All Issue

2022 Vol.34, Issue 2

Review Article

Utilization of Imaging Data from Different Sources for Bacterial and Fungal Diseases Detection in Major Crops in the Digital Era: A Review
Ndosiri Josepha Ngwangum1
,
Rupesh Tayade1
,
Lay Liny1
,
Jung-Beom Yoon2
,
Yong-Suk Chung3
,
Yoonha Kim1*
1Department of Applied Biosciences, Kyungpook National University, Daegu 41566, South Korea
2Horticultural and Herbal Crop Environment Division, National Institute of Horticultural and Herbal Science, Rural Development Administration, Wanju 55365, Korea
3Department of Plant Resources and Environment, Jeju National University, Jeju 63243, South Korea
*Corresponding Author
31 July 2022. pp. 97-117
PDF XML Citation
Abstract

Crops such as wheat (Triticum aestivum L.), rice (Oryza sativa L.), maize (Zea mays L.), and soybean (Glycine max L.) are the most important sources of food and ensure food security worldwide. Yield losses because of plant-bacteria and fungi are a major global concern. Therefore, various management technologies like diagnostic techniques for bacterial and fungal diseases are among the most important criteria for yield loss management from biotic diseases. In particular, the early detection, prediction, and classification of plant diseases are essential for improved monitoring of plant diseases and resources. Over the last few decades, the utilization of digital imaging systems for plant disease identification has received considerable attention. Moreover, digital imaging methods have facilitated the early detection of several plant diseases using both 2-dimensional image assessment and the current more accurate 3-dimensional image analysis techniques via knowledge-based approaches using MRI and CT. Simultaneously, state-of-the-art, machine and deep learning approaches with different algorithms have progressed to increase precision in disease detection. In this study, we review and discuss important bacterial and fungal diseases that occur in major food crops, the importance of their early detection, and different imaging systems used in plant disease detection, their applications, challenges, and prospects. A literature survey indicated that with the emergence of new tools, the accuracy of the digital imaging system for plant disease detection is bound to increase and has a wide scope in the agriculture sector for helping the farming community as well as increasing sustainability and food security.

Keywords
Imaging data
Maize
Plant diseases
Rice
Wheat
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Information
  • Publisher :Agriculture and Life Sciences Research Institute, Kangwon National University
  • Publisher(Ko) :강원대학교 농업생명과학대학 농업생명과학연구원
  • Journal Title :Journal of Agricultural, Life and Environmental Sciences
  • Journal Title(Ko) :농업생명환경연구
  • Volume : 34
  • No :2
  • Pages :97-117
  • Received Date : 2022-05-13
  • Revised Date : 2022-05-30
  • Accepted Date : 2022-06-13
  • DOI :https://doi.org/10.22698/jales.20220012
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