Classification of Macronutrient Deficiency in Chili Leaves using Support Vector Machine

DOI

10.2991/978-94-6463-086-2_77How to use a DOI?

Keywords

Image Processing; Machine Learning Algorithm; Nutrient Deficiency; Color Feature Extraction; Classifier

Abstract

Chili is a horticultural crop that has high economic value in Indonesia. The productivity level of chili in the country is not proportional to the level of consumption, one of the causes is malnutrition. Each plant requires different amounts of macronutrients and micronutrients to support plant growth and development. Chili plants that lack or excess macronutrients show different visual symptoms. Digital Image Processing is a non-destructive method that is useful for determining plant health conditions based on visual symptoms of chili leaves. The combination of digital image processing and learning methods such as the Support Vector Machine (SVM) helps classify the types of macronutrient deficiencies in order to obtain a nutrient solution. In this study, there are several stages in determining macronutrient deficiencies in chili plants, namely image acquisition, pre-processing, feature extraction, to classification using SVM with several kernels. Based on the experimental results in this study, the SVM method can help modern farmers to determine the health condition of plants non-destructively with 97.76% accuracy using a Polynomial kernel. Applying this system to an intelligent farming system is expected to support the realization of precision agriculture in Indonesia.

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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TY  - CONF
AU  - Deffa Rahadiyan
AU  - Sri Hartati
AU  - Wahyono
AU  - Andri Prima Nugroho
AU  - Lilik Sutiarso
PY  - 2022
DA  - 2022/12/28
TI  - Classification of Macronutrient Deficiency in Chili Leaves using Support Vector Machine
BT  - Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)
PB  - Atlantis Press
SP  - 564
EP  - 575
SN  - 2468-5747
UR  - https://doi.org/10.2991/978-94-6463-086-2_77
DO  - 10.2991/978-94-6463-086-2_77
ID  - Rahadiyan2022
ER  -