近红外光谱法测定苜蓿中的叶含量  

Prediction of Leaf Concentration in Alfalfa Using Near Infrared Reflectance Spectroscopy

作　　者：聂志东[1] 韩建国[1] 玉柱[1] 张录达[2] 

机构地区：[1]中国农业大学草地研究所,北京100094 [2]中国农业大学理学院,北京100094

出　　处：《光谱学与光谱分析》2008年第2期317-320,共4页Spectroscopy and Spectral Analysis

基　　金：农业部“948”项目和国家行业科技专项项目(nyhyzx07-022)资助

摘　　要：叶含量是一项对苜蓿的营养价值和家畜采食量、消化率都很重要的指标,目前常用的手工茎叶分离后测定叶含量的方法非常费时费力。利用近红外光谱分析技术(NIRS)对人工配制叶含量为15%～55%的41个苜蓿样品,建立了苜蓿中叶含量的预测模型。用15,25,35个定标样品分别建立的3个模型的RMSEP分别为1.02,1.97,0.51,RPD依次为5.50,2.85,25.93,外部验证的决定系数r2为0.9789,0.9844,0.9989。结果表明,15个定标样品已经能够建立准确测定苜蓿叶含量的近红外预测模型,且模型的准确性随着数量增加而升高。Leaf concentration in alfalfa is an important factor affecting the nutritive value, forage intake and digestibility. Estimates of leaf concentrations commonly used currently involve a labor intensive process of hand separating leaf and stem fractions. In the present study, a total of 41 artificial alfalfa samples were mixed with different leaf concentrations ranging from 15% to 55%. The object was to develop 3 calibrations for predicting alfalfa leaf concentrations using 15, 25 and 35 calibrated samples by near infrared reflectance spectroscopy. The root mean square error of prediction（RMSEP）was 1.02, 1.97 and 0. 51, respectively. External validation had a coefficient of determination （r^2 ） ranging from 0. 979 8 to 0. 998 9. The ratio of performance to standard deviation （RPD） varied from 2.85 to 25.93. The results showed that 15 samples could develop accurate NIRS model of alfalfa leaf concentrations; the calibration equations got better accuracy with the increase in calibrated samples numbers from 15 to 35.

关 键 词：近红外反射光谱 苜蓿 叶含量 

分 类 号：O657.3[理学—分析化学]