Muestreo calabacin

Muestreo 15 de dic en calabacín (Cucurbita pepo L.)

mode_function <- function(v) {
   uniqv <- unique(v)
   uniqv[which.max(tabulate(match(v, uniqv)))]
}

Análisis

Cultivo

Cobertura

cultivo %>%
  summarise(media = round(mean(`Cobertura (%)`),2),
            desv = round(sd(`Cobertura (%)`),2),
            vari = round(var(`Cobertura (%)`),2),
            coef = round((100* desv/media),2)) %>%
  datatable()

cultivo %>%
  ggplot(aes(x = 0, y = `Cobertura (%)`, color = "cyan")) +
  geom_boxplot()+
  theme(legend.position = 'none')+
  geom_violin(color = 'black', alpha = 0.3)+
  stat_summary(fun = mean, color = 'red')

Altura

cultivo %>%
  summarise(media = round(mean(`Altura (cm)`),2),
            desv = round(sd(`Altura (cm)`),2),
            vari = round(var(`Altura (cm)`),2),
            coef = round((100* desv/media),2)) %>%
  datatable()

cultivo %>%
  ggplot(aes(x = 0, y = `Altura (cm)`, color = "cyan")) +
  geom_boxplot()+
  theme(legend.position = 'none')+
  geom_violin(color = 'black', alpha = 0.3)+
  stat_summary(fun = mean, color = 'red')

Modas

cultivo %>%
  summarise(moda_fen = mode_function(BBCH),
            moda_fis = mode_function(FISIOLOGIA),
            moda_est = mode_function(`Establecimiento (%)`),
            moda_flM = mode_function(`No de flores masculinas`),
            moda_flF = mode_function(`No flores femeninas`),
            moda_fru = mode_function(`No de frutos`),
            moda_hojas = mode_function(`No de hojas`)
            )%>%
  datatable(rownames = FALSE,
          extensions = c('Buttons'),
          options = list(
            dom = 'Brftip',
            buttons = c('excel', 'pdf')))

Enfermedades

enfermedades %>%
  group_by(ENFERMEDAD) %>%
  summarise(moda_incidencia = mode_function(Incidencia),
            media_severidad = round(mean(`Severidad (%)`),2),
            desv_severidad = round(sd(`Severidad (%)`),2),
            var_severidad = round(var(`Severidad (%)`),2),
            coef_severidad = round((100 * desv_severidad/media_severidad),2)
            ) %>%
  datatable()

enfermedades %>%
  filter(ENFERMEDAD == 'Mildeo velloso') %>%
  ggplot(aes(x = 0,y = `Severidad (%)`))+
  geom_boxplot(color = 'cyan')+
  geom_violin(alpha = 0.3)+
  stat_summary(fun = mean, color = 'red')

## Warning: Removed 1 rows containing missing values (geom_segment).

Plagas

plagas %>%
  group_by(Plaga, Especie) %>%
  summarise(media = round(mean(`Densidad (Indiv/p. muest) Promedio`, na.rm = TRUE),2),
            desv = round(sd(`Densidad (Indiv/p. muest) Promedio`, na.rm = TRUE),2),
            vari = round(var(`Densidad (Indiv/p. muest) Promedio`, na.rm = TRUE),2),
            coef = round((100* desv/media), 2)
            )%>%
  datatable()

## `summarise()` has grouped output by 'Plaga'. You can override using the `.groups` argument.

plagas %>%
  filter(Plaga == 'Trips') %>%
  ggplot(aes(x = 0,y = `Densidad (Indiv/p. muest) Promedio`, color = Especie))+
  geom_boxplot()+
  geom_violin(alpha = 0.3)+
  stat_summary(fun = mean, color = 'red', cex = 0.3)+
  facet_wrap(~ Especie)+
  theme(legend.position = 'none')

plagas %>%
  filter(Plaga == 'Diptera') %>%
  ggplot(aes(x = 0,y = `Densidad (Indiv/p. muest) Promedio`))+
  geom_boxplot(color = 'gold')+
  geom_violin(alpha = 0.3)+
  stat_summary(fun = mean, color = 'red', cex = 0.3)+
  theme(legend.position = 'none')

Malezas

Cobertura

malezas %>%
  group_by(MALEZA) %>%
  summarise(media_co = round(mean(Cobertura, na.rm = TRUE), 2),
            desv_co = round(sd(Cobertura, na.rm = TRUE), 2),
            var_co = round(var(Cobertura, na.rm = TRUE), 2),
            coef_co = round((100*desv_co/media_co),2),
            media_indi = round(mean(`No individuos`, na.rm = TRUE), 2),
            desv_indi = round(sd(`No individuos`, na.rm = TRUE), 2),
            var_indi = round(var(`No individuos`, na.rm = TRUE), 2),
            coef_indi = round((100*desv_indi/media_indi),2),
            moda_etapa = mode_function(`Etapa Fenológica`)
            ) %>%
  datatable()

malezas %>%
  group_by(MALEZA) %>%
  ggplot(aes(x = 0, y = Cobertura, fill = MALEZA))+
  geom_boxplot()+
  geom_violin(alpha = 0.3)+
  stat_summary(fun = mean, color = 'red', cex = 0.3)+
  facet_wrap(~ MALEZA)+
  theme(legend.position = 'none')

malezas %>%
  group_by(MALEZA) %>%
  ggplot(aes(x = 0, y = `No individuos`, fill = MALEZA))+
  geom_boxplot()+
  geom_violin(alpha = 0.3)+
  stat_summary(fun = mean, color = 'red', cex = 0.3)+
  facet_wrap(~ MALEZA)+
  theme(legend.position = 'none')