TY - JOUR
T1 - Prediction of chemical, physical and sensory data from process parameters for frozen cod using multivariate analysis
AU - Bechmann, Iben Ellegaard
AU - Jensen, H.S.
AU - Bøknæs, Niels
AU - Warm, Karin
AU - Nielsen, Jette
PY - 1998
Y1 - 1998
N2 - Physical, chemical and sensory quality parameters were determined for 115 cod (Gadus morhua) samples stored under varying frozen storage conditions. Five different process parameters (period of frozen storage, frozen storage. temperature, place of catch, season for catching and state of rigor) were varied systematically at two levels. The data obtained were evaluated using the multivariate methods, principal component analysis (PCA) and partial least squares (PLS) regression. The PCA models were used to identify which process parameters were actually most important for the quality of the frozen cod. PLS models that were able to predict the physical, chemical and sensory quality parameters from the process parameters of the frozen raw material were generated. The prediction abilities of the PLS models were good enough to give reasonable results even when the process parameters were characterised by ones and zeroes only. These results illustrate the application of multivariate analysis as an effective strategy for improving the quality of frozen fish products. (C) 1998 Society of Chemical Industry
AB - Physical, chemical and sensory quality parameters were determined for 115 cod (Gadus morhua) samples stored under varying frozen storage conditions. Five different process parameters (period of frozen storage, frozen storage. temperature, place of catch, season for catching and state of rigor) were varied systematically at two levels. The data obtained were evaluated using the multivariate methods, principal component analysis (PCA) and partial least squares (PLS) regression. The PCA models were used to identify which process parameters were actually most important for the quality of the frozen cod. PLS models that were able to predict the physical, chemical and sensory quality parameters from the process parameters of the frozen raw material were generated. The prediction abilities of the PLS models were good enough to give reasonable results even when the process parameters were characterised by ones and zeroes only. These results illustrate the application of multivariate analysis as an effective strategy for improving the quality of frozen fish products. (C) 1998 Society of Chemical Industry
U2 - 10.1002/(SICI)1097-0010(199811)78:3<329::AID-JSFA121>3.0.CO;2-E
DO - 10.1002/(SICI)1097-0010(199811)78:3<329::AID-JSFA121>3.0.CO;2-E
M3 - Journal article
VL - 78
SP - 329
EP - 336
JO - Journal of the Science of Food and Agriculture
JF - Journal of the Science of Food and Agriculture
SN - 0022-5142
IS - 3
ER -