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DC Field | Value | Language |
---|---|---|
dc.creator | Santana, Lucas Santos | - |
dc.creator | Ferraz, Gabriel Araújo e Silva | - |
dc.creator | Santos, Sthéfany Airane dos | - |
dc.creator | Dias, Jessica Ellen Lima | - |
dc.date.accessioned | 2024-02-24T12:20:57Z | - |
dc.date.available | 2024-02-24T12:20:57Z | - |
dc.date.issued | 2022-09 | - |
dc.identifier.citation | SANTANA, L. S. et al. Precision coffee growing: A review. Coffee Science, Lavras, v. 17, e172007, 2022. DOI: 10.25186/.v17i.2007. | pt_BR |
dc.identifier.uri | https://coffeescience.ufla.br/index.php/Coffeescience/article/view/2007 | pt_BR |
dc.identifier.uri | http://repositorio.ufla.br/jspui/handle/1/58919 | - |
dc.description.abstract | Precision Agriculture (PA) technologies introduction in coffee-growing is becoming essential to advances in sustainable cultivation and increase in output. Applications that involve PA techniques in coffee production are defined now as Precision Coffee growing (PC). Systematically explored, studies on the subject contribute to improvements in the area, relating soil variability to its impacts on plants. The PC's scientific approach offers new forms of management and more security in coffee production. Aimed at reducing pesticides application and nutrients to the soil, contributing to sustainable development in coffee production. Initially, the research on coffee production had dealt with soil spatial variability, highlighting the geostatistical methods and specific ways to sample the soil. With technological advances in agriculture, new ways of monitoring spatial variability are available. In this context, studies are arising on spatial variability related to the plant, applying terrestrial, aerial and orbital sensors, possibly creating perspectives for monitoring and mapping coffee production. Artificial intelligence, Remotely Piloted Aircraft (ARP) products, harvesting yield sensors, automatic grain classifiers, and remote sensing stand out as new technologies under development in coffee production. These applications in PC involving multidisciplinary research demonstrate new relevant ways of improving crop managing and sustainability guaranteeing. | pt_BR |
dc.language | en | pt_BR |
dc.publisher | Universidade Federal de Lavras | pt_BR |
dc.rights | acesso aberto | pt_BR |
dc.source | Coffee Science | pt_BR |
dc.subject | Digital agriculture | pt_BR |
dc.subject | Agricultura digital | pt_BR |
dc.subject | Spatial variability | pt_BR |
dc.subject | Variabilidade espacial | pt_BR |
dc.subject | Agricultural crops - Sustainability | pt_BR |
dc.subject | Cultivos agrícolas - Sustentabilidade | pt_BR |
dc.subject | Remote sensing | pt_BR |
dc.subject | Sensoriamento remoto | pt_BR |
dc.subject | Sensors | pt_BR |
dc.subject | Sensores | pt_BR |
dc.title | Precision coffee growing: A review | pt_BR |
dc.type | Artigo | pt_BR |
Appears in Collections: | DEA - Artigos publicados em periódicos |
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