We are providing genetic solutions using state-of-the-art phenomics, breeding and genomics tools to Iowa farmers that meet their on-farm requirements and help improve profitability. We develop varieties that addresses their on-farm production issues, and develop unique genetic resources that are desirable to the private industry and indirectly benefit Iowa farmers. Market ready cultivars provide another opportunity for IA farmers as we combine high yield, quality with disease and abiotic stress tolerance. These also provides additional competitiveness in the seed industry. This project will build on existing breeding network at ISU. This funding is enabling graduate students to work on innovative technology driven breeding projects integrating phenomics and genomics in breeding. Seed and tech companies actively recruits our students due to their cross-disciplinary training and expertise.

The main objectives of this project are to (1) increase soybean seed yield using genetic and phenomics tools, (2) improve seed quality (develop clear hilum, high oleic, high sucrose, improved oil and meal) varieties for increased market capture, and (3) develop breeding population to improve protection traits (biotic and abiotic stress tolerance). We will focus on infusion of engineering and data analytic tools, as well as work with a larger population pool.

Develop new soybean varieties.
Commercialize new varieties.
Develop workforce in soybean breeding and production research.

Updated September 5, 2025:
In the reporting period, a safe and successful harvest was completed in the fall of 2024. Post-harvest, seed processing, and trait data acquisition were also completed in late fall and winter. Selection decisions on advancements were made. Additionally, plant material was sent to the winter nursery to get the second crop cycle. Preparations for 2025 planting were initiated, and at the time of reporting, packaging for 2025 is in full swing.

Major highlights:
(a) Variety release: Eight soybean varieties were disclosed to ISURF. These have shown merit for release due to their combination of high yield, disease resistance (SDS, white mold), abiotic stress tolerance (flooding), SCN resistance (including Peking source), and higher seed oil. Foundation seed of most will commence in 2025.

IAS25C2 is a maturity group 2.5 conventional yellow hilum soybean with high yield and PI88788 source of soybean cyst nematode resistance (SCN). It has high yield performance across multiple states.
IAS27C3 is a mid to late maturity group 2 conventional soybean with high yield.
IAS29C1 is a late maturity group 2 conventional soybean with high yield, PI88788 SCN resistance, good tolerance to sudden death syndrome and white mold, good standability, and good tolerance to waterlogging conditions. It has resistance to soybean aphid biotype 1 (Rag2), and molecular marker data indicates Rps1k for phytophthora root resistance.
IAS29C3 is a late maturity group 2 conventional soybean with high yield, SCN resistance (Hg Type 2.5.7) and seed oil ~24% (dry weight basis). Molecular marker data indicated Peking source of SCN resistance.
IAS29C4 is a late maturity group 2 conventional soybean with high yield, SCN resistance and seed oil ~24% (dry weight basis). Molecular marker data indicate Peking source of SCN resistance.
IAS32C1 is an early maturity group 3 conventional soybean with high yield, Peking source of SCN resistance, and SDS resistance.
IAS31C2 is an early maturity group 3 conventional soybean. It combines high seed yield, good standability, resistance to sudden death syndrome and white mold diseases, flooding tolerance and “Peking” SCN resistance. It has higher seed oil ~24% (dry weight basis).
IAS34C1 is a high yielding, mid-maturity group 3 conventional soybean with resistance to soybean cyst nematode from Peking source.

(b) Research publications

Book Chapter

Singh, A.K., Jones, S.E., Van der Laan, L., Ayanlade, T., Raigne, J., Saleem, N., Joshi, S., Arshad, M.A., ZareMehrjerdi, H., Rairdin., Di Salvo, J., Elango, D., De Azevedo Peixoto, L., Jubery, T.Z., Krishnamurthy, A., Singh, A., Sarkar, S., Ganapathysubramanian, B. 2025. Chapter five - Use of artificial intelligence in soybean breeding and production. In Sparks, D. (eds.) Advances in Agronomy. 190 (2025). Academic Press. pp. 199-273.
Singh AK et al. (2021). High throughput phenotyping in soybean. In “High-throughput Crop Phenotyping” Eds. J. Zhou, H. Nguyen. Springer-Nature.
Ayanlade T, SE Jones, LV der Laan, S Chattopadhyay, D Elango, J Raigne, A Saxena, A Singh, B Ganapathysubramanian, AK Singh, S Sarkar. 2024. Multi-modal AI for Ultra-precision Agriculture. Chapter 2 In Harnessing Data Science for Sustainable Agriculture and Natural Resource Management." Springer Nature. Publication date: Dec 20, 2024.pp299-334.
Journal research and review papers

Feng J, SW Blair, TT Ayanlade, A Balu, B Ganapathysubramanian, A Singh, S Soumik, AK Singh. 2025. Robust soybean seed yield estimation using high-throughput ground robot videos. Frontiers in Plant Science. v16. DOI=10.3389/fpls.2025.1554193
Krause MD, KOG Dias, AK Singh, WD Beavis. 2025. Using soybean historical field trial data to study genotype by environment variation and identify mega-environments with the integration of genetic and non-genetic factors. Volume117, Issue1. e70023
Van der Laan L, K Parmley, M Saadati, HT Pacin, S Panthulugiri, B Ganapathysubramanian, S Sarkar, A Lorenz, AK Singh. 2025. Genomic and Phenomic Prediction for Soybean Seed Yield, Protein, and Oil. The Plant Genome. DOI: 10.1002/tpg2.70002
Ganapathysubramanian B, S Sarkar, A Singh, AK Singh. (2025). Digital twins for the plant sciences. Trends in Plant Science. Online 9th Jan, 2025.
Chiranjeevi S, M Saadati, ZK Deng, J Koushik, TZ Jubery, D Mueller, ME O'Neal, N Merchant, A Singh, AK Singh, Soumik Sarkar, Arti Singh, Baskar Ganapathysubramanian. (2024). PNAS Nexus. Page575.
Jones SE, TT Ayanlade, B Fallen, TZ Jubery, A Singh, B Ganapathysubramanian, S Sarkar, AK Singh. (2024). Multi-sensor and multi-temporal high-throughput phenotyping for monitoring and early detection of water-limiting stress in soybean. The Plant Phenome Journal. V7(1) e70009. Dec, 2024.
Fotouhi F, K Menke, A Prestholt, A Gupta, ME Carroll, H-J Yang, EJ Skidmore, M O’Neal, N Merchant, SK Das, P Kyveryga, B Ganapathysubramanian, AK Singh, A Singh, Soumik Sarkar. (2024). Persistent monitoring of insect-pests on sticky traps through hierarchical transfer learning and slicing-aided hyper inference. Front. Plant Sci., Sec. Sustainable and Intelligent Phytoprotection. v15.
Singh AK, D Elango, J Raigne, L Van der Laan, A Rairdin, C Soregaon, A. Singh. (2024) Plant-based protein crops and their improvement: Current status and future perspectives. Crop Science. V65(1): e21389.
Also, three conference papers were published.

(c) Graduate student researchers: Liza Van Der Laan and Sarah Jones completed their Ph.D. degrees. Liza worked on soybean heat stress and seed quality traits project. Sarah worked on soybean drought trait. Their results were utilized in the breeding pipeline. Sam Blair and Joscif Raigne completed their M.S. degrees. Sam worked on drone and robot based phenotyping for seed yield prediction and crop maturity using automated tools. Joscif worked on soybean residue trait. Joscif is pursuing a Ph.D. degree in the group. Juan Di Salvo completed his M.S. degree and joined as a Ph.D. student working on cold stress traits. Currently, six graduate students are working on soybean related topics. For example, drone and satellite based phenotyping, cold stress tolerance, prescriptive breeding, flooding stress, screening for heat-drought-flooding in specialized systems, crop physiology and modelling.

The technology developed from this project, including varieties, germplasm, phenomic tools, phenotyping and screening methods will help the Iowa farmers, private and public breeders, and research community looking for outputs on increased yield, protection traits, and seed quality. Varieties developed for this project are dual purpose: generic and food grade therefore create and cater to a premium paying market. ISU varieties provide a seed cost advantage due to their lower price, and yield competitiveness with commercial varieties. The ISU lines are tested or used under licensing agreements by small or large seed companies for breeding applications or direct commercialization. Soybean varieties can be converted to any traited technology, such as herbicide tolerance. Our varieties have been actively taken up by Iowa and mid-western seed companies through material transfer agreements and licensing agreements. We prepare high caliber workforce to work as breeders and scientist in seed, chemical and agricultural companies. ISA funding is also bringing in other investments through research funding agencies, including new partnership projects between our team and ISA, which benefits ISA and ISU to advance farmer interests and profitability.