metan (version 1.2.1)

env_dissimilarity: Dissimilarity between environments

Description

Computes the dissimilarity between environments based on several approaches. See the section details for more details.

Usage

env_dissimilarity(.data, env, gen, rep, resp)

Arguments

.data

The dataset containing the columns related to Environments, Genotypes, replication/block and response variable(s).

env

The name of the column that contains the levels of the environments.

gen

The name of the column that contains the levels of the genotypes.

rep

The name of the column that contains the levels of the replications/blocks.

resp

The response variable(s). To analyze multiple variables in a single procedure a vector of variables may be used. For example resp = c(var1, var2, var3). Select helpers are also allowed.

Value

A list with the following matrices:

• SPART_CC: The percentage of the single (non cross-over) part of the interaction between genotypes and pairs of environments according to the method proposed by Cruz and Castoldi (1991).

• CPART_CC: The percentage of the complex (cross-over) part of the interaction between genotypes and pairs of environments according to the method proposed by Cruz and Castoldi (1991).

• SPART_RO: The percentage of the single (non cross-over) part of the interaction between genotypes and pairs of environments according to the method proposed by Robertson (1959).

• CPART_RO: The percentage of the complex (cross-over) part of the interaction between genotypes and pairs of environments according to the method proposed by Robertson (1959).

• MSGE: Interaction mean square between genotypes and pairs of environments.

• SSGE: Interaction sum of square between genotypes and pairs of environments.

• correlation: Correlation coefficients between genotypes's average in each pair of environment.

Details

Roberteson (1959) proposed the partition of the mean square of the genotype-environment interaction (MS_GE) into single (S) and complex (C) parts, where \(S = \frac{1}{2}(\sqrt{Q1}-\sqrt{Q2})^2)\) and \(C = (1-r)\sqrt{Q1-Q2}\), being r the correlation between the genotype's average in the two environments; and Q1 and Q2 the genotype mean square in the environments 1 and 2, respectively. Cruz and Castoldi (1991) proposed a new decomposition of the MS_GE, in which the complex part is given by \(C = \sqrt{(1-r)^3\times Q1\times Q2}\).

References

Cruz, C.D., Castoldi, F. (1991). Decomposicao da interacao genotipos x ambientes em partes simples e complexa. Ceres, 38:422-430. Available at: http://www.ceres.ufv.br/ojs/index.php/ceres/article/view/2165.

Robertson, A. (1959). Experimental design on the measurement of heritabilities and genetic correlations. biometrical genetics. New York: Pergamon Press.

Examples

# NOT RUN {
mod <- env_dissimilarity(data_ge, ENV, GEN, REP, GY)
print(mod)
# }