CRCIL research teams completed three Sorghum Quick Win projects in Ethiopia and Senegal.
Ethiopia
The Drought Adaptation Enhancement Sorghum Quick Win Project in Ethiopia focused on enhancing local sorghum landraces for drought adaptation through genomic-enabled selection for maturity genes and stress-adaptive traits. The Ethiopian Institute of Agricultural Research’s Tokuma Guta led the project with assistance from Moira Sheehan and Meseret Wondifraw from Breeding Insight at Cornell University.
The project furthered previously funded work completed in partnership with other global experts and supported by U.S. government investments, including the previous Sorghum and Millet Innovation Lab, which was also based at Kansas State University.
The primary focus was on marker-based screening of a Multi-parent Advanced Generation Inter-Cross (MAGIC) population developed from local sorghum landraces for early flowering, maturity, and stress-adaptive traits.
The MAGIC panel was planted for generational advancement, and tissue samples were collected on the 100 MAGIC founder lines. These samples were shipped to CRCIL researchers at Cornell for whole-genome sequencing. Researchers identify alleles by genotyping the founder landraces and then conducting phenotypic evaluation of the progeny to pinpoint the specific regions of the DNA responsible for the desirable trait.
The impact of this project extends beyond the Quick Win. Researchers can continually study the resources developed for other climate resilience traits and use the data to create tools that accelerate the integration of favorable traits into already robust, widely used sorghum varieties.
U.S. farmers also face difficulties related to changing climate conditions. Identifying, validating, and transferring these alleles into the U.S. sorghum seed system will enable U.S. farmers to produce higher yields and meet the demand for sorghum.
Senegal
IRSA-CERAAS led a Sorghum Quick Win project aimed at enhancing sorghum's adaptation to environmental constraints in West Africa.
The project built upon work initiated by the former Sorghum and Millet Innovation Lab, which developed near-isogenic lines (NILs) for stay-green and striga resistance alleles. Using a marker-assisted backcross (MABC) selection, the NILs were generated from the West African Backcross-Nested Association Mapping Panel (BCNAM).
The project assessed 50 promising sorghum lines across multiple sites in Senegal–Babey, Roff, Darou, and Sinthiou—of which 25 included post-flowering drought-tolerant, stay green alleles and 25 contained the striga resistance (Lgs-I) allele.
These lines can be used directly in the sorghum breeding programs upon favorable performance reviews. CERAAS, a leader in regional cereal research, distributed the lines to partners in Burkina Faso, Niger, and Togo to conduct the same assessment, allowing for an even greater geographic impact for these climate-resilient traits.
Adapting sorghum to changing environmental conditions also benefits U.S. farmers. Developing stable, high-yielding varieties preferred by end users and adapted to different agro-ecological zones broadens U.S. farmers’ ability to grow sorghum successfully.
Crop modeling for sorghum was the focus of another Quick Win Project in Senegal. Researchers adapted an existing maize-based crop model for sorghum. Charlie Messina at the University of Florida and Modou Mbaye with ISRA-CERAAS led the project.
The project had three objectives:
- Activate a sorghum model tailored for CRCIL geographies and germplasm in West Africa.
- Build a simulation system to characterize the current and future Target Population of Environments (TPE), assess yield potentials, and quantify productivity and resiliency gaps.
- Demonstrate the utility of these tools for germplasm enhancement, specifically for sorghum in West Africa. These methods are already widely utilized in the maize industry in the US, Australia, and European countries.
The rates of genetic gain in sorghum in Africa are the lowest in the world, and sorghum is a critical crop across the continent. Unlocking the potential of sorghum across Sub-Saharan Africa has the potential to address food security and supply necessary resources for sorghum around the globe.
Breeding Gap Analysis (BGA) and Trait Profiling Assessment (TPA) will be used to understand the causes of slowed genetic gain and identify gaps between current and potential future yields.
The team made significant progress in implementing an information technology infrastructure to run models at scale on the University of Florida's supercomputer (HiPerGator), connecting with world experts in sorghum modeling, developing state-of-the-art methodologies for sorghum breeding, and undertaking field research to train models in Senegal.
The team utilized the Agricultural Production Systems sIMulator (APSIM) model because it had already been tested for the West Africa region, thereby saving both time and money. The BGA and TPA assessments can reveal the biophysical limits of sorghum production and identify management and breeding pathways that can help shift these limits to achieve greater yield production. The team in Senegal is conducting field trials needed to validate the crop simulation model.
Once validated, these crop models can be adapted for use in other geographic locations to develop sorghum growth models, which can be helpful for U.S. farmers.