Multiway methods in food science

TY - CHAP

T1 - Multiway methods in food science

AU - Rinnan, Åsmund

AU - Amigo Rubio, Jose Manuel

AU - Skov, Thomas

PY - 2013/12/27

Y1 - 2013/12/27

N2 - This chapter gives an introduction to the world of multiway chemometrics, as well as showing how it can be applied to different types of multidimensional data related to food science and technology. It describes how information can be extracted from multiway data in a meaningful way by keeping the multiway dimensionality, or even by adding a new dimensionality to traditional two-dimensional data (data tables). The chapter mainly focuses on fluorescence and gas chromatography mass spectrometry (GC-MS) data. However, the methods discussed are not limited to the few cases shown, but rather to any multiway data which contain (or can be transformed to contain) a trilinear data structure.

AB - This chapter gives an introduction to the world of multiway chemometrics, as well as showing how it can be applied to different types of multidimensional data related to food science and technology. It describes how information can be extracted from multiway data in a meaningful way by keeping the multiway dimensionality, or even by adding a new dimensionality to traditional two-dimensional data (data tables). The chapter mainly focuses on fluorescence and gas chromatography mass spectrometry (GC-MS) data. However, the methods discussed are not limited to the few cases shown, but rather to any multiway data which contain (or can be transformed to contain) a trilinear data structure.

UR - http://onlinelibrary.wiley.com/book/10.1002/9781118434635

U2 - 10.1002/9781118434635.ch09

DO - 10.1002/9781118434635.ch09

M3 - Book chapter

SN - 9781118433683

SP - 143

EP - 174

BT - Mathematical and statistical methods in food science and technology

A2 - Granato, Daniel

A2 - Ares, Gastón

PB - Wiley

ER -