老芒麦(Elymus sibiricus L.)是青藏高原地区主要禾本科牧草,对该区畜牧业具有重要作用.粗蛋白(CP)、酸性洗涤纤维(ADF)、中性洗涤纤维(NDF)和体外干物质消化率(IVDMD)是影响牧草营养价值高低的主要参数.基于近红外光谱技术(NIRS)结合偏最小二乘法建立了老芒麦CP,ADF,NDF和IVDMD的近红外预测模型.所建CP,ADF,NDF和IVDMD模型校正决定系数(R2cal)分别为0.994　5,0.949　9,0.913　3和0.982　2,校正标准差(SEC,%DM)分别为0.329　9,0.779　9,1.343　0和1.376　2;验证决定系数(R2val)分别为0.993　8,0.944　9,0.890　7和0.979　0,验证标准差(SEP,%DM)分别为0.362　1,0.787　8,1.385　2和1.430　3.预测相关系数(r)大于0.943　8,相对分析误差(RPD)为3.02~12.63,表明NIRS能够对老芒麦CP,ADF,NDF和IVDMD进行准确分析.

AbstractSiberian wildrye (Elymus sibiricus L.) is one of the predominant pasture species in Qinghai-Tibet plateau of China.It supplies a large number of fodders to domestic animals in spring and winter,and provides a large proportion of the summer and autumn grazing in these alpine regions.Crude protein (CP),acid detergent fiber (ADF),neutral detergent fiber (NDF) and　in vitro dry matter digestibility (IVDMD) are the most important aspects of nutritive value of forages.A successful application of near infrared spectroscopy (NIRS) in combination with partial least square regression (PLSR) for the determination of four parameters (CP,ADF,NDF and IVDMD) of Siberian wildrye was developed.The standard errors of calibration (SEC,%DM) and R2cal values (in parentheses) were 0.329　9(0.994　5),0.779　9(0.949　9),1.343　0(0.913　3),and 1.376　2(0.982　2) for CP,ADF,NDF and IVDMD equations,respectively.The standard errors of prediction (SEP,%DM) and R2val values (in parentheses) were 0.362　1(0.993　8),0.787　8(0.944　9),1.385　2(0.890　7),and 1.430　3(0.979　0) for CP,ADF,NDF and IVDMD,respectively.A good correlation (r>0.943　8) was found between results from NIRS and the traditional chemical method,and residual predictive deviation (RPD) ranged from 3.02 to 12.63.It was concluded that NIR spectroscopic technique associated with chemometrics is sufficiently sensitive to allow the accurate prediction of the concentrations of components (CP,ADF and NDF) and IVDMD of Siberian wildrye.