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基于拉曼光谱的植物生物与非生物胁迫诊断。综述

Raman-Based Diagnostics of Biotic and Abiotic Stresses in Plants. A Review.

作者信息

Payne William Z, Kurouski Dmitry

机构信息

Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, United States.

出版信息

Front Plant Sci. 2021 Jan 20;11:616672. doi: 10.3389/fpls.2020.616672. eCollection 2020.

Abstract

Digital farming is a novel agricultural philosophy that aims to maximize a crop yield with the minimal environmental impact. Digital farming requires the development of technologies that can work directly in the field providing information about a plant health. Raman spectroscopy (RS) is an emerging analytical technique that can be used for non-invasive, non-destructive, and confirmatory diagnostics of diseases, as well as the nutrient deficiencies in plants. RS is also capable of probing nutritional content of grains, as well as highly accurate identification plant species and their varieties. This allows for Raman-based phenotyping and digital selection of plants. These pieces of evidence suggest that RS can be used for chemical-free surveillance of plant health directly in the field. High selectivity and specificity of this technique show that RS may transform the agriculture in the US. This review critically discusses the most recent research articles that demonstrate the use of RS in diagnostics of abiotic and abiotic stresses in plants, as well as the identification of plant species and their nutritional analysis.

摘要

数字农业是一种新型农业理念,旨在以最小的环境影响实现作物产量最大化。数字农业需要开发能够直接在田间工作以提供植物健康信息的技术。拉曼光谱(RS)是一种新兴的分析技术,可用于对疾病以及植物营养缺乏症进行非侵入性、非破坏性和确定性诊断。RS还能够探测谷物的营养成分,以及高度准确地识别植物物种及其品种。这使得基于拉曼光谱的植物表型分析和数字选择成为可能。这些证据表明,RS可直接用于田间对植物健康进行无化学物质监测。该技术的高选择性和特异性表明,RS可能会改变美国的农业。本综述批判性地讨论了最近的研究文章,这些文章展示了RS在植物非生物和生物胁迫诊断、植物物种识别及其营养分析中的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d79/7854695/0f61576e286e/fpls-11-616672-g001.jpg

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