Evaluation and identification of markers of damage in mushrooms (Agaricus bisporus) postharvest using a GC/MS metabolic profiling approach

The aim of this research was to use the gas chromatography-mass spectrometry (GC/MS) profiling method coupled with chemometric tools to profile mechanically damaged and undamaged mushrooms during storage and to identify specific metabolites that may be used as markers of damage. Mushrooms grown under controlled conditions were bruise damaged by vibration to simulate damage during normal transportation. Three damage levels were evaluated; undamaged, damaged for 20 min and damaged for 40 min and two time levels studied; day zero and day one after storage at 4ºC. Applying this technique over 100 metabolites were identified, quantified and compiled in a library. Random forest classification models were used to predict damage in mushrooms producing models with error rates of >10% using cap and stipe tissue. Fatty acids were found to be the most important group of metabolites for predicting damage in mushrooms. PLS models were also developed producing models with low error rates. With a view to exploring biosynthetic links between metabolites, a pairwise correlation analysis was performed for all polar and non-polar metabolites. The appearance of high correlation between linoleic acid and pentadecanoic acid in the non-polar phase of damaged mushrooms indicated the switching on of a metabolic pathway when a mushroom is damaged.