GerminaR"

In GerminaR: Indices and Graphics for Assess Seed Germination Process

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GerminaR is a platform base in open source package to calculate and graphic the main germination indices in R. GerminaR include a web application called “GerminQuant for R” for interactive analysis.

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GerminaR

Project

Analysis for the germination experiment can follow a routine. The functions will de explain according to the data set included in the GerminaR package: "*prosopis*". 

1. Install and load the GerminaR package. Load the "*prosopis*" dataset on your session. In case of using another dataset, you can load your own data and proceed according to the following script:

```r
# Install packages and dependencies

library(GerminaR)
library(dplyr)

# load data

fb <- prosopis %>% 
   mutate(across(c(nacl, temp, rep), as.factor))

# Prosopis data set

fb %>% 
   head(10) %>% 
   kable(caption = "Prosopis dataset")

1. Calculate the germination indices and perform the ANOVA and the mean comparison tests. The user can generate the graphs, expressing their results, which can be either of bars or lines graphics.

# germination analysis (ten variables)

gsm <- ger_summary(SeedN = "seeds"
                   , evalName = "D"
                   , data = fb
                   )

# Prosopis data set processed

gsm %>% 
  head(10) %>% 
  mutate(across(where(is.numeric), ~round(., 2))) %>% 
  kable(caption = "Function ger_summary performe ten germination indices")

Punctual analysis of germination

Germination percentage

## Germination Percentage (GRP)

# analysis of variance

av <- aov(grp ~ nacl*temp + rep, data = gsm)

# mean comparison test

mc_grp <- ger_testcomp(aov = av
                       , comp = c("temp", "nacl")
                       , type = "snk"
                       )

# data result

mc_grp$table %>% 
   kable(caption = "Germination percentage mean comparision")

# bar graphics for germination percentage

grp <- mc_grp$table %>% 
   fplot(data = .
       , type = "bar"
       , x = "temp"
       , y = "grp"
       , group = "nacl"
       , ylimits = c(0, 120, 30)
       , ylab = "Germination ('%')"
       , xlab = "Temperature"
       , glab = "NaCl (MPa)"
       , error = "ste"
       , sig = "sig"
       , color = F
       )

grp

Mean germination time

## Mean Germination Time (MGT)

# analysis of variance

av <- aov(mgt ~ nacl*temp + rep, data = gsm)

# mean comparison test

mc_mgt <- ger_testcomp(aov = av
                       , comp = c("temp", "nacl")
                       , type = "snk")

# data result

mc_mgt$table %>% 
   kable(caption = "Mean germination time comparison")

# bar graphics for mean germination time

mgt <- mc_mgt$table %>% 
   fplot(data = .
       , type = "bar" 
       , x = "temp"
       , y = "mgt"
       , group = "nacl"
       , ylimits = c(0,10, 1)
       , ylab = "Mean germination time (days)"
       , xlab = "Temperature"
       , glab = "NaCl (MPa)"
       , sig = "sig"
       , error = "ste"
       , color = T
       )

mgt

You can add at each plot different arguments as the standard error, significance of the mean test, color, labels and limits. The resulted graphics are performed for publications and allows to insert math expression in the titles.

Cumulative analysis of germination

The cumulative analysis of the germination allows to observe the evolution of the germination process, being able to be expressed as the percentage of germination or with the relative germination.

In time analysis for NaCl

# data frame with percentage or relative germination in time by NaCl

git <- ger_intime(Factor = "nacl"
                  , SeedN = "seeds"
                  , evalName = "D"
                  , method = "percentage"
                  , data = fb
                  )

# data result

git %>% 
   head(10) %>% 
   kable(caption = "Cumulative germination by nacl factor")

# graphic germination in time by NaCl

nacl <- git %>% 
   fplot(data = .
        , type = "line"
        , x = "evaluation"
        , y = "mean"
        , group = "nacl"
        , ylimits = c(0, 110, 10)
        , ylab = "Germination ('%')"
        , xlab = "Day"
        , glab = "NaCl (MPa)"
        , color = T
        , error = "ste"
        )
nacl

In time analysis for temperature

# data frame with percentage or relative germination in time by temperature

git <- ger_intime(Factor = "temp"
                  , SeedN = "seeds"
                  , evalName = "D"
                  , method = "percentage"
                  , data = fb) 

# data result

git %>% 
   head(10) %>% 
   kable(caption = "Cumulative germination by temperature factor")

# graphic germination in time by temperature

temp <- git %>% 
   fplot(data = .
        , type = "line"
        , x = "evaluation"
        , y = "mean"
        , group = "temp"
        , ylimits = c(0, 110, 10)
        , ylab = "Germination ('%')"
        , xlab = "Day"
        , glab = "Temperature"
        , color = F
        ) 
temp

Using ggplot2

As the function fplot() is build using ggplot2 [@R-ggplot2]. You can add more arguments for modify the graphics adding +.

library(ggplot2)

git <- ger_intime(Factor = "temp"
                  , SeedN = "seeds"
                  , evalName = "D"
                  , method = "percentage"
                  , data = fb
                  ) 

ggplot <- git %>% 
   fplot(data = .
        , type = "line"
        , x = "evaluation"
        , y = "mean"
        , group = "temp"
        , ylimits = c(0, 110, 10)
        , ylab = "Germination ('%')"
        , xlab = "Day"
        , glab = "Temperature"
        , color = T
        ) +
  scale_x_continuous(n.breaks = 10, limits = c(0, 11)) 

ggplot

References {-}

if(!file.exists("files/pkgs.bib")){write_bib(c(.packages()),'files/pkgs.bib')}

GerminaR documentation built on May 20, 2022, 1:06 a.m.