## 1 Introduction  
Fungal contamination plays a major role in food spoilage and represents a problem which can result in huge economic losses, deterioration of food quality, reduction in nutrients availability, and contamination with compounds with high potential toxicity, such as mycotoxins [1]. Mycotoxins are secondary metabolites produced by fungi that have adverse health effects on humans, animals, and crops. In this sense, prevention and control of these toxicine fungi and mycotoxins in agricultural commodities have been priority objectives in food quality and safety [2; 3; 4]. Among different classes of food which are susceptible to fungal infection, table grapes are a very common case due to their thin pericarp and succulent flesh. Thus, grapes can be easily contaminated with filamentous fungi in different steps across their production chain and for this reason, the quality control of table grapes must be very strict and effective [5; 6]. Some of the most relevant species related to the fungal infection of grapes are members of the genus Aspergillus [5]. _Aspergillus niger_ is one of the main species responsible for contamination in grapes and derived products, causing serious economic losses, with the distribution of black aspergillus in table grapes reported worldwide [6; 7; 8]. The production of mycotoxins by _A. niger_ is well known but the contribution to mycotoxin content in foodstuffs as well as the differences in production among species are controversial topics. Ochratoxin A is one of the metabolites usually associated to contamination by _A. niger_[9; 2; 10; 11], including in grapes [7]. However, as it is not specific for this species, it therefore cannot be used as an unambiguous biomarker. On the other hand, recent studies reported a set of metabolites that may be assigned as _A. niger_ biomarkers [12; 13; 14]. These metabolites are distributed in several chemical families, such as aldehydes, ethers, alcohols, esters, ketones, hydrocarbons, and terpenic compounds. Metabolic pathways such as amino acid metabolism, biosynthesis and metabolism of fatty acids, degradation of aromatic compounds, mono and sesquiterpenoid synthesis, and carotenoid cleavage are found to be related to these set of compounds [14]. Nevertheless, studies on production of these metabolites specifically by _A. niger_ have still not been completely explored [14; 15]. Considering the importance of early diagnosis in food authentication and contamination, metabolomics enables the development of rapid and highly accurate chemical methods for the identification of the species [9; 16; 17; 18; 19; 20; 21; 22]. Microbial metabolomics represents a holistic approach for comprehensive monitoring of metabolites directly linked to cellular metabolism, providing an accurate snapshot of the microorganism metabolic profile and can be potentially useful for early detection [23; 24; 25; 26; 27; 28]. Untargeted microbial metabolomic approaches using mass spectrometry or mass spectroscopy-based analytical platforms have become extremely important in the last few years [13; 29; 30]. Although it is very informative whole metabolome studies can provide a huge volume of data, when it comes to detection of food contamination, only a partial and significant fraction of the metabolic profile is useful and desirable in order to detect the contaminant [13; 14]. However, access to properly interpretable data from a specific microbe's metabolite profile can be a real challenge due to the complexity of these samples. Therefore, the use of high throughput and highly sensitive tools like comprehensive two dimensional gas chromatography (GC\(\times\)GC) has been used in order to explore and extract useful data from microbial metabolome [22; 27; 31; 32; 33; 34; 35; 36; 37]. GC\(\times\)GC provides higher sensitivity and resolution when compared to conventional one-dimensional gas chromatography (\({}^{1}\)D-GC), which fulfils the requirements for the analysis of complex biological samples.