Precision Agriculture under a bibliometric view

Abstract

Precision Agriculture comprises techniques to monitor and control the differentiated application of agricultural inputs, considering the variability of cultivation areas over time to increase productivity and maintain environmental sustainability. Its current form considers the use of high-tech equipment to ensure food safety in the future and, therefore, constantly seeks research that produces innovations for the sector. However, there is a tremendous challenge in evaluating scientific development, given the large volume of information. This study aimed to carry out a scientific mapping of Precision Agriculture from a set of bibliometric techniques supported using the R bibliometrix tool. Based on this objective, the research questions were formulated and answered throughout qualitative quantitative and descriptive exploratory study. The data processing resulted 5,807 articles (13,705 authors) obtained from 1993 to 2020. Among the main results, there is constant growth in the number of publications, especially between 2016 and 2020; more significant concentration among countries, forming well-defined collaboration subnetworks through their institutions; presence of expressive central themes in the research with a high density of studies, such as the use of remote sensing combined with machine learning techniques, due to the growing trend in the amount of processed data.

Agricultura de Precisão: monitoramento tecnológico a partir da análise de patentes

“…Para garantir a manutenção desses sistemas agrícolas e a produtividade no longo prazo, diversas técnicas de mecanização, irrigação, fertilização, entre outras, foram introduzidas na agricultura ao longo do tempo. Com o uso das Tecnologias da Informação (TI) e, mais recentemente, da Internet das Coisas (IoT) e da Inteligência Artificial (IA), os sistemas de Agricultura de Precisão (AP) têm promovido a otimização do uso de insumos, como sementes, água, fertilizantes, corretivos, defensivos, etc., considerando o mapeamento da variabilidade espacial e temporal dos campos agrícolas (Cisternas et al, 2020;Silva & Silva-Mann, 2021).…”