Multifaceted Evaluation of Frozen Tempura Batter Coating Focusing on Food Texture

Importance of the Topic

Texture (mouthfeel) is a critical sensory attribute influencing consumer preference and product selection for coated fried foods. Objective, instrument-based evaluation of texture complements and reduces the variability of sensory panels, enabling reproducible, mechanistic understanding of how processing (here: heating method) alters structure, oil distribution, and mechanical response of batter coatings. Such multifaceted analysis supports targeted product development and quality control in food manufacturing.

Study Goals and Overview

This application study investigated how different heating protocols (microwave-only = "Moist" vs microwave plus oven = "Crisp") change the batter coating of frozen kabocha (Japanese winter squash) tempura. The aims were to (1) quantify textural differences with a texture analyzer, (2) visualize macroscopic and microscopic structural changes and coating thickness by X-ray CT, laser confocal microscopy and SEM, and (3) correlate structural/oil-distribution features with sensory and instrumental texture metrics to explain the origins of ‘moist’ versus ‘crisp’ mouthfeel.

Methodology

Samples: Commercial frozen kabocha tempura prepared either by 1 min microwave heating (Moist) or 1 min microwave plus additional oven heating (Crisp). Coating samples were excised for tests when required.

Texture analysis (mechanical test): Piercing test on Shimadzu EZTest with a 3 mm diameter plunger at 1 mm/s. Coating pieces cut to 20 × 20 mm and fixed in a jig. n = 10 per condition. Measured indices: maximum test force (hardness) and strain at maximum force (related to crispness/fracture behavior).

X-ray computed tomography (XSeeker 8000): Non-destructive 3D scan to observe internal structure, oil-rich regions and quantify coating wall thickness using VGSTUDIO MAX. Scan mode: Resin/Fine, 160 kV, 5 min, voxel size 0.1 mm.

Laser confocal microscope (OLS5500): Reflective confocal 405 nm laser imaging and white-LED color imaging to map surface color (oil-rich regions appear dark) and topography (arithmetical mean height Sa). Tile-stitching used for wide-area observation; objective 20×, ultra-high speed mode.

Scanning electron microscopy (SUPERSCAN SS-2000): Low-vacuum SEM (10 Pa H2O) to compare the same area before and after oven heating. Conditions: low-mag 25× (4.7 mm field), high-mag 300× (0.4 mm field), 15 keV accelerating voltage, 1 nA beam current. Secondary/backscattered electron imaging and EDS elemental mapping were used to assess oil distribution and surface morphology.

Instrumentation Used

• Texture analyzer: Shimadzu EZTest (piercing test, φ3 mm plunger)
• X-ray CT: Shimadzu XSeeker 8000 (Resin/Fine mode, 160 kV, voxel 0.1 mm)
• Laser microscope: Olympus OLS5500 (405 nm laser confocal, color imaging, topography, Sa measurement)
• Scanning electron microscope: Shimadzu SUPERSCAN SS-2000 (low-vacuum SEM with EDS)

Main Results and Discussion

Sensory evaluation (15 assessors, 100-point scale) confirmed the expected profiles: Moist sample had high moistness (avg 75.6) and low crispness (avg 12.7); Crisp sample showed the opposite pattern (moistness avg 42.9, crispness avg 73.9). Coefficients of variation indicated greater assessor spread for the Crisp moistness rating.

Texture analyzer results (n = 10): Moist coating exhibited low maximum force (hardness = 0.88 N) and high strain at maximum (227%), consistent with a soft, ductile, non-fracturing coating. Crisp coating showed substantially higher hardness (3.84 N, ~4.3× higher) and much lower strain at peak (80.6%), indicating brittle/fracture-prone behavior that corresponds to perceived crispness. Fine force fluctuations in the Crisp force-strain curves matched micro-fracture events linked to surface roughness.

X-ray CT findings: 3D scans revealed that the Crisp coating was overall thinner, with more voids, while the Moist coating was thicker and contained oil-rich regions visible as higher-attenuation contrast. Wall-thickness analysis (VR color maps and histograms) quantitatively confirmed a shift toward thinner coatings after oven heating. Oil-rich pockets seen in the Moist sample appeared reduced or absent in Crisp.

Laser microscopy: Color imaging identified oil-rich surface areas as dark/black regions; Moist surfaces exhibited extensive dark areas while Crisp showed more yellow (less oil). Topographic maps showed an increase in surface roughness and mean height after oven heating: Sa increased from 164.7 μm (Moist) to 199.6 μm (Crisp). Local heights in selected profiles rose from ~100 μm to ~500 μm in convex regions, indicating formation of protrusions that promote localized stress concentrations during biting.

SEM and EDS: High-magnification secondary electron images showed smooth surfaces with oil droplets on Moist samples and granular, convex microstructures on Crisp samples. Backscattered images corroborated the disappearance of oil-rich depressions in Crisp. EDS mapping in the Crisp sample revealed broad carbon distribution and locally reduced oxygen signal where oil had been concentrated previously, supporting the imaging-based assessment of oil redistribution or removal upon oven heating.

Integrated interpretation: Crispness arises from a combination of (i) reduced overall coating thickness with increased internal density, (ii) micro-scale surface roughening and protrusion formation that localize mechanical stress and favor brittle fracture, and (iii) decreased surface/oil content which reduces plasticizing effects and promotes fracture. Moist mouthfeel is associated with thicker, oil-rich coatings that deform rather than fracture under load.

Practical Benefits and Applications

• Objective metrics: Instrumental quantification (force, strain, Sa, wall thickness, oil distribution) provides reproducible proxies for sensory descriptors like moistness and crispness.
• Process optimization: Insights into how oven finishing reduces oil and modifies microstructure can guide heating profiles to achieve target textures.
• Formulation guidance: Knowledge of how coating thickness and oil content correlate with texture assists in recipe and batter composition development.
• Quality control: Non-destructive X-ray CT and laser microscopy can be incorporated for batch monitoring or failure analysis in R&D and QC labs.

Future Trends and Opportunities

• Correlative multimodal workflows: Performing mechanical tests directly on the same observed areas (post-imaging physical tests) will improve causal links between microstructure and mechanical response.
• Time-resolved and in-situ imaging: Real-time CT or microscopy during heating could capture transient oil migration, expansion and microstructural evolution.
• Higher-resolution and faster CT/optical systems: Improved voxel resolution and throughput enable more detailed void and oil-droplet analysis.
• Machine learning and image analytics: Automated classification of surface features and quantitative correlation with sensory scores can accelerate product optimization.
• Broader applications: Techniques extend to reformulation for lower-fat or alternative oils, plant-based coatings, shelf-life studies, and industrial QC implementation.

Conclusion

A combined instrumental approach—texture analysis, X-ray CT, laser confocal microscopy and SEM—successfully linked sensory perceptions of moistness and crispness in frozen tempura to measurable physical and structural properties. Crispness was associated with thinner, denser coatings, increased surface roughness and reduced oil content, whereas moistness correlated with thicker, oil-rich, deformable coatings. Multifaceted, correlative evaluation enables mechanistic understanding and actionable guidance for product design, processing and quality assurance.

Reference

Migita K., Koike N., Kogure A., Aoshima T. Multifaceted Evaluation of Frozen Tempura Batter Coating Focusing on Food Texture. Shimadzu Application Note. First Edition: Jul. 2026. Shimadzu Corporation. (Application note, authors and title as provided in the source.)