苜蓿干草常规营养成分含量近红外预测模型的建立

Near Infrared Prediction Model Establishment for Routine Nutritional Component Contents of Alfalfa Hay

本试验旨在建立一线生产企业所用苜蓿干草常规营养成分含量的近红外预测模型。从9个省份的奶牛场及牧草生产企业采集265个苜蓿干草草捆样品,利用近红外光谱技术,采用偏最小二乘(PLS)的化学计量学方法,结合4种散射校正和10种导数处理方法,建立苜蓿干草干物质(DM)、粗蛋白质(CP)、中性洗涤纤维(NDF)、酸性洗涤纤维(ADF)和粗灰分(Ash)含量这5个指标的近红外预测模型。结果显示:CP含量的预测决定系数(RSQ V)和外部验证相对分析误差(RPD V)最高,而DM、NDF和ADF含量的RSQ V和RPD V略低于CP;DM、CP、NDF和ADF含量这4个指标的RSQ V均大于0.80、RPD V均大于2.50,说明这4个指标的建模效果较好,能用于实际含量测定;Ash含量的RSQ V和RPD V分别为0.793和2.102,分别低于0.80和2.50,说明Ash含量的预测模型仅能用于粗略筛选,暂不能用于实际含量测定。综上所述,本试验初步建立苜蓿干草DM、CP、NDF和ADF含量这4个指标的近红外预测模型,为生产中快速高效测定苜蓿干草这4个指标提供了便利。

In order to establish the near infrared prediction model of routine nutritional component contents of alfalfa hay used by manufacturing enterprises,a total of 265 alfalfa hay bale samples were collected from dairy farms and forage production enterprises in nine provinces.Using near-infrared spectroscopy by partial least squares(PLS)method with four spectral pretreatments and ten derivative treatments,this study established the near infrared prediction models of five indexes[including dry matter(DM),crude protein(CP),neutral detergent fiber(NDF),acid detergent fiber(ADF)and ash(Ash)contents]of the alfalfa hay.The results showed that the coefficient of determination for validation(RSQ V)and the ratio of performance to deviation for validation(RPD V)of CP content were the highest,while those of DM,NDF and ADF contents were slightly lower than those of CP content.The RSQ V and RPD V of DM,CP,NDF and ADF contents were higher than 0.80 and 2.50,respectively,indicating that the modeling effects of the four indexes were good and could be used to detect the actual content.However,the RSQ V of Ash content was 0.793 and was lower than 0.80,while the RPD V was 2.102 and was lower than 2.50.It showed that the model of Ash content could only be used for the rough prediction and could not be used to detect the actual content.In conclusion,the near-infrared prediction models of DM,CP,NDF and ADF contents of alfalfa hay are preliminarily established,which improves the convenience for the rapid and efficient determination of these four indexes in production.