Experimental Design Factors Affecting Error Variation in Orchardgrass

Casler, Michael D.; Tageldin, M. H.

doi:10.2134/agronj1996.00021962008800050011x

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…Thus, spatial variation appeared to be due to field heterogeneity per se, and was not affected by variation in alley position between rows of plots. This is consistent with observations of Casler and Tageldin (1996), who showed that variation in alley position or marking was important for 1.4-m 2 plots, but not for plot sizes of 2.8 m 2 or greater. Lin and Binns (1986) described working rules for improving the precision of future RCB designed trials, using blocking information from prior RCB designed trials.…”

Section: Resultssupporting

confidence: 91%

“…Furthermore, no method of spatial analysis attempted in this study was effective at decreasing ?-values of these trials. Spatial adjustments should be less effective for small blocks, because the probability of significant spatial variation is substantially reduced compared with large blocks (Briggs and Shebeski, 1968;Casler and Tageldin, 1996;Warren and Mendez, 1982). These three trials were excluded from all analyses.…”

Section: Resultsmentioning

confidence: 99%

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Spatial Variation Affects Precision of Perennial Cool‐Season Forage Grass Trials

Casler

1999

Agronomy Journal

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Randomized complete block (RCB) designs, although commonly used in testing forage grass cultivars, often are inefficient. The objective of this study was to evaluate the RCB design, the lattice design, trend analysis, and nearest‐neighbor analysis (NNA) for their ability to account for spatial variability in 27 perennial cool‐season forage grass cultivar evaluation trials conducted over a 15‐yr period at Arlington, WI. Each trial was made up of cultivars or experimental populations of one of six species or groups of species: orchardgrass (Dactylis glomerata L.), ryegrasses [a group comprising perennial ryegrass, Lolium perenne L.; intermediate ryegrass, L. hybridum Hausskn.; and festulolium, ✕ Festulolium braunii (K. Richt.) A. Camus], smooth bromegrass (Bromus inermis Leyss.), reed canarygrass (Phalaris arundinacea L.), tall fescue (Festuca arundinacea Schreb.), and timothy (Phleum pratense L.). Dry matter forage yield was determined for 3 yr on each trial and expressed, for each plot, as mean annual yield. Yield data for each trial were analyzed by the RCB or lattice model, trend analysis, and two NNA models (one or two covariates). Three incremental improvements in precision of entry means were observed: an average of 15% due to the RCB design, an additional average of 17% due to the lattice design, and an additional average of 22 to 30% due to trend analysis or NNA. Trials were highly variable in the relative efficiency of both their experimental design and the spatial analyses, but this variability was not related to species, planting years, or plot size. The only useful predictor of trial efficiency was number of entries: three of five trials with eight or fewer entries failed to show significant differences among entries, regardless of the analysis. Spatial analysis methods cannot overcome lack of true differences among entries or failure to detect differences due to low degrees of freedom. Trend analysis or NNA appear to be useful mechanisms to account for intrablock variability in fields where it is impossible or uneconomical to predict proper blocking patterns.

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Section: Resultssupporting

confidence: 91%

Section: Resultsmentioning

confidence: 99%

Spatial Variation Affects Precision of Perennial Cool‐Season Forage Grass Trials

Casler

1999

Agronomy Journal

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“…Phenotypic selection based on spaced‐plant evaluations is used in forage breeding to access the within‐family genetic variability and it increases the accuracy and genetic gain as shown here. However, selection experiments in perennial grasses and legumes have shown that genetic correlations between some traits, for example, biomass yield, evaluated in spaced plantings and sward plots ranges from negative to positive values, depending on species and target trait (Casler and Tageldin, 1996; Annicchiarico, 2006; Casler, 2008; Casler and Brummer, 2008; Wilkins and Humphreys, 2003). The optimal choice of selection methods was independent of whether selection was based directly on the target trait y or indirectly on trait x , relying on correlated responses to achieve gains in trait y .…”

Section: Discussionmentioning

confidence: 99%

Selection Methods in Forage Breeding: A Quantitative Appraisal

2013

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Forage breeding can be extraordinarily complex because of the number of species, perenniality, mode of reproduction, mating system, and a variable genetic correlation between spaced plants and sward plots. Aiming to compare eight forage breeding methods for direct selection gain and correlated response, different scenarios of trait heritability and genetic correlation have been evaluated based on deterministic equations of expected (theoretical) breeding accuracy applied to half‐sib progenies evaluated in spaced‐plant trails, sward‐plot trials, or both. Relative efficiency for each method is given in relation to individual selection. Methods differ most when heritability is lower than 0.3, which coincides with the majority of the situations met by forage breeders. Genetic gain of best linear unbiased prediction (BLUP)‐based methods is superior to all other methods for trait heritability lower than 0.3, independent of field‐trail plot methods, except for parental selection. Methods based on BLUP have also shown higher efficiency when the genetic correlation between spaced‐plant and sward‐plot trials evaluations of a trait is lower than 0.7 and indirect‐trait heritability is lower than 0.3. The choice of forage breeding method should include consideration of the mode of reproduction and the target‐trait heritability. The benefits of BLUP‐based selection methods should receive more serious consideration by forage breeders.

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“…The experimental design was a sets‐in‐replicates design (Schutz and Cockerham, 1966) with 50 sets for orchardgrass and smooth bromegrass or 60 for hybrid wheatgrass, seven polycross families per set, and two replicates. Set size was determined partly by data from an orchardgrass uniformity trial (Casler and Tageldin, 1996) and partly by previous experiences with block sizes ranging from 4 to 35 in numerous cultivar tests. Each set contained polycross families from only one population.…”

Section: Methodsmentioning

confidence: 99%

Among‐and‐within‐Family Selection in Eight Forage Grass Populations

Casler

2008

Crop Science

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Forage yields increased little during the twentieth century, despite intensive breeding efforts in many species. Half‐sib family (HSF) and/or among‐and‐within‐family (AWF) selection methods may overcome this problem. The objective of this study was to compare HSF and AWF selection using forage yield of sward plots as the among‐family selection criterion and natural selection of survivors within swards as the within‐family selection criterion. Selection for increased forage yield was practiced in eight populations of orchardgrass (Dactylis glomerata L.), smooth bromegrass (Bromus inermis Leyss.), and hybrid wheatgrass [Elytrigia × muctonata (Opiz ex Bercht.) Prokud.]. Two methods of recombination were used: random plants from remnant seed (HSF) or sod cores from selected families four years after establishment (AWF). There were no consistent differences between HSF and AWF selection for orchardgrass, a bunch grass. For the other two species, both highly rhizomatous, AWF selection was two to four times more effective than HSF selection for increasing forage yield. Natural selection within families of the two rhizomatous grasses favored genotypes capable of filling in open spaces left by plant and/or tiller mortality. The consistent differences in selection responses between orchardgrass and the two rhizomatous species suggested that natural selection acted on some characteristic of the rhizomatous trait of these two grasses.

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Experimental Design Factors Affecting Error Variation in Orchardgrass

Cited by 6 publications

References 13 publications

Spatial Variation Affects Precision of Perennial Cool‐Season Forage Grass Trials

Spatial Variation Affects Precision of Perennial Cool‐Season Forage Grass Trials

Selection Methods in Forage Breeding: A Quantitative Appraisal

Among‐and‐within‐Family Selection in Eight Forage Grass Populations

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