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Models based on vegetation indices (VI) from digital aerial images are promising for predicting biometric variables in agricultural crops. The objective of this study was to generate prediction models... ...

Repository: BDPA     Publication year: 2023

Abstract: The use of non-destructive methods with less human interference is of great interest in agricultural industry and crop breeding. Modern imaging technologies enable the automatic visualizatio... ...

Repository: BDPA     Publication year: 2021

The processing of multispectral images acquired with embedded cameras in unmanned aerial vehicles (drones) has brought new opportunities for precision agriculture. In this study a method for evaluatin... ...

Repository: BDPA     Publication year: 2024

Abstract: Soil mapping demands large-scale surveys that are costly and time consuming. It is necessary to identify strategies with reduced costs to obtain detailed information for soil mapping. We aim... ...

Repository: BDPA     Publication year: 2018

The coffee leaf miner (Leucoptera coffeella) is a primary pest for coffee plants. The attack of this pest reduces the photosynthetic area of the leaves due to necrosis, causing premature leaf falling,... ...

Repository: BDPA     Publication year: 2022

The advancement of digital agriculture combined with computational tools and Unmanned Aerial Vehicles (UAVs) has opened the way to large-scale data collection for the calculation of vegetation indices... ...

Repository: BDPA     Publication year: 2024

Este estudo monitorou um vinhedo de Cabernet Sauvignon por meio de dados orbitais a partir das imagens dos satélites Planet e Sentinel-2, avaliando a adequabilidade dos dois sensores por meio do Índic... ...

Repository: BDPA     Publication year: 2024

Remote sensing by spectral imaging of the Earth's surface can be widely used, but only when the atmospheric influence is nullified and the data are reduced to surface reflectance units. The atmospheri... ...

Repository: BDPA     Publication year: 2012

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