Quality Assessment of the Inshell Hazelnuts Based on TD-NMR Analysis
2020 (English) In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 69, no 6, p. 3770-3779, article id 8794590Article in journal (Refereed) Published
Abstract [en]
Nondestructive testing is critical in the quality detection of products. Among several techniques, time-domain nuclear magnetic resonance (TD-NMR) is gaining attention in the field of food quality control, thanks to its ability to detect liquid and solid materials, which are strictly related to the quality of some kinds of products. In this article, a novel method for the inline quality evaluation of the inshell hazelnuts, based on TD-NMR analysis, is disclosed. Different studies have been carried out on the quality control of hazelnuts or, more in general, shell fruit. They usually focus on laboratory application and the analysis of a single physical property. Conversely, the proposed method focuses on the signal processing with the aim of reducing the execution time making the procedure suitable for an inline application. Moreover, the main hidden defects are analyzed together to identify the defective nuts from the good ones in a two-class classification procedure. © 1963-2012 IEEE.
Place, publisher, year, edition, pages Institute of Electrical and Electronics Engineers Inc. , 2020. Vol. 69, no 6, p. 3770-3779, article id 8794590
Keywords [en]
Digital signal processing, food quality, nondestructive technique, time-domain nuclear magnetic resonance (TD-NMR), Defects, Nondestructive examination, Nuclear magnetic resonance, Signal processing, Time domain analysis, Classification procedure, Food quality controls, NMR analysis, Quality assessment, Quality detection, Quality evaluation, Solid material, Time domain nuclear magnetic resonance, Quality control
National Category
Physical Chemistry
Identifiers URN: urn:nbn:se:miun:diva-41524 DOI: 10.1109/TIM.2019.2934662 ISI: 000546623300049 Scopus ID: 2-s2.0-85084918192 OAI: oai:DiVA.org:miun-41524 DiVA, id: diva2:1536263
2021-03-102021-03-102021-04-27 Bibliographically approved