The influence of factors, including canopy structure, needs to be eliminated before using canopy reflectance to estimate N concentration 8. This method has been used to monitor the chlorophyll, lignin, N, and water status of vegetation 3, 6, 7. Multispectral and hyperspectral remote sensing are nondestructive methods of estimating the foliar biochemical concentration of vegetation 4, 5. Considering that plant N content is strongly influenced by growth stages, we measured LNCs in the present study. As an important indicator for crop growth diagnosis, the concept of plant N concentration is based on dry matter 2, while plant N content is based on field area, and is the product of N concentration and dry biomass 3.
Thus, accurate monitoring of the status of rice leaf N concentration (LNC) not only enables high yields but also improves the efficiency of applied nitrogenous fertilizer and prevents eutrophication. Nitrogenous fertilizer is used extensively because nitrogen (N) supply is a crucial factor in improving crop yields. In addition, immoderate application of fertilizers has given rise to serious environmental consequences, such as water eutrophication and soil hardening 1.
The expansion of cities has resulted in a decrease in available land for paddies. Rice ( Oryza sativa) is a daily necessity among people. Estimation of rice LNC could be significantly improved with the finer spectral resolution of HSL compared with MSL ( R 2 = 0.56). Results demonstrated that HSL provided the best indicator for predicting rice LNC, yielding a coefficient of determination ( R 2) of 0.74 and a root mean square error of 2.80 mg/g with a support vector machine, similar to the performance of ASD ( R 2 = 0.73). Spectral reflectance and biochemical composition were determined in rice leaves of different cultivars (Yongyou 4949 and Yangliangyou 6) throughout two growing seasons (2014–2015).
#Multispec inc pro#
This study compared the performance of ASD FieldSpec Pro FR, MSL, and HSL for estimating rice ( Oryza sativa) LNC. With more wavelengths than MSL, the hyperspectral LiDAR (HSL) system provides greater possibilities for remote sensing crop physiological conditions. In the last decade, multispectral LiDAR (MSL) systems have promoted developments in the earth and ecological sciences with the additional spectral information. Fast and nondestructive assessment of leaf nitrogen concentration (LNC) is critical for crop growth diagnosis and nitrogen management guidance. Also, Anti-X-Talk™ technology enables the use and interchange of a wide range of lens types on the same camera and allows better light collection efficiency since filter response is insensitive to large aperture settings (e.g., f/2.8). Furthermore, high quality image data from the MSC and MSC2 cameras can be used as is without the need for proprietary post-processing algorithms. The result is multispectral images with better spectral discrimination and higher contrast. It works by blocking stray light between adjacent filters, so the pixel response is predictable and directly related to the actual spectral response of the overlying pixelated filter. Spectral Devices invented Anti-X-Talk™ technology to overcome these problems.
Without Anti-X-Talk™ technology, images suffer from low contrast and spectral ambiguity. Without Anti-X-Talk™ technology, stray light between spectral channels is significant, often exceeding the light leakage due to spectral overlap between adjacent filters. Anti-X-Talk™ technology works at the filter level and prevents light leakage between individual filters. Anti-X-Talk™ technology is unique to Spectral Devices multispectral cameras.
0 kommentar(er)
