Analysing multivariate storage data of seafood spreads. A case study based on combining split-plot design, principal component analysis and partial least squares predictions

被引:2
|
作者
Sivertsen, Edvard [1 ,6 ]
Thyholt, Kari [2 ,6 ]
Rustad, Turid [3 ]
Slizyte, Rasa [4 ]
Josefsen, Kjell D. [1 ]
Haugen, Eva Johanne [5 ]
Johansen, Aina T. [6 ,7 ]
Schei, Marte
Naes, Tormod [8 ,9 ]
机构
[1] SINTEF AS, SP Andersens Veg 3, N-7034 Trondheim, Norway
[2] Fremtidens Ind AS, Verkstedvegen 4, N-7125 Vanvikan, Norway
[3] NTNU, Dept Biotechnol & Food Sci, Hogskoleringen 1, N-7034 Trondheim, Norway
[4] SINTEF Ocean, Brattorkaia 17 C, N-7010 Trondheim, Norway
[5] SalMar ASA, Ind 51, N-7266 Kverva, Norway
[6] Mills AS, Sofienberg Gate 19, N-0558 Oslo, Norway
[7] Tine SA, Lakkegata 23, N-0187 Oslo, Norway
[8] Norwegian Inst Food Fisheries & Aquaculture Res, Nofima, Osloveien 2, N-1430 As, Norway
[9] Univ Copenhagen, Dept Food Sci, Copenhagen, Denmark
关键词
Fish spread; Sea farming; Value chain; Eating quality; Split-plot design; Time series; QUALITY;
D O I
10.1016/j.foodcont.2021.108385
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
As part of an extended fish product (mixed salmon spread) value chain involving multiple treatment procedures and mixing processes, oxidation and microbial spoilage can be initiated at any number of steps and go on to accelerate product deterioration. This may occur, for example, when salmon rest raw materials are processed to form mixed emulsion products. To investigate the effect of selected variables in the value chain, a model experiment was designed and implemented, consisting of a chain divided into four steps involving fish feed composition, fish processing, fish spread production and storage. By using this case, the objectives of the paper are to 1) show how a complex split-plot design can be analysed using analysis of variance (ANOVA) and multivariate statistical analyses, 2) show how an interplay of the methodologies can contribute to improvement in the interpretation and validation of results, and 3) identify the quality markers most affected by the design variables, and then use these to optimise response measurements for different raw material properties. We also propose some new monitoring and control strategies based on the PCA and results obtained. The analysis has indicated in this case that it may be beneficial for the long shelf-life of the spread to use fresh and lean salmon cuts, to store the product under superchilled conditions and to avoid the addition of secondary seafood ingredients. Salmon feed variables do not affect the eating quality of the spreads. The early addition of a smoke component and the rigor status of the salmon at the time of processing had little effect on eating quality. The variables that did not affect eating quality or shelf-life can be optimised based on aspects such as nutritional or health benefits, or production costs. This article demonstrates that PCA is a useful method both for the monitoring of eating quality with storage time, the definition of control limits for product acceptability, and the statistical validation of split-plot ANOVA results.
引用
收藏
页数:12
相关论文
共 10 条
  • [1] Study of the Fouling Characteristics of Arc Pipe Based on Principal Component Analysis and Partial Least Squares
    Song Jingdong
    Wen Xiaoqiang
    MANUFACTURING SCIENCE AND MATERIALS ENGINEERING, PTS 1 AND 2, 2012, 443-444 : 731 - 737
  • [2] Combining multivariate cumulative sum control charts with principal component analysis and partial least squares model to detect sickness behaviour in dairy cattle
    Dittrich, I.
    Gertz, M.
    Maassen-Francke, B.
    Krudewig, K. -H.
    Junge, W.
    Krieter, J.
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2021, 186
  • [3] Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: Application to the detection of breast cancer
    Gu, Haiwei
    Pan, Zhengzheng
    Xi, Bowei
    Asiago, Vincent
    Musselman, Brian
    Raftery, Daniel
    ANALYTICA CHIMICA ACTA, 2011, 686 (1-2) : 57 - 63
  • [4] European strawberry yogurt market analysis with a case study on acceptance drivers for children in Spain using principal component analysis and partial least squares regression
    Ward, CDW
    Koeferli, CS
    Schwegler, PP
    Schaeppi, D
    Plemmons, LE
    FOOD QUALITY AND PREFERENCE, 1999, 10 (4-5) : 387 - 400
  • [5] Megavariate analysis of environmental QSAR data. Part I – A basic framework founded on principal component analysis (PCA), partial least squares (PLS), and statistical molecular design (SMD)
    Lennart Eriksson
    Patrik L. Andersson
    Erik Johansson
    Mats Tysklind
    Molecular Diversity, 2006, 10 : 169 - 186
  • [6] Megavariate analysis of environmental QSAR data. Part I - A basic framework founded on principal component analysis (PCA), partial least squares (PLS), and statistical molecular design (SMD)
    Eriksson, Lennart
    Andersson, Patrik L.
    Johansson, Erik
    Tysklind, Mats
    MOLECULAR DIVERSITY, 2006, 10 (02) : 169 - 186
  • [7] Organic Matter Maturity Profile of a Well Case Study by Combination of Raman Spectroscopy and Principal Component Analysis-Partial Least Squares Regression (PCA-PLS) Chemometric Methods
    Bonoldi, Lucia
    Frigerio, Francesco
    Di Paolo, Lea
    Savoin, Alberto.
    Barbieri, Donato
    Grigo, Domenico
    ENERGY & FUELS, 2018, 32 (09) : 8955 - 8965
  • [8] Improving the robustness of a partial least squares (PLS) model based on pure component selectivity analysis and range optimization: Case study for the analysis of an etching solution containing hydrogen peroxide
    Lee, Youngbok
    Chung, Hoeil
    Arnold, Mark A.
    ANALYTICA CHIMICA ACTA, 2006, 572 (01) : 93 - 101
  • [9] Comparison of dimension reduction-based logistic regression models for case-control genome-wide association study:principal components analysis vs.partial least squares
    Honggang Yi
    Hongmei Wo
    Yang Zhao
    Ruyang Zhang
    Junchen Dai
    Guangfu Jin
    Hongxia Ma
    Tangchun Wu
    Zhibin Hu
    Dongxin Lin
    Hongbing Shen
    Feng Chen
    The Journal of Biomedical Research, 2015, 29 (04) : 298 - 307
  • [10] Comparison of dimension reduction-based logistic regression models for case-control genome-wide association study: principal components analysis vs. partial least squares
    Yi, Honggang
    Wo, Hongmei
    Zhao, Yang
    Zhang, Ruyang
    Dai, Junchen
    Jin, Guangfu
    Ma, Hongxia
    Wu, Tangchun
    Hu, Zhibin
    Lin, Dongxin
    Shen, Hongbing
    Chen, Feng
    JOURNAL OF BIOMEDICAL RESEARCH, 2015, 29 (04): : 298 - 307