Traditional media fill inspection relies heavily on manual visual inspection, a slow and labor- intensive process. With laser-based headspace analysis, it is possible to directly detect microbial growth inside sealed containers. This opens the way for automation of this crucial inspection step.

The analytical approach to detection of growth using non-destructive laser-based headspace analysis is demonstrated in this scientific article using compendial microorganisms such as Staphylococcus aureus, Bacillus subtilis, Candida albicans, and Aspergillus brasiliensis.

Their gas-exchange patterns were mathematically modeled using the Baranyi-Roberts equation,
enabling precise, quantitative comparisons to known microbial growth curves.

Because the method can be fully automated, the analysis of hundreds of vials per minute becomes a possibility.

Discover the full methodology, data modeling, and experimental results.