Tese
Índices de estabilidade genotípica e seleção simultânea multivariada: uma nova abordagem
Fecha
2019-12-19Autor
Olivoto, Tiago
Institución
Resumen
In order to better understand and explore the genotype-environment interaction (GEI) in plant
breeding, the development of new methods for adaptability and stability analysis, as well as the
improvement of existing ones, is necessary. This study introduces the theoretical foundations,
shows the numerical application and the implementation into a statistical software of new indexes
for genotypic stability and multivariate simultaneous selection in plant breeding. The singular value
decomposition of a two-way matrix containing the BLUPs (Best Linear Unbiased Prediction) of the
GEI effects obtained in a linear mixed-effect model (LMM) was used to produce biplots useful in
identifying the patterns of a random structure of GEI. A new quantitative index of genotypic stability
called WAASB, based on the weighted average of the absolute value decomposition scores of the
BLUPs matrix for the effects of IGA obtained in an MLM is proposed. By definition, the lower the
WAASB value, the more stable a given genotype is. It is also introduced the theoretical foundations
of a superiority index that allows weighting between stability (WAASB) and mean performance (Y),
which was conveniently called WAASBY. The WAASBY assumes values in the range of 0−100,
with 100 being assigned to the ideotype, i.e., the genotype that was most stable and that best
performed on average among those considered in the test environments. A multi-trait stability index
(MTSI) is used to extend the WAASB and WAASBY indexes to a multivariate structure, thus
allowing selection for stability or simultaneous selection for stability and mean performance based
on several traits. The application of these indexes is illustrated using real data from multienvironment
trials with white oat (Avena sativa L.) crop. The WAASB allowed the quantification of
genotypic stability and the identification of genotype groups with different patterns for stability and
mean performance. Using the WAASBY index it was possible to identify genotypes that combine
simultaneously high performance and yield stability. In the context of multivariate selection, positive
selection differentials (SD) (1.75% ≤ SD ≤ 17.8%) were observed for trait means that wanted to
increase and negative (SD = −11.7%) for one variable that wanted to reduce. The negative DS
obtained for the WAASB index (−63% ≤ SD ≤ −12%) suggesting that the selected genotypes were
more stable. Reliable stability measures using WAASB can help breeders and agronomists make
the right decisions when selecting or recommending genotypes. Besides, the simultaneous
selection index, WAASBY, will be useful when selection considers different weights for stability and
mean performance. The MTSI has broad applicability in simultaneous selection for stability and
mean performance based on multiple traits since it provides a unique selection process that is
easy-to-handle and considers the correlation structure between traits. The proposed indices were
implemented in the R metan (multi-environment trial analysis) software package. The development
version of metan is available on Github <https://tiagoolivoto.github.io/metan/> and can be installed
directly via console R using devtools::install_github("TiagoOlivoto/metan"). The
package metan presents a collection of functions for verifying, manipulating and summarizing
typical multi-environment trial data, analyzing single-environment trials using both fixed- and mixedeffect
models, computing parametric and non-parametric stability statistics, and implementing multivariate analysis.