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Multispec inc11/13/2022 ![]() Nevertheless, their wavelength number is limited to 2–3. A few promising commercial multispectral laser scanners have been developed 18, 19, 20. Recently, MSL/HSL systems have been applied to estimate leaf moisture contents under laboratory conditions 15, represent the chlorophyll content of harvested Scots pine shoots 16, and reflect leaf nitrogen content levels 17. Compared with traditional single-wavelength LiDAR systems such as active flash sensor (AFS) and GreenSeeker (NTech Industries, Inc., Ukiah, CA), multispectral LiDAR (MSL) and hyperspectral LiDAR (HSL) with high spectral resolution allow for increased sensitivity to characterize leaf biochemistry by emitting separate laser beams simultaneously, or utilizing a supercontinuum laser source with a wide spectrum range and a multi-channel detector. LiDAR intensity is useful in retrieving plant chlorophyll content 12, nitrogen status 13, and leaf water content 14. The potential use of the intensity of point clouds in plant biochemistry estimation needs further exploration 11. Given the advantage of obtaining precise three-dimensional (3D) information, light detection and ranging (LiDAR) has undergone advanced developments in quantifying the 3D surface properties and processes in earth and ecological sciences 9, 10. However, passive remote sensing is often influenced by multiple aerial/atmospheric condition factors, including pollution, clouds, and solar zenith angle. 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. ![]()
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