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Thurmond, M
Tremblay, N
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Authors
Longchamps, L
Panneton, B
Tremblay, N
Oliveira, M.F
Carneiro, F.M
Thurmond, M
del Val, M.D
Oliveira, L.P
Ortiz, B
Sanz-Saez, A
Tedesco, D
Topics
Precision Horticulture
Big Data, Data Mining and Deep Learning
Type
Oral
Year
2018
2022
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1. Observational Studies in Agriculture: Paradigm Shift Required

There is a knowledge gap in agriculture. For instance, there is no way to tell with precision what is the outcome of cutting N fertilizer by a quarter on important outcomes such as yield, net return, greenhouse gas emissions or groundwater pollution. Traditionally, the way to generate knowledge in agriculture has been to conduct research with the experimental method where experiments are conducted in a controlled environment with trials replicated in space and... L. Longchamps, B. Panneton, N. Tremblay

2. 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