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Oliveira, R.M
Oliveira, L.P
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Authors
Oliveira, M.F
Carneiro, F.M
Thurmond, M
del Val, M.D
Oliveira, L.P
Ortiz, B
Sanz-Saez, A
Tedesco, D
Oliveira , T
Ramos da Silva, G
Souza, E.A
Oliveira, R.M
Souza, B.F
Faria, M.A
Topics
Big Data, Data Mining and Deep Learning
Digital Solutions for Soil Health, Water Quality, and Conservation Practices
Type
Oral
Poster
Year
2022
2026
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1. Predicting Below and Above Ground Peanut Biomass and Maturity Using Multi-target Regression

Peanut growth and maturity prediction can help farmers and breeding programs improving crop management. Remote sensing images collected by satellites and drones make possible and accurate crop monitoring. Today, empirical relations between crop biomass and spectral reflectance could be used for prediction of single variables such as aboveground crop biomass, pod weight (PW), or peanut maturity. Robust algorithms such as multioutput regression (MTR) implemented through multioutput random forest... M.F. Oliveira, F.M. Carneiro, M. Thurmond, M.D. Del val, L.P. Oliveira, B. Ortiz, A. Sanz-saez, D. Tedesco

2. Management Zone Delineation for Subsoiling Using Apparent Electrical Conductivity, Elevation, and Soil Moisture

Soil compaction is a primary physical factor limiting agricultural crop development. It mechanically impedes root growth, alters soil water dynamics, and consequently affects plant nutrient uptake. In agricultural systems under mechanization or animal trampling, compacted layers are spatially heterogeneous. This necessitates spatial analysis approaches for more precise management decisions, as average values often prove inadequate for site-specific problem resolution. Consequently,... T. Oliveira , G. Ramos da silva, E.A. Souza, R.M. Oliveira, B.F. Souza, M.A. Faria