RAFA 2021: High-Throughput Analysis of Freshness Markers in Various Food Samples by SIFT-MS

Consumer acceptance and food safety are key for wholesalers and retailers of fresh fruit, vegetable, fish or meat products. Although consumers provide the ultimate feedback on quality, suitable instrument-based methods can provide rapid analysis, objectivity and low costs per sample, which are not always possible using human subjects.

During ripening, fruits emit a diverse range of low molecular weight compounds arising from various hormonal and metabolic processes. The relative abundances of these volatiles change over time and are detected, quantified and monitored in a high-throughput manner by SIFT-MS.

SIFT-MS (Selected Ion Flow Tube Mass Spectrometry) is a very rapid, direct, and sensitive technique with detection limits matching those of human olfactory system and minimal samples preparation. Therefore, it is ideal for detecting spoiling of food at an early stage and for a wide-scale and high-throughput freshness screening.

SIFT-MS uses soft, precisely controlled chemical ionisation coupled with MS detection to rapidly quantify VOC down to pptv concentrations. For this study, it was combined with a headspace autosampler (Gerstel). Since no front-end separation but a direct analysis of all samples is performed, the setup provides a robust, easy to operate solution for sensitive, quantitative screening of hundreds of samples per day.

Presenter: Dr Vaughan Langford (Principal Scientist, Syft Technologies, New Zealand)

After completing his PhD in Physical Chemistry at the University of Canterbury, he performed post-doctoral fellowships at the University Geneva and the University of Western Australia. With an extensive background and over 20 peer-reviewed publications in diverse applications of SIFT-MS, he provides advanced applications development and support to SIFT-MS users globally.