sti: Compute stress tolerance indices

In reyzaguirre/st4gi: Statistical tools for genetic improvement

Compute stress tolerance indices

Description

Compute several stress tolerance indices.

Usage

sti(dfr, vars, geno, normal, stress)

Arguments

dfr	The name of the data frame.
vars	The list of variables.
geno	The name of the column that identifies the genotypes.
normal	The identification for the normal group.
stress	The identification for the stress group.

Details

The names of the columns for the variables must follow the convention y.normal and y.stress, so the data frame must be in wide format for the factor with levels normal and stress.

For a variable y with values y_n and y_s under normal and stress conditions, the stress intensity (si) is computed:

si = 1 - \frac{\bar y_s}{\bar y_n}

It ranges between 0 and 1 and the larger the value, the more severe is the stress intensity. Then, the following indices are computed:

• tol : Tolerance.

  tol = y_n - y_s

• yrr : Yield reduction ratio.

  yrr = 1 - \frac{y_s}{y_n}

• ssi : Stress susceptibility index.

  ssi = \frac{yrr}{si}

• sti : Stress tolerance index.

  sti = \frac{y_n \times y_s}{\bar y_n^2}

• mp : Mean productivity.

  mp = \frac{y_n + y_s}{2}

• gmp : Geometric mean productivity.

  gmp = \sqrt{y_n \times y_s}

Value

It returns a data frame with the indices and a data frame with the stress intensity values for each variable. The names for the indices follow the convention y.index.

Author(s)

Raul Eyzaguirre.

References

Fernandez, G.C.J. (1992). Effective Selection Criteria for Assessing Stress Tolerance. In: Kuo, C.G., Ed., Proceedings of the International Symposium on Adaptation of Vegetables and Other Food Crops in Temperature and Water Stress, AVRDC Publication, Tainan, 257-270.

Examples

vars <- c("nmtp", "mtwp", "nnomtp")
sti(potatostress, vars, 'genotype', 'DTWW', 'DTWS')

reyzaguirre/st4gi documentation built on March 29, 2025, 10:38 p.m.