Multi-Response Quality Optimization of Gluten-Free Noodles Through the Integration of Taguchi, GRA and PCA Method - M. Hanifuddin Hakim; Al-ma’rifati Ilahiyah; Andini Puspa Kinasih; Naufal Daffa Arsalan; Altiara Dwi Erlangga (Universitas Suryakancana, 2026)
The demand for gluten-free noodles has steadily increased in response to growing health awareness and dietary needs of individuals with celiac disease or gluten intolerance. A primary challenge in developing gluten-free noodles lies in replicating the viscoelastic properties of gluten to achieve elastic and chewy texture. This study aims to optimize the formulation of gluten-free noodles using a combination of mocaf flour and rice flour through a quality engineering approach by integrating Taguchi Method, Grey Relational Analysis (GRA), and Principal Component Analysis (PCA). The Taguchi method was employed to design experiments involving two main factors—mocaf flour and rice flour—each with three levels. The observed responses were elongation (elasticity) and water absorption. As the study involves multiple quality responses, GRA was used to convert the results into a single value called Grey Relational Grade (GRG), while PCA was applied to determine objective response weights based on eigenvalues derived from the data variables. The experimental results indicated that the optimal combination was achieved with 150 grams of mocaf flour and 50 grams of rice flour (A2B2), with mocaf flour contributing the most to product quality at 71.27%. The integrated methodology effectively identified the optimal parameters without requiring repeated trial-and-error processes and produced consistently high-quality noodles. Statistical assumption tests confirmed that the data were normally distributed and homogeneous, validating the reliability of the ANOVA results. This integrated approach provides a systematic and objective solution to multiresponse optimization in food product development. The study not only contributes to the enhancement of gluten-free noodle quality but also promotes the broader utilization of local ingredients such as mocaf. By adopting this method, producers can efficiently refine their formulations and improve gluten-free product quality, offering a viable alternative to meet the modern market's preferences for gluten-free diets