Identification of wheat grain in different states based on hyperspectral imaging technology-Reference-Cited by-同舟云学术

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Identification of wheat grain in different states based on hyperspectral imaging technology

Published:2019-07-03 Issue:6 Volume:52 Page:356-366
ISSN:0038-7010
Container-title:Spectroscopy Letters
language:en
Short-container-title:Spectroscopy Letters

Author:

Zhang Liu¹²^ORCID,Ji Haiyan¹²

Affiliation:

1. Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing, China;

2. Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, China Agricultural University, Beijing, China

Publisher

Informa UK Limited

Subject

Spectroscopy,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/00387010.2019.1639762

Reference26 articles.

1. Classification of maize seeds of different years based on hyperspectral imaging and model updating

2. Classification of Frozen Corn Seeds Using Hyperspectral VIS/NIR Reflectance Imaging

3. Discrimination between durum and common wheat kernels using near infrared hyperspectral imaging

4. Detection of sprout damage in wheat kernels using NIR hyperspectral imaging

5. Feasibility of near infrared spectroscopy for analyzing corn kernel damage and viability of soybean and corn kernels

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1. Varietal Identification of Cereal Grains: Review;Current Nutrition & Food Science;2024-03

2. Advancements, limitations and challenges in hyperspectral imaging for comprehensive assessment of wheat quality: An up-to-date review;Food Chemistry: X;2024-03

3. Accurate determination of sorghum origin based on hyperspectral imaging technology and machine learning;Microwave and Optical Technology Letters;2024-03

4. Hyperspectral Imaging for e-waste Material Identification;Environmental Science and Engineering;2024

5. Early detection of citrus anthracnose caused by Colletotrichum gloeosporioides using hyperspectral imaging;Computers and Electronics in Agriculture;2023-11

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