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What is NIR Spectroscopy for Pinus massoniana Moisture Detection about?

This study presents a multi-learner model for detecting moisture content in Pinus massoniana seedlings using near-infrared (NIR) spectroscopy. By employing preprocessing techniques and feature selection, the model achieved a high prediction accuracy, with a coefficient of determination R2 reaching 0.9430. This approach offers a non-destructive and efficient method for monitoring seedling moisture content, which is crucial for improving afforestation success rates.

Author

kalis hubi

Language

EN