TY - JOUR
T1 - Theme Mapping and Bibliometric Analysis of Two Decades of Smart Farming
AU - Kushartadi, Tri
AU - Mulyono, Aditya Eka
AU - Al Hamdi, Azhari Haris
AU - Rizki, Muhammad Afif
AU - Sadat Faidar, Muhammad Anwar
AU - Harsanto, Wirawan Dwi
AU - Suryanegara, Muhammad
AU - Asvial, Muhamad
N1 - Funding Information:
The authors are grateful to the class member of Technological Innovation and Entrepreneurship, academic year 2022, for the support of this research.
Publisher Copyright:
© 2023 by the authors.
PY - 2023/7
Y1 - 2023/7
N2 - The estimated global population for 2050 is 9 billion, which implies an increase in food demand. Agriculture is the primary source of food production worldwide, and improving its efficiency and productivity through an integration with information and communication technology system, so-called “smart farming”, is a promising approach to optimizing food supply. This research employed bibliometric analysis techniques to investigate smart farming trends, identify their potential benefits, and analyze their research insight. Data were collected from 1141 publications in the Scopus database in the period 1997–2021 and were extracted using VOS Viewer, which quantified the connections between the articles using the co-citation unit, resulting in a mapping of 10 clusters, ranging from agriculture to soil moisture. Finally, the analysis further focuses on the three major themes of smart farming, namely the IoT; blockchain and agricultural robots; and smart agriculture, crops, and irrigation.
AB - The estimated global population for 2050 is 9 billion, which implies an increase in food demand. Agriculture is the primary source of food production worldwide, and improving its efficiency and productivity through an integration with information and communication technology system, so-called “smart farming”, is a promising approach to optimizing food supply. This research employed bibliometric analysis techniques to investigate smart farming trends, identify their potential benefits, and analyze their research insight. Data were collected from 1141 publications in the Scopus database in the period 1997–2021 and were extracted using VOS Viewer, which quantified the connections between the articles using the co-citation unit, resulting in a mapping of 10 clusters, ranging from agriculture to soil moisture. Finally, the analysis further focuses on the three major themes of smart farming, namely the IoT; blockchain and agricultural robots; and smart agriculture, crops, and irrigation.
KW - bibliometric
KW - clustering
KW - machine learning
KW - smart farming
KW - text mining
UR - http://www.scopus.com/inward/record.url?scp=85166394581&partnerID=8YFLogxK
U2 - 10.3390/info14070396
DO - 10.3390/info14070396
M3 - Article
AN - SCOPUS:85166394581
SN - 2078-2489
VL - 14
JO - Information (Switzerland)
JF - Information (Switzerland)
IS - 7
M1 - 396
ER -
