Here is one method using dplyr and ggplot2.
DF <- data.frame(
stringsAsFactors = FALSE,
treatment = c("start","start","start",
"start","start","start","start","start","start","start",
"start","start","start","start","start","start",
"start","start","start","start","start","start",
"start","start","start","start","start","start","start",
"start","end","end","end","end","end","end",
"end","end","end","end","end","end","end","end","end",
"end","end","end","end","end","end","end","end",
"end","end","end","end","end","end","end"),
kg = c(45L,56L,35L,47L,46L,49L,
61L,50L,42L,50L,45L,38L,30L,46L,53L,48L,43L,54L,
67L,78L,63L,85L,79L,60L,74L,78L,57L,76L,91L,
77L,53L,65L,37L,58L,43L,54L,75L,54L,37L,56L,
60L,39L,37L,54L,48L,43L,47L,50L,76L,85L,62L,98L,
81L,66L,85L,83L,53L,89L,94L,90L)
)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(ggplot2)
DF %>% filter(treatment == "start") %>%
ggplot(aes(x = kg)) + geom_histogram(fill = "skyblue", color = "white", bins = 10)

Created on 2022-05-22 by the reprex package (v0.2.1)