Caio Canella Vieira Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor of Soybean Breeding
faculty
Crop, Soil and Environmental Sciences
14 h-index
89 pubs
612 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Caio Canella Vieira, Assistant Professor of Soybean Breeding at the University of Arkansas at Fayetteville, focuses on advancing soybean genetics and breeding. His research investigates the genetic underpinnings of disease resistance in soybean, with publications addressing global perspectives on this issue and specific research on Soybean mosaic virus resistance. Vieira also explores improving the nutritional quality of soybeans and reducing antinutritional traits. His work incorporates advanced methodologies, including the use of unmanned aerial vehicles (UAVs) and machine learning for high-throughput phenotyping and prediction accuracy in progeny testing and line selection. He has authored or co-authored 89 publications, with an h-index of 14 and 584 citations. Vieira collaborates extensively with researchers at the University of Arkansas, including Dongho Lee, Pengyin Chen, Leandro Mozzoni, and R. T. Robbins.
Metrics
- h-index: 14
- Publications: 89
- Citations: 612
Selected Publications
-
Registration of ‘S18PR‐190 HOLL’: A soybean cultivar with high oleic and low linolenic acid seed oil and multiple disease resistance (2026)
-
Registration of high yield conventional soybean ‘S17‐2193’ with resistance to multiple diseases (2025)
-
Registration of ‘R19C‐1012’: A high‐yielding soybean cultivar with improved flooding tolerance at early vegetative stages (2025)
-
Registration of R19‐42848 as a drought‐tolerant, high‐yielding soybean germplasm line (2025)
-
Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials (2024)
-
Across-environment seed protein stability and genetic architecture of seed components in soybean (2024)
-
Registration of R18‐14147: A high‐protein conventional soybean germplasm line (2024)
-
Registration of ‘S16‐16814R’: A glyphosate‐tolerant, high‐oleic soybean cultivar (2024)
-
Using machine learning to integrate genetic and environmental data to model genotype-by-environment interactions (2024)
-
Registration of R16‐45 as a flood‐tolerant, high‐yielding soybean germplasm line (2024)
-
Registration of ‘S16‐16641R’: A glyphosate‐tolerant, high‐oleic soybean cultivar with multiple disease resistance (2024)
-
Soybean genetics, genomics, and breeding for improving nutritional value and reducing antinutritional traits in food and feed (2023)
-
Genetic architecture of soybean tolerance to off-target dicamba (2023)
-
Registration of ‘S11‐17025C’ soybean: A high‐yielding and high‐oil conventional cultivar with broad resistance to diseases and nematodes (2023)
Collaboration Network
Top Collaborators
Henry T. Nguyen
University of Missouri (US)
30 shared publications
- Breeding for disease resistance in soybean: a global perspective
- Soybean genetics, genomics, and breeding for improving nutritional value and reducing antinutritional traits in food and feed
- Differentiate Soybean Response to Off-Target Dicamba Damage Based on UAV Imagery and Machine Learning
- A major quantitative trait locus resistant to southern root‐knot nematode sustains soybean yield under nematode pressure
- Registration of ‘S13‐3851C’ soybean as a high‐yielding conventional cultivar with high oil content and broad disease resistance and adaptation
Showing 5 of 30 shared publications
Dongho Lee
University of Arkansas at Fayetteville
27 shared publications
In database
- Breeding for disease resistance in soybean: a global perspective
- Soybean genetics, genomics, and breeding for improving nutritional value and reducing antinutritional traits in food and feed
- Decades of Genetic Research on Soybean mosaic virus Resistance in Soybean
- Registration of ‘S13‐3851C’ soybean as a high‐yielding conventional cultivar with high oil content and broad disease resistance and adaptation
- Exploring Machine Learning Algorithms to Unveil Genomic Regions Associated With Resistance to Southern Root-Knot Nematode in Soybeans
Showing 5 of 27 shared publications
Pengyin Chen
University of Missouri
25 shared publications
In database
- Breeding for disease resistance in soybean: a global perspective
- Decades of Genetic Research on Soybean mosaic virus Resistance in Soybean
- The numbers game of soybean breeding in the United States
- Incorporation of Soil-Derived Covariates in Progeny Testing and Line Selection to Enhance Genomic Prediction Accuracy in Soybean Breeding
- Differentiate Soybean Response to Off-Target Dicamba Damage Based on UAV Imagery and Machine Learning
Showing 5 of 25 shared publications
Mariola Usovsky
University of Missouri (US)
22 shared publications
- Decades of Genetic Research on Soybean mosaic virus Resistance in Soybean
- A major quantitative trait locus resistant to southern root‐knot nematode sustains soybean yield under nematode pressure
- Registration of ‘S13‐3851C’ soybean as a high‐yielding conventional cultivar with high oil content and broad disease resistance and adaptation
- Exploring Machine Learning Algorithms to Unveil Genomic Regions Associated With Resistance to Southern Root-Knot Nematode in Soybeans
- ‘S13‐1955C’: A high‐yielding conventional soybean with high oil content, multiple disease resistance, and broad adaptation
Showing 5 of 22 shared publications
Scotty Smothers
Delta Air Lines (United States) (US)
22 shared publications
- Registration of ‘S13‐3851C’ soybean as a high‐yielding conventional cultivar with high oil content and broad disease resistance and adaptation
- Registration of ‘S13‐2743C’ as a conventional soybean cultivar with high oil content, broad disease resistance, and high yield potential
- ‘S13‐1955C’: A high‐yielding conventional soybean with high oil content, multiple disease resistance, and broad adaptation
- Registration of ‘S16‐3747GT’: A high‐yielding determinate maturity group V soybean cultivar with broad biotic and abiotic stressors tolerance
- Identification of genomic regions associated with soybean responses to off-target dicamba exposure
Showing 5 of 22 shared publications
Melissa G. Mitchum
University of Georgia (US)
21 shared publications
- A major quantitative trait locus resistant to southern root‐knot nematode sustains soybean yield under nematode pressure
- Registration of ‘S13‐3851C’ soybean as a high‐yielding conventional cultivar with high oil content and broad disease resistance and adaptation
- Registration of ‘S13‐2743C’ as a conventional soybean cultivar with high oil content, broad disease resistance, and high yield potential
- ‘S13‐1955C’: A high‐yielding conventional soybean with high oil content, multiple disease resistance, and broad adaptation
- Registration of ‘S16‐3747GT’: A high‐yielding determinate maturity group V soybean cultivar with broad biotic and abiotic stressors tolerance
Showing 5 of 21 shared publications
Grover Shannon
University of Wisconsin–Extension (US)
21 shared publications
- Soybean genetics, genomics, and breeding for improving nutritional value and reducing antinutritional traits in food and feed
- A major quantitative trait locus resistant to southern root‐knot nematode sustains soybean yield under nematode pressure
- Registration of ‘S13‐3851C’ soybean as a high‐yielding conventional cultivar with high oil content and broad disease resistance and adaptation
- Exploring Machine Learning Algorithms to Unveil Genomic Regions Associated With Resistance to Southern Root-Knot Nematode in Soybeans
- Registration of ‘S13‐2743C’ as a conventional soybean cultivar with high oil content, broad disease resistance, and high yield potential
Showing 5 of 21 shared publications
Melissa Crisel
Delta Air Lines (United States) (US)
21 shared publications
- Registration of ‘S13‐3851C’ soybean as a high‐yielding conventional cultivar with high oil content and broad disease resistance and adaptation
- Registration of ‘S13‐2743C’ as a conventional soybean cultivar with high oil content, broad disease resistance, and high yield potential
- ‘S13‐1955C’: A high‐yielding conventional soybean with high oil content, multiple disease resistance, and broad adaptation
- Registration of ‘S16‐3747GT’: A high‐yielding determinate maturity group V soybean cultivar with broad biotic and abiotic stressors tolerance
- Registration of ‘S16‐5503GT’ soybean cultivar with high yield, broad adaptation, and glyphosate tolerance
Showing 5 of 21 shared publications
Michael Clubb
University of Missouri (US)
21 shared publications
- Registration of ‘S13‐3851C’ soybean as a high‐yielding conventional cultivar with high oil content and broad disease resistance and adaptation
- Registration of ‘S13‐2743C’ as a conventional soybean cultivar with high oil content, broad disease resistance, and high yield potential
- ‘S13‐1955C’: A high‐yielding conventional soybean with high oil content, multiple disease resistance, and broad adaptation
- Registration of ‘S16‐3747GT’: A high‐yielding determinate maturity group V soybean cultivar with broad biotic and abiotic stressors tolerance
- Registration of ‘S16‐5503GT’ soybean cultivar with high yield, broad adaptation, and glyphosate tolerance
Showing 5 of 21 shared publications
Md Liakat Ali
University of Missouri (US)
21 shared publications
- Registration of ‘S13‐3851C’ soybean as a high‐yielding conventional cultivar with high oil content and broad disease resistance and adaptation
- Registration of ‘S13‐2743C’ as a conventional soybean cultivar with high oil content, broad disease resistance, and high yield potential
- ‘S13‐1955C’: A high‐yielding conventional soybean with high oil content, multiple disease resistance, and broad adaptation
- Registration of ‘S16‐3747GT’: A high‐yielding determinate maturity group V soybean cultivar with broad biotic and abiotic stressors tolerance
- Registration of ‘S16‐5503GT’ soybean cultivar with high yield, broad adaptation, and glyphosate tolerance
Showing 5 of 21 shared publications
Clinton G. Meinhardt
University of Missouri (US)
21 shared publications
- Registration of ‘S13‐3851C’ soybean as a high‐yielding conventional cultivar with high oil content and broad disease resistance and adaptation
- Registration of ‘S13‐2743C’ as a conventional soybean cultivar with high oil content, broad disease resistance, and high yield potential
- ‘S13‐1955C’: A high‐yielding conventional soybean with high oil content, multiple disease resistance, and broad adaptation
- Registration of ‘S16‐3747GT’: A high‐yielding determinate maturity group V soybean cultivar with broad biotic and abiotic stressors tolerance
- Registration of ‘S16‐5503GT’ soybean cultivar with high yield, broad adaptation, and glyphosate tolerance
Showing 5 of 21 shared publications
Andrew Scaboo
University of Missouri (US)
19 shared publications
- Improve Soybean Variety Selection Accuracy Using UAV-Based High-Throughput Phenotyping Technology
- Registration of ‘S13‐3851C’ soybean as a high‐yielding conventional cultivar with high oil content and broad disease resistance and adaptation
- Registration of ‘S13‐2743C’ as a conventional soybean cultivar with high oil content, broad disease resistance, and high yield potential
- ‘S13‐1955C’: A high‐yielding conventional soybean with high oil content, multiple disease resistance, and broad adaptation
- Registration of ‘S16‐3747GT’: A high‐yielding determinate maturity group V soybean cultivar with broad biotic and abiotic stressors tolerance
Showing 5 of 19 shared publications
Leandro Mozzoni
University of Arkansas at Fayetteville
19 shared publications
In database
- Impact of flooding at the early reproductive growth stage on soybean yield and seed composition
- Across-environment seed protein stability and genetic architecture of seed components in soybean
- Registration of ‘S16‐3747GT’: A high‐yielding determinate maturity group V soybean cultivar with broad biotic and abiotic stressors tolerance
- Registration of ‘S16‐5503GT’ soybean cultivar with high yield, broad adaptation, and glyphosate tolerance
- ‘S16‐7922C’: A semi‐determinate maturity group IV conventional soybean cultivar with high yield and broad disease resistance
Showing 5 of 19 shared publications
Jason P. Bond
Southern Illinois University Carbondale (US)
18 shared publications
- Registration of ‘S13‐3851C’ soybean as a high‐yielding conventional cultivar with high oil content and broad disease resistance and adaptation
- Registration of ‘S13‐2743C’ as a conventional soybean cultivar with high oil content, broad disease resistance, and high yield potential
- ‘S13‐1955C’: A high‐yielding conventional soybean with high oil content, multiple disease resistance, and broad adaptation
- Registration of ‘S16‐3747GT’: A high‐yielding determinate maturity group V soybean cultivar with broad biotic and abiotic stressors tolerance
- Registration of ‘S16‐5503GT’ soybean cultivar with high yield, broad adaptation, and glyphosate tolerance
Showing 5 of 18 shared publications
Zenglu Li
University of Georgia (US)
17 shared publications
- A major quantitative trait locus resistant to southern root‐knot nematode sustains soybean yield under nematode pressure
- Exploring Machine Learning Algorithms to Unveil Genomic Regions Associated With Resistance to Southern Root-Knot Nematode in Soybeans
- Registration of ‘S16‐3747GT’: A high‐yielding determinate maturity group V soybean cultivar with broad biotic and abiotic stressors tolerance
- Registration of ‘S16‐5503GT’ soybean cultivar with high yield, broad adaptation, and glyphosate tolerance
- ‘S16‐7922C’: A semi‐determinate maturity group IV conventional soybean cultivar with high yield and broad disease resistance
Showing 5 of 17 shared publications
Similar Researchers
Based on overlapping research topics
Pengyin Chen
University of Arkansas at Fayetteville
Soybean genetics and cultivation
Plant breeding
Genomics and Phylogenetic Studies
Dongho Lee
University of Arkansas at Fayetteville
Soybean genetics and cultivation
Genomics and Phylogenetic Studies
Machine Learning Applications
Cunxiang Wu
University of Arkansas at Fayetteville
Soybean genetics and cultivation
Genomics and Phylogenetic Studies
Plant Stress Responses and Tolerance
Richard E. Mason
University of Arkansas at Fayetteville
Genomics and Phylogenetic Studies
Machine Learning Applications
Plant Stress Responses and Tolerance
Samuel B. Fernandes
University of Arkansas at Fayetteville
Genomics and Phylogenetic Studies
Machine Learning Applications
Plant Stress Responses and Tolerance
M. P. da Silva
University of Arkansas at Fayetteville
Soybean genetics and cultivation
Genomics and Phylogenetic Studies
Plant Stress Responses and Tolerance