Create a custom sized Core Collection based on a distance matrix and applying
  the A-NE (accession nearest entry), E-NE (entry nearest entry) or E-E (entry entry) method
  as introduced in Jansen and van Hintum (2007) <doi:10.1007/s00122-006-0433-9> and
  further elaborated on in Odong, T.L. (2012) <https://edepot.wur.nl/212422>.
  Optionally a list of preselected accessions to be included into the core can be set.
  For each accession in the computed core, if available nearby accessions are retrievable
  that can be used as an alternative.

Computed tomography (CT) imaging is a powerful tool for understanding the composition of sediment cores. This package streamlines and accelerates the analysis of CT data generated in the context of environmental science. Included are tools for processing raw DICOM images to characterize sediment composition (sand, peat, etc.). Root analyses are also enabled, including measures of external surface area and volumes for user-defined root size classes. For a detailed description of the application of computed tomography imaging for sediment characterization, see: Davey, E., C. Wigand, R. Johnson, K. Sundberg, J. Morris, and C. Roman. (2011) <DOI: 10.1890/10-2037.1>.

Core Hunter is a tool to sample diverse, representative subsets from large germplasm
    collections, with minimum redundancy. Such so-called core collections have applications in plant
    breeding and genetic resource management in general. Core Hunter can construct cores based on
    genetic marker data, phenotypic traits or precomputed distance matrices, optimizing one of many
    provided evaluation measures depending on the precise purpose of the core (e.g. high diversity,
    representativeness, or allelic richness). In addition, multiple measures can be simultaneously
    optimized as part of a weighted index to bring the different perspectives closer together.
    The Core Hunter library is implemented in Java 8 as an open source project (see
    <http://www.corehunter.org>).