R Markdown
MATRIZ_DE_DATOS_ANTIESPORULANTES <- read_excel("C:/Users/JuanSebH2/Downloads/Archivos/MATRIZ DE DATOS ANTIESPORULANTES.xlsx",
sheet = "Union")
Anti=data.frame(MATRIZ_DE_DATOS_ANTIESPORULANTES)
Anti
## Trt Esporu Variedad Rep Tiempo
## 1 Maxcontrol 1 VIPink 1 24
## 2 Maxcontrol 1 VIPink 1 48
## 3 Bioperac 0 VIPink 1 24
## 4 Bioperac 1 VIPink 1 48
## 5 ACPM+Redux 0 VIPink 1 24
## 6 ACPM+Redux 0 VIPink 1 48
## 7 Control 0 VIPink 1 24
## 8 Control 0 VIPink 1 48
## 9 Maxcontrol 1 VIPink 2 24
## 10 Maxcontrol 1 VIPink 2 48
## 11 Bioperac 0 VIPink 2 24
## 12 Bioperac 1 VIPink 2 48
## 13 ACPM+Redux 0 VIPink 2 24
## 14 ACPM+Redux 0 VIPink 2 48
## 15 Control 0 VIPink 2 24
## 16 Control 0 VIPink 2 48
## 17 Maxcontrol 1 VIPink 3 24
## 18 Maxcontrol 1 VIPink 3 48
## 19 Bioperac 0 VIPink 3 24
## 20 Bioperac 0 VIPink 3 48
## 21 ACPM+Redux 0 VIPink 3 24
## 22 ACPM+Redux 0 VIPink 3 48
## 23 Control 0 VIPink 3 24
## 24 Control 0 VIPink 3 48
## 25 Maxcontrol 1 VIPink 4 24
## 26 Maxcontrol 1 VIPink 4 48
## 27 Bioperac 0 VIPink 4 24
## 28 Bioperac 1 VIPink 4 48
## 29 ACPM+Redux 0 VIPink 4 24
## 30 ACPM+Redux 0 VIPink 4 48
## 31 Control 0 VIPink 4 24
## 32 Control 0 VIPink 4 48
## 33 Maxcontrol 1 FullMonty 1 24
## 34 Maxcontrol 1 FullMonty 1 48
## 35 Bioperac 1 FullMonty 1 24
## 36 Bioperac 1 FullMonty 1 48
## 37 ACPM+Redux 0 FullMonty 1 24
## 38 ACPM+Redux 0 FullMonty 1 48
## 39 Control 0 FullMonty 1 24
## 40 Control 0 FullMonty 1 48
## 41 Maxcontrol 1 FullMonty 2 24
## 42 Maxcontrol 1 FullMonty 2 48
## 43 Bioperac 1 FullMonty 2 24
## 44 Bioperac 1 FullMonty 2 48
## 45 ACPM+Redux 0 FullMonty 2 24
## 46 ACPM+Redux 0 FullMonty 2 48
## 47 Control 0 FullMonty 2 24
## 48 Control 0 FullMonty 2 48
## 49 Maxcontrol 1 FullMonty 3 24
## 50 Maxcontrol 1 FullMonty 3 48
## 51 Bioperac 1 FullMonty 3 24
## 52 Bioperac 1 FullMonty 3 48
## 53 ACPM+Redux 0 FullMonty 3 24
## 54 ACPM+Redux 0 FullMonty 3 48
## 55 Control 0 FullMonty 3 24
## 56 Control 0 FullMonty 3 48
## 57 Maxcontrol 1 FullMonty 4 24
## 58 Maxcontrol 1 FullMonty 4 48
## 59 Bioperac 1 FullMonty 4 24
## 60 Bioperac 1 FullMonty 4 48
## 61 ACPM+Redux 0 FullMonty 4 24
## 62 ACPM+Redux 0 FullMonty 4 48
## 63 Control 0 FullMonty 4 24
## 64 Control 0 FullMonty 4 48
## 65 Maxcontrol 1 Momentum 1 24
## 66 Maxcontrol 1 Momentum 1 48
## 67 Bioperac 1 Momentum 1 24
## 68 Bioperac 0 Momentum 1 48
## 69 ACPM+Redux 1 Momentum 1 24
## 70 ACPM+Redux 0 Momentum 1 48
## 71 Control 0 Momentum 1 24
## 72 Control 0 Momentum 1 48
## 73 Maxcontrol 1 Momentum 2 24
## 74 Maxcontrol 1 Momentum 2 48
## 75 Bioperac 1 Momentum 2 24
## 76 Bioperac 0 Momentum 2 48
## 77 ACPM+Redux 1 Momentum 2 24
## 78 ACPM+Redux 0 Momentum 2 48
## 79 Control 0 Momentum 2 24
## 80 Control 0 Momentum 2 48
## 81 Maxcontrol 1 Momentum 3 24
## 82 Maxcontrol 1 Momentum 3 48
## 83 Bioperac 1 Momentum 3 24
## 84 Bioperac 0 Momentum 3 48
## 85 ACPM+Redux 0 Momentum 3 24
## 86 ACPM+Redux 0 Momentum 3 48
## 87 Control 0 Momentum 3 24
## 88 Control 0 Momentum 3 48
## 89 Maxcontrol 1 Momentum 4 24
## 90 Maxcontrol 1 Momentum 4 48
## 91 Bioperac 1 Momentum 4 24
## 92 Bioperac 0 Momentum 4 48
## 93 ACPM+Redux 0 Momentum 4 24
## 94 ACPM+Redux 0 Momentum 4 48
## 95 Control 0 Momentum 4 24
## 96 Control 0 Momentum 4 48
collapsibleTree(Anti, hierarchy=c("Variedad", "Trt", "Tiempo", "Rep"), collapsed =F)
#table(Anti$Trt)
#table(Anti$Variedad)
library(ggplot2)
# Gráfico de barras
ggplot(Anti, aes(x = factor(Variedad), fill = factor(Esporu))) +
geom_bar(position = "dodge") +
labs(title = "Comportamiento de la esporulación de Mildeo Velloso (Peronospora sparsa)
en las tres variedades de rosa" ,x = "Tratamientos", y = "N° de tallos", fill = "Esporulación") +
#facet_wrap(~tiempo)+
theme_update()
ggplot(Anti, aes(x = factor(Variedad), fill = factor(Esporu))) +
geom_bar(position = "dodge") +
labs(title = "Comportamiento de la esporulación de Mildeo Velloso (Peronospora sparsa)
en las tres variedades de rosa y los dos tiempo de evaluación" ,x = "Tratamientos", y = "N° de tallos", fill = "Esporulación") +
facet_wrap(~Tiempo)+
theme_update()
library(ggplot2)
# Gráfico de barras
ggplot(Anti, aes(x = factor(Trt), fill = factor(Esporu))) +
geom_bar(position = "dodge") +
labs(title = "Comportamiento de la esporulación de Mildeo Velloso (Peronospora sparsa)
frente a los productos de evaluación en tres variedades de rosa" ,x = "Tratamientos", y = "N° de tallos", fill = "Esporulación") +
#ggtitle()+
theme_update()
library(ggplot2)
# Gráfico de barras
ggplot(Anti, aes(x = factor(Trt), fill = factor(Esporu))) +
geom_bar(position = "dodge") +
labs(title = "Comportamiento de la esporulación de Mildeo Velloso (Peronospora sparsa)
frente a los productos y tiempos de evaluación en tres variedades de rosa" ,x = "Tratamientos", y = "N° de tallos", fill = "Esporulación") +
facet_wrap(~Tiempo)+
theme_update()
ggplot(Anti, aes(x = "", fill = factor(Esporu))) +
geom_bar(width = 1) +
coord_polar("y", start = 0) +
facet_wrap(~Variedad) +
labs(x = NULL, y = NULL, fill = "Esporulación") +
ggtitle("Grafico 3. Grafico de tortas", subtitle = "Grafico de tortas")+
#facet_wrap(~Tiempo)+
theme_update()
ggplot(Anti, aes(x = "", fill = factor(Esporu))) +
geom_bar(width = 1) +
coord_polar("y", start = 0) +
facet_wrap(~Variedad) +
labs(title = "Comportamiento de la esporulación de Mildeo Velloso (Peronospora sparsa)
en función de los dos tiempo de evalucación",x = NULL, y = NULL, fill = "Esporulación") +
#ggtitle("Grafico 3. Grafico de tortas en función de tiempo", subtitle = "Grafico de tortas divididas por los tiempo")+
facet_wrap(~Tiempo)+
theme_update()
modelo <- glm(Esporu ~ Variedad + Trt + Tiempo, data = Anti, family = binomial)
summary(modelo)
##
## Call:
## glm(formula = Esporu ~ Variedad + Trt + Tiempo, family = binomial,
## data = Anti)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.27582 1.41168 -0.195 0.845093
## VariedadMomentum -0.93970 1.00162 -0.938 0.348151
## VariedadVIPink -2.35634 1.09887 -2.144 0.032007 *
## TrtBioperac 3.46411 1.00392 3.451 0.000559 ***
## TrtControl -18.12210 3404.15171 -0.005 0.995752
## TrtMaxcontrol 23.82276 3379.25172 0.007 0.994375
## Tiempo -0.04045 0.03474 -1.164 0.244255
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 131.035 on 95 degrees of freedom
## Residual deviance: 38.704 on 89 degrees of freedom
## AIC: 52.704
##
## Number of Fisher Scoring iterations: 19
library(multcomp)
## Loading required package: mvtnorm
## Loading required package: survival
## Loading required package: TH.data
## Loading required package: MASS
##
## Attaching package: 'MASS'
## The following object is masked from 'package:dplyr':
##
## select
##
## Attaching package: 'TH.data'
## The following object is masked from 'package:MASS':
##
## geyser
tukey_trt <- glht(modelo, linfct = mcp(Trt = "Tukey"))
summary(tukey_trt)
##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: glm(formula = Esporu ~ Variedad + Trt + Tiempo, family = binomial,
## data = Anti)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Bioperac - ACPM+Redux == 0 3.464 1.004 3.451 0.00205 **
## Control - ACPM+Redux == 0 -18.122 3404.152 -0.005 1.00000
## Maxcontrol - ACPM+Redux == 0 23.823 3379.252 0.007 1.00000
## Control - Bioperac == 0 -21.586 3404.152 -0.006 1.00000
## Maxcontrol - Bioperac == 0 20.359 3379.252 0.006 1.00000
## Maxcontrol - Control == 0 41.945 4796.623 0.009 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)
tukey_variedad <- glht(modelo, linfct = mcp(Variedad = "Tukey"))
summary(tukey_variedad)
##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: glm(formula = Esporu ~ Variedad + Trt + Tiempo, family = binomial,
## data = Anti)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Momentum - FullMonty == 0 -0.9397 1.0016 -0.938 0.6156
## VIPink - FullMonty == 0 -2.3563 1.0989 -2.144 0.0809 .
## VIPink - Momentum == 0 -1.4166 1.0150 -1.396 0.3426
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)