diff --git a/DataExplore.r b/DataExplore.r
index 01cfb98..a8b5fe7 100644
--- a/DataExplore.r
+++ b/DataExplore.r
@@ -35,6 +35,7 @@ c("/depot/smarterag/data/HSI/Master files/Hyperspectral_data_AAPF_experiment_374
 "/depot/smarterag/data/HSI/Master files/Hyperspectral_data_AAPF_experiment_401.xlsx")
 
 path.rgb.long <- ("./df_rgb_long.csv")
+path.hsi.long <- ("./df_hsi_long.csv")
 
 
 
@@ -49,14 +50,15 @@ path.rgb.long <- ("./df_rgb_long.csv")
 #    (e.g., a handful of measurements in an enough time period).
 # 3. Review this list and decide which measurements you want 
 #    to exclude from your analysis.
-# 4. Look for a variable named df.unwanted below. 
+# 4. Look for a variable named df.unwanted.{rgb|hsi} below. 
 #    This variable is a list where you can specify the unwanted 
 #    measurements you identified in step 3.
-# 5. Fill in the list under df.unwanted with the attributes of the 
-#    measurements you want to exclude. The number of items in the list will 
-#    depend on your specific experiment and the output from DataExplore.r.
+# 5. Fill in the list under df.unwanted.{rgb|hsi} with the attributes 
+#    of the measurements you want to exclude. The number of items in 
+#    the list will depend on your specific experiment and the output 
+#    from DataExplore.r.
 # 
-# Unwanted data example:
+# Unwanted data example (RGB):
 #----------------------------------------------------------
 # EXP ID  TREATMENT DFP   SCAN_DATETIME_BY15MIN  NUM_SCANS
 #----------------------------------------------------------
@@ -77,7 +79,14 @@ path.rgb.long <- ("./df_rgb_long.csv")
 # 5
 # 396     20-1       55   2024-04-29 12:00:00    1
 #----------------------------------------------------------
-df.unwanted <- data.frame(
+# Unwanted data example(HSI):
+#----------------------------------------------------------
+# EXP ID  TREATMENT DFP   SCAN_DATETIME_BY30MIN  NUM_SCANS
+#----------------------------------------------------------
+# 1
+# 390     20-1       45   2024-03-08 10:30:00    4
+#----------------------------------------------------------
+df.unwanted.rgb <- data.frame(
     EXP_ID=c(374, 374, 374, 374, 396),
     TREATMENT=c("20 -1", "50-3", "50-3", "50-4", "20-1"),
     SCAN_DATETIME_BY15MIN=c("2023-10-30 11:15:00", 
@@ -86,6 +95,12 @@ df.unwanted <- data.frame(
                             "2023-09-28 09:45:00", 
                             "2024-04-29 12:00:00"),
     stringsAsFactors=FALSE)
+df.unwanted.hsi <- data.frame(
+    EXP_ID=c(390),
+    TREATMENT=c("20-1"),
+    SCAN_DATETIME_BY30MIN=c("2024-03-08 10:30:00"),
+    stringsAsFactors=FALSE)
+
 
 
 # List descriptive treatment info
@@ -189,11 +204,16 @@ id.vars <- c("EXP ID", "POT_BARCODE", "SCAN_TIME", "SCAN_DATE",
 # Columns not exported
 drops.col.rgb <- c("SCAN_TIME", "SCAN_DATE", 
                    "SCAN_DATETIME", "SCAN_DATETIME_BY15MIN")
+drops.col.hsi <- c("SCAN_TIME", "SCAN_DATE", 
+                   "SCAN_DATETIME", "SCAN_DATETIME_BY30MIN")
 
 # Order of columns for exported dataframe
 rgb.col.order <- c("EXP ID", "POT_BARCODE", "TREATMENT", "VARIETY", 
                    "DFP", "GROWTH_STAGE", "View", "frame_nr", 
                    "variable", "value")
+hsi.col.order <- c("EXP ID", "POT_BARCODE", "TREATMENT", "VARIETY", 
+                   "DFP", "GROWTH_STAGE", "View", "frame_nr", 
+                   "variable", "value")
 
 # Columns used as factors
 col.factor <- c("EXP ID", "VARIETY", "TREATMENT", 
@@ -202,6 +222,12 @@ col.factor <- c("EXP ID", "VARIETY", "TREATMENT",
 
 
 
+
+
+
+
+
+
 # Create empty rgb dataframe
 mat <- matrix(ncol=0, nrow=0) 
 df.rgb <- data.frame(mat) 
@@ -260,6 +286,110 @@ message('Succeeded importing RGB data...')
 
 
 
+# Overview 1: Show summary of rgb data
+df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
+message('\nRGB Data Acquisiton Summary (Overview 1)\n')
+print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP))
+
+
+
+
+
+# Overview 2: Round down scan date and time down to nearest 15 minute and display
+format <- "%Y-%m-%d %H:%M:%S"
+df.rgb.perscan["SCAN_DATETIME"] = 
+    as.POSIXct(paste(as.Date(df.rgb.perscan$SCAN_DATE), df.rgb.perscan$SCAN_TIME), 
+               format=format)
+df.rgb.perscan["SCAN_DATETIME_BY15MIN"] = 
+    lubridate::round_date(df.rgb.perscan$SCAN_DATETIME, "15 minutes")
+message('\nRGB Data Acquisiton Summary by Date and Time (Overview 2)\n')
+print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP, SCAN_DATETIME_BY15MIN))
+message('\nPlease check [`EXP ID`, TREATMENT, SCAN_DATETIME_BY15MIN]')
+message('to exclude data from incomplete scan session...')
+message('Check df.unwanted.rgb in DataExplore.r to exclude such records...\n')
+
+
+
+
+
+# Overview 3: Drop unwanted rgb data
+df.rgb["SCAN_DATETIME"] = 
+    as.POSIXct(paste(as.Date(df.rgb$SCAN_DATE), df.rgb$SCAN_TIME), format=format)
+df.rgb["SCAN_DATETIME_BY15MIN"] = 
+    lubridate::round_date(df.rgb$SCAN_DATETIME, "15 minutes")
+for(i in 1:nrow(df.unwanted.rgb)){
+    row <- df.unwanted.rgb[i,]
+    df.rgb <- df.rgb %>% filter(!(`EXP ID`  == row$EXP_ID &
+                                  TREATMENT == row$TREATMENT &
+                                  SCAN_DATETIME_BY15MIN == row$SCAN_DATETIME_BY15MIN))
+}
+df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
+message('\nRGB Data Acquisiton Summary (Unwanted Data Filtered, Overview 3)\n')
+print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP))
+
+
+
+
+
+# Overview 4: Convert treatment attributes
+for(i in 1:nrow(df.convert.treatment)){
+    row <- df.convert.treatment[i,]
+    df.rgb$TREATMENT[df.rgb$TREATMENT==row$from] <- row$to
+}
+df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
+message('\nRGB Data Acquisiton Summary (Treatment Updated, Overview 4)\n')
+print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP))
+
+
+
+
+
+# Overview 5: DFP is always smaller than 365 (to prevent case with wrong year input)
+df.rgb$DFP = df.rgb$DFP %% 365
+df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
+message('\nRGB Data Acquisiton Summary (DFP Always Less Than 365, Overview 5)\n')
+print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP))
+
+
+
+
+
+# Overview 6: Add growth stage attribute
+df.rgb$GROWTH_STAGE <- NA
+for(i in 1:nrow(df.growth.stage)){
+    row <- df.growth.stage[i,]
+    df.rgb$GROWTH_STAGE[(df.rgb$`EXP ID` == row$EXP_ID) & 
+                        (df.rgb$TREATMENT == row$TREATMENT) &
+                        (df.rgb$DFP == row$DFP)] <- row$GROWTH_STAGE
+}
+df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
+message('\nRGB Data Acquisiton Summary (Growth Stage Added, Overview 6)\n')
+print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP, GROWTH_STAGE))
+
+
+
+
+
+# Drop unused columns
+df.rgb <- df.rgb[ , !(names(df.rgb) %in% drops.col.rgb)]
+
+# Change column order
+df.rgb <- df.rgb[, rgb.col.order]
+df.rgb[col.factor] <- lapply(df.rgb[col.factor], factor)
+
+# Export rgb dataframe
+message('\nExporting rgb dataframe (long format)...')
+write.csv(df.rgb, path.rgb.long, row.names=F)
+
+
+
+
+
+
+
+
+
+
 # Create empty hsi dataframe
 mat <- matrix(ncol=0, nrow=0) 
 df.hsi <- data.frame(mat) 
@@ -309,105 +439,108 @@ message('Succeeded importing HSI data...')
 
 
 
+# Overview 1: Show summary of rgb data
+df.hsi.perscan <- df.hsi[which(df.hsi$View=="Top" & df.hsi$variable=="NDVI_mean"), ]
+message('\nHSI Data Acquisiton Summary (Overview 1)\n')
+print(count(df.hsi.perscan, `EXP ID`, TREATMENT, DFP))
 
 
 
-# Get unique rgb measurement 
-df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
 
-# Show summary of rgb data
-message('\nRGB Data Acquisiton Summary (Overview 1)\n')
-print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP))
 
-# Round down scan date and time down to nearest 15 minute and display
+# Overview 2: Round down scan date and time down to nearest 15 minute and display
 format <- "%Y-%m-%d %H:%M:%S"
-df.rgb.perscan["SCAN_DATETIME"] = 
-    as.POSIXct(paste(as.Date(df.rgb.perscan$SCAN_DATE), df.rgb.perscan$SCAN_TIME), 
+df.hsi.perscan["SCAN_DATETIME"] = 
+    as.POSIXct(paste(as.Date(df.hsi.perscan$SCAN_DATE), df.hsi.perscan$SCAN_TIME), 
                format=format)
-df.rgb.perscan["SCAN_DATETIME_BY15MIN"] = 
-    lubridate::round_date(df.rgb.perscan$SCAN_DATETIME, "15 minutes")
-message('\nRGB Data Acquisiton Summary by Date and Time (Overview 2)\n')
-print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP, SCAN_DATETIME_BY15MIN))
-message('\nPlease check [`EXP ID`, TREATMENT, SCAN_DATETIME_BY15MIN]')
+df.hsi.perscan["SCAN_DATETIME_BY30MIN"] = 
+    lubridate::round_date(df.hsi.perscan$SCAN_DATETIME, "30 minutes")
+message('\nHSI Data Acquisiton Summary by Date and Time (Overview 2)\n')
+print(count(df.hsi.perscan, `EXP ID`, TREATMENT, DFP, SCAN_DATETIME_BY30MIN))
+message('\nPlease check [`EXP ID`, TREATMENT, SCAN_DATETIME_BY30MIN]')
 message('to exclude data from incomplete scan session...')
-message('Check df.unwanted in DataExplore.r to exclude such records...\n')
+message('Check df.unwanted.hsi in DataExplore.r to exclude such records...\n')
 
 
 
 
-# Drop unwanted rgb data
-df.rgb["SCAN_DATETIME"] = 
-    as.POSIXct(paste(as.Date(df.rgb$SCAN_DATE), df.rgb$SCAN_TIME), format=format)
-df.rgb["SCAN_DATETIME_BY15MIN"] = 
-    lubridate::round_date(df.rgb$SCAN_DATETIME, "15 minutes")
-for(i in 1:nrow(df.unwanted)){
-    row <- df.unwanted[i,]
-    df.rgb <- df.rgb %>% filter(!(`EXP ID`  == row$EXP_ID &
+
+# Overview 3: Drop unwanted hsi data
+df.hsi["SCAN_DATETIME"] = 
+    as.POSIXct(paste(as.Date(df.hsi$SCAN_DATE), df.hsi$SCAN_TIME), format=format)
+df.hsi["SCAN_DATETIME_BY15MIN"] = 
+    lubridate::round_date(df.hsi$SCAN_DATETIME, "30 minutes")
+for(i in 1:nrow(df.unwanted.hsi)){
+    row <- df.unwanted.hsi[i,]
+    df.hsi <- df.hsi %>% filter(!(`EXP ID`  == row$EXP_ID &
                                   TREATMENT == row$TREATMENT &
-                                  SCAN_DATETIME_BY15MIN == row$SCAN_DATETIME_BY15MIN))
+                                  SCAN_DATETIME_BY15MIN == row$SCAN_DATETIME_BY30MIN))
 }
-df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
-message('\nRGB Data Acquisiton Summary (Unwanted Data Filtered, Overview 3)\n')
-print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP))
+df.hsi.perscan <- df.hsi[which(df.hsi$View=="Top" & df.hsi$variable=="NDVI_mean"), ]
+message('\nHSI Data Acquisiton Summary (Unwanted Data Filtered, Overview 3)\n')
+print(count(df.hsi.perscan, `EXP ID`, TREATMENT, DFP))
 
 
 
 
 
-# Convert treatment attributes
+# Overview 4: Convert treatment attributes
 for(i in 1:nrow(df.convert.treatment)){
     row <- df.convert.treatment[i,]
-    df.rgb$TREATMENT[df.rgb$TREATMENT==row$from] <- row$to
+    df.hsi$TREATMENT[df.hsi$TREATMENT==row$from] <- row$to
 }
-df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
-message('\nRGB Data Acquisiton Summary (Treatment Updated, Overview 4)\n')
-print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP))
+df.hsi.perscan <- df.hsi[which(df.hsi$View=="Top" & df.hsi$variable=="NDVI_mean"), ]
+message('\nHSI Data Acquisiton Summary (Treatment Updated, Overview 4)\n')
+print(count(df.hsi.perscan, `EXP ID`, TREATMENT, DFP))
 
 
 
 
 
-# DFP is always smaller than 365 (to prevent case with wrong year input)
-df.rgb$DFP = df.rgb$DFP %% 365
-df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
-message('\nRGB Data Acquisiton Summary (DFP Always Less Than 365, Overview 5)\n')
-print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP))
+# Overview 5: DFP is always smaller than 365 (to prevent case with wrong year input)
+df.hsi$DFP = df.hsi$DFP %% 365
+df.hsi.perscan <- df.hsi[which(df.hsi$View=="Top" & df.hsi$variable=="NDVI_mean"), ]
+message('\nHSI Data Acquisiton Summary (DFP Always Less Than 365, Overview 5)\n')
+print(count(df.hsi.perscan, `EXP ID`, TREATMENT, DFP))
 
 
 
 
 
-# Add growth stage attribute
-df.rgb$GROWTH_STAGE <- NA
+# Overview 6: Add growth stage attribute
+df.hsi$GROWTH_STAGE <- NA
 for(i in 1:nrow(df.growth.stage)){
     row <- df.growth.stage[i,]
-    df.rgb$GROWTH_STAGE[(df.rgb$`EXP ID` == row$EXP_ID) & 
-                        (df.rgb$TREATMENT == row$TREATMENT) &
-                        (df.rgb$DFP == row$DFP)] <- row$GROWTH_STAGE
+    df.hsi$GROWTH_STAGE[(df.hsi$`EXP ID` == row$EXP_ID) & 
+                        (df.hsi$TREATMENT == row$TREATMENT) &
+                        (df.hsi$DFP == row$DFP)] <- row$GROWTH_STAGE
 }
-df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
-message('\nRGB Data Acquisiton Summary (Growth Stage Added, Overview 6)\n')
-print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP, GROWTH_STAGE))
+df.hsi.perscan <- df.hsi[which(df.hsi$View=="Top" & df.hsi$variable=="NDVI_mean"), ]
+message('\nHSI Data Acquisiton Summary (Growth Stage Added, Overview 6)\n')
+print(count(df.hsi.perscan, `EXP ID`, TREATMENT, DFP, GROWTH_STAGE))
 
 
 
 
 
 # Drop unused columns
-df.rgb <- df.rgb[ , !(names(df.rgb) %in% drops.col.rgb)]
+df.hsi <- df.hsi[ , !(names(df.hsi) %in% drops.col.hsi)]
 
 # Change column order
-df.rgb <- df.rgb[, rgb.col.order]
-df.rgb[col.factor] <- lapply(df.rgb[col.factor], factor)
+df.hsi <- df.hsi[, hsi.col.order]
+df.hsi[col.factor] <- lapply(df.hsi[col.factor], factor)
+
+# Export hsi dataframe
+message('\nExporting hsi dataframe (long format)...')
+write.csv(df.hsi, path.hsi.long, row.names=F)
+
+
+
 
-# Export dataframe
-message('\nExporting rgb dataframe (long format)...')
-write.csv(df.rgb, path.rgb.long, row.names=F)
 
 
 
 
-# Repeat for df.hsi
 # Combine rgb and hsi data using df <- rbind(df.rgb, df.hsi)