Advances and Challenges in Sensory Evaluation of Food: Bridging Traditional Methods With Digital Innovation for Sustainable Food Systems

Sensory evaluation has developed to be more than a subjective taste-testing approach and a multidimensional science that incorporates psychophysics, digital technologies, and data analytics. This review covers and examines methodological advances in line with classical hedonic and descriptive methods, as well as modern methods of using AI to predict and multisensory virtual experiments. Particular attention is given to how rheological, tribological, and AI-driven approaches are advancing the objective and predictive assessment of food texture and mouthfeel, in line with the scope of texture-focused research. This paper explains how sensory evaluation can be used to develop products, assure quality, and conduct consumer research; where it plays a pivotal role in ensuring sustainable and health-focused product development. New developments like machine learning and the integration of omics and digital sensory systems have transformed how products are designed by connecting the molecular structure to human sensations. Although significant improvements have been made, the subjectivity, cultural bias, data heterogeneity, and reproducibility are still issues. The review highlights the importance of aligning protocols, working interdisciplinary, and automation as the means of improving the predictive ability of sensory science. The suggested directions in the future are focused on personalized nutrition, introducing a circular economy, and models of human-AI hybrid in real-time, sustainable food innovation.