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University of Idaho (2008)

Remote sensing of wheat nitrogen status for improved protein management in dryland systems

Eitel, Jan Ulrich Hermann

Titre : Remote sensing of wheat nitrogen status for improved protein management in dryland systems

Auteur : Eitel, Jan Ulrich Hermann

Université de soutenance : University of Idaho

Grade : Doctor of Philosophy (PhD) 2008

Résumé
Growers require pre-harvest information about grain protein to optimize nitrogen (N) fertilizer inputs and grain harvest. The aim of this dissertation was to predict final grain protein of dryland wheat based on mid-seasonal remote sensing data. Grain protein predictions have relied on weather, cultivar and crop N status information. The latter has been remotely sensed by means of spectral indices. These indices generally employ narrow wavebands (40 nm) are a viable alternative to higher-cost and less-available narrow-band imagery (waveband <40 nm). The results suggest that broad-band satellite data are suitable when the new index MCARI/MTVI2 is employed. Chapter 4 describes the methodology and assumptions of a new protein prediction approach that combines remote predictions of crop N status with weather and cultivar performance data. The models show to predict final grain protein concentration (GPC) well at the model development site (0.87 ≤ Residual Mean Square Error ≤ 50.93 ; 0.74 ≤ r2 ≤ 0.77) but less well when validated with independent data (0.87 ≤ Residual Mean Square Error ≤ 1.90 ; 0.06 ≤ r2 ≤ 0.68).

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Page publiée le 16 mai 2011, mise à jour le 9 mars 2019