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Determination of Romanian alfalfa crude protein and crude fiber contents as well as in vitro organic matter digestibility by NIR spectrometry

机译:近红外光谱法测定罗马尼亚苜蓿粗蛋白和粗纤维含量以及体外有机物消化率

摘要

Alfalfa (Medicago sativa L.) is a high quality forage which has been used worldwide. The superiority of alfalfa lies in its high yield, high protein content and high digestibility. The aim of this study was to develop a simple, fast and non-destructive method, named Near Infrared Spectroscopy (NIRS) to determinate alfalfa quality. To realize this study, alfalfa samples were obtained from Mănăştur Experimental Station – Farm Cojocna in 2008–2009, in one experiment carried out using randomization blocks design with two experimental factors (mineral fertilization and period of harvest). Alfalfa quality was first determinated on 48 samples by classical analyses: crude protein CP (AOAC, 1990), crude fiber CF (Fiber Cap, FOSS, DK) and in vitro organic matter digestibility OMDrt (DeBoever, 1986). Then the samples were scanned by NIRS. Calibration models were performed by PerkinElmer Spectrum Quant + 4.21 program (USA) on the 48 samples determinated by classical analysis. The results showed fully confirmed by acceptable coefficients of determination and standard error of cross-validation (R2=0.96 for CP, 0.94 for CF, 0.98 for OMDrt and SECV=0.77 for CP, 1.35 for CF, 1.13 for OMDrt). Successful results for prediction of other 176 alfalfa samples were then obtained using these calibration models: SEP=0.869 for CP, 1.058 for CF, 1.058 for OMDrt). The highest CP and OMDrt values of alfalfa were obtained in bud stage (22.0% and 66.0% respectively). While for CF, the highest content was registered in the seed formation stage (46.0%). The NIRS technique offers us the possibility to determinate rapidly and easily Romanian alfalfa important parameters, but the system could also be used for the determination of other constituents.
机译:紫花苜蓿(苜蓿(Medicago sativa L.))是已在世界范围内使用的高质量草料。苜蓿的优势在于其高产量,高蛋白含量和高消化率。这项研究的目的是开发一种简单,快速且无损的方法,称为近红外光谱(NIRS),用于确定苜蓿的质量。为了实现这项研究,在2008–2009年从Mănăştur实验站– Cojocna农场获得了苜蓿样品,其中一项实验是使用具有两个实验因素(矿物施肥和收获期)的随机区组设计进行的。苜蓿的质量首先通过经典分析在48个样品上确定:粗蛋白CP(AOAC,1990),粗纤维CF(Fiber Cap,FOSS,DK)和体外有机物消化率OMDrt(DeBoever,1986)。然后通过NIRS扫描样品。通过PerkinElmer Spectrum Quant + 4.21程序(美国)对经典分析确定的48个样品进行校准模型。通过可接受的测定系数和交叉验证的标准误差充分证实了结果(CP的R2 = 0.96,CF的0.94,OMDrt的0.98,CP的SECV = 0.77,CF的1.35,OMDrt的1.13)。然后,使用这些校准模型获得了其他176个苜蓿样品的成功预测结果:CP的SEP = 0.869,CF的1.058,OMDrt的1.058。紫花苜蓿在萌芽期获得最高的CP和OMDrt值(分别为22.0%和66.0%)。而对于CF,在种子形成阶段的含量最高(46.0%)。 NIRS技术为我们提供了快速而轻松地确定罗马尼亚苜蓿重要参数的可能性,但该系统也可用于确定其他成分。

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