Fungal growth can occur on green coffee beans along all the distribution chain, eventually bringing on health hazards to consumers, because of the production of toxic metabolites (mycotoxins) [1]. Besides, the sensorial contamination due to volatiles by-products of fungal metabolism could cause defects on coffee also after roasting. Therefore, it is necessary to devise strategies to detect and quantify fungal infection and toxin production at early stages of the food chain. One of the most promising techniques is the analysis of volatile compounds in the headspace gas surrounding the samples. The aim of this work was to verify the ability of the Electronic Nose (EN EOS(835)) to early detect the microbial contamination of Arabica green coffee. This EN is equipped with Metal Oxide Semiconductor sensor array. Gas chromatography coupled to mass spectrometry (GC-MS) analysis of the static headspace of non-contaminated Arabica green coffee samples was carried out to confirm the EN ability to provide satisfactory indications about the presence of contamination.