Search results for " electronic nose"
showing 3 items of 3 documents
FRUIT QUALITY EVALUATION OF FOUR LOQUAT CULTIVARS GROWN IN SICILY
2011
Chemical (soluble solids content, titratable acidity, pH), morphological (weight, longitudinal and transversal diameter, thickness of the flesh, number of seeds, peel colour), and sensorial characteristics of four loquat cultivars (‘Algerie’, ‘Claudia’, ‘Nespolone di Trabia’ and ‘Sanfilippara’) from mature, organically-grown trees in Sicily, were analysed. The determinations were carried out by traditional instrumental techniques, by a panel test and by an electronic olfactory system. A panel of 10 trained judges was used to determine intensity of some attributes in the sensory profile of the different cultivars, while the electronic olfactory system was used to identify possible difference…
Instrumental Odour Monitoring System Classification Performance Optimization by Analysis of Different Pattern-Recognition and Feature Extraction Tech…
2020
Instrumental odour monitoring systems (IOMS) are intelligent electronic sensing tools for which the primary application is the generation of odour metrics that are indicators of odour as perceived by human observers. The quality of the odour sensor signal, the mathematical treatment of the acquired data, and the validation of the correlation of the odour metric are key topics to control in order to ensure a robust and reliable measurement. The research presents and discusses the use of different pattern recognition and feature extraction techniques in the elaboration and effectiveness of the odour classification monitoring model (OCMM). The effect of the rise, intermediate, and peak period …
Modular Point-of-Care Breath Analyzer and Shape Taxonomy-Based Machine Learning for Gastric Cancer Detection
2022
Background: Gastric cancer is one of the deadliest malignant diseases, and the non-invasive screening and diagnostics options for it are limited. In this article, we present a multi-modular device for breath analysis coupled with a machine learning approach for the detection of cancer-specific breath from the shapes of sensor response curves (taxonomies of clusters). Methods: We analyzed the breaths of 54 gastric cancer patients and 85 control group participants. The analysis was carried out using a breath analyzer with gold nanoparticle and metal oxide sensors. The response of the sensors was analyzed on the basis of the curve shapes and other features commonly used for comparison. These f…