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Crispness is a sensory attribute commonly associated with dry and brittle food materials and is related to the interaction between structural characteristics, mechanical fracture, and acoustic emission. Its interpretation spans multivariable domains due to the coupled nature of these phenomena and their dependence on composition and microstructure. In this study, crispness is described as a dimensionless number derived from the relationship between mechanical and acoustic energy during fracture. Mechanical energy input was obtained from force-displacement curves measured in compression tests using a dental prosthesis, while acoustic energy release was estimated from fracture sounds recorded at high sampling rate and analyzed using Short-Time Fourier Transform (STFT) and power spectral density. Based on these quantities, the Crispness Index (CI) was defined as the ratio between acoustic and mechanical energy, representing the fraction of mechanical work associated with sound emission. Six commercial food products with different structures and processing routes, including baked, fried, and extruded systems, were evaluated. The results show that CI reflects differences in fracture behavior across these materials, including cases in which low mechanical resistance is associated with higher acoustic emission. These observations indicate that crispness is related to the manner in which stored energy is released during fracture. A dimensionless model was also formulated based on the Buckingham Pi theorem, incorporating porosity, moisture content, geometric ratios, and stress parameters. The model presented consistent trends, with porosity showing a strong influence on the relationship between mechanical dissipation and acoustic emission. Multivariate analysis supported the association between structural properties and fracture response. The proposed approach provides a consistent basis for describing crispness in food materials and may support further developments in process and product design. This study was supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil, under Grant No. 400982/2025-0.
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