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EstimateBreed

EstimateBreed is an R package designed to perform analyses and estimate environmental covariates and genetic parameters related to selection strategies and the development of superior genotypes. The package offers two main functionalities:

  • Prediction models for environmental covariates and processes.
  • Estimation of genetic parameters and selection strategies for developing superior genotypes.

Installation

You can install the development version of EstimateBreed from GitHub with:

if (!requireNamespace("pak", quietly = TRUE)) {
  install.packages("pak")
}
pak::pak("willyanjnr/EstimateBreed")

Genotype selection

Obtain the genetic selection index for resilience (ISGR) for selecting genotypes for environmental stressors, as described by Bandeira et al. (2024).

library(EstimateBreed)

#Obtain environmental deviations
data("desvamb")
DPclim <- with(desvamb,desv_clim(ENV,TMED,PREC))
DPclim
# A tibble: 3 × 5
#  ENV   STMED TMEDR SPREC PRECIR
#  <chr> <dbl> <dbl> <dbl>  <dbl>
# 1 E1     2.65  24.8  5.46   339.
# 2 E2     3.65  23.8  5.27   344.
# 3 E3     2.81  24.5  5.47   362.

#Get the ISGR
data("genot")
isgr_index <- with(genot, isgr(GEN,ENV,NG,MG,CICLO))
isgr_index
#    Gen Env      ISGR
# 26 L454  E1  6.489941
# 22 L455  E1  7.084315
# 19 L541  E1  7.653157
# 18 L367  E1  7.862185
# 16 L380  E1  8.329434
# 12 L393  E1  9.638909
# 10 L439  E1 10.552056
# 28 L298  E3 12.209433
# 30 L358  E2 23.347984
# 29 L346  E2 23.793351
# 27 L195  E2 24.719927
# 25 L179  E2 25.747317
# 24 L359  E2 26.300686
# 23 L345  E2 26.886419
# 1  L445  E1 27.255375
# 21 L185  E2 28.211433
# 20 L310  E2 28.942165
# 17 L178  E2 31.418785
# 15 L261  E2 33.424611
# 14 L269  E2 34.605133
# 13 L209  E2 35.959423
# 11 L263  E2 39.127798
# 9  L201  E2 43.145922
# 8  L299  E2 45.686042
# 7  L152  E2 48.926278
# 6   L26  E2 52.988109
# 5  L166  E2 57.596139
# 4  L155  E2 64.251152
# 3  L277  E2 74.756384
# 2  L162  E2 86.543916

Selection of transgressive genotypes with the selection differential (mean and standard deviations).

library(EstimateBreed)

Gen <- paste0("G", 1:20)
Var <- round(rnorm(20, mean = 3.5, sd = 0.8), 2)
Control <- rep(3.8, 20)

data <- data.frame(Gen,Var,Control)

with(data,transg(Gen,Var,Control))

Returns the general parameters and the genotypes selected for each treshold. Also plot a representative graph of the selected genotypes based on the mean and standard deviations.

---------------------------------------------------------------------
Selection of Transgressive Genotypes - Selection Differential (SD)
---------------------------------------------------------------------
Parameters:
---------------------------------------------------------------------
Overall Mean         : 3.566
Control Mean         : 3.800
Standard Deviation   : 0.603
Mean + 1SD           : 4.169
Mean + 2SD           : 4.771
Mean + 3SD           : 5.374

---------------------------------------------------------------------
Genotypes above each threshold:
---------------------------------------------------------------------
Genotypes above Control Mean : G4, G7, G8, G9, G12, G14,
  G20 
Genotype above Overall Mean : G4, G7, G8, G9, G12, G14,
  G16, G18, G20 
Genotypes above Mean + 1SD : G7, G9, G20 
Genotypes above Mean + 2SD : G7 
Genotypes above Mean + 3SD     : None
---------------------------------------------------------------------

Estimation of environmental variables and processes

Predict ∆T to determine the ideal times to apply agricultural pesticides.

library(EstimateBreed)

# Forecasting application conditions
tdelta(-53.696944444444,-28.063888888889,type=1,days=10)

# Retrospective analysis of application conditions
tdelta(-53.6969,-28.0638,type=2,days=10,dates=c("2023-01-01","2023-05-01"))

Estimation of soybean plastochron using average air temperature and number of nodes

library(EstimateBreed)
data("pheno")

with(pheno, plast(GEN,TMED,EST,NN,habit="ind",plot=TRUE))

#

Documentation

Complete documentation can be found when using the package within R.

Citing

When citing this package, please use,

library(EstimateBreed)
citation("EstimateBreed")

To cite package ‘EstimateBreed’ in publications use:

  Willyan Jr. A. Bandeira, Ivan R. Carvalho, Murilo V. Loro, Leonardo
  C. Pradebon, José A. G. da Silva (2025). _EstimateBreed: Estimation
  of Environmental Variables and Genetic Parameters_. R package
  version 0.1.0, <https://github.com/willyanjnr/EstimateBreed>.

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {EstimateBreed: Estimation of Environmental Variables and Genetic Parameters},
    author = {{Willyan Jr. A. Bandeira} and {Ivan R. Carvalho} and {Murilo V. Loro} and {Leonardo C. Pradebon} and {José A. G. da Silva}},
    year = {2025},
    note = {R package version 0.1.0},
    url = {https://github.com/willyanjnr/EstimateBreed},
  }

Getting Help

  • If you find any errors, please make a report with the commands used so that we can repeat, check and adjust the functions! Send it to github or send an email to bandeira.wjab@gmail.com.

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Version

Install

install.packages('EstimateBreed')

Monthly Downloads

197

Version

1.0.2

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Maintainer

Willyan Junior Adorian Bandeira

Last Published

November 3rd, 2025

Functions in EstimateBreed (1.0.2)

genot

Data: GxE Interaction
indviab

Ear Indexes
linearest

Estimates using polynomial equations.
isgr

ISGR - Genetic Selection Index for Resilience
hw

Hectolitre weight of cereals
is_qindustrial

Industrial quality of wheat
lin

Data: Wheat Data Set with Protein and Grain Yield
ptermal

Photothermal Index
risk

Risk of Disease Occurrence in Soybeans
genot2

Data Set for obtaining genetic parameters.
transg

Selection Differential (Mean and Deviations)
restr

Restriction of control variability
maize

Data: Maize Dataset
vig

Data Set for Seed Vigor Extraction
ptn

Data: Wheat Dataset 1
trigo

Data: Wheat Dataset 3
pheno

Soybean Plastochron Estimation Data Set
plast

Soybean plastochron estimation
tdelta

Optimum conditions for pesticide application
tamef

Effective Population Size
termaldata

Data Set with air temperature and incident radiation.
stind

Stress indices for genotype selection
optemp

Plotting the optimum and cardinal temperatures for crops
lai

Leaf Area Index (LAI)
ptnrg

Data: Wheat Dataset 2
rend_ind

Peeling Index and Industrial Yield
leafarea

Data Set for Leaf Area Index
desvamb

Data: Data set for calculating the environmental deviation
default_seg

Standard Segregation
didint

Allelic and genotype-environment interactions
desv_clim

Auxiliary function for calculating ISGR
atsum

Accumulated Thermal Sum
COI

Inbreeding coefficient
SG

General Selection Gain Function
genpar

Genetic parameters for selection
het

Heterosis and Heterobeltiosis
is_ptnerg

Selection index for protein and grain yield
aveia

Dataset: Oat data
clima

Data: Climate Data Set for Predictions
coefend

Data: Data: Endogamy Coefficient Data Set
itu

Environmental Stress Index