High Efficiency in Multi-Sample Analysis by Automatic Analysis System of LabSolutions™ UV-Vis
Applications | 2020 | ShimadzuInstrumentation
UV-Vis spectrophotometry plays a key role in routine inspection of raw materials and QA/QC across industries. Automating repetitive quantitative analyses reduces manual workload, increases throughput, and minimizes human error.
This application note demonstrates how Shimadzu’s LabSolutions UV-Vis software, combined with Teledyne CETAC autosamplers ASX-280/ASX-560, automates the full workflow of quantitative UV-Vis analysis—from calibration curve generation to pass/fail judgments—using a red food coloring model.
The software interface allows visual setup of sequences for standard (S), rinse (R), and sample injections, with options for baseline correction and prewash.
Automated analysis of 5 standards and 20 quantitation samples yielded concentration results and pass/fail judgments within the range of 105–115 ppm. Three intentionally deviated samples were correctly flagged as “fail.” Automation halved the analysis time from ~60 minutes (manual) to ~30 minutes.
Automation of UV-Vis analyses is expected to expand into multi-wavelength kinetics, high-throughput screening in pharmaceutical and food industries, and integration with LIMS for end-to-end data management. Enhanced software intelligence may enable real-time monitoring and adaptive QC decision-making.
Implementing LabSolutions UV-Vis with an integrated autosampler streamlines quantitative spectrophotometric workflows, delivering consistent results, significant time savings, and efficient pass/fail evaluation. This approach supports high-throughput laboratories in achieving robust QA/QC performance.
Sample Preparation, UV–VIS spectrophotometry
IndustriesManufacturerShimadzu, Teledyne LABS
Summary
Significance of the Topic
UV-Vis spectrophotometry plays a key role in routine inspection of raw materials and QA/QC across industries. Automating repetitive quantitative analyses reduces manual workload, increases throughput, and minimizes human error.
Objectives and Study Overview
This application note demonstrates how Shimadzu’s LabSolutions UV-Vis software, combined with Teledyne CETAC autosamplers ASX-280/ASX-560, automates the full workflow of quantitative UV-Vis analysis—from calibration curve generation to pass/fail judgments—using a red food coloring model.
Methodology and Instrumentation
- Instrument: Shimadzu UV-1900i UV-Vis spectrophotometer
- Autosampler: Teledyne CETAC ASX-280 (120 vials) or ASX-560 (240 vials)
- Measurement wavelength: 505 nm; slit width: 1 nm
- Suction speed: high; suction time: 6 s; discharge time: 4 s; stabilization time: 2 s
- Rinse cycles: 1; accessory: 160 μL sipper unit
The software interface allows visual setup of sequences for standard (S), rinse (R), and sample injections, with options for baseline correction and prewash.
Main Results and Discussion
Automated analysis of 5 standards and 20 quantitation samples yielded concentration results and pass/fail judgments within the range of 105–115 ppm. Three intentionally deviated samples were correctly flagged as “fail.” Automation halved the analysis time from ~60 minutes (manual) to ~30 minutes.
Benefits and Practical Applications
- Time savings: up to 50% reduction in routine analysis time
- Scalability: up to 240 samples per run with ASX-560
- Reduced manual errors through standardized workflows
- Easy data export via CSV and copy/paste for report generation
Future Trends and Potential Uses
Automation of UV-Vis analyses is expected to expand into multi-wavelength kinetics, high-throughput screening in pharmaceutical and food industries, and integration with LIMS for end-to-end data management. Enhanced software intelligence may enable real-time monitoring and adaptive QC decision-making.
Conclusion
Implementing LabSolutions UV-Vis with an integrated autosampler streamlines quantitative spectrophotometric workflows, delivering consistent results, significant time savings, and efficient pass/fail evaluation. This approach supports high-throughput laboratories in achieving robust QA/QC performance.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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