Caio Canella Vieira Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Assistant Professor of Soybean Breeding

University of Arkansas at Fayetteville

faculty

13 h-index 89 pubs 562 cited

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Biography and Research Information

OverviewAI-generated summary

Caio Canella Vieira's research focuses on soybean breeding and genetics, with a particular emphasis on improving disease resistance and nutritional value. His work investigates methods to enhance soybean varieties for both food and feed applications, aiming to reduce antinutritional traits. Vieira has explored the genetic basis for resistance to specific diseases, such as Soybean mosaic virus, and has contributed to understanding the broader landscape of global disease resistance breeding in soybeans. He also examines the application of advanced technologies in breeding programs, including the use of Unmanned Aerial Vehicle (UAV) imagery and machine learning for phenotyping and yield prediction. This approach aims to improve the accuracy of progeny testing and line selection in soybean breeding. Vieira has a significant publication record, with 89 total publications and an h-index of 13, accumulating over 560 citations. He collaborates extensively with researchers at the University of Arkansas, including Pengyin Chen, Leandro Mozzoni, R. T. Robbins, and Liliana Florez‐Palacios.

Metrics

  • h-index: 13
  • Publications: 89
  • Citations: 562

Selected Publications

  • Registration of high yield conventional soybean ‘S17‐2193’ with resistance to multiple diseases (2025) DOI
  • Registration of ‘R19C‐1012’: A high‐yielding soybean cultivar with improved flooding tolerance at early vegetative stages (2025) DOI
  • Registration of R19‐42848 as a drought‐tolerant, high‐yielding soybean germplasm line (2025) DOI
  • Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials (2024) DOI
  • Across-environment seed protein stability and genetic architecture of seed components in soybean (2024) DOI
  • Registration of R18‐14147: A high‐protein conventional soybean germplasm line (2024) DOI
  • Registration of ‘S16‐16814R’: A glyphosate‐tolerant, high‐oleic soybean cultivar (2024) DOI
  • Using machine learning to integrate genetic and environmental data to model genotype-by-environment interactions (2024) DOI
  • Registration of R16‐45 as a flood‐tolerant, high‐yielding soybean germplasm line (2024) DOI
  • Registration of ‘S16‐16641R’: A glyphosate‐tolerant, high‐oleic soybean cultivar with multiple disease resistance (2024) DOI
  • Soybean genetics, genomics, and breeding for improving nutritional value and reducing antinutritional traits in food and feed (2023) DOI
  • Genetic architecture of soybean tolerance to off-target dicamba (2023) DOI
  • Registration of ‘S11‐17025C’ soybean: A high‐yielding and high‐oil conventional cultivar with broad resistance to diseases and nematodes (2023) DOI

Collaborators

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