metan (version 1.15.0)

ge_stats: Statistics for genotype-vs-environment interaction

Description

Computes (i) within-environment analysis of variance, GEI effect, GEI means, and genotype plus GEI effects; (ii) parametric statistics including AMMI-based indexes, Annicchiarico's genotypic confidence index (1992), Ecovalence (Wricke, 1965), regression-based stability (Eberhart and Russell., 1966), Shukla's stability variance parameter (1972); and (iii) nonparametric statistics including Fox's stability function (Fox et al. 1990), superiority index (Lin and Binns, 1988), Huehn's stability statistics (Huehn, 1979), and Thennarasu (1995) statistics.

Usage

ge_stats(.data, env, gen, rep, resp, verbose = TRUE, prob = 0.05)

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 use, for example, resp = c(var1, var2, var3).

verbose

Logical argument. If verbose = FALSE the code will run silently.

prob

The probability error assumed.

Value

An object of class ge_stats which is a list with one data frame for each variable containing the computed indexes.

Details

The function computes the statistics and ranks for the following stability indexes. "Y" (Response variable), "CV" (coefficient of variation), "ACV" (adjusted coefficient of variation calling ge_acv() internally); POLAR (Power Law Residuals, calling ge_polar() internally) "Var" (Genotype's variance), "Shukla" (Shukla's variance, calling Shukla() internally), "Wi_g", "Wi_f", "Wi_u" (Annichiarrico's genotypic confidence index for all, favorable and unfavorable environments, respectively, calling Annicchiarico() internally ), "Ecoval" (Wricke's ecovalence, ecovalence() internally), "Sij" (Deviations from the joint-regression analysis) and "R2" (R-squared from the joint-regression analysis, calling ge_reg() internally), "ASV" (AMMI-stability value), "SIPC" (sum of the absolute values of the IPCA scores), "EV" (Average of the squared eigenvector values), "ZA" (Absolute values of the relative contributions of the IPCAs to the interaction), and "WAAS" (Weighted Average of Absolute Scores), by calling AMMI_indexes() internally; "HMGV" (Harmonic mean of the genotypic value), "RPGV" (Relative performance of the genotypic values), "HMRPGV" (Harmonic mean of the relative performance of the genotypic values), by calling blup_indexes() internally; "Pi_a", "Pi_f", "Pi_u" (Superiority indexes for all, favorable and unfavorable environments, respectively, calling superiority() internally), "Gai" (Geometric adaptability index, calling gai() internally), "S1" (mean of the absolute rank differences of a genotype over the n environments), "S2" (variance among the ranks over the k environments), "S3" (sum of the absolute deviations), "S6" (relative sum of squares of rank for each genotype), by calling Huehn() internally; and "N1", "N2", "N3", "N4" (Thennarasu"s statistics, calling Thennarasu() internally ).

References

Annicchiarico, P. 1992. Cultivar adaptation and recommendation from alfalfa trials in Northern Italy. Journal of Genetic \& Breeding, 46:269-278

Doring, T.F., and M. Reckling. 2018. Detecting global trends of cereal yield stability by adjusting the coefficient of variation. Eur. J. Agron. 99: 30-36. 10.1016/j.eja.2018.06.007

Doring, T.F., S. Knapp, and J.E. Cohen. 2015. Taylor's power law and the stability of crop yields. F. Crop. Res. 183: 294-302. 10.1016/j.fcr.2015.08.005

Eberhart, S.A., and W.A. Russell. 1966. Stability parameters for comparing Varieties. Crop Sci. 6:36-40. 10.2135/cropsci1966.0011183X000600010011x

Fox, P.N., B. Skovmand, B.K. Thompson, H.J. Braun, and R. Cormier. 1990. Yield and adaptation of hexaploid spring triticale. Euphytica 47:57-64. 10.1007/BF00040364.

Huehn, V.M. 1979. Beitrage zur erfassung der phanotypischen stabilitat. EDV Med. Biol. 10:112.

Kang, M.S., and H.N. Pham. 1991. Simultaneous Selection for High Yielding and Stable Crop Genotypes. Agron. J. 83:161. 10.2134/agronj1991.00021962008300010037x

Lin, C.S., and M.R. Binns. 1988. A superiority measure of cultivar performance for cultivar x location data. Can. J. Plant Sci. 68:193-198. 10.4141/cjps88-018

Olivoto, T., A.D.C. L\'ucio, J.A.G. da silva, V.S. Marchioro, V.Q. de Souza, and E. Jost. 2019a. Mean performance and stability in multi-environment trials I: Combining features of AMMI and BLUP techniques. Agron. J. 111:2949-2960. 10.2134/agronj2019.03.0220

Mohammadi, R., & Amri, A. (2008). Comparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments. Euphytica, 159(3), 419-432. 10.1007/s10681-007-9600-6

Shukla, G.K. 1972. Some statistical aspects of partitioning genotype-environmental components of variability. Heredity. 29:238-245. 10.1038/hdy.1972.87

Thennarasu, K. 1995. On certain nonparametric procedures for studying genotype x environment interactions and yield stability. Ph.D. thesis. P.J. School, IARI, New Delhi, India.

Wricke, G. 1965. Zur berechnung der okovalenz bei sommerweizen und hafer. Z. Pflanzenzuchtg 52:127-138.

Examples

# NOT RUN {
library(metan)

model <- ge_stats(data_ge, ENV, GEN, REP, GY)
get_model_data(model, "stats")
# }
# NOT RUN {

# }