gpbStat (version 0.4.4)

dti: Estimation of Drought Tolerance Indices.

Description

Estimation of Drought Tolerance Indices.

Usage

dti(data, environment, genotype, traits, ns, st)

Value

TOL

Stress tolerance.

STI

Stress tolerance index.

SSPI

Stress susceptibility percentage index.

YI

Yield index.

YSI

Yield stability index.

RSI

Relative stress index.

MP

Mean productivity.

GMP

Geometric mean productivity

HM

Harmonic mean.

MRP

Mean relative performance.

PYR

Percent yield Reduction.

PYR

Drought Susceptibility Index.

SSP

Stress Susceptibility Index.

Arguments

data

dataframe containing following variables

environment

column with two levels i.e., non-stress and stress conditions

genotype

genotypes evaluated

traits

trait of interest

ns

name of level indicating evaluation under non-stress (irrigated) conditions

st

name of level indicating evaluation under stress conditions

Author

Nandan Patil

Details

Estimation various Drought Tolerance Indices of genotypes evaluated under stress and non-stress conditions of both replicated and non-replicated data.

References

Pour‐Aboughadareh, A., Yousefian, M., Moradkhani, H., Moghaddam Vahed, M., Poczai, P., & Siddique, K. H. (2019). ipastic: An online toolkit to estimate plant abiotic stress indices. Applications in Plant Sciences, 7(7). https://doi.org/10.1002/aps3.11278 Sabouri, A., Dadras, A.R., Singh V., Azar, M., Kouchesfahani, A. S., Taslimi, M. and Jalalifar, R. (2022). Screening of rice drought‑tolerantlines by introducing a new composite selection index and competitive with multivariate methods. Scientific Reports, 12. https://doi.org/10.1038/s41598-022-06123-9 Fischer, R. and Maurer, R. (1978) Drought Resistance in Spring Wheat Cultivars. I. Grain Yield Responses. Australian Journal of Agricultural Research, 29, 897-912. https://doi.org/10.1071/AR9780897

See Also

ltc, ltcchk, ltcmt

Examples

if (FALSE) # Estimating drought tolerance indices
library(gpbStat)

data(datdti)
result1 =  dti(datdti, environment = ENV, genotype = GEN, datdti[,3:8],
              ns = 'NS-DWR', st = 'ST-DWR')
result1

data(datrdti)
result2 = dti(datrdti, environment = ENV, genotype = GEN, datrdti[,4:9],
            ns = 'NS-DWR', st = 'ST-DWR')
result2