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Potential for Predicting Soil Properties Using Low Cost Near-Infrared Spectroscopy and Machine Learning

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Using two public soil spectral libraries, we examined potential for low-cost nearinfrared devices for in-field testing. Results showed strong promise with conventional neural networks, comparable to previously published results with deep learning.

© 2020 The Author(s)

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