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Phenotypic and Biomass Yield Variations in Natural Populations of Prairie Cordgrass (Spartina pectinata Link) in the USA

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Abstract

Prairie cordgrass (Spartina pectinata Link) is a productive warm-season, C4 perennial grass native to most of North America having tolerance to wet, cold, and saline growing conditions. Excellent stress tolerance, along with high biomass yields, makes prairie cordgrass a good candidate as a dedicated energy crop on marginal land. However, there is little information available on genetic variation, including yield potential, of native populations in the USA. The objectives of this study were to evaluate biomass yield and to identify the nature and extent of genetic variation in natural populations of prairie cordgrass by comparing endemic strains collected throughout the USA. Forty-two prairie cordgrass populations were collected from prairie-remnant sites in 13 states and evaluated at the University of Illinois in Urbana, IL. The 4-year field study of prairie cordgrass revealed extensive variations in biomass yield and phenotypic traits associated with biomass yield among these populations. Strong correlations were observed between the phenotypic values and origins of the populations. Path coefficient analysis indicated that tiller mass, tiller density, heading date, plant height, and phytomer number positively affected biomass yield directly or indirectly. However, the phenotypic traits including biomass yield showed significant variation among years except for phytomer number and heading date. With the extensive genetic variability and high biomass yield potential demonstrated in this experiment, prairie cordgrass could become a highly productive bioenergy crop by developing a well-planned breeding program.

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References

  1. Barkworth ME, Anderton LK, Capels KM, Long S, Piep MB (eds) (2007) Manual of grasses for North America north of Mexico. Utah St. Univ. Press, Logan, UT

  2. Beringer TIM, Lucht W, Schaphoff S (2011) Bioenergy production potential of global biomass plantations under environmental and agricultural constraints. GCB Bioenergy 3(4):299–312

    Article  CAS  Google Scholar 

  3. Boe A, Owens V, Gonzalez-Hernandez J, Stein J, Lee DK, Koo BC (2009) Morphology and biomass production of prairie cordgrass on marginal lands. GCB Bioenergy 1(3):240–250

    Article  Google Scholar 

  4. Boe A, Lee DK (2007) Genetic variation for biomass production in prairie cordgrass and switchgrass. Crop Sci 47:929–934

    Article  Google Scholar 

  5. Boe A, Beck DL (2008) Yield components of biomass in switchgrass. Crop Sci 48(4):1306–1311

    Article  Google Scholar 

  6. Boe A, Casler MD (2005) Hierarchical analysis of switchgrass morphology. Crop Sci 45:2465–2472

    Article  Google Scholar 

  7. Boe A, Ross JG (1983) Path coefficient analysis of seed yield in big bluestem. J Range Manag 36:652–653

    Article  Google Scholar 

  8. Casler MD, Vogel KP, Taliaferro CM, Wynia RL (2004) Latitudinal adaptation of switchgrass populations. Crop Sci 44(1):293–303

    Google Scholar 

  9. Church GL (1940) Cytotaxonomic studies in the Graminea Spartina, Andropogon and Panicum. Am J Bot 27:263–271

    Article  Google Scholar 

  10. Clausen J, Hiesey WM (1958) Experimental studies on the nature of species. IV. Genetic structure of ecological races. Experimental studies on the nature of species. IV. Genetic structure of ecological races

  11. Dale VH, Kline KL, Wright LL, Perlack RD, Downing M, Graham RL (2011) Interactions among bioenergy feedstock choices, landscape dynamics, and land use. Ecol Appl 21(4):1039–1054

    Article  PubMed  Google Scholar 

  12. Das MK, Fuentes RG, Taliaferro CM (2004) Genetic variability and trait relationships in switchgrass. Crop Sci 44(2):443–448

    Article  Google Scholar 

  13. Demirbas A (2009) Political, economic and environmental impacts of biofuels: a review. Appl Energy 86:S108–S117

    Article  CAS  Google Scholar 

  14. Dewey DR, Lu KH (1959) A correlation and path-coefficient analysis of components of crested wheatgrass seed production. Agron J 51(9):515–518

    Article  Google Scholar 

  15. Garson GD (2008) Path analysis. from Statnotes: Topics in Multivariate Analysis. Retrieved 9(05):2009

    Google Scholar 

  16. Gedye KR, Gonzalez-Hernandez JL, Owens V, Boe A (2012) Advances towards a Marker-Assisted Selection Breeding Program in Prairie Cordgrass, a Biomass Crop. Int J Plant Genom 2012:8

    Google Scholar 

  17. Gelfand I, Sahajpal R, Zhang X, Izaurralde RC, Gross KL, Robertson GP (2013) Sustainable bioenergy production from marginal lands in the US Midwest. Nature 493(7433):514–517

    Article  CAS  PubMed  Google Scholar 

  18. Kim S, Rayburn AL, Voigt T, Parrish A, Lee DK (2012) Salinity effects on germination and plant growth of prairie cordgrass and switchgrass. Bioenergy Res 5(1):225–235

    Article  Google Scholar 

  19. Kim S, Rayburn AL, Parrish A, Lee DK (2012) Cytogeographic distribution and genome size variation in prairie cordgrass (Spartina pectinata Bosc ex Link). Plant Mol Biol Report 30(5):1073–1079

    Article  Google Scholar 

  20. Kim S, Rayburn AL, Boe A, Lee DK (2012) Neopolyploidy in Spartina pectinata Link: 1. Morphological analysis of tetraploid and hexaploid plants in a mixed natural population. Plant Syst Evol 298(6):1073–1083

    Article  Google Scholar 

  21. Kim S, Rayburn AL, Voigt TB, Ainouche ML, Ainouche AK, Lee DK (2013) Chloroplast DNA intraspecific phylogeography of prairie cordgrass (Spartina pectinata Bosc ex Link). Plant Mol Biol Report 31(6):1376–1383

    Article  Google Scholar 

  22. Laird DA (2008) The charcoal vision: a win–win–win scenario for simultaneously producing bioenergy, permanently sequestering carbon, while improving soil and water quality. Agron J 100(1):178–181

    Article  Google Scholar 

  23. Lenka D, Mishra B (1973) Path coefficient analysis of yield in rice varieties. Indian J Agric Sci 43(4):376

    Google Scholar 

  24. Long SP (1983) C4 photosynthesis at low temperatures. Plant Cell Environ 6(4):345–363

    CAS  Google Scholar 

  25. Madakadze IC, Coulman BE, Mcelroy AR, Stewart KA, Smith DL (1998) Evaluation of selected warm-season grasses for biomass production in areas with a short growing season. Bioresour Technol 65(1):1–12

    Article  CAS  Google Scholar 

  26. Miller C (2013) release brochure for Kingston Germplasm prairie cordgrass (Spartina pectinata). USDA-Natural Resources Conservation Service, Big Flats Plant Materials Center, Corning

    Google Scholar 

  27. Miller C (2013) Release brochure for Southampton Germplasm prairie cordgrass (Spartina pectinata). USDA-Natural Resources Conservation Service, Cape May Plant Materials Center, Cape May

    Google Scholar 

  28. Mobberley DG (1953) Taxonomy and distribution of the genus Spartina.(Doctoral dissertation, Iowa State College)

  29. Mohammadi SA, Prasanna BM, Singh NN (2003) Sequential path model for determining interrelationships among grain yield and related characters in maize. Crop Sci 43(5):1690–1697

    Article  Google Scholar 

  30. Montemayor MB, Price JS, Rochefort L, Boudreau S (2008) Temporal variations and spatial patterns in saline and waterlogged peat fields: 1. Survival and growth of salt marsh graminoids. Environ Exp Bot 62(3):333–342

    Article  Google Scholar 

  31. Reeder JR (1977) Chromosome numbers in western grasses. Am J Bot 64:102–110

    Article  Google Scholar 

  32. Rosseel Y (2012) lavaan: An R package for structural equation modeling. J Stat Softw 48(2):1–36

    Google Scholar 

  33. Samonte SO, Wilson LT, McClung AM (1998) Path analyses of yield and yield-related traits of fifteen diverse rice genotypes. Crop Sci 38(5):1130–1136

    Article  Google Scholar 

  34. Simmons BA, Loque D, Blanch HW (2008) Next-generation biomass feedstocks for biofuel production. Genome Biol 9(2):242–242

    Article  PubMed Central  PubMed  Google Scholar 

  35. Skinner RH, Zobel RW, Van der Grinten M, Skaradek W (2009) Evaluation of native warm-season grass cultivars for riparian zones. J Soil Water Conserv 64(6):413–422

    Article  Google Scholar 

  36. Team RC (2012) R: A language and environment for statistical computing

  37. USDA Natural Resources Conservation Service, Plant Materials Center, Bismarck, ND (2012) Release Brochure for Red River Natural Germplasm prairie cordgrass (Spartina pectinata). www.plant-materials.nrcs.usda.gov

  38. USDA-NRCS (2008) Plants database. See http://plants.usda.gov/index. (Verified20November 2014).

  39. Weaver JE (1954) North American Prairie. Johnsen Publ. Co., Lincoln

    Google Scholar 

  40. Weaver JE (1960) Extent of communities and abundance of the most common grasses in prairie. Bot Gaz 122:25–33

  41. Weaver JE, Fitzpatrick TJ (1932) Ecology and relative importance of the dominants of tall-grass prairie. Bot Gaz 93:113–150

  42. Zilverberg C, Johnson WC, Archer D, Kronberg S, Schumacher T, Boe A, Novotny C (2014) Profitable prairie restoration: The EcoSun Prairie Farm experiment. J Soil Water Conserv 69(1):22A–25A

    Article  Google Scholar 

Download references

Acknowledgments

This work was funded by the Energy Biosciences Institute.

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Correspondence to D. K. Lee.

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Guo, J., Thapa, S., Voigt, T. et al. Phenotypic and Biomass Yield Variations in Natural Populations of Prairie Cordgrass (Spartina pectinata Link) in the USA. Bioenerg. Res. 8, 1371–1383 (2015). https://doi.org/10.1007/s12155-015-9604-3

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  • DOI: https://doi.org/10.1007/s12155-015-9604-3

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