Using Response Surface Methodology and High-Intensity Sweeteners’ Positive Synergy to Optimize Peach Nectar Acceptability

Abstract

<p style="text-align:justify;" class="MsoNormal"> <span>Combining the high-intensity sweeteners’ positive synergy with response surface methodology (RSM), it is possible to optimize food and beverage products liking, masking undesired sensory attributes and reducing costs and consumers’ additives intake (up to 50%). </span><span>A RSM based on a five-level, two variable central composite rotatable design</span><span>s</span><span> (CCRD) was applied, varying aspartame and acesulfame-K concentrations in order to optimize consumers’ sensory liking (n = 118) for peach nectar in terms of appearance, aroma, flavor, and overall liking. Statistically valid models were found for flavor and overall liking attributes and highest liking values were found for samples combining the two sweeteners (therefore overcoming acesulfame-K’s sensory limitations) in lower concentrations, confirming the synergetic effect and allowing cost reduction and less additives intake, without losing sensory quality.</span> </p

Optimization of recipe for development of Aonla squash- A Response surface methodology approach

“…ANOVA analysis (Table 4) indicates that the overall acceptability of aonla squash was highly significant at 5% level on linear term of juice (A) and quadratic term of (A 2 ). Previous investigation by Melo et al (2013) optimized peach nectar (low calorie) via. RSM and found that F-test value and R 2 for overall liking was 101.2 and 0.99, respectively while Majumdar et al (2012) reported 51.90 F-value and 0.97 R 2 value for sensory scores in developed ashgourd-mint leaves juice using RSM.…”

The Brazilian Way to Consume acai: Do guarana Extract and Sugar Concentrations Influence on Acceptance?

“…RSM consists of a group of mathematical and statistical procedures that can be used to study relationships between one or more responses (dependent variables) and a number of factors (independent variables) (Diniz & Martin, 1996). In the last decade, RSM has been successfully used to adjust formulations (Abdullah & Cheng, 2001;Castro et al, 2004;Murphy et al, 2004;Chu & Resurreccion, 2005;Granato et al, 2010;Melo et al, 2013) and process conditions (Chávez-Jáuregui et al, 2000;Mendes et al, 2001;Loh et al, 2005;Fernández et al, 2006;Kumar et al, 2009;Rehrah et al, 2009), reducing the number of trials and providing multiple regression approach to achieve optimization (Gan et al, 2007). However, to the best of our knowledge, there are no studies using response surface methodology to explore the best concentration of guaraná and sugar in the commercial açaí.…”