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Analysis of RGB Plant Images to Identify Root Rot Disease in Korean Ginseng Plants Using Deep Learning

Authors :
Praveen Kumar Jayapal
Eunsoo Park
Mohammad Akbar Faqeerzada
Yun-Soo Kim
Hanki Kim
Insuck Baek
Moon S. Kim
Domnic Sandanam
Byoung-Kwan Cho
Source :
Applied Sciences, Vol 12, Iss 5, p 2489 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Ginseng is an important medicinal plant in Korea. The roots of the ginseng plant have medicinal properties; thus, it is very important to maintain the quality of ginseng roots. Root rot disease is a major disease that affects the quality of ginseng roots. It is important to predict this disease before it causes severe damage to the plants. Hence, there is a need for a non-destructive method to identify root rot disease in ginseng plants. In this paper, a method to identify the root rot disease by analyzing the RGB plant images using image processing and deep learning is proposed. Initially, plant segmentation is performed, and then the noise regions are removed in the plant images. These images are given as input to the proposed linear deep learning model to identify root rot disease in ginseng plants. Transfer learning models are also applied to these images. The performance of the proposed method is promising in identifying root rot disease.

Details

Language :
English
ISSN :
20763417
Volume :
12
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.8a9c0b82ab84c28a7569daf39cfe6b9
Document Type :
article
Full Text :
https://doi.org/10.3390/app12052489