change environment size on scale_colour_manual to assign colour to factors to use across multiples plots

I need to make 5 plots of bacteria species. Each plot has a different number of species present in a range of 30-90. I want each bacteria to always have the same color in all plots, therefore I need to set an assigned color to each name. I tried to use scale_colour_manual to create a color set but, the environment created has only 16 colors. How can I increase the number of colors present in the environment created?

the code I am using can be replicated as follow:

colour_genus <- stringi::stri_rand_strings(90, 5) #to be random names

nb.cols = nrow(colour_genus) #to set the length of my string
MyPalette = colorRampPalette(brewer.pal(12,"Set1"))(nb.cols) # the palette of choice
colGenus <- scale_color_manual(name = colour_genus, values = MyPalette)

The output formed contains only 16 values, so when I try to apply it to a figure with 90 factors, it complains I have only 16 values

abundance <- runif(90, min = 10, max = 100)
my_data <- data.frame(colour_genus, abundance)

p <- ggplot(my_data, aes(x = colour_genus, y= abundance)) +
  geom_bar(aes(color = colour_genus, fill = colour_genus), stat = "identity", position = "stack") +
  labs(x = "", y = "Relative Abundance\n") +
  theme(panel.background = element_blank())
p + theme(legend.text= element_text(size=7, face="bold"), axis.text.x = element_text(angle = 90)) + guides(fill=guide_legend(ncol=2)) + scale_fill_manual(values=colGenus)

The following error shows: Error: Insufficient values in manual scale. 90 needed but only 16 provided.

Thank you very much for your help.

When you know all your 90 bacci names in front of plotting, you can try.

set.seed(123)
colour_genus <- sort(stringi::stri_rand_strings(90, 5))#to be random names. I sorted the vector to illustrate the output better (optional). 
MyPalette <- sample(colors(), length(colour_genus))
# named vector for scale_fill
names(MyPalette) <- colour_genus

# data
abundance <- runif(90, min = 10, max = 100)
my_data <- data.frame(colour_genus, abundance)

# two sets to show results
set1 <- my_data[20:30,]
set2 <- my_data[25:35,]
ggplot(set1, aes(x = colour_genus, y= abundance)) +
  geom_col(aes(fill = colour_genus)) +
  scale_fill_manual(values = MyPalette)

ggplot(set2, aes(x = colour_genus, y= abundance)) +
  geom_col(aes(fill = colour_genus)) +
  scale_fill_manual(values = MyPalette)