scholarly journals A Bibliometric Network Analysis of Recent Publications on Digital Agriculture to Depict Strategic Themes and Evolution Structure

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7889
Author(s):  
Michele Kremer Sott ◽  
Leandro da Silva Nascimento ◽  
Cristian Rogério Foguesatto ◽  
Leonardo B. Furstenau ◽  
Kadígia Faccin ◽  
...  
Keyword(s):  
Network Analysis ◽  
Web Of Science ◽  
Future Research ◽  
Comprehensive Overview ◽  
Broad Perspective ◽  
Agriculture Sector ◽  
Challenges And Opportunities ◽  
Increase Productivity ◽  
Digital Agriculture ◽  
Smart Agriculture

The agriculture sector is one of the backbones of many countries’ economies. Its processes have been changing to enable technology adoption to increase productivity, quality, and sustainable development. In this research, we present a scientific mapping of the adoption of precision techniques and breakthrough technologies in agriculture, so-called Digital Agriculture. To do this, we used 4694 documents from the Web of Science database to perform a Bibliometric Performance and Network Analysis of the literature using SciMAT software with the support of the PICOC protocol. Our findings presented 22 strategic themes related to Digital Agriculture, such as Internet of Things (IoT), Unmanned Aerial Vehicles (UAV) and Climate-smart Agriculture (CSA), among others. The thematic network structure of the nine most important clusters (motor themes) was presented and an in-depth discussion was performed. The thematic evolution map provides a broad perspective of how the field has evolved over time from 1994 to 2020. In addition, our results discuss the main challenges and opportunities for research and practice in the field of study. Our findings provide a comprehensive overview of the main themes related to Digital Agriculture. These results show the main subjects analyzed on this topic and provide a basis for insights for future research.

scholarly journals Agriculture 4.0 and Smart Sensors. The Scientific Evolution of Digital Agriculture: Challenges and Opportunities

2021 ◽  
Author(s):  
Michele Kremer Sott ◽  
Leandro da Silva Nascimento ◽  
Cristian Rogério Foguesatto ◽  
Leonardo B. Furstenau ◽  
Kadígia Faccin ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Web Of Science ◽  
Smart Sensors ◽  
Agriculture Sector ◽  
Technological Adoption ◽  
Challenges And Opportunities ◽  
Increase Productivity ◽  
Digital Agriculture ◽  
Smart Agriculture ◽  
Theoretical Reflection

: The agriculture sector is one of the backbones of many countries’ economies and its processes have been changing in order to enable technological adoption to increase productivity, quality, and sustainable development. In this research, we present a theoretical reflection through a scientific mapping of the adoption of precision techniques and breakthrough technologies in agriculture, the so-called Precision Agriculture (PA) and Agriculture 4.0 (A4.0). To do this, we used 4,694 documents from the Web of Science database to perform a Bibliometric Performance and Network Analysis (BPNA) of the literature with the support of the PICOC protocol and the SciMAT software. Our findings present 22 strategic themes related to Digital Agriculture (DA) such as Internet of Things (IoT) and Climate-smart Agriculture (CSA) among others, and the thematic network structures of the motor themes and the thematic evolution structure of the field of the study over time. In addition, our results discuss the main challenges and opportunities of DA. Our findings have the potential to provide insights for practitioners and researchers in decision-making and pave the way for future works.

scholarly journals A Bibliometric Network Analysis of Coronavirus during the First Eight Months of COVID-19 in 2020

2021 ◽  
Vol 18 (3) ◽  
pp. 952 ◽  
Author(s):  
Leonardo B. Furstenau ◽  
Bruna Rabaioli ◽  
Michele Kremer Sott ◽  
Danielli Cossul ◽  
Mariluza Sott Bender ◽  
...  
Keyword(s):  
Decision Making ◽  
Network Analysis ◽  
Web Of Science ◽  
Future Research ◽  
Future Trends ◽  
Damage Prevention ◽  
Over Time ◽  
The Web

The COVID-19 pandemic has affected all aspects of society. Researchers worldwide have been working to provide new solutions to and better understanding of this coronavirus. In this research, our goal was to perform a Bibliometric Network Analysis (BNA) to investigate the strategic themes, thematic evolution structure and trends of coronavirus during the first eight months of COVID-19 in the Web of Science (WoS) database in 2020. To do this, 14,802 articles were analyzed, with the support of the SciMAT software. This analysis highlights 24 themes, of which 11 of the more important ones were discussed in-depth. The thematic evolution structure shows how the themes are evolving over time, and the most developed and future trends of coronavirus with focus on COVID-19 were visually depicted. The results of the strategic diagram highlight ‘CHLOROQUINE’, ‘ANXIETY’, ‘PREGNANCY’ and ‘ACUTE-RESPIRATORY-SYNDROME’, among others, as the clusters with the highest number of associated citations. The thematic evolution. structure presented two thematic areas: “Damage prevention and containment of COVID-19” and “Comorbidities and diseases caused by COVID-19”, which provides new perspectives and futures trends of the field. These results will form the basis for future research and guide decision-making in coronavirus focused on COVID-19 research and treatments.

scholarly journals Risk in agriculture: An overview of the theoretical insights and recent development trends during last decade – A review

2019 ◽  
Vol 65 (No. 9) ◽  
pp. 435-444 ◽  
Author(s):  
Lina Novickytė
Keyword(s):  
Network Analysis ◽  
Bibliometric Analysis ◽  
Web Of Science ◽  
Recent Decade ◽  
Future Research ◽  
Scientometric Analysis ◽  
Development Trends ◽  
Policy Makers ◽  
Research Areas ◽  
The Web

The main purpose of this paper is to provide a detailed overview of the theoretical insights and recent development trends on risk in agriculture. It focuses on the synthesis and analysis of the research studies published over the period from 2008 through 2018 and aims to identify major findings obtained over the recent decade and determine the areas for future research. This paper reviews a total of 397 unique publications retrieved from the international journals accessible in the Web of Science database. Based on different criteria deployed by the scientometric analysis, the selected articles have been reviewed and classified. The bibliometric analysis includes the citation volumes, authors, names of journals, research areas, affiliations, and contributing countries. The network analysis includes the examination of keywords. This article provides an opportunity for scholars, practitioners, and policy-makers to understand and manage risk in agriculture and at the same time presents a roadmap for future research in this field.

Image Processing Techniques Aiding Smart Agriculture

2020 ◽  
pp. 23-48
Author(s):  
Aspira S. Tripathy ◽  
Deepak Kumar Sharma
Keyword(s):  
Image Processing ◽  
Development Spectrum ◽  
Comprehensive Overview ◽  
Major Topic ◽  
Image Processing Techniques ◽  
Agriculture Sector ◽  
Smart Farming ◽  
Smart Agriculture ◽  
Processing Techniques ◽  
Increasing Load

With the ever-increasing load of satiating the agricultural demands, the transition of the orthodox methods into smart ones is inevitable. The agriculture sector for long has served as a momentous source of livelihood for many globally. It is arguably a major topic for nations of the development spectrum, contributing towards their export earnings and aiding in their GDP assessment. Thus, it is quite conspicuous that nations would work towards its expansion. In congruence, the burgeoning population and its demands have posed a threat to the environment due to extensive exploitation of resources, which in turn is escalating towards the downfall of the quality and quantity of agricultural produces requiring a 70% increment in the produces by 2050 for sustainability. To combat such hurdles, developed techniques are being employed. Through a survey of existing literature, this chapter provides a comprehensive overview of various image processing means that could come in handy for ameliorating the present scenario and shows their implied extension in the smart farming world.

scholarly journals A Look at the Past, Present and Future Research Trends of Artificial Intelligence in Agriculture

Agronomy ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1839
Author(s):  
José Luis Ruiz-Real ◽  
Juan Uribe-Toril ◽  
José Antonio Torres Arriaza ◽  
Jaime de Pablo Valenciano
Keyword(s):  
Artificial Intelligence ◽  
Web Of Science ◽  
Scientific Literature ◽  
Green Economy ◽  
Future Research ◽  
Agriculture Sector ◽  
The Past ◽  
Use Of Resources ◽  
Research Organizations ◽  
Prolific Authors

Technification in agriculture has resulted in the inclusion of more efficient companies that have evolved into a more complex sector focused on production and quality. Artificial intelligence, one of the relevant areas of technology, is transforming the agriculture sector by reducing the consumption and use of resources. This research uses a bibliometric methodology and a fractional counting method of clustering to analyze the scientific literature on the topic, reviewing 2629 related documents recorded on the Web of Science and Scopus databases. The study found significant results regarding the most relevant and prolific authors (Hoogenboom), supporting research organizations (National Natural Science Foundation of China) and countries (U.S., China, India, or Iran). The identification of leaders in this field gives researchers new possibilities for new lines of research based on previous studies. An in-depth examination of authors’ keywords identified different clusters and trends linking Artificial Intelligence and green economy, sustainable development, climate change, and the environment.

Measuring environmental performance in business to business relationships: a bibliometric review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Umar Burki ◽  
Usama Najam ◽  
Robert Dahlstrom
Keyword(s):  
Environmental Performance ◽  
Web Of Science ◽  
Future Research ◽  
Business Relationships ◽  
Comprehensive Overview ◽  
Content Type ◽  
Research Themes ◽  
Bibliometric Review ◽  
Business To Business ◽  
Practical Implications

PurposeThis study presents a bibliometric review of environmental performance in business to business relationships research.Design/methodology/approachWe applied suitable keywords to retrieve relevant peer-reviewed articles from the Web of Science database between 1992 and 2019. The study uses bibliographic coupling as a tool to screen 358 relevant articles' titles, abstracts, keywords, frameworks and headings for analysis. For visualization analysis, the study applied the visualizing scientific landscapes viewer.FindingsOur review systematically reports about the evolution of environmental performance in business-to-business literature relationships. Bibliometric procedures reveal prominent authors and publication outlets (journals) as well as noteworthy thematic and theoretical contributions to the literature.Practical implicationsThis study provides a comprehensive overview of environmental performance in business relationships and theoretical directions for further research.Originality/valueThe paper contributes to business literature by outlining emerging research themes and theoretical clusters on environmental performance for future research.

Emerging Technological Model to Sustainable Agriculture

2021 ◽  
pp. 101-122
Author(s):  
Palanivel Kuppusamy ◽  
Suganthi Shanmugananthan ◽  
Pradeep Tomar
Keyword(s):  
Sustainable Agriculture ◽  
Agricultural Sector ◽  
State Of The Art ◽  
The State ◽  
Conventional Agriculture ◽  
Agricultural Industry ◽  
Agriculture Sector ◽  
Digital Agriculture ◽  
Smart Agriculture ◽  
Technological Model

The agricultural sector has witnessed significant technological transformations over the last few decades. The state-of-the-art technologies are transforming the traditional agriculture models into digital agriculture. From these technologies, conventional agriculture has evolved and shifted towards a smart agriculture system. In a smart agriculture system, farmers can collect and analyze the collected data to fertilize and tend their crops. The smart agriculture system provides economical and more accurate ways to predict and protect crop growth. The incorporation of these technologies digitalizes the agricultural industry by increasing profits, reducing waste, improving efficiency, and becoming sustainable. This chapter aims to study the state-of-the-art technologies used in the agriculture sector and proposes a smart agriculture model using these technologies.

scholarly journals 100 Years of Scientific Evolution of Work and Organizational Psychology: A Bibliometric Network Analysis From 1919 to 2019

2020 ◽  
Vol 11 ◽  
Author(s):  
Michele K. Sott ◽  
Mariluza S. Bender ◽  
Leonardo B. Furstenau ◽  
Laura M. Machado ◽  
Manuel J. Cobo ◽  
...  
Keyword(s):  
Network Analysis ◽  
Network Structure ◽  
Web Of Science ◽  
Organizational Psychology ◽  
Future Research ◽  
Process Data ◽  
Field Of Study ◽  
Emerging Themes ◽  
High Degree ◽  
The Web

In this study, we explore a 100 years of Work and Organizational Psychology (WOP). To do this, we carry out a bibliometric performance and network analysis (BPNA) to understand the evolution structure and the most important themes in the field of study. To perform the BNPA, 8,966 documents published since 1919 were exported from the Web of Science and Scopus databases. The SciMAT software was used to process data and to create the evolution structure, the strategic diagram, and the thematic network structure of the strategic themes of the field of WOP. We identified 29 strategic clusters and discuss the most important themes (motor themes) and their relationship with other clusters. This research presents the complete evolution of the field of study, identifying emerging themes and others with a high degree of development. We hope that this work will support researchers and future research in the field of WOP.

A Systematic Literature Review of the EFQM Excellence Model from 1991 to 2019

1970 ◽  
Vol 2 (2) ◽  
pp. 11-15
Author(s):  
Muhammad Yousaf ◽  
Petr Bris
Keyword(s):  
Quality Management ◽  
Data Collection ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Quantitative Research ◽  
Web Of Science ◽  
State Of The Art ◽  
Future Research ◽  
European Foundation ◽  
The Subject

A systematic literature review (SLR) from 1991 to 2019 is carried out about EFQM (European Foundation for Quality Management) excellence model in this paper. The aim of the paper is to present state of the art in quantitative research on the EFQM excellence model that will guide future research lines in this field. The articles were searched with the help of six strings and these six strings were executed in three popular databases i.e. Scopus, Web of Science, and Science Direct. Around 584 peer-reviewed articles examined, which are directly linked with the subject of quantitative research on the EFQM excellence model. About 108 papers were chosen finally, then the purpose, data collection, conclusion, contributions, and type of quantitative of the selected papers are discussed and analyzed briefly in this study. Thus, this study identifies the focus areas of the researchers and knowledge gaps in empirical quantitative literature on the EFQM excellence model. This article also presents the lines of future research.

Challenges and Opportunities for Neuroimaging in Young Patients with Traumatic Brain Injury: a Coordinated Effort towards Advancing Discovery from the ENIGMA Pediatric Moderate/Severe TBI Group

2019 ◽  
Author(s):  
Emily L. Dennis ◽  
Karen Caeyenberghs ◽  
Robert F. Asarnow ◽  
Talin Babikian ◽  
Brenda Bartnik-Olson ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Meta Analysis ◽  
Young Patients ◽  
Future Research ◽  
Childhood And Adolescence ◽  
Developmental Issues ◽  
Challenges And Opportunities ◽  
Severe Tbi ◽  
Advance Research

Traumatic brain injury (TBI) is a major cause of death and disability in children in both developed and developing nations. Children and adolescents suffer from TBI at a higher rate than the general population; however, research in this population lags behind research in adults. This may be due, in part, to the smaller number of investigators engaged in research with this population and may also be related to changes in safety laws and clinical practice that have altered length of hospital stays, treatment, and access to this population. Specific developmental issues also warrant attention in studies of children, and the ever-changing context of childhood and adolescence may require larger sample sizes than are commonly available to adequately address remaining questions related to TBI. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Pediatric Moderate-Severe TBI (msTBI) group aims to advance research in this area through global collaborative meta-analysis. In this paper we discuss important challenges in pediatric TBI research and opportunities that we believe the ENIGMA Pediatric msTBI group can provide to address them. We conclude with recommendations for future research in this field of study.

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