Chiang Mai Journal of Science

Print ISSN: 0125-2526 | eISSN : 2465-3845

1,647
Articles
Q3 0.80
Impact Factor
Q3 1.3
CiteScore
7 days
Avg. First Decision

Qualitative Characterization of Astringent and De-astringed Intact ‘Xichu’ Persimmon Fruit Using VIS/SWNIR and Chemometrics

Phuangphet Hemrattrakun, Danai Boonyakiat, Kazuhiro Nakano, Shintaroh Ohashi, Phonkrit Maniwara, Sila Kittiwachana and Parichat Theanjumpol
* Author for corresponding; e-mail address: parichatcmu@gmail.com
Volume: Vol.49 No.2 (March 2022)
Research Article
DOI: https://doi.org/10.12982/CMJS.2022.031
Received: 23 July 2021, Revised: 17 December 2021, Accepted: 19 December 2021, Published: -

Citation: Hemrattrakun P., Boonyakiat D., Nakano K., Ohashi S., Maniwara P., Kittiwachana S., et al., Qualitative Characterization of Astringent and De-astringed Intact ‘Xichu’ Persimmon Fruit Using VIS/SWNIR and Chemometrics, Chiang Mai Journal of Science, 2022; 49(2): 409-419. DOI 10.12982/CMJS.2022.031.

Abstract

     Astringency removal is considered as a key process before commercialize persimmon cv. ‘Xichu’, due to its high content of soluble tannins. Application of carbon dioxide treatment effective in removing astringency and widely used as a commercial postharvest practice for astringent persimmon fruit. The aim of this research is study to the application of visible and shortwave near infrared (VIS/SWNIR) spectroscopy in the spectral data of 400-1100 nm to discriminate astringent (A) and de-astringed (DA) fruit non-destructively based on the sensorial perception as 0.10% soluble tannin of fresh weight. The highest classifi cation accuracy score was obtained from QDA model combined with 2D preprocessing technique as 98.99% in the external validation set. Therefore, the results obtained in this study can be considered as a non-destructive analytical method to monitoring the effectiveness of the astringency removal treatment in ‘Xichu’ persimmon fruit.

Keywords: persimmon, near infrared, astringency, chemometrics

Related Articles

Big Data-driven for Fuel Quality using NIR Spectrometry Analysis
page: 1161 - 1172

Ibrahim M. Almanjahie, Zoulikha Kaid, Khlood A. Assiri and Ali Laksaci

Vol.48 No.4 (July 2021)
Research Article View: 947 Download: 614
Fabrication of a Low-cost NIR Spectrometer for Detection of Agricultural Product Quality
page: 332 - 340

Nutthatida Phuangsaijai, Parichat Theanjumpol, Nadthawat Muenmanee and Sila Kittiwachana*

Vol.48 No.2 (March 2021)
Research Article View: 1,127 Download: 1,588
Application of Artificial Neural Network for Tracing the Geographical Origins of Coffee Bean in Northern Areas of Thailand Using Near Infrared Spectroscopy
page: 163 - 175

Sakunna Wongsaipun, Parichat Theanjumpol, Nadthawat Muenmanee, Danai Boonyakiat, Sujitra Funsueb and Sila Kittiwachana*

Vol.48 No.1 (January 2021)
Research Article View: 1,207 Download: 1,255
Outline
Figures