Last updated: 2023-11-30

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Knit directory: HenriqueDGen/

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Introduction

Phenotypic data

Descriptive and deviance analysis were performed to verify the distribution and the genotypic effects for resistance to foliar diseases.

Foliar Disease data

suppressMessages(library(tidyverse))
library(here)
here() starts at /Users/luciano/Documents/GitHub/HenriqueDGen
suppressMessages(library(reactable))

# Data read by R using here package to allow the read in any computer with different directory path
PhenoData <- readRDS(here::here("data", "DadosFenotipicos.rds"))
#write.table(PhenoData, file = "data/xx.csv", quote = F, sep = ",", row.names = F)
#PhenoData2 <- read.table("data/xx.csv", header = T, sep = ",")
#saveRDS(PhenoData2, file = here::here("data", "DadosFenotipicos.rds"))
# Add the control information for the Mixed Models analysis
control <- names(table(PhenoData$accession_name)[table(PhenoData$accession_name) > 30])
PhenoData$control <- ifelse(PhenoData$accession_name %in% control, PhenoData$accession_name, "999") 
PhenoData$new <- ifelse(PhenoData$accession_name %in% control, 0, 1)

# Change the Disease names to english abbreviations
colnames(PhenoData)[10:13] <- c("Anth", "WhLS", "BrLS", "BlLS")

Table 1. Phenotypic data for resistance to foliar disease evaluated at the Cassava Germplasm Bank of EMBRAPA, data collected in 2021.

Anthracnosis (Anth), White Leaf spot (WhLS), Brown Leaf spot (BrLS), Blight Leaf Spot (BlLS).

lnfUtl <- colnames(PhenoData)[c(1:6, 14:15)]
PhenoData$talhao_number <- NULL
PhenoData$Idade <- NULL
PhenoData$is_a_control <- NULL
traits <- colnames(PhenoData)[!colnames(PhenoData) %in% lnfUtl]
PhenoData2 <- PhenoData %>% gather(key = traits, value = Y, -all_of(lnfUtl))

saveRDS(PhenoData2, here::here("output", "DadosDoencasv2.RDS"))

Table 2. Data entry for the descriptive analysis and mixed models for resistance of foliar disease in cassava.

Anthracnosis (Anth), White Leaf spot (WhLS), Brown Leaf spot (BrLS), Blight Leaf Spot (BlLS).

Yield Traits

library(reshape2); library(tidyverse)

Attaching package: 'reshape2'
The following object is masked from 'package:tidyr':

    smiths
DadosProdutivos <- read.table(here::here("data", "Dados Produtivos 2011-2022.csv"), header = T, sep = ",",
                              na.strings = "NA")

head(DadosProdutivos)
   Ano      Campo     Local Fazenda Genotipos.BGM Genotipos Delineamento
1 2011 Agroverde1 CruzAlmas   CNPMF      BGM-0023  BGM-0023          DBC
2 2011 Agroverde1 CruzAlmas   CNPMF      BGM-0023  BGM-0023          DBC
3 2011 Agroverde1 CruzAlmas   CNPMF      BGM-0023  BGM-0023          DBC
4 2011 Agroverde1 CruzAlmas   CNPMF      BGM-0025  BGM-0025          DBC
5 2011 Agroverde1 CruzAlmas   CNPMF      BGM-0025  BGM-0025          DBC
6 2011 Agroverde1 CruzAlmas   CNPMF      BGM-0025  BGM-0025          DBC
  Controle Bloco Linha Coluna Stand  AP APsF   DMC   DRY   PTR   PRC  PRNC
1        0     1    27      7    18 128   NA 29.91 12.08 47.81 41.56  6.25
2        0     2    25     14    17 229   NA 29.93 11.61 45.94 35.06 10.88
3        0     3    16     24    20 268   NA 31.52 19.14 71.25 59.95 11.30
4        0     1     7      2    16 174   NA 35.34  6.52 21.25 13.96  7.29
5        0     2     4     11    17 202   NA 26.68  5.51 25.00 19.91  5.09
6        0     3     3     20    17 230   NA 27.92  3.78 16.25  9.19  7.06
    PPA NR Vigor Vigor45D Vigor6M Vigor12M Retencao.foliar
1 46.88 NA    NA       NA      NA       NA              NA
2 49.06 NA    NA       NA      NA       NA              NA
3 56.56 NA    NA       NA      NA       NA              NA
4 21.25 NA    NA       NA      NA       NA              NA
5 27.50 NA    NA       NA      NA       NA              NA
6 29.38 NA    NA       NA      NA       NA              NA
colnames(DadosProdutivos)[c(5, 13:26)] <- c("Genotipo_BGM","AP", "APsF","DMC", "DRY",
                                            "PTR","PRC", "PRNC","PPA","NR","Vigor",
                                            "Vigor45D","Vigor6M","Vigor12M", "RF")

DadosPhen2 <- DadosProdutivos %>% dplyr::select(-c(AP, APsF, PRC, PRNC, Vigor, Vigor45D, Vigor6M))

head(DadosPhen2)
   Ano      Campo     Local Fazenda Genotipo_BGM Genotipos Delineamento
1 2011 Agroverde1 CruzAlmas   CNPMF     BGM-0023  BGM-0023          DBC
2 2011 Agroverde1 CruzAlmas   CNPMF     BGM-0023  BGM-0023          DBC
3 2011 Agroverde1 CruzAlmas   CNPMF     BGM-0023  BGM-0023          DBC
4 2011 Agroverde1 CruzAlmas   CNPMF     BGM-0025  BGM-0025          DBC
5 2011 Agroverde1 CruzAlmas   CNPMF     BGM-0025  BGM-0025          DBC
6 2011 Agroverde1 CruzAlmas   CNPMF     BGM-0025  BGM-0025          DBC
  Controle Bloco Linha Coluna Stand   DMC   DRY   PTR   PPA NR Vigor12M RF
1        0     1    27      7    18 29.91 12.08 47.81 46.88 NA       NA NA
2        0     2    25     14    17 29.93 11.61 45.94 49.06 NA       NA NA
3        0     3    16     24    20 31.52 19.14 71.25 56.56 NA       NA NA
4        0     1     7      2    16 35.34  6.52 21.25 21.25 NA       NA NA
5        0     2     4     11    17 26.68  5.51 25.00 27.50 NA       NA NA
6        0     3     3     20    17 27.92  3.78 16.25 29.38 NA       NA NA
DadosPhenfin <- reshape2::melt(data = DadosPhen2, id.vars = c("Ano", "Campo",
                                                             "Fazenda", "Local",
                                                             "Delineamento","Controle",
                                                             "Genotipo_BGM","Genotipos",
                                                             "Bloco", "Linha",
                                                             "Coluna", "Stand"),
                                     variable.name = "Trait",
                                     value.name = "y") %>%
  dplyr::filter(!is.na(y)) %>% 
  dplyr::mutate(Ano = Ano,
         Campo = Campo,
         Local = Local,
         trial = match(paste(Ano, Campo, Local, sep = "."), unique(paste(Ano, Campo, Local, sep = "."))),
         studyDesign = Delineamento,
         clone = Genotipo_BGM,
         rep = Bloco,
         check = ifelse(Controle == "1", clone, "999"),
         check = ifelse(clone %in% unique(check), clone, "999"),
         new = ifelse(check != "999", 0, 1),
         .keep = "unused") %>% dplyr::select(-c("Genotipos")) %>%
  dplyr::filter(Trait != "NR" | (Trait=="NR" & y < 30))
head(DadosPhenfin)
   Ano      Campo Fazenda     Local Linha Coluna Stand Trait     y trial
1 2011 Agroverde1   CNPMF CruzAlmas    27      7    18   DMC 29.91     1
2 2011 Agroverde1   CNPMF CruzAlmas    25     14    17   DMC 29.93     1
3 2011 Agroverde1   CNPMF CruzAlmas    16     24    20   DMC 31.52     1
4 2011 Agroverde1   CNPMF CruzAlmas     7      2    16   DMC 35.34     1
5 2011 Agroverde1   CNPMF CruzAlmas     4     11    17   DMC 26.68     1
6 2011 Agroverde1   CNPMF CruzAlmas     3     20    17   DMC 27.92     1
  studyDesign    clone rep check new
1         DBC BGM-0023   1   999   1
2         DBC BGM-0023   2   999   1
3         DBC BGM-0023   3   999   1
4         DBC BGM-0025   1   999   1
5         DBC BGM-0025   2   999   1
6         DBC BGM-0025   3   999   1
saveRDS(object = DadosPhenfin, file = here::here("output", "DadosFenotipicos.rds"))

Dendrogram and Shannon-Weaver Index


sessionInfo()
R version 4.3.1 (2023-06-16)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Sonoma 14.0

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: America/Sao_Paulo
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] reshape2_1.4.4  reactable_0.4.4 here_1.0.1      lubridate_1.9.2
 [5] forcats_1.0.0   stringr_1.5.0   dplyr_1.1.2     purrr_1.0.2    
 [9] readr_2.1.4     tidyr_1.3.0     tibble_3.2.1    ggplot2_3.4.3  
[13] tidyverse_2.0.0

loaded via a namespace (and not attached):
 [1] sass_0.4.7        utf8_1.2.3        generics_0.1.3    stringi_1.7.12   
 [5] hms_1.1.3         digest_0.6.33     magrittr_2.0.3    timechange_0.2.0 
 [9] evaluate_0.21     grid_4.3.1        fastmap_1.1.1     plyr_1.8.8       
[13] rprojroot_2.0.3   workflowr_1.7.0   jsonlite_1.8.7    whisker_0.4.1    
[17] promises_1.2.1    fansi_1.0.4       crosstalk_1.2.0   scales_1.2.1     
[21] jquerylib_0.1.4   cli_3.6.1         rlang_1.1.1       ellipsis_0.3.2   
[25] munsell_0.5.0     reactR_0.4.4      withr_2.5.0       cachem_1.0.8     
[29] yaml_2.3.7        tools_4.3.1       tzdb_0.4.0        colorspace_2.1-0 
[33] httpuv_1.6.11     vctrs_0.6.3       R6_2.5.1          lifecycle_1.0.3  
[37] git2r_0.32.0      htmlwidgets_1.6.2 fs_1.6.3          pkgconfig_2.0.3  
[41] pillar_1.9.0      bslib_0.5.1       later_1.3.1       gtable_0.3.3     
[45] glue_1.6.2        Rcpp_1.0.11       xfun_0.40         tidyselect_1.2.0 
[49] rstudioapi_0.15.0 knitr_1.43        htmltools_0.5.6   rmarkdown_2.24   
[53] compiler_4.3.1