diff --git a/sits.Rproj b/sits.Rproj
index 16c4a9cba..c1d6889aa 100644
--- a/sits.Rproj
+++ b/sits.Rproj
@@ -1,5 +1,4 @@
 Version: 1.0
-ProjectId: 285a470e-fd26-4cdb-ae88-2e3d6112030d
 
 RestoreWorkspace: Default
 SaveWorkspace: Ask
diff --git a/tests/testthat/test-apply.R b/tests/testthat/test-apply.R
index 4c9436f30..6dd49a77f 100644
--- a/tests/testthat/test-apply.R
+++ b/tests/testthat/test-apply.R
@@ -88,18 +88,6 @@ test_that("Testing normalized index generation", {
     start_date <- timeline[1]
     end_date <- timeline[length(timeline)]
 
-    # test with data frame
-    #
-    gc_cube2 <- gc_cube
-    class(gc_cube2) <- "data.frame"
-
-    gc_cube2 <- sits_apply(gc_cube2,
-                              NDRE = (B8A - B05) / (B8A + B05),
-                              multicores = 1,
-                              output_dir = dir_images
-    )
-    expect_true("NDRE" %in% sits_bands(gc_cube2))
-
     csv_tb <- purrr::map2_dfr(lats, longs, function(lat, long) {
         tibble::tibble(
             longitude = long,
diff --git a/tests/testthat/test-bands.R b/tests/testthat/test-bands.R
index e58506a11..91ac69a94 100644
--- a/tests/testthat/test-bands.R
+++ b/tests/testthat/test-bands.R
@@ -17,8 +17,4 @@ test_that("band rename", {
     new_band <- sits_bands(sinop)
     expect_equal(new_band, "NDVI2")
 
-    sp <- sinop
-    class(sinop) <- "data.frame"
-    bands_cube <- sits_bands(sinop)
-    expect_equal(bands_cube, "NDVI2")
 })
diff --git a/tests/testthat/test-clustering.R b/tests/testthat/test-clustering.R
index e39b92964..29c674883 100644
--- a/tests/testthat/test-clustering.R
+++ b/tests/testthat/test-clustering.R
@@ -43,14 +43,4 @@ test_that("Creating a dendrogram and clustering the results", {
     expect_true(sits_cluster_frequency(clusters_new)[3, 1] >
         sits_cluster_frequency(clean)[3, 1])
 
-    # test default
-    samples_df <- cerrado_2classes
-    class(samples_df) <- "data.frame"
-    clusters_df <- suppressMessages(
-        sits_cluster_dendro(
-            samples_df,
-            bands = c("NDVI", "EVI")
-        )
-    )
-    expect_equal(nrow(clusters_df), 746)
 })
diff --git a/tests/testthat/test-cube-bdc.R b/tests/testthat/test-cube-bdc.R
index bc66e0f2c..86b52fa4c 100644
--- a/tests/testthat/test-cube-bdc.R
+++ b/tests/testthat/test-cube-bdc.R
@@ -105,29 +105,8 @@ test_that("Creating cubes from BDC - MOD13Q1-6.1 based on ROI using sf object",
     intersects <- .cube_intersects(modis_cube, sf_mt)
     expect_true(all(intersects))
 
-    modis_cube2 <- modis_cube
-    class(modis_cube2) <- "data.frame"
-    in2 <- .cube_intersects(modis_cube2, sf_mt)
-    expect_true(all(in2))
-    expect_true(.tile_intersects(modis_cube2[1,], sf_mt))
 
-    expect_false(.tile_within(modis_cube2[1,], sf_mt))
-    expect_false(.tile_within(modis_cube2[6,], sf_mt))
 
-    modis_cube3 <- .cube_filter_spatial(modis_cube2, sf_mt)
-    expect_equal(nrow(modis_cube2), nrow(modis_cube3))
-
-    modis_cube4 <- .cube_filter_bands(modis_cube2, "EVI")
-    expect_true(.cube_bands(modis_cube4) %in% .cube_bands(modis_cube2))
-    tile <- modis_cube2[1,]
-    modis_evi <- .tile_filter_bands(tile, "EVI")
-    expect_equal("EVI", sits_bands(modis_evi))
-
-    modis_tiles <- .cube_tiles(modis_cube2)
-    expect_true(all(c("011009", "012010") %in% .cube_tiles(modis_cube)))
-
-    tile_011009 <- .cube_filter_tiles(modis_cube, "011009")
-    expect_equal(nrow(tile_011009), 1)
 
 })
 test_that("Creating cubes from BDC - MOD13Q1-6.1 invalid roi", {
diff --git a/tests/testthat/test-cube-mpc.R b/tests/testthat/test-cube-mpc.R
index d2384d307..8a8f448d2 100644
--- a/tests/testthat/test-cube-mpc.R
+++ b/tests/testthat/test-cube-mpc.R
@@ -254,30 +254,6 @@ test_that("Creating cubes from MPC - MOD13Q1-6.1 based on ROI using sf object",
     intersects <- .cube_intersects(modis_cube, sf_mt)
     expect_true(all(intersects))
 
-    modis_cube2 <- modis_cube
-    class(modis_cube2) <- "data.frame"
-    in2 <- .cube_intersects(modis_cube2, sf_mt)
-    expect_true(all(in2))
-    expect_true(.tile_intersects(modis_cube2[1,], sf_mt))
-
-    expect_false(.tile_within(modis_cube2[1,], sf_mt))
-    expect_false(.tile_within(modis_cube2[6,], sf_mt))
-
-    modis_cube3 <- .cube_filter_spatial(modis_cube2, sf_mt)
-    expect_equal(nrow(modis_cube2), nrow(modis_cube3))
-
-    modis_cube4 <- .cube_filter_bands(modis_cube2, "EVI")
-    expect_true(.cube_bands(modis_cube4) %in% .cube_bands(modis_cube2))
-    tile <- modis_cube2[1,]
-    modis_evi <- .tile_filter_bands(tile, "EVI")
-    expect_equal("EVI", sits_bands(modis_evi))
-
-    modis_tiles <- .cube_tiles(modis_cube2)
-    expect_true(all(c("h13v10", "h13v9") %in% .cube_tiles(modis_cube)))
-
-    tile_h13v10 <- .cube_filter_tiles(modis_cube, "h13v10")
-    expect_equal(nrow(tile_h13v10), 1)
-
 })
 test_that("Creating cubes from MPC - MOD09A1-6.1 based on ROI using sf object", {
     shp_file <- system.file(
diff --git a/tests/testthat/test-mixture_model.R b/tests/testthat/test-mixture_model.R
index a02c47464..9b0132c63 100644
--- a/tests/testthat/test-mixture_model.R
+++ b/tests/testthat/test-mixture_model.R
@@ -82,7 +82,6 @@ test_that("Mixture model tests", {
     csv_file <- paste0(tempdir(), "/mmodel.csv")
 
     reg_cube3 <- reg_cube
-    class(reg_cube3) <- "data.frame"
     mm_rmse_csv <- sits_mixture_model(
         data = reg_cube3,
         endmembers = csv_file,
diff --git a/tests/testthat/test-raster.R b/tests/testthat/test-raster.R
index 95f3796dc..2137e1ff2 100644
--- a/tests/testthat/test-raster.R
+++ b/tests/testthat/test-raster.R
@@ -61,9 +61,6 @@ test_that("Classification with rfor (single core)", {
 
     # defaults and errors
     expect_error(sits_classify(probs_cube, rf_model))
-    sinop_df <- sinop
-    class(sinop_df) <- "data.frame"
-    expect_error(sits_classify(sinop_df, rfor_model, output_dir = tempdir()))
     expect_true(all(file.remove(unlist(sinop_probs$file_info[[1]]$path))))
 })
 test_that("Classification with SVM", {
@@ -446,94 +443,6 @@ test_that("Classification with post-processing", {
         dir.create(output_dir)
     }
 
-    sinop2c <- sits:::.cube_find_class(sinop)
-    expect_true("raster_cube" %in% class(sinop2c))
-    expect_true("eo_cube" %in% class(sinop2c))
-
-    sinop2 <- sinop
-    class(sinop2) <- "data.frame"
-    new_cube <- sits:::.cube_find_class(sinop2)
-    expect_true("raster_cube" %in% class(new_cube))
-    expect_true("eo_cube" %in% class(new_cube))
-
-    bands <- .cube_bands(sinop2)
-    expect_equal(bands, "NDVI")
-
-    path1 <- .tile_path(sinop2, date = "2013-09-14",
-                        band = "NDVI")
-    expect_true(grepl("jp2", path1))
-
-    expect_equal(.tile_source(sinop2), "BDC")
-    expect_equal(.tile_collection(sinop2), "MOD13Q1-6.1")
-    expect_equal(.tile_satellite(sinop2), "TERRA")
-    expect_equal(.tile_sensor(sinop2), "MODIS")
-    expect_equal(.tile_bands(sinop2), "NDVI")
-    expect_equal(.tile_ncols(sinop2), 255)
-    expect_equal(.tile_nrows(sinop2), 147)
-    expect_equal(.tile_size(sinop2)$ncols, 255)
-    expect_equal(.tile_size(sinop2)$nrows, 147)
-    expect_gt(.tile_xres(sinop2), 231)
-    expect_gt(.tile_yres(sinop2), 231)
-    expect_equal(as.Date(.tile_start_date(sinop2)), as.Date("2013-09-14"))
-    expect_equal(as.Date(.tile_end_date(sinop2)), as.Date("2014-08-29"))
-    expect_equal(.tile_fid(sinop), .tile_fid(sinop2))
-    expect_equal(.tile_crs(sinop), .tile_crs(sinop2))
-    expect_error(.tile_area_freq(sinop))
-    expect_equal(.tile_timeline(sinop), .tile_timeline(sinop2))
-    expect_true(.tile_is_complete(sinop2))
-    band_conf <- .tile_band_conf(sinop2, band = "NDVI")
-    expect_equal(band_conf$band_name, "NDVI")
-
-    expect_error(.cube_find_class(samples_modis_ndvi))
-
-    is_complete <- .cube_is_complete(sinop2)
-    expect_true(is_complete)
-
-    time_tb <- .cube_timeline_acquisition(sinop2, period = "P2M", origin = NULL)
-    expect_equal(nrow(time_tb), 6)
-    expect_equal(time_tb[[1,1]], as.Date("2013-09-14"))
-
-    bbox <- .cube_bbox(sinop2)
-    expect_equal(bbox[["xmin"]], -6073798)
-    bbox2 <- .tile_bbox(sinop2)
-    expect_equal(bbox2[["xmin"]], -6073798)
-
-    sf_obj <- .cube_as_sf(sinop2)
-    bbox3 <- sf::st_bbox(sf_obj)
-    expect_equal(bbox[["xmin"]], bbox3[["xmin"]])
-
-    sf_obj2 <- .tile_as_sf(sinop2)
-    bbox4 <- sf::st_bbox(sf_obj2)
-    expect_equal(bbox[["xmin"]], bbox4[["xmin"]])
-
-    expect_true(.cube_during(sinop2, "2014-01-01", "2014-04-01"))
-    expect_true(.tile_during(sinop2, "2014-01-01", "2014-04-01"))
-
-    t <- .cube_filter_interval(sinop2, "2014-01-01", "2014-04-01")
-    expect_equal(length(sits_timeline(t)), 3)
-
-    t1 <- .tile_filter_interval(sinop2, "2014-01-01", "2014-04-01")
-    expect_equal(length(sits_timeline(t1)), 3)
-
-    timeline <- sits_timeline(sinop2)
-    dates <- as.Date(c(timeline[1], timeline[3], timeline[5]))
-    t2 <- .cube_filter_dates(sinop2, dates)
-    expect_equal(.tile_timeline(t2), dates)
-
-    paths <- .cube_paths(sinop2)[[1]]
-    expect_equal(length(paths), 12)
-    expect_true(grepl("jp2", paths[12]))
-
-    expect_true(.cube_is_local(sinop2))
-
-    cube <- .cube_split_features(sinop2)
-    expect_equal(nrow(cube), 12)
-
-    cube <- .cube_split_assets(sinop2)
-    expect_equal(nrow(cube), 12)
-
-    expect_false(.cube_contains_cloud(sinop2))
-
     sinop_probs <- sits_classify(
         data = sinop,
         ml_model = rfor_model,
@@ -574,27 +483,6 @@ test_that("Classification with post-processing", {
     expect_true(max_lab == 4)
     expect_true(min_lab == 1)
 
-    # test access for data.frame objects
-    #
-    sinop4 <- sinop_class
-    class(sinop4) <- "data.frame"
-    new_cube4 <- .cube_find_class(sinop4)
-    expect_true("raster_cube" %in% class(new_cube4))
-    expect_true("derived_cube" %in% class(new_cube4))
-    expect_true("class_cube" %in% class(new_cube4))
-
-    labels <- .cube_labels(sinop4)
-    expect_true(all(c("Cerrado", "Forest", "Pasture","Soy_Corn") %in% labels))
-    labels <- .tile_labels(sinop4)
-    expect_true(all(c("Cerrado", "Forest", "Pasture","Soy_Corn") %in% labels))
-
-    labels <- sits_labels(sinop4)
-    expect_true(all(c("Cerrado", "Forest", "Pasture","Soy_Corn") %in% labels))
-
-    sits_labels(sinop4) <- c("Cerrado", "Floresta", "Pastagem","Soja_Milho")
-    labels <- sits_labels(sinop4)
-    expect_true("Cerrado" %in% labels)
-
     expect_equal(.tile_area_freq(sinop_class)[1,3],.tile_area_freq(sinop4)[1,3])
 
     expect_error(.tile_update_label(
@@ -602,45 +490,6 @@ test_that("Classification with post-processing", {
         c("Cerrado", "Floresta", "Pastagem","Soja_Milho")
     ))
 
-    class(sinop4) <- "data.frame"
-    col <- .cube_collection(sinop4)
-    expect_equal(col, "MOD13Q1-6.1")
-
-    col <- .tile_collection(sinop4)
-    expect_equal(col, "MOD13Q1-6.1")
-
-    crs <- .cube_crs(sinop4)
-    expect_true(grepl("Sinusoidal", crs))
-    expect_true(grepl("Sinusoidal", .tile_crs(sinop4)))
-
-    class <- .cube_s3class(sinop4)
-    expect_true("raster_cube" %in% class)
-    expect_true("derived_cube" %in% class)
-    expect_true("class_cube" %in% class)
-
-    expect_equal(.cube_ncols(sinop4), 255)
-    expect_equal(.tile_ncols(sinop4), 255)
-    expect_equal(.cube_nrows(sinop4), 147)
-    expect_equal(.tile_nrows(sinop4), 147)
-    expect_equal(.cube_source(sinop4), "BDC")
-    expect_equal(.tile_source(sinop4), "BDC")
-    expect_equal(.cube_collection(sinop4), "MOD13Q1-6.1")
-    expect_equal(.tile_collection(sinop4), "MOD13Q1-6.1")
-
-    sd <- .cube_start_date(sinop4)
-    expect_equal(sd, as.Date("2013-09-14"))
-
-    ed <- .cube_end_date(sinop4)
-    expect_equal(ed, as.Date("2014-08-29"))
-
-    timeline <- .cube_timeline(sinop4)[[1]]
-    expect_equal(timeline[1], sd)
-    expect_equal(timeline[2], ed)
-
-    size <- .tile_size(sinop4)
-    expect_equal(size$nrows, 147)
-    expect_true(.tile_is_complete(sinop4))
-
     # Save QML file
     qml_file <- paste0(tempdir(),"/myfile.qml")
     sits_colors_qgis(sinop_class, qml_file)
@@ -711,13 +560,6 @@ test_that("Classification with post-processing", {
     max_unc <- max(.raster_get_values(r_unc))
     expect_true(max_unc <= 10000)
 
-    sinop5 <- sinop_uncert
-    class(sinop5) <- "data.frame"
-    new_cube5 <- .cube_find_class(sinop5)
-    expect_true("raster_cube" %in% class(new_cube5))
-    expect_true("derived_cube" %in% class(new_cube5))
-    expect_true("uncert_cube" %in% class(new_cube5))
-
 
     timeline_orig <- sits_timeline(sinop)
     timeline_probs <- sits_timeline(sinop_probs)
@@ -734,12 +576,6 @@ test_that("Classification with post-processing", {
     expect_equal(timeline_orig[length(timeline_orig)], timeline_class[2])
 
 
-    sinop6 <- sinop_probs
-    class(sinop6) <- "data.frame"
-
-    sinop_bayes_3 <- sits_smooth(sinop6, output_dir = tempdir())
-    expect_equal(sits_bands(sinop_bayes_3), "bayes")
-
     expect_error(sits_smooth(sinop, output_dir = tempdir()))
     expect_error(sits_smooth(sinop_class, output_dir = tempdir()))
     expect_error(sits_smooth(sinop_uncert, output_dir = tempdir()))
@@ -817,21 +653,6 @@ test_that("Clean classification",{
         sits_clean(cube = sinop_probs,
                    output_dir = output_dir)
     )
-    sp <- sinop_class
-    class(sp) <- "data.frame"
-
-    clean_cube2 <- sits_clean(
-        cube = sp,
-        output_dir = output_dir,
-        version = "v2",
-        progress = FALSE
-    )
-    sum_clean2 <- summary(clean_cube2)
-
-    expect_equal(nrow(sum_orig), nrow(sum_clean2))
-    expect_equal(sum(sum_orig$count), sum(sum_clean2$count))
-    expect_lt(sum_orig[2,4], sum_clean2[2,4])
-
 })
 test_that("Clean classification with class cube from STAC",{
     cube_roi <- c("lon_min" = -62.7,  "lon_max" = -62.5,
diff --git a/tests/testthat/test-regularize.R b/tests/testthat/test-regularize.R
index 065f20d10..d7616ca43 100644
--- a/tests/testthat/test-regularize.R
+++ b/tests/testthat/test-regularize.R
@@ -47,31 +47,13 @@ test_that("Regularizing cubes from AWS, and extracting samples from them", {
     expect_equal(.tile_ncols(rg_cube), 458)
     expect_equal(tile_bbox$xmax, 309780, tolerance = 1e-1)
     expect_equal(tile_bbox$xmin, 199980, tolerance = 1e-1)
-
     tile_fileinfo <- .fi(rg_cube)
-
     expect_equal(nrow(tile_fileinfo), 2)
 
-    # Checking input class
-    s2_cube <- s2_cube_open
-    class(s2_cube) <- "data.frame"
-    expect_error(
-        sits_regularize(
-            cube = s2_cube,
-            output_dir = dir_images,
-            res = 240,
-            period = "P16D",
-            multicores = 2,
-            progress = FALSE
-        )
-    )
-
     # Retrieving data
-
     csv_file <- system.file("extdata/samples/samples_amazonia.csv",
         package = "sits"
     )
-
     # read sample information from CSV file and put it in a tibble
     samples <- tibble::as_tibble(utils::read.csv(csv_file))
 
diff --git a/tests/testthat/test-tibble.R b/tests/testthat/test-tibble.R
index e2a0d6840..6eac64340 100644
--- a/tests/testthat/test-tibble.R
+++ b/tests/testthat/test-tibble.R
@@ -26,12 +26,6 @@ test_that("Apply", {
         tolerance = 0.1
     )
 })
-test_that("Data frame",{
-    point_df <- point_mt_6bands
-    class(point_df) <- "data.frame"
-    point_df_ndvi <- sits_select(point_df, bands = "NDVI")
-    expect_equal(sits_bands(point_df_ndvi), "NDVI")
-})
 test_that("Bands", {
     bands <- sits_bands(samples_modis_ndvi)
 
diff --git a/tests/testthat/test-variance.R b/tests/testthat/test-variance.R
index 8dc5e589d..cf4e77c0e 100644
--- a/tests/testthat/test-variance.R
+++ b/tests/testthat/test-variance.R
@@ -23,19 +23,9 @@ test_that("Variance cube", {
     # check is variance cube
     .check_is_variance_cube(var_cube)
 
-    varc <- var_cube
-    class(varc) <- "data.frame"
-    new_cube <- .cube_find_class(varc)
-    expect_true("raster_cube" %in% class(new_cube))
-    expect_true("derived_cube" %in% class(new_cube))
-    expect_true("variance_cube" %in% class(new_cube))
-
-
     r_obj <- .raster_open_rast(var_cube$file_info[[1]]$path[[1]])
-
     max_lyr1 <- max(.raster_get_values(r_obj)[, 1], na.rm = TRUE)
     expect_true(max_lyr1 <= 4000)
-
     max_lyr3 <- max(.raster_get_values(r_obj)[, 3], na.rm = TRUE)
     expect_true(max_lyr3 <= 4000)
 
@@ -54,24 +44,7 @@ test_that("Variance cube", {
     )
     expect_error(sits_variance(class_cube, output_dir = tempdir()))
 
-    probs_df <- probs_cube
-    class(probs_df) <- "data.frame"
-    # test reading cube as data frame
-    df_var <- sits_variance(
-        cube = probs_df,
-        output_dir = tempdir(),
-        version = "vardf"
-    )
-    r_obj <- .raster_open_rast(df_var$file_info[[1]]$path[[1]])
-
-    max_lyr1 <- max(.raster_get_values(r_obj)[, 1], na.rm = TRUE)
-    expect_true(max_lyr1 <= 4000)
-
-    max_lyr3 <- max(.raster_get_values(r_obj)[, 3], na.rm = TRUE)
-    expect_true(max_lyr3 <= 4000)
-
     expect_true(all(file.remove(unlist(probs_cube$file_info[[1]]$path))))
-    expect_true(all(file.remove(unlist(df_var$file_info[[1]]$path))))
     expect_true(all(file.remove(unlist(var_cube$file_info[[1]]$path))))
     expect_true(all(file.remove(unlist(class_cube$file_info[[1]]$path))))
 })