Prediction of Pasting Properties of Dough from Mixolab Measurements Using Artificial Neuronal Networks.

Codină Codină,Dabija Dabija,Oroian Oroian

doi:10.3390/foods8100447

Codină Codină, Dabija Dabija + Show 1 more

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https://doi.org/10.3390/foods8100447

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Abstract

An artificial neuronal network (ANN) system was conducted to predict the Mixolab parameters which described the wheat flour starch-amylase part (torques C3, C4, C5, and the difference between C3-C4and C5-C4, respectively) from physicochemical properties (wet gluten, gluten deformation index, Falling number, moisture content, water absorption) of 10 different refined wheat flours supplemented bydifferent levels of fungal α-amylase addition. All Mixolab parameters analyzed and the Falling number values were reduced with the increased level of α-amylase addition. The ANN results accurately predicted the Mixolab parameters based on wheat flours physicochemical properties and α-amylase addition. ANN analyses showed that moisture content was the most sensitive parameter in influencing Mixolab maximum torque C3 and the difference between torques C3 and C4, while wet gluten was the most sensitive parameter in influencing minimum torque C4 and the difference between torques C5 and C4, and α-amylase level was the most sensitive parameter in predicting maximum torque C5. It is obvious that the Falling number of all the Mixolab characteristics best predicted the difference between torques C3 and C4.

Highlights

Nowadays, different types of enzymes are used in the bakery field in order to improve the technological processes of the bakery industry and the quality of the baked products [1].Of these, the most commonly used enzymes are amylases due to their high practical importance.First, amylases provides fermentable sugars for yeast cells and favors the production of carbon dioxide
The parameters mostly used to evaluate the wheat flour quality are Falling number (FN), moisture content, water absorption, and protein quality for bread making, which can be found on any analysis bulletin of wheat flour [19]. Because these parameters are the most common and are critical to assessing the quality of wheat flour, we considered it useful to investigate the prediction of the influence of these parameters alongside different levels of fungal α-amylase addition on pasting properties of wheat flour dough determined with the Mixolab device
The levels of the α-amylase used were of 0, 2800, 5600, 8400 SKB kg−1 wheat flour, which meet the amount of enzyme that dextrinizes 1 g/3-amylase treated starch in one hour at 30◦ C and pH 4.85

Summary

Introduction

Amylases provides fermentable sugars for yeast cells and favors the production of carbon dioxide It contributes to the improvement of dough rheological properties and to the quality of the bakery products [2]. It is well-known that, in general, α-amylase activity is lacking or is present in a very low amount in the wheat flour, whereas the β-amylase is present in a large amount [3,4]. The importance of adjusting the level of α-amylase activity in wheat flours is essential for bread making For this purpose, the most common practice used in bread making is the addition of fungal α-amylase during the baking process [7]. A high level of α-amylase in wheat flour is undesirable because it leads to sticky dough, large holes in bread, and gummy crumbs [8]

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