Multiobjective process optimization for betaine enriched spelt flour based extrudates

Abstract

The main purposes of this work are successful modeling of twin‐screw extrusion process using predictive models, investigating the effect of process parameters such as screw speed, feed rate, and feed moisture content on the process and product responses and finally optimizing the process regarding betaine content in the extruded product and energy consumption. The second order polynomial approximation models and the artificial neural network were developed to predict the betaine content, showing the high accuracy in the prediction of experimental results. This study introduces the multiobjective optimization (MOO) approach in the extrusion process of spelt flour. The maximal betaine content (between 1,506.8 and 1,605.2 mg/40 g) and minimal energy consumption (between 101.3 and 108.5 W hr/kg) were indicated by MOO procedure, which were gained using the following input parameters: feed flow rate feed about 24 kg/h, screw speed about 252 RPM and moisture content from 21.6 to 23.4%. Practical applications This study introduces the multiobjective optimization (MOO) approach in the extrusion process of spelt flour, which provides the selection of optimal solution that enables the extruder to reach the optimum conditions of the process and provide decision maker with deeper understanding of the process. The present study analyzes the influence of extrusion cooking parameters like: screw speed, feed flow rate, and feed moisture content on the betaine content in the extrudate product and specific mechanical energy input during the processing of betaine enriched spelt flour based extrudates. One way to improve the intake of betaine in the general population can be to enrich foods with betaine. According to European Breakfast Cereal Association for extruded products portion sizes should be 40 g. Consuming a portion of a functional extrudate product with the addition of betaine (1,500 mg/day) could give expected health effects. Final extrudate product from this study satisfies these statements.

Dough bread from refined wheat flour partially replaced by grape peels: Optimizing the rheological properties

“…In addition, the ANN technique permits the study of relationships between the input variables and of the outputs of the process using a limited number of experimental run (Bingöl, Hercan, Elevli, & Kılıç, 2012), being commonly applied for modeling and optimization of various processes. ANNs have been used in prediction of some parameters in various processes (Alvarez, 2009;Chakraborty & Shrivastava, 2019;Kashaninejad, Dehghani, & Kashiri, 2009;Koji c et al, 2019;Lamrini, Della Valle, Trelea, Perrot, & Trystram, 2012;Sablani, Baik, & Marcotte, 2002) and food quality evaluation (Broyart & Trystram, 2003;Funes et al, 2015;Goyache et al, 2001) or to predict dough rheological properties (farinograph peak, extensibility, and maximum resistance) from the torque developed during mixing (Ruan, Almaer, & Zhang, 1995). Other studies revealed that ANNs were used to predict the parameters of farinograph (Abbasi, Emam-Djomeh, & Seyedin, 2011), extensograph, alveograph, and fundamental rheological properties of dough from several physicochemical properties of flour (Abbasi et al, 2012;Abbasi, Emam-Djomeh, & Ardabili, 2014;Abbasi & Mohammadifar, 2015).…”

Modelling of extrusion process for evaluation of spelt wholegrain snack expansion

“…Spelt flour was extruded using co-rotating twin-screw extruder (Bühler BTSK 30/28D, 7 sections, length/diameter ratio = 28:1, Bühler, Uzwil, Switzerland). The extrusion cooking process was described previously in our work (Kojić et al 2019).…”

“…The values for the expansion index were predicted by ANN. The procedure for constructing ANN and Yoon model can be found in the paper Kojić et al (2019).…”

“…A high content of nutritionally valuable components (proteins, vitamins, minerals, fibers) makes the spelt suitable for the production of a wide range of food products (Krulj et al, 2019). Nowadays, increased production and use of spelt wholegrain flour in human nutrition increase the necessity to define and characterize snack products made by extrusion from this raw material (Kojić et al, 2019). During the extrusion operation, even small variations in processing parameters affect the whole process as well as the product quality.…”

Application of soybean oil and glycerol in animal feed production, ANN model

“…In order to obtain good network behaviour, it is necessary to make a trial and error procedure and also to choose the number of hidden layers, and the number of neurons in hidden layer(s) (20). A multi-layer perceptron model (MLP) consisted of three layers (input, hidden and output).…”