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Zeitschriftendaten
Format
Zeitschrift
eISSN
2199-577X
Erstveröffentlichung
17 Aug 2013
Erscheinungsweise
2 Hefte pro Jahr
Sprachen
Englisch

Suche

Volumen 51 (2014): Heft 2 (December 2014)

Zeitschriftendaten
Format
Zeitschrift
eISSN
2199-577X
Erstveröffentlichung
17 Aug 2013
Erscheinungsweise
2 Hefte pro Jahr
Sprachen
Englisch

Suche

7 Artikel
Uneingeschränkter Zugang

An alternative methodology for imputing missing data in trials with genotype-by-environment interaction: some new aspects

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 75 - 88

Zusammenfassung

Abstract

A common problem in multi-environment trials arises when some genotypeby- environment combinations are missing. In Arciniegas-Alarcón et al. (2010) we outlined a method of data imputation to estimate the missing values, the computational algorithm for which was a mixture of regression and lower-rank approximation of a matrix based on its singular value decomposition (SVD). In the present paper we provide two extensions to this methodology, by including weights chosen by cross-validation and allowing multiple as well as simple imputation. The three methods are assessed and compared in a simulation study, using a complete set of real data in which values are deleted randomly at different rates. The quality of the imputations is evaluated using three measures: the Procrustes statistic, the squared correlation between matrices and the normalised root mean squared error between these estimates and the true observed values. None of the methods makes any distributional or structural assumptions, and all of them can be used for any pattern or mechanism of the missing values.

Schlüsselwörter

  • cross-validation
  • singular value decomposition
  • imputation
  • genotype-by-environment interaction
  • weights
  • missing values
Uneingeschränkter Zugang

Statistical analysis of yield trials by AMMI analysis of genotype × environment interaction

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 89 - 102

Zusammenfassung

Abstract

The genotype by environment interaction (GEI)) has an influence on the selection and recommendation of cultivars. The aim of this work is to study the effect of GEI and evaluate the adaptability and stability of productivity (kg/ha) of nine maize genotypes using AMMI model (Additive Main effects and Multiplicative Interaction). The AMMI model is one of the most widely used statistical tools in the analysis of multiple-environment trials. It has two purposes, namely understanding complex GEI and increasing accuracy. Nevertheless, the AMMI model is a widely used tool for the analysis of multiple-environment trials, where the data are represented by a two-way table of GEI means. In the complete tables, least squares estimation for the AMMI model is equivalent to fitting an additive two-way ANOVA model for the main effects and applying a singular value decomposition to the interaction residuals. It assumes equal weights for all GEI means implicitly. The experiments were conducted in twenty environments, and the experimental design was a randomized complete block design with four repetitions. The AMMI model identified the best combinations of genotypes and environments with respect to the response variable. This paper concerns a basic and a common application of AMMI: yield-trial analysis without consideration of special structure or additional data for either genotypes or environments.

Schlüsselwörter

  • genotype environment interaction (GEI)
  • adaptability and stability
  • additive main effects and multiplicative interaction model
  • multienvironment trials
Uneingeschränkter Zugang

Analysis of multivariate repeated measures data using a MANOVA model and principal components

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 103 - 114

Zusammenfassung

Abstract

In this paper we consider a set of T repeated measurements on p characteristics on each of n individuals. The n individuals themselves may be divided and randomly assigned to K groups. These data are analyzed using a mixed effect MANOVA model, assuming that the data on an individual have a covariance matrix which is a Kronecker product of two positive definite matrices. Results are illustrated on a data set obtained from experiments with varieties of winter rye.

Schlüsselwörter

  • multivariate repeated measures data (doubly multivariate data)
  • Kronecker product covariance structure
  • maximum likelihood estimates
  • mixed MANOVA model
  • principal component analysis
Uneingeschränkter Zugang

Control treatments in designs with split units generated by Latin squares

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 125 - 142

Zusammenfassung

Abstract

This paper deals with two-factor experiments with split units. The whole plot treatments occur in a repeated Latin square, modified Latin square or Youden square, while subplot treatments occur in a block design within the whole plots. The statistical properties of the considered designs are examined. Special attention is paid to the case where one of the treatments is an individual control or an individual standard treatment. In addition, we give a brief overview of work on the design of experiments using the considered designs, as well as possible arrangements of controls in the experiments.

Schlüsselwörter

  • Latin square
  • Youden square
  • split units
  • efficiency factors
  • merging treatment method
Uneingeschränkter Zugang

The influence of weather conditions on annual height increments of Scots pine

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 143 - 152

Zusammenfassung

Abstract

Annual height increments are a very important characteristic of Scots pine. They have a direct effect on the determination of the dendrometric properties of a stand, such as volume increment. In the present study the data concern height increments of the main shoot in selected age classes of trees (age 72 to 92 years). A relationship is determined between the values of the increments and meteorological conditions such as temperature, precipitation and sunshine. On the basis of lasso regression analysis, precipitation in the year preceding the incremental season was shown to have the greatest effect on height increments of Scots pine.

Schlüsselwörter

  • height increments
  • lasso regression
  • precipitation
  • Scots pine (Pinus sylvestris L.)
  • sunshine
  • temperature
Uneingeschränkter Zugang

Biometric characteristics of interspecific hybrids in the genus Secale

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 153 - 170

Zusammenfassung

Abstract

Breeding work using European rye populations has resulted in a considerable reduction of genetic variation in breeding materials of that species. Many taxa from the genus Secale may constitute a potential source of genetic variation in rye breeding. A source of new genetic variation can be found in such species as Secale montanum and Secale vavilovii, which are sources of resistance to fusarium ear blight and septoria leaf blotch, while Secale vavilovii may also be a source of sterilising cytoplasm. The aim of this study was to assess the efficiency of crossing the wild species Secale vavilovii and the rye subspecies Secale cereale subsp. afghanicum, Secale cereale subsp. ancestrale, Secale cereale subsp. dighoricum, Secale cereale subsp. segetale with the crop species Secale cereale ssp. cereale, and to produce F1 hybrids and describe selected morphological traits. Observations of biometric traits indicate that the F1 crosses produced may be potential sources of variation for common rye. The greatest variation in terms of all analysed phenotypic traits combined was found for the cross combinations S. c. ssp. cereale cv. Amilo × S. c. ssp. ancestrale and S. c. ssp. cereale cv. Dańkowskie Diament × S. c. ssp. dighoricum. The hybrids showed considerable variation in the analysed biometric traits within individual cross combinations.

Schlüsselwörter

  • Secale genus
  • interspecific crossing
  • biometrical traits
  • F1 hybrids
Uneingeschränkter Zugang

An evaluation of the efficiency of plant protection products via nonlinear statistical methods – a simulation study

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 171 - 179

Zusammenfassung

Abstract

A nonlinear statistical approach was used to evaluate the efficiency of plant protection products. The methodology presented can be implemented when the observations in an experiment are recorded as success or failure. This occurs, for example, when following the application of a herbicide or pesticide, a single weed or insect is classified as alive (failure) or dead (success). Then a higher probability of success means a higher efficiency of the tested product. Using simulated data sets, a comparison was made of three methods based on the logit, probit and threshold models, with special attention to the effect of sample size and number of replications on the accuracy of the estimation of probabilities.

Schlüsselwörter

  • threshold model
  • logistic model
  • plant protection
  • simulated data
7 Artikel
Uneingeschränkter Zugang

An alternative methodology for imputing missing data in trials with genotype-by-environment interaction: some new aspects

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 75 - 88

Zusammenfassung

Abstract

A common problem in multi-environment trials arises when some genotypeby- environment combinations are missing. In Arciniegas-Alarcón et al. (2010) we outlined a method of data imputation to estimate the missing values, the computational algorithm for which was a mixture of regression and lower-rank approximation of a matrix based on its singular value decomposition (SVD). In the present paper we provide two extensions to this methodology, by including weights chosen by cross-validation and allowing multiple as well as simple imputation. The three methods are assessed and compared in a simulation study, using a complete set of real data in which values are deleted randomly at different rates. The quality of the imputations is evaluated using three measures: the Procrustes statistic, the squared correlation between matrices and the normalised root mean squared error between these estimates and the true observed values. None of the methods makes any distributional or structural assumptions, and all of them can be used for any pattern or mechanism of the missing values.

Schlüsselwörter

  • cross-validation
  • singular value decomposition
  • imputation
  • genotype-by-environment interaction
  • weights
  • missing values
Uneingeschränkter Zugang

Statistical analysis of yield trials by AMMI analysis of genotype × environment interaction

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 89 - 102

Zusammenfassung

Abstract

The genotype by environment interaction (GEI)) has an influence on the selection and recommendation of cultivars. The aim of this work is to study the effect of GEI and evaluate the adaptability and stability of productivity (kg/ha) of nine maize genotypes using AMMI model (Additive Main effects and Multiplicative Interaction). The AMMI model is one of the most widely used statistical tools in the analysis of multiple-environment trials. It has two purposes, namely understanding complex GEI and increasing accuracy. Nevertheless, the AMMI model is a widely used tool for the analysis of multiple-environment trials, where the data are represented by a two-way table of GEI means. In the complete tables, least squares estimation for the AMMI model is equivalent to fitting an additive two-way ANOVA model for the main effects and applying a singular value decomposition to the interaction residuals. It assumes equal weights for all GEI means implicitly. The experiments were conducted in twenty environments, and the experimental design was a randomized complete block design with four repetitions. The AMMI model identified the best combinations of genotypes and environments with respect to the response variable. This paper concerns a basic and a common application of AMMI: yield-trial analysis without consideration of special structure or additional data for either genotypes or environments.

Schlüsselwörter

  • genotype environment interaction (GEI)
  • adaptability and stability
  • additive main effects and multiplicative interaction model
  • multienvironment trials
Uneingeschränkter Zugang

Analysis of multivariate repeated measures data using a MANOVA model and principal components

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 103 - 114

Zusammenfassung

Abstract

In this paper we consider a set of T repeated measurements on p characteristics on each of n individuals. The n individuals themselves may be divided and randomly assigned to K groups. These data are analyzed using a mixed effect MANOVA model, assuming that the data on an individual have a covariance matrix which is a Kronecker product of two positive definite matrices. Results are illustrated on a data set obtained from experiments with varieties of winter rye.

Schlüsselwörter

  • multivariate repeated measures data (doubly multivariate data)
  • Kronecker product covariance structure
  • maximum likelihood estimates
  • mixed MANOVA model
  • principal component analysis
Uneingeschränkter Zugang

Control treatments in designs with split units generated by Latin squares

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 125 - 142

Zusammenfassung

Abstract

This paper deals with two-factor experiments with split units. The whole plot treatments occur in a repeated Latin square, modified Latin square or Youden square, while subplot treatments occur in a block design within the whole plots. The statistical properties of the considered designs are examined. Special attention is paid to the case where one of the treatments is an individual control or an individual standard treatment. In addition, we give a brief overview of work on the design of experiments using the considered designs, as well as possible arrangements of controls in the experiments.

Schlüsselwörter

  • Latin square
  • Youden square
  • split units
  • efficiency factors
  • merging treatment method
Uneingeschränkter Zugang

The influence of weather conditions on annual height increments of Scots pine

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 143 - 152

Zusammenfassung

Abstract

Annual height increments are a very important characteristic of Scots pine. They have a direct effect on the determination of the dendrometric properties of a stand, such as volume increment. In the present study the data concern height increments of the main shoot in selected age classes of trees (age 72 to 92 years). A relationship is determined between the values of the increments and meteorological conditions such as temperature, precipitation and sunshine. On the basis of lasso regression analysis, precipitation in the year preceding the incremental season was shown to have the greatest effect on height increments of Scots pine.

Schlüsselwörter

  • height increments
  • lasso regression
  • precipitation
  • Scots pine (Pinus sylvestris L.)
  • sunshine
  • temperature
Uneingeschränkter Zugang

Biometric characteristics of interspecific hybrids in the genus Secale

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 153 - 170

Zusammenfassung

Abstract

Breeding work using European rye populations has resulted in a considerable reduction of genetic variation in breeding materials of that species. Many taxa from the genus Secale may constitute a potential source of genetic variation in rye breeding. A source of new genetic variation can be found in such species as Secale montanum and Secale vavilovii, which are sources of resistance to fusarium ear blight and septoria leaf blotch, while Secale vavilovii may also be a source of sterilising cytoplasm. The aim of this study was to assess the efficiency of crossing the wild species Secale vavilovii and the rye subspecies Secale cereale subsp. afghanicum, Secale cereale subsp. ancestrale, Secale cereale subsp. dighoricum, Secale cereale subsp. segetale with the crop species Secale cereale ssp. cereale, and to produce F1 hybrids and describe selected morphological traits. Observations of biometric traits indicate that the F1 crosses produced may be potential sources of variation for common rye. The greatest variation in terms of all analysed phenotypic traits combined was found for the cross combinations S. c. ssp. cereale cv. Amilo × S. c. ssp. ancestrale and S. c. ssp. cereale cv. Dańkowskie Diament × S. c. ssp. dighoricum. The hybrids showed considerable variation in the analysed biometric traits within individual cross combinations.

Schlüsselwörter

  • Secale genus
  • interspecific crossing
  • biometrical traits
  • F1 hybrids
Uneingeschränkter Zugang

An evaluation of the efficiency of plant protection products via nonlinear statistical methods – a simulation study

Online veröffentlicht: 20 Dec 2014
Seitenbereich: 171 - 179

Zusammenfassung

Abstract

A nonlinear statistical approach was used to evaluate the efficiency of plant protection products. The methodology presented can be implemented when the observations in an experiment are recorded as success or failure. This occurs, for example, when following the application of a herbicide or pesticide, a single weed or insect is classified as alive (failure) or dead (success). Then a higher probability of success means a higher efficiency of the tested product. Using simulated data sets, a comparison was made of three methods based on the logit, probit and threshold models, with special attention to the effect of sample size and number of replications on the accuracy of the estimation of probabilities.

Schlüsselwörter

  • threshold model
  • logistic model
  • plant protection
  • simulated data

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