Rapid analysis of layer manure using near-infrared reflectance spectroscopy

Diverse samples (n=91) were used to investigate the feasibility of near-infrared reflectance spectroscopy (NIRS) technology for rapid analysis of the nutrient composition of layer manure. Near-infrared reflectance spectroscopy calibration models for moisture, organic matter, total N, ammonium N, total P, total K, Cu, Fe, Mg, and Na were developed by using the modified partial least squares method. Results showed that the NIRS method could provide accurate predictions of moisture, organic matter, total N, and ammonium N concentrations, with a correlation coefficient of validation (r(v)(2)) and a ratio of SD over the root mean square error of prediction (RPD) of 0.86 (2.68), 0.89 (2.91), 0.88 (2.75), and 0.88 (2.62), respectively. Total P (r(v)(2)=0.80, RPD=2.01) could be approximately determined by NIRS. It was difficult to determine total K (r(v)(2)=0.58, RPD=1.51), Cu (r(v)(2)=0.48, RPD=1.38), Fe (r(v)(2)=0.55, RPD=1.47), Mg (r(v)(2)= 0.60, RPD=1.51), and Na (r(v)(2)=0.62, RPD=1.87) by NIRS.