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 tryanother609@gmail.com

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

Examples

Run this code

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

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