Trends in invasive insect pest research: a bibliometric analysis

Ghosh, Pritha; Lal, Priyanka

doi:10.1007/s42690-023-01022-6

Cited by 3 publications

(2 citation statements)

References 30 publications

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“…Today, bibliometric software like VOS viewer (https://www.vosviewer.com, Van Eck and Waltman 2010) and scienti c databases like Web of Science have advanced and become more accessible, which is one of the reasons why bibliometric analysis has grown in popularity. The data collection involves the gathering of relevant literature from reputable scienti c databases, such as Web of Science, Dimension, Scopus, PubMed, or Google Scholar for bibliometric studies (Ghosh and Lal, 2023). We used the 'Dimensions' database to nd relevant literature on vector borne plant diseases.…”

Section: Methodsmentioning

confidence: 99%

WITHDRAWN: Unveiling The Research Trends And Visualization of Vector Borne Plant Virus Diseases Through Bibliometric Analysis

Ghosh,

TS,

Kumar

2023

Preprint

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Agricultural crops are threatened by plethora of Plant diseases. Diseases can lead to 100% crop loss, and can destroy the economic production. Various groups of micro-organisms are known to cause epidemic, endemic, pandemic and sporadic diseases in plants. Plant viral diseases have significant economic consequences for the agricultural industry. They can reduce crop yields, lower the quality of harvested produce, and lead to crop losses. Some of them also gets transmitted by different insects and spread rapidly. Mainly the sucking insects like aphids, whiteflies, leafhoppers, thrips etc are majorly known vectors of plant diseases. Since decades, the vector borne transmission studies, protection techniques, dissemination studies were the core interest of the scientific community. In our current bibliometric research, we have aimed to identify the majorly contributed countries, the collaborative institutes, suggestive precautionary methods to analyse all vector borne plant diseases. The purpose of this study is to examine global research conducted between 1966 and 2023, with a focus on the use of different vector borne plant diseases, protection techniques, identification techniques for diagnostic assays studies. This analysis provides insights into the major publishing journals, institutions involved, leading journals, influential authors, most cited articles, and common keywords by retrieving data from the 'Dimensions' database and employing bibliometric visualization software. According to our analysis, the research on vector borne plant diseases has been surged after 2000. Summary of the abstract is picturized below.

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Section: Methodsmentioning

confidence: 99%

WITHDRAWN: Unveiling The Research Trends And Visualization of Vector Borne Plant Virus Diseases Through Bibliometric Analysis

Ghosh,

TS,

Kumar

2023

Preprint

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“…Seemingly, bibliometric analysis is a widely used methodology within the agriculture domain. More specifically, within crop protection, bibliometric assessments are gaining much more momentum [73][74][75]. In the study, we utilised a systematic structural approach for screening the resources, portraying the visualisation along with the literature review, designing the article, and accumulating the bibliographical information as recommended by Rowley and Slack [76].…”

Section: Introductionmentioning

confidence: 99%

Bibliometric Analysis of Integrated Pest Management Practices

et al. 2023

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Integrated pest management (IPM) is a wide-ranging strategy that involves tactics for the structural control of pests and diseases, also known as integrated pest control (IPC). The prime aim of this study is to explore global scientific publications regarding integrated pest management and map the recent global trends in this innovative research domain, thereby providing future research directions based on dynamic observations. Bibliometric assessment is used in the research to provide a more detailed evaluation of the existing state of IPM, which will ultimately lead policymakers to develop novel measures to promote the efficient utilisation of the IPM measure. The study explores the Web of Science (WoS) core collection database covering published articles from 1993 to 2022, and we evaluated 1217 articles. The study employed the Biblioshiny app (V4.1, K-Synth, Naples, Italy), specially designed for the Bibliometrix R package, and a robust Java-based application, namely CiteSpace (V6.2.R3, Chaomei Chen, Philadelphia, PA, USA), to convert, process, visualise and evaluate the selected dataset. Moreover, we utilised another Java-based app VOSViewer (Leiden University, Leiden, The Netherlands), to provide a comprehensive visualisation. Based on citation analysis, we presented a list of the top 10 articles based on global citation count, the top 10 institutes, the top 10 journals, and the top 10 countries. By carefully evaluating the co-occurrence network, this study structurally represents the 9 clusters and the 20 prime keywords, which will be assisted the future researcher in understanding the key terms used by the prior research and the density criteria. The strategic coordinate mapping is utilised to evaluate the keywords’ inner relationship and provide strong themes of recent research progression of IPM by evaluating the centrality and density quadrant tactics. This technique has not been rehashed previously within the IPM domain. We identify gaps related to the formulation, implementation, and assessment of the IPM mechanisms and propose avenues for future studies to fill those gaps.

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Unveiling Trends in Forecasting Models for Crop Pest and Disease Outbreaks: A Systematic and Scientometric Analysis

Goyal,

Singh,

Raghuraman

et al. 2024

Preprint

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The exacerbation of global warming has significantly heightened the occurrence of crop pest and disease outbreaks, resulting in substantial agricultural losses worldwide. Weather-driven forecasting models play a pivotal role in predicting these outbreaks, facilitating timely and effective intervention strategies. This paper undertakes a comprehensive systematic review of the existing literature, to evaluate the comparative strengths, limitations, and relative efficacy of statistical versus machine learning forecasting models. Additionally, a bibliometric analysis encompassing 1,215 scientific studies sourced from the Web of Science Core Collection database (2000–2023), uncovering a sharp increase in research activity, particularly post-2019, across key disciplines like entomology, agronomy, and plant science. The continents leading in publication volume are Asia, Europe, and North America, with China, the United States, and India ranking as the top publishing countries. Chinese researchers rank highest among the top ten most productive authors in the field. Key journals with the highest citation rates include Plos One, Insects, and Computers and Electronics in Agriculture. The major research themes identified include deep learning, convolutional neural networks, artificial neural networks, and forecasting models, with keywords such as regression, prediction, insects, population dynamics etc. frequently occurring in the literature. Current research increasingly focuses on leveraging statistical as well as advanced machine learning methodologies, including hybrid and ensemble techniques, aimed at enhancing the accuracy and efficiency of forecasting pest and disease outbreaks. This study not only provides valuable insights into the current landscape of crop pest and disease forecasting but also offers a foundational framework for future research endeavors.

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Trends in invasive insect pest research: a bibliometric analysis

Cited by 3 publications

References 30 publications

WITHDRAWN: Unveiling The Research Trends And Visualization of Vector Borne Plant Virus Diseases Through Bibliometric Analysis

WITHDRAWN: Unveiling The Research Trends And Visualization of Vector Borne Plant Virus Diseases Through Bibliometric Analysis

Bibliometric Analysis of Integrated Pest Management Practices

Unveiling Trends in Forecasting Models for Crop Pest and Disease Outbreaks: A Systematic and Scientometric Analysis

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