Genotype × environment interaction patterns of dry matter yield in meadow brome, orchardgrass, tall fescue, and timothy evaluated at harsh winter sites

Abstract

Background: Genotype × environment interaction (GEI) slows genetic gains and complicates selection decisions in plant breeding programs. Forage breeding program seed sales often encompass large geographic regions to which the cultivars may not be adapted. An understanding of the extent of GEI in perennial, cool-season forage grasses will facilitate improved selection decisions and end-use in areas with harsh winters.

Methods: We evaluated the dry matter yield of nine meadow brome (Bromus biebersteinii Roemer & J. A. Schultes), nine orchardgrass (Dactylis glomerata L.), seven tall fescue (Lolium arundinaceum (Schreb.) Darbysh.), and 10 timothy (Phleum pratense L.) cultivars or breeding populations at seven high latitude and/or elevation locations in Canada and the United States from 2019 to 2021.

Results: For each of the species, we found significant differences among the genotypes for dry matter yield across environments and found significant levels of GEI. Using site regression analysis and GGE biplot visualizations, we then characterized the extent of the interactions in each species. Except for tall fescue, there was little evidence for the broad adaptation of genotypes across locations.

Conclusions: This research adds further evidence to the limitations of perennial, forage breeding programs to develop widely adapted cultivars and the need to maintain regional breeding efforts.

Keywords

cool-season forage grass / forage yield / genotype × environment interaction

References

[1] Alderson, J., & Sharp, W. C. (1994). Grass varieties in the United States, Agriculture handbook. United States Department of Agriculture.

[2] Annicchiarico, P., Bellah, F., & Chiari, T. (2005). Defining subregions and estimating benefits for a specific-adaptation strategy by breeding programs: A case study. Crop Science, 45, 1741–1749.

[3] de Araujo, M. R. A., & Coulman, B. E. (2004). Parent–offspring regression in meadow bromegrass (Bromus riparius Rehm.): Evaluation of two methodologies on heritability estimates. Canadian Journal of Plant Science, 84(1), 125–127.

[4] Berg, C. C., McElroy, A. R., & Kunelius, K. T. (1996). Timothy. In L. E. Moser, D. R. Buxton, & M. D. Casler (Eds.), Cool-season forage grasses.

[5] Butler, D. (2022). asreml: Fits the linear mixed model. R package version 4.1.0.176. VSNi. https://www.vsni.co.uk

[6] Casler, M. D., Pedersen, J. F., Eizenga, G. C., & Stratton, S. D. (1996). Germplasm and cultivar development. In L. E. Moser, D. R. Buxton, & M. D. Casler (Eds.), Cool-season forage grasses. ASA-CSSA-SSSA Publishers.

[7] Ceccarelli, S. (1989). Wide adaptation: How wide? Euphytica, 40, 197–205.

[8] Gauch, Jr., H. G., & Zobel, R. W. (1997). Identifying mega-environments and targeting genotypes. Crop Science, 37, 311–326.

[9] Gray, E. (1982). Genotype × environment interactions and stability analysis for forage yield of orchardgrass clones. Crop Science, 22(2), 19–23.

[10] Helgadóttir, A., & Kristjánsdóttir, T. A. (1991). Simple approach to the analysis of G × E interactions in a multilocational spaced plant trial with timothy. Euphytica, 54, 65–73.

[11] Jensen, K. B., Robins, J. G., Bushman, B. S., Johnson, D. A., Stratton, S. D., & Heaton, K. (2014). UTDG-101, a late-maturing orchardgrass germplasm with increased winter hardiness and forage quality. Journal of Plant Registrations, 8(3), 318–323.

[12] Knowles, R. P. (1990). Registration of ‘Paddock’ meadow bromegrass. Crop Science, 30(3), 741.

[13] Larsen, A. (1994). Breeding winter hardy grasses. In O. A. Rognli, E. Solberg, I. Schjelderup, (Eds.), Breeding fodder crops for marginal conditions: Proceedings of the 18th Eucarpia Fodder Crops Section Meeting, Loen, Norway, 25–28 August 1993 (pp. 149–158). Springer.

[14] Nguyen, H. T., Sleper, D. A., & Hunt, K. L. (1980). Genotype × environment interactions and stability analysis for herbage yield of tall fescue Synthetics. Crop Science, 20(2), 221–224.

[15] Olivoto, T., & Lúcio, A. D. (2020). metan: An R package for multi-environment trial analysis. Methods in Ecology and Evolution, 11(6), 738–789.

[16] Pecetti, L., Annicchiarico, P., Abdelguerfi, A., Kallida, R., Mefti, M., Porqueddu, C., Simões, N. M., Volaire, F., & Lelièvre, F. (2011). Response of Mediterranean tall fescue cultivars to contrasting agricultural environments and implications for selection. Journal of Agronomy and Crop Science, 197(1), 12–20.

[17] R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/

[18] Revelle, W. (2023). psych: Procedures for psychological, psychometric, and personality research. R package version 2.3.9. Northwestern University. https://CRAN.R-project.org/package=psych

[19] Robins, J. G., & Jensen, K. B. (2011). Identification of creeping foxtail germplasm with high dry matter yield and nutritive value. Crop Science, 51(2), 728–735.

[20] Robins, J. G., & Jensen, K. B. (2017). Genotype × environment interaction effects of propagation and defoliation on meadow bromegrass. Crop Science, 57(4), 2007–2016.

[21] Robins, J. G., Jensen, K. B., & Bushman, B. S. (2017). Variation and best linear unbiased predictors in a novel source of orchardgrass germplasm with increased winter hardiness. Canadian Journal of Plant Science, 97(6), 999–1003.

[22] Robins, J. G., Jensen, K. B., & Bushman, B. S. (2018). Registration of USDA-UTWH-102 winter-hardy orchardgrass germplasm. Journal of Plant Registrations, 12(2), 251–252.

[23] Robins, J. G., Smith, R., Hall, M. H., Teutsch, C. D., & Undersander, D. J. (2017). Associations among U.S. locations for orchardgrass production. Crop, Forage & Turfgrass Management, 3(1), 1–7.

[24] Van Santen, E., & Sleper, D. A. (1996). Orchardgrass. L. E. Moser, D. R. Buxton & M. D. Casler (Eds.), Cool-season forage grasses. ASA-CSSA-SSSA Publishers.

[25] Singh, M., Ceccarelli, S., & Grando, S. (1999). Genotype × environment interaction of crossover type: Detecting its presence and estimating the crossover point. Theoretical and Applied Genetics, 99, 988–995.

[26] Sleper, D. A., & West, C. P. (1996). Tall fescue. In L. E. Moser, D. R. Buxton, & M. D. Casler (Eds.), Cool-season forage grasses. ASA-CSSA-SSSA Publishers.

[27] Smith, K. F., & Casler, M. D. (2004). Spatial analysis of forage grass trials across locations, years, and harvests. Crop Science, 44(1), 56–62.

[28] Vogel, K. P., Moore, K. J., & Moser, L. E. (1996). Bromegrasses. In L. E. Moser, D. R. Buxton, & M. D. Casler (Eds.), Cool-season forage grasses.

[29] Yan, W., Hunt, L. A., Sheng, Q., & Szlavnics, Z. (2000). Cultivar evaluation and mega-environment investigation based on the GGE Biplot. Crop Science, 40(3), 597–605.

[30] Yan, W., Mitchell-Fetch, J., Beattie, A., Nilsen, K. T., Pageau, D., DeHaan, B., Hayes, M., Mountain, N., Cummiskey, A., & MacEachern, D. (2021). Oat mega-environments in Canada. Crop Science, 61(2), 1141–1153.

RIGHTS & PERMISSIONS

2024 The Authors. Grassland Research published by John Wiley & Sons Australia, Ltd on behalf of Chinese Grassland Society and Lanzhou University.