Knowledge mapping trends of Internet of Things (IoT) in plant disease and insect pest study: a visual analysis

The study and literature on the Internet of Things (IoT) and its applications in agriculture for smart farming are increasing worldwide. However, the knowledge mapping trends related to IoT applications in plant disease, pest management, and control are still unclear and rarely reported. The primary...

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Main Authors: Mohd Zawawi, Muhammad Akmal, Jusoh, Mohd Fauzie, Muhammad, Marinah, Naher, Laila, Abdul Latif, Nurul Syaza, Abdul Muttalib, Muhammad Firdaus, Radzuan, Mohd Nazren, Nugroho, Andri Prima
Format: Article
Language:English
Published: Universiti Putra Malaysia Press 2023
Online Access:http://psasir.upm.edu.my/id/eprint/102064/
http://psasir.upm.edu.my/id/eprint/102064/1/02%20JST-3618-2022.pdf
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author Mohd Zawawi, Muhammad Akmal
Jusoh, Mohd Fauzie
Muhammad, Marinah
Naher, Laila
Abdul Latif, Nurul Syaza
Abdul Muttalib, Muhammad Firdaus
Radzuan, Mohd Nazren
Nugroho, Andri Prima
author_facet Mohd Zawawi, Muhammad Akmal
Jusoh, Mohd Fauzie
Muhammad, Marinah
Naher, Laila
Abdul Latif, Nurul Syaza
Abdul Muttalib, Muhammad Firdaus
Radzuan, Mohd Nazren
Nugroho, Andri Prima
author_sort Mohd Zawawi, Muhammad Akmal
building UPM Institutional Repository
collection Online Access
description The study and literature on the Internet of Things (IoT) and its applications in agriculture for smart farming are increasing worldwide. However, the knowledge mapping trends related to IoT applications in plant disease, pest management, and control are still unclear and rarely reported. The primary aim of the present study is to identify the current trends and explore hot topics of IoT in plant disease and insect pest research for future research direction. Peer review articles published from Web of Science (WoS) Core Collection (2010-2021) were identified using keywords, and extracted database was analysed scientifically via Microsoft Excel 2019, VOSviewer and R programming software. A total of 231 documents with 5321 cited references authored by 878 scholars showed that the knowledge on the studied area has been growing positively and rapidly for the past ten years. India and China are the most productive countries, comprising more than half (52%) of the total access database on the subject area in WoS. IoT application has been integrated with other knowledge domains, such as machine learning, deep learning, image processing, and artificial intelligence, to produce excellent crop and pest disease monitoring research. This study contributes to the current knowledge of the research topic and suggests possible hot topics for future direction.
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spelling upm-1020642023-08-11T08:49:30Z http://psasir.upm.edu.my/id/eprint/102064/ Knowledge mapping trends of Internet of Things (IoT) in plant disease and insect pest study: a visual analysis Mohd Zawawi, Muhammad Akmal Jusoh, Mohd Fauzie Muhammad, Marinah Naher, Laila Abdul Latif, Nurul Syaza Abdul Muttalib, Muhammad Firdaus Radzuan, Mohd Nazren Nugroho, Andri Prima The study and literature on the Internet of Things (IoT) and its applications in agriculture for smart farming are increasing worldwide. However, the knowledge mapping trends related to IoT applications in plant disease, pest management, and control are still unclear and rarely reported. The primary aim of the present study is to identify the current trends and explore hot topics of IoT in plant disease and insect pest research for future research direction. Peer review articles published from Web of Science (WoS) Core Collection (2010-2021) were identified using keywords, and extracted database was analysed scientifically via Microsoft Excel 2019, VOSviewer and R programming software. A total of 231 documents with 5321 cited references authored by 878 scholars showed that the knowledge on the studied area has been growing positively and rapidly for the past ten years. India and China are the most productive countries, comprising more than half (52%) of the total access database on the subject area in WoS. IoT application has been integrated with other knowledge domains, such as machine learning, deep learning, image processing, and artificial intelligence, to produce excellent crop and pest disease monitoring research. This study contributes to the current knowledge of the research topic and suggests possible hot topics for future direction. Universiti Putra Malaysia Press 2023-07-03 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/102064/1/02%20JST-3618-2022.pdf Mohd Zawawi, Muhammad Akmal and Jusoh, Mohd Fauzie and Muhammad, Marinah and Naher, Laila and Abdul Latif, Nurul Syaza and Abdul Muttalib, Muhammad Firdaus and Radzuan, Mohd Nazren and Nugroho, Andri Prima (2023) Knowledge mapping trends of Internet of Things (IoT) in plant disease and insect pest study: a visual analysis. Pertanika Journal of Science & Technology, 31 (4). pp. 1-12. ISSN 0128-7680; ESSN: 2231-8526 http://www.pertanika.upm.edu.my/pjst/browse/prepress-issue?article=JST-3618-2022 10.47836/pjst.31.4.02
spellingShingle Mohd Zawawi, Muhammad Akmal
Jusoh, Mohd Fauzie
Muhammad, Marinah
Naher, Laila
Abdul Latif, Nurul Syaza
Abdul Muttalib, Muhammad Firdaus
Radzuan, Mohd Nazren
Nugroho, Andri Prima
Knowledge mapping trends of Internet of Things (IoT) in plant disease and insect pest study: a visual analysis
title Knowledge mapping trends of Internet of Things (IoT) in plant disease and insect pest study: a visual analysis
title_full Knowledge mapping trends of Internet of Things (IoT) in plant disease and insect pest study: a visual analysis
title_fullStr Knowledge mapping trends of Internet of Things (IoT) in plant disease and insect pest study: a visual analysis
title_full_unstemmed Knowledge mapping trends of Internet of Things (IoT) in plant disease and insect pest study: a visual analysis
title_short Knowledge mapping trends of Internet of Things (IoT) in plant disease and insect pest study: a visual analysis
title_sort knowledge mapping trends of internet of things (iot) in plant disease and insect pest study: a visual analysis
url http://psasir.upm.edu.my/id/eprint/102064/
http://psasir.upm.edu.my/id/eprint/102064/
http://psasir.upm.edu.my/id/eprint/102064/
http://psasir.upm.edu.my/id/eprint/102064/1/02%20JST-3618-2022.pdf