Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big Data
Nondestructive testing with sensor technology is one of the fastest growing and most promising wheat quality information analysis technologies. Nondestructive testing with sensor technology benefits from the latest achievement of many disciplines such as computer, optics, mathematics, chemistry, and...
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Series: | Journal of Analytical Methods in Chemistry |
Online Access: | http://dx.doi.org/10.1155/2020/8851509 |
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doaj-ab4b5325506649cdbfb139ccefa256822020-11-30T09:11:27ZengHindawi LimitedJournal of Analytical Methods in Chemistry2090-88652090-88732020-01-01202010.1155/2020/88515098851509Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big DataYan-Ge Tian0Zheng-Nan Zhang1Shuang-Qi Tian2Henan University of Technology, High-tech Development Zone, Zhengzhou 450001, ChinaZhengzhou Electronic & Information Engineering School, Zhengzhou 450007, ChinaHenan University of Technology, High-tech Development Zone, Zhengzhou 450001, ChinaNondestructive testing with sensor technology is one of the fastest growing and most promising wheat quality information analysis technologies. Nondestructive testing with sensor technology benefits from the latest achievement of many disciplines such as computer, optics, mathematics, chemistry, and chemometrics. It has the advantages of simplicity, speed, low cost, no pollution, and no contact. It is widely used in wheat quality analysis and testing research. This article summarizes nondestructive testing with sensor technology for wheat quality, including the mechanical model, hyperspectral technology, Raman spectroscopy, and near-infrared techniques for wheat mechanical properties, storage properties, and physical and chemical properties (such as moisture, ash, protein, and starch) in the past decade. Based on the current research progress, big data technology needs a lot of research in spectral data mining, modeling algorithm optimization, model robustness, etc. to provide more data support and method reference for the research and application of wheat quality.http://dx.doi.org/10.1155/2020/8851509 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yan-Ge Tian Zheng-Nan Zhang Shuang-Qi Tian |
spellingShingle |
Yan-Ge Tian Zheng-Nan Zhang Shuang-Qi Tian Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big Data Journal of Analytical Methods in Chemistry |
author_facet |
Yan-Ge Tian Zheng-Nan Zhang Shuang-Qi Tian |
author_sort |
Yan-Ge Tian |
title |
Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big Data |
title_short |
Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big Data |
title_full |
Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big Data |
title_fullStr |
Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big Data |
title_full_unstemmed |
Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big Data |
title_sort |
nondestructive testing for wheat quality with sensor technology based on big data |
publisher |
Hindawi Limited |
series |
Journal of Analytical Methods in Chemistry |
issn |
2090-8865 2090-8873 |
publishDate |
2020-01-01 |
description |
Nondestructive testing with sensor technology is one of the fastest growing and most promising wheat quality information analysis technologies. Nondestructive testing with sensor technology benefits from the latest achievement of many disciplines such as computer, optics, mathematics, chemistry, and chemometrics. It has the advantages of simplicity, speed, low cost, no pollution, and no contact. It is widely used in wheat quality analysis and testing research. This article summarizes nondestructive testing with sensor technology for wheat quality, including the mechanical model, hyperspectral technology, Raman spectroscopy, and near-infrared techniques for wheat mechanical properties, storage properties, and physical and chemical properties (such as moisture, ash, protein, and starch) in the past decade. Based on the current research progress, big data technology needs a lot of research in spectral data mining, modeling algorithm optimization, model robustness, etc. to provide more data support and method reference for the research and application of wheat quality. |
url |
http://dx.doi.org/10.1155/2020/8851509 |
work_keys_str_mv |
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