Low-Cost Optoelectronic Sensor for Early Screening of Citrus Greening in Leaves
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914018408529920 |
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| author | Gupta, Ramji Das, Ashis Kumar Mena, Sushmita Bharadwaj, Saurav |
| author_facet | Gupta, Ramji Das, Ashis Kumar Mena, Sushmita Bharadwaj, Saurav |
| contents | Citrus greening, or Huanglongbing (HLB), is a serious disease affecting citrus crops, with no known cure. Early detection is essential, but current methods are often expensive. To address this, a low-cost, portable sensor was developed to distinguish between HLB-infected and healthy citrus leaves using a LED-based optical sensing circuit. The device uses white and infrared (IR) LEDs to illuminate the adaxial leaf surface and measures change in reflectance intensities caused by differences in biochemical compositions between healthy and HLB-infected leaves. These changes, analyzed across four spectral bands (blue, green, red, and IR), were processed using machine learning models, including Random Forest. Experimental results indicated that the IR band was the most effective, with the Random Forest model achieving an accuracy of 89.58% and precision of 93.75%. Similarly, the green band also achieved an accuracy of 85.42% and precision of 90.62%. These results suggest that this LED-based optical system could be a hand-held screening tool for early detection of HLB, providing small-scale farmers with a cost-effective solution. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_02656 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Low-Cost Optoelectronic Sensor for Early Screening of Citrus Greening in Leaves Gupta, Ramji Das, Ashis Kumar Mena, Sushmita Bharadwaj, Saurav Other Quantitative Biology Image and Video Processing Citrus greening, or Huanglongbing (HLB), is a serious disease affecting citrus crops, with no known cure. Early detection is essential, but current methods are often expensive. To address this, a low-cost, portable sensor was developed to distinguish between HLB-infected and healthy citrus leaves using a LED-based optical sensing circuit. The device uses white and infrared (IR) LEDs to illuminate the adaxial leaf surface and measures change in reflectance intensities caused by differences in biochemical compositions between healthy and HLB-infected leaves. These changes, analyzed across four spectral bands (blue, green, red, and IR), were processed using machine learning models, including Random Forest. Experimental results indicated that the IR band was the most effective, with the Random Forest model achieving an accuracy of 89.58% and precision of 93.75%. Similarly, the green band also achieved an accuracy of 85.42% and precision of 90.62%. These results suggest that this LED-based optical system could be a hand-held screening tool for early detection of HLB, providing small-scale farmers with a cost-effective solution. |
| title | Low-Cost Optoelectronic Sensor for Early Screening of Citrus Greening in Leaves |
| topic | Other Quantitative Biology Image and Video Processing |
| url | https://arxiv.org/abs/2509.02656 |