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Futing (Eds.), Encyclopedia of social sciences research methods (pp. This new approach may be potentially applied to precision apple orchard nutrient management.Ībdi, H. Furthermore, nitrogen distribution maps at both leaf and canopy levels were generated based on the nitrogen contents estimated by the MLR model based on raw reflectance.
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However, the MLR model based on raw reflectance demonstrated its advantage over the PLS models as well as the MLR model based on first derivative reflectance, because it only used 4 key wavelengths (505, 560, 675 and 705 nm) while the other models were based on either the full wavelengths (132 wavelengths) or more narrowband wavelengths adjacent to the selected key wavelengths. The results showed that both PLS and MLR models achieved reasonable predictive accuracy (PLS and MLR models based on raw reflectance: R 2 = 0.7728 and 0.7843 (p < 0.001) PLS and MLR models based on first derivative reflectance: R 2 = 0.7745 and 0.774 (p < 0.001)). Partial least squares (PLS) regression and multiple linear regression (MLR) analyses were performed to estimate nitrogen content from reflectance.
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Raw reflectance and first derivative reflectance were used to relate to leaf nitrogen content.
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Nitrogen content in apple leaves was measured by Vario EL cube. An ImSpector V10 system was used to collect hyperspectral images (400–1000 nm) for both apple leaves and canopies. This study presents a rapid and non-destructive approach for estimation and mapping of nitrogen content in apple trees at both leaf and canopy levels. Accurate and rapid diagnosis of nitrogen status in fruit trees on an individual tree basis is a prerequisite for precision orchard nutrient management.