Recent advances for the use of colorimetric sensor arrays, near‐infrared and mid‐infrared spectroscopy in the quantitative analysis of volatile organic compounds in peanut seeds

Abstract

Abstract BACKGROUND A first‐of‐its‐kind method for quantitatively determining volatile organic compounds (VOCs) in peanut seed samples was developed and implemented utilizing a colorimetric sensor array (CSA), as well as near‐infrared (NIR) and mid‐infrared (MIR) spectroscopy, both independently and in conjunction, in addition to chemometrics, to address the unreliability of single technologies for detection of VOCs in peanut seed samples. The developed method was tested to see whether it could quantitatively analyze VOCs in peanut seed samples. RESULTS The compounds were isolated utilizing gas chromatography–mass spectrometry following extraction through solid phase microextraction. To quantitatively analyze the abundant VOCs in peanut seed samples, six calibration models were developed. CSA with NIR showed the best predictive models for 2‐furanmethanol ( R p = 0.9096), hexanoic acid ( R p = 0.9111), benzaldehyde ( R p = 0.9268), 2,3‐dimethylpyrazine ( R p = 0.9697), 2‐pentylfuran ( R p = 0.9563) and 2‐pyrrolidinone ( R p = 0.8641). The results achieved with NIR spectroscopy combined with CSA are superior to those obtained with MIR spectroscopy. CONCLUSION The results obtained in the present study showed that the developed multi‐technology fusion system can quickly and quantitatively predict VOCs in peanut seed samples of different varieties, and the NIR combined with the CSA system has the best prediction effect. © 2025 Society of Chemical Industry.