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juanchiem/yield_resp_barley.R

Last active October 19, 2022 01:36
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yield_resp_barley.R
library(tidyverse)
dat <- tibble::tribble(
~precio_cereal, ~gasto_comer, ~ingreso_neto, ~`kg/$`, ~producto, ~costo_dosis, ~mosquito, ~costo_apli, ~rinde_obj, ~`pisada_%`, ~pisada_kg, ~costo_trat_kg, ~costo_tot_kg,
310L, 20L, 248, 4.03, "MD", 22L, 8.5, 30.5, 2500L, 2.5, 62.5, 123L, 185L,
310L, 20L, 248, 4.03, "MD", 22L, 8.5, 30.5, 3000L, 2.5, 75, 123L, 198L,
310L, 20L, 248, 4.03, "MD", 22L, 8.5, 30.5, 3500L, 2.5, 87.5, 123L, 210L,
310L, 20L, 248, 4.03, "MD", 22L, 8.5, 30.5, 4000L, 2.5, 100, 123L, 223L,
320L, 20L, 256, 3.91, "MD", 22L, 8.5, 30.5, 2500L, 2.5, 62.5, 119L, 182L,
320L, 20L, 256, 3.91, "MD", 22L, 8.5, 30.5, 3000L, 2.5, 75, 119L, 194L,
320L, 20L, 256, 3.91, "MD", 22L, 8.5, 30.5, 3500L, 2.5, 87.5, 119L, 207L,
320L, 20L, 256, 3.91, "MD", 22L, 8.5, 30.5, 4000L, 2.5, 100, 119L, 219L,
330L, 20L, 264, 3.79, "MD", 22L, 8.5, 30.5, 2500L, 2.5, 62.5, 116L, 178L,
330L, 20L, 264, 3.79, "MD", 22L, 8.5, 30.5, 3000L, 2.5, 75, 116L, 191L,
330L, 20L, 264, 3.79, "MD", 22L, 8.5, 30.5, 3500L, 2.5, 87.5, 116L, 203L,
330L, 20L, 264, 3.79, "MD", 22L, 8.5, 30.5, 4000L, 2.5, 100, 116L, 216L,
310L, 20L, 248, 4.03, "MT", 37L, 8.5, 45.5, 2500L, 2.5, 62.5, 183L, 246L,
310L, 20L, 248, 4.03, "MT", 37L, 8.5, 45.5, 3000L, 2.5, 75, 183L, 258L,
310L, 20L, 248, 4.03, "MT", 37L, 8.5, 45.5, 3500L, 2.5, 87.5, 183L, 271L,
310L, 20L, 248, 4.03, "MT", 37L, 8.5, 45.5, 4000L, 2.5, 100, 183L, 283L,
320L, 20L, 256, 3.91, "MT", 37L, 8.5, 45.5, 2500L, 2.5, 62.5, 178L, 240L,
320L, 20L, 256, 3.91, "MT", 37L, 8.5, 45.5, 3000L, 2.5, 75, 178L, 253L,
320L, 20L, 256, 3.91, "MT", 37L, 8.5, 45.5, 3500L, 2.5, 87.5, 178L, 265L,
320L, 20L, 256, 3.91, "MT", 37L, 8.5, 45.5, 4000L, 2.5, 100, 178L, 278L,
330L, 20L, 264, 3.79, "MT", 37L, 8.5, 45.5, 2500L, 2.5, 62.5, 172L, 235L,
330L, 20L, 264, 3.79, "MT", 37L, 8.5, 45.5, 3000L, 2.5, 75, 172L, 247L,
330L, 20L, 264, 3.79, "MT", 37L, 8.5, 45.5, 3500L, 2.5, 87.5, 172L, 260L,
330L, 20L, 264, 3.79, "MT", 37L, 8.5, 45.5, 4000L, 2.5, 100, 172L, 272L
) %>%
janitor::clean_names()
p <- dat %>% #names
ggplot()+
aes(x=precio_cereal, y=costo_tot_kg, col=factor(rinde_obj))+
geom_point()+
geom_line()+
facet_wrap("producto")+
labs(col="Rinde objetivo (kg/ha)",
x = "Precio cereal - enero '23 (US$/Ton)",
y = "Costo tratamiento (kg/ha)",
caption =
"Pisada: 2.5%
Gastos de comercialización: 20%
MD-Mecla doble triazol + estrobi: 22 US$/dosis
MT-Mecla triple triazol + estrobi + carboxa: 37 US$/dosis") +
theme(legend.position = "top", legend.direction = "horizontal")
p
dat %>%
pivot_longer(cols = c(pisada_kg, costo_trat_kg)) %>%
ggplot()+
aes(x = precio_cereal, y = value, fill = name, label = value) +
geom_bar(stat = "identity") +
geom_text(size = 3, position = position_stack(vjust = 0.5))+
facet_grid(producto ~ rinde_obj)+
labs(fill="Componentes costo",
x = "Precio cereal - enero '23 (US$/Ton)",
y = "Costo total tratamiento (kg/ha)",
caption =
"Pisada: 2.5%
Gastos de comercialización: 20%
MD-Mecla doble triazol + estrobi: 22 US$/dosis
MT-Mecla triple triazol + estrobi + carboxa: 37 US$/dosis") +
theme(legend.position = "top", legend.direction = "horizontal")
dat_resp <- tibble::tribble(
~`resp%`, ~rinde_obj, ~resp_abs,
2L, 2500L, 50L,
2L, 3000L, 60L,
2L, 3500L, 70L,
2L, 4000L, 80L,
4L, 2500L, 100L,
4L, 3000L, 120L,
4L, 3500L, 140L,
4L, 4000L, 160L,
6L, 2500L, 150L,
6L, 3000L, 180L,
6L, 3500L, 210L,
6L, 4000L, 240L,
8L, 2500L, 200L,
8L, 3000L, 240L,
8L, 3500L, 280L,
8L, 4000L, 320L
)%>%
janitor::clean_names()
dat_resp %>%
ggplot()+
aes(rinde_obj, resp_abs, col= factor(resp_percent))+
geom_point()+
geom_line()+
labs(
col="Cebada - Respuesta rinde (%)",
x = "Rinde objetivo (kg/ha)",
y = "Respuesta absoluta (kg/ha)",
caption = "Datos de ensayos no publicados.
Respuesta a fungicidas con baja presion de enfermedades en HB-1 y HB-2
Campañas 2018 a 2021") +
theme(legend.position = "top", legend.direction = "horizontal")
@juanchiem
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juanchiem commented Oct 18, 2022 •
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