CFCRA Soybean Cluster: Activity 7 – Breeding of high yielding resistance & value-added soybean using elite and exotic germplasm
Principal Investigator: Istvan Rajcan
Research Institution: University of Guelph
Objectives:
- Develop food grade, non-genetically modified (non-GM) soybean varieties for maturity groups (MG) 00 to 1, with enhanced yields, enhanced value and market opportunities, improved genetic resistance to soybean cyst nematode (SCN), and improved resistance to white mould.
Impacts:
- The development and release of highly productive and disease resistant soybean cultivars to the seed industry allows farmers to remain competitive in the non-GM soybean global market.
- The introduction of genetic diversity to Canadian soybeans by hybridizing elite Canadian cultivars with elite Chinese cultivars will offset the danger of narrow genetic variation in Canadian soybean.
- The development of soybean cyst nematode (SCN) resistant soybean cultivars allows farmers to combat the rapid spread and economic damages that SCN poses to soybean production in Ontario.
- The improved understanding of genetic control of soyasaponins as compounds with antioxidant and anti-cancerous attributes, naturally found in soybean seeds, may lead to the development of healthy soyasaponin-enhanced soybean cultivars in the future.
Scientific Summary:
This activity developed food grade, non-GM soybean varieties with increased yields, disease resistance, and desired market traits for maturity group (MG) 1-00 growing regions. The new soybean varieties were developed to have the following characteristics:
- Enhanced yield, incorporating new alleles from elite Canadian and exotic sources such as the elite and modern Chinese varieties using molecular breeding and genomic tools.
- Enhanced value and market opportunities for value-added markets including improved tofu and soymilk properties, higher sucrose content, saponin, isoflavones, and modified oil profiles for the healthy foods and bio-products markets.
- Improved genetic resistance to soybean cyst nematode (SCN) using new SCN resistance sources, beyond the common source of resistance, P188788.
- Improved resistance to white mould using genomic approaches.
Results:
During the project, the soybean breeding program on the Guelph campus of the University of Guelph developed 23 high yielding soybean cultivars as follows: OAC Bounty (2019), OAC Cooper (2019), OAC Acclaim (2019), OAC Bryce (2020), OAC Hastings (2020), OAC Shine (2020), OAC Dawn (2020), OAC Casey (2020), OAC Malory (2020), OAC Elevation (2020), OAC Candy (2020), OAC Glaze (2020), OAC Dunkel (2020), OAC Aberdeen (2021), OAC Attika (2021), OAC Almond (2021), OAC Kamran (2021), OAC Rush (2021), OAC Ambrose (2022), OAC Carson (2022), OAC Bruno (2022), OAC Moria (2022), OAC Kyiv (2023). Of these, three varieties are resistant to SCN. Refer to the table below for variety descriptions.
Variety | Licensed to | MG | Description |
OAC Rush | SeCan | 1.0 | SCN resistant food grade variety with very strong yield levels for its maturity |
OAC Kamran | SeCan | 0.6 | Food grade variety with imperfect yellow hilum, excellent standability, SCN resistance, and moderately tolerant rating to Phytophthora root rot. Competitive combination of yield and protein levels for growers and IP exporters |
OAC Aberdeen | Huron Commodities | 1.6 | High yielding food grade variety with imperfect yellow hilum and SCN resistance |
OAC Attika | CanGro Genetics | 0.4 | High yielding food grade variety with imperfect yellow hilum |
OAC Almond | CanGro Genetics | 0.1 | High yielding food grade variety with imperfect yellow hilum |
OAC Bryce | SeCan | 0.8 | Food grade variety with imperfect yellow hilum and strong yield levels for lower protein, non-GMO markets |
OAC Hastings | SeCan | 0.5 | Food grade variety with imperfect yellow hilum and slightly later maturity than OAC Strive |
OAC Shine | SeCan | 0.5 | Food grade variety with strong seed protein levels (44.3%) |
OAC Dawn | SeCan | 0.8 | Light brown hilum conventional soybean with strong protein content and competitive yield levels |
OAC Casey | SeCan | 0.9 | Food grade variety with imperfect yellow hilum and good field tolerance to Phytophthora root rot |
OAC Malory | SeCan | 1.0 | Yellow hilum food grade variety with SCN resistance. Slightly shorter maturing than OAC Avatar with higher protein levels and comparable seed size |
OAC Elevation | SeCan | 1.3 | Imperfect yellow hilum food grade variety with large seed size, strong yields and high protein levels (44%) |
OAC Cooper | CanGro Genetics | 00.7 | High yielding food grade variety with yellow hilum |
OAC Bounty | CanGro Genetics | 0.7 | High yielding food grade variety with imperfect yellow hilum, and resistance to Phytophthora root rot |
OAC Acclaim | CanGro Genetics | 0.5 | High yielding food grade variety with imperfect yellow hilum, high resistance to Phytophthora root rot, and above average protein content |
OAC Ambrose | SeCan | 0.7 | Food grade variety with yellow hilum, good standability and very competitive yield levels |
OAC Carson | SeCan | 0.4 | Food grade variety with imperfect yellow hilum, good field tolerance to Phytophthora root rot, and comparable maturity and protein levels to OAC Strive (with slightly smaller seed size) |
OAC Bruno | SeCan | 0.6 | High yielding, imperfect yellow hilum food grade variety with SCN resistance for the lower protein, non-GMO market |
OAC Moria | CanGro Genetics | 0.5 | Imperfect yellow hilum food grade variety with excellent lodging resistance and good tolerance to Phytophthora root rot |
OAC Candy | CanGro Genetics | 0.5 | High yield, imperfect yellow hilum, high protein |
OAC Glaze | CanGro Genetics | 0.7 | High yield, very high protein (44%), imperfect yellow hilum, food grade |
OAC Dunkel | CanGro Genetics | 0.5 | High yield, imperfect yellow hilum, food grade |
OAC Kyiv | CanGro Genetics | 0.3 | High yield, very early, high protein, imperfect hilum, food grade |
Several studies looking at genomic contributions to traits of interest were also carried out during the project. Publications from these studies are listed in the “Project Related Publications” section of this summary.
External Funding Partners:
This activity was funded in part by the Government of Canada under the Canadian Agricultural Partnership’s AgriScience Program, with industry support from the Canadian Field Crop Research Alliance (CFCRA) whose members include: Atlantic Grains Council; Producteurs de grains du Quebec; Grain Farmers of Ontario; Manitoba Corn Growers Association; Manitoba Pulse & Soybean Growers; Saskatchewan Pulse Growers; Prairie Oat Growers Association; SeCan; and FP Genetics.
Project Related Publications:
Belzile, F., Torkamaneh, D., Tardivel, A., Lemay, M.A., Boudhrioua, C., Arsenault-Labrecque, G., Dussault-Benoit, C., Lebreton, A., de Ronne, M., Tremblay, V., Labbé, C., O’Donoughue, L., St-Amour, V.TB., Copley, T., Fortier, E., Ste-Croix, D.T., Mimee, B., Cober, E., Rajcan, I., Warkentin, T., Gagnon, É., Legay, S., Auclair, J. and Bélanger, R. 2022. The SoyaGen Project: Putting genomics to work for soybean breeders. Front. Plant Sci. 13:887553.
Buerstmayr, H., Dreccer, M.F., Miladinović, M., Qiu, L., Rajcan, I., Reif, J., Varshney, R.K., and Vollmann, J. 2022. Plant breeding for increased sustainability: challenges, opportunities and progress. Theor. Appl. Genetics. 135:3679–3683.
Ficht, A., Bruce, R., Torkamaneh, D., Grainger, C.M., Eskandari, M., and Rajcan, I. 2022. Genetic analysis of sucrose concentration in soybean seeds using a historical soybean genomic panel. Theor Appl Genet. 135: 1375–1383.
Gebre, M.G., Rajcan, I. and Earl, H.J. 2022. Genetic variation for effects of drought stress on yield formation traits among commercial soybean [Glycine max (L.) Merr.] cultivars adapted to Ontario, Canada. Front. Plant Science. 13.
Hashemi, S.M., Perry, G.E., Rajcan, I., and Eskandari, M. 2022. SoyMAGIC population: a novel platform for genetic studies and breeding activities in soybean. Front. Plant Sci.
Hong, H., Yoosefzadeh, N. and Rajcan, I. 2022. Correlations between soybean seed quality traits using a genome-wide association study panel grown in Canadian and Ukrainian mega-environments. Can J. Plant Sci. 102: 1040–1052.
Hong, H., Yoosefzadeh, N., M., Torkamaneh, D., and Rajcan, I. 2022. Identification of quantitative trait loci associated with seed quality traits between Canadian and Ukrainian mega-environments using genome-wide association study. Accepted for publication in Theor. Appl. Genet. 135(7): 2515-2530.
Khatri, P., Chen, L., Rajcan, I., and Dhaubhadel, S. 2023. Functional characterization of cinnamate 4-hydroxylase gene family in soybean (Glycine max). PLOS One.
Khatri, P., Wally, O., Rajcan, I. and Dhaubhadel, S. 2022. Comprehensive analysis of cytochrome P450 monooxygenases reveals insight into their role in partial resistance against Phytophthora sojae in soybean. Front. Plant Sci. 13:862314.
Mugabe, D., Najafabadi, M.Y., & Rajcan, I. 2024. Genetic diversity and genome-wide association study of partial resistance to Sclerotinia stem rot in a Canadian soybean germplasm panel. Theor. Appl Genet. Published online.
Priyanatha, C., and Rajcan, I. 2022a. Phenotypic evaluation of Canadian x Chinese germplasm in a diversity panel for seed yield and seed quality traits. Canadian Journal of Plant Science. 102: 1032–1039.
Priyanatha, C., Torkamaneh, D. and Rajcan, I. 2022b. Genome-wide association study of soybean germplasm derived from Canadian × Chinese crosses to mine for novel alleles to improve seed yield and seed quality traits. Front. Plant Sci. 13:866300.
Yoosefzadeh-Najafabadi, M. and Rajcan, I. 2023. Six decades of soybean breeding in Ontario, Canada: a tradition of innovation. Canadian Journal of Plant Science. 00: 1–20 (2023).
Yoosefzadeh-Najafabadi, M., Rajcan, I., and Eskandari, M. 2022. Optimizing genomic selection in soybean: An important improvement in agricultural genomics. Heliyon. 8(11).
Yoosefzadeh-Najafabadi M., Rajcan I. and Vazin, M. 2022. High-throughput plant breeding approaches: Moving along with plant-based food demands for pet food industries. Front. Vet. Sci. 9:991844.
Yoosefzadeh-Najafabadi, M., Eskandari, M., Torabi, S., Torkamaneh, D., Tulpan, D., Rajcan, I. 2022. Machine-learning-based genome-wide association studies for uncovering QTL underlying soybean yield and its components. Int. J. Mol. Sci. 2022, 23, 5538.