EstimateBreed:Estimation of Environmental Variables and Genetic Parameters
Performs analyzes and estimates of environmental covariates and genetic parameters related to selection
strategies and development of superior genotypes. It has two
main functionalities, the first being about prediction models
of covariates and environmental processes, while the second
deals with the estimation of genetic parameters and selection
strategies. Designed for researchers and professionals in
genetics and environmental sciences, the package combines
statistical methods for modeling and data analysis. This
includes the plastochron estimate proposed by Porta et al.
(2024) <doi:10.1590/1807-1929/agriambi.v28n10e278299>, Stress
indices for genotype selection referenced by Ghazvini et al.
(2024) <doi:10.1007/s10343-024-00981-1>, the Environmental
Stress Index described by Tazzo et al. (2024)
<https://revistas.ufg.br/vet/article/view/77035>, industrial
quality indices of wheat genotypes (Szareski et al., 2019),
<doi:10.4238/gmr18223>, Ear Indexes estimation (Rigotti et al.,
2024), <doi:10.13083/reveng.v32i1.17394>, Selection index for
protein and grain yield (de Pelegrin et al., 2017),
<doi:10.4236/ajps.2017.813224>, Estimation of the ISGR -
Genetic Selection Index for Resilience for environmental
resilience (Bandeira et al., 2024)
<https://www.cropj.com/Carvalho_18_12_2024_825_830.pdf>,
estimation of Leaf Area Index (Meira et al., 2015)
<https://www.fag.edu.br/upload/revista/cultivando_o_saber/55d1ef202e494.pdf>,
Restriction of control variability (Carvalho et al., 2023)
<doi:10.4025/actasciagron.v45i1.56156>, Risk of Disease
Occurrence in Soybeans described by Engers et al. (2024)
<doi:10.1007/s40858-024-00649-1> and estimation of genetic
parameters for selection based on balanced experiments (Yadav
et al., 2024) <doi:10.1155/2024/9946332>.
