PLS-R modeling and sensory optimization of functional brownies formulated with spinach and modified cassava flour
DOI:
https://doi.org/10.33830/fsj.v6i1.11850.2026Abstract
This study investigates the complex sensory dynamics of functional brownies formulated with wheat flour, modified cassava flour (mocaf), and spinach powder. The novelty of this research lies in the application of Partial Least Squares Regression (PLS-R) to decode the non-linear interactions and structural trade-offs within a gluten-free matrix, a departure from traditional linear sensory analysis. Formulations varied in flour composition (70-0% wheat, 25-95% mocaf, and 5-10% spinach powder), and were evaluated by 70 untrained panelists using a 7-point hedonic scale. Statistical modeling was performed using R Studio (v2024.12.1+563) with the pls, tidyverse, and plsVarSel packages. Results revealed that the PLS-R model effectively identified wheat flour as the primary driver for texture (VIP=1.343) and aroma (VIP=1.300). Despite low explanatory power (R2 < 1.5%), the model successfully mapped the antagonistic relationship of spinach antioxidants towards flavor formation and the significant textural compromises in high-mocaf substitutions. These findings provide a multivariate framework for optimizing functional bakery products, emphasizing that wheat remains essential for sensory integrity at substitution levels above 40%.
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