Match tier
Confirmed
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-10-05
S
Samuel B. Fernandes
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor
Also affiliated: Universidade Federal de Lavras (2016); University of Illinois Urbana-Champaign (2017–2022); University of Arkansas System (2024–2026); University of Illinois System (2021); Carl R. Woese Institute for Genomic Biology (2018–2021)
Center for Agricultural Data Analytics
15 h-index
77 pubs
1,068 cited
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Samuel B. Fernandes is an Assistant Professor at the University of Arkansas at Fayetteville's Center for Agricultural Data Analytics. His research focuses on applying genomic and machine learning approaches to plant breeding and genetics, particularly in sorghum and maize. Fernandes investigates methods for improving crop traits such as water use efficiency, biomass yield, and architectural characteristics through genomic selection and genome-wide association studies (GWAS). His work utilizes advanced phenotyping techniques, including optical topometry and thermal imaging, often integrated with machine learning algorithms to accelerate trait evaluation. He has published research on comparative evolutionary genetics, exploring deleterious mutation load in crop species, and has developed novel Bayesian network models for predicting developmental traits. Fernandes's scholarship metrics include an h-index of 15, with 77 total publications and over 1,000 citations.
Metrics
- h-index: 15
- Publications: 77
- Citations: 1,068
Positions
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Assistant Professor 2022–presentUniversity of Arkansas at Fayetteville Crop, Soil, and Environmental Sciences ORCID
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Postdoctoral Researcher 2017–2022University of Illinois at Urbana-Champaign Institute for Genomic Biology ORCID
Selected Publications
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Reduced tillage and cover crop treatment effects on growing-season greenhouse gas emissions from a soybean-corn rotation on silt-loam soil in southeast Arkansas (2026)
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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 NPQ 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)
Collaboration Network
Top Collaborators
Alexander E. Lipka
University of Illinois Urbana-Champaign (US)
11 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
- Improving Multi-Trait Genomic Prediction Efficiency Through The Incorporation Of Synthetic Traits Selected Based on Co-heritability
Showing 5 of 11 shared publications
Martin Bohn
University of Illinois Urbana-Champaign (US)
8 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 8 shared publications
Candice N. Hirsch
University of Minnesota (US)
8 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 8 shared publications
Mark A. Mikel
University of Illinois Urbana-Champaign (US)
6 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
Showing 5 of 6 shared publications
Rafael Della Coletta
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
Kaio Olímpio das Graças Dias
Universidade Federal de Viçosa (BR)
4 shared publications
- Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials
- 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
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
Celulose Beira Industrial (Portugal) (PT)
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
Celulose Beira Industrial (Portugal) (PT)
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
Caio Canella Vieira
United States Department of Agriculture
3 shared publications
In database
- Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials
- Using machine learning to integrate genetic and environmental data to model genotype-by-environment interactions
- Genomic prediction and association mapping of early season flood tolerance in soybean
Kristofor R. Brye
University of Arkansas at Fayetteville
3 shared publications
In database
- 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
- Reduced tillage and cover crop treatment effects on growing-season greenhouse gas emissions from a soybean-corn rotation on silt-loam soil in southeast Arkansas
John N. Ferguson
University of Essex (GB)
3 shared publications
- Improving Multi-Trait Genomic Prediction Efficiency Through The Incorporation Of Synthetic Traits Selected Based on Co-heritability
- High‐Throughput Screen of NPQ in Sorghum Shows Highly Polygenic Architecture of Photoprotection
- High throughput screen of NPQ in sorghum shows highly polygenic architecture of photoprotection
Andrew D. B. Leakey
University of Illinois Urbana-Champaign (US)
3 shared publications
- Improving Multi-Trait Genomic Prediction Efficiency Through The Incorporation Of Synthetic Traits Selected Based on Co-heritability
- Leaf-level hyperspectral reflectance on the WEST and TERRA-MEPP biomass sorghum diversity panel
- Leaf-level hyperspectral reflectance on the WEST and TERRA-MEPP biomass sorghum diversity panel
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