LABORARIO ASEXUAL
Diana Posada
2023-11-25
ESTACAS HERBÁCEAS
ROMERO
trt <- gl(4,4,16,c("-YEMA-AUX","-YEMA+AUX","+YEMA-AUX","+YEMA+AUX"))
trt## [1] -YEMA-AUX -YEMA-AUX -YEMA-AUX -YEMA-AUX -YEMA+AUX -YEMA+AUX -YEMA+AUX
## [8] -YEMA+AUX +YEMA-AUX +YEMA-AUX +YEMA-AUX +YEMA-AUX +YEMA+AUX +YEMA+AUX
## [15] +YEMA+AUX +YEMA+AUX
## Levels: -YEMA-AUX -YEMA+AUX +YEMA-AUX +YEMA+AUXrep <- as.factor(gl(4,1,16,c("I","II","III","IV")))
rep## [1] I II III IV I II III IV I II III IV I II III IV
## Levels: I II III IVLR <- c(11.8,9.3,7,12.9,
11.5,8.6,8.4,12.1,
11.3,9.34,8.3,8.35,
13.01,6.6,6.53,10.87)
LR## [1] 11.80 9.30 7.00 12.90 11.50 8.60 8.40 12.10 11.30 9.34 8.30 8.35
## [13] 13.01 6.60 6.53 10.87NR <- c(9,10,1,11,
15,9,6,11,
4,10,5,4,
14,7,10,12)
NR## [1] 9 10 1 11 15 9 6 11 4 10 5 4 14 7 10 12PR <- c(1.232,1.169,0.028,1.488,
2.264,0.819,0.615,1.497,
0.488,0.571,0.556,0.369,
1.169,0.126,0.520,0.757)
PR## [1] 1.232 1.169 0.028 1.488 2.264 0.819 0.615 1.497 0.488 0.571 0.556 0.369
## [13] 1.169 0.126 0.520 0.757df <- data.frame(trt, rep,LR, NR, PR)
df## trt rep LR NR PR
## 1 -YEMA-AUX I 11.80 9 1.232
## 2 -YEMA-AUX II 9.30 10 1.169
## 3 -YEMA-AUX III 7.00 1 0.028
## 4 -YEMA-AUX IV 12.90 11 1.488
## 5 -YEMA+AUX I 11.50 15 2.264
## 6 -YEMA+AUX II 8.60 9 0.819
## 7 -YEMA+AUX III 8.40 6 0.615
## 8 -YEMA+AUX IV 12.10 11 1.497
## 9 +YEMA-AUX I 11.30 4 0.488
## 10 +YEMA-AUX II 9.34 10 0.571
## 11 +YEMA-AUX III 8.30 5 0.556
## 12 +YEMA-AUX IV 8.35 4 0.369
## 13 +YEMA+AUX I 13.01 14 1.169
## 14 +YEMA+AUX II 6.60 7 0.126
## 15 +YEMA+AUX III 6.53 10 0.520
## 16 +YEMA+AUX IV 10.87 12 0.757library(agricolae)
mod <- aov(LR~trt, df)
summary(mod)## Df Sum Sq Mean Sq F value Pr(>F)
## trt 3 3.36 1.120 0.195 0.898
## Residuals 12 69.06 5.755comparison<- LSD.test(mod,"trt",alpha=0.01,group=TRUE)
print(comparison$groups)## LR groups
## -YEMA-AUX 10.2500 a
## -YEMA+AUX 10.1500 a
## +YEMA-AUX 9.3225 a
## +YEMA+AUX 9.2525 aletra <- c("a","a","a","a")
library(ggplot2)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionp <- df%>%
group_by(trt)%>%
summarise(media_trt=mean(LR),
minimo=min(LR),
maximo=max(LR)) %>%
ggplot(aes(x=trt, y=media_trt, fill=trt))+
geom_col()+
ylim(0,15)+
geom_text(aes(label=letra),
position=position_dodge(width = 0),
vjust=-3,
hjust=2)+
scale_fill_manual(values=c('#333333','#666666','#999999','#E6E6E6')) +
geom_errorbar(aes(ymin=minimo, ymax=maximo), width=0.2, color='black', position="dodge")+
labs(title = 'Longitud de las raíces', x = 'Tratamiento', y = 'Longitud de las raíces (cm)') +
theme_minimal()
p
p+
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())+
xlab("Tratamientos")
library(agricolae)
mod1 <- aov(NR~trt, df)
summary(mod1)## Df Sum Sq Mean Sq F value Pr(>F)
## trt 3 64.75 21.58 1.65 0.23
## Residuals 12 157.00 13.08comparison<- LSD.test(mod1,"trt",alpha=0.01,group=TRUE)
print(comparison$groups)## NR groups
## +YEMA+AUX 10.75 a
## -YEMA+AUX 10.25 a
## -YEMA-AUX 7.75 a
## +YEMA-AUX 5.75 aletra## [1] "a" "a" "a" "a"library(ggplot2)
library(dplyr)
p <- df%>%
group_by(trt)%>%
summarise(media_trt=mean(NR),
minimo=min(NR),
maximo=max(NR)) %>%
ggplot(aes(x=trt, y=media_trt, fill=trt))+
geom_col()+
ylim(0,15)+
geom_text(aes(label=letra), position = position_dodge(width = 0),
vjust=-3,
hjust=2)+
scale_fill_manual(values=c('#333333','#666666','#999999','#E6E6E6')) +
geom_errorbar(aes(ymin=minimo, ymax=maximo), width=0.2, color='black', position="dodge")+
labs(title = 'Número de raíces', x = 'Tratamiento', y = 'Número de raíces') +
theme_minimal()
p
p+
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())+
xlab("Tratamientos")
library(agricolae)
mod2 <- aov(PR~trt, df)
summary(mod2)## Df Sum Sq Mean Sq F value Pr(>F)
## trt 3 1.545 0.5149 1.75 0.21
## Residuals 12 3.530 0.2941comparison<- LSD.test(mod2,"trt",alpha=0.01,group=TRUE)
print(comparison$groups)## PR groups
## -YEMA+AUX 1.29875 a
## -YEMA-AUX 0.97925 a
## +YEMA+AUX 0.64300 a
## +YEMA-AUX 0.49600 aletra## [1] "a" "a" "a" "a"library(ggplot2)
library(dplyr)
p <- df%>%
group_by(trt)%>%
summarise(media_trt=mean(PR),
minimo=min(PR),
maximo=max(PR)) %>%
ggplot(aes(x=trt, y=media_trt, fill=trt))+
geom_col()+
ylim(0,2.5)+
geom_text(aes(label=letra), position = position_dodge(width = 0),
vjust=-3,
hjust=2)+
scale_fill_manual(values=c('#333333','#666666','#999999','#E6E6E6')) +
geom_errorbar(aes(ymin=minimo, ymax=maximo), width=0.2, color='black', position="dodge")+
labs(title = 'Peso de raíces', x = 'Tratamiento', y = 'Peso de raíces (g)') +
theme_minimal()
p
p+
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())+
xlab("Tratamientos")
OREGANO
trt <- gl(4,4,16,c("-YEMA-AUX","-YEMA+AUX","+YEMA-AUX","+YEMA+AUX"))
trt## [1] -YEMA-AUX -YEMA-AUX -YEMA-AUX -YEMA-AUX -YEMA+AUX -YEMA+AUX -YEMA+AUX
## [8] -YEMA+AUX +YEMA-AUX +YEMA-AUX +YEMA-AUX +YEMA-AUX +YEMA+AUX +YEMA+AUX
## [15] +YEMA+AUX +YEMA+AUX
## Levels: -YEMA-AUX -YEMA+AUX +YEMA-AUX +YEMA+AUXrep <- as.factor(gl(4,1,16,c("1","2","3","4")))
rep## [1] 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
## Levels: 1 2 3 4LR <- c(17.2,18.4,15.4,17.43,
6.4,8.5,7.8,8,
11.17,15.9,18.7,10.8,
11.49,12.94,10,12.31)
LR## [1] 17.20 18.40 15.40 17.43 6.40 8.50 7.80 8.00 11.17 15.90 18.70 10.80
## [13] 11.49 12.94 10.00 12.31NR <- c(12,11,15,7,
72,68,57,73,
13,23,28,36,
94,124,127,113)
NR## [1] 12 11 15 7 72 68 57 73 13 23 28 36 94 124 127 113PR <- c(3.322,3.219,3.367,1.383,
5.838,6.832,3.776,6.338,
2.450,3.921,3.541,2.895,
7.066,7.737,5.945,6.467)
PR## [1] 3.322 3.219 3.367 1.383 5.838 6.832 3.776 6.338 2.450 3.921 3.541 2.895
## [13] 7.066 7.737 5.945 6.467df <- data.frame(trt, rep,LR, NR, PR)
df## trt rep LR NR PR
## 1 -YEMA-AUX 1 17.20 12 3.322
## 2 -YEMA-AUX 2 18.40 11 3.219
## 3 -YEMA-AUX 3 15.40 15 3.367
## 4 -YEMA-AUX 4 17.43 7 1.383
## 5 -YEMA+AUX 1 6.40 72 5.838
## 6 -YEMA+AUX 2 8.50 68 6.832
## 7 -YEMA+AUX 3 7.80 57 3.776
## 8 -YEMA+AUX 4 8.00 73 6.338
## 9 +YEMA-AUX 1 11.17 13 2.450
## 10 +YEMA-AUX 2 15.90 23 3.921
## 11 +YEMA-AUX 3 18.70 28 3.541
## 12 +YEMA-AUX 4 10.80 36 2.895
## 13 +YEMA+AUX 1 11.49 94 7.066
## 14 +YEMA+AUX 2 12.94 124 7.737
## 15 +YEMA+AUX 3 10.00 127 5.945
## 16 +YEMA+AUX 4 12.31 113 6.467library(agricolae)
mod <- aov(LR~trt, df)
summary(mod)## Df Sum Sq Mean Sq F value Pr(>F)
## trt 3 191.11 63.70 13.69 0.000352 ***
## Residuals 12 55.84 4.65
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1comparison<- LSD.test(mod,"trt",alpha=0.01,group=TRUE)
print(comparison$groups)## LR groups
## -YEMA-AUX 17.1075 a
## +YEMA-AUX 14.1425 ab
## +YEMA+AUX 11.6850 bc
## -YEMA+AUX 7.6750 cletra <- c("a","c","ab","bc")
library(ggplot2)
library(dplyr)
p <- df%>%
group_by(trt)%>%
summarise(media_trt=mean(LR),
minimo=min(LR),
maximo=max(LR)) %>%
ggplot(aes(x=trt, y=media_trt, fill=trt))+
geom_col()+
ylim(0,22)+
geom_text(aes(label=letra),
position=position_dodge(width = 0),
vjust=-2,
hjust=1)+
scale_fill_manual(values=c('#333333','#666666','#999999','#E6E6E6')) +
geom_errorbar(aes(ymin=minimo, ymax=maximo), width=0.2, color='black', position="dodge")+
labs(title = 'Longitud de las raíces', x = 'Tratamiento', y = 'Longitud de las raíces (cm)') +
theme_minimal()
p
p+
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())+
xlab("Tratamientos")
library(agricolae)
mod1 <- aov(NR~trt, df)
summary(mod1)## Df Sum Sq Mean Sq F value Pr(>F)
## trt 3 26039 8680 91.31 1.57e-08 ***
## Residuals 12 1141 95
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1comparison<- LSD.test(mod1,"trt",alpha=0.01,group=TRUE)
print(comparison$groups)## NR groups
## +YEMA+AUX 114.50 a
## -YEMA+AUX 67.50 b
## +YEMA-AUX 25.00 c
## -YEMA-AUX 11.25 cletra <- c("c","b","c","a")
library(ggplot2)
library(dplyr)
p <- df%>%
group_by(trt)%>%
summarise(media_trt=mean(NR),
minimo=min(NR),
maximo=max(NR)) %>%
ggplot(aes(x=trt, y=media_trt, fill=trt))+
geom_col()+
ylim(0,140)+
geom_text(aes(label=letra), position = position_dodge(width = 0),
vjust=-2,
hjust=2)+
scale_fill_manual(values=c('#333333','#666666','#999999','#E6E6E6')) +
geom_errorbar(aes(ymin=minimo, ymax=maximo), width=0.2, color='black', position="dodge")+
labs(title = 'Número de raíces', x = 'Tratamiento', y = 'Número de raíces') +
theme_minimal()
p
p+
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())+
xlab("Tratamientos")
library(agricolae)
mod2 <- aov(PR~trt, df)
summary(mod2)## Df Sum Sq Mean Sq F value Pr(>F)
## trt 3 44.67 14.890 15.86 0.000178 ***
## Residuals 12 11.27 0.939
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1comparison<- LSD.test(mod2,"trt",alpha=0.01,group=TRUE)
print(comparison$groups)## PR groups
## +YEMA+AUX 6.80375 a
## -YEMA+AUX 5.69600 a
## +YEMA-AUX 3.20175 b
## -YEMA-AUX 2.82275 bletra <- c("b","a","b","a")
library(ggplot2)
library(dplyr)
p <- df%>%
group_by(trt)%>%
summarise(media_trt=mean(PR),
minimo=min(PR),
maximo=max(PR)) %>%
ggplot(aes(x=trt, y=media_trt, fill=trt))+
geom_col()+
ylim(0,9.5)+
geom_text(aes(label=letra), position = position_dodge(width = 0),
vjust=-3,
hjust=2)+
scale_fill_manual(values=c('#333333','#666666','#999999','#E6E6E6')) +
geom_errorbar(aes(ymin=minimo, ymax=maximo), width=0.2, color='black', position="dodge")+
labs(title = 'Peso de raíces', x = 'Tratamiento', y = 'Peso de raíces (g)') +
theme_minimal()
p
p+
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())+
xlab("Tratamientos")
ESTACAS LEÑOSAS
TOMATE DE ARBOL
dis <- gl(2,3,6,c("APICAL","BASAL"))
dis## [1] APICAL APICAL APICAL BASAL BASAL BASAL
## Levels: APICAL BASALNR <- c(8,0,7,0,9,5)
NR## [1] 8 0 7 0 9 5LR <- c(15.2,0,8,0,7,9)
LR## [1] 15.2 0.0 8.0 0.0 7.0 9.0PR <- c(2.274,0,1.803,0,2.663,1.832)
PR## [1] 2.274 0.000 1.803 0.000 2.663 1.832df <- data.frame(dis,LR,NR,PR)
df## dis LR NR PR
## 1 APICAL 15.2 8 2.274
## 2 APICAL 0.0 0 0.000
## 3 APICAL 8.0 7 1.803
## 4 BASAL 0.0 0 0.000
## 5 BASAL 7.0 9 2.663
## 6 BASAL 9.0 5 1.832library(agricolae)
mod <- aov(LR~dis, df)
summary(mod)## Df Sum Sq Mean Sq F value Pr(>F)
## dis 1 8.64 8.64 0.216 0.667
## Residuals 4 160.29 40.07comparison<- LSD.test(mod,"dis",alpha=0.01,group=TRUE)
print(comparison$groups)## LR groups
## APICAL 7.733333 a
## BASAL 5.333333 aletra <- c("a","a")
library(ggplot2)
library(dplyr)
p <- df%>%
group_by(dis)%>%
summarise(media_trt=mean(LR),
minimo=min(LR),
maximo=max(LR)) %>%
ggplot(aes(x=dis, y=media_trt, fill=dis))+
geom_col()+
ylim(0,18)+
geom_text(aes(label=letra),
position=position_dodge(width = 0),
vjust=-3,
hjust=2)+
scale_fill_manual(values=c('#333333','#666666','#999999','#E6E6E6')) +
geom_errorbar(aes(ymin=minimo, ymax=maximo), width=0.2, color='black', position="dodge")+
labs(title = 'Longitud de las raíces', x = 'Tratamiento', y = 'Longitud de las raíces (cm)') +
guides(fill = guide_legend(title = "Disposición"))+
theme_minimal()
p
p+
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())+
xlab("Disposición")
library(agricolae)
mod <- aov(NR~dis, df)
summary(mod)## Df Sum Sq Mean Sq F value Pr(>F)
## dis 1 0.17 0.167 0.008 0.931
## Residuals 4 78.67 19.667comparison<- LSD.test(mod,"dis",alpha=0.01,group=TRUE)
print(comparison$groups)## NR groups
## APICAL 5.000000 a
## BASAL 4.666667 aletra <- c("a","a")
library(ggplot2)
library(dplyr)
p <- df%>%
group_by(dis)%>%
summarise(media_trt=mean(NR),
minimo=min(NR),
maximo=max(NR)) %>%
ggplot(aes(x=dis, y=media_trt, fill=dis))+
geom_col()+
ylim(0,9)+
geom_text(aes(label=letra),
position=position_dodge(width = 0),
vjust=-3,
hjust=2)+
scale_fill_manual(values=c('#333333','#666666','#999999','#E6E6E6')) +
geom_errorbar(aes(ymin=minimo, ymax=maximo), width=0.2, color='black', position="dodge")+
labs(title = 'Número de raíces', x = 'Tratamiento', y = 'Número de raíces') +
guides(fill = guide_legend(title = "Disposición"))+
theme_minimal()
p
p+
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())+
xlab("Disposición")
library(agricolae)
mod <- aov(PR~dis, df)
summary(mod)## Df Sum Sq Mean Sq F value Pr(>F)
## dis 1 0.029 0.0291 0.018 0.901
## Residuals 4 6.594 1.6485comparison<- LSD.test(mod,"dis",alpha=0.01,group=TRUE)
print(comparison$groups)## PR groups
## BASAL 1.498333 a
## APICAL 1.359000 aletra <- c("a","a")
library(ggplot2)
library(dplyr)
p <- df%>%
group_by(dis)%>%
summarise(media_trt=mean(PR),
minimo=min(PR),
maximo=max(PR)) %>%
ggplot(aes(x=dis, y=media_trt, fill=dis))+
geom_col()+
ylim(0,3)+
geom_text(aes(label=letra),
position=position_dodge(width = 0),
vjust=-3,
hjust=2)+
scale_fill_manual(values=c('#333333','#666666','#999999','#E6E6E6')) +
geom_errorbar(aes(ymin=minimo, ymax=maximo), width=0.2, color='black', position="dodge")+
labs(title = 'Peso de raíces', x = 'Tratamiento', y = 'Peso de raíces (g)') +
guides(fill = guide_legend(title = "Disposición"))+
theme_minimal()
p
p+
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())+
xlab("Disposición")
ESTACAS DE HOJA
GULUPA
AUXINAS <- c(rep(c("-AUX","+AUX") , 2, each=2))
AUXINAS## [1] "-AUX" "-AUX" "+AUX" "+AUX" "-AUX" "-AUX" "+AUX" "+AUX"trt1 <- rep(c("HOJA" , "PECIOLO") , 1, each=4)
trt1## [1] "HOJA" "HOJA" "HOJA" "HOJA" "PECIOLO" "PECIOLO" "PECIOLO"
## [8] "PECIOLO"P.ENRAIZAMIENTO <-c(0,100,0,100,75,25,0,100)
P.ENRAIZAMIENTO## [1] 0 100 0 100 75 25 0 100ENRAIZAMIENTO <- c("SI","NO","SI","NO","SI","NO","SI","NO")
ENRAIZAMIENTO## [1] "SI" "NO" "SI" "NO" "SI" "NO" "SI" "NO"dt <- data.frame(trt1,AUXINAS,P.ENRAIZAMIENTO,ENRAIZAMIENTO)
dt## trt1 AUXINAS P.ENRAIZAMIENTO ENRAIZAMIENTO
## 1 HOJA -AUX 0 SI
## 2 HOJA -AUX 100 NO
## 3 HOJA +AUX 0 SI
## 4 HOJA +AUX 100 NO
## 5 PECIOLO -AUX 75 SI
## 6 PECIOLO -AUX 25 NO
## 7 PECIOLO +AUX 0 SI
## 8 PECIOLO +AUX 100 NO# Gráfica
library(dplyr)
library(ggplot2)
library(cowplot)
library(viridis)## Loading required package: viridisLitelibrary(hrbrthemes)## Warning: package 'hrbrthemes' was built under R version 4.3.2## NOTE: Either Arial Narrow or Roboto Condensed fonts are required to use these themes.## Please use hrbrthemes::import_roboto_condensed() to install Roboto Condensed and## if Arial Narrow is not on your system, please see https://bit.ly/arialnarrowp <- ggplot(dt, aes(fill=ENRAIZAMIENTO,y=P.ENRAIZAMIENTO, x=AUXINAS)) +
geom_bar(position="dodge", stat="identity") +
ggtitle("PORCENTAJE DE ENRAIZAMIENTO EN
ESTACAS DE GULUPA")+
xlab("Tratamientos")+
ylab("Porcentaje de enraizamiento (%)")+
ylim(c(0,100))+
facet_grid(~trt1, switch = "both")+
theme_minimal()p+
scale_fill_manual(values=c('#333333',"#999999"))
AUXINAS <- c(rep(c("-AUX","+AUX") , 2, each=2))
AUXINAS## [1] "-AUX" "-AUX" "+AUX" "+AUX" "-AUX" "-AUX" "+AUX" "+AUX"trt1 <- rep(c("HOJA" , "PECIOLO") , 1, each=4)
trt1## [1] "HOJA" "HOJA" "HOJA" "HOJA" "PECIOLO" "PECIOLO" "PECIOLO"
## [8] "PECIOLO"P.CALLO <-c(0,100,75,25,75,25,100,0)
P.CALLO## [1] 0 100 75 25 75 25 100 0PR.CALLO <- c("SI","NO","SI","NO","SI","NO","SI","NO")
PR.CALLO## [1] "SI" "NO" "SI" "NO" "SI" "NO" "SI" "NO"dt <- data.frame(trt1,AUXINAS,P.CALLO,PR.CALLO)
dt## trt1 AUXINAS P.CALLO PR.CALLO
## 1 HOJA -AUX 0 SI
## 2 HOJA -AUX 100 NO
## 3 HOJA +AUX 75 SI
## 4 HOJA +AUX 25 NO
## 5 PECIOLO -AUX 75 SI
## 6 PECIOLO -AUX 25 NO
## 7 PECIOLO +AUX 100 SI
## 8 PECIOLO +AUX 0 NOggplot(dt, aes(fill=PR.CALLO,y=P.CALLO, x=AUXINAS)) +
geom_bar(position="dodge", stat="identity") +
ggtitle("PORCENTAJE DE PRESENCIA DE CALLO
EN ESTACAS DE GULUPA")+
xlab("Tratamientos")+
ylab("Porcentaje de presencia
de callo (%)")+
ylim(c(0,100))+
facet_grid(~trt1, switch = "both")+
scale_fill_manual(values=c('#333333',"#999999"))+
guides(fill = guide_legend(title = "Presencia de callo"))+
theme_minimal()
trt <- gl(4,4,16,c("HOJA-AUX","HOJA+AUX","PECIOLO-AUX","PECIOLO+AUX"))
trt## [1] HOJA-AUX HOJA-AUX HOJA-AUX HOJA-AUX HOJA+AUX HOJA+AUX
## [7] HOJA+AUX HOJA+AUX PECIOLO-AUX PECIOLO-AUX PECIOLO-AUX PECIOLO-AUX
## [13] PECIOLO+AUX PECIOLO+AUX PECIOLO+AUX PECIOLO+AUX
## Levels: HOJA-AUX HOJA+AUX PECIOLO-AUX PECIOLO+AUXCR <- as.factor(c("NO","NO","NO","NO",
"NO","NO","NO","NO",
"SI","SI","SI","NO",
"NO","NO","NO","NO"))
CR## [1] NO NO NO NO NO NO NO NO SI SI SI NO NO NO NO NO
## Levels: NO SILR <- c(0,0,0,0,
0,0,0,0,
3.5,2,2.5,0,
0,0,0,0)
LR## [1] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.5 2.0 2.5 0.0 0.0 0.0 0.0 0.0NR <- c(0,0,0,0,
0,0,0,0,
6,4,8,0,
0,0,0,0)
NR## [1] 0 0 0 0 0 0 0 0 6 4 8 0 0 0 0 0PR <- c(0,0,0,0,
0,0,0,0,
0.056,0.067,0.01,0,
0,0,0,0)
PR## [1] 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.056 0.067 0.010 0.000
## [13] 0.000 0.000 0.000 0.000CALLO <-c("NO","NO","NO","NO",
"SI","NO","SI","SI",
"SI","SI","NO","SI",
"SI","SI","SI","SI")
CALLO## [1] "NO" "NO" "NO" "NO" "SI" "NO" "SI" "SI" "SI" "SI" "NO" "SI" "SI" "SI" "SI"
## [16] "SI"PC <- c(0,0,0,0,
0.028,0,0.143,0.228,
0.274,0.057,0,0.124,
0.045,0.201,0.183,0.021)
PC## [1] 0.000 0.000 0.000 0.000 0.028 0.000 0.143 0.228 0.274 0.057 0.000 0.124
## [13] 0.045 0.201 0.183 0.021df <- data.frame(trt,CR,LR,NR,PR,CALLO,PC)
df## trt CR LR NR PR CALLO PC
## 1 HOJA-AUX NO 0.0 0 0.000 NO 0.000
## 2 HOJA-AUX NO 0.0 0 0.000 NO 0.000
## 3 HOJA-AUX NO 0.0 0 0.000 NO 0.000
## 4 HOJA-AUX NO 0.0 0 0.000 NO 0.000
## 5 HOJA+AUX NO 0.0 0 0.000 SI 0.028
## 6 HOJA+AUX NO 0.0 0 0.000 NO 0.000
## 7 HOJA+AUX NO 0.0 0 0.000 SI 0.143
## 8 HOJA+AUX NO 0.0 0 0.000 SI 0.228
## 9 PECIOLO-AUX SI 3.5 6 0.056 SI 0.274
## 10 PECIOLO-AUX SI 2.0 4 0.067 SI 0.057
## 11 PECIOLO-AUX SI 2.5 8 0.010 NO 0.000
## 12 PECIOLO-AUX NO 0.0 0 0.000 SI 0.124
## 13 PECIOLO+AUX NO 0.0 0 0.000 SI 0.045
## 14 PECIOLO+AUX NO 0.0 0 0.000 SI 0.201
## 15 PECIOLO+AUX NO 0.0 0 0.000 SI 0.183
## 16 PECIOLO+AUX NO 0.0 0 0.000 SI 0.021library(agricolae)
mod <- aov(LR~trt, df)
summary(mod)## Df Sum Sq Mean Sq F value Pr(>F)
## trt 3 12.0 4.000 7.385 0.00461 **
## Residuals 12 6.5 0.542
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1comparison<- LSD.test(mod,"trt",alpha=0.01,group=TRUE)
print(comparison$groups)## LR groups
## PECIOLO-AUX 2 a
## HOJA-AUX 0 b
## HOJA+AUX 0 b
## PECIOLO+AUX 0 bletra <- c("b","b","a","b")
library(ggplot2)
library(dplyr)
p <- df%>%
group_by(trt)%>%
summarise(media_trt=mean(LR),
minimo=min(LR),
maximo=max(LR)) %>%
ggplot(aes(x=trt, y=media_trt, fill=trt))+
geom_col()+
ylim(0,4)+
geom_text(aes(label=letra),
position=position_dodge(width = 0),
vjust=-2,
hjust=1)+
scale_fill_manual(values=c('#333333','#666666','#999999','#E6E6E6')) +
geom_errorbar(aes(ymin=minimo, ymax=maximo), width=0.2, color='black', position="dodge")+
labs(title = 'Longitud de las raíces', x = 'Tratamiento', y = 'Longitud de las raíces (cm)') +
theme_minimal()
p
p+
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())+
xlab("Tratamientos")
library(agricolae)
mod <- aov(NR~trt, df)
summary(mod)## Df Sum Sq Mean Sq F value Pr(>F)
## trt 3 60.75 20.250 6.943 0.00579 **
## Residuals 12 35.00 2.917
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1comparison<- LSD.test(mod,"trt",alpha=0.01,group=TRUE)
print(comparison$groups)## NR groups
## PECIOLO-AUX 4.5 a
## HOJA-AUX 0.0 b
## HOJA+AUX 0.0 b
## PECIOLO+AUX 0.0 bletra <- c("b","b","a","b")
library(ggplot2)
library(dplyr)
p <- df%>%
group_by(trt)%>%
summarise(media_trt=mean(NR),
minimo=min(NR),
maximo=max(NR)) %>%
ggplot(aes(x=trt, y=media_trt, fill=trt))+
geom_col()+
ylim(0,8)+
geom_text(aes(label=letra), position = position_dodge(width = 0),
vjust=-3,
hjust=2)+
scale_fill_manual(values=c('#333333','#666666','#999999','#E6E6E6')) +
geom_errorbar(aes(ymin=minimo, ymax=maximo), width=0.2, color='black', position="dodge")+
labs(title = 'Número de raíces', x = 'Tratamiento', y = 'Número de raíces') +
theme_minimal()
p
p+
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())+
xlab("Tratamientos")
library(agricolae)
mod2 <- aov(PR~trt, df)
summary(mod2)## Df Sum Sq Mean Sq F value Pr(>F)
## trt 3 0.003317 0.0011056 4.017 0.0342 *
## Residuals 12 0.003303 0.0002752
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1comparison<- LSD.test(mod2,"trt",alpha=0.01,group=TRUE)
print(comparison$groups)## PR groups
## PECIOLO-AUX 0.03325 a
## HOJA-AUX 0.00000 a
## HOJA+AUX 0.00000 a
## PECIOLO+AUX 0.00000 aletra <- c("a","a","a","a")
library(ggplot2)
library(dplyr)
p <- df%>%
group_by(trt)%>%
summarise(media_trt=mean(PR),
minimo=min(PR),
maximo=max(PR)) %>%
ggplot(aes(x=trt, y=media_trt, fill=trt))+
geom_col()+
ylim(0,0.1)+
geom_text(aes(label=letra), position = position_dodge(width = 0),
vjust=-3,
hjust=2)+
scale_fill_manual(values=c('#333333','#666666','#999999','#E6E6E6')) +
geom_errorbar(aes(ymin=minimo, ymax=maximo), width=0.2, color='black', position="dodge")+
labs(title = 'Peso de raíces', x = 'Tratamiento', y = 'Peso de raíces (g)') +
theme_minimal()
p
p+
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())+
xlab("Tratamientos")
library(agricolae)
mod2 <- aov(PC~trt, df)
summary(mod2)## Df Sum Sq Mean Sq F value Pr(>F)
## trt 3 0.03591 0.011968 1.421 0.285
## Residuals 12 0.10109 0.008424comparison<- LSD.test(mod2,"trt",alpha=0.01,group=TRUE)
print(comparison$groups)## PC groups
## PECIOLO-AUX 0.11375 a
## PECIOLO+AUX 0.11250 a
## HOJA+AUX 0.09975 a
## HOJA-AUX 0.00000 aletra <- c("a","a","a","a")
library(ggplot2)
library(dplyr)
p <- df%>%
group_by(trt)%>%
summarise(media_trt=mean(PR),
minimo=min(PR),
maximo=max(PR)) %>%
ggplot(aes(x=trt, y=media_trt, fill=trt))+
geom_col()+
ylim(0,0.1)+
geom_text(aes(label=letra), position = position_dodge(width = 0),
vjust=-3,
hjust=2)+
scale_fill_manual(values=c('#333333','#666666','#999999','#E6E6E6')) +
geom_errorbar(aes(ymin=minimo, ymax=maximo), width=0.2, color='black', position="dodge")+
labs(title = 'Peso de callo', x = 'Tratamiento', y = 'Peso de callo (g)') +
theme_minimal()
p
p+
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())+
xlab("Tratamientos")
ACODO
ARBOLOCO
TRATAMIENTO <- c("+AUX","-AUX")
TRATAMIENTO## [1] "+AUX" "-AUX"LR <- c(5.125, 4.2)
LR## [1] 5.125 4.200NR <- c(4,1)
NR## [1] 4 1df <- data.frame(TRATAMIENTO,LR,NR)
df## TRATAMIENTO LR NR
## 1 +AUX 5.125 4
## 2 -AUX 4.200 1ggplot(df, aes(fill=TRATAMIENTO,y=LR, x=TRATAMIENTO)) +
geom_bar(position="dodge", stat="identity") +
scale_fill_manual(values=c('#333333','#999999'))+
ggtitle("LONGITUD DE LA RAÍZ EN ARBOLOCO
(Smallanthus pyramidalis)")+
xlab("Tratamientos")+
ylab("Longitud de la raíz (cm)")+
ylim(c(0,5.2))
ggplot(df, aes(fill=TRATAMIENTO,y=NR, x=TRATAMIENTO)) +
geom_bar(position="dodge", stat="identity") +
scale_fill_manual(values=c('#333333','#999999'))+
ggtitle("NÚMERO DE RAICES EN ARBOLOCO
(Smallanthus pyramidalis)")+
xlab("Tratamientos")+
ylab("Número de raíces")+
ylim(c(0,4))