Potato Breeding at UF
Potato producers in Florida face uniquely challenging climate conditions compared to growing regions in the Midwest. As Florida's 5th largest vegetable crop, there is a significant need for elite locally-adapted potato varieties. Our program is working to produce robust Florida-adapted varieties for both processing and table potato markets, by leveraging a combination of traditional and advanced breeding techniques.
Breeding potatoes adapted to Florida's climate condition
Our program contains two major breeding groups: chipping potatoes and table potatoes (reds, yellows, and russets). Traditional breeding goals for each group includes yield, tuber specific gravity, disease and pest resistance, and environment adaptation. For a Florida-specific market, in addition to general adaptability, we are targeting two key areas:
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Tolerance to heat stress​
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Increased nutrient utilization efficiency (NUE), specifically for nitrogen and phosphorous
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Integration of advanced tools into potato breeding pipeline
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The traditional plant breeding cycle, that is phenotyping, selection, and crossing, is still the core of modern breeding programs. However, new methods and technology can greatly optimize and streamline this process. As our program grows, there are several advanced plant breeding tools that we are working to integrate:
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Genomic selection
Utilizes genetic markers, pedigrees, and parental phenotypic observations to predict progeny phenotypes. Genomic selection allows us to make selections prior to in-field evaluations, reducing operational costs and accelerating the breeding cycle.
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Crop modeling
Dynamic models that use several predictor variables including weather and soil data, management practices, crop species and cultivar, and collected experimental data to predict future performance.
A potato plant divided in five main components: petioles, stems, roots, tubers, and leaves. By tracking the mass of each component throughout a growing season, we can generate time series growth curves representative of our specific environment and genotypes to increase accuracy of crop growth models. In turn, these models are used in analyzing and predicting performance in our target environment and crop.
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Phenotyping via imagery
At the end of the day, our main goal is to develop varieties that consistently produce a desired phenotype. Aerial images collected using drones can allow for rapid high-quality phenotyping of agronomic traits while greatly reducing manpower. Additionally, phenotyping can be done at a farm, field, or even small plot level. Currently, we are developing pipelines to use this technology to phenotype for traits such as biomass and associate it with yield.
