利用近红外光谱技术快速分析全株玉米青贮营养成分

研究旨在利用近红外光谱技术(near infrared reflectance spectroscopy,NIRS)建立全株玉米青贮6种营养成分的近红外预测模型,为生产实践中合理利用全株玉米青贮饲料资源提供理论依据。选取玉米青贮样品64份作为定标集,16份作为验证集。利用NIRS结合改良偏最小二乘法(modified partial least squares,MPLS)构建并且验证其建立预测模型的优劣。结果表明:构建的玉米青贮干物质(DM)、粗蛋白(CP)、酸性洗涤纤维(ADF)和粗灰分(Ash)预测模型的交叉验证相关系数(1-VR)分别为0.83、0.80、0.93和0.78,都在0.80左右,可以用于实际预测。粗脂肪(EE)和中性洗涤纤维(NDF)含量预测模型1-VR为0.64和0.40,低于0.80,构建的模型相关性较差,模型还需要进一步优化。

Rapid Analysis of Nutritional Components of Whole Plant Silage Using Near-Infrared Spectroscopy

The purpose of this study was to use near-infrared reflectance spectroscopy(NIRS)to establish a near-infrared prediction model of 6 types of nutrients in Whole Plant Corn Silage and to provide the theoretical basis.64 corn silage samples were selected as the calibration sets and 16 were used as the validation sets.NIRS was used with combination of Modified Partial Least Squares(MPLS)to construct and verify the pros and cons of establishing a prediction model.The results showed that the cross-validation correlation coefficients(1-VR)of the corn silage DM,CP,ADF,and Ash prediction models were 0.83,0.80,0.93,and 0.78,all around 0.80,which can be used for actual prediction.The EE and NDF content prediction models 1-VR were 0.64 and 0.40,lower than 0.80.The correlation of the constructed models was poor,and the models needed further optimization.