ArticleScientific reports2025
Deep learning using inductively coupled plasma spectroscopy spectra accurately predicts various soil physicochemical properties for soil diagnosis.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Improving soil diagnosis-based agriculture can help reduce fertilizer utilization and its environmental impact. However, conventional soil diagnostic methods are time-consuming and expensive, which limits their application. Although various rapid soil testing methods have been suggested, their accuracy remains largely unexplored. Herein, multiple soil parameters were predicted using the spectral data obtained from inductively coupled plasma (ICP) spectroscopy combined with deep learning. We analyzed 1941 soil samples from seven countries with various land-use patterns and histories. All ICP wavelength spectral data from the 1 M NH
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