:In this work, we numerically investigate the performances of optical regenerators based on self-phase modulation and spectral offset filtering at 40 Gbit/s. We outline the different effects affecting the device performances and explain the choice of the optimal working power. The impact of the regenerator on the output signal is also analysed through a statistical approach. Both single and double stage configurations are investigated.
Spectral measurements are employed in many precision agriculture applications, due to their ability to monitor the vegetation’s health state. Spectral vegetation indices are one of the main techniques currently used in remote sensing activities, since they are related to biophysical and biochemical crop variables. Moreover, they have been evaluated in some studies as potentially beneficial for detecting or differentiating crop diseases. Flavescence Dorée (FD) is an infectious, incurable disease of the grapevine that can produce severe yield losses and, hence, compromise the stability of the vineyards. The aim of this study was to develop specific spectral disease indices (SDIs) for the detection of FD disease in grapevines. Spectral signatures of healthy and diseased grapevine leaves were measured with a non-imaging spectro-radiometer at two infection severity levels. The most discriminating wavelengths were selected by a genetic algorithm (GA) feature selection tool, the Spectral Disease Indices (SDIs) are designed by exhaustively testing all possible combinations of wavelengths chosen. The best weighted combination of a single wavelength and a normalized difference is chosen to create the index. The SDIs are tested for their ability to differentiate healthy from diseased vine leaves and they are compared to some common set of Spectral Vegetation Indices (SVIs). It was demonstrated that using vegetation indices was, in general, better than using complete spectral data and that SDIs specifically designed for FD performed better than traditional SVIs in most of cases. The precision of the classification is higher than 90%. This study demonstrates that SDIs have the potential to improve disease detection, identification and monitoring in precision agriculture applications.
Although both initial residual leaf area and initial N reserves influenced alfalfa regrowth, the residual leaf area had a greater effect on final forage production and N composition in the taproot, whereas the N uptake rate and final total N content in plant were more affected by the initial N reserve status than by the residual leaf area. Moreover, N storage as proteins (especially as vegetative storage proteins, rather than nitrate or amino acids) in the taproot allowed nitrate uptake to occur at significant rates. This suggests that protein storage is not only a means of sequestering N in a tissue for further mobilization, utilization for growth or tissue maintenance, but may also indirectly influence both N acquisition and reduction capacities.
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