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.
ge_stats(.data, env, gen, rep, resp, verbose = TRUE, prob = 0.05)The dataset containing the columns related to Environments, Genotypes, replication/block and response variable(s).
The name of the column that contains the levels of the environments.
The name of the column that contains the levels of the genotypes.
The name of the column that contains the levels of the replications/blocks.
The response variable(s). To analyze multiple variables in a
single procedure use, for example, resp = c(var1, var2, var3).
Logical argument. If verbose = FALSE the code will run
silently.
The probability error assumed.
An object of class ge_stats which is a list with one data
frame for each variable containing the computed indexes.
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 Resende_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 ).
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.
# NOT RUN {
library(metan)
model <- ge_stats(data_ge, ENV, GEN, REP, GY)
get_model_data(model, "stats")
# }
# NOT RUN {
# }
Run the code above in your browser using DataLab