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Thin layer chromatography, a case study
Author(s) -
Akkerboom J.C.,
Schepers P.,
Werff J. v.d.
Publication year - 1980
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/j.1467-9574.1980.tb00700.x
Subject(s) - sample (material) , thin layer chromatography , section (typography) , class (philosophy) , identification (biology) , order (exchange) , solvent , mathematics , computer science , chemistry , chromatography , artificial intelligence , organic chemistry , botany , finance , economics , biology , operating system
This paper gives an account of the collaboration between two mathematical statisticians and a toxicologist (the second author) interested in thin layer chromatography (TLC). A TLC “system” consists of a medium through which a solvent is transported. If a solution of some (toxic) sample is applied to the medium, then the components are carried forward by the solvent over different distances. Section 1 describes the concept of a data bank which provides standard values for the degrees of migration characteristic for each of m well‐studied substances in each of n systems. Sections 2–5 are mainly devoted to the construction of The “best design(s)”{ j 1 *… j k * } of k systems from the n available ones. The attention is restricted to the situation that an unidentified sample exclusively contains one of the m substances covered by the data bank and produces the scores xj … x j k in the systems j,… j k respectively. Three different approaches to the identification problem were successively considered. Each approach leads to a class of procedures and their performances. The performance of the optimum procedure can be used to define the performance of any of the ( n k ) designs ( j 1 … j k }. The latter performance is maximized in order to determine { j 1 *.,., j k * }. In practice usually data is obtained for mixtures instead of single. pure substances. Section 6 gives some tentative theory for the evaluation of such data.