THz Data Analysis and Self-Organizing Map (SOM) for the Quality Assessment of Hazelnuts

Year: 2024

Authors: Greco M., Giarnetti S., Giovenale E., Taschin A., Leccese F., Doria A., Senni L.

Autors Affiliation: Univ Roma Tre, Sci Dept, I-00146 Rome, Italy; Se Te L Servizi Tecn Logist SRL, I-00142 Rome, Italy; ENEA, Fus Dept, I-00044 Rome, Italy; CNR, Inst Appl Math Mauro Picone IAC, Rome I-00185, Italy.

Abstract: In recent years, the use of techniques based on electromagnetic radiation as an investigative tool in the agri-food industry has grown considerably, and between them, the application of imaging and THz spectroscopy has gained significance in the field of food quality control. This study presents the development of an experimental setup operating in transmission mode within the frequency range of 18 to 40 GHz, which was specifically designed for assessing various quality parameters of hazelnuts. The THz measurements were conducted to distinguish between healthy and rotten hazelnut samples. Two different data analysis techniques were employed and compared: a traditional approach based on data matrix manipulation and curve fitting for parameter extrapolation, and the utilization of a Self-Organizing Map (SOM), for which we use a neural network commonly known as the Kohonen neural network, which is recognized for its efficacy in analyzing THz measurement data. The classification of hazelnuts based on their quality was performed using these techniques. The results obtained from the comparative analysis of coding efforts, analysis times, and outcomes shed light on the potential applications of each method. The findings demonstrate that THz spectroscopy is an effective technique for quality assessment in hazelnuts, and this research serves to clarify the suitability of each analysis technique.

Journal/Review: APPLIED SCIENCES-BASEL

Volume: 14 (4)      Pages from: 1555-1  to: 1555-13

KeyWords: terahertz; quality assessment; self-organizing map (SOM); Kohonen´s algorithm; hazelnut; agri-food industry; millimeter waves
DOI: 10.3390/app14041555