Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big Data

Joint Authors

Tian, Yan-Ge
Zhang, Zheng-Nan
Tian, Shuang-Qi

Source

Journal of Analytical Methods in Chemistry

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-11-20

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Chemistry

Abstract EN

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.

American Psychological Association (APA)

Tian, Yan-Ge& Zhang, Zheng-Nan& Tian, Shuang-Qi. 2020. Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big Data. Journal of Analytical Methods in Chemistry،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1174961

Modern Language Association (MLA)

Tian, Yan-Ge…[et al.]. Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big Data. Journal of Analytical Methods in Chemistry No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1174961

American Medical Association (AMA)

Tian, Yan-Ge& Zhang, Zheng-Nan& Tian, Shuang-Qi. Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big Data. Journal of Analytical Methods in Chemistry. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1174961

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1174961