Author

David Henriques da Matta

Universidade Federal de GoiásORCID 0000-0003-0199-2075Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Alexandre Bryan HeinemanniD· 2 shared Germano Costa‐NetoiD· 2 shared Igor Kuivjogi FernandesiD· 2 shared L. F. StoneiD· 1 shared Roberto Fritsche‐NetoiD· 1 shared

Activity by Year

2022-2022 · peak 2/yr

Co-Author Collaboration Network

5 top collaborators · 9 mutual co-author links

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2 shared papersGenetics

Alexandre Bryan HeinemannORCID

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2 papers

Recent·Most cited

GeneticsField Crops ResearchPeer-reviewedJul 16, 2022

Enviromic prediction is useful to define the limits of climate adaptation: A case study of common beans in Brazil

Alexandre Bryan Heinemann, Germano Costa‐Neto, Roberto Fritsche‐Neto…·Igor Kuivjogi Fernandes

This paper develops an enviromic prediction approach using GAM to analyze climate impacts on common bean yield in Brazil, identifying key environmental drivers and optimal conditions for different regions and seasons.

42 citationstop 5%

statistical modelbenchmarking

𝕏 PostBluesky

GeneticsbioRxivPreprintJun 2, 2022

Data-driven machine learning for pattern recognition supports environmental quality prediction for irrigated rice in Brazil

Germano Costa‐Neto, David Henriques da Matta, Igor Kuivjogi Fernandes…·Alexandre Bryan Heinemann

The paper uses machine learning to predict environmental quality for irrigated rice in Brazil by clustering yield data and analyzing genotype-environment interactions.

1 citation

machine learning (classical)benchmarking

𝕏 PostBluesky