Estimating chlorophyll content in tea leaves using spectral reflectance and deep learning methods
Accurate estimation of chlorophyll content in tea leaves is essential for evaluating plant health, managing fertilization, and optimizing harvest timing in precision agriculture. This study investigates the use of hyperspectral reflectance data (400–850 nm, 5 nm intervals; 91 bands) to estimate chlo...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-11-01
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| Series: | Ecological Informatics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S157495412500408X |
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