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Confirmed
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-08-15
S
Samuel B. Fernandes
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor
Also affiliated: Universidade Federal de Lavras (2016); United States Department of Agriculture (2025); Illinois Department of Natural Resources (2021); University of Illinois Urbana-Champaign (2017–2022); Urbana University (2017); University of Arkansas System (2023–2026); University of Illinois System (2021); Carnegie Department of Plant Biology (2018); Center for Genomic Science (2018–2019); HUN-REN Centre for Agricultural Research (2026); Institute of Crop Science (2019); Arkansas Department of Agriculture (2026); Goodwin College (2021–2022)
Faculty Researcher
Center for Agricultural Data Analytics
14 h-index
75 pubs
1,031 cited
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Samuel B. Fernandes investigates the genetic basis of plant traits, focusing on quantitative genetics and genome-wide association studies (GWAS). His work utilizes machine learning for advanced phenotyping, enabling the analysis of complex traits related to water use efficiency and photosynthetic efficiency in crops such as sorghum and maize. He has explored the evolutionary genetics of deleterious load in these species and employed optical topometry and thermal imaging for trait measurement. Fernandes also applies machine learning to predict maize grain yield by integrating genetic and environmental data. His research network includes collaborators like Igor Kuivjogi Fernandes, Mike Daniels, Gerson Laerson Drescher, and Kristofor R. Brye, all at the University of Arkansas at Fayetteville. Fernandes holds an h-index of 14 with over 1,000 citations across his 74 publications.
Metrics
- h-index: 14
- Publications: 75
- Citations: 1,031
Selected Publications
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Assessing Malted and Adjunct Rice Potential in Diverse Rice Germplasm through Simulated Enzymatic Hydrolysis (2026)
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Dissecting genetic variance structure and evaluating genomic prediction models for single-cross hybrids derived from Stiff Stalk and Non-Stiff Stalk maize heterotic groups (2026)
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An efficient strategy for genomic prediction in new locations via enviromic indexing (2026)
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Modeling genotype‐by‐environment interaction for variety recommendation in tropical wheat (2026)
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Dissecting genetic variance structure and evaluating genomic prediction models for single-cross hybrids derived from Stiff Stalk and Non-Stiff Stalk maize heterotic groups (2026)
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Nonlinear genomic selection index accelerates multi-trait crop improvement (2026)
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Optimizing population simulations to accurately parallel empirical data for digital breeding (2026)
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High‐Throughput Screen of <scp>NPQ</scp> in Sorghum Shows Highly Polygenic Architecture of Photoprotection (2026)
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Leaf-level hyperspectral reflectance on the WEST and TERRA-MEPP biomass sorghum diversity panel (2025)
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Leaf-level hyperspectral reflectance on the WEST and TERRA-MEPP biomass sorghum diversity panel (2025)
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Replication Data for: Nonlinear Genomic Selection Index Accelerates Multi-Trait Crop Improvement (2025)
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Fluridone use in furrow-irrigated rice: Palmer amaranth control and crop response (2025)
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Genomic prediction and association mapping of early season flood tolerance in soybean (2025)
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Biochar type and rate effects on greenhouse gas emissions from furrow‐irrigated rice (2025)
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Improving Multi-Trait Genomic Prediction Efficiency Through The Incorporation Of Synthetic Traits Selected Based on Co-heritability (2025)
Collaboration Network
Top Collaborators
Alexander E. Lipka
University of Illinois Urbana-Champaign (US)
10 shared publications
- Importance of genetic architecture in marker selection decisions for genomic prediction
- Linking genetic and environmental factors through marker effect networks to understand trait plasticity
- Linking genetic and environmental factors through marker effect networks to understand trait plasticity
- Importance of genetic architecture in marker selection decisions for genomic prediction
- High throughput screen of NPQ in sorghum shows highly polygenic architecture of photoprotection
Showing 5 of 10 shared publications
Martin Bohn
University of Illinois Urbana-Champaign (US)
7 shared publications
- Importance of genetic architecture in marker selection decisions for genomic prediction
- Linking genetic and environmental factors through marker effect networks to understand trait plasticity
- Linking genetic and environmental factors through marker effect networks to understand trait plasticity
- Importance of genetic architecture in marker selection decisions for genomic prediction
- Optimizing population simulations to accurately parallel empirical data for digital breeding
Showing 5 of 7 shared publications
Rafael Della Coletta
University of Minnesota System (US)
5 shared publications
- Importance of genetic architecture in marker selection decisions for genomic prediction
- Linking genetic and environmental factors through marker effect networks to understand trait plasticity
- Linking genetic and environmental factors through marker effect networks to understand trait plasticity
- Importance of genetic architecture in marker selection decisions for genomic prediction
- Optimizing population simulations to accurately parallel empirical data for digital breeding
Mark A. Mikel
University of Illinois Urbana-Champaign (US)
5 shared publications
- Importance of genetic architecture in marker selection decisions for genomic prediction
- Linking genetic and environmental factors through marker effect networks to understand trait plasticity
- Linking genetic and environmental factors through marker effect networks to understand trait plasticity
- Importance of genetic architecture in marker selection decisions for genomic prediction
- Dissecting genetic variance structure and evaluating genomic prediction models for single-cross hybrids derived from Stiff Stalk and Non-Stiff Stalk maize heterotic groups
Candice N. Hirsch
University of Minnesota (US)
5 shared publications
- Importance of genetic architecture in marker selection decisions for genomic prediction
- Linking genetic and environmental factors through marker effect networks to understand trait plasticity
- Linking genetic and environmental factors through marker effect networks to understand trait plasticity
- Importance of genetic architecture in marker selection decisions for genomic prediction
- Optimizing population simulations to accurately parallel empirical data for digital breeding
Trenton L. Roberts
University of Arkansas at Fayetteville
4 shared publications
In database
- Potassium losses in runoff from cotton production fields
- Biochar type and rate effects on greenhouse gas emissions from furrow‐irrigated rice
- Near-Surface Soil Chemical Properties as Affected by Cover Crops Over Time in the Lower Mississippi River Valley
- Fluridone use in furrow-irrigated rice: Palmer amaranth control and crop response
Filipe Manoel Ferreira
Universidade Estadual Paulista (Unesp) (BR)
3 shared publications
- A novel strategy to predict clonal composites by jointly modeling spatial variation and genetic competition
- Realized genetic gain with reciprocal recurrent selection in a Eucalyptus breeding program
- A data-driven approach for enhancing forest productivity by accounting for indirect genetic effects
Saulo Fabrício da Silva Chaves
Universidade Federal de Viçosa (BR)
3 shared publications
- A novel strategy to predict clonal composites by jointly modeling spatial variation and genetic competition
- Realized genetic gain with reciprocal recurrent selection in a Eucalyptus breeding program
- A data-driven approach for enhancing forest productivity by accounting for indirect genetic effects
Rodrigo Silva Alves
3 shared publications
- A novel strategy to predict clonal composites by jointly modeling spatial variation and genetic competition
- Realized genetic gain with reciprocal recurrent selection in a Eucalyptus breeding program
- A data-driven approach for enhancing forest productivity by accounting for indirect genetic effects
Elizabete Keiko Takahashi
3 shared publications
- A novel strategy to predict clonal composites by jointly modeling spatial variation and genetic competition
- Realized genetic gain with reciprocal recurrent selection in a Eucalyptus breeding program
- A data-driven approach for enhancing forest productivity by accounting for indirect genetic effects
Kaio Olímpio das Graças Dias
Universidade Federal de Viçosa (BR)
3 shared publications
- A novel strategy to predict clonal composites by jointly modeling spatial variation and genetic competition
- Using machine learning to integrate genetic and environmental data to model genotype-by-environment interactions
- A data-driven approach for enhancing forest productivity by accounting for indirect genetic effects
John N. Ferguson
University of Essex (GB)
3 shared publications
- High throughput screen of NPQ in sorghum shows highly polygenic architecture of photoprotection
- Improving Multi-Trait Genomic Prediction Efficiency Through The Incorporation Of Synthetic Traits Selected Based on Co-heritability
- High‐Throughput Screen of <scp>NPQ</scp> in Sorghum Shows Highly Polygenic Architecture of Photoprotection
Sharon E. Liese
University of Illinois Urbana-Champaign (US)
2 shared publications
- Linking genetic and environmental factors through marker effect networks to understand trait plasticity
- Linking genetic and environmental factors through marker effect networks to understand trait plasticity
Patrick J. Monnahan
University of Minnesota (US)
2 shared publications
- Importance of genetic architecture in marker selection decisions for genomic prediction
- Importance of genetic architecture in marker selection decisions for genomic prediction
Mike Daniels
University of Arkansas at Fayetteville
2 shared publications
In database
- Potassium losses in runoff from cotton production fields
- Biochar type and rate effects on greenhouse gas emissions from furrow‐irrigated rice
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