REFLECTANCE SPECTROPHOTOMETRY AND COLORIMETRY

Color is one of the key factors used for identification of rocks and minerals. The development of a handheld spectrophotometer that can quickly produce a detailed spectrum from the surface of a rock or sediment has given scientists a semiquantitative method of determining composition. The spectrophotometer allows higher density, noninvasive analyses that can identify changes in composition and cyclical changes and can help pinpoint where the beginning of the changes occurred. These types of data helped with core-to-core and hole-to-hole correlations. Some sediment constituents have characteristic spectral signatures that could be used to better estimate the quantity of those constituents in sediments before samples were taken for detailed analysis.

ODP began using the Minolta photospectrometer CM-2002 during Leg 154. The Minolta measured the reflected light from the surface of the core over the visible spectrum (400–700 nm). More than 2,250,000 RSC measurements were taken with the Minolta during the 39 legs in which color reflectance data were collected.

Data Acquisition

The Minolta CM-2002 spectrophotometer was used to collect RSC data during ODP. For the first few years, the Minolta was operated manually and required significant effort on the part of the scientists and laboratory technicians to collect data. The measurement of RSC was time-critical because of the changes that occurred in the surface of the split core as the sediment or rock was exposed to air. During Leg 180, the Minolta was mounted on the AMST in order to automate data acquisition. There were some problems with track operation and automated data acquisition for a few legs, but starting during Leg 188, RSC data were routinely collected with the track system instead of manually.

Standard Operating Procedures

RSC measurements were taken on the archive half, preferably ~1 hr after the core had been split. The split core was covered with cling film to protect the glass cover on the aperture of the Minolta when the instrument was set on the surface to take measurements. The film transmits light uniformly over the spectrum of visible light and has minimal effect on the spectra (Blum, 1997). Even under manual operation, the data were acquired with personal computer–based data acquisition software.

The Minolta had several options that affected the measurement and processing of reflectance data. The recommended settings for ODP cores were

In addition to the spectral measurements downloaded from the Minolta, the camera's acquisition program also calculated standard color parameters. The Munsell HVC color system had been used by Earth scientists for many years as a way to standardize color descriptions of rocks. However, new color systems have been developed recently that relate reflectance spectra to color. The tristimulus system is based on matching a color under standardized conditions against the three primary colors red, green and blue, which are expressed as values X, Y, and Z. The tristimulus values can also be related to spectral wavelength. The L*a*b* color space system was recommended for sediment and rock analyses. In the L*a*b* system, L* is the lightness variable and a* and b* are chromaticity variables, with a* being the green to red axis and b* being the blue to yellow axis.

Calibration

Two types of calibration were performed on the Minolta CM-2002. A "zero calibration" was performed by aiming the aperture into a space where there were no objects within 1 m and no light source aimed at it. This calibration was performed to compensate for effects of stray light caused by the flare characteristics of the optical system. A "white calibration" was performed immediately after a zero calibration. The standard was a white ceramic cap supplied with the Minolta CM-2002 that was factory-calibrated over the 400–700 nm range. White calibrations were performed regularly. After the Janus database was operational, white calibration data were archived in the database.

Archive

Pre-Janus Archive

The original RSC data files were archived in the ODP/TAMU servers. There was no interim database for RSC data. The reflectance spectra were stored in the camera and downloaded to a file using a personal computer–based data acquisition program. The convention was to create a file after all the sections of a core were analyzed.

Migration of RSC Data to Janus

The data model for RSC can be found in "Janus Color Reflectance Data Model" in "Appendix M." Included are the relational diagram and the list of the tables that contain data pertinent to RSC, column names, and the definition of each column attribute. ODP Information Services Database Group was responsible for the migration of pre-Leg 171 data to Janus. In order to ensure that the X, Y, Z, L*, a*, and b* parameters were calculated based on the D65 illuminant and 10° standard observer, these parameters were recalculated and uploaded for the migrated data.

Janus RSC Data Format

RSC data are available through the Janus Web Color Reflectance query. The RSC query Web page allows the user to extract data using the following variables to restrict the amount of data retrieved: leg, site, hole, core, section, depth ranges, or latitude and longitude ranges. In addition, the user can use the output raw data option in the query to extract the spectral reflectance percentages for each wavelength (Table T31). Additional information about ODP RSC data can be found in Chapter 7 of Technical Note 26 (Blum, 1997). "Description of Data Items from RSC Query" in "Appendix M" contains additional information about the fields retrieved using the Janus Web RSC query, and the data format for the archived ASCII files.

Data Quality

Several things affect the quality of RSC data. The type of material and the drilling method used to recover the core are major factors. Disturbed material with cracks and voids yields poor quality measurements. Factors such as surface moisture or uncontrolled drying of the material, surface roughness, particle size, oxidation, and use of the protective film also affect the quality of the data.

Data quality was also dependent on the operator. The Minolta was manually operated for several legs. The operator needed to be sure the camera was properly set up and calibrated, placed on the core surface properly, and held in contact with the surface for the required period of time for each measurement. Even a tiny crack that allowed ambient light inside could contaminate the measurement.

There were problems when the Minolta was mounted on the AMST. It was thought that the aperture could be held slightly above the split-core surface to take measurements with the data corrected by a height adjustment. This would have been beneficial for at least two reasons: the section would not have to be wrapped in plastic wrap and movement of the camera down the track would be somewhat easier. However, data collected in this configuration were very poor. Light contamination made the spectra essentially useless. Data were collected during Legs 180–183, 185, and 186 before the problems were corrected. These data were not entered into the database but can be requested through the IODP/TAMU Data Librarian. The Shipboard Scientific Parties for those legs indicated that the spectral data may be acceptable in a relative sense, but the absolute spectral values are damaged. Data collection during Legs 184 and 186 was performed with the older manual method.

After the track-mounted system was operational, there could still be operator errors. Throughout ODP, the operator manually entered core information into the data acquisition program. Typographical errors or entering the wrong section identification information occasionally happened, and some mistakes were not identified. An effort was made during the verification of post-Leg 171 data to find sections that were misidentified. This was done using log sheets that were often used to document the analyses on AMST and looking for clues to misidentified analyses. Some of the clues that were used to find misidentified sections include

  1. Two runs for a section but no run for the following section;
  2. Run numbers out of sequence;
  3. Two runs for a section, run numbers out of sequence, but no data for that core number and section in a different hole. Run number sequence would be correct if placed in different hole.
  4. Comparison of data, and nature of the core material (length of core, voids, etc.).

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