Trends on Advanced Information and Communication Technologies for Improving Agricultural Productivities: A Bibliometric Analysis

被引:25
作者
Armenta-Medina, Dagoberto [1 ,2 ]
Ramirez-delReal, Tania A. [1 ,3 ]
Villanueva-Vasquez, Daniel [1 ,2 ]
Mejia-Aguirre, Cristian [2 ]
机构
[1] CONACyT Consejo Nacl Ciencia & Tecnol, Direcc Catedras, Insurgentes Sur 1582, Ciudad de Mexico 03940, Mexico
[2] INFOTEC Ctr Invest & Innovac Tecnol Informac & Co, Circuito Tecnopolo Sur 112,Fracc Tecnopolo Pocito, Aguascalientes 20313, Aguascalientes, Mexico
[3] CentroGEO Ctr Invest Ciencias Informac Geoespacia, Circuito Tecnopolo Norte 117,Col Tecnopolo Pocito, Aguascalientes 20313, Aguascalientes, Mexico
来源
AGRONOMY-BASEL | 2020年 / 10卷 / 12期
关键词
bibliometrics; precision agriculture; science mapping; smart farming; IoT; PRECISION AGRICULTURE; SCIENTIFIC-RESEARCH; WORLD; INDICATORS; KNOWLEDGE; SUPPORT; SYSTEMS; MODEL; TOOL; EU;
D O I
10.3390/agronomy10121989
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
In this work, an exhaustive revision is given of the literature associated with advanced information and communication technologies in agriculture within a window of 25 years using bibliometric tools enabled to detect of the main actors, structure, and dynamics in the scientific papers. The main findings are a trend of growth in the dynamics of publications associated with advanced information and communication technologies in agriculture productivity. Another assertion is that countries, like the USA, China, and Brazil, stand out in many publications due to allocating more resources to research, development, and agricultural productivity. In addition, the collaboration networks between countries are frequently in regions with closer cultural and idiomatic ties; additionally, terms' occurrence are obtained with Louvain algorithm predominating four clusters: precision agriculture, smart agriculture, remote sensing, and climate smart agriculture. Finally, the thematic-map characterization with Callon's density and centrality is applied in three periods. The first period of thematic analysis shows a transition in detecting the variability of a nutrient, such as nitrogen, through the help of immature georeferenced techniques, towards greater remote sensing involvement. In the transition from the second to the third stage, the maturation of technologies, such as unmanned aerial vehicles, wireless sensor networks, and the machine learning area, is observed.
引用
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页数:24
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