A note on the parameter set for factor analysis models

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

Mycotoxins are small (MW approximately 700), toxic chemical products formed as secondary metabolites by a few fungal species that readily colonise crops and contaminate them with toxins in the field or after harvest. Ochratoxins and Aflatoxins are mycotoxins of major significance and hence there has been significant research on broad range of analytical and detection techniques that could be useful and practical. Due to the variety of structures of these toxins, it is impossible to use one standard technique for analysis and/or detection. Practical requirements for high-sensitivity analysis and the need for a specialist laboratory setting create challenges for routine analysis. Several existing analytical techniques, which offer flexible and broad-based methods of analysis and in some cases detection, have been discussed in this manuscript. There are a number of methods used, of which many are lab-based, but to our knowledge there seems to be no single technique that stands out above the rest, although analytical liquid chromatography, commonly linked with mass spectroscopy is likely to be popular. This review manuscript discusses (a) sample pre-treatment methods such as liquid-liquid extraction (LLE), supercritical fluid extraction (SFE), solid phase extraction (SPE), (b) separation methods such as (TLC), high performance liquid chromatography (HPLC), gas chromatography (GC), and capillary electrophoresis (CE) and (c) others such as ELISA. Further currents trends, advantages and disadvantages and future prospects of these methods have been discussed.
Original languageEnglish
Title of host publicationLinear algebra and its applications
Pages261-266
DOIs
Publication statusPublished - 1999

Publication series

NameLinear Algebra and its Applications
Volume289

Keywords

  • factor analysis

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    Krijnen, W. P. (1999). A note on the parameter set for factor analysis models. In Linear algebra and its applications (pp. 261-266). (Linear Algebra and its Applications; Vol. 289). https://doi.org/10.1016/S0024-3795(97)10044-1