# Detection of Volatile Organic Compounds (VOCs) in Livestock Houses Based on Electronic Nose
###### Abstract  
The composition of volatile organic compounds (VOCs) in large-scale livestock farms is complex, which seriously affects the health of livestock and is difficult to evaluate. In order to quickly analyze the pollution degree of VOCs in livestock farms, electronic nose technology was used in this study to detect and analyze the gases in pig and chicken houses, respectively. Firstly, the gas chromatography-mass spectrometry (GC-MS) and electronic nose were used to analyze the VOCs in the pig and chicken houses at different time and locations. The types and relative contents of VOCs were obtained from different livestock farms by GC-MS analysis. The sensor array response of the electronic nose showed similar results. In addition, linear discriminant analysis (LDA), K nearest neighbor (KNN) and support vector machine (SVM) analyses were performed on the electrical signal that was generated by the sensors of electronic nose, respectively. Finally, the classification rate of different odor sources in livestock farms was the highest (>85%), which indicates that SVM is a more effective method suitable for volatile gases recognition in livestock farms. The results have shown that the developed electronic nose sensor is a promising and feasible instrument for characterizing volatile odors in livestock farms. electronic nose; livestock farms; VOC detection; odor identification +
Footnote †: journal:livestock houses using GC-MS [6]. However, it lacks portability, has a long analysis period, and is costly. Currently, it can only be used in the laboratory and cannot realize real-time online monitoring [7; 8]. An electronic nose is an instrument that mimics the mammalian olfactory system in sensory response and information processing, and it can be used for mixed gas evaluation [9]. The electronic nose system mainly includes a sensor array, a signal conditioning circuit, and a pattern recognition system that can recognize odors. It obtains multiple features from the dynamic response of each sensor and extracts the main characteristics of the odor under study. Finally, obtained information can be identified and judged through the pattern recognition system, and then a unique response will be generated for a specific odor sample [10]. In recent decades, electronic nose technology has developed rapidly and has been applied in many fields. According to the investigations, the research has been focused on food [11], medicine [12], and environmental detection [13; 14]. The electronic nose exhibits an excellent performance in distinguishing volatile organic compounds (VOCs) and volatile organic compound (VOC) mixtures [15]. _[PERSON]_ established an electronic nose model based on 24 metal oxide semiconductor sensors (MOSs), which can be used to predict the odor concentration in broiler sheds [16]. _[PERSON]_ created an odor distribution map of a chicken farm using electronic nose technology and distinguished the odor concentration in different sampling points in the chicken house and the farm [17]. _[PERSON]_ used an electronic nose to continuously monitor the odor of a fattening pig house [18]. The electronic nose is a low-cost, safe and fast detection technique, which does not damage the integrity of the sample. It is one of the most promising technologies for gas detection in livestock farms. However, the current research on volatile substances in livestock farms is mostly focused on the detection of single or several gas concentrations [19], the source of volatile substances [20], the law of odor pollution diffusion [21], protection distance and pollution control [22], etc. There are few rapid detections and comprehensive evaluations of volatile substances in different times and spaces of different livestock farms. Our previous studies have found that the e-nose can effectively identify gases from inside and outside a pigsty at different times, but we have not studied the odor from different locations in the piggery and the chicken house [23]. This paper takes pig and chicken houses as representatives.