Optimization of athletic pasta formulation by D‐optimal mixture design

Abstract

The aim of this study was to produce an athletic pasta by the addition of various sources of protein. For this purpose, D‐optimal mixture design used for optimization of formulation of athletic pasta and protein with considering the hardness as main parameter. Various properties of the optimized formulation were evaluated. The optimal formulation contained 45.41% of semolina, 24% of pea protein isolate (PPI), 18% of oat flour (OF), 5% of soy protein isolate (SPI), 5% whey protein isolate (WPI), and 2% of gluten (G). In optimized formulation, the protein content increased by more than 2.9 times compared to control with the hardness in the range (569 g). Hardness, optimal cooking time, and cooking loss of products increased as the level of protein increased. The optimal formulation had a higher sensory acceptance than the control, which is probably related to color changes. Due to the amount and biological value of the proteins used and the high acceptance obtained, this formulation can be suggested for athletes. The obtained results indicated that production of athletic pasta with high biological value by using mixture of SPI, PPI, WPI, OF, and G is possible.

Formulation of Environmentally Safe Graffiti Remover Containing Esterified Plant Oils and Sugar Surfactant

“…The design of experiments (DoE) and quality by design (QbD) approaches based on statistical calculations are usually employed in formulation optimization. Analysis of variance (ANOVA) of the response surfaces estimated by d -optimal design for dependent variables Y 1 –Y 4 indicated that the quadratic model exhibited the best fit in all cases, which is a typical solution in mixture designs in the literature [ 36 , 39 , 40 , 61 ]. The minor modifications for quadratic fitting were included for the viscosity (Y 1 ) and the runoff speed (Y 3 ) responses by implementing inverse linear regression in order to increase the robustness of the optimization model.…”

Optimization of novel multigrain pasta and evaluation of physicochemical properties: using D‐optimal mixture design

“…The textural parameters were adjusted according to the method described by Kamali Rousta et al. ( 2020 ). During the first compression, hardness was described as the highest compression force (Ghandehari Yazdi et al., 2017 ; Rosa‐Sibakov et al., 2016 ).…”

“…Fortification with these components is an efficient method to increase the nutritional attributes of pasta; however, it presents a challenge because of their effects on the texture, cooking, and sensory properties of pasta (Kamali Rousta et al., 2020 ). Meanwhile, using the Mixture design methodology might be considered a useful tool to investigate the role of each component in processed foods and accents the significance of component interactions (Arteaga et al., 1993 ).…”

Background, Applications and Issues of the Experimental Designs for Mixture in the Food Sector

“…The mixture design was also applied to pasta, with the aims of study the rheological properties of a gluten-free dough [20], optimize the tensile strength of rice noodles [43] or formulate a protein-fortified pasta for athletes [44].…”

“…Kamali Rousta et al [44] study the formulation of athletic pasta, prepared a D-optimal design with all the six ingredients of the product (semolina, pea protein isolate, whey protein isolate, soy protein isolate, oat flour and gluten), leading to 31 experimental trials. The usual linear, quadratic and special cubic models were fitted to each of the responses (hardness, protein).…”