Mechanical Characterization of Crispness in Dry Foods via Multi Specimen Compression Testing

Abstract

Texture is a critical quality attribute of dry snack foods, with crispness being especially important for consumer enjoyment. However, crispness is often judged subjectively by sensory evaluation, leading to ambiguity and inconsistency. This study develops a quantitative mechanical method to characterize crispness in dry foods using a multi-specimen uniaxial compression test that simulates human biting. Cassava chips (at three slice thicknesses) and a traditional dried Sus cake were tested in batches within a custom container under identical conditions. Statistical analysis (ANOVA) confirmed that these parameters notably differentiate samples (at P < 0.20 level) and correlate with sensory crispness rankings. The thinnest cassava chips (1 mm) exhibited the highest crispness (lowest energy and slope, highest jaggedness), whereas thicker chips were less crisp. Notably, the dried Sus cake, despite its different origin, showed higher crispness metrics than even the thinnest cassava chips, aligning with sensory perception. These results demonstrate that the proposed multi-specimen compression test can quantitatively distinguish crispness levels in foods of irregular shape. This study offers a qualitative data of crispiness on multi-specimen basis for specimen with random shapes by using the uniaxial compression test with two parallel plates. The key variables taken into account are the strain energy, mean slope of the stress-strain curve, and the jaggedness of the load-displacement curve.