Estimates of Genetic Parameters in Switchgrass<sup>1</sup>

Talbert, L. E.; Timothy, D. H.; Burns, J. C.; Rawlings, John O.; Moll, R. H.

doi:10.2135/cropsci1983.0011183x002300040029x

Cited by 69 publications

(86 citation statements)

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“…For the SL-93 population, estimates of h 2 n (0.12 and 0.13 for PFM and individual plant selection, respectively) obtained from the progeny-parent regression method were considerably lower for both PFM and individual plant selection than those reported by Talbert et al (1983) in a lowland switchgrass population via estimation from variance component methods (0.59 and 0.25 for PFM and individual plant selection, respectively). This may be, in part, due to the progeny-parent regression method employed in elucidating estimates of h 2 n for the populations in this study, which tends to produce conservative estimates of h 2 n (Casler, 1982).…”

Section: Discussionmentioning

confidence: 69%

“…Switchgrass is allogamous and polymorphic with reported chromosome numbers ranging from 2n = 2x = 18 to 2n = 12x = 108 (Nielson, 1944;Henry & Taylor, 1989). Cross-pollination in the species is enforced by a gametophytic self-incompatibility system that is similar to the S-Z incompatibility system found in other Poaceae (Talbert et al, 1983;Martinè z-Reyna & Vogel, 2002;Taliaferro, 2002). All confirmed lowland ecotypes have been tetraploids (2n = 4x = 36) and most upland ecotypes are octoploids (2n = 8x = 72) .…”

Section: Introductionmentioning

confidence: 98%

“…Newell & Eberhart (1961) also reported narrow-sense heritability (h 2 n ) estimates for dm yield for forage of 0.18, 0.52 and 0.05 for 'small blue-green', 'medium-tall bluegreen' and 'tall-green' plant populations derived from Nebraska and Kansas germplasm. Talbert et al (1983) reported estimates of genetic parameters in a population of lowland switchgrass for in vitro dm disappearance, percent N dry weight and dry weight. They reported h 2 n estimates of 0.25 and 0.59 for dry weight on an individual plant and family basis, respectively.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Estimation of genetic variability and heritability for biofuel feedstock yield in several populations of switchgrass

Rose¹,

Das²,

Taliaferro³

2007

Annals of Applied Biology

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Information on heritability and predicted gains from selection for increased biomass yield for ethanol production in switchgrass is limited and may vary among breeding populations. The purpose of this study was to estimate heritability and predicted gains from selection for higher biomass yield within a lowland ecotype switchgrass population, Southern Lowland 93 (SL-93), and two upland ecotype switchgrass populations, Southern Upland Northern Upland Early Maturing (SNU-EM) and Southern Upland Northern Upland Late Maturing (SNU-LM). Narrowsense heritabilities (h n 2 ) for biomass yield in each of the three populations were estimated via progeny-parent regression analysis. Half-sib (HS) progeny families from 130 randomly selected plants from the SL-93 population were evaluated for biomass yield in replicated trials in 2002 and 2003. Clonal parent plants were evaluated for biomass yield in separate environments to provide unbiased h n 2 estimates from progeny-parent regression. Yield differences were highly significant among SL-93 HS progenies within and over years. For the SL-93 population, h n 2 estimates were 0.13 and 0.12 based on individual plant and phenotypic family mean (PFM) selection, respectively. Predicted genetic gains (DG) per selection cycle were 0.15 kg dry matter (dm) plant 21 and 0.10 kg dm plant 21 for PFM and individual plant selection methods, respectively. For the SNU-EM and SNU-LM populations, year and year Â HS family effects were highly significant (P < 0.01) and the HS family effect over years was nonsignificant (P < 0.05). However, HS family effects were highly significant within respective years (P < 0.01). Estimates of h n 2 for the SNU-EM and SNU-LM populations based on PFM and individual plant selection were similar, ranging from 0.44 to 0.47; DG per selection cycle ranged from 0.22 to 0.33 kg dm plant 21 .The magnitudes of the estimates of additive genetic variation suggest that selection for higher biomass yield should be possible. The substantial effect of environment on biomass yields in the upland populations and the failure of families to respond similarly over years stress the importance of adequately testing biomass yield over years.

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Section: Discussionmentioning

confidence: 69%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimation of genetic variability and heritability for biofuel feedstock yield in several populations of switchgrass

Rose¹,

Das²,

Taliaferro³

2007

Annals of Applied Biology

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“…Switchgrass is a highly heterozygous, self-incompatible and out-crossing species [41] with multiple ploidy levels ranging from 2n=2x=18 to 2n=12x=108 [3,7,33].…”

Section: Introductionmentioning

confidence: 99%

Genetic Diversity in Switchgrass Collections Assessed by EST-SSR Markers

et al. 2008

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Switchgrass (Panicum virgatum L.), is a warm season C 4 perennial grass, native to North American tall grass prairies. The high biomass production potential of switchgrass with low inputs makes it an excellent choice as a sustainable bioenergy crop. The objective of this study was to determine the genetic variability within and among 31 switchgrass populations obtained from Germplasm Resources Information Network (GRIN). Six plants from each population (186 genotypes) were characterized with 24 conserved grass expressed sequence tag-simple sequence repeats (EST-SSR) and 39 switchgrass EST-SSR markers. The partitioning of variance components based on the analysis of molecular variance (AMOVA) revealed that the variability within population was significantly higher (80%) than among populations (20%). Pair-wise genetic distance estimates based on SSR data revealed dissimilarity coefficients for genotypes ranging from 0.45 to 0.81. The uplands and lowlands were generally grouped in distinct sub-clusters. The genotypes were grouped into the different adaptive zones based on the geographical locations of the collections. Ploidy estimation showed that 20 of the accessions were tetraploid, four of them were octoploids and the remaining seven had mixed ploidy levels. Flow cytometry analysis of genotypes within cultivars collected from commercial seed sources did not always support the ploidy mixtures that were found in GRIN collections. Three genotypes of two accessions that clustered differently from other genotypes of the same accessions also had different ploidy levels.

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“…In most previous investigations researchers used heading date and/or flowering time to measure earliness versus lateness of reproductive development in switchgrass populations. Talbert et al (1983) and Van Esbroeck (1998) reported there was large genetic variation for flowering time in lowland switchgrass germplasm. Talbert et al (1983) reported high narrow-sense heritabilities (0.91 or above) for switchgrass maturity based on a lowland population of 33 half-sib families.…”

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confidence: 99%