Tracing the origin of food using MC-ICP-MS

Significance of the topic

Tracing food origin is critical to verify regional labelling schemes and protect both producers and consumers against fraud. Strontium isotopic fingerprinting provides a direct link between agricultural produce and the underlying geology offering high selectivity even among neighboring regions beyond classical light stable isotope methods.

Objectives and Overview

This study demonstrates the use of multicollector ICP MS analysis of strontium isotopes combined with multi element and light stable isotope data to classify apples and cereals from protected designation areas and non indicated sites in Northern Italy. Two case studies address apple varieties under PDO PGI schemes and cereal grains from South Tyrol and adjacent regions.

Methodology

• Sampling strategy
  • Collection of Golden Delicious apples and other varieties from Val di Non PDO South Tyrolean PGI Valtellina PGI and non indicated districts alongside rye and spelt from South Tyrol Trentino and Tyrol with corresponding soil sampling at root depth yielding over 1200 samples
• Sample preparation
  • Microwave assisted nitric acid digestion for plant matrices and buffer extraction for bioavailable soil fraction
  • Oven drying of apple pulp and high temperature pyrolysis for hydrogen and oxygen isotope analysis
• Strontium separation and analysis
  • Sr specific ion exchange chromatography followed by 87Sr86Sr measurement on Neptune Plus MC ICP MS using sample bracketing and NIST SRM 987 for mass bias correction and interference adjustments
• Multi element profiling
  • Quantification of 20 plus trace elements by iCAP Q ICP MS to enhance discrimination models

Instrumentation

• Neptune Plus MC ICP MS for high precision strontium isotope ratios
• iCAP Q ICP MS for trace element quantification
• TC EA coupled to DELTA V Advantage IRMS for hydrogen and oxygen isotopes

Main results and discussion

A strong linear correlation (R gt0.98 p lt0.001) between soil and crop 87Sr86Sr ratios confirmed direct transfer of geological signature. No significant isotope fractionation was found among apple cultivars or cereal species. Linear discriminant models combining strontium isotope data with element ratios such as CaBa SrBa and element concentrations including Rb Fe and Mo achieved over 90 percent classification accuracy for regional origin.

Benefits and Practical Applications

• Objective authentication of high value horticultural products
• Support for compliance with PDO PGI labelling regulations
• Deterrence of fraud and protection of regional brand equity
• Applicability across diverse crops and food matrices

Future Trends and Potential Applications

• Integration of lead and boron isotope systems for comprehensive provenance markers
• Advances in pre MS matrix removal to enable direct analysis without complex column chemistry
• Expansion of regional reference databases to refine classification at finer geographical scales
• Workflow driven software and automation to accelerate routine adoption in QC laboratories

Conclusion

Strontium isotope analysis by multicollector ICP MS combined with multi element and light stable isotope data represents a robust approach for food provenance. It delivers high confidence classification at regional level supporting authenticity and quality control for premium labelled products.

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