diff --git a/r_app/CI_report_dashboard_planet.Rmd b/r_app/CI_report_dashboard_planet.Rmd
index 3e5812c..4d33263 100644
--- a/r_app/CI_report_dashboard_planet.Rmd
+++ b/r_app/CI_report_dashboard_planet.Rmd
@@ -343,7 +343,7 @@ ggplot(pred_ffs_rf, aes(y = predicted_Tcha, x = tonnage_ha)) +
        y = "Predicted tonnage/ha (Tcha)") +
   theme_minimal() 
 
-ggplot(pred_rf_current_season, aes(x = Age_days, y = predicted_Tcha, col = field)) +
+ggplot(pred_rf_current_season, aes(x = Age_days, y = predicted_Tcha)) +
   geom_point(size = 2, alpha = 0.6) +  # Adjust point size and transparency
   labs(title = "Predicted Yields for Fields Over 300 Days \nOld Yet to Be Harvested",
        x = "Age (days)", 
diff --git a/r_app/Rplots.pdf b/r_app/Rplots.pdf
index f098abe..7647a7c 100644
Binary files a/r_app/Rplots.pdf and b/r_app/Rplots.pdf differ
diff --git a/r_app/ci_extraction.R b/r_app/ci_extraction.R
index 9e63793..f1b4d26 100644
--- a/r_app/ci_extraction.R
+++ b/r_app/ci_extraction.R
@@ -48,11 +48,23 @@ raster_files <- list.files(planet_tif_folder,full.names = T, pattern = ".tif")
 filtered_files  <- map(dates$days_filter, ~ raster_files[grepl(pattern = .x, x = raster_files)]) %>%
   compact() %>%
   flatten_chr()
-head(filtered_files)
+
+  # Remove files that do not exist
+  existing_files <- filtered_files[file.exists(filtered_files)]
+
+  # Check if the list of existing files is empty
+  if (length(existing_files) == 0) {
+    message("No files exist for the given date(s).")
+    stop("Terminating script.")
+  }
+
+  # Continue with the rest of the script
+  print(existing_files)
+
 
 vrt_list <- list()
 
-for (file in filtered_files) {
+for (file in existing_files) {
   v_crop <- create_mask_and_crop(file, field_boundaries, merged_final)
   emtpy_or_full <- global(v_crop, "notNA")
 
@@ -109,7 +121,7 @@ if (!file.exists(file_path)) {
   extracted_values <- map(dates$days_filter, ~ extracted_values[grepl(pattern = .x, x = extracted_values)]) %>%
     compact() %>%
     flatten_chr()
-  
+
   pivot_stats <- extracted_values %>%
     map(readRDS) %>% list_rbind() %>%
     group_by(sub_field)