Proceedings
Authors
| Filter results6 paper(s) found. |
|---|
1. Influence of Application Rate and Flight Orientation on Droplet Deposition by Remotely Piloted Aircraft (RPA) in ‘Gala’ Apple OrchardsApple production is a cornerstone of the fruit industry, with the ‘Gala’ variety holding a prominent position due to its commercial value. However, this cultivar is highly susceptible to apple scab (Venturia inaequalis), requiring application technologies of fungicides that ensure canopy protection, especially during flowering. In this sense, precision horticulture has sought alternatives to optimize the application of crop protection products, aiming to reduce... L. Espindola Müller, T. Buchener, B. Nogueira, R. Silva, S.J. Silveira, C. Bredemeier |
2. Analysis of Mixed Models in UAV-based Spectral Vegetation Indices for Prediction of Agronomic Variables in Soybean Subjected to FloodingThe identification of soybean genotypes with increased flooding tolerance is relevant for yield stability in lowlands producing areas. In this context, the use of relevant spectral vegetation indices based on multispectral sensors embedded in unmanned aerial vehicles (UAVs) for the selection of more flooding-tolerant soybean genotypes is a primary demand within plant phenomics. Nonetheless, the environmental effects can change the accuracy of spectral indices and the correct methodology for deduction... C.D. Lima, B. Nogueira, A. , D.U. Junior, I.R. Carvalho, C. Bredemeier |
3. Importance of Irradiance Correction for UAV-based Vegetation Indices in the Prediction of Shoot Biomass in WheatThe extraction of vegetation indices from multispectral images obtained with UAV-bsed sensors for biomass estimation has proven to be a useful tool for designing site-specific interventions on wheat. The reflectance values from monochromatic bands collected with optical sensors for calculating vegetation indices should have high reliability and repeatability in the case of successive assessments under different illumination conditions. In this context, the objective of the study was to characterize... A.C. Figueiró, B. Nogueira, E. Bender, R. Silva, V.M. Cassol, S.J. Silveira , C. Bredemeier, A.L. Vian |
4. Estimation of Agronomic Parameters in Maize Using UAV-based Vegetation Indices Obtained by a Multispectral SensorPrecision agriculture emerges as a response to optimize input use and to monitor crop spatial variability over time. In this context, the use of vegetation indices obtained by optical sensors embedded in drones or satellites has become a useful tool for predicting agronomic parameters in maize fields, such as aboveground dry biomass, leaf chlorophyll content, and grain yield. Thus, the objective of this study was to correlate field agronomic parameters with vegetation indexes obtained by a multispectral... B. Nogueira, A.C. Figueiró, A. , E. Bender, C.D. Lima, A.L. Vian, C. Bredemeier |
5. Selection of UAV-based Vegetation Indices for the Prediction of Leaf Chlorophyll Content in Maize Using a Normalized Partial Least Squares Regression (PLSR) Reduction ApproachThe accurate monitoring of the nutritional status is essential for optimizing nitrogen (N) fertilization and maximizing maize grain yield. Variations in N availability directly affect agronomic parameters such as leaf chlorophyll content, which can be estimated using optical sensors. This study assessed the effects of urease inhibitors and nitrogen application rates on leaf chlorophyll content and predicted total leaf chlorophyll content in maize using relevant vegetation indices under field conditions.... B. Nogueira, E. Bender, D. De Carvalho Arruda, M. Da Costa Salem, L. Espindola Muller, S.R. Dos Santos Gonçalves Junior, G. Eissmann Souza, J.V. Muller Klassmann, B.B. Gallo, C. Bredemeier |
6. Hyperspectral Imagery for Prediction of Leaf Chlorophyll Content in Maize Under the Application of Different Urease Inhibitors Using Machine LearningUrea is the most common and widely used nitrogen (N) source. However, it is highly susceptible to ammonia volatilization losses, especially under favorable climatic conditions. The use of urease inhibitors becomes an important strategy because these compounds slow down the hydrolysis of urea, increasing efficiency in terms of N assimilation, enhancing leaf chlorophyll content, promoting plant growth, and maximizing maize grain yield. In parallel, hyperspectral sensors have emerged as a non-destructive... S.R. Gonçalves Junior, M. Da Costa Salem, G. Eissmann Souza, D. Carvalho De Arruda, E. Bender, B. Nogueira, L. Espindola Muller, B.B. Gallo, C. Bredemeier |