By Owais AliReviewed by Lexie CornerJun 10 2025Environmental and chemical stresses negatively affect plant growth, metabolism, and yield by disrupting physiological and biochemical processes.
Traditional detection methods rely on visual inspection and laboratory analyses. These approaches are time-consuming, labor-intensive, and typically detect stress only after significant damage has occurred. As a result, they are not well-suited for large-scale or real-time monitoring.
Raman spectroscopy is a non-destructive technique that can detect biochemical changes in plants at early stages. It provides molecular-level insights into their physiological condition.
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Significance of Early Plant Stress Detection
Modern agriculture faces growing challenges from a range of environmental stressors that affect the sustainability of global food production. Climate change, salinization, nutrient deficiencies, and pathogen infestations contribute to both abiotic and biotic stresses that impair plant physiology and reduce productivity.
Abiotic factors such as water deficit, salinity, and nutrient imbalance interfere with key physiological processes. These disruptions reduce water and nutrient uptake, lower photosynthetic efficiency, and accelerate plant aging. Biotic stresses, caused by viral, bacterial, and fungal pathogens as well as insect pests, affect plant immune responses, damage tissues, and can lead to systemic infections and crop loss.
Delayed detection of plant stress has economic consequences, including higher production costs, lower crop quality, and reduced market value. It is estimated that abiotic stressors account for about 70 % of global yield losses, while biotic factors contribute around 30 %.
Early identification allows farmers to apply targeted and cost-effective interventions. These include localized nutrient application and focused pest control, helping to limit damage, reduce resource waste, and minimize environmental impact.1
How Does Raman Spectroscopy Detect Plant Stress at The Molecular Level?
Raman spectroscopy detects plant stress by measuring vibrational energy shifts in molecular bonds within plant tissues. These shifts provide a biochemical fingerprint that reflects physiological changes.
New to Raman Spectroscopy? Watch this 7-minute tutorial on Raman basics by Bruker
Raman Basics | Principles of Raman Spectroscopy | 7 Minute Tutorial
Under stress conditions, the concentration and structure of key biomolecules, such as carotenoids, phenylpropanoids, proteins, and lipids, are altered. These changes generate distinct spectral signatures. Specific Raman bands shift in response to these molecular alterations, enabling early detection of stress before visible symptoms appear.
Chemometric analysis of the spectral data further improves the ability to distinguish between different stress types and levels. This molecular-level sensitivity makes Raman spectroscopy a useful, non-invasive tool for diagnosing plant stress.
Detection of Abiotic Stresses
Raman spectroscopy detects abiotic stress by identifying changes in the vibrational signatures of biomolecules affected by adverse conditions. These include alterations in nitrates, pigments, and structural polymers resulting from nutrient deficiency, salinity, and other stressors. Such molecular changes can indicate physiological disruption before symptoms are visible.
The technique’s high chemical specificity and sensitivity allow it to detect subtle metabolic variations in stressed plants. In a study published in Scientific Reports, portable Raman sensors were used to detect nitrogen deficiency in Arabidopsis thaliana and Brassicaceae crops. Spectroscopic analysis with 830 nm excitation revealed a reduction in nitrate-related spectral features in nitrogen-deficient plants.
A pronounced decrease in intensity at the 1045 cm⁻¹ peak was observed within the 1030–1080 cm⁻¹ spectral region. These chemical changes were detected even when there were no visible phenotypic differences or changes in chlorophyll content between nitrogen-deficient and control plants.
This early detection capability can support timely nutrient management decisions in agriculture, potentially improving crop health and reducing yield loss.2
Water Deficit and Salinity Stresses
Water deficit and salinity are key abiotic stressors that reduce crop productivity worldwide. Early detection of these conditions is important for applying timely interventions and minimizing yield losses.
However, conventional remote sensing methods, such as UAV-based or satellite imaging, often identify stress only after visible symptoms appear. This limits their usefulness for early, proactive crop management.
To overcome this limitation, a study used Raman spectroscopy to detect and differentiate water deficit and salinity stresses in Arachis hypogaea L. (peanut) by analyzing changes in specific vibrational bands.
The researchers observed reduced Raman signals for carotenoids (1,000, 1,155, and 1,526 cm⁻¹), phenylpropanoids (1,605 cm⁻¹), and aliphatic compounds (1,218–1,442 cm⁻¹) under stress conditions.
Chemometric analysis allowed for classification of stressed versus unstressed plants with an accuracy of up to 95.6 %. It also enabled differentiation between water deficit and salinity stresses with over 86 % accuracy. These results highlight the potential of Raman spectroscopy for use in high-throughput phenotyping and precision agriculture.3
Detection of Biotic Stresses
Raman spectroscopy detects biotic stress by measuring the inelastic scattering of monochromatic laser light as it interacts with molecular vibrations in plant biomolecules.
The resulting spectra serve as chemical signatures that reflect changes in physiological conditions caused by pathogens. These changes can be observed in compounds such as carotenoids, lignin, cellulose, and pectin.
In addition, the molecular specificity of Raman spectroscopy enables differentiation between healthy and infected tissues during early infection stages, often preceding the development of visible symptoms.
A study published in Planta validated this approach by investigating Candidatus Liberibacter solanacearum infection in tomato plants. Infected tissues exhibited significant decreases in spectral peak intensities at 1000 and 1525 cm⁻¹, corresponding to carotenoid degradation caused by bacterial activity.
Additional reductions at 747, 1155, 1184, and 1218 cm⁻¹ reflected decreases in pectin, cellulose, and xylan content, indicating pathogen-induced hydrolysis of structural polysaccharides. These molecular changes were detected three weeks post-infection, preceding the onset of observable symptoms.
Chemometric analysis of the spectra further enabled classification of infected versus healthy plants with 80 % accuracy. These findings support the use of Raman spectroscopy for early detection and management of biotic stress in crops.4
Detection of Minute Stresses Using Surface-Enhanced Raman Scattering
Plant stress induces subtle molecular changes, including secondary metabolite production, pigment composition shifts, and toxin accumulation, often undetectable by conventional spectroscopic methods.
Surface-enhanced Raman Scattering (SERS) addresses these limitations by amplifying weak vibrational signals of stress-related molecules, enabling detection at trace concentrations with high sensitivity and molecular specificity.
SERS works by adsorbing plant-derived molecules onto engineered metallic nanostructures, usually made of silver or gold. These structures act as substrates that enhance the Raman signal. When stress-related compounds from plant tissues or exudates interact with the substrate, their vibrational signals are amplified.
Spectral data can be collected using portable or benchtop Raman spectrometers. Chemometric tools, such as principal component analysis (PCA) or partial least squares regression (PLSR), are then used to analyze the data. This helps distinguish between healthy and stressed plants and allows for the quantification of specific stress-related molecular markers.
One study demonstrated the use of SERS for detecting mycotoxins in corn with a portable Raman system. The sensor design included a magnetic core with a polydopamine shell for selective adsorption of mycotoxins. A layer of gold nanoparticles was added to enhance the Raman signal.
This setup enabled the selective detection of multiple mycotoxins at concentrations as low as 1 ng/mL. The results show the potential of SERS as a sensitive and selective tool for plant health diagnostics.5
Explore More Applications
Raman spectroscopy is emerging as a valuable tool for real-time, non-invasive plant stress detection, with portable systems enabling in-field use for early diagnosis and crop monitoring.
While accessibility remains a challenge due to equipment costs, continued innovation and service-based models could make this technology more broadly available.1,6
Interested in how spectroscopy is advancing across other sectors? Discover how related techniques are improving environmental sensing, food safety, and material analysis:
References and Further Reading
- Saletnik, A., Saletnik, B., Zaguła, G., & Puchalski, C. (2023). Raman Spectroscopy for Plant Disease Detection in Next-Generation Agriculture. Sustainability, 16(13), 5474. https://doi.org/10.3390/su16135474
- Gupta, S., Huang, C. H., Singh, G. P., Park, B. S., Chua, N., & Ram, R. J. (2020). Portable Raman leaf-clip sensor for rapid detection of plant stress. Scientific Reports, 10(1), 1-10. https://doi.org/10.1038/s41598-020-76485-5
- Morey, R., Farber, C., McCutchen, B., Burow, M. D., Simpson, C., Kurouski, D., & Cason, J. (2021). Raman spectroscopy-based diagnostics of water deficit and salinity stresses in two accessions of peanut. Plant Direct, 5(8), e342. https://doi.org/10.1002/pld3.342
- Sanchez, L., Ermolenkov, A., Tang, XT. et al. (2020). Non-invasive diagnostics of Liberibacter disease on tomatoes using a hand-held Raman spectrometer. Planta 251, 64. https://doi.org/10.1007/s00425-020-03359-5
- Zhang, Y., Zhao, C., Picchetti, P., Zheng, K., Zhang, X., Wu, Y., Shen, Y., De Cola, L., Shi, J., Guo, Z., & Zou, X. (2024). Quantitative SERS sensor for mycotoxins with extraction and identification function. Food Chemistry, 456, 140040. https://doi.org/10.1016/j.foodchem.2024.140040
- Payne, W. Z., & Kurouski, D. (2021). Raman-Based Diagnostics of Biotic and Abiotic Stresses in Plants. A Review. Frontiers in Plant Science, 11, 616672. https://doi.org/10.3389/fpls.2020.616672
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