plot_B <- d_1 %>%

filter(Genotype == "LM19", tr=="32C38C") %>%

arrange(tr) %>%

ggplot(aes(x = Tleaf,

y = ETR,

group = interaction(Genotype, PotSizeumber),

shape = tr,

linetype = tr)) +

geom_point(size = 1.5) +

geom_smooth(method = "lm", formula = y ~ poly(x, 3), se = FALSE,

colour = 'black', linewidth = 0.6) +

facet_wrap(vars(Genotype)) +

stat_poly_eq(method = "lm",

formula = y ~ poly(x, 3),

aes(label = paste(stat(eq.label), stat(adj.rr.label), sep = "~~~~")),

parse = TRUE)

Hello everyone! I've been working on a script to plot individual curves for each replicate (PotSizeumber) using `geom_smooth`

. I intentionally used a 3rd degree polynomial regression to fit the curves. However, when I tried to extract the curve equations using `stat_poly_eq`

, I noticed that the equations provided by `stat_poly_eq`

are not matching with the curves from `geom_smooth`

. I'm wondering if anyone has any insights or ideas as to why this might be happening. Thank you in advance for your help.