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中文摘要：
试验共采集我国北方不同区域、不同生育期、不同干燥方式的羊草干草150份，利用近红外漫反射光谱（NIRS）技术，采用偏最小二乘回归算法（PLS），在国内首次建立了适配范围广的羊草干草的粗蛋白（CP）、中性洗涤纤维（NDF）和酸性洗涤纤维（ADF）的校正模型，并对模型的预测能力进行了验证。结果表明，所建模型的预测结果与常规化学分析得到的结果十分相近：交互验证相关系数（Rcv）分别为0．9637，0．9594和0．9479，交互验证误差（RSECV）分别为1．41％，1．27％和1．27％；外部验证相关系数为0．965，0．956和0．953；并且验证集样品的标准差与预测标准差之比均大于3．0。由此可见，近红外光谱技术可以准确预测羊草干草中的CP，NDF和ADF含量，这对于快速测定我国羊草的品质、准确筛选优质的育种材料均具有十分重要的意义。
英文摘要：
One hundred fifty Leymus chinensis samples with different growth stage, areas, and preparing method （oven-drying and shading natural dry）, were selected to study the potential of determination of crude protein（CP）, neutral detergent fiber （NDF）and acid detergent fiber（ADF）in the present research. The quality parameters of Leymuschinensis were firstly predicted using the near infrared reflectance spectroscopy in China. The three models were validated by cross-validation and external-validation. The results indicated that the NIRS models of Le3nnus chinensis quality prediction highly accessed the precision of chemical analysis. The coefficient of correlation of cross-validation of crude protein, neutral detergent fiber and acid detergent fiber were 0. 963 7, 0. 959 4 and 0. 947 9, and the RMSECV of the three models were 1.41%, 1.27% and 1.27%, respectively; the correlation coefficients of external-validation were 0. 965, 0. 956 and 0. 953, and all the ratios of standard deviation to root mean square error of prediction were higher than 3. Thus it can be testified that using NIRS analysis can rapidly and accurately determine the quality of Leymus chinensis. This method is of great significance for quick analysis of the trait of Leymus chinensis production and screening of breeding materials in Leymus spp. research of China.
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