Dorshorst M E, Hoffman P C
Department of Dairy Science, University of Wisconsin-Madison, 53706, USA.
J Dairy Sci. 2000 Jul;83(7):1503-4. doi: 10.3168/jds.S0022-0302(00)75022-3.
Previous research from our laboratory has demonstrated that near-infrared reflectance spectroscopy has utility in predicting rumen-undegradable protein (RUP) contents of legume and grass silages. This study was conducted to evaluate whether application of previous research techniques could yield a useful near-infrared reflectance spectroscopy RUP prediction system for legume and grass hays. Legume and grass hays (n = 106) were evaluated for RUP content by in situ techniques in four ruminally cannulated cows. In situ RUP for legume and grass hays averaged 25.9% CP and ranged from 14.6 to 45.5% CP, respectively. We developed a near-infrared reflectance spectroscopy RUP calibration equation for the legume and grass hay data set using in situ RUP contents as base data. This procedure resulted in an acceptable (R2 = 0.87, SE = 2.46% CP) near-infrared reflectance spectroscopy equation to predict RUP content of legume and grass hays. Data suggest that near-infrared spectroscopy predicts RUP contents of legume and grass hays with accuracies similar to legume and grass silages.
我们实验室之前的研究表明,近红外反射光谱法可用于预测豆科和禾本科青贮饲料中瘤胃不可降解蛋白(RUP)的含量。本研究旨在评估应用先前的研究技术是否能为豆科和禾本科干草建立一个有用的近红外反射光谱法RUP预测系统。通过在四头装有瘤胃瘘管的奶牛中采用原位技术,对豆科和禾本科干草(n = 106)的RUP含量进行了评估。豆科和禾本科干草的原位RUP平均粗蛋白含量为25.9%,分别在14.6%至45.5%之间。我们以原位RUP含量作为基础数据,为豆科和禾本科干草数据集建立了一个近红外反射光谱法RUP校准方程。这一过程得出了一个可接受的(R2 = 0.87,标准误 = 2.46%粗蛋白)近红外反射光谱法方程,用于预测豆科和禾本科干草的RUP含量。数据表明,近红外光谱法预测豆科和禾本科干草RUP含量的准确性与预测豆科和禾本科青贮饲料的准确性相似。