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高光谱成像技术在果蔬品质与安全无损检测中的原理及应用

Principles and Applications of Hyperspectral Imaging Technique in Quality and Safety Inspection of Fruits and Vegetables

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摘要

水果和蔬菜的品质与安全是消费者最为关心的问题。 传统的化学检测方法是一种费时费力的破坏性检测技术。 随着成像和光谱技术的快速发展, 高光谱成像技术已经广泛应用于农产品品质与安全的快速无损检测中。 高光谱成像技术融合了传统的成像和光谱技术的优点, 可以同时获取被检测物体的空间信息和光谱信息, 因此该技术既可以像检测物体的外部品质, 又可以像光谱技术一样检测物体的内部品质和品质安全。 目前, 已经有大量的基于高光谱成像技术检测水果和蔬菜品质与安全的研究性论文发表, 为了深入了解高光谱成像技术的检测原理并跟踪国内外最新的研究进展, 综述了高光谱成像技术在水果和蔬菜外部品质、 内部品质和品质安全检测中的原理、 发展和应用。 另外, 还简要介绍和讨论了高光谱成像系统的构成、 常用的数据分析方法、 发展趋势及面临的挑战。

Abstract

The quality and safety of fruits and vegetables are the most concerns of consumers. Chemical analytical methods are traditional inspection methods which are time-consuming and labor intensive destructive inspection techniques. With the rapid development of imaging technique and spectral technique, hyperspectral imaging technique has been widely used in the nondestructive inspection of quality and safety of fruits and vegetables. Hyperspectral imaging integrates the advantages of traditional imaging and spectroscopy. It can obtain both spatial and spectral information of inspected objects. Therefore, it can be used in either external quality inspection as traditional imaging system, or internal quality or safety inspection as spectroscopy. In recent years, many research papers about the nondestructive inspection of quality and safety of fruits and vegetables by using hyperspectral imaging have been published, and in order to introduce the principles of nondestructive inspection and track the latest research development of hyperspectral imaging in the nondestructive inspection of quality and safety of fruits and vegetables, this paper reviews the principles, developments and applications of hyperspectral imaging in the external quality, internal quality and safety inspection of fruits and vegetables. Additionally, the basic components, analytical methods, future trends and challenges are also reported or discussed in this paper.

Newport宣传-MKS新实验室计划
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中图分类号:TP391.4

DOI:10.3964/j.issn.1000-0593(2014)10-2743-09

基金项目:国家自然科学基金青年基金项目(31301236)和国家科技支撑计划课题(2014BAD21B01)资助

收稿日期:2014-05-25

修改稿日期:2014-07-26

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作者单位    点击查看

张保华:上海交通大学机械系统与振动国家重点实验室, 上海 200240北京市农林科学院, 北京农业智能装备技术研究中心, 北京 100097
李江波:北京市农林科学院, 北京农业智能装备技术研究中心, 北京 100097
樊书祥:北京市农林科学院, 北京农业智能装备技术研究中心, 北京 100097
黄文倩:北京市农林科学院, 北京农业智能装备技术研究中心, 北京 100097
张驰:北京市农林科学院, 北京农业智能装备技术研究中心, 北京 100097
王庆艳:北京市农林科学院, 北京农业智能装备技术研究中心, 北京 100097
肖广东:北京市农林科学院, 北京农业智能装备技术研究中心, 北京 100097

联系人作者:张保华(zhangbaohua@sjtu.edu.cn)

备注:张保华, 1986年生, 上海交通大学机械与动力工程学院博士研究生

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引用该论文

ZHANG Bao-hua,LI Jiang-bo,FAN Shu-xiang,HUANG Wen-qian,ZHANG Chi,WANG Qing-yan,XIAO Guang-dong. Principles and Applications of Hyperspectral Imaging Technique in Quality and Safety Inspection of Fruits and Vegetables[J]. Spectroscopy and Spectral Analysis, 2014, 34(10): 2743-2751

张保华,李江波,樊书祥,黄文倩,张驰,王庆艳,肖广东. 高光谱成像技术在果蔬品质与安全无损检测中的原理及应用[J]. 光谱学与光谱分析, 2014, 34(10): 2743-2751

被引情况

【1】于宏威,王 强,刘 丽,石爱民,胡 晖,刘红芝. 粮油品质安全高光谱成像检测技术的研究进展. 光谱学与光谱分析, 2016, 36(11): 3643-3650

【2】于宏威,王 强,石爱民,杨 颖,刘 丽,胡 晖,刘红芝. 高光谱成像技术结合化学计量学可视化花生中蛋白质含量分布. 光谱学与光谱分析, 2017, 37(3): 853-858

【3】黄立贤,李大鹏,吴 凡,沈志学,曹宁翔,段佳著,王海峰. 近红外光谱成像系统在液体安检中的应用. 强激光与粒子束, 2018, 30(1): 19001--1

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