Response Surface Methodology in the Development of Rice Flour Yeast Breads: Sensory Evaluation

Abstract

Reference breadYeast breads were developed from rice flour (80%) and potato starch (20%). Using sensory measurement from a trained panel, response surface methodology (RSM) was applied to find carboxymethylcellulose (CMC), hydroxypropylmethylcellulose (HPMC), and water level combinations for gluten-free breads from three different rice flours. Formulations resulted in rice breads that met wheat bread reference standards for moistness, cohesiveness, yeasty flavor, adhesiveness, aftertaste, top crust and crumb color, cell size uniformity and predominant cell size. Medium grain rice flour breads met more sensory reference standards than long grain rice flour breads.A commercially prepared wheat flour (white) bread served as reference (REF) for all sensory evaluations. Eighteen loaves of bread were purchased (within 4 hr of baking) in five different lots over six wk. Reference breads were frozen after purchase for l-5 days and thawed (21"C) for 1.5-2 hr before sampling for sensory evaluation. Sensory evaluationNineteen potential panelists were screened using a series of 16 triangle tests in which panelists chose the odd rice bread sample with respect to firmness and/or moistness. Sixteen panelists were subsequently selected, on the basis of ability to correctly identify the odd sample (70% of the time) and on their availability, and trained 11 weeks. During training, panelists individually evaluated a variety of rice and wheat flour yeast bread samples. Group discussions facilitated development and refinement of the vocabulary for sensory characteristics of the rice breads, the ballot, appropriate descriptors and procedure for assessing rice bread quality. Fifteen attributes (yeasty odor, rice odor, firmness, moistness, cohesiveness, yeasty flavor, rice flavor, adhesiveness, graininess, aftertaste, top crust color, crumb color, predominant cell size, cell size uniformity and cell wall thickness) were selected for assessment of rice breads. Two performance evaluations were conducted, after the sixth and tenth week of training, according to the procedure of Cross et al. (1978). The panel was selected, based on results of the second evaluation. The panel consisted of 8 female students and staff in the Faculty of Home Economics at the Univ. of Alberta who were regular yeast bread consumers. INTRODUCTIONSPECIAL DIET PRODUCTS, such as gluten-free breads, often do not provide the sensory quality consumers expect (Paulus, 1986). To ensure gluten-free bread is accepted, gluten-free yeast breads with sensory characteristics similar to those of wheat flour yeast bread are needed. However, developmental research on gluten-free breads rarely has included sensory evaluation by a trained taste panel. Response surface methodology (RSM) has been successfully used with trained taste panel evaluations in development of baked products such as pie crusts (Smith and Rose, 1963), high protein bread (Henselman et al., 1974) and cakes (Vaisey-Genser et al., 1987). This suggested that use of both RSM and trained panel sensory evaluation wo...

Flour mixture of rice flour, corn and cassava starch in the production of gluten-free white bread

“…7) presented an expandable crumb, gummy and dense granulation, without alveoli, suggesting an adequate clinging in the dough. This result was in agreement with those by Ylimaki (1991), who considered a firm and gummy crumb as one of the most important characteristic of gluten-free breads. According to He and Hoseney (1991), the capability to retain gas can be expressed in terms of bread volume.…”

“…The texture of flour rice bread shown in Fig. 5, indicated the presence of small alveoli, slightly elongated with thin walls distributed homogeneously, similar to the breads prepared by Ylimaki et al (1991), who reported that rice bread presented rougher texture and smaller cells in the crumb when compared with wheat bread. The corn starch bread presented larger alveoli and some roles with crumbling characteristics, as shown in Fig.…”

Statistical optimization for tannase production from Aspergillus niger under submerged fermentation

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