Which test to use with three variables? that's my chart:

let's say that D0.5 was missing OJ. what statistical test could I use in this case?

You could use a One-way Anova to compare the means of three or more variables using the function aov. Your outcome variable is len and the independent variable is dose. Here is the visualization:
library(ggpubr)
data('ToothGrowth')

ggline(ToothGrowth, x = "dose", y = "len", color = "supp",
       add = c("mean_se", "dotplot"), palette = c("#00AFBB", "#E7B800"))


Let's test it with aov and check the summary:
res.aov <- aov(len ~ dose, data = ToothGrowth)
summary(res.aov)
#>             Df Sum Sq Mean Sq F value   Pr(>F)    
#> dose         1   2224  2224.3   105.1 1.23e-14 ***
#> Residuals   58   1228    21.2                     
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Created on 2022-12-11 with reprex v2.0.2
You can see that the p-value is less than 0.05, which means that there is a significant differences between the groups highlighted with * in the output.

Sources:

*

*One-Way ANOVA Test in R
