Proceedings :: International Society of Precision Agriculture

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Costa Barboza, T

Lima, C.D

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Authors

Lima, C.D

Nogueira, B

, A

Junior, D.U

Carvalho, I.R

Bredemeier, C

Nogueira, B

Figueiró, A.C

, A

Bender, E

Lima, C.D

Vian, A.L

Bredemeier, C

Topics

Remote and Proximal Sensing of Soils and Crops

UAV-Based Scouting, Imaging, and Targeted Applications

Type

Poster

Year

2026

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Filter results2 paper(s) found.
1. Analysis of Mixed Models in UAV-based Spectral Vegetation Indices for Prediction of Agronomic Variables in Soybean Subjected to Flooding The 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
2. Estimation of Agronomic Parameters in Maize Using UAV-based Vegetation Indices Obtained by a Multispectral Sensor Precision 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

Filter results2 paper(s) found.

1. Analysis of Mixed Models in UAV-based Spectral Vegetation Indices for Prediction of Agronomic Variables in Soybean Subjected to Flooding

The 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

2. Estimation of Agronomic Parameters in Maize Using UAV-based Vegetation Indices Obtained by a Multispectral Sensor

Precision 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