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The effect of LUE optimisation on remote-sensing based yield modelling
Cód:
491_9783659542589

Por: R$ 540,49ou X de

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Crop models seek to quantify relationships between weather, crop growth and effects of management to allow yield prediction, diagnosis, management decision and environmental assessment. This study assesses if spatial optimisation of light use efficiency (LUE) in a semi-emprical model improves yield prediction within fields of winter rape. Three fields of winter rape were measured for yield and global solar radiation. This data was used together with fAPAR and climate efficiency to optimise LUE and then compare accuracy levels of Monteiths model and empirical model. In empirical modelling, measured yield was related to ANDVI using regression analysis. Field 1 data was used for calibration while fields 2 and 3 data was used for validation. Results show that Montheiths model with pixel optimised LUE values does improve yield prediction accuracy and the accuracy levels are higher than using empirical model, or than Montheiths model with a constant from literature or than Monteiths model with a constant field optimised LUE value.
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