dc.creator | Madueño Luna, José Miguel | es |
dc.creator | Madueño Luna, Antonio | es |
dc.creator | Hidalgo Fernández, Rafael E. | es |
dc.date.accessioned | 2020-11-18T14:38:01Z | |
dc.date.available | 2020-11-18T14:38:01Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Madueño Luna, J.M., Madueño Luna, A. y Hidalgo Fernández, R.E. (2020). Characterization and Differentiation between Olive Varieties through Electrical Impedance Spectroscopy, Neural Networks and IoT. Sensors, 2020 (20) (2020 (5932)), 1 p.-20 p.. | |
dc.identifier.issn | 1424-8220 | es |
dc.identifier.uri | https://hdl.handle.net/11441/102701 | |
dc.description.abstract | Electrical impedance has shown itself to be useful in measuring the properties and
characteristics of agri-food products: fruit quality, moisture content, the germination capacity in seeds
or the frost-resistance of fruit. In the case of olives, it has been used to determine fat content and
optimal harvest time. In this paper, a system based on the System on Chip (SoC) AD5933 running a
1024-point discrete Fourier transform (DFT) to return the impedance value as a magnitude and phase
and which, working together with two ADG706 analog multiplexers and an external programmable
clock based on a synthesized DDS in a FPGA XC3S250E-4VQG100C, allows for the impedance
measurement in agri-food products with a frequency sweep from 1 Hz to 100 kHz. This paper
demonstrates how electrical impedance is affected by the temperature both in freshly picked olives
and in those processed in brine and provides a way to characterize cultivars by making use of only the
electrical impedance, neural networks (NN) and the Internet of Things (IoT), allowing information to
be collected from the olive samples analyzed both on farms and in factories | es |
dc.format | application/pdf | es |
dc.format.extent | 20 p. | es |
dc.language.iso | eng | es |
dc.publisher | MDPI | es |
dc.relation.ispartof | Sensors, 2020 (20) (2020 (5932)), 1 p.-20 p.. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Electrical impedance | es |
dc.subject | SoC AD5933 | es |
dc.subject | Artificial neural networks (ANNs) | es |
dc.subject | Internet of things (IoT) | es |
dc.subject | Temperature | es |
dc.title | Characterization and Differentiation between Olive Varieties through Electrical Impedance Spectroscopy, Neural Networks and IoT | es |
dc.type | info:eu-repo/semantics/article | es |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería Aeroespacial y Mecánica de Fluidos | es |
dc.relation.publisherversion | https://www.mdpi.com/1424-8220/20/20/5932 | es |
dc.identifier.doi | 10.3390/s20205932 | es |
dc.contributor.group | Universidad de Sevilla. AGR280: Ingeniería Rural | es |
dc.journaltitle | Sensors | es |
dc.publication.volumen | 2020 (20) | es |
dc.publication.issue | 2020 (5932) | es |
dc.publication.initialPage | 1 p. | es |
dc.publication.endPage | 20 p. | es |
dc.identifier.sisius | 3946 | es |