More articles from Volume 4, Issue 1, 2015
Evaluating the Ultra-High Pressure Homogenization (UHPH) and Pasteurization effects on the quality and shelf life of donkey milk
Almond milk fermented with different potentially probiotic bacteria improves iron uptake by intestinal epithelial (Caco-2) cells
Training requirements for agro-food industry in Portugal
Applicability of Mixolab test with local wheat flours
Effect of incorporating alum in cane juice clarification efficiency and sucrose losses
Citations
6
Ottavia Parenti, Lorenzo Guerrini, Sara Bossa Mompin, Mònica Toldrà, Bruno Zanoni
(2021)
The determination of bread dough readiness during kneading of wheat flour: A review of the available methods
Journal of Food Engineering, 309()
10.1016/j.jfoodeng.2021.110692
Georgiana Gabriela Codină, Adriana Dabija, Mircea Oroian
(2019)
Prediction of Pasting Properties of Dough from Mixolab Measurements Using Artificial Neuronal Networks
Foods, 8(10)
10.3390/foods8100447
Mehak Fatima, Allah Rakha, Muhammad Saeed, Muhammad Shahid, Filip Van Bockstaele
(2025)
Effect of okra polysaccharides extract powder on mixolab attributes, physicochemical characteristics and in-vitro starch digestibility of wheat bread
Bioactive Carbohydrates and Dietary Fibre, 34()
10.1016/j.bcdf.2025.100491
Grant M. Campbell, Konstantina Solomou, Keira J. O’Byrne, Kane L. Spencer
(2025)
Using the Chopin Mixolab to model the effects of arabinoxylan ingredients on breadmaking. Part 1: Modelling combined effects of AX and water adjustment on Mixolab parameters
Food and Bioproducts Processing, 150()
10.1016/j.fbp.2024.11.026
Marcelo Helguera, Aigul Abugalieva, Sarah Battenfield, Ferenc Békés, Gérard Branlard, Martha Cuniberti, Alexandra Hüsken, Eva Johansson, Craig F. Morris, Eric Nurit, Mike Sissons, Daniel Vazquez
(2020)
Wheat Quality For Improving Processing And Human Health
, ()
10.1007/978-3-030-34163-3_12
Hyukjin Kwon, Geunhyuk Yang, Sungmin Jeong, Jaepil Roh, Suyong Lee
(2022)
Establishment of machine learning hyperparameters for predicting the extensional properties of noodles from the thermo-mechanical properties of wheat flour
Journal of Food Engineering, 321()
10.1016/j.jfoodeng.2022.110940Applicability of Mixolab test with local wheat flours
Instituto Nacional de Investigaci´on Agropecuaria (INIA) Uruguay
Molino Rıo Uruguay Uruguay
Abstract
Several types of equipment have been used to predict dough behaviour during breadmaking. The complexity of requirements means that no device is able to predict all the properties, and therefore, new tests are released continuously. The Chopin Mixolab mixes the dough at different temperatures, allowing the study of dough mixing properties, weakening, gelatinization, gel stability and retrogradation in one test. The objective of this work was to study the suitability of the Mixolab to predict rheological properties and breadmaking quality of local wheats. Flour was obtained from 29 wheat samples from different genotypes and environments. The correlation of results from traditional analyses (test weight, protein content, sedimentation volume, wet gluten, Falling Number, Alveograph and Farinograph) with Mixolab parameters was studied. The properties of two different bread types were compared with all these parameters. Stability and water absorption values from the Farinograph were highly correlated with the respective Mixolab parameters. It was concluded that wheat samples could be sorted by mixing properties in similar order independently of which method was used. Beyond that, gluten strength estimators obtained from these three rheological methods and the sedimentation volume test were highly correlated. Whilst the correlation of Mixolab parameters with pan loaf volume was not as high as traditional ones, Mixolab developing time, stability and C5 were the best correlated with the most important hearth bread characteristics. Studies performed by other researchers, using wheats from diverse origins, found different results. The need for empirical rheology evaluation with local wheat samples was proved.
Keywords
References
Citation
Copyright

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Article metrics
The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.