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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Main Authors: Yan-Ge Tian, Zheng-Nan Zhang, Shuang-Qi Tian
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Journal of Analytical Methods in Chemistry
Online Access:http://dx.doi.org/10.1155/2020/8851509
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spelling 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
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AT zhengnanzhang nondestructivetestingforwheatqualitywithsensortechnologybasedonbigdata
AT shuangqitian nondestructivetestingforwheatqualitywithsensortechnologybasedonbigdata
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