Plant Breeding
Available Languages:
English
Plant breeding is the science of genetically improving plants for the benefit of humankind. [AGROVOC]
Narrower Topics
Related Topics: Strawberries, Plant Breeding
Publications
Tropical Foliage Plant Development: Origin of New Cultivars
R. J. Henny and J. Chen
Tropical Foliage Plant Development: Breeding Techniques for Anthurium and Spathiphyllum
R.J. Henny, J. Chen, and T. A. Mellich
Tropical Foliage Plant Development: Breeding Techniques for Aglaonema and Dieffenbachia
R.J. Henny, J. Chen and T.A. Mellich
Multi-Cavity Collection: A Method for Sampling Bulk Solutions from Plug Media
Jianjun Chen, Yangfeng Huang, Cynthia A. Robinson, and Russell D. Caldwell
The UF/IFAS Strawberry Clean Plant Program
Catalina Moyer, Natalia A. Peres, andVance M. Whitaker
Florida strawberry growers primarily utilize cultivars developed by the UF/IFAS Strawberry Breeding Program. These cultivars are bred to provide the yield and quality traits needed by the Florida industry. Yet if a new cultivar has the traits that Florida growers need but pathogen-tested planting stock is not available to growers, the cultivar’s impact will be limited. The Clean Plant Program generates the pathogen-tested planting stock that nurseries and growers require.
Caladium Cultivars Developed at the UF/IFAS
Zhanao Deng, Brent Harbaugh, andBrent K. Harbaugh
A Beginner’s Guide to Begonias: Hybridization and the Gateway to a New World in Its Breeding
Wisnu Ardi, Tao Jiang, andHeqiang Huo
Begonia spp. is one of the most diverse and popular ornamental plant groups, with over 2,000 species and hybrids valued for their foliage, flowers, and adaptability. Florida’s climate and horticultural industry make it a center for begonia production, yet practical guidance on hybridization remains limited. This publication provides a clear, step-by-step introduction to hybrid breeding for horticultural professionals, advanced gardeners, and researchers. Topics include basic genetics, selecting parent plants for desirable traits, pollination techniques to control crosses, and potential challenges. Methods for seed collection, germination, and hybrid evaluation are outlined with emphasis on assessing ornamental quality and stress resistance. Case studies from UF/IFAS breeding programs highlight successful crosses. This guide bridges science and practice to advance Begonia breeding for Florida and beyond.
Improving Strawberry Varieties by Somaclonal Variation
Cheol-Min Yoo, Cheryl Dalid, Catalina Moyer, Vance M. Whitaker, andSeonghee Lee
Somaclonal variation is a breeding method utilizing natural genetic variation induced by a tissue culture process instead of by hybridization. This offers an alternative to mutation breeding for the introduction of new genetic variations in existing strawberry varieties. The main purpose of this new 5-page publication of the UF/IFAS Horticultural Sciences Department is to share the potential of this technique with plant breeders in the public and private industries. The secondary purpose is to educate the industry and the public on the scientific background of somaclonal variation. Written by Cheol-Min Yoo, Cheryl Dalid, Catalina Moyer, Vance Whitaker, and Seonghee Lee.
Current Status of Research, Regulations, and Future Challenges for CRISPR Gene Editing in Crop Improvement
Sadikshya Sharma, Kaitlyn Vondracek, Heqiang Huo, Tie Liu and Seonghee Lee
A UF/IFAS numbered peer reviewed Fact Sheet. in support of UF/IFAS Extension program: Citizen awareness of food systems and the environment
PhenoSnap: An AI-Powered Web Application for Automated Specialty Crop Trait Extraction
Santhi Daggubati, Xu Wang, Xue Zhou, Shubham Singh, andJessica Chitwood-Brown
Manual quantification of specialty crop traits, such as flowers and fruits, is often labor-intensive, time-consuming, and inconsistent, limiting scalability and precision. We present PhenoSnap, an artificial intelligence (AI)-powered web application that provides an intuitive and efficient interface for automated specialty crop trait extraction from images. PhenoSnap bridges the gap between advanced computer vision technologies and practical agricultural applications by eliminating the need for programming expertise. This ready-to-use solution can enable growers, breeders, and Extension faculty to accelerate field work and enhance decision-making related to strawberry and tomato yield estimation for breeding selections and strawberry runner management. Written by Santhi Daggubati, Xu Wang, Xue Zhou, Shubham Singh, and Jessica Chitwood-Brown, and published by the UF/IFAS Department of Agricultural and Biological Engineering, June 2026.