Screening naturally mildewed maize kernels based on Raman hyperspectral imaging coupled with machine learning classifiers-Reference-Cited by-同舟云学术

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Screening naturally mildewed maize kernels based on Raman hyperspectral imaging coupled with machine learning classifiers

Published:2022-08-05 Issue:11 Volume:45 Page:
ISSN:0145-8876
Container-title:Journal of Food Process Engineering
language:en
Short-container-title:J Food Process Engineering

Author:

Long Yuan¹²³,Wang Qingyan²³,Tian Xi²³,Zhang Bin¹^ORCID,Huang Wenqian²³

Affiliation:

1. College of Engineering China Agricultural University Beijing China

2. Intelligent Equipment Research Center Beijing Academy of Agriculture and Forestry Sciences Beijing China

3. National Research Center of Intelligent Equipment for Agriculture Beijing China

Funder

Chinese Universities Scientific Fund

National Natural Science Foundation of China

Publisher

Wiley

Subject

General Chemical Engineering,Food Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jfpe.14148

Reference39 articles.

1. Determination of amylose content in starch using Raman spectroscopy and multivariate calibration analysis

2. Hyperspectral NIR imaging for calibration and prediction: a comparison between image and spectrometer data for studying organic and biological samples

3. Classifying maize kernels naturally infected by fungi using near-infrared hyperspectral imaging

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Applications of hyperspectral imaging technology in the food industry;Nature Reviews Electrical Engineering;2024-03-26

2. Identification of mould varieties infecting maize kernels based on Raman hyperspectral imaging technique combined with multi-channel residual module convolutional neural network;Journal of Food Composition and Analysis;2024-01

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