Experimental study demonstrates one-pot thermomorphic extraction and derivatization of fatty acids in food matrices, highlighting an automation-friendly alternative to manual workflows.
Conventional lipid extraction workflows (e.g., Folch or Bligh-Dyer) remain difficult to integrate into high-throughput automation because they rely on centrifugation, manual phase handling, and labor-intensive solvent-transfer steps. This study introduces a streamlined one-pot thermomorphic workflow that addresses these bottlenecks by exploiting the temperature-programmed phase behavior of a cyclohexane/methanol system with a literature upper critical solution temperature (UCST) of 45.5°C at x(MeOH) = 0.506. Heating above the UCST enables simultaneous thermal extraction and acid-catalyzed transesterification in a homogeneous single phase. Passive cooling then regenerates the biphasic state, partitioning fatty acid methyl esters (FAMEs) into a directly injectable cyclohexane-rich upper phase for gas chromatography–tandem mass spectrometry (GC–MS/MS) without centrifugation, solvent transfer, or evaporative concentration. The selected operating point (65°C, 20 min, φ = 0.50, defined before acetyl chloride addition) was obtained from multivariate screening with an inter-replicate relative standard deviation (RSD) of 2.45%. Calibration yielded linear responses for ten target FAMEs (R² ≥ 0.9672), with limits of detection of 0.070–2.3 mg L⁻¹ and limits of quantification of 0.24–7.8 mg L⁻¹. BCR-162R provided analyte-specific spike-recovery data for five C16–C18 FAMEs, with strongest agreement for C18:2n6-ME and defined limitations for C18:0-ME, C18:1n9-ME, and C18:3n3-ME. Application to six commercial food matrices demonstrated operational feasibility but also matrix- and target-panel-dependent quantitative limitations. NIST SRM 3275 defined the applicability boundary for long-chain polyunsaturated fatty acids (LC-PUFAs) in marine oil. AGREEprep benchmarking gave scores of 0.46 (default) and 0.64 (context-adjusted), indicating a resource-efficient, automation-compatible alternative to conventional lipid sample-preparation workflows.
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Wickneswaran et al. (2026) studied this question.
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