas Mataram, Mataram, Indonesia
*Corresponding author. Email: lilik-soetiarso@ugm.ac.id
Corresponding Author
L Sutiarso
Available Online 28 December 2022.
DOI
10.2991/978-94-6463-086-2_4How to use a DOI?
Keywords
ANN; model; red chili; regression
Abstract

Several factors influence plant growth, including sun intensity, nutrient content, soil moisture, temperature, genes, and hormones. Many studies have been carried out in constructing plant growth models to simulate plant growth in different treatments. This study aims to develop a mathematical model with a linear regression approach and an artificial neural network. This research method used an experimental design using three treatments consisting of control (T1), 50% shade (T2), and 80% shade (T3). Each treatment had five replications of the chili plant. The tools and materials used were red chili (Capsicum annuum L.) seeds of 30 DAP, a greenhouse of 3 x 3 meters, a drip irrigation control system, 25 x 30 cm polybags, and fertile soil media. The results showed that linear regression models of the 1st and 2nd order could be used to predict plant growth with an average RMSE value of 1.53. In contrast, the use of artificial neural networks showed a smaller RMSE value of 0.12 which means that the artificial neural network method was better at predicting plant growth.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)
Series
Advances in Biological Sciences Research
Publication Date
28 December 2022
ISBN
978-94-6463-086-2
ISSN
2468-5747
DOI
10.2991/978-94-6463-086-2_4How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - GMD Putra
AU  - L Sutiarso
AU  - AP Nugroho
AU  - Ngadisih
AU  - MSI Chaer
PY  - 2022
DA  - 2022/12/28
TI  - Plant Growth Prediction Model of Red Chili (Capsicum annuum L.) by Different Manipulation Environment
BT  - Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)
PB  - Atlantis Press
SP  - 19
EP  - 27
SN  - 2468-5747
UR  - https://doi.org/10.2991/978-94-6463-086-2_4
DO  - 10.2991/978-94-6463-086-2_4
ID  - Putra2022
ER  -