# Advancements and Prospects of Electronic Nose in Various Applications: A Comprehensive Review
## 3 Application Areas
### Disease Diagnosis
#### 3.3.2 Veterinary-Wildlife Pathology
Among the infectious diseases affecting wildlife, White Nose Syndrome (WNS) stands out as a significant affliction targeting Nearctic cave-dwelling bats [183]. This virulent malady has precipitated remarkable declines in bat populations, even reaching an alarming 99% reduction [184]. Its origins are traced back to the nonnative dermatophytic fungus Pseudogymnoascus destructans (Pd) [185,186]. This pathogenic agent triggers a cascade of detrimental consequences in bats, encompassing dehydration, starvation, riboflavin-induced dermal and hypodermal necrosis, membranous wing disintegration, physiological shocks, and hypothermia (Figure 9). The affliction compels WNS-affected bats to venture outside of Pd-infested caves during the winter, exacerbating their already dire circumstances [187, 188, 189]. The repercussions of WNS extend beyond the realm of wildlife conservation, given that insectivorous bats play an indispensable role in controlling agricultural pests and curtailing the propagation of disease vectors. Figure 9: Lesions on the skin of a bat due to _P. destructans_ (license: common use). Nevertheless, the existing diagnostic methods for WNS are intrusive and post-mortem in nature, often conducted after the onset of clinical symptoms. This temporal gap hampers the swift implementation of therapeutic interventions. Hence, there is an undeniable urgency for enhancing early detection techniques that facilitate management interventions before symptomatic manifestations arise. These advancements are pivotal for effective disease control and the successful execution of mitigation strategies. [PERSON] et al. [191] significantly contributed to assessing the C-320 electronic nose (e-nose) for differentiating bat species through their VOC emissions. This study captured healthy bats from nine species, collecting VOCs with new portable devices. By comparing sensor-array responses to bat VOCs and pure standards, unique smell print signatures were generated. Two-dimensional and three-dimensional principal component analysis (PCA) created aroma map plots, revealing notable species discrimination. The study suggests the e-nose's potential for detecting species-specific VOC metabolites, crucial for early bat disease detection. This work forms the basis for next phase of testing in White Nose Syndrome (WNS) detection in bats during hibernation. Further research on disease-related VOCs in various bat species could expand e-nose health monitoring capabilities during hibernation. In another application of electronic nose technology, [PERSON] et al. [192] delved into its potential for detecting Cutaneous myriasis, a debilitating disease primarily caused by Lucilia cuprina flies in sheep in Australia [193; 194]. Cutaneous myriasis involves the infestation of larvae in moist or stained areas of sheep fleece, leading to tissue damage and potential lethality. The challenge of early disease detection necessitates continuous flock monitoring for timely intervention. To confront this challenge, the researchers harnessed the capabilities of an electronic nose equipped with six metal oxide semiconductor sensors, along with temperature and humidity sensors, to capture the odors emitted during flystrike development. Through the application of nonlinear signal measurement techniques and linear discriminant analysis (LDA), they effectively extracted and processed signal features to categorically distinguish between different odor groups. Their results highlighted the electronic nose's proficiency in accurately discerning flystrike odors from those of dry wool across multiple experimental scenarios, even within 24 h of larval implantation. Furthermore, the technology demonstrated the ability to differentiate flystrike odors from fleece stained with urine and feces. These encouraging outcomes lay the foundation for the viability of using electronic nose technology for early flystrike detection.