Hydrophilic interaction liquid chromatography (HILIC)—a powerful separation technique

Hydrophilic interaction liquid chromatography (HILIC) provides an alternative approach to effectively separate small polar compounds on polar stationary phases. The purpose of this work was to review the options for the characterization of HILIC stationary phases and their applications for separations of polar compounds in complex matrices. The characteristics of the hydrophilic stationary phase may affect and in some cases limit the choices of mobile phase composition, ion strength or buffer pH value available, since mechanisms other than hydrophilic partitioning could potentially occur. Enhancing our understanding of retention behavior in HILIC increases the scope of possible applications of liquid chromatography. One interesting option may also be to use HILIC in orthogonal and/or two-dimensional separations. Bioapplications of HILIC systems are also presented

Spaceborne Hyperspectral EO-1 Hyperion Data Pre-Processing

Increases in global populations and acceleration in land cover and land use change necessitate the rapid monitoring of such changes to address issues like global food security and global water security. Remote sensing has been instrumental in doing this over the past 50 years. There have also been many advances in remote sensing technology; although many of these advances have been limited to multispectral sensors, we have hyperspectral data from the recently decommissioned Hyperion sensor, and upcoming hyperspectral sensors such as Germany's EnMAP and the National Aeronautics Space Administration's (NASA's) HyspIRI. However, there is no standardized protocol for pre-processing hyperspectral data, such as the Hyperion imagery. We need to establish such protocols for hyperspectral data to facilitate the use of these large datasets efficiently to address ecological questions at global extents. In this chapter, we review methods available for pre-processing Hyperion data and suggest a workflow for Hyperion image pre-processing. Examples of these pre-processing steps are also provided for the Google Earth Engine (GEE) cloud-computing platform, which facilitates studies at a global extent by eliminating the need to store and process imagery on a personal computer. These hyperspectral datasets, once pre-processed, are useful for many applications including vegetation classification, biomass estimation, and crop water productivity estimation