Electronic nose, which is designed to perceive artificially the odour-active molecules in a sample headspace, has seen an increased use in the food industry as a rapid and reliable tool for quality assessment, classification, and authentication of several food items. The use of chemometrics and pattern recognition methods, together with gas sensors, emerged to be a very powerful analytical approach. In this chapter, an overview of the recent achievements in the field of electronic nose applications on animal-source food is given. Moreover, the authors deal with the recent research trends to overcome the actual sensor shortcomings, including sensor fusion techniques and their applications to evaluate animal-source foods and novel electronic nose systems.
TopBackground
In order to grant an adequate level of quality and safety, all food products need to be subjected to several analysis steps. In addition, to compete effectively in the marketplace, food companies must produce foods that meet consumers’ expectation of safe, nutritious and high-quality food products (Di Rosa et al., 2017). Moreover, attention must be paid to the government regulations and to the policies and standards of international organizations (Nielsen, 2010).
Generally, food quality is specified in terms of traceable origin, known chemical composition, commensurate physical properties, satisfactory sensory evaluation, safety and health safeguards with respect to microbiological and toxic contamination, and is influenced by the processing and storage (Borras et al., 2015). Once food has been authenticated, the main technique for quality assessment, from the consumer point of view, is the sensory analysis, which is based on the evaluation of the attributes perceptible by the five sense organs, and allows establishing the organoleptic profile of the diverse products (Piana et al., 2004). This method, however, suffers from several disadvantages, being considered time-consuming and expensive, subjective (depending upon the professional acumen of the personnel involved) (Kiani et al., 2016), inconsistent and unpredictable, due to various human factors (Banerjee et al., 2016), and requires a panel of skilled assessors. Consequently, despite the extreme importance of aroma as an indicator of quality and product conformity, monitoring of food products is mainly performed via physicochemical measurements, due to the lack of reliable odour assessing instruments (Ampuero and Bosset, 2003). Conventional standard methods for gas analysis usually rely on the utilization of precision laboratory instruments like headspace gas chromatography (HGC) and two-dimensional gas chromatography using different types of detectors, for example, mass spectrometry coupled to olfactometry (Wardencki et al., 2009). These methods, providing an accurate approach for the analysis of type and concentration of the single component in a mixture of substances, may be considered a useful sensorial tool for food odour analysis. However, they are laborious and time-consuming, require considerable analytical skills, involve a lot of tedious and complex pre-treatment of samples, and use many hazardous organic reagents (Huang et al., 2015).
In the last two decades, much research has been performed to substitute the perception of human senses with artificial systems, providing signals related to the sensory attributes (Di Rosa et al., 2017). In this regard, advances in sensor technology, microelectronics and artificial intelligence led to the development of instruments such as the electronic nose (E-nose), capable of measuring and characterizing the odour of various products (Wilson and Baietto, 2009; Ghasemi-Varnamkhasti et al., 2011; Cubero et al., 2011). E-noses have been used in various research fields; however, the most attention has been paid to the food industry. Particularly, this technology has been employed for quality control of raw and manufactured products: process, freshness and maturity monitoring, shelf-life investigations, authenticity assessments of premium products and microbial pathogen detection (Schaller et al., 1998). In conclusion, the aim of this chapter is to give an overview of the most important, recent achievements in the field of E-nose applications, with regards to the assessment of animal source food products.