Analytical laboratories working in food and environmental testing rarely handle pristine samples. Instead, they analyze complex, variable matrices that place sustained demands on both instruments and workflows. According to Tarun Anumol, Director of Global Applied Markets at Agilent Technologies, robustness must be defined around real-world samples rather than idealized conditions.
Agilent’s approach to robustness builds on long-standing design improvements across GC-MS and LC-MS platforms, including advances in quadrupoles, ion optics, and electronics that support stable, long-term operation with challenging matrices. These developments help laboratories maintain consistent performance and data quality over extended use.
However, instrument design alone does not solve robustness challenges. Sample preparation, front-end handling, and data processing all influence system durability and uptime. By working closely with customers, Agilent takes a workflow-level view—addressing analytical challenges holistically rather than as isolated instrument issues.
For laboratories managing demanding applications, robustness emerges from aligning technology, workflow, and real sample needs.
