Factor Analysis and Modelling for Rapid Quality Assessment of Croatian Wheat Cultivars with Different Gluten Characteristics

• Published in: Food technology and biotechnology Vol. 46; no. 3; pp. 270 - 277
• Main Authors: Kurtanjek, Z, Horvat, D, Magdic, D, Drezner, G
• Format: Journal Article
• Language: English
• Published: University of Zagreb Faculty of Food Technology and Biotechnology 01.07.2008
• Subjects: gluten proteins; principal component analysis; RP-HPLC; technological quality; Triticum aestivum; wheat
• ISSN: 1330-9862; 1334-2606

Factor analysis and multivariate chemometric modelling for rapid assessment of baking quality of wheat cultivars from Slavonia region, Croatia, have been applied. The cultivars zitarka, Kata, Monika, Ana, Demetra, Divana and Sana were grown under controlled conditions at the experimental field of Agricultural Institute Osijek during three years (2000-2002). Their quality properties were evaluated by 45 different chemical, physical and biochemical variables. The measured variables were grouped as: indirect quality parameters (6), farinographic parameters (7), extensographic parameters (5), baking test parameters (2) and reversed phase-high performance liquid chromatography (RP-HPLC) of gluten proteins (25). The aim of this study is to establish minimal number (three), i.e. principal factors, among the 45 variables and to derive multivariate linear regression models for their use in simple and fast prediction of wheat properties. Selection of the principal factors based on the principal component analysis (PCA) has been applied. The first three main factors of the analysis include: total glutenins (TGT), total?-gliadins (T?-) and the ratio of dough resistance/extensibility (R/Ext). These factors account for 76.45 % of the total variance. Linear regression models gave average regression coefficients (R) evaluated for the parameter groups: indirect quality R=0.91, baking test R=0.63, farinographic R=0.78, extensographic R=0.95 and RP-HPLC of gluten data R=0.90. Errors in the model predictions were evaluated by the 95 % significance intervals of the calibration lines. Practical applications of the models for rapid quality assessment and laboratory experiment planning were emphasized.