Raman Spectroscopy for Plant Disease Detection in Next-Generation Agriculture

Abstract

The present review focuses on recent reports on the contribution of the Raman method in the development of digital agriculture, according to the premise of maximizing crops with a minimal impact of agriculture on the environment. The Raman method is an optically based spectrum technique that allows for the species-independent study of plant physiology as well as the real-time determination of key compounds in a non-destructive manner. The review focuses on scientific reports related to the possibility of using the Raman spectrometer to monitor the physiological state of plants and, in particular, to effectively diagnose biotic and abiotic stresses. This review primarily aims to draw attention to and raise awareness of the potential of Raman spectroscopy as a digital tool capable of bridging the gap between scientists’ detailed knowledge of plants grown under laboratory conditions and farmers’ work. The Raman spectrometer allows plant breeders to take appropriate measures in a well-defined area, which will reduce the territory occupied by biotic and abiotic stresses, thus increasing yields and improving their quality. Raman technology applied to modern agriculture can positively affect the accuracy and speed of crop quality assessments, contributing to food safety, productivity and economic profitability. Further research and analysis on cooperation between farmers and scientists is indispensable to increase the viability and availability of Raman spectrometers for as many farmers and investors as possible.

Plant phenotyping relevance

植物の生理状態と生物・非生物ストレスをRaman分光で評価する方法に焦点を当てたレビューであり、植物フェノタイピング手法のレビューとして中心的です。

Code and data availability

This is a review article on Raman spectroscopy for plant disease detection. The supplied blocks describe and cite prior studies but contain no public phenotype/trait datasets, plant images, sensor data, author analysis code, trained models, or supplements with such assets. No data or code availability statements appear

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