Prediction of wheat gluten composition via near-infrared spectroscopy

Clemens Schuster, Julien Huen, Katharina Anne Scherf

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Gluten composition is an important quality parameter for wheat flour, because it is strongly correlated to baking quality. Wheat proteins are commonly extracted stepwise and analysed using RP-HPLC-UV to determine the gluten composition. This procedure is very time-consuming and labour-intensive. Therefore, a new, fast and easy method to quantitate gluten proteins was established using NIR spectroscopy (NIRS). PLS-regression models were calculated containing 207 samples for calibration and 169 for test set validation. Albumin/globulin (ALGL), gluten, gliadin and glutenin content was predicted with a root mean square error of prediction (RMSEP) of 2.01 mg/g, 6.09 mg/g, 4.25 mg/g and 3.50 mg/g, respectively. High-molecular-weight glutenin subunits (HMW-GS) and low-molecular-weight glutenin subunits (LMW-GS) were predicted with a RMSEP of 1.12 mg/g and 2.38 mg/g. The relative error was too high for ALGL, LMW-GS and HMW-GS, but that of gluten, gliadins and glutenins was in a range comparable to the reference method. Therefore, the new NIRS method can be used to estimate the gluten composition of wheat flour, including the gliadin/glutenin and the LMW-GS/HMW-GS ratio.

Original languageEnglish
Article number100471
JournalCurrent Research in Food Science
Volume6
DOIs
StatePublished - Jan 2023
Externally publishedYes

Keywords

  • Baking quality
  • Gliadin
  • Glutenin
  • NIRS
  • PLS-regression
  • Reversed-phase high-performance liquid chromatography (RP-HPLC)

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