NIR based wireless sensing approach for fruit monitoring

Meng Wang; Dongjie Luo; Yunyue Yang; Marina A. Nikitina; Xiaoshuan Zhang; Xinqing Xiao

Results in Engineering (Jun 2022)

NIR based wireless sensing approach for fruit monitoring

Meng Wang,
Dongjie Luo,
Yunyue Yang,
Marina A. Nikitina,
Xiaoshuan Zhang,
Xinqing Xiao

Affiliations

Meng Wang: Beijing Laboratory of Food Quality and Safety, College of Engineering, China Agricultural University, Beijing, 100083, PR China
Dongjie Luo: Beijing Laboratory of Food Quality and Safety, College of Engineering, China Agricultural University, Beijing, 100083, PR China
Yunyue Yang: Beijing Laboratory of Food Quality and Safety, College of Engineering, China Agricultural University, Beijing, 100083, PR China
Marina A. Nikitina: V.M. Gorbatov Federal Research Center for Foods Systems of RAS, 26, Talalikhina Str., 109316, Moscow, Russia
Xiaoshuan Zhang: Beijing Laboratory of Food Quality and Safety, College of Engineering, China Agricultural University, Beijing, 100083, PR China
Xinqing Xiao: Beijing Laboratory of Food Quality and Safety, College of Engineering, China Agricultural University, Beijing, 100083, PR China; Corresponding author. China Agricultural University, Beijing, 100083, PR China.

Journal volume & issue: Vol. 14
p. 100403

Abstract

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Monitoring the storage phase of grapes is a key issue as it is closely related to berry quality, so it is essential to investigate a rapid and comprehensive method of non-destructive wireless inspection applied to the berry storage process. In this study, a cost-effective optical measurement system was designed, built, and tested to determine optimal storage results. NIR spectral measurement system covers 6 separate on-device filters from 610 nm to 860 nm. The experiments were performed on Kyoho grapes. In addition, each sample was analyzed for soluble solids content (SSC) by conventional laboratory methods and used as a reference parameter. The results showed that the use of the artificial neural network (ANN) (RMSEP = 0.62 and Rp2 = 0.69) worked best and could be used for preliminary screening of fruit quality.

Published in Results in Engineering

ISSN: 2590-1230 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Technology
Website: https://www.journals.elsevier.com/results-in-engineering

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