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Prediction of wheat baking quality based on gliadin fractions and HMW-GS data by chemometric analysis (PLS modelling)

Kurtanjek, Ž. and Horvat, D. and Drezner, G. and Magdić, D. (2013) Prediction of wheat baking quality based on gliadin fractions and HMW-GS data by chemometric analysis (PLS modelling). Acta Alimentaria, 42 (4). pp. 609-617. ISSN 0139-3006

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Abstract

Gluten proteins composed of gliadins and glutenins are important contributors to the wheat quality properties. Twenty-eight winter wheat cultivars differing in bread processing quality were collected at the experimental fields of the Agricultural Institute Osijek, Croatia, in growing season 2006/2007.The HMW-GS composition and gliadin contents were determined by SDS-PAGE and RP-HPLC, respectively, with the aim to determine their relationship with wheat quality properties. Based on gliadins and HMW-GS data for 28 wheat cultivars PLS models were developed for the prediction of 15 baking quality parameters.NIPALS algorithm was applied for the evaluation of the latent variables and regression coefficient parameters. The obtained 4-th order models have average coefficients of determination R<sup>2</sup>=0.80.Determined variable importance in projections (VIP) coefficients revealed that HMW-GS data have the dominant influence on the baking quality parameters. For extensographic and farinographic properties the Glu-D1 locus has the main VIP coefficient while Glu-B1 locus is the most important for the indirect quality parameters. The derived PLS models and VIP coefficients could be used in molecular based wheat selection and breeding program.

Item Type: Article
Subjects: Q Science / természettudomány > QD Chemistry / kémia > QD01 Analytical chemistry / analitikai kémia
Depositing User: xKatalin xBarta
Date Deposited: 07 Feb 2017 08:21
Last Modified: 07 Feb 2017 08:21
URI: http://real.mtak.hu/id/eprint/47463

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