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

Rosielle, A. A.

doi:10.1007/bf00037258

Cited by 16 publications

(19 citation statements)

References 6 publications

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“…Nesses casos, pode ser constatado que os valores dos limites dos intervalos de confiança foram bem próximos (Tabela 2). Esses resultados não são coincidentes com os obtidos nas análises de variância individuais (Tabela 3), o que sugere que apesar de a interação famílias x locais não ter sido significativa na maioria das estratégias de análise de variância, sua participação na estimativa dos componentes de variância foi considerável, confirmando, assim, as observações feitas por Rosielle (1980) e Helms et al (1995). Esses autores verificaram que, sendo a diferença entre os métodos, evidente, em um local isolado, não o será na análise de variância conjunta, pela interação genótipos x ambientes.…”

Section: Resultsunclassified

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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Section: Resultsunclassified

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

Souza

Geraldi²,

Ramalho

2000

Pesq. agropec. bras.

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“…selection for protein content, which is often practised on individual progenies during early generations of a breeding programme. In later generations, when results from several environments are available, intra-site error would probably be unimportant in comparison to genotype environment interaction (Rosielle 1980). However, correlations between entry means across environments were clearly increased after adjustment for spatial variation in the 1992 experiments at Frauenkirchen, Probstdorf and Raasdorf (Table 3), which suggests that adjusting for field variation can improve the prediction value of a particular selection environment.…”

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Seed protein content of soybean as affected by spatial variation in field experiments

Vollmann¹,

Hadad²,

Gretzmacher³

et al. 1996

Plant Breeding

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The variation of soybean seed protein content has been investigated in performance trials of maturity group 000 to I genotypes at different locations in the eastern part of Austria between 1992 and 1994. In all experiments evaluated, significant portions of spatial variation were identified which affected seed protein content in the range of -25 to + 30 g/kg. Lattice and neighbour analysis were more efficient than the randomized complete block design in reducing error variance in most experiments. Neighbour analysis was superior to the lattice design when soil trends were changing over short distances or in both longitudinal and latitudinal directions. In most instances, neighbour analysis based on two or three neighbouring plots at each side of a test plot was more efficient than an analysis using only the nearest neighbours. Residuals derived from neighbour analysis were also used to visualize spatial heterogeneity, and clear trends of protein content were identified for particular experimental sites. The ranking of genetic entries was considerably biased by spatial variations, which would have reduced the efficiency of selection for high protein content if genotype performance was not adjusted for field variation.

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“…The performance of a cultivar is expressed as the differences between it and the adjacent check plot or as a percentage of the check plots if a high correlation between check plot and test plot exists. If the check plot misrepresents the soil variation, improper adjustment might result (Mak et al, 1978;Townley -Smith and Hurd, 1973;Rosielle, 1980). The use of check plots was substantially less efficient than using lattice designs or appropriate incomplete designs (Besag and Kempton, 1986).…”

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confidence: 99%

Evaluation of Moving Mean and Border Row Mean Covariance Analysis for Error Control in Yield Trials

Fernandez¹

1990

jashs

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The effectiveness of using moving mean covariance analysis (MMCA) rather than randomized complete-block design (RCBD) in experimental error control was compared in a large-scale mungbean [Vigna radiata (L.) Wilczek] yield trial. The MMCA was superior to the RCBD, since it significantly reduced the experimental error and the coefficient of variation (cv). Inclusion of five neighboring plots in the moving mean computation provided better error control. However, the estimation of optimum number of neighboring plots to be used and moving mean calculations were tedious. The feasibility of using border-row measurements such as mean plant height at 50% flowering or mean seed yield/m of row as a covariate in an analysis of covariance (BRMCA) was examined in a separate mungbean yield trial in which border rows were planted with a check cultivar. Both border-row measurements were equally effective in reducing the experimental error. However, plant height measurements were simpler than measuring seed yield. Because border-row measurements could be readily used as covariate in analysis of covariance without a need for moving mean computation from the response variable, BRMCA could be advantageous for error control in row crops yield evaluation.

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

Cited by 16 publications

References 6 publications

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

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

Seed protein content of soybean as affected by spatial variation in field experiments

Evaluation of Moving Mean and Border Row Mean Covariance Analysis for Error Control in Yield Trials

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