【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。更多还原

【Abstract】 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(r2) 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.更多还原