S<-data.frame(read_excel("总数据.xlsx",1))

S$treat = factor(S$treat, levels=c("CK","N","P","NP"))

pc1<-subset(S,acid=="no")

pc2<-subset(S,acid=="yes")

model1<-aov(pPFrich~treat,data=pc1)

model2<-aov(pPFrich~treat,data=pc2)

out1<-data.frame(cbind(rownames(LSD.test(model1,"treat" )$groups),LSD.test(model1,"treat" )$groups[,2]))#显著性和位置

out2<-data.frame(cbind(rownames(LSD.test(model2,"treat" )$groups),toupper(LSD.test(model2,"treat" )$groups[,2])))#显著性和位置

c<-data.frame()

for (i in out1$X1) {

  a<-subset(pc1,treat==i)

  b<-mean(a$pPFrich)+sd(a$pPFrich)/sqrt(length(a$pPFrich))

  c<-rbind(c,b)

}

colnames(c)<-"po"#字母的位置

out1<-cbind(out1,c)

c1<-data.frame()

for (i in out2$X1) {

  a1<-subset(pc2,treat==i)

  b1<-mean(a1$pPFrich)+sd(a1$pPFrich)/sqrt(length(a1$pPFrich))

  c1<-rbind(c1,b1)

}

colnames(c1)<-"po"#字母的位置

out2<-cbind(out2,c1)

d<-rbind(c,c1)

posi<-(cbind(rbind(out1,out2),d))

e<-data.frame()

for (i in match(pc1$treat,out1$X1)) {

  a<-out1[i,2:3]

  e<-rbind(e,a)

}

colnames(e)<-c("sig","po")#字母文本和显著性字母

e1<-data.frame()

for (i in match(pc2$treat,out2$X1)) {

  a<-out2[i,2:3]

  e1<-rbind(e1,a)

}

colnames(e1)<-c("sig","po")#字母文本和显著性字母

S<-cbind(rbind(e,e1),rbind(pc1,pc2))

p<-ggplot(S,aes(x=treat,y=pPFrich ,fill=acid))+stat_summary(geom = "bar",fun = "mean",

position = position_dodge(0.6),width=0.6, color="black")+stat_summary(geom = "errorbar",

fun.min = ebbottom,

fun.max = ebtop,

position = position_dodge(0.6),

width=0.2)+ geom_text(aes(x=treat,y=po+po*0.04,label = sig),position = position_dodge(0.6))+theme(legend.position = c('none')

,axis.text.y=element_text(angle=90),axis.title.x = element_blank())+scale_y_continuous(limits = c(0,8),expand = c(0, 0))+scale_fill_manual(values=c("#008B00","#FF7F24"))

p