Browsing by Person "Popper, Lutz"

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Fluorescence spectroscopy of flour fractions and dough: analysis of spectral differences and potential to improve wheat quality prediction
(2025) Ziegler, Denise; Buck, Lukas; Scherf, Katharina Anne; Popper, Lutz; Hitzmann, Bernd; Ziegler, Denise; Department of Process Analytics, Institute of Food Science and Biotechnology, University of Hohenheim, Stuttgart, Germany; Buck, Lukas; Department of Bioactive and Functional Food Chemistry, Institute of Applied Biosciences, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany; Scherf, Katharina Anne; Department of Bioactive and Functional Food Chemistry, Institute of Applied Biosciences, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany; Popper, Lutz; Mühlenchemie GmbH & Co. KG, Ahrensburg, Germany; Hitzmann, Bernd; Department of Process Analytics, Institute of Food Science and Biotechnology, University of Hohenheim, Stuttgart, Germany
Background and Objectives: Spectroscopy of wheat kernels and flour has been used as a rapid tool to assess wheat quality, but predictions still lack in accuracy for most quality parameters except for protein content. To enable an improved prediction of further quality characteristics, new approaches are needed. This study investigates if the preprocessing of flour into flour fractions (by air classification, sieving) or dough and subsequent spectroscopic analysis of these types of samples could be a new way to improve wheat quality predictions. For this purpose, spectral differences are investigated and predictions of farinograph parameters are compared for fluorescence spectra of flour, flour fractions, and dough. Findings: A wide variety of fluorophores present in cereal products was identified. Their peak intensities significantly differed for flour, flour fractions, and dough. Flour and sieve fractions were superior in predicting water absorption (R2CV flour = 0.79; R2CV 32–50 µm = 0.81), while gluten and dough samples strongly improved predictions of rheological properties, especially dough development time (R2CV flour = 0.64; R2CV dough = 0.90; R2CV gluten = 0.84). Conclusion: Preprocessing of flour samples greatly alters their composition (e.g., protein enrichment), which is also reflected by spectral differences. Spectra of different sample types therefore contain different information and have the potential to improve the prediction of wheat quality. Significance and Novelty: This is the first study that investigates spectral differences of a large number of different flour fractions and dough using fluorescence spectroscopy and subsequently underlines the potential of this novel approach to improve wheat quality prediction in the future.
Improved prediction of wheat baking quality by three novel approaches involving spectroscopic, rheological and analytical measurements and an optimized baking test
(2025) Ziegler, Denise; Buck, Lukas; Scherf, Katharina Anne; Popper, Lutz; Schaum, Alexander; Hitzmann, Bernd; Ziegler, Denise; Department of Process Analytics, Institute of Food Science and Biotechnology, University of Hohenheim, Stuttgart, Germany; Buck, Lukas; Department of Bioactive and Functional Food Chemistry, Institute of Applied Biosciences, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany; Scherf, Katharina Anne; Department of Bioactive and Functional Food Chemistry, Institute of Applied Biosciences, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany; Popper, Lutz; Mühlenchemie GmbH & Co. KG, Ahrensburg, Germany; Schaum, Alexander; Department of Process Analytics, Institute of Food Science and Biotechnology, University of Hohenheim, Stuttgart, Germany; Hitzmann, Bernd; Department of Process Analytics, Institute of Food Science and Biotechnology, University of Hohenheim, Stuttgart, Germany
Baking quality, defined as loaf volume, is one of the most important quality attributes of wheat. An accurate and rapid determination is of great interest for the wheat supply chain. However, this remains difficult to date, because reported predictions based on other wheat characteristics (e.g. protein content) or flour spectroscopy are poor. This study investigates three novel approaches to improve the prediction of specific loaf volume determined by an optimized mini-baking test. The predictions are based on a large variety of rheological and analytical data as well as fluorescence, near-infrared (NIR) and Raman spectroscopy of flour and flour fractions. Furthermore, the influence of data fusion on the predictions is investigated. All three approaches presented promising results and showed great potential for practical application with R2CV > 0.90 for various regression models. For example, the combination of farinograph data with solvent retention capacity data or NIR flour spectra yielded R2CV of 0.91 in both cases. Combining Raman spectra of the < 32 μm and 75–100 μm fractions as well as NIR spectra of gluten, flour and starch both also yielded R2CV of 0.91. The results underline that loaf volume is a complex quality characteristic that can be better predicted when different data types are combined. Different rheological and analytical tests and different spectroscopic methods capture specific wheat quality characteristics that have different relations to baking volume and can therefore provide complementary information for improved predictions. Furthermore, the importance of rheological tests (especially farinograph, extensograph, alveograph) and the baking procedure for the prediction of baking quality are emphasized.