Use of Moving Means in Wheat Yield Trials

Townley‐Smith, T. F.; Hurd, E. A.

doi:10.4141/cjps73-086

Cited by 30 publications

(24 citation statements)

References 3 publications

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“…Generally most error variance reduction occurred when six to eight adjacent plots were used. Similar results were reported by TOWNLEY-SMITH t~¢ HURD (1973) andMAK et al (1978).…”

Section: Resultssupporting

confidence: 80%

Effect of moving mean covariance adjustments on error and genetic variance estimates and selection of superior lines in peanuts (Arachis hypogaeal L.)

Shorter¹,

Butler²

1986

Euphytica

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Effects of moving mean covariance adjustments on error control, genetic variance component estimates and selection were examined in nine trails in peanut breeding nurseries. Neighbourhood sizes of two to fourteen adjacent plots were used in two types of moving mean covariates: one based on adjacent plot yields and a second based on adjacent plot residuals after removal of replicate and treatment effects. Both covariate types reduced error variance, in one trial by up to 57%, although the covariate type giving the most error reduction varied among trials. Generally most error variance reduction occurred when six to eight adjacent plots were used.In some trials genetic variance component estimates following covariance adjustment were higher than those from unadjusted analyses and in other trials they were lower. As the neighbourhood size included in the moving mean increased from two to fourteen plots the genetic variance component estimate changed considerably in some trials. However, large rank changes did not appear to be associated with these genetic variance component changes as neighbourhood size had little influence on the selection of progenies. Also, genetic effects included in the yield covariate had little influence on selection of elite lines as essentially the same lines were chosen or rejected when residual covariates lacking these genetic effects wre used.

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“…Generally most error variance reduction occurred when six to eight adjacent plots were used. Similar results were reported by TOWNLEY-SMITH t~¢ HURD (1973) andMAK et al (1978).…”

Section: Resultssupporting

confidence: 80%

Effect of moving mean covariance adjustments on error and genetic variance estimates and selection of superior lines in peanuts (Arachis hypogaeal L.)

Shorter¹,

Butler²

1986

Euphytica

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“…Entre esses métodos, o de Papadakis (1937) e o de médias mó-veis (Townley-Smith & Hurd, 1973). Recentemente, em razão do interesse nesse tipo de análise, novas propostas surgiram (Bartlett, 1978;Wilkinson et al, 1983;Besag & Kempton, 1986;Samra et al, 1990;Vivaldi, 1990;Zimmerman & Harville, 1991;Ball et al, 1993;Brownie et al, 1993;Stroup et al, 1994;Helms et al, 1995;Anoshenko, 1996;Clarke & Baker, 1996).…”

Section: Introductionunclassified

Alternativas experimentais na avaliação de famílias em programas de melhoramento genético do feijoeiro

Souza

Geraldi²,

Ramalho

2000

Pesq. agropec. bras.

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EXPERIMENTAL ALTERNATIVES IN THE EVALUATION OF FAMILIES IN THE GENETIC IMPROVEMENT OF BEAN PLANTSABSTRACT -The aim of this work was to evaluate the viability of using the augmented block designs and spatial analysis methods for early-stage selection in breeding programs for common bean (Phaseolus vulgaris L.). A total of 121 S 2 progenies were evaluated in three locations: Lavras, Lambari and Patos de Minas, Brazil. A simple 11 x 11 lattice design was employed by location. Additionally, two controls, Carioca and EMGOPA 201-Ouro, were included. The split plots were composed by two 2 m lines with 15 seeds/m. The data of the production (g/plot) were submitted to a variance analysis, considering the following strategies: lattice design, augmented block design, randomized complete block design, Papadakis' method, moving means method, and check plots method. The comparison between the different strategies was done considering their efficiency in controlling the experimental error and in relation to the precision of the estimates of genetic and phenotypic parameters obtained in each method. General results indicate that augmented block design is useful in earlier stage of selection, when the intensities of selection are moderate to low; however, this design is not useful for estimation of genetic and phenotypic parameters due to lower precision of estimates; the use of check plots method did not improve the experimental precision; the nearest neighbour, Papadakis and moving means methods were efficient in removing the heterogeneity within blocks; this efficiency was equivalent to lattice analysis for estimation of genetic and phenotypic parameters.

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“…The check plot method has the disadvantage of requiring many additional plots and WIANCKO et al (1921) recommended the use of additional replication rather than check plots for error control. TOWNLEY-SMITH & HURD (1973) used a moving-average method in which the mean of a number of adjacent plots is used as a covariate for adjusting plot values, obviating the need to devote plots to checks. MAK et al (1978) found that a partially balanced square lattice design achieved superior error control to both check plots and moving means for grain yield and protein content of barley; check plots and moving means gave similar error control.…”

Section: Introductionmentioning

confidence: 99%

Comparison of lattice designs, check plots, and moving means in wheat breeding trials

Rosielle¹

1980

Euphytica

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Efficiencies of lattice designs, check plot designs, and moving means were compared in seven environments for control of error in wheat breeding trials. Lattice analyses of lattice designs and check plot covariance analyses of check plot designs gave similar CV's and intra-site heritabilities and were superior to direct RCBD analyses of these designs. Moving mean covariance analyses were generally only slightly less efficient than lattice analyses or check plot covariance analyses. Differences between designs and methods ofanalysis, which were evident on an intra-site basis, were not evident from combined analyses indicating that genotype x environment interaction is much more important than intra-site error in limiting progress from selection, Moving mean covariance analyses with 2 replicates per location and as many locations as feasible is suggested as a useful strategy for early generation wheat breeding trials.

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Use of Moving Means in Wheat Yield Trials

Cited by 30 publications

References 3 publications

Effect of moving mean covariance adjustments on error and genetic variance estimates and selection of superior lines in peanuts (Arachis hypogaeal L.)

Effect of moving mean covariance adjustments on error and genetic variance estimates and selection of superior lines in peanuts (Arachis hypogaeal L.)

Alternativas experimentais na avaliação de famílias em programas de melhoramento genético do feijoeiro

Comparison of lattice designs, check plots, and moving means in wheat breeding trials

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