Fully Automated Preparation and Analysis of Fatty Acid Methyl Esters Using the FOCUS Sample Processing Robot
Applications | | GL SciencesInstrumentation
The derivatization of fatty acids into methyl esters is a cornerstone in lipid analysis by gas chromatography. Traditional methods such as BF3-methanol require extensive manual handling, high volumes of reagents and solvents, and lengthy extraction steps. Implementing a fully automated workflow enhances reproducibility, reduces operator time, lowers running costs, and allows continuous operation, meeting the growing demand for high-throughput lipid profiling in research and industry.
This study evaluates the performance of a fully automated sample preparation and analysis protocol using the FOCUS Sample Processing Robot in conjunction with GC-FID. The goals were to compare the automated sodium methoxide method to the classical BF3 approach, assess precision across diverse oil matrices, and demonstrate suitability for routine fatty acid methyl ester (FAME) analysis.
The automated protocol involves:
Used Instrumentation:
Precision studies on coconut oil showed relative standard deviations (RSD) below 3.4 % for major fatty acids and comparable performance for minor components. Analysis of the BCR 164 reference oil confirmed certified value alignment within analytical uncertainty. Chromatographic profiles across olive, rapeseed, margarine and other oils demonstrated clear separation of saturated and unsaturated FAMEs, with no significant carry-over or reagent artifacts.
The automated system delivers:
These advantages are particularly valuable in quality control laboratories, research facilities, and industrial settings requiring robust lipid profiling.
Advancements may include integration with mass spectrometry detectors for detailed lipidomics, automated data processing using machine learning algorithms, and expansion to other polar lipid classes. Coupling robotic platforms with digital laboratory management systems will further streamline workflows and ensure traceability in regulated environments.
The fully automated FOCUS sample processing workflow matches or exceeds the performance of classical BF3-based methods, offering significant gains in throughput, reproducibility and cost efficiency. Adoption of this approach supports modern analytical demands for high-volume, reliable fatty acid analysis.
GC, Sample Preparation
IndustriesFood & Agriculture
ManufacturerAgilent Technologies, GL Sciences
Summary
Significance of the Topic
The derivatization of fatty acids into methyl esters is a cornerstone in lipid analysis by gas chromatography. Traditional methods such as BF3-methanol require extensive manual handling, high volumes of reagents and solvents, and lengthy extraction steps. Implementing a fully automated workflow enhances reproducibility, reduces operator time, lowers running costs, and allows continuous operation, meeting the growing demand for high-throughput lipid profiling in research and industry.
Objectives and Study Overview
This study evaluates the performance of a fully automated sample preparation and analysis protocol using the FOCUS Sample Processing Robot in conjunction with GC-FID. The goals were to compare the automated sodium methoxide method to the classical BF3 approach, assess precision across diverse oil matrices, and demonstrate suitability for routine fatty acid methyl ester (FAME) analysis.
Methodology and Instrumentation
The automated protocol involves:
- Weighing ~10 mg of lipid sample into an autosampler vial and dissolving in 1 mL n-hexane
- Adding excess sodium methoxide reagent followed by agitation
- Allowing phase separation before drawing 1 µL of the upper hexane layer for injection
Used Instrumentation:
- ATAS FOCUS Sample Processing Robot
- ATAS OPTIC Programmable Injector
- Hewlett-Packard HP6890 GC with Flame Ionization Detector
- Hewlett-Packard ChemStation data system
- HP-23 Cis/Trans capillary column (30 m×0.20 mm×0.25 µm)
Main Results and Discussion
Precision studies on coconut oil showed relative standard deviations (RSD) below 3.4 % for major fatty acids and comparable performance for minor components. Analysis of the BCR 164 reference oil confirmed certified value alignment within analytical uncertainty. Chromatographic profiles across olive, rapeseed, margarine and other oils demonstrated clear separation of saturated and unsaturated FAMEs, with no significant carry-over or reagent artifacts.
Benefits and Practical Applications
The automated system delivers:
- High sample throughput through 24-hour unattended operation
- Consistent derivatization and extraction, improving reproducibility
- Reduced reagent consumption and waste, lowering disposal costs
- Minimal manual intervention, freeing analyst time for data interpretation
These advantages are particularly valuable in quality control laboratories, research facilities, and industrial settings requiring robust lipid profiling.
Future Trends and Applications
Advancements may include integration with mass spectrometry detectors for detailed lipidomics, automated data processing using machine learning algorithms, and expansion to other polar lipid classes. Coupling robotic platforms with digital laboratory management systems will further streamline workflows and ensure traceability in regulated environments.
Conclusion
The fully automated FOCUS sample processing workflow matches or exceeds the performance of classical BF3-based methods, offering significant gains in throughput, reproducibility and cost efficiency. Adoption of this approach supports modern analytical demands for high-volume, reliable fatty acid analysis.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
Similar PDF
Automating the Analysis of Mineral Oils in Water as according to ISO/DIS 9377-4 Using the Focus Sample Processing Robot
|Thermo Fisher Scientific|Applications
Application Note No. 014 Automating the Analysis of Mineral Oils in Water as according to ISO/DIS 9377-4 Using the Focus Sample Processing Robot. Oliver Lerch & Dr. P. Zinn, Department of Analytical Chemistry, Ruhr University of Bochum, Germany Comparison of…
Key words
damaging, damagingrobot, robotwater, waterorganic, organicsample, samplemineral, mineraltphs, tphsgcq, gcqpetroleum, petroleumoils, oilsconcentraion, concentraionphase, phaseproposition, propositionfocus, focushydrocarbons
Automated Determination of Fatty Acid Methyl Ester and Cis/Trans- Methyl Ester Composition of Fats and Oils
|Agilent Technologies|Applications
Application Note No. 061 Automated Determination of Fatty Acid Methyl Ester and Cis/TransMethyl Ester Composition of Fats and Oils Sjaak de Koning. Fully automated sample preparation and injection 24 hour, unattended operation Instrumentation Optic…
Key words
focus, focusshakes, shakesvial, vialadds, addstransmethyl, transmethylmethanolate, methanolateester, esterlipid, lipidsettle, settleinjects, injectsrobot, robotautomated, automatedfats, fatsdissolve, dissolvesample
Automating the Analysis of Selected Phenols Using The Focus Sample Processing Robot
|Agilent Technologies|Applications
Application Note No. 017 Automating the Analysis of Selected Phenols Using The Focus Sample Processing Robot Bob Green Introduction Phenols are currently prepared in using a traditional solvent extraction technique. The method involves the simultaneous extraction and derivatisation of selected…
Key words
robot, robotphenols, phenolsderivatising, derivatisingpentafluorobenzoyl, pentafluorobenzoylfocus, focusbob, bobatas, atasderivatisation, derivatisationxyz, xyzscales, scalesselected, selectedprocessing, processingpentachlorophenol, pentachlorophenolautomating, automatingbuffered
Testing the Performance of the Focus Direct-TD with Real Samples
|Agilent Technologies|Technical notes
Application Note No. 063 Testing the Performance of the Focus Direct-TD with Real Samples Diane Nicholas. Introduction The Focus Direct-TD is an automated thermal desorber. It uses the Focus autosampling robot to automatically exchange special packed sample tubes, SepLiners, held…
Key words
volts, voltsfocus, focusdtd, dtdcarryover, carryoverliners, linersminutes, minutesvolatiles, volatilesorganisations, organisationsdesorption, desorptionautosampling, autosamplingliner, lineratas, atasarea, areathermal, thermalcontamination