diff --git a/tutorials/R/AOP/Hyperspectral/Work-With-Hyperspectral-Data-In-R/Work-With-Hyperspectral-Data-In-R.html b/tutorials/R/AOP/Hyperspectral/Work-With-Hyperspectral-Data-In-R/Work-With-Hyperspectral-Data-In-R.html
index 08587a07..3103f67e 100644
--- a/tutorials/R/AOP/Hyperspectral/Work-With-Hyperspectral-Data-In-R/Work-With-Hyperspectral-Data-In-R.html
+++ b/tutorials/R/AOP/Hyperspectral/Work-With-Hyperspectral-Data-In-R/Work-With-Hyperspectral-Data-In-R.html
@@ -121,7 +121,7 @@ <h2 id="about-hyperspectral-remote-sensing-data">About Hyperspectral Remote Sens
 <p>The HDF5 data model natively compresses data stored within it (makes it smaller) and supports data slicing (extracting only the portions of the data that you need to work with rather than reading the entire dataset into memory). These features make it ideal for working with large data cubes such as those generated by imaging spectrometers, in addition to supporting spatial data and associated metadata.</p>
 <p>In this tutorial we will demonstrate how to read and extract spatial raster data stored within an HDF5 file using R.</p>
 <h2 id="read-hdf5-data-into-r">Read HDF5 data into R</h2>
-<p>We will use the <code>raster</code> and <code>rhdf5</code> packages to read in the HDF5 file that contains hyperspectral data for the
+<p>We will use the <code>terra</code> and <code>rhdf5</code> packages to read in the HDF5 file that contains hyperspectral data for the
 <a href="https://www.neonscience.org/field-sites/SJER" target="_blank">NEON San Joaquin (SJER) field site</a>.
 Let’s start by calling the needed packages and reading in our NEON HDF5 file.</p>
 <p>Please be sure that you have <em>at least</em> version 2.10 of <code>rhdf5</code> installed. Use: