RIASSUNTO
Abstract
Crusted crispness refers to coatings with a dry and brittle surface contrasting a high‐moisture core; it is desirable for the enjoyment and quality of deep‐fried goods. This study aims to investigate instrumental measurements and sensory measurements of crispness. Deep‐fried breadcrumb coatings of eight sizes were investigated: 4.0 mm, 2.8 mm, 2.0 mm, 1.4 mm, 1.0 mm, 710 μm, 500 μm, and 355 μm. Sensory profiling was carried out to develop a tailored lexicon for deep‐fried battered and breaded shrimp. Principal component analysis highlights that large breadcrumb sizes correlate with crispness, hardness, particle size, surface color, color uniformity, surface irregularity, total porosity, maximum force, area, drop in force, number of sound peaks, and sound pressure level. Agglomerative hierarchical clustering was used to confirm clustering of samples according to breadcrumb size. Multiple factor analysis confirmed overall correlation between sensory measurements and instrumental measurements (RV = 0.810). Partial least squares regression was used to develop a predictive model for crispness from instrumental measurements (R2 = .854). The use of texture analysis and Acoustics provide information of the structures strength and deformation behavior, while X‐ray microCT provides a high resolution and noninvasive method that acquires information on the internal morphology. These instrumental methods collectively demonstrate the relationship between microstructure to sensory. This study investigates how a change in the microstructure of deep‐fried battered and breaded coatings affect crispness perception. These changes were investigated analytically and by using a sensory panel, this is important from a manufacturing perspective in order to understand what the major contributors are to a crisp texture. The key highlights of this study include both instrumental measurements and sensory measurements can be used to measure crispness as both types of testing are correlated. Changes in the size of breadcrumbs affect both instrumental measurements and sensory measurements. A predictive model can be re‐simulated to allow prediction of crispness in deep‐fried battered and breaded coatings.