Data set with wheat cultivars and grain rheological characters.

datasets

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>.

Willyan Junior Adorian Bandeira

EstimateBreed

Estimation of Environmental Variables and Genetic Parameters

Ivan Ricardo Carvalho

Murilo Vieira Loro

Leonardo Cesar Pradebon

Jose Antonio Gonzalez da Silva

ptn function

A data.frame with 360 observations and 5 variables:<dl>
 <dt>Cult</dt>
<dd>Wheat cultivars.</dd> <dt>Am</dt>
<dd>Sample identification number.</dd> <dt>NQ</dt>
<dd>Falling Number.</dd> <dt>W</dt>
<dd>Gluten Strength (W).</dd> <dt>PTN</dt>
<dd>Grain Protein.</dd>
</dl>

Format

Data: Wheat Dataset 1 — ptn

A data.frame with 360 observations and 5 variables:<dl>
 <dt>Cult</dt>
<dd>Wheat cultivars.</dd>

 <dt>Am</dt>
<dd>Sample identification number.</dd>

 <dt>NQ</dt>
<dd>Falling Number.</dd>

 <dt>W</dt>
<dd>Gluten Strength (W).</dd>

 <dt>PTN</dt>
<dd>Grain Protein.</dd>


</dl>

ptn: Data: Wheat Dataset 1

Description

Usage

Arguments

Format