Improving the baking quality of bread wheat using rapid tests and genomics: The prediction of dough rheological parameters by gluten peak indices and genomic selection models |
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| Institution: | 1. Department for Agrobiotechnology (IFA-Tulln), Institute for Biotechnology in Plant Production, University of Natural Resources and Life Sciences (BOKU), Vienna, Konrad-Lorenz-Str. 20, 3430 Tulln, Austria;2. Versuchsanstalt für Getreideverarbeitung, Österreichische Mühlenvereinigung e.V., Prinz-Eugen-Straße 14/1/4, 1040 Vienna, Austria;3. Saatzucht Donau GesmbH. & CoKG, Saatzuchtstrasse 11, 2301 Probstdorf, Austria;1. Agroscope, Plants and Plant Products, Reckenholzstrasse 191, 8046 Zurich, Switzerland;2. Agroscope, Plant Breeding, Route de Duiller 50, 1260 Nyon, Switzerland;3. Austrian Agency for Health and Food Safety (AGES), Spargelfeldstrasse 191, 1220 Vienna, Austria;4. Department of Crop Sciences, University of Natural Resources and Life Sciences, Vienna, Konrad Lorenz Str. 24, 3430 Tulln, Austria;5. Chair of Plant Nutrition, Technical University Munich, Emil-Ramann-Strasse 2, 85354 Freising, Germany;1. Department of Soil Science, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada;2. Department of Food and Human Nutritional Sciences, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada;1. Department of Agriculture and Forest Sciences (DAFNE), University of Tuscia, Via San Camillo de Lellis snc, Viterbo, 01100, Italy;2. Council for Agricultural Research and Economics, Research Centre for Engineering and Agro-Food Processing, Via Manziana 30, Rome, 00189, Italy;3. NSW Department of Primary Industries, Tamworth Agricultural Institute, 4 Marsden Park Road, Tamworth, 2340, NSW, Australia |
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| Abstract: | The measurement of baking quality by dough mixing and viscoelastic tests is often labor-intensive and time-consuming, thus the possibility to predict these rheological parameters either by rapid tests or genomic selection models based on molecular markers was investigated in this study. A winter wheat breeding population of 128 genotypes was measured for its rheological parameters, gluten peak indices and other rapid test variables in multiple environments. The prediction accuracy of the rheological parameters was assessed in different cross-validation schemes, reflecting scenarios encountered either in food-processing or by plant breeders. Predictions based on gluten peak indices (r = 0.41–0.82) outperformed the other investigated rapid tests in the food-processing scenario. The combination of gluten peak indices with sedimentation value and protein content gave furthermore the overall highest prediction accuracy (r = 0.70). Cross-validation results from the plant breeding scenario revealed that the prediction accuracy of genomic selection models was merely slightly lower (r = 0.42) than using a combination of sedimentation value and protein content (r = 0.44). Merging gluten peak indices with genomic estimated breeding values resulted in a higher accuracy than either method alone (r = 0.52), and was a promising strategy to select for baking quality in wheat breeding. |
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