# Advancements and Prospects of Electronic Nose in Various Applications: A Comprehensive Review
## 3 Application Areas
### Disease Diagnosis
#### 3.3.2 Veterinary-Wildlife Pathology  
The accurate and timely detection of infectious diseases affecting wildlife is paramount, especially with the potential of virulent microbial pathogens to swiftly spread and cause substantial mortality within native animal populations. Traditional diagnostic methods often rely on observing clinical symptoms, which may only manifest after the disease has taken hold. However, there is a growing need for specialized diagnostic methods that can provide early indications of disease processes before visible symptoms emerge. This proactive approach is crucial for effectively managing and mitigating the impact of such \begin{table}
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**Application** & **Type of Sensor** & \
\begin{tabular}{c} **Data Processing** \\ **Algorithm** \\ \end{tabular} & **Description** & **References** \\ \hline \multirow{5}{*}{Cystic fibrosis} & \multirow{5}{*}{Cyanose 320} & \multirow{5}{*}{PCA, ROC curves, and CDA} & The authors of this study made a significant contribution by employing electronic nose technology to analyze exhaled breath samples from 260 children with cystic fibrosis (CF), 25 with primary ciliary dyskinesia (PCD), and 23 healthy controls. Their use of the electronic nose successfully differentiated between CF and PCD patients, as well as healthy individuals. Additionally, the study revealed distinct changes in breath profiles during exacerbations, highlighting the technology’s potential for non-invasive diagnosis and monitoring in CF and PCD. This work addresses a critical need in disease management and offers promising avenues for future research. &
\begin{tabular}{c} The authors introduced a nose-on-a-chip for early ventilator-associated pneumonia (VAP) diagnosis. This chip, incorporating sensors and circuits, achieved a 94.06\% identification rate for VAP and 100\% accuracy in identifying specific microorganisms associated with VAP. \\ \end{tabular} & \multirow{5}{*}{CRBM} & The authors introduced a nose-on-a-chip for early ventilator-associated pneumonia (VAP) diagnosis. This chip, incorporating sensors and circuits, achieved a 94.06\% identification rate for VAP and 100\% accuracy in identifying specific microorganisms associated with VAP. \\ \cline{1-1}  & & & & [181] \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: _Cont._diseases on wildlife health and conservation efforts. Leveraging advancements in e-nose technology offers a promising avenue for non-invasive disease detection in animals by analyzing the array of VOCs present in clinical samples. E-nose instruments detect differences in VOC concentrations to discriminate between healthy and diseased states, akin to metabolomic approaches. However, using e-noses for wildlife disease detection in field conditions presents several potential limitations, primarily influenced by environmental variability and animal behavior. Environmental factors such as temperature, humidity, and background odors can affect the accuracy and reliability of e-nose measurements, obscuring or altering the VOC profiles emitted by animals [182]. Additionally, animal behavior, including movement patterns, feeding habits, and social interactions, can impact the accessibility and sampling consistency required for e-nose measurements. Animals may exhibit stress-induced changes in VOC emissions unrelated to disease, further complicating interpretation. Moreover, the specificity and sensitivity of e-noses may vary across different animal species and diseases, necessitating thorough validation and calibration for each application. Addressing these limitations through robust study designs, data interpretation techniques, and technological advancements tailored to the complexities of natural ecosystems is essential to enhance the effectiveness of e-noses for wildlife disease detection in field conditions.