Amaranth as a bread enriching ingredient

Assessment of Physicochemical Properties and Quality of the Breads Made from Organically Grown Wheat and Legumes

This study aimed to explore the feasibility of substituting wheat flour with varying levels (10%, 15%, 20%, and 25%) of flour derived from field bean, chickpea, lentil, and pea seeds. The investigation focused on assessing the physical properties of wheat dough and the physicochemical characteristics of bread samples. The addition of legume seed flours significantly influenced the dough's development time, particularly with chickpea flour causing a notable increase in this parameter. While dough stability was generally shorter for mixtures containing wheat flour and legume seed flour, chickpea flour was an exception, significantly prolonging dough stability time. Furthermore, the inclusion of legume flours resulted in increased protein, ash, fiber, fat, and phenolic contents in the enriched bread, while the carbohydrate content decreased. Additionally, the crumb exhibited increased redness and yellowness and decreased lightness due to the enrichment of the bread. Notably, the antioxidant activity of bread containing legume flour also increased, with the most significant increase observed when pea flour was utilized. Conversely, negative effects on bread volume, crumb density, and texture parameters were noted with the incorporation of legume additives. Taking into consideration the results of both physicochemical analyses and sensory evaluation, it is recommended that the incorporation of the specified legume flours should not exceed 15% in relation to the quantity of wheat flour used.

The Effects of Quinoa and Amaranth Flour on the Qualitative Characteristics of Gluten-Free Cakes

The effect of pseudocereal flour such as quinoa and amaranth in different concentrations (0, 10, 20, and 30%) was investigated in gluten-free cake formulation. Cake containing amaranth and quinoa flour showed higher protein, fat, ash, and fiber content. A30 (30% amaranth) and Q30 (30% quinoa) had the highest values, and the control sample had the lowest values. The moisture content of the gluten-free cakes was not in the range of the Iranian standard. The sample containing 20% quinoa flour showed the highest specific volume (2.88 ± 0.09 cm³/g) and the lowest hardness (259.33 ± 10.09 g) (p < 0.05). L^∗ value varied from 72.09 to 79, and the gluten-free cakes had a darker color. All the cakes containing quinoa and amaranth flour showed low a^∗ and b^∗ values (p < 0.05). Gluten-free cakes contain high amounts of unsaturated fatty acids (linoleic and linolenic acids) and minerals (iron, calcium, magnesium, and zinc). The results of the sensory evaluation showed that the sample containing 10% of amaranth and quinoa flour obtained the highest taste, aroma, color, appearance, and overall acceptability score compared to other treatments. In conclusion, it is possible to produce gluten-free cakes with quinoa and amaranth flour with sensory and physicochemical properties similar to wheat cakes. The formulations containing 20% and 30% quinoa were the best.

Features of Bread Made from Different Amaranth Flour Fractions Partially Substituting Wheat Flour

Amaranth flour (AF) is recognized as high-quality raw material regarding nutrients and bioactive compounds, essential in supplying human health benefits, compared with white flour (WF). In this study, the effects of factors, different particles sizes (large, medium, and small), and levels of AF (5, 10, 15, and 20%) substituting WF on the responses, empirical and dynamic dough rheological properties, and some quality parameters of bread were successfully modeled using predictive models. Finally, the optimization of a formulation to maximize the AF level whilst maintaining bread quality for each type of particle size (PS) was performed based on the response surface methodology models generated. The rheological properties of the composite flour formulated were evaluated using Mixolab, alveograph, rheofermentometer, and dynamic rheometer. In addition, bread quality parameters, loaf volume, instrumental texture features, and firmness were evaluated. The anticipation of the optimal value for each response in terms of dough rheological properties during mixing, protein weakening, starch gelatinization and retrogradation, biaxial extension, fermentation, viscoelastic moduli, and creep and recovery compliance depending on PS. The optimal addition level was determined by a multi-objective optimization approach. The optimal addition level was 9.41% for large, 9.39% for medium, and 7.89% for small PS. The results can help manufacturers to develop bread products with the desired particle size with optimal technological and physical features.