Harnessing crop models and machine learning for a spatial-temporal characterization of irrigated rice breeding environments in Brazil

Author:

Heinemann Alexandre Bryan,Costa-Neto Germano,da Matta David Henriques,Fernandes Igor Kuivjogi,Stone Luís Fernando

Publisher

Elsevier BV

Reference52 articles.

1. ANA. Agência Nacional de Águas e Saneamento Básico, 2020. Mapeamento do arroz irrigado no Brasil. Conab, Brasília.

2. Fitting linear mixed-effects models using lme4;Bates;J. Stat. Softw.,2015

3. Artificial neural networks and decision tree classification for predicting soil drainage classes in Denmark;Beucher;Geoderma,2019

4. ORYZA2000: Modelling Lowland Rice;Bouman,2001

5. Aprova o Zoneamento Agrícola de Risco Climático para a cultura de arroz irrigado tropical no Estado de Goiás;Brasil;Diário Of. [da] Rep. ública Fed. do Bras.,2020

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