Raman Spectroscopy for the Early Detection of Huanglongbing and Citrus Canker in Plants: A Review
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arXiv
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866914017351565312 |
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| author | Das, Ashis Kumar Sharma, Shikha Gujarathi, Snehprabha Mena, Sushmita Bharadwaj, Saurav |
| author_facet | Das, Ashis Kumar Sharma, Shikha Gujarathi, Snehprabha Mena, Sushmita Bharadwaj, Saurav |
| contents | Citrus crops are of immense economic and agricultural importance worldwide, but are highly vulnerable to destructive diseases such as Huanglongbing (citrus greening) and citrus canker. These diseases often remain asymptomatic in early stages, making timely diagnosis difficult and resulting in substantial yield and quality losses. Rapid, non-invasive, and accurate early detection methods are therefore essential for effective disease management and sustainable citrus production. Raman spectroscopy, with its molecular specificity, non-destructive nature, and minimal sample preparation requirements, has emerged as a promising diagnostic technology for this purpose. This review outlines recent advances in applying Raman spectroscopy for the early detection of Huanglongbing and citrus canker, with a focus on spectral biomarkers that reflect pathogen-induced physiological and biochemical alterations in citrus tissues. Comparative insights are provided between portable, in-field Raman devices and conventional laboratory-based systems, highlighting diagnostic accuracy, operational feasibility, and deployment potential. The integration of chemometric and machine learning techniques for enhanced classification and automated disease recognition is examined. By consolidating current research, this review underscores the potential of Raman spectroscopy as a field-deployable solution for precision agriculture. It discusses future challenges and opportunities for the large-scale adoption of this technology in citrus orchard monitoring. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_02255 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Raman Spectroscopy for the Early Detection of Huanglongbing and Citrus Canker in Plants: A Review Das, Ashis Kumar Sharma, Shikha Gujarathi, Snehprabha Mena, Sushmita Bharadwaj, Saurav Quantitative Methods Citrus crops are of immense economic and agricultural importance worldwide, but are highly vulnerable to destructive diseases such as Huanglongbing (citrus greening) and citrus canker. These diseases often remain asymptomatic in early stages, making timely diagnosis difficult and resulting in substantial yield and quality losses. Rapid, non-invasive, and accurate early detection methods are therefore essential for effective disease management and sustainable citrus production. Raman spectroscopy, with its molecular specificity, non-destructive nature, and minimal sample preparation requirements, has emerged as a promising diagnostic technology for this purpose. This review outlines recent advances in applying Raman spectroscopy for the early detection of Huanglongbing and citrus canker, with a focus on spectral biomarkers that reflect pathogen-induced physiological and biochemical alterations in citrus tissues. Comparative insights are provided between portable, in-field Raman devices and conventional laboratory-based systems, highlighting diagnostic accuracy, operational feasibility, and deployment potential. The integration of chemometric and machine learning techniques for enhanced classification and automated disease recognition is examined. By consolidating current research, this review underscores the potential of Raman spectroscopy as a field-deployable solution for precision agriculture. It discusses future challenges and opportunities for the large-scale adoption of this technology in citrus orchard monitoring. |
| title | Raman Spectroscopy for the Early Detection of Huanglongbing and Citrus Canker in Plants: A Review |
| topic | Quantitative Methods |
| url | https://arxiv.org/abs/2509.02255 |