Poult. Sci.
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Poult Sci 2008. 87:1281-1286. doi:10.3382/ps.2007-00464
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ENVIRONMENT, WELL-BEING, AND BEHAVIOR

Rapid Analysis of Layer Manure Using Near-Infrared Reflectance Spectroscopy1

L. Xing*,{dagger}, L. J. Chen*,{ddagger} and L. J. Han*,{ddagger},2

* College of Engineering, China Agricultural University, Beijing 100083, China; {dagger} Industrial Technology Service Center, Chinese Academy of Agricultural Mechanization Sciences, Beijing 100083, China; and {ddagger} Key Laboratory of Modern Precision Agriculture System Integration, Ministry of Education, Beijing 100083, China

2 Corresponding author: hanlj{at}cau.edu.cn

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 (rv2) 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 (rv2 = 0.80, RPD = 2.01) could be approximately determined by NIRS. It was difficult to determine total K (rv2 = 0.58, RPD = 1.51), Cu (rv2 = 0.48, RPD = 1.38), Fe (rv2 = 0.55, RPD = 1.47), Mg (rv2 = 0.60, RPD = 1.51), and Na (rv2 = 0.62, RPD = 1.87) by NIRS.

Key Words: near-infrared reflectance spectroscopy • modified partial least squares • layer manure • prediction

1 Supported by the Excellent Young Teachers Program of Ministry of Education, Beijing, P. R. China.






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