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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Precision agriculture and the digital contributions for site-specific management of the fields

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Molin, Jose Paulo [1] ; Bazame, Helizani Couto [1] ; Maldaner, Leonardo [1] ; Corredo, Lucas de Paula [1] ; Martello, Mauricio [1] ; Canata, Tatiana Fernanda [1]
Total Authors: 6
[1] Univ Sao Paulo, Escola Super Agr Luiz de Queiroz ESALQ, Lab Agr Precisdo, Dept Engn Biossistemas, Piracicaba, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: REVISTA CIENCIA AGRONOMICA; v. 51, n. SI 2020.
Web of Science Citations: 0

Site-specific management practices have been possible due to the wide range of solutions for data acquisition and interventions at the field level. Different approaches have to be considered for data collection, like dedicated soil and plant sensors, or even associated with the capacity of the agricultural machinery to generate valuable data that allows the farmer or the manager to infer the spatial variability of the fields. However, high computational resources are needed to convert extensive databases into useful information for site-specific management. Thus, technologies from industry, such as the Internet of Things and Artificial Intelligence, applied to agricultural production, have supported the decision-making process of precision agriculture practices. The interpretation and the integration of information from different sources of data allow enhancement of agricultural management due to its capacity to predict attributes of the crop and soil using advanced data-driven tools. Some examples are crop monitoring, local applications of inputs, and disease detection using cloud-based systems in digital platforms, previously elaborated for decision-support systems. In this review, we discuss the different approaches and technological resources, popularly named as Agriculture 4.0 or digital farming, inserted in the context of the management of spatial variability of the fields considering different sources of crop and soil data. (AU)

FAPESP's process: 18/25008-8 - Sugarcane qualitative attributes determination and mapping by spectral sensors
Grantee:Lucas de Paula Corrêdo
Support Opportunities: Scholarships in Brazil - Doctorate