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Smart Agriculture ›› 2022, Vol. 4 ›› Issue (2): 121-134.doi: 10.12133/j.smartag.SA202201013

• 综合研究 • 上一篇    下一篇

典型拉曼光谱技术及其在农业检测中应用研究进展

高振1,2(), 赵春江1,2, 杨桂燕2, 董大明2()   

  1. 1.中国农业大学 信息与电气工程学院,北京 100083
    2.北京市农林科学院国家农业智能装备工程技术研究中心,北京 100097
  • 收稿日期:2021-08-25 出版日期:2022-06-30
  • 基金资助:
    国家自然科学基金(32101609);北京市自然科学基金(JQ19023)
  • 作者简介:高 振(1995-),男,博士研究生,研究方向为光学传感和拉曼光谱技术及其应用系统研发等。E-mail:z@cau.edu.cn
  • 通信作者: 董大明(1983-),男,博士,研究员,研究方向为红外与激光光谱技术在环境监测和农业中的应用。E-mail:dongdm@nercita.org.cn

Typical Raman Spectroscopy Ttechnology and Research Progress in Agriculture Detection

GAO Zhen1,2(), ZHAO Chunjiang1,2, YANG Guiyan2, DONG Daming2()   

  1. 1.College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
    2.National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
  • Received:2021-08-25 Online:2022-06-30

摘要:

拉曼光谱是一种散射光谱,具有快速、不易受水分干扰、样品无需预处理和在体检测等特点,可作为分析、测试物质分子成分和结构强有力的表征手段。随着拉曼光谱技术的不断发展,其在农业检测领域中逐渐发挥出极其重要的作用。本文概述了拉曼光谱的检测原理,从共聚焦显微拉曼光谱、傅里叶变换拉曼光谱、表面增强拉曼光谱、针尖增强拉曼光谱、共振拉曼光谱、空间偏移拉曼光谱、移频激发拉曼差分光谱、基于非线性光学的拉曼光谱等8个方面介绍了拉曼光谱技术,重点总结了拉曼光谱技术在植物检测、土壤检测、水质检测、食品检测等方面的应用研究进展,并提出了其在农业检测领域中应用需要解决的难题和未来的发展方向,以期对未来农业生产和研究带来启发。

关键词: 拉曼光谱, 植物表型, 植物胁迫, 土壤检测, 农药残留检测, 水质检测, 食品检测

Abstract:

Raman spectroscopy is a type of scattering spectroscopy with features such as rapid, less susceptible to moisture interference, no sample pre-treatment and in vivo detection. As a powerful characterization tool for analyzing and testing the molecular composition and structure of substances, Raman spectroscopy is also playing an extremely important role in the detection of plant and animal phenotypes, food safety, soil and water quality in the agricultural field with the continuous improvement of Raman spectroscopy technology. In this paper, the detection principles of Raman spectroscopy are introduced, and the new progresses of eight Raman spectroscopy technology are summarized, including confocal microscopy Raman spectroscopy, Fourier transform Raman spectroscopy, surface-enhanced Raman spectroscopy, tip-enhanced Raman spectroscopy, resonance Raman spectroscopy, spatially shifted Raman spectroscopy, frequency-shifted excitation Raman difference spectroscopy and Raman spectroscopy based on nonlinear optics, etc. And their advantages and disadvantages and application scenarios are prerented, respectively. The applications of Raman spectroscopy in plant detection, soil detection, water quality detection, food detection, etc. are summarized. It can be specifically subdivided into plant phenotype, plant stress, soil pesticide residue detection, soil colony detection, soil nutrient detection, food pesticide detection, food quality detection, food adulteration detection, and water quality detection. In future agricultural applications, the elimination of fluorescence background due to complex living organisms in Raman spectroscopy is the next research direction. The study of stable enhanced substrates is an important direction in the application of Surface Enhanced Raman Spectroscopy (SERS). In order to meet the measurement of different scenarios, portable and telemetric Raman spectrometers will also play an important role in the future. Raman spectroscopy needs to be further explored for a wide variety of research objects in agriculture, especially for applications in animal science, for which there is still a paucity of relevant studies up to now. In the existing field of agricultural research, it is necessary to pursue the characterization of more specific substances by Raman spectroscopy, which can prompt the application of Raman spectroscopy for a wider range of uses in agriculture. Further, the pursuit of lower detection limits and higher stability for practical applications is also the direction of development of Raman spectroscopy in the field of agriculture. Finally, the challenges that need to be solved and the future development directions of Raman spectroscopy are proposed in the field of agriculture in order to bring more inspiration to future agricultural production and research.

Key words: Raman spectroscopy, plant phenotyping, plant stress detection, soil detection, pesticide residue detection, water quality detection, food detection

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