Machine learning and fluorosensing for estimation of maize nitrogen status at early growth-stages

•Fluorescence indices indicate discrimination capabilities of variable N rates in crop.•Assess accuracies of crop canopy N indicators estimated using machine learning model.•Model transferability in a cross-site experiment was assessed. Potential of mobile fluorescence sensor measurements have been...

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Veröffentlicht in:Computers and electronics in agriculture 2024-10, Vol.225, p.109341, Article 109341
Hauptverfasser: Mandal, Dipankar, Siqueira, Rafael de, Longchamps, Louis, Khosla, Raj
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Sprache:eng
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