Estimation of Low Organic Matter Content in Desert Soil of Arid Area Based on Fractional Order Sprott Chaotic Circuit and Gray Theory

Weak spectral response and low model accuracy problems occurred in the process of quantitative inversion of low organic matter content of desert soil in arid areas. This study collects soil samples and field spectral data from different human interference regions in Fukang City, Xinjiang, to search the soil hyperspectral response law that based on the fractional Sprott chaotic system, and combined with the gray system theory to estimate organic matter content rapidly and accurately. Simulation shows that for those sampling soil with lower organic matter content, the range of X and Y components of the dynamic error motion curve distribution of the Sprott chaotic system is larger, and the motion curve of the non-integer order 1.9-order dynamic error is the most obvious. Since the chaotic attractors will appear as a linear trend according to different contents of the organic matter, so this thesis establishes a gray prediction model based on the 1.9 fractional order chaotic attractors. The R-2, RPD, and RMSE of the low organic matter content in the region without human interruption are 0.995, 14.86, and 0.17, respectively. The R-2, RPD, and RMSE of low organic matter content in the region with human interruption are 0.992, 11.95, and 0.11, respectively. This study demonstrates that it is feasible to estimate the low organic matter content of desert soils in arid regions via the gray prediction model that based on fractional chaotic attractors. This study provides a novel method for soil spectra signal analysis and estimation of the organic matter content.