Analytical Solutions for Food Development

Importance of Topic

Reliable, objective evaluation of food texture, aroma, flavor and quality parameters is essential for modern product development and quality control. Instrumental analysis complements sensory testing by providing quantitative, reproducible data that support safer, more appealing food products and ingredients.

Objectives and Overview

This study reviews Shimadzu’s comprehensive analytical solutions tailored for food development. It surveys methods for measuring texture, particle structure, moisture, melting behavior, aroma, flavor compounds, metabolites, nutrients, minerals and color. Key objectives include illustrating practical workflows, highlighting example applications and demonstrating how these tools enable data‐driven decision making across R&D, QA/QC and regulatory compliance.

Methodology and Instrumentation

Analytical approaches and representative instruments:

• Texture analysis: compression, shear, penetration tests (EZ Test Texture Analyzer)
• Particle size & shape: laser diffraction (SALD-2300) and dynamic image analysis (iSpect DIA-10)
• Internal structure: non-destructive X-ray CT imaging (XSeeker 8000)
• Moisture content: thermogravimetric analysis (Moisture Analyzer MOC63u)
• Mouth-melt & phase transitions: Differential Scanning Calorimetry (DSC-60 Plus)
• Aroma profiling: headspace GC-MS (HS-20 NX TRAP + GCMS-QP2050), SPME Arrow and Smart Aroma Database
• Off-flavor detection: automated SPME GC-MS workflow with off-flavor database
• Flavor and functional compounds: HPLC (i-Series/Nexera), UHPLC with RF-20AXS fluorescence, LC-MS/MS (LCMS-TQ RX, LCMS-8050RX), multivariate analysis via Traverse MS and eMSTAT Solution
• Metabolomics: GC-MS/MS and LC-MS/MS with Smart Metabolites Database and Multi-omics Analysis Package
• Nutrient vitamins and amino acids: simultaneous HPLC/LC-MS and dedicated LC/MS/MS kits
• Mineral analysis: EDX-8100/ALTRACE X-ray fluorescence, ICP-MS (ICPMS-2040/2050), ICP-AES (ICPE-9800) and AAS (AA-7800)
• Color measurement: UV-VIS-NIR spectrophotometry (UV-3600i Plus) and colorimetry software
• Specialty separations: supercritical fluid chromatography (Nexera UC) and ELSD detection

Main Results and Discussion

Examples of key findings include:

• Machine learning models predicting sensory texture scores from EZ Test compression curves, enabling rapid objective predictions.
• Accurate particle size and shape distributions at realistic concentrations, linking microstructure to mouthfeel.
• 3D visualization of internal porosity in bakery products by bench-top X-ray CT.
• High‐precision moisture profiling of emulsions and complex matrices via moisture analyzer and automated reports.
• DSC characterization of chocolate polymorph melting and bread staling kinetics to optimize shelf life.
• Comprehensive aroma component mapping of almonds and beers enabling product differentiation and sensory optimization.
• Off-flavor identification in beverages by GC-MS/MS with database‐driven quantitation and odor threshold evaluation.
• Simultaneous quantitation of catechins in tea, bitter acids in beer, D/L amino acids and sugars in dairy and alcoholic beverages, illustrating compositional fingerprints.
• Wide‐target metabolomics distinguishing yeast strains and beer types through GC-MS/MS and LC-MS/MS coupled multivariate analysis.
• Simultaneous detection of water and fat‐soluble vitamins, essential minerals in infant formula, and trace hazardous elements meeting regulatory standards.
• Rapid colorimetric classification of vegetable juices, linking chromatic coordinates to consumer perception.

Benefits and Practical Applications

These methods deliver:

• Objective, quantitative data correlating with sensory attributes.
• High throughput and automation to accelerate R&D and QC workflows.
• Regulatory compliance via validated, reproducible assays.
• Scalable sampling from high‐concentration food matrices to trace contaminants.
• Enhanced product profiling and differentiation for branding and process optimization.

Future Trends and Potential Applications

Emerging directions include integrating AI/ML for predictive analytics, IoT connectivity for remote monitoring, real‐time on‐line SFE/SFC purification, expanded multi-omics platforms, virtual prototyping via digital twins and eco-friendly supercritical fluid extraction to reduce organic solvents.

Conclusion

By combining diverse analytical techniques with advanced software and databases, modern food development can transition from empirical to data‐centric workflows. This unified analytical ecosystem supports safer, tastier and more innovative products while meeting regulatory and consumer demands.

Instrumentation Used

Key instruments:

• EZ Test Texture Analyzer
• SALD-2300 Laser Diffraction Particle Size Analyzer
• iSpect DIA-10 Dynamic Particle Image Analysis System
• XSeeker 8000 X-Ray CT System
• MOC63u Moisture Analyzer
• DSC-60 Plus Differential Scanning Calorimeter
• HS-20 NX TRAP + GCMS-QP2050 Headspace GC-MS
• Nexera i-Series/UHPLC with RF-20AXS Fluorescence Detector
• LCMS-TQ RX, LCMS-8050RX Triple Quadrupole MS
• ICPMS-2040/2050 ICP-MS, ICPE-9800 ICP-AES, AA-7800 AAS
• EDX-8100/ALTRACE Energy Dispersive X-ray Fluorescence
• UV-3600i Plus UV-VIS-NIR Spectrophotometer
• Nexera UC Supercritical Fluid Chromatograph

References

• Nakano Y, Konya Y, Taniguchi M, Fukusaki E. Journal of Bioscience and Bioengineering 123:134–138 (2016).
• N. Iwata, M. Kobayashi. Chromatography 45:63–72 (2024).