Comparative Sensitivity of Vegetation Indices Measured via Proximal and Aerial Sensors for Assessing N Status and Predicting Grain Yield in Rice Cropping Systems

Reflectance-based vegetation indices can be valuable for assessing crop nitrogen (N) status and predicting grain yield. While proximal sensors have been widely studied in agriculture, there is increasing interest utilizing aerial sensors. Given that few studies compared sensors, the objective of this study was to quantitatively compare sensitivity aerially sensed Normalized Difference Vegetation Index (NDVI) Red-Edge (NDRE) proximally NDVI total N uptake at panicle initiation (PI-NUP) yield rice. Nitrogen response trials were established over a 3-year period (10 site-years) various locations throughout Sacramento Valley rice growing region California. At PI, multispectral unmanned aircraft system (UAS) used measure NDVIUAS NDREUAS (average ground sampling distance: 3.7 cm pixel?1), GreenSeeker (GS) sensor record NDVIGS. To enable direct comparisons across different on an equivalent numeric scale, each index normalized by calculating Sufficiency-Index (SI) relative non-N-limiting plot. Kernel density distributions indicated had narrower range values poorly differentiated NDVIGS NDREUAS. The critical PI-NUP where yields did not increase with higher averaged 109 kg ha?1 (±4 ha?1). relationship between SI saturated lower than (96 ha?1), whereas 111 130 ha?1, respectively. This indicates less suitable making management decisions stage Linear mixed effects models developed evaluate how well measured PI able predict least sensitive variation as reflected having highest slope (2.4 Mg per 0.1 SI). In contrast, slopes 0.9 1.1 SI, respectively, indicating greater yields. Altogether, these results indicate ability inform depends measurement platform used. Both produced measurements enough fertilizer system, more limited.