光谱学与光谱分析 |
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Near Infrared Spectral Analysis and Measuring System for Primary Nutrient of Soil |
GAO Hong-zhi1,2, LU Qi-peng1* |
1. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China 2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China |
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Abstract Soil is the foundation of agricultural production. Rapid analysis of soil nutrients, using near infrared spectral analysis technology, can guide process of agricultural production. Developing near-infrared measuring system with discrete wavelength will change the extensive operation situation of agricultural production. First, the spectra of 85 black soil samples of northeast China, collected by FOSS XDS near-infrared spectrometer were analyzed using the correlation spectra and successive projection algorithm. Then, the characteristic wavelengths of total nitrogen and organic matter were obtained. After that the authors collected the spectra of soil samples using the measuring system with high signal to noise ratio (SNR) that the authors developed. The calibration models for total nitrogen and organic matter were established. The root mean square error of prediction (RMSEP) of total nitrogen and organic matter is 0.019% and 0.36% respectively, and the correlation coefficient of prediction (Rp) is 0.851 and 0.923, respectively. Experimental results indicate that the characteristic wavelengths for total nitrogen and organic matter can be obtained through the near infrared spectra analyses. The measuring system can be used for soil nutrient analysis and lays the foundation for the industrial applications.
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Received: 2010-06-28
Accepted: 2010-09-29
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Corresponding Authors:
LU Qi-peng
E-mail: luqipeng@126.com
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[1] Cozzolino D, Moro′n A. Soil & Tillage Research, 2006, 85: 78. [2] CHEN Xing-dan(陈星旦). Optics and Precision Engineering(光学精密工程),2008, 16(5): 759. [3] ZHANG Yi-hui, LAO Cai-lian, JI Hai-yan, et al(张晔晖, 劳彩莲, 吉海彦,等). Modern Instruments(现代仪器),2001, (5): 11. [4] ZHANG Jun, CHEN Xing-dan, PIAO Ren-guan, et al(张 军, 陈星旦, 朴仁官,等). Optics and Precision Engineering(光学精密工程), 2008, 16(6): 986. [5] Lü Jin, ZHAO Xin-xiang, LIU Hui-jun, et al(吕 进, 赵鑫祥, 刘辉军,等). Chinese Journal of Scientific Instrument(仪器仪表学报),2009, 30(11): 2411. [6] WANG Dong-min, JIN Shang-zhong, CHEN Hua-cai, et al(王动民, 金尚忠, 陈华才,等). Optics and Precision Engineering(光学精密工程),2008, 16(11): 2051. [7] GUO Zhi-ming, ZHAO Jie-wen, CHEN Quan-sheng, et al(郭志明, 赵杰文, 陈全胜,等). Optics and Precision Engineering(光学精密工程),2009, 17(8): 1839. [8] DING Hai-quan,LU Qi-peng,PIAO Ren-guan,et al(丁海泉,卢启鹏,朴仁官,等). Optics and Precision Engineering(光学精密工程),2007,15(12):1946. [9] HUANG Fu-rong,PAN Tao,ZHANG Gan-lin,et al(黄富荣,潘 涛,张甘霖,等). Optics and Precision Engineering(光学精密工程),2010,18(3):586. [10] Galvo R K H, Araújo M C U, Fragoso W D. Chemometrics and Intelligent Laboratory Systems,2008, 92(1): 83. [11] Verboven S, Hubert M. Chemometrics and Intelligent Laboratory Systems ,2005, 75: 127. [12] Galvo R K H, Araújo M C U, Jose G E, et al. Talanta, 2005, 67: 736. [13] CHEN Xing-dan(陈星旦). Near Infrared Spectroscopy Technology in Modern China(当代中国近红外光谱技术). Beijing: China Petrochemical Press(北京: 中国石化出版社),2006. [14] LU Wan-zhen(陆婉珍). Modern Near-Infrared Spectroscopy Analytical Technology(现代近红外光谱分析技术). Beijing:China Petrochemical Press(北京:中国石化出版社),2006.
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