library(readxl)
library(ggplot2)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
P_G <- read_excel("C:/Users/JuanSebH2/Downloads/Archivos/Datos_repro.xlsx",
sheet = "R (P.Germinacion) ");P_G=data.frame(P_G);P_G #Listo
## Cultivo Repeticion No.germinadas Germinadas Taza.de.germinacion
## 1 Maiz 1 2 23 92
## 2 Maiz 2 2 23 92
## 3 Maiz 3 2 23 92
## 4 Maiz 4 2 23 92
## 5 Pepino 1 9 16 64
## 6 Pepino 2 1 24 96
## 7 Pepino 3 9 16 64
## 8 Pepino 4 1 24 96
CE<- read_excel("C:/Users/JuanSebH2/Downloads/Archivos/Datos_repro.xlsx",
sheet = "R (CE)");CE=data.frame(CE);CE #Listo
## Cultivo CE_cm CE_g
## 1 Frijol Cargamanto_1 378.17 18.91
## 2 Frijol Cargamanto_1 276.17 13.81
## 3 Frijol Cargamanto_2 45.47 2.24
## 4 Frijol Cargamanto_2 40.37 1.98
## 5 Arveja 2416 642.17 32.11
## 6 Arveja 2416 278.17 13.91
## 7 Arveja 2416 642.17 32.11
## 8 Arveja 2416 278.17 13.91
## 9 Garbanzo_1 800.00 40.00
## 10 Garbanzo_1 1070.00 53.50
## 11 Garbanzo_2 1060.00 53.00
## 12 Garbanzo_2 680.00 34.00
G_PL<- read_excel("C:/Users/JuanSebH2/Downloads/Archivos/Datos_repro.xlsx",
sheet = "R (Germinacion PL)");G_PL=data.frame(G_PL);G_PL #Listo
## Cultivo Tratamiento Germinacion Taza.de.germinacion
## 1 Acacia Control 0 0
## 2 Acacia Control 0 0
## 3 Acacia Control 0 0
## 4 Acacia Control 0 0
## 5 Acacia Escarificadas Control 0 0
## 6 Acacia Escarificadas Control 0 0
## 7 Acacia Escarificadas Control 0 0
## 8 Acacia Escarificadas Control 0 0
## 9 Acacia Escarificadas Acido giberelico 7 28
## 10 Acacia Escarificadas Acido giberelico 7 28
## 11 Acacia Escarificadas Acido giberelico 7 28
## 12 Acacia Escarificadas Acido giberelico 7 28
## Problemas.fitosanitarios
## 1 0
## 2 0
## 3 0
## 4 0
## 5 3
## 6 3
## 7 3
## 8 3
## 9 3
## 10 3
## 11 3
## 12 3
C_PL <- read_excel("C:/Users/JuanSebH2/Downloads/Archivos/Datos_repro.xlsx",
sheet = "R (Crecimiento PL)");C_PL=data.frame(C_PL);C_PL#Listo
## Cultivo Tratamiento Replica Lonitud_parte_aerea
## 1 Acacia Control 1 0.0
## 2 Acacia Control 2 0.0
## 3 Acacia Control 3 0.0
## 4 Acacia Control 4 0.0
## 5 Acacia Control 5 0.0
## 6 Acacia Control 6 0.0
## 7 Acacia Control 7 0.0
## 8 Acacia Control 8 0.0
## 9 Acacia Control 9 0.0
## 10 Acacia Control 10 0.0
## 11 Acacia Control 11 0.0
## 12 Acacia Control 12 0.0
## 13 Acacia Control 13 0.0
## 14 Acacia Control 14 0.0
## 15 Acacia Control 15 0.0
## 16 Acacia Control 16 0.0
## 17 Acacia Control 17 0.0
## 18 Acacia Control 18 0.0
## 19 Acacia Control 19 0.0
## 20 Acacia Control 20 0.0
## 21 Acacia Control 21 0.0
## 22 Acacia Control 22 0.0
## 23 Acacia Control 23 0.0
## 24 Acacia Control 24 0.0
## 25 Acacia Control 25 0.0
## 26 Acacia Escarificadas Control 1 0.0
## 27 Acacia Escarificadas Control 2 0.0
## 28 Acacia Escarificadas Control 3 0.0
## 29 Acacia Escarificadas Control 4 0.0
## 30 Acacia Escarificadas Control 5 0.0
## 31 Acacia Escarificadas Control 6 0.0
## 32 Acacia Escarificadas Control 7 0.0
## 33 Acacia Escarificadas Control 8 0.0
## 34 Acacia Escarificadas Control 9 0.0
## 35 Acacia Escarificadas Control 10 0.0
## 36 Acacia Escarificadas Control 11 0.0
## 37 Acacia Escarificadas Control 12 0.0
## 38 Acacia Escarificadas Control 13 0.0
## 39 Acacia Escarificadas Control 14 0.0
## 40 Acacia Escarificadas Control 15 0.0
## 41 Acacia Escarificadas Control 16 0.0
## 42 Acacia Escarificadas Control 17 0.0
## 43 Acacia Escarificadas Control 18 0.0
## 44 Acacia Escarificadas Control 19 0.0
## 45 Acacia Escarificadas Control 20 0.0
## 46 Acacia Escarificadas Control 21 0.0
## 47 Acacia Escarificadas Control 22 0.0
## 48 Acacia Escarificadas Control 23 0.0
## 49 Acacia Escarificadas Control 24 0.0
## 50 Acacia Escarificadas Control 25 0.0
## 51 Acacia Escarificadas Acido giberelico 1 8.0
## 52 Acacia Escarificadas Acido giberelico 2 8.0
## 53 Acacia Escarificadas Acido giberelico 3 20.7
## 54 Acacia Escarificadas Acido giberelico 4 14.5
## 55 Acacia Escarificadas Acido giberelico 5 1.7
## 56 Acacia Escarificadas Acido giberelico 6 8.0
## 57 Acacia Escarificadas Acido giberelico 7 6.0
## 58 Acacia Escarificadas Acido giberelico 8 0.0
## 59 Acacia Escarificadas Acido giberelico 9 0.0
## 60 Acacia Escarificadas Acido giberelico 10 0.0
## 61 Acacia Escarificadas Acido giberelico 11 0.0
## 62 Acacia Escarificadas Acido giberelico 12 0.0
## 63 Acacia Escarificadas Acido giberelico 13 0.0
## 64 Acacia Escarificadas Acido giberelico 14 0.0
## 65 Acacia Escarificadas Acido giberelico 15 0.0
## 66 Acacia Escarificadas Acido giberelico 16 0.0
## 67 Acacia Escarificadas Acido giberelico 17 0.0
## 68 Acacia Escarificadas Acido giberelico 18 0.0
## 69 Acacia Escarificadas Acido giberelico 19 0.0
## 70 Acacia Escarificadas Acido giberelico 20 0.0
## 71 Acacia Escarificadas Acido giberelico 21 0.0
## 72 Acacia Escarificadas Acido giberelico 22 0.0
## 73 Acacia Escarificadas Acido giberelico 23 0.0
## 74 Acacia Escarificadas Acido giberelico 24 0.0
## 75 Acacia Escarificadas Acido giberelico 25 0.0
## Longitud_raiz Longitu_total
## 1 0.0 0.0
## 2 0.0 0.0
## 3 0.0 0.0
## 4 0.0 0.0
## 5 0.0 0.0
## 6 0.0 0.0
## 7 0.0 0.0
## 8 0.0 0.0
## 9 0.0 0.0
## 10 0.0 0.0
## 11 0.0 0.0
## 12 0.0 0.0
## 13 0.0 0.0
## 14 0.0 0.0
## 15 0.0 0.0
## 16 0.0 0.0
## 17 0.0 0.0
## 18 0.0 0.0
## 19 0.0 0.0
## 20 0.0 0.0
## 21 0.0 0.0
## 22 0.0 0.0
## 23 0.0 0.0
## 24 0.0 0.0
## 25 0.0 0.0
## 26 0.0 0.0
## 27 0.0 0.0
## 28 0.0 0.0
## 29 0.0 0.0
## 30 0.0 0.0
## 31 0.0 0.0
## 32 0.0 0.0
## 33 0.0 0.0
## 34 0.0 0.0
## 35 0.0 0.0
## 36 0.0 0.0
## 37 0.0 0.0
## 38 0.0 0.0
## 39 0.0 0.0
## 40 0.0 0.0
## 41 0.0 0.0
## 42 0.0 0.0
## 43 0.0 0.0
## 44 0.0 0.0
## 45 0.0 0.0
## 46 0.0 0.0
## 47 0.0 0.0
## 48 0.0 0.0
## 49 0.0 0.0
## 50 0.0 0.0
## 51 4.0 12.0
## 52 4.5 12.5
## 53 8.5 29.2
## 54 0.5 15.0
## 55 0.0 1.7
## 56 3.5 11.5
## 57 5.7 11.7
## 58 0.0 0.0
## 59 0.0 0.0
## 60 0.0 0.0
## 61 0.0 0.0
## 62 0.0 0.0
## 63 0.0 0.0
## 64 0.0 0.0
## 65 0.0 0.0
## 66 0.0 0.0
## 67 0.0 0.0
## 68 0.0 0.0
## 69 0.0 0.0
## 70 0.0 0.0
## 71 0.0 0.0
## 72 0.0 0.0
## 73 0.0 0.0
## 74 0.0 0.0
## 75 0.0 0.0
P_Via <- read_excel("C:/Users/JuanSebH2/Downloads/Archivos/Datos_repro.xlsx",
sheet = "Prueba de viavilidad (tetrazoli");P_Via=data.frame(P_Via);P_Via #
## Cultivo N..Semillas Viables
## 1 Frijol 5 0
## 2 Frijol 5 0
## 3 Frijol 5 0
## 4 Frijol 5 0
## 5 Maiz 5 4
## 6 Maiz 5 4
## 7 Maiz 5 4
## 8 Maiz 5 4
###PG
NoGer= aov(No.germinadas~Cultivo, P_G)
anova(NoGer)
## Analysis of Variance Table
##
## Response: No.germinadas
## Df Sum Sq Mean Sq F value Pr(>F)
## Cultivo 1 18 18.000 1.6875 0.2416
## Residuals 6 64 10.667
TukeyHSD(NoGer)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = No.germinadas ~ Cultivo, data = P_G)
##
## $Cultivo
## diff lwr upr p adj
## Pepino-Maiz 3 -2.6509 8.6509 0.2416143
library(TukeyC)
## Warning: package 'TukeyC' was built under R version 4.3.2
tc=TukeyC(NoGer,'Cultivo')
plot(tc, title ="No Germinadas")
Ger= aov(Germinadas~Cultivo, P_G)
anova(Ger)
## Analysis of Variance Table
##
## Response: Germinadas
## Df Sum Sq Mean Sq F value Pr(>F)
## Cultivo 1 18 18.000 1.6875 0.2416
## Residuals 6 64 10.667
TukeyHSD(Ger)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Germinadas ~ Cultivo, data = P_G)
##
## $Cultivo
## diff lwr upr p adj
## Pepino-Maiz -3 -8.6509 2.6509 0.2416143
library(TukeyC)
tc=TukeyC(Ger,'Cultivo')
plot(tc, title="Germinadas")
T_G= aov(Taza.de.germinacion~Cultivo, P_G)
anova(T_G)
## Analysis of Variance Table
##
## Response: Taza.de.germinacion
## Df Sum Sq Mean Sq F value Pr(>F)
## Cultivo 1 288 288.00 1.6875 0.2416
## Residuals 6 1024 170.67
TukeyHSD(T_G)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Taza.de.germinacion ~ Cultivo, data = P_G)
##
## $Cultivo
## diff lwr upr p adj
## Pepino-Maiz -12 -34.6036 10.6036 0.2416143
library(TukeyC)
tc=TukeyC(T_G,'Cultivo')
plot(tc, title="Tasa de germinación")
datos_resumen= P_G |>
group_by(Cultivo) |>
summarise(media= mean(No.germinadas),
desviacion=sd(No.germinadas), n=n()) |>
mutate(error=1.96*desviacion/sqrt(n))
ggplot(datos_resumen)+
aes(x=Cultivo, y=media, fill=Cultivo)+
geom_col(strat= 'identity', position = 'dodge', color = 'black')+
labs(x = "Cultivo", y = "No germinadas")+
geom_text(aes(label=c("a","a"), y= media+0.2), color= "black", size=6)+
theme_bw()
## Warning in geom_col(strat = "identity", position = "dodge", color = "black"):
## Ignoring unknown parameters: `strat`
datos_resumen= P_G |>
group_by(Cultivo) |>
summarise(media= mean(Germinadas),
desviacion=sd(Germinadas), n=n()) |>
mutate(error=1.96*desviacion/sqrt(n))
ggplot(datos_resumen)+
aes(x=Cultivo, y=media, fill=Cultivo)+
geom_col(strat= 'identity', position = 'dodge', color = 'black')+
labs(x = "Cultivo", y = "Germinadas")+
geom_text(aes(label=c("a","a"), y= media+2), color= "black", size=6)+
theme_bw()
## Warning in geom_col(strat = "identity", position = "dodge", color = "black"):
## Ignoring unknown parameters: `strat`
datos_resumen= P_G |>
group_by(Cultivo) |>
summarise(media= mean(Taza.de.germinacion),
desviacion=sd(Taza.de.germinacion), n=n()) |>
mutate(error=1.96*desviacion/sqrt(n))
ggplot(datos_resumen)+
aes(x=Cultivo, y=media, fill=Cultivo)+
geom_col(strat= 'identity', position = 'dodge', color = 'black')+
labs(x = "Cultivo", y = "Tasa de germinación")+
geom_text(aes(label=c("a","a"), y= media+4), color= "black", size=6)+
theme_bw()
## Warning in geom_col(strat = "identity", position = "dodge", color = "black"):
## Ignoring unknown parameters: `strat`
###CE
CE_cm= aov(CE_cm~Cultivo, CE)
anova(CE_cm)
## Analysis of Variance Table
##
## Response: CE_cm
## Df Sum Sq Mean Sq F value Pr(>F)
## Cultivo 4 1133145 283286 8.0492 0.009327 **
## Residuals 7 246361 35194
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
TukeyHSD(CE_cm)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = CE_cm ~ Cultivo, data = CE)
##
## $Cultivo
## diff lwr upr p adj
## Frijol Cargamanto_1-Arveja 2416 -133.00 -714.31226 448.3123 0.9167278
## Frijol Cargamanto_2-Arveja 2416 -417.25 -998.56226 164.0623 0.1784751
## Garbanzo_1-Arveja 2416 474.83 -106.48226 1056.1423 0.1141040
## Garbanzo_2-Arveja 2416 409.83 -171.48226 991.1423 0.1889503
## Frijol Cargamanto_2-Frijol Cargamanto_1 -284.25 -955.49158 386.9916 0.5846092
## Garbanzo_1-Frijol Cargamanto_1 607.83 -63.41158 1279.0716 0.0763405
## Garbanzo_2-Frijol Cargamanto_1 542.83 -128.41158 1214.0716 0.1183908
## Garbanzo_1-Frijol Cargamanto_2 892.08 220.83842 1563.3216 0.0124443
## Garbanzo_2-Frijol Cargamanto_2 827.08 155.83842 1498.3216 0.0184451
## Garbanzo_2-Garbanzo_1 -65.00 -736.24158 606.2416 0.9961505
library(TukeyC)
tc=TukeyC(CE_cm,'Cultivo')
plot(tc, title ="Conductividad eléctrica (µS/cm)")
CE_g= aov(CE_g~Cultivo, CE)
anova(CE_g)
## Analysis of Variance Table
##
## Response: CE_g
## Df Sum Sq Mean Sq F value Pr(>F)
## Cultivo 4 2836.2 709.04 8.0586 0.009297 **
## Residuals 7 615.9 87.99
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
TukeyHSD(CE_g)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = CE_g ~ Cultivo, data = CE)
##
## $Cultivo
## diff lwr upr p adj
## Frijol Cargamanto_1-Arveja 2416 -6.65 -35.715643 22.415643 0.9167281
## Frijol Cargamanto_2-Arveja 2416 -20.90 -49.965643 8.165643 0.1774477
## Garbanzo_1-Arveja 2416 23.74 -5.325643 52.805643 0.1141312
## Garbanzo_2-Arveja 2416 20.49 -8.575643 49.555643 0.1889944
## Frijol Cargamanto_2-Frijol Cargamanto_1 -14.25 -47.812114 19.312114 0.5824866
## Garbanzo_1-Frijol Cargamanto_1 30.39 -3.172114 63.952114 0.0763562
## Garbanzo_2-Frijol Cargamanto_1 27.14 -6.422114 60.702114 0.1184152
## Garbanzo_1-Frijol Cargamanto_2 44.64 11.077886 78.202114 0.0123912
## Garbanzo_2-Frijol Cargamanto_2 41.39 7.827886 74.952114 0.0183635
## Garbanzo_2-Garbanzo_1 -3.25 -36.812114 30.312114 0.9961505
library(TukeyC)
tc=TukeyC(CE_g,'Cultivo')
plot(tc, title="Conductividad eléctrica (µS/cm*g)")
orden_cultivos <- c("Garbanzo_1", "Garbanzo_2", "Arveja 2416", "Frijol Cargamanto_1", "Frijol Cargamanto_2")
CE$Cultivo <- factor(CE$Cultivo, levels = orden_cultivos)
datos_resumen= CE |>
group_by(Cultivo) |>
summarise(media= mean(CE_cm),
desviacion=sd(CE_cm), n=n()) |>
mutate(error=1.96*desviacion/sqrt(n))
ggplot(datos_resumen)+
aes(x=Cultivo, y=media, fill=Cultivo)+
geom_col(strat= 'identity', position = 'dodge', color = 'black')+
labs(x = "Cultivo", y = "Conductividad eléctrica (µS/cm)")+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1, size = 7))+
geom_text(aes(label=c("a","a","ab", "ab", "b"), y= media+100), color= "black", size=6)
## Warning in geom_col(strat = "identity", position = "dodge", color = "black"):
## Ignoring unknown parameters: `strat`
datos_resumen= CE |>
group_by(Cultivo) |>
summarise(media= mean(CE_g),
desviacion=sd(CE_g), n=n()) |>
mutate(error=1.96*desviacion/sqrt(n))
ggplot(datos_resumen)+
aes(x=Cultivo, y=media, fill=Cultivo)+
geom_col(strat= 'identity', position = 'dodge', color = 'black')+
labs(x = "Cultivo", y = "Conductividad eléctrica (µS/cm*g)")+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1, size = 7))+
geom_text(aes(label=c("a","a","ab", "ab", "b"), y= media+4), color= "black", size=6)
## Warning in geom_col(strat = "identity", position = "dodge", color = "black"):
## Ignoring unknown parameters: `strat`
#####G_PL
G_PL_Ger= aov(Germinacion~Tratamiento, G_PL)
anova(G_PL_Ger)
## Warning in anova.lm(G_PL_Ger): ANOVA F-tests on an essentially perfect fit are
## unreliable
## Analysis of Variance Table
##
## Response: Germinacion
## Df Sum Sq Mean Sq F value Pr(>F)
## Tratamiento 2 130.67 65.333 2.9672e+33 < 2.2e-16 ***
## Residuals 9 0.00 0.000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
TukeyHSD(G_PL_Ger)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Germinacion ~ Tratamiento, data = G_PL)
##
## $Tratamiento
## diff
## Escarificadas Acido giberelico-Control 7.000000e+00
## Escarificadas Control-Control -5.551115e-16
## Escarificadas Control-Escarificadas Acido giberelico -7.000000e+00
## lwr
## Escarificadas Acido giberelico-Control 7.000000e+00
## Escarificadas Control-Control -8.480609e-16
## Escarificadas Control-Escarificadas Acido giberelico -7.000000e+00
## upr p adj
## Escarificadas Acido giberelico-Control 7.000000e+00 0.0000000
## Escarificadas Control-Control -2.621621e-16 0.0012994
## Escarificadas Control-Escarificadas Acido giberelico -7.000000e+00 0.0000000
library(TukeyC)
tc=TukeyC(G_PL_Ger,'Tratamiento')
## Warning in qt(sig.level, aux_mt$coef[, 3]): NaNs produced
## Warning in qt(sig.level, aux_mt$coef[, 3]): NaNs produced
## Warning in qt(sig.level, aux_mt$coef[, 3]): NaNs produced
## Warning in qt(sig.level, aux_mt$coef[, 3]): NaNs produced
plot(tc, title ="Germinación")
C_PL_TG= aov(Taza.de.germinacion~Tratamiento, G_PL)
anova(C_PL_TG)
## Warning in anova.lm(C_PL_TG): ANOVA F-tests on an essentially perfect fit are
## unreliable
## Analysis of Variance Table
##
## Response: Taza.de.germinacion
## Df Sum Sq Mean Sq F value Pr(>F)
## Tratamiento 2 2090.7 1045.3 2.9672e+33 < 2.2e-16 ***
## Residuals 9 0.0 0.0
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
TukeyHSD(C_PL_TG)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Taza.de.germinacion ~ Tratamiento, data = G_PL)
##
## $Tratamiento
## diff
## Escarificadas Acido giberelico-Control 2.800000e+01
## Escarificadas Control-Control -2.220446e-15
## Escarificadas Control-Escarificadas Acido giberelico -2.800000e+01
## lwr
## Escarificadas Acido giberelico-Control 2.800000e+01
## Escarificadas Control-Control -3.392244e-15
## Escarificadas Control-Escarificadas Acido giberelico -2.800000e+01
## upr p adj
## Escarificadas Acido giberelico-Control 2.800000e+01 0.0000000
## Escarificadas Control-Control -1.048648e-15 0.0012994
## Escarificadas Control-Escarificadas Acido giberelico -2.800000e+01 0.0000000
library(TukeyC)
tc=TukeyC(C_PL_TG,'Tratamiento')
## Warning in qt(sig.level, aux_mt$coef[, 3]): NaNs produced
## Warning in qt(sig.level, aux_mt$coef[, 3]): NaNs produced
## Warning in qt(sig.level, aux_mt$coef[, 3]): NaNs produced
## Warning in qt(sig.level, aux_mt$coef[, 3]): NaNs produced
plot(tc, title="Tasa de germinacion")
datos_resumen= G_PL |>
group_by(Tratamiento) |>
summarise(media= mean(Germinacion),
desviacion=sd(Germinacion), n=n()) |>
mutate(error=1.96*desviacion/sqrt(n))
ggplot(datos_resumen)+
aes(x=Tratamiento, y=media, fill=Tratamiento)+
geom_col(strat= 'identity', position = 'dodge', color = 'black')+
geom_text(aes(label=c("b","a","b"), y= media+2), color= "black", size=6)
## Warning in geom_col(strat = "identity", position = "dodge", color = "black"):
## Ignoring unknown parameters: `strat`
datos_resumen= G_PL |>
group_by(Tratamiento) |>
summarise(media= mean(Taza.de.germinacion),
desviacion=sd(Taza.de.germinacion), n=n()) |>
mutate(error=1.96*desviacion/sqrt(n))
ggplot(datos_resumen)+
aes(x=Tratamiento, y=media, fill=Tratamiento)+
geom_col(strat= 'identity', position = 'dodge', color = 'black')+
geom_text(aes(label=c("b","a", "b"), y= media+2), color= "black", size=6)
## Warning in geom_col(strat = "identity", position = "dodge", color = "black"):
## Ignoring unknown parameters: `strat`
####C_PL
L_PA= aov(Lonitud_parte_aerea~Tratamiento, C_PL)
anova(L_PA)
## Analysis of Variance Table
##
## Response: Lonitud_parte_aerea
## Df Sum Sq Mean Sq F value Pr(>F)
## Tratamiento 2 119.35 59.675 6.2215 0.003219 **
## Residuals 72 690.61 9.592
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
TukeyHSD(L_PA)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Lonitud_parte_aerea ~ Tratamiento, data = C_PL)
##
## $Tratamiento
## diff lwr
## Escarificadas Acido giberelico-Control 2.676000e+00 0.5796733
## Escarificadas Control-Control -5.062617e-16 -2.0963267
## Escarificadas Control-Escarificadas Acido giberelico -2.676000e+00 -4.7723267
## upr p adj
## Escarificadas Acido giberelico-Control 4.7723267 0.0087571
## Escarificadas Control-Control 2.0963267 1.0000000
## Escarificadas Control-Escarificadas Acido giberelico -0.5796733 0.0087571
library(TukeyC)
tc=TukeyC(L_PA,'Tratamiento')
plot(tc, title ="Lonitud_parte_aerea")
L_R= aov(Longitud_raiz~Tratamiento, C_PL)
anova(L_R)
## Analysis of Variance Table
##
## Response: Longitud_raiz
## Df Sum Sq Mean Sq F value Pr(>F)
## Tratamiento 2 19.01 9.5052 5.4761 0.006112 **
## Residuals 72 124.97 1.7358
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
TukeyHSD(L_R)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Longitud_raiz ~ Tratamiento, data = C_PL)
##
## $Tratamiento
## diff lwr
## Escarificadas Acido giberelico-Control 1.068000e+00 0.1762267
## Escarificadas Control-Control -1.554312e-16 -0.8917733
## Escarificadas Control-Escarificadas Acido giberelico -1.068000e+00 -1.9597733
## upr p adj
## Escarificadas Acido giberelico-Control 1.9597733 0.0148744
## Escarificadas Control-Control 0.8917733 1.0000000
## Escarificadas Control-Escarificadas Acido giberelico -0.1762267 0.0148744
library(TukeyC)
tc=TukeyC(L_R,'Tratamiento')
plot(tc, title="Longitud_raiz")
L_t= aov(Longitu_total~Tratamiento, C_PL)
anova(L_t)
## Analysis of Variance Table
##
## Response: Longitu_total
## Df Sum Sq Mean Sq F value Pr(>F)
## Tratamiento 2 233.63 116.813 6.4722 0.002601 **
## Residuals 72 1299.48 18.048
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
TukeyHSD(L_t)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Longitu_total ~ Tratamiento, data = C_PL)
##
## $Tratamiento
## diff lwr
## Escarificadas Acido giberelico-Control 3.744000e+00 0.8683966
## Escarificadas Control-Control 2.930989e-16 -2.8756034
## Escarificadas Control-Escarificadas Acido giberelico -3.744000e+00 -6.6196034
## upr p adj
## Escarificadas Acido giberelico-Control 6.6196034 0.0073423
## Escarificadas Control-Control 2.8756034 1.0000000
## Escarificadas Control-Escarificadas Acido giberelico -0.8683966 0.0073423
library(TukeyC)
tc=TukeyC(L_t,'Tratamiento')
plot(tc, title="Longitud total")
orden_cultivos <- c("Escarificadas Acido giberelico", "Escarificadas Control", "Control")
C_PL$Tratamiento <- factor(C_PL$Tratamiento, levels = orden_cultivos)
datos_resumen= C_PL|>
group_by(Tratamiento) |>
summarise(media= mean(Lonitud_parte_aerea),
desviacion=sd(Lonitud_parte_aerea), n=n()) |>
mutate(error=1.96*desviacion/sqrt(n))
ggplot(datos_resumen)+
aes(x=Tratamiento, y=media, fill=Tratamiento)+
geom_col(strat= 'identity', position = 'dodge', color = 'black')+
labs(x = "Tratamiento", y = "Lonitud parte aerea")+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1, size = 7))+
geom_text(aes(label=c("a","b","b"), y= media+0.2), color= "black", size=6)
## Warning in geom_col(strat = "identity", position = "dodge", color = "black"):
## Ignoring unknown parameters: `strat`
datos_resumen= C_PL |>
group_by(Tratamiento) |>
summarise(media= mean(Longitud_raiz),
desviacion=sd(Longitud_raiz), n=n()) |>
mutate(error=1.96*desviacion/sqrt(n))
ggplot(datos_resumen)+
aes(x=Tratamiento, y=media, fill=Tratamiento)+
geom_col(strat= 'identity', position = 'dodge', color = 'black')+
labs(x = "Tratamiento", y = "Longitud_raiz")+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1, size = 7))+
geom_text(aes(label=c("a","b","b"), y= media+2), color= "black", size=6)
## Warning in geom_col(strat = "identity", position = "dodge", color = "black"):
## Ignoring unknown parameters: `strat`
datos_resumen= C_PL |>
group_by(Tratamiento) |>
summarise(media= mean(Longitu_total),
desviacion=sd(Longitu_total), n=n()) |>
mutate(error=1.96*desviacion/sqrt(n))
ggplot(datos_resumen)+
aes(x=Tratamiento, y=media, fill=Tratamiento)+
geom_col(strat= 'identity', position = 'dodge', color = 'black')+
labs(x = "Tratamiento", y = "Longitud total")+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1, size = 7))+
geom_text(aes(label=c("a","b","b"), y= media+4), color= "black", size=6)
## Warning in geom_col(strat = "identity", position = "dodge", color = "black"):
## Ignoring unknown parameters: `strat`
####Via
Via= aov(Viables~Cultivo, P_Via)
anova(Via)
## Warning in anova.lm(Via): ANOVA F-tests on an essentially perfect fit are
## unreliable
## Analysis of Variance Table
##
## Response: Viables
## Df Sum Sq Mean Sq F value Pr(>F)
## Cultivo 1 32 32 1.9471e+33 < 2.2e-16 ***
## Residuals 6 0 0
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
TukeyHSD(Via)
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Viables ~ Cultivo, data = P_Via)
##
## $Cultivo
## diff lwr upr p adj
## Maiz-Frijol 4 4 4 0
library(TukeyC)
tc=TukeyC(Via,'Cultivo')
plot(tc, title="Viabilidad")
datos_resumen= P_Via |>
group_by(Cultivo) |>
summarise(media= mean(Viables),
desviacion=sd(Viables), n=n()) |>
mutate(error=1.96*desviacion/sqrt(n))
ggplot(datos_resumen)+
aes(x=Cultivo, y=media, fill=Cultivo)+
geom_col(strat= 'identity', position = 'dodge', color = 'black')+
labs(x = "Cultivo", y = "Viabilidad")+
geom_text(aes(label=c("b","a"), y= media+0.2), color= "black", size=6)+
theme_bw()
## Warning in geom_col(strat = "identity", position = "dodge", color = "black"):
## Ignoring unknown parameters: `strat`
