Sensoriamento remoto aéreo na avaliação do estado nutricional de cafeeiro arábica cultivado em lavoura microterraceada
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Data
2025-09-25
Autores
Jordaim, Renan Baptista
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Universidade Federal do Espírito Santo
Resumo
Coffee farming is one of the main sources of income and employment for rural properties in Espírito Santo. More than half of the crops are cultivated in the southern region of the state, in mountainous areas with sloping terrain, low technological levels, and soils with low natural fertility. Among the main factors that have limited the increase in the productivity of these crops, the low efficiency in fertilization management stands out, which has compromised the sustainability of coffee farming in mountainous regions. The application of precision agriculture tools can help in detecting the spatial and temporal variability of the nutritional status of these crops and enable more adequate plant nutrition management in order to achieve a higher productive potential. In this sense, this study aimed to evaluate the spatio-temporal behavior of the nutritional status of coffee plants and its relationship with productivity in microterraced crops, as well as to use multispectral remote sensing in the delineation of management zones for the purpose of diagnosing the nutritional status of the crop. The study was conducted in an arabica coffee plantation located in the municipality of Ibatiba-ES. For data collection, an irregular sampling grid containing 100 sampling points was created. Leaf samples were collected during the 2019/2020 and 2021/2022 growing seasons. Aerial surveys were carried out using a drone equipped with a RedEdge MX multispectral sensor to determine the spectral signature of the canopy and subsequently calculate different vegetation indices. The values obtained from the spectral bands and vegetation indices were correlated with the foliar nutrients of the plants, and those that showed a significant, moderate to high correlation were used to delineate management zones. The Kappa index was used to verify the agreement between the management zone classes and the foliar nutrients. The study highlighted the significant spatial and temporal variability in the productivity and nutritional status of coffee plants in a microterraced system. Through multispectral aerial remote sensing, it was possible to characterize the vegetative vigor of the plants and delineate management zones that can be used to support fertilization strategies at variable rates. The NIR and RedEdge spectral bands and the NDVI and GNDVI vegetation indices stood out in this process as more stable, and the Blue band and GNDVI index showed potential for the nutritional assessment of coffee plants
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Agricultura de precisão , Geoestatística , Índices de vegetação , Zonas de manejo , Precision agriculture , Geostatistics , Vegetation indices , Management zones