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Application of Electronic-Nose Technologies for the Detection of Key Volatile Compounds in Food, Plant, Animal, Human and Environmental Fields

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Flavours and Fragrances".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 2339

Special Issue Editors


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Guest Editor
Department of Agricultural and Food Sciences, University of Bologna, Piazza Goidanich 60, 47521 Cesena, FC, Italy
Interests: sensory evaluation of food (wine, fruit juices, sweeteners); analytical techniques useful in food characterization: spectrophotometric (UV-Vis), spectroscopy methods (FT-NIR, FT-IR), chromatographic methods (HPLC, IC, MECK), electronic nose; statistical analysis; correlation between analytical techniques and sensory evaluation; polyphenolic compounds, natural antioxidants, bioactive compounds in food, beverages and wine; nutraceutical and technological exploitation of food grade tannins; food waste recovery
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department for Innovation in Biological, Agro-Food and Forest Systems, University of Tuscia, Via S. Camillo de Lellis, 01100 Viterbo, Italy
Interests: food science; non-destructive analyses; chemometrics; electronic nose; NIR; post-harvest; wine chemistry; spectroscopy

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Guest Editor
DIBAF—Department for Innovation in Biological, Agro-Food and Forest System, UNITUS, Via San Camillo de Lellis s.n.c., 01100 Viterbo, Italy
Interests: enviromental-friendly alternatives to plant protection products; agrifood industry; post-harvest and storage; bioactive compound biosynthesis and secondary metabolites; non-destructive techniques; food quality

Special Issue Information

Dear Colleagues,

Electronic nose (E-nose) was first applied for disease detection in medicine during the mid-1980s, then its use was extended to the fields of plant and animal studies. To date, E-nose devices are one of the most innovative tools in medical, veterinary, environmental, and food industry research due to their large spectrum of applications, such as the early detection of different human and animal diseases, differentiation of plants, pests and infections, crop ripening processes, food and beverages quality or deterioration processes, and environmental pollution. This is possible mainly due to the capability of the sensors to differentiate between volatile biomarkers. These compounds refer to a large category of volatile organic compounds which are deemed to be strictly linked to a particular disease or stress condition, as well asmetabolic or compositional changes, which can be measured accurately and reproducibly. In this context, considerable progress has been made, particularly in the identification of key volatile biomarkers strictly linked to particular conditions (such as specific and rare disease), improvements in sensor design and precision, modelling for discriminant analysis. This Special Issue collects the actual and innovative advancements in utilizing the e-nose as a tool that can be used in different fields, such as early detections of human and animal diseases, plant–host interactions, soil and air pollution contaminants, as well as the identification of key factors for agri-food and the quality monitoring of beverages.

Dr. Giuseppina Paola Parpinello
Dr. Andrea Bellincontro
Dr. Margherita Modesti
Guest Editors

Manuscript Submission Information

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Keywords

  • metabolites
  • early detection
  • diseases
  • volatiles
  • pollution
  • noninvasive detection
  • chemometrics
  • gas sensor

Published Papers (1 paper)

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Research

19 pages, 3311 KiB  
Article
Application of MOS Gas Sensors Coupled with Chemometrics Methods to Predict the Amount of Sugar and Carbohydrates in Potatoes
by Ali Khorramifar, Mansour Rasekh, Hamed Karami, James A. Covington, Sayed M. Derakhshani, Jose Ramos and Marek Gancarz
Molecules 2022, 27(11), 3508; https://doi.org/10.3390/molecules27113508 - 30 May 2022
Cited by 15 | Viewed by 1984
Abstract
Five potato varieties were studied using an electronic nose with nine MOS sensors. Parameters measured included carbohydrate content, sugar level, and the toughness of the potatoes. Routine tests were carried out while the signals for each potato were measured, simultaneously, using an electronic [...] Read more.
Five potato varieties were studied using an electronic nose with nine MOS sensors. Parameters measured included carbohydrate content, sugar level, and the toughness of the potatoes. Routine tests were carried out while the signals for each potato were measured, simultaneously, using an electronic nose. The signals obtained indicated the concentration of various chemical components. In addition to support vector machines (SVMs that were used for the classification of the samples, chemometric methods, such as the partial least squares regression (PLSR) method, the principal component regression (PCR) method, and the multiple linear regression (MLR) method, were used to create separate regression models for sugar and carbohydrates. The predictive power of the regression models was characterized by a coefficient of determination (R2), a root-mean-square error of prediction (RMSEP), and offsets. PLSR was able to accurately model the relationship between the smells of different types of potatoes, sugar, and carbohydrates. The highest and lowest accuracy of models for predicting sugar and carbohydrates was related to Marfona potatoes and Sprite cultivar potatoes. In general, in all cultivars, the accuracy in predicting the amount of carbohydrates was somewhat better than the accuracy in predicting the amount of sugar. Moreover, the linear function had 100% accuracy for training and validation in the C-SVM method for classification of five potato groups. The electronic nose could be used as a fast and non-destructive method for detecting different potato varieties. Researchers in the food industry will find this method extremely useful in selecting the desired product and samples. Full article
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