R Markdow

library(dplyr)
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library(PerformanceAnalytics)
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## Loading required package: zoo
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library(plotly)
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library(tidyverse)
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library(reshape2)
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library(ggrepel)
library(rgl)
library(car)
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library(sf)
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library(tmap)
library(rgdal)
## Loading required package: sp
## rgdal: version: 1.5-18, (SVN revision 1082)
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## Loaded GDAL runtime: GDAL 3.0.4, released 2020/01/28
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library(esquisse)
library(ggplot2)
library(gridExtra)
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library(readxl)
library(agricolae)
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##     kurtosis, skewness
exp <- read_excel("C:/Users/User/Desktop/exp.xlsx", 
                  sheet = "expseca3")
attach(exp)
names(exp)
##  [1] "vector"   "Planta"   "defh"     "Rept"     "numhojas" "areafol" 
##  [7] "folhas"   "folhas2"  "talo"     "talo2"    "raiz"     "raiz2"
#View(exp)
attach(exp)
## The following objects are masked from exp (pos = 3):
## 
##     areafol, defh, folhas, folhas2, numhojas, Planta, raiz, raiz2,
##     Rept, talo, talo2, vector
names(exp)
##  [1] "vector"   "Planta"   "defh"     "Rept"     "numhojas" "areafol" 
##  [7] "folhas"   "folhas2"  "talo"     "talo2"    "raiz"     "raiz2"
a <- as.factor(vector)
b <- as.factor(defh)
inter<-as.factor(a:b)

############ 1.1 anova numero de folhas  ###########################

summary(aov(numhojas ~ a+b+inter, data = exp))
##             Df Sum Sq Mean Sq F value  Pr(>F)   
## a            3  57.79  19.263   5.820 0.00182 **
## b            2  28.00  14.002   4.231 0.02044 * 
## inter        6   8.05   1.341   0.405 0.87191   
## Residuals   47 155.55   3.310                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 1 observation deleted due to missingness
LSD.test(aov(numhojas ~ a + b + inter, data = exp),
         "a", alpha = 0.05)["groups"]
## $groups
##     numhojas groups
## VØ 11.000000      a
## VF 10.733333      a
## MT 10.266667      a
## VG  8.466667      b
LSD.test(aov(numhojas ~ a + b + inter, data = exp),
         "b", alpha = 0.05)["groups"]
## $groups
##     numhojas groups
## 100 10.94737      a
## 60  10.10000     ab
## 30   9.30000      b
LSD.test(aov(numhojas ~ a + b + inter, data = exp),
         "inter", alpha = 0.05)["groups"]
## $groups
##        numhojas groups
## VØ:100    12.25      a
## VF:100    11.60     ab
## VØ:60     11.00    abc
## MT:100    10.80    abc
## VF:30     10.40    abc
## MT:60     10.20    abc
## VF:60     10.20    abc
## VØ:30     10.00    abc
## MT:30      9.80    abc
## VG:100     9.40     bc
## VG:60      9.00     cd
## VG:30      7.00      d
shapiro.test(unlist(aov(numhojas ~ a + b + inter, 
                        data = exp)["residuals"]))
## 
##  Shapiro-Wilk normality test
## 
## data:  unlist(aov(numhojas ~ a + b + inter, data = exp)["residuals"])
## W = 0.96913, p-value = 0.1389
res <-sort(unlist(aov( numhojas ~ a + b + inter, 
                       data = exp)["residuals"]),decreasing = TRUE)
ks.test(res,  "pnorm" ,mean(res),sd(res))
## Warning in ks.test(res, "pnorm", mean(res), sd(res)): ties should not be present
## for the Kolmogorov-Smirnov test
## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  res
## D = 0.10216, p-value = 0.5692
## alternative hypothesis: two-sided
kruskal(numhojas, inter)["groups"]
## $groups
##        numhojas groups
## VØ:100    45.75      a
## VF:100    42.50     ab
## VØ:60     37.30    abc
## MT:100    36.70    abc
## VF:30     32.60    abc
## MT:60     30.70    abc
## VF:60     30.30    abc
## VØ:30     29.10    abc
## MT:30     26.60   abcd
## VG:100    23.60    bcd
## VG:60     19.80     cd
## VG:30      8.20      d
############ 1.1 anova area foliar  ###########################

summary(aov(areafol ~ a+b+inter, data = exp))
##             Df Sum Sq Mean Sq F value  Pr(>F)    
## a            3  19965    6655  10.506 2.1e-05 ***
## b            2   6204    3102   4.897  0.0117 *  
## inter        6   6041    1007   1.590  0.1712    
## Residuals   47  29772     633                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 1 observation deleted due to missingness
LSD.test(aov(areafol ~ a + b + inter, data = exp),
         "a", alpha = 0.05)["groups"]
## $groups
##      areafol groups
## MT 127.21200      a
## VØ 112.36714      a
## VF  88.59267      b
## VG  81.61467      b
LSD.test(aov(areafol ~ a + b + inter, data = exp),
         "b", alpha = 0.05)["groups"]
## $groups
##      areafol groups
## 100 113.2768      a
## 60  105.0940      a
## 30   89.0145      b
LSD.test(aov(areafol ~ a + b + inter, data = exp),
         "inter", alpha = 0.05)["groups"]
## $groups
##        areafol groups
## VØ:100 141.080      a
## MT:100 140.616      a
## MT:60  126.520     ab
## MT:30  114.500    abc
## VØ:60  108.070   abcd
## VG:100  98.796    bcd
## VF:60   97.906    bcd
## VØ:30   93.694     cd
## VF:30   89.696    cde
## VG:60   87.880    cde
## VF:100  78.176     de
## VG:30   58.168      e
shapiro.test(unlist(aov(areafol ~ a + b + inter, 
                        data = exp)["residuals"]))
## 
##  Shapiro-Wilk normality test
## 
## data:  unlist(aov(areafol ~ a + b + inter, data = exp)["residuals"])
## W = 0.97008, p-value = 0.1543
res <-sort(unlist(aov( areafol ~ a + b + inter, 
                       data = exp)["residuals"]),decreasing = TRUE)
ks.test(res,  "pnorm" ,mean(res),sd(res))
## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  res
## D = 0.092281, p-value = 0.6622
## alternative hypothesis: two-sided
kruskal(areafol, inter)["groups"]
## $groups
##        areafol groups
## MT:100    49.8      a
## VØ:100    49.5     ab
## MT:60     44.0    abc
## MT:30     36.8   abcd
## VØ:60     31.8   bcde
## VG:100    27.6   cdef
## VF:60     27.0   cdef
## VØ:30     24.4    def
## VF:30     22.4    def
## VG:60     21.0    def
## VF:100    18.2     ef
## VG:30     11.4      f
############ 1.1 anova Biomassa de folhas###########################
summary(aov(folhas ~ a+b+inter, data = exp))
##             Df Sum Sq Mean Sq F value   Pr(>F)    
## a            3 0.3864 0.12881  10.865 1.46e-05 ***
## b            2 0.1219 0.06096   5.142  0.00948 ** 
## inter        6 0.0841 0.01401   1.182  0.33190    
## Residuals   48 0.5691 0.01186                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
LSD.test(aov(folhas ~ a + b + inter, data = exp),
         "a", alpha = 0.05)["groups"]
## $groups
##       folhas groups
## MT 0.4606667      a
## VØ 0.3786667      b
## VF 0.2700000      c
## VG 0.2700000      c
LSD.test(aov(folhas ~ a + b + inter, data = exp),
         "b", alpha = 0.05)["groups"]
## $groups
##     folhas groups
## 100 0.4065      a
## 60  0.3280      b
## 30  0.3000      b
LSD.test(aov(folhas ~ a + b + inter, data = exp),
         "inter", alpha = 0.05)["groups"]
## $groups
##        folhas groups
## MT:100  0.538      a
## VØ:100  0.480     ab
## MT:60   0.474     ab
## MT:30   0.370     bc
## VG:100  0.344     bc
## VØ:60   0.330     cd
## VØ:30   0.326     cd
## VF:30   0.300     cd
## VF:100  0.264     cd
## VG:60   0.262     cd
## VF:60   0.246     cd
## VG:30   0.204      d
shapiro.test(unlist(aov(folhas ~ a + b + inter, 
                        data = exp)["residuals"]))
## 
##  Shapiro-Wilk normality test
## 
## data:  unlist(aov(folhas ~ a + b + inter, data = exp)["residuals"])
## W = 0.98706, p-value = 0.776
res <-sort(unlist(aov( folhas ~ a + b + inter, 
                       data = exp)["residuals"]),decreasing = TRUE)
ks.test(res,  "pnorm" ,mean(res),sd(res))
## Warning in ks.test(res, "pnorm", mean(res), sd(res)): ties should not be present
## for the Kolmogorov-Smirnov test
## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  res
## D = 0.083333, p-value = 0.799
## alternative hypothesis: two-sided
kruskal(folhas, inter)["groups"]
## $groups
##        folhas groups
## MT:60    50.7      a
## MT:100   50.5      a
## VØ:100   46.3     ab
## MT:30    36.5    abc
## VG:100   30.9    bcd
## VØ:60    28.9    cde
## VØ:30    28.1    cde
## VF:30    23.7    cde
## VG:60    20.9    cde
## VF:100   18.9     de
## VF:60    17.2     de
## VG:30    13.4      e
############ 1.1 anova Biomassa de talo ###########################
summary(aov(talo ~ a+b+inter, data = exp))
##             Df Sum Sq Mean Sq F value   Pr(>F)    
## a            3 0.2088 0.06961   7.300 0.000396 ***
## b            2 0.0769 0.03845   4.033 0.024050 *  
## inter        6 0.0089 0.00148   0.156 0.987011    
## Residuals   48 0.4577 0.00953                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
LSD.test(aov(talo ~ a + b + inter, data = exp),
         "a", alpha = 0.05)["groups"]
## $groups
##         talo groups
## MT 0.3366667      a
## VØ 0.2900000      a
## VF 0.2713333      a
## VG 0.1746667      b
LSD.test(aov(talo ~ a + b + inter, data = exp),
         "b", alpha = 0.05)["groups"]
## $groups
##       talo groups
## 100 0.3180      a
## 60  0.2510      b
## 30  0.2355      b
LSD.test(aov(talo ~ a + b + inter, data = exp),
         "inter", alpha = 0.05)["groups"]
## $groups
##         talo groups
## MT:100 0.398      a
## MT:60  0.334     ab
## VØ:100 0.326     ab
## VF:100 0.322     ab
## VØ:60  0.280     ab
## MT:30  0.278     ab
## VØ:30  0.264     bc
## VF:30  0.252     bc
## VF:60  0.240     bc
## VG:100 0.226     bc
## VG:60  0.150      c
## VG:30  0.148      c
shapiro.test(unlist(aov(talo ~ a + b + inter, 
                        data = exp)["residuals"]))
## 
##  Shapiro-Wilk normality test
## 
## data:  unlist(aov(talo ~ a + b + inter, data = exp)["residuals"])
## W = 0.91865, p-value = 0.0006767
res <-sort(unlist(aov( talo ~ a + b + inter, 
                       data = exp)["residuals"]),decreasing = TRUE)
ks.test(res,  "pnorm" ,mean(res),sd(res))
## Warning in ks.test(res, "pnorm", mean(res), sd(res)): ties should not be present
## for the Kolmogorov-Smirnov test
## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  res
## D = 0.1174, p-value = 0.3799
## alternative hypothesis: two-sided
kruskal(talo, inter)["groups"]
## $groups
##        talo groups
## MT:100 50.2      a
## MT:60  41.7     ab
## VF:100 41.2     ab
## VØ:100 34.2     ab
## VØ:60  33.7     ab
## MT:30  33.4     ab
## VØ:30  31.4      b
## VF:30  29.7      b
## VF:60  27.2     bc
## VG:100 23.9     bc
## VG:30  10.5      c
## VG:60   8.9      c
############ 1.1 anova Biomassa de talo2 ###########################
summary(aov(talo2 ~ a+b+inter, data = exp))
##             Df Sum Sq Mean Sq F value  Pr(>F)   
## a            3 0.2531 0.08437   5.973 0.00152 **
## b            2 0.0749 0.03744   2.650 0.08094 . 
## inter        6 0.0930 0.01551   1.098 0.37750   
## Residuals   48 0.6780 0.01413                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
LSD.test(aov(talo2 ~ a + b + inter, data = exp),
         "a", alpha = 0.05)["groups"]
## $groups
##    talo2 groups
## MT 0.314      a
## VØ 0.280     ab
## VF 0.226     bc
## VG 0.142      c
LSD.test(aov(talo2 ~ a + b + inter, data = exp),
         "b", alpha = 0.05)["groups"]
## $groups
##      talo2 groups
## 100 0.2885      a
## 60  0.2285     ab
## 30  0.2045      b
LSD.test(aov(talo2 ~ a + b + inter, data = exp),
         "inter", alpha = 0.05)["groups"]
## $groups
##        talo2 groups
## MT:100 0.392      a
## VØ:100 0.370     ab
## VØ:60  0.306    abc
## MT:60  0.282   abcd
## MT:30  0.268   abcd
## VF:30  0.248   abcd
## VF:100 0.240    bcd
## VF:60  0.190     cd
## VØ:30  0.164     cd
## VG:100 0.152      d
## VG:30  0.138      d
## VG:60  0.136      d
shapiro.test(unlist(aov(talo2 ~ a + b + inter, 
                        data = exp)["residuals"]))
## 
##  Shapiro-Wilk normality test
## 
## data:  unlist(aov(talo2 ~ a + b + inter, data = exp)["residuals"])
## W = 0.97962, p-value = 0.4126
res <-sort(unlist(aov( talo2 ~ a + b + inter, 
                       data = exp)["residuals"]),decreasing = TRUE)
ks.test(res,  "pnorm" ,mean(res),sd(res))
## Warning in ks.test(res, "pnorm", mean(res), sd(res)): ties should not be present
## for the Kolmogorov-Smirnov test
## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  res
## D = 0.064742, p-value = 0.963
## alternative hypothesis: two-sided
kruskal(talo2, inter)["groups"]
## $groups
##        talo2 groups
## MT:100  49.5      a
## VØ:100  47.0     ab
## VØ:60   38.1    abc
## MT:60   37.4    abc
## MT:30   34.3   abcd
## VF:30   29.5    bcd
## VF:100  28.9    bcd
## VF:60   23.9     cd
## VG:100  21.9     cd
## VG:60   19.3     cd
## VØ:30   19.2     cd
## VG:30   17.0      d
############ 1.1 anova Biomassa de raiz###########################
summary(aov(raiz ~ a+b+inter, data = exp))
##             Df  Sum Sq  Mean Sq F value   Pr(>F)    
## a            3 0.04236 0.014120  11.519 8.31e-06 ***
## b            2 0.00352 0.001762   1.437    0.248    
## inter        6 0.00845 0.001408   1.149    0.349    
## Residuals   48 0.05884 0.001226                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
LSD.test(aov(raiz ~ a + b + inter, data = exp),
         "a", alpha = 0.05)["groups"]
## $groups
##         raiz groups
## MT 0.1560000      a
## VØ 0.1360000      a
## VF 0.1006667      b
## VG 0.0900000      b
LSD.test(aov(raiz ~ a + b + inter, data = exp),
         "b", alpha = 0.05)["groups"]
## $groups
##       raiz groups
## 60  0.1290      a
## 100 0.1225      a
## 30  0.1105      a
LSD.test(aov(raiz ~ a + b + inter, data = exp),
         "inter", alpha = 0.05)["groups"]
## $groups
##         raiz groups
## MT:60  0.178      a
## VØ:100 0.150     ab
## VØ:60  0.148    abc
## MT:30  0.146    abc
## MT:100 0.144    abc
## VF:100 0.112    bcd
## VØ:30  0.110    bcd
## VF:30  0.104     cd
## VG:60  0.104     cd
## VF:60  0.086      d
## VG:100 0.084      d
## VG:30  0.082      d
shapiro.test(unlist(aov(raiz ~ a + b + inter, 
                        data = exp)["residuals"]))
## 
##  Shapiro-Wilk normality test
## 
## data:  unlist(aov(raiz ~ a + b + inter, data = exp)["residuals"])
## W = 0.97019, p-value = 0.149
res <-sort(unlist(aov( raiz ~ a + b + inter, 
                       data = exp)["residuals"]),decreasing = TRUE)
ks.test(res,  "pnorm" ,mean(res),sd(res))
## Warning in ks.test(res, "pnorm", mean(res), sd(res)): ties should not be present
## for the Kolmogorov-Smirnov test
## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  res
## D = 0.066658, p-value = 0.9525
## alternative hypothesis: two-sided
kruskal(raiz, inter)["groups"]
## $groups
##        raiz groups
## MT:60  52.6      a
## VØ:100 45.4      a
## MT:30  42.9     ab
## MT:100 42.7    abc
## VØ:60  36.7   abcd
## VF:100 26.6   bcde
## VØ:30  25.8    cde
## VG:60  23.5     de
## VF:30  23.1     de
## VG:100 17.5      e
## VF:60  16.1      e
## VG:30  13.1      e
############ 1.1 anova Biomassa de raiz2 ###########################
summary(aov(raiz2 ~ a+b+inter, data = exp))
##             Df  Sum Sq  Mean Sq F value   Pr(>F)    
## a            3 0.05526 0.018419   7.112 0.000477 ***
## b            2 0.00434 0.002172   0.838 0.438600    
## inter        6 0.01218 0.002029   0.784 0.587028    
## Residuals   48 0.12432 0.002590                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
LSD.test(aov(raiz2 ~ a + b + inter, data = exp),
         "a", alpha = 0.05)["groups"]
## $groups
##         raiz2 groups
## MT 0.14466667      a
## VØ 0.11533333     ab
## VF 0.09000000     bc
## VG 0.06266667      c
LSD.test(aov( raiz2 ~ a + b + inter, data = exp),
         "b", alpha = 0.05)["groups"]
## $groups
##      raiz2 groups
## 100 0.1145      a
## 60  0.1010      a
## 30  0.0940      a
LSD.test(aov(raiz2 ~ a + b + inter, data = exp),
         "inter", alpha = 0.05)["groups"]
## $groups
##        raiz2 groups
## MT:100 0.170      a
## VØ:100 0.138     ab
## MT:60  0.134    abc
## MT:30  0.130    abc
## VØ:60  0.120   abcd
## VF:30  0.108  abcde
## VF:60  0.090   bcde
## VØ:30  0.088   bcde
## VG:100 0.078   bcde
## VF:100 0.072    cde
## VG:60  0.060     de
## VG:30  0.050      e
shapiro.test(unlist(aov(raiz2 ~ a + b + inter, 
                        data = exp)["residuals"]))
## 
##  Shapiro-Wilk normality test
## 
## data:  unlist(aov(raiz2 ~ a + b + inter, data = exp)["residuals"])
## W = 0.96477, p-value = 0.08065
res <-sort(unlist(aov( raiz2 ~ a + b + inter, 
                       data = exp)["residuals"]),decreasing = TRUE)
ks.test(res,  "pnorm" ,mean(res),sd(res))
## Warning in ks.test(res, "pnorm", mean(res), sd(res)): ties should not be present
## for the Kolmogorov-Smirnov test
## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  res
## D = 0.097107, p-value = 0.6235
## alternative hypothesis: two-sided
kruskal(raiz2, inter)["groups"]
## $groups
##        raiz2 groups
## MT:100  51.4      a
## MT:60   42.7     ab
## MT:30   40.5     ab
## VØ:100  39.1    abc
## VØ:60   35.8   abcd
## VF:30   30.9   bcde
## VF:60   26.0   bcde
## VØ:30   26.0   bcde
## VG:100  21.2    cde
## VG:60   19.0     de
## VF:100  18.7     de
## VG:30   14.7      e
########## Anova CLOROFILA EXPERIMENTOS 2-3##############

exp <- read_excel("C:/Users/User/Desktop/exp.xlsx", 
                  sheet = "clor2")
#View(exp)
attach(exp)
names(exp)
## [1] "genot"    "cc"       "rep"      "clora2"   "clorb2"   "clortot2"
a <- as.factor(genot)
b <- as.factor(cc)
inter<-as.factor(a:b)
############ 1.1 anova Clorofila A2 ###########################

summary(aov(clora2 ~ a+b+inter, data = exp))
##             Df Sum Sq Mean Sq F value  Pr(>F)   
## a            3  336.2  112.06   4.406 0.00833 **
## b            2    0.9    0.46   0.018 0.98208   
## inter        6  203.8   33.97   1.336 0.26094   
## Residuals   46 1170.0   25.43                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 2 observations deleted due to missingness
LSD.test(aov(clora2 ~ a + b + inter, data = exp),
         "a", alpha = 0.05)["groups"]
## $groups
##      clora2 groups
## VF 38.91333      a
## VA 37.50000      a
## MT 36.20667     ab
## VG 32.51333      b
LSD.test(aov(clora2 ~ a + b + inter, data = exp),
         "b", alpha = 0.05)["groups"]
## $groups
##       clora2 groups
## 60  36.38000      a
## 100 36.23333      a
## 30  36.11000      a
LSD.test(aov(clora2 ~ a + b + inter, data = exp),
         "inter", alpha = 0.05)["groups"]
## $groups
##          clora2 groups
## VA:60  41.26000      a
## VF:30  40.82000     ab
## VF:100 38.88000    abc
## MT:100 37.96000    abc
## VF:60  37.04000   abcd
## MT:60  36.16000   abcd
## VA:30  35.94000   abcd
## MT:30  34.50000    bcd
## VA:100 33.83333    bcd
## VG:100 33.30000     cd
## VG:30  33.18000     cd
## VG:60  31.06000      d
shapiro.test(unlist(aov(clora2 ~ a + b + inter, 
                        data = exp)["residuals"]))
## 
##  Shapiro-Wilk normality test
## 
## data:  unlist(aov(clora2 ~ a + b + inter, data = exp)["residuals"])
## W = 0.97854, p-value = 0.3924
res <-sort(unlist(aov( clora2 ~ a + b + inter, 
                       data = exp)["residuals"]),decreasing = TRUE)
ks.test(res,  "pnorm" ,mean(res),sd(res))
## Warning in ks.test(res, "pnorm", mean(res), sd(res)): ties should not be present
## for the Kolmogorov-Smirnov test
## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  res
## D = 0.068384, p-value = 0.9491
## alternative hypothesis: two-sided
kruskal(clora2, inter)["groups"]
## $groups
##          clora2 groups
## VA:60  45.40000      a
## VF:30  45.30000      a
## VF:100 36.70000     ab
## MT:100 35.10000     ab
## VA:30  29.80000    abc
## VF:60  29.50000    abc
## MT:60  27.60000    abc
## MT:30  27.40000    abc
## VG:30  20.60000     bc
## VA:100 19.33333     bc
## VG:100 18.20000     bc
## VG:60  15.00000      c
############ 1.2 anova Clorofila B2 ###########################

summary(aov(clorb2 ~ a+b+inter, data = exp))
##             Df Sum Sq Mean Sq F value  Pr(>F)   
## a            3  184.6   61.52   4.290 0.00944 **
## b            2    1.4    0.68   0.047 0.95406   
## inter        6  102.2   17.03   1.188 0.32965   
## Residuals   46  659.6   14.34                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 2 observations deleted due to missingness
LSD.test(aov(clorb2 ~ a + b + inter, data = exp),
         "a", alpha = 0.05)["groups"]
## $groups
##      clorb2 groups
## VA 15.56923      a
## VF 15.18667      a
## MT 14.96667      a
## VG 11.18000      b
LSD.test(aov(clorb2 ~ a + b + inter, data = exp),
         "b", alpha = 0.05)["groups"]
## $groups
##       clorb2 groups
## 30  14.43500      a
## 60  14.10000      a
## 100 13.98333      a
LSD.test(aov(clorb2 ~ a + b + inter, data = exp),
         "inter", alpha = 0.05)["groups"]
## $groups
##          clorb2 groups
## VA:60  17.34000      a
## VF:30  16.96000     ab
## VF:100 16.04000     ab
## MT:100 15.70000    abc
## MT:60  15.34000    abc
## VA:30  14.52000   abcd
## VA:100 14.36667   abcd
## MT:30  13.86000   abcd
## VF:60  12.56000   abcd
## VG:30  12.40000    bcd
## VG:60  11.16000     cd
## VG:100  9.98000      d
shapiro.test(unlist(aov(clorb2 ~ a + b + inter, 
                        data = exp)["residuals"]))
## 
##  Shapiro-Wilk normality test
## 
## data:  unlist(aov(clorb2 ~ a + b + inter, data = exp)["residuals"])
## W = 0.96355, p-value = 0.07887
res <-sort(unlist(aov( clorb2 ~ a + b + inter, 
                       data = exp)["residuals"]),decreasing = TRUE)
ks.test(res,  "pnorm" ,mean(res),sd(res))
## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  res
## D = 0.08704, p-value = 0.7388
## alternative hypothesis: two-sided
kruskal(clorb2, inter)["groups"]
## $groups
##        clorb2 groups
## VA:60    44.2      a
## VF:30    41.7     ab
## VF:100   37.1    abc
## MT:60    35.5    abc
## MT:100   34.8   abcd
## VA:30    29.7   abcd
## VA:100   27.0   abcd
## MT:30    25.2   abcd
## VF:60    23.9    bcd
## VG:30    21.1     cd
## VG:60    17.6     cd
## VG:100   15.2      d
############ 1.2 anova Clorofila total2 ###########################

summary(aov(clortot2 ~ a+b+inter, data = exp))
##             Df Sum Sq Mean Sq F value Pr(>F)  
## a            3   1015   338.3   2.721 0.0547 .
## b            2    377   188.5   1.516 0.2299  
## inter        6   2248   374.6   3.013 0.0140 *
## Residuals   48   5969   124.3                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
LSD.test(aov(clortot2 ~ a + b + inter, data = exp),
         "a", alpha = 0.05)["groups"]
## $groups
##    clortot2 groups
## VF 54.10000      a
## MT 51.17333     ab
## VA 45.99333     ab
## VG 43.69333      b
LSD.test(aov(clortot2 ~ a + b + inter, data = exp),
         "b", alpha = 0.05)["groups"]
## $groups
##     clortot2 groups
## 30    50.545      a
## 60    50.480      a
## 100   45.195      a
LSD.test(aov(clortot2 ~ a + b + inter, data = exp),
         "inter", alpha = 0.05)["groups"]
## $groups
##        clortot2 groups
## VA:60     58.60      a
## VF:30     57.78      a
## VF:100    54.92     ab
## MT:100    53.66     ab
## MT:60     51.50     ab
## VA:30     50.46     ab
## VF:60     49.60     ab
## MT:30     48.36     ab
## VG:30     45.58     ab
## VG:100    43.28      b
## VG:60     42.22     bc
## VA:100    28.92      c
shapiro.test(unlist(aov(clortot2 ~ a + b + inter, 
                        data = exp)["residuals"]))
## 
##  Shapiro-Wilk normality test
## 
## data:  unlist(aov(clortot2 ~ a + b + inter, data = exp)["residuals"])
## W = 0.96518, p-value = 0.08453
res <-sort(unlist(aov( clortot2~ a + b + inter, 
                       data = exp)["residuals"]),decreasing = TRUE)
ks.test(res,  "pnorm" ,mean(res),sd(res))
## Warning in ks.test(res, "pnorm", mean(res), sd(res)): ties should not be present
## for the Kolmogorov-Smirnov test
## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  res
## D = 0.081413, p-value = 0.8213
## alternative hypothesis: two-sided
kruskal(clortot2,inter)["groups"]
## $groups
##        clortot2 groups
## VA:60      47.2      a
## VF:30      45.6      a
## VF:100     38.8     ab
## MT:100     38.4     ab
## MT:60      33.7    abc
## VA:30      32.4    abc
## VF:60      28.2    abc
## MT:30      28.0    abc
## VG:30      23.2     bc
## VG:100     18.3      c
## VG:60      16.6      c
## VA:100     15.6      c
exp <- read_excel("C:/Users/User/Desktop/exp.xlsx", 
                  sheet = "clor3")
#View(exp)
attach(exp)
## The following objects are masked from exp (pos = 3):
## 
##     cc, genot, rep
names(exp)
## [1] "genot" "cc"    "rep"   "clora" "clorb" "clor"
a <- as.factor(genot)
b <- as.factor(cc)
inter<-as.factor(a:b)

############ 1.2 anova Clorofila A3 ###########################


summary(aov(clora ~ a+b+inter, data = exp))
##             Df Sum Sq Mean Sq F value Pr(>F)
## a            3    7.5    2.49   0.050  0.985
## b            2   48.8   24.42   0.487  0.617
## inter        6  246.5   41.08   0.820  0.560
## Residuals   48 2406.2   50.13
LSD.test(aov(clora ~ a + b + inter, data = exp),
         "a", alpha = 0.05)["groups"]
## $groups
##       clora groups
## VA 37.92667      a
## MT 37.69333      a
## VF 37.60667      a
## VG 36.97333      a
LSD.test(aov(clora ~ a + b + inter, data = exp),
         "b", alpha = 0.05)["groups"]
## $groups
##     clora groups
## 30  38.65      a
## 100 37.56      a
## 60  36.44      a
LSD.test(aov(clora ~ a + b + inter, data = exp),
         "inter", alpha = 0.05)["groups"]
## $groups
##        clora groups
## MT:100 40.36      a
## VA:60  39.66      a
## VF:30  39.36      a
## VA:30  39.30      a
## VF:100 39.22      a
## MT:30  39.02      a
## VG:60  38.16      a
## VG:30  36.92      a
## VG:100 35.84      a
## VA:100 34.82      a
## VF:60  34.24      a
## MT:60  33.70      a
shapiro.test(unlist(aov(clora ~ a + b + inter, 
                        data = exp)["residuals"]))
## 
##  Shapiro-Wilk normality test
## 
## data:  unlist(aov(clora ~ a + b + inter, data = exp)["residuals"])
## W = 0.81671, p-value = 3.613e-07
res <-sort(unlist(aov( clora ~ a + b + inter, 
                       data = exp)["residuals"]),decreasing = TRUE)
ks.test(res,  "pnorm" ,mean(res),sd(res))
## Warning in ks.test(res, "pnorm", mean(res), sd(res)): ties should not be present
## for the Kolmogorov-Smirnov test
## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  res
## D = 0.18426, p-value = 0.03401
## alternative hypothesis: two-sided
kruskal(clora, inter)["groups"]
## $groups
##        clora groups
## VA:100  36.8      a
## MT:30   35.6      a
## VA:60   35.4      a
## VG:60   34.7      a
## VA:30   32.4      a
## VF:30   31.4      a
## MT:100  31.1      a
## MT:60   29.8      a
## VF:100  29.2      a
## VF:60   27.8      a
## VG:100  22.6      a
## VG:30   19.2      a
############ 1.2 anova Clorofila B3 ###########################

summary(aov(clorb ~ a+b+inter, data = exp))
##             Df Sum Sq Mean Sq F value Pr(>F)
## a            3   41.7  13.905   0.894  0.451
## b            2   12.9   6.469   0.416  0.662
## inter        6   85.0  14.174   0.911  0.495
## Residuals   48  746.9  15.561
LSD.test(aov(clorb ~ a + b + inter, data = exp),
         "a", alpha = 0.05)["groups"]
## $groups
##       clorb groups
## VA 17.12667      a
## VF 16.42667      a
## MT 15.91333      a
## VG 14.84000      a
LSD.test(aov(clorb ~ a + b + inter, data = exp),
         "b", alpha = 0.05)["groups"]
## $groups
##     clorb groups
## 60  16.56      a
## 30  16.22      a
## 100 15.45      a
LSD.test(aov(clorb ~ a + b + inter, data = exp),
         "inter", alpha = 0.05)["groups"]
## $groups
##        clorb groups
## VA:100 18.22      a
## MT:60  17.78      a
## VF:30  17.12     ab
## VF:100 16.92     ab
## VA:60  16.74     ab
## VG:60  16.48     ab
## VA:30  16.42     ab
## MT:30  15.68     ab
## VG:30  15.66     ab
## VF:60  15.24     ab
## MT:100 14.28     ab
## VG:100 12.38      b
shapiro.test(unlist(aov(clorb ~ a + b + inter, 
                        data = exp)["residuals"]))
## 
##  Shapiro-Wilk normality test
## 
## data:  unlist(aov(clorb ~ a + b + inter, data = exp)["residuals"])
## W = 0.8978, p-value = 0.0001095
res <-sort(unlist(aov( clorb ~ a + b + inter, 
                       data = exp)["residuals"]),decreasing = TRUE)
ks.test(res,  "pnorm" ,mean(res),sd(res))
## Warning in ks.test(res, "pnorm", mean(res), sd(res)): ties should not be present
## for the Kolmogorov-Smirnov test
## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  res
## D = 0.13566, p-value = 0.2194
## alternative hypothesis: two-sided
kruskal(clorb, inter)["groups"]
## $groups
##        clorb groups
## VA:100  45.0      a
## MT:60   38.0     ab
## VG:60   34.5     ab
## VF:30   34.1     ab
## VF:100  33.0     ab
## VA:30   32.1     ab
## VA:60   31.6     ab
## MT:30   31.0     ab
## VF:60   25.5     ab
## VG:30   25.5     ab
## VG:100  19.4      b
## MT:100  16.3      b
############ 1.2 anova Clorofila total3 ###########################

summary(aov(clor ~ a+b+inter, data = exp))
##             Df Sum Sq Mean Sq F value Pr(>F)
## a            3     82   27.45   0.304  0.822
## b            2     46   23.19   0.257  0.775
## inter        6    282   47.06   0.521  0.790
## Residuals   48   4336   90.34
LSD.test(aov(clor ~ a + b + inter, data = exp),
         "a", alpha = 0.05)["groups"]
## $groups
##        clor groups
## VA 55.05333      a
## VF 54.03333      a
## MT 53.60667      a
## VG 51.81333      a
LSD.test(aov(clor ~ a + b + inter, data = exp),
         "b", alpha = 0.05)["groups"]
## $groups
##      clor groups
## 30  54.87      a
## 100 53.01      a
## 60  53.00      a
LSD.test(aov(clor ~ a + b + inter, data = exp),
         "inter", alpha = 0.05)["groups"]
## $groups
##         clor groups
## VF:30  56.48      a
## VA:60  56.40      a
## VF:100 56.14      a
## VA:30  55.72      a
## MT:30  54.70      a
## MT:100 54.64      a
## VG:60  54.64      a
## VA:100 53.04      a
## VG:30  52.58      a
## MT:60  51.48      a
## VF:60  49.48      a
## VG:100 48.22      a
shapiro.test(unlist(aov(clor ~ a + b + inter, 
                        data = exp)["residuals"]))
## 
##  Shapiro-Wilk normality test
## 
## data:  unlist(aov(clor ~ a + b + inter, data = exp)["residuals"])
## W = 0.86674, p-value = 9.859e-06
res <-sort(unlist(aov( clor~ a + b + inter, 
                       data = exp)["residuals"]),decreasing = TRUE)
ks.test(res,  "pnorm" ,mean(res),sd(res))
## Warning in ks.test(res, "pnorm", mean(res), sd(res)): ties should not be present
## for the Kolmogorov-Smirnov test
## 
##  One-sample Kolmogorov-Smirnov test
## 
## data:  res
## D = 0.14964, p-value = 0.1361
## alternative hypothesis: two-sided
kruskal(clor,inter)["groups"]
## $groups
##        clor groups
## VG:60  37.7      a
## VA:100 35.7      a
## VF:30  34.6      a
## VA:30  33.6      a
## MT:30  33.5      a
## VA:60  32.5      a
## VF:100 31.1      a
## MT:60  30.2      a
## MT:100 28.1      a
## VF:60  25.9      a
## VG:30  22.2      a
## VG:100 20.9      a