摘要
红外光声光谱是基于光声理论的新型数据采集方式,与传统红外光谱相比,其吸收系数大,适合高吸收和高散射的土壤分析。以中国三种典型土壤为试验材料,研究了这三种土壤(红壤,潮土和水稻土)的中红外光声光谱特征。结果表明,土壤的中红外光声光谱的测定快速方便,土壤样品不需前处理,光谱吸收值适中,具有更丰富的吸收,且土壤主要组成成分的中红外光声光谱也具有明显不同的吸收特征,因此中红外光声光谱能更好地适用于土壤分析;利用主成分分析处理土壤中红外光声光谱时,第1和第2主成分包含了光谱98.17%的信息;利用这两个主成分作二维散点分布图,结果表明该分布能对这三种土壤进行有效分类,这为土壤鉴定提供了快捷的新手段,并使中红外光声光谱在进一步的土壤定量分析中将具有潜在的应用前景。
Infrared photoacoustic spectroscopy （PAS） is a new style to obtain data based on photoacoustic theory. Photoacoustic thoeory is based on the absorption of electromagnetic radiation by analyte molecules, and the absorbed energy is measured by detecting pressure fluctuations in the form of sound waves or shock pulses. In contrast to conventional absorption spectroscopy, PAS allows the determination of absorption coefficients over several orders of magnitude, even in very black and strongly scattering soil samples. Red soil, fulvic soil and paddy soil were collected from Fengqiu National Ecological Experimental Station, Yingtan Red Soil Experimental Station, and Changshu Ecological Experimental Station, respectively. These soil samples were used as experimental materials to characterize the Fourier transform mid-infrared photoacoustic spectra （FTIR-PAS）. Compared with infrared transmittance spectra and reflectance spectra, the testing of FTIR-PAS spectra was very fast and convenient without any pr-treatment, and there were more abundant absorptions as well as appropriate absorption values in the spectra; The main soil components （kaolin, bentonite, sand and CaCO3 ） also showed several strong absorptions with specific characteristics in the spectra; Further more, the interference of water with the PAS spectra was significantly smaller than that with reflectance spectra. Therefore, the soil properties could be better characterized by FTIR-PAS. The principal components analysis based on the FTIR-PAS spectra indicated that there were two main principal components （PCA1, PCA2） which contained 98.17% variance of the spectra, and the two-dimensionol distribution was made by plotting these two principal components to classify the soil type, and the results indicated that this distribution could be applied to distinguish soil type, which provided new technique for soil identification as well as further quantitative analysis in soil science.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2008年第6期1242-1245,共4页
Spectroscopy and Spectral Analysis
基金
国家高新技术计划"863"项目(2006AA10A301)资助
关键词
土壤
红外光声光谱
主成分分析
土壤鉴定
Soils Infrared photoacoustic spectroscopy
Principal components analysis
Soil identification
