dti | R Documentation |
Estimation of Drought Tolerance Indices.
dti(data, environment, genotype, traits, ns, st)
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 |
Estimation various Drought Tolerance Indices of genotypes evaluated under stress and non-stress conditions of both replicated and non-replicated data.
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. |
The function can handle both replicated and non-replicated data refer the examples.
Nandan Patil tryanother609@gmail.com
PourâAboughadareh, 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 droughtâtolerantlines 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
ltc, ltcchk, ltcmt
## Not run: # 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
## End(Not run)
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