A multivariate algorithm for identifying contaminated peanut using visible and near-infrared hyperspectral imaging-Reference-Cited by-同舟云学术

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A multivariate algorithm for identifying contaminated peanut using visible and near-infrared hyperspectral imaging

Published:2024-01 Issue: Volume:267 Page:125187
ISSN:0039-9140
Container-title:Talanta
language:en
Short-container-title:Talanta

Author:

Guo Zhen,Zhang Jing,Sun Jiashuai,Dong Haowei,Huang Jingcheng,Geng Lingjun,Li Shiling,Jing Xiangzhu,Guo Yemin^ORCID,Sun Xia

Publisher

Elsevier BV

Subject

Analytical Chemistry

Reference38 articles.

1. The beneficial role of peanuts in the diet–Part 2, Nutr;Higgs;Food Sci. (N. Y.),2003

2. Degradation of aflatoxin B1 in aqueous medium through UV irradiation;Liu;Eur. Food Res. Technol.,2011

3. Utilization of spectral-spatial characteristics in shortwave infrared hyperspectral images to classify and identify fungi-contaminated peanuts;Qiao;Food Chem.,2017

4. Spatio-temporal patterns of Aspergillus flavus infection and aflatoxin B1 biosynthesis on maize kernels probed by SWIR hyperspectral imaging and synchrotron FTIR microspectroscopy;Lu;Food Chem.,2022

5. A novel hyperspectral-based approach for identification of maize kernels infected with diverse Aspergillus flavus fungi;Tao;Biosyst. Eng.,2020

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2. Dual-aspect attention spatial-spectral transformer and hyperspectral imaging: A novel approach to detecting Aspergillus flavus contamination in peanut kernels;Postharvest Biology and Technology;2024-07

3. NIR sensors combined with chemometric algorithms in intelligent quality evaluation of sweetpotato roots from ‘Farm’ to ‘Table’: Progresses, challenges, trends, and prospects;Food Chemistry: X;2024-06

4. Discrimination of untreated and sodium sulphite treated bean sprouts by Fourier transform infrared spectroscopy and chemometrics;Food Additives & Contaminants: Part A;2024-04-22

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