sclerotinia Sclerotiorum em Tomate MT
library(agricolae)
library(readxl)
library(agricolae)
library(dplyr)
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library(PerformanceAnalytics)
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library(car)
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library(sf)
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library(rgdal)
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library(esquisse)
library(ggplot2)
library(gridExtra)
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dt <- read_excel("C:/Users/User/Desktop/Sclerotinia_Sclerotiorum.xlsx",
sheet = "re2")
attach(dt)
names(dt)
## [1] "vector" "trat" "folha" "talof" "folhsec" "talosec" "raizsec"
a <- as.factor(vector)
b <- as.factor(trat)
inter<-as.factor(a:b)
############ 1.1 anova folha fresca ###########################
summary(aov(folha ~ a+b+inter, data = dt))
## Df Sum Sq Mean Sq F value Pr(>F)
## a 4 2.45 0.61 9.174 5.77e-05 ***
## b 1 39.36 39.36 588.573 < 2e-16 ***
## inter 4 0.91 0.23 3.405 0.0207 *
## Residuals 30 2.01 0.07
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
LSD.test(aov(folha ~ a + b + inter, data = dt),
"a", alpha = 0.05)["groups"]
## $groups
## folha groups
## MT 1.936750 a
## VF.1 1.527500 b
## VF 1.428500 bc
## VG 1.286750 bc
## VA 1.243375 c
LSD.test(aov(folha ~ a + b + inter, data = dt),
"b", alpha = 0.05)["groups"]
## $groups
## folha groups
## controle 2.47655 a
## inocu 0.49260 b
LSD.test(aov(folha ~ a + b + inter, data = dt),
"inter", alpha = 0.05)["groups"]
## $groups
## folha groups
## MT:controle 3.21850 a
## VF.1:controle 2.48150 b
## VF:controle 2.27200 b
## VG:controle 2.25000 b
## VA:controle 2.16075 b
## MT:inocu 0.65500 c
## VF:inocu 0.58500 c
## VF.1:inocu 0.57350 c
## VA:inocu 0.32600 c
## VG:inocu 0.32350 c
shapiro.test(unlist(aov(folha ~ a + b + inter,
data = dt)["residuals"]))
##
## Shapiro-Wilk normality test
##
## data: unlist(aov(folha ~ a + b + inter, data = dt)["residuals"])
## W = 0.98327, p-value = 0.808
res <-sort(unlist(aov( folha ~ a + b + inter,
data = dt)["residuals"]),decreasing = TRUE)
ks.test(res, "pnorm" ,mean(res),sd(res))
##
## One-sample Kolmogorov-Smirnov test
##
## data: res
## D = 0.095912, p-value = 0.8214
## alternative hypothesis: two-sided
kruskal(folha, inter)["groups"]
## $groups
## folha groups
## MT:controle 38.500 a
## VF.1:controle 32.000 ab
## VF:controle 28.500 b
## VG:controle 27.000 b
## VA:controle 26.500 b
## MT:inocu 14.750 c
## VF:inocu 12.500 cd
## VF.1:inocu 12.250 cd
## VA:inocu 7.125 d
## VG:inocu 5.875 d
##### 1.2 anova talo fresco #####################################################
summary(aov(talof ~ a+b+inter, data = dt))
## Df Sum Sq Mean Sq F value Pr(>F)
## a 4 1.878 0.470 6.897 0.000462 ***
## b 1 12.508 12.508 183.732 2.51e-14 ***
## inter 4 0.247 0.062 0.905 0.473333
## Residuals 30 2.042 0.068
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
LSD.test(aov(talof ~ a + b + inter, data = dt),
"a", alpha = 0.05)["groups"]
## $groups
## talof groups
## MT 1.4205 a
## VF 1.3925 ab
## VF.1 1.1470 bc
## VA 0.9725 c
## VG 0.8815 c
LSD.test(aov(folha ~ a + b + inter, data = dt),
"b", alpha = 0.05)["groups"]
## $groups
## folha groups
## controle 2.47655 a
## inocu 0.49260 b
LSD.test(aov(talof ~ a + b + inter, data = dt),
"inter", alpha = 0.05)["groups"]
## $groups
## talof groups
## MT:controle 2.0990 a
## VF:controle 1.8785 ab
## VF.1:controle 1.7030 bc
## VA:controle 1.5820 bc
## VG:controle 1.3475 c
## VF:inocu 0.9065 d
## MT:inocu 0.7420 de
## VF.1:inocu 0.5910 def
## VG:inocu 0.4155 ef
## VA:inocu 0.3630 f
shapiro.test(unlist(aov(talof ~ a + b + inter,
data = dt)["residuals"]))
##
## Shapiro-Wilk normality test
##
## data: unlist(aov(talof ~ a + b + inter, data = dt)["residuals"])
## W = 0.97042, p-value = 0.3711
res <-sort(unlist(aov( talof ~ a + b + inter,
data = dt)["residuals"]),decreasing = TRUE)
ks.test(res, "pnorm" ,mean(res),sd(res))
##
## One-sample Kolmogorov-Smirnov test
##
## data: res
## D = 0.1125, p-value = 0.6508
## alternative hypothesis: two-sided
kruskal(talof, inter)["groups"]
## $groups
## talof groups
## MT:controle 36.00 a
## VF:controle 33.75 ab
## VF.1:controle 30.25 abc
## VA:controle 27.50 bc
## VG:controle 23.50 cd
## VF:inocu 17.00 de
## MT:inocu 15.50 e
## VF.1:inocu 10.25 ef
## VG:inocu 7.00 f
## VA:inocu 4.25 f
#######1.3 anova folhas secas #################################
summary(aov(folhsec ~ a+b+inter, data = dt))
## Df Sum Sq Mean Sq F value Pr(>F)
## a 4 0.01025 0.002562 0.583 0.677
## b 1 0.02448 0.024478 5.572 0.025 *
## inter 4 0.00175 0.000437 0.100 0.982
## Residuals 30 0.13180 0.004393
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
LSD.test(aov(folhsec ~ a + b + inter, data = dt),
"a", alpha = 0.05)["groups"]
## $groups
## folhsec groups
## MT 0.1775000 a
## VF 0.1622500 a
## VF.1 0.1577500 a
## VG 0.1397500 a
## VA 0.1329375 a
LSD.test(aov(folhsec ~ a + b + inter, data = dt),
"b", alpha = 0.05)["groups"]
## $groups
## folhsec groups
## inocu 0.178775 a
## controle 0.129300 b
LSD.test(aov(folhsec ~ a + b + inter, data = dt),
"inter", alpha = 0.05)["groups"]
## $groups
## folhsec groups
## MT:inocu 0.201500 a
## VF:inocu 0.181500 ab
## VF.1:inocu 0.175500 ab
## VA:inocu 0.169375 ab
## VG:inocu 0.166000 ab
## MT:controle 0.153500 ab
## VF:controle 0.143000 ab
## VF.1:controle 0.140000 ab
## VG:controle 0.113500 ab
## VA:controle 0.096500 b
shapiro.test(unlist(aov(folhsec ~ a + b + inter,
data = dt)["residuals"]))
##
## Shapiro-Wilk normality test
##
## data: unlist(aov(folhsec ~ a + b + inter, data = dt)["residuals"])
## W = 0.96814, p-value = 0.3137
res <-sort(unlist(aov( folhsec ~ a + b + inter,
data = dt)["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 = 0.087688, p-value = 0.9181
## alternative hypothesis: two-sided
kruskal(talof, inter)["groups"]
## $groups
## talof groups
## MT:controle 36.00 a
## VF:controle 33.75 ab
## VF.1:controle 30.25 abc
## VA:controle 27.50 bc
## VG:controle 23.50 cd
## VF:inocu 17.00 de
## MT:inocu 15.50 e
## VF.1:inocu 10.25 ef
## VG:inocu 7.00 f
## VA:inocu 4.25 f
#######1.4 anova talo seco #################################
summary(aov(talosec ~ a+b+inter, data = dt))
## Df Sum Sq Mean Sq F value Pr(>F)
## a 4 0.01627 0.004068 1.194 0.33363
## b 1 0.02670 0.026703 7.839 0.00886 **
## inter 4 0.00246 0.000614 0.180 0.94686
## Residuals 30 0.10219 0.003406
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
LSD.test(aov(talosec ~ a + b + inter, data = dt),
"a", alpha = 0.05)["groups"]
## $groups
## talosec groups
## MT 0.1525000 a
## VF 0.1357500 a
## VG 0.1112500 a
## VF.1 0.1087500 a
## VA 0.0969375 a
LSD.test(aov(talosec ~ a + b + inter, data = dt),
"b", alpha = 0.05)["groups"]
## $groups
## talosec groups
## inocu 0.146875 a
## controle 0.095200 b
LSD.test(aov(talosec ~ a + b + inter, data = dt),
"inter", alpha = 0.05)["groups"]
## $groups
## talosec groups
## MT:inocu 0.182500 a
## VF:inocu 0.153500 ab
## VG:inocu 0.142500 abc
## VA:inocu 0.131875 abc
## VF.1:inocu 0.124000 abc
## MT:controle 0.122500 abc
## VF:controle 0.118000 abc
## VF.1:controle 0.093500 bc
## VG:controle 0.080000 bc
## VA:controle 0.062000 c
shapiro.test(unlist(aov(talosec ~ a + b + inter,
data = dt)["residuals"]))
##
## Shapiro-Wilk normality test
##
## data: unlist(aov(talosec ~ a + b + inter, data = dt)["residuals"])
## W = 0.91665, p-value = 0.006054
res <-sort(unlist(aov( talosec ~ a + b + inter,
data = dt)["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 = 0.17309, p-value = 0.1819
## alternative hypothesis: two-sided
kruskal(talof, inter)["groups"]
## $groups
## talof groups
## MT:controle 36.00 a
## VF:controle 33.75 ab
## VF.1:controle 30.25 abc
## VA:controle 27.50 bc
## VG:controle 23.50 cd
## VF:inocu 17.00 de
## MT:inocu 15.50 e
## VF.1:inocu 10.25 ef
## VG:inocu 7.00 f
## VA:inocu 4.25 f
#######1.5 anova raiz seca #################################
summary(aov(raizsec ~ a+b+inter, data = dt))
## Df Sum Sq Mean Sq F value Pr(>F)
## a 4 0.001334 0.0003335 1.114 0.368
## b 1 0.000007 0.0000074 0.025 0.876
## inter 4 0.000671 0.0001678 0.560 0.693
## Residuals 30 0.008985 0.0002995
LSD.test(aov(raizsec ~ a + b + inter, data = dt),
"a", alpha = 0.05)["groups"]
## $groups
## raizsec groups
## MT 0.04475000 a
## VF 0.04123500 a
## VG 0.03273438 a
## VA 0.03125000 a
## VF.1 0.03055750 a
LSD.test(aov(raizsec ~ a + b + inter, data = dt),
"b", alpha = 0.05)["groups"]
## $groups
## raizsec groups
## inocu 0.03653675 a
## controle 0.03567400 a
LSD.test(aov(raizsec ~ a + b + inter, data = dt),
"inter", alpha = 0.05)["groups"]
## $groups
## raizsec groups
## MT:controle 0.04950000 a
## VF:controle 0.04437500 a
## MT:inocu 0.04000000 a
## VF:inocu 0.03809500 a
## VA:inocu 0.03737500 a
## VG:inocu 0.03659375 a
## VF.1:inocu 0.03062000 a
## VF.1:controle 0.03049500 a
## VG:controle 0.02887500 a
## VA:controle 0.02512500 a
shapiro.test(unlist(aov(raizsec ~ a + b + inter,
data = dt)["residuals"]))
##
## Shapiro-Wilk normality test
##
## data: unlist(aov(raizsec ~ a + b + inter, data = dt)["residuals"])
## W = 0.93972, p-value = 0.03385
res <-sort(unlist(aov( raizsec ~ a + b + inter,
data = dt)["residuals"]),decreasing = TRUE)
ks.test(res, "pnorm" ,mean(res),sd(res))
##
## One-sample Kolmogorov-Smirnov test
##
## data: res
## D = 0.11338, p-value = 0.6413
## alternative hypothesis: two-sided
kruskal(talof, inter)["groups"]
## $groups
## talof groups
## MT:controle 36.00 a
## VF:controle 33.75 ab
## VF.1:controle 30.25 abc
## VA:controle 27.50 bc
## VG:controle 23.50 cd
## VF:inocu 17.00 de
## MT:inocu 15.50 e
## VF.1:inocu 10.25 ef
## VG:inocu 7.00 f
## VA:inocu 4.25 f