analise.Rmd

---
title: "Relatório análise"
author: "Gabriel Paiva"
date: "2023-01-25"
output:
  word_document: default
  html_document: default
  pdf_document: default
---

```{r}
library(readxl)
library(tidyverse)
library(rstatix)
library(DHARMa)
library(agricolae)
library(patchwork)
library(emmeans)
library(multcomp)
library(ggthemes)
library(knitr)
library(ggpmisc)
library(ec50estimator)
library(drc)
library(car)
```

# Crescimento 1
```{r}
crescimento1 <- read_excel("dados.xlsx") %>% 
  mutate(dose = as.factor(dose))

modelo1 <- aov (cres ~ inoc*dose, data = crescimento1)
anova(modelo1)

plot(simulateResiduals(modelo1))

means_modelo1 <- emmeans (modelo1, ~ inoc*dose, type="response")
means_modelo1

## Comparação dos tratamentos
### Dose - Inoc
emms <-  emmeans(means_modelo1, ~inoc|dose, type = "response")
cld(emms, interaction = "pairwise", Letters = LETTERS)

### Inoc - Dose
emms <-  emmeans(means_modelo1, ~dose|inoc, type = "response")
cld(emms, interaction = "pairwise", Letters = LETTERS)
```

# Crescimento 4
```{r}
crescimento4 <- read_excel("dados.xlsx", 2) %>% 
  mutate(dose = as.factor(dose))

modelo4 <- aov (cres ~ inoc*dose, data = crescimento4)
anova(modelo4)

plot(simulateResiduals(modelo4))

means_modelo4 <- emmeans (modelo4, ~ inoc*dose, type="response")
means_modelo4

## Comparação dos tratamentos
### Dose - Inoc
emms <-  emmeans(means_modelo4, ~inoc|dose, type = "response")
cld(emms, interaction = "pairwise", Letters = LETTERS)

### Inoc - Dose
emms <-  emmeans(means_modelo4, ~dose|inoc, type = "response")
cld(emms, interaction = "pairwise", Letters = LETTERS)
```

# Crescimento 6
```{r}
crescimento6 <- read_excel("dados.xlsx", 3) %>% 
  mutate(dose = as.factor(dose))

modelo6 <- aov (cres ~ inoc*dose, data = crescimento6)
anova(modelo6)

plot(simulateResiduals(modelo6))

means_modelo6 <- emmeans (modelo6, ~ inoc*dose, type="response")
means_modelo6

## Comparação dos tratamentos
### Dose - Inoc
emms <-  emmeans(means_modelo6, ~inoc|dose, type = "response")
cld(emms, interaction = "pairwise", Letters = LETTERS)

### Inoc - Dose
emms <-  emmeans(means_modelo6, ~dose|inoc, type = "response")
cld(emms, interaction = "pairwise", Letters = LETTERS)
```

# MS Parte aérea
```{r}
mspa <- read_excel("dados.xlsx", 4) %>% 
  mutate(dose = as.factor(dose))

modelomspa <- aov (ms_aerea ~ inoc*dose, data = mspa)
anova(modelomspa)

plot(simulateResiduals(modelomspa))

means_modelomspa <- emmeans (modelomspa, ~ inoc*dose, type="response")
means_modelomspa

## Comparação dos tratamentos
### Dose - Inoc
emms <-  emmeans(means_modelomspa, ~inoc|dose, type = "response")
cld(emms, interaction = "pairwise", Letters = LETTERS)

### Inoc - Dose
emms <-  emmeans(means_modelomspa, ~dose|inoc, type = "response")
cld(emms, interaction = "pairwise", Letters = LETTERS)
```

# MS Raiz
```{r}
msrz <- read_excel("dados.xlsx", 5) %>% 
  mutate(dose = as.factor(dose))

modelomsrz <- aov (ms_raiz ~ inoc*dose, data = msrz)
anova(modelomsrz)

plot(simulateResiduals(modelomsrz))

means_modelomsrz <- emmeans (modelomsrz, ~ inoc*dose, type="response")
means_modelomsrz

## Comparação dos tratamentos
### Dose - Inoc
emms <-  emmeans(means_modelomsrz, ~inoc|dose, type = "response")
cld(emms, interaction = "pairwise", Letters = LETTERS)

### Inoc - Dose
emms <-  emmeans(means_modelomsrz, ~dose|inoc, type = "response")
cld(emms, interaction = "pairwise", Letters = LETTERS)
```

```{r}
comb <- read_excel("dados.xlsx", 6) %>% 
  mutate(exp = as.factor(exp),
         cres = as.numeric(cres))

comb %>% 
ggplot(aes(dose, cres, color = exp)) + 
  geom_point()+
  geom_smooth(method = "lm", formula = y ~ x, se = FALSE) +
  stat_poly_eq(formula = y ~ x, eq.with.lhs = "italic((y))~`=`~", aes(label = paste(..eq.label.., ..rr.label.., sep = "~")), parse = TRUE) +
  facet_grid(~inoc) +
  scale_color_manual(values = c("#610d04", "#124203", "#03094a")) +
  labs(x = "Doses (%)",
       y = "Plant height  (cm)",
       color = "Days after planting") +
  ylim(10, 125) +
  scale_x_continuous(breaks = seq(0, 125, by = 25)) +
  theme_classic() +
  theme(plot.title = element_text(hjust = 0.5))

ggsave("Crescimento.png", width=7.5, height=4 , dpi=600)
```

```{r}
comb2 <- read_excel("dados.xlsx", 7) %>% 
  mutate(exp = as.factor(exp),
         cres = as.numeric(cres))

comb2 %>% 
ggplot(aes(dose, cres, color = exp)) + 
  geom_point()+
  geom_smooth(method = "lm", formula = y ~ x, se = FALSE) +
  stat_poly_eq(formula = y ~ x, eq.with.lhs = "italic((y))~`=`~", aes(label = paste(..eq.label.., ..rr.label.., sep = "~")), parse = TRUE) +
  facet_grid(~inoc) +
  scale_color_manual(values = c("#124203", "#03094a")) +
  labs(y = "Shoot (g)",
       x = "Doses (%)",
       color = "Dry dough") +
  scale_x_continuous(breaks = seq(0, 125, by = 25)) +
  theme_classic() +
  theme(plot.title = element_text(hjust = 0.5))

ggsave("Massa seca.png", width=7.5, height=4 , dpi=600)
```