11th International Symposium on the Nutrition of Herbivores

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Packages

library(emmeans)

DATA

data=read.csv("D:/Armazenamento/DATA R/Herbivoros 2023/data.csv")
data

View(data)

ANOVA

1- pregrazing.height

boxplot(data$pregrazing.height)

mod1 = lm(pregrazing.height~treatments, data = data)

anova(mod1)

Analysis of Variance Table

Response: pregrazing.height
           Df Sum Sq Mean Sq F value Pr(>F)
treatments  1   0.26  0.2552  0.0245 0.8762
Residuals  46 478.66 10.4056               

medias1=emmeans(mod1,~treatments)
summary(medias1)

 treatments emmean    SE df lower.CL upper.CL
 exclusive    29.6 0.658 46     28.2     30.9
 SPS          29.4 0.658 46     28.1     30.7

Confidence level used: 0.95 

2- postgrazing.height

boxplot(data$postgrazing.height)

mod2 = lm(postgrazing.height~treatments, data = data)

anova(mod2)

Analysis of Variance Table

Response: postgrazing.height
           Df Sum Sq Mean Sq F value Pr(>F)
treatments  1   0.27    0.27  0.0231 0.8798
Residuals  46 537.27   11.68               

medias2=emmeans(mod2,~treatments)
summary(medias2)

 treatments emmean    SE df lower.CL upper.CL
 exclusive    13.0 0.698 46     11.6     14.4
 SPS          12.8 0.698 46     11.4     14.2

Confidence level used: 0.95 

3- bra.FM

boxplot(data$bra.FM)

mod3 = lm(bra.FM~treatments, data = data)

anova(mod3)

Analysis of Variance Table

Response: bra.FM
           Df   Sum Sq Mean Sq F value Pr(>F)
treatments  1   178499  178499  0.6512 0.4238
Residuals  46 12609192  274113               

medias3=emmeans(mod3,~treatments)
summary(medias3)

 treatments emmean  SE df lower.CL upper.CL
 exclusive    1428 107 46     1213     1643
 SPS          1550 107 46     1334     1765

Confidence level used: 0.95 

4- thi.FM

boxplot(data$thi.FM)

psych::describeBy(data[,8])

Warning: no grouping variable requested

5- total.FM

boxplot(data$total.FM)

mod5 = lm(total.FM~treatments, data = data)

anova(mod5)

Analysis of Variance Table

Response: total.FM
           Df   Sum Sq Mean Sq F value  Pr(>F)  
treatments  1  1807258 1807258  5.1539 0.02792 *
Residuals  46 16130228  350657                  
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Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

medias5=emmeans(mod5,~treatments)
summary(medias5)

 treatments emmean  SE df lower.CL upper.CL
 exclusive    1428 121 46     1184     1671
 SPS          1816 121 46     1572     2059

Confidence level used: 0.95 

6- bra.accumulation.rate

boxplot(data$bra.FM.rate)

mod6 = lm(bra.FM.rate~treatments, data = data)

anova(mod6)

Analysis of Variance Table

Response: bra.FM.rate
           Df  Sum Sq Mean Sq F value Pr(>F)
treatments  1   169.2  169.16  0.3068 0.5823
Residuals  46 25364.6  551.40               

medias6=emmeans(mod6,~treatments)
summary(medias6)

 treatments emmean   SE df lower.CL upper.CL
 exclusive    51.3 4.79 46     41.6     60.9
 SPS          55.0 4.79 46     45.4     64.7

Confidence level used: 0.95 

7- bra.leaves

boxplot(data$bra.leaves)

mod7 = lm(bra.leaves~treatments, data = data)

anova(mod7)

Analysis of Variance Table

Response: bra.leaves
           Df  Sum Sq Mean Sq F value Pr(>F)
treatments  1   64592   64592  1.4994  0.227
Residuals  46 1981596   43078               

medias7=emmeans(mod7,~treatments)
summary(medias7)

 treatments emmean   SE df lower.CL upper.CL
 exclusive     644 42.4 46      559      729
 SPS           571 42.4 46      485      656

Confidence level used: 0.95 

8- bra.stems

boxplot(data$bra.stems)

mod8 = lm(bra.stems~treatments, data = data)

anova(mod8)

Analysis of Variance Table

Response: bra.stems
           Df Sum Sq Mean Sq F value Pr(>F)
treatments  1  15307 15306.7  2.1829 0.1464
Residuals  46 322555  7012.1               

medias8=emmeans(mod8,~treatments)
summary(medias8)

 treatments emmean   SE df lower.CL upper.CL
 exclusive     143 17.1 46      108      177
 SPS           179 17.1 46      144      213

Confidence level used: 0.95 

9- bra.deadmaterial

boxplot(data$bra.deadmaterial)

mod9 = lm(bra.deadmaterial~treatments, data = data)

anova(mod9)

Analysis of Variance Table

Response: bra.deadmaterial
           Df  Sum Sq Mean Sq F value Pr(>F)
treatments  1   17598   17599   0.762 0.3872
Residuals  46 1062314   23094               

medias9=emmeans(mod9,~treatments)
summary(medias9)

 treatments emmean SE df lower.CL upper.CL
 exclusive     188 31 46      126      251
 SPS           226 31 46      164      289

Confidence level used: 0.95