Prediction of the nutritional value of grass species in the semiarid region by repeatability analysis

Abstract: The objective of this work was to estimate the repeatability (r) and the number of samples required to measure the nutritional value of four warm-season forage grasses growing in a semiarid region. The grasses evaluated were Urochloa mosambicensis, Cenchrus ciliaris, Digitaria pentzii, and Megathyrsus maximus. Evaluations occurred under two forage management conditions: stockpiling and grazing. Hand-plucked forage samples were analyzed for dry matter (DM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), lignin, and in vitro DM digestibility (IVDMD). Four methods were used to estimate r and the number of samples required: analysis of variance, method of principal components based on the covariance (PCCOV) and the correlation (PCCOR) matrices, and structural analysis (EVCOR). Species were compared by the probability of the difference using the t-test. The method PCCOV presents the highest coefficient of repeatability and, therefore, a lower number of samples required. Lignin is the trait that have the highest number of samples required. In terms of qualitative traits, D. pentzii and M. maximus show the best forage qualities among the species evaluated.

摘要：本研究旨在估算半干旱地区种植的4种暖季饲用牧草的重复性（repeatability, r），并明确测定其营养价值所需的样本量。供试牧草分别为穆桑比臂形草（Urochloa mosambicensis）、非洲狗尾草（Cenchrus ciliaris）、彭氏马唐草（Digitaria pentzii）及大黍（Megathyrsus maximus）。试验设置两种饲草管理模式：堆贮管理与放牧管理。研究人员对人工拔取的饲草样品开展指标分析，测定指标包括干物质（dry matter, DM）、粗蛋白（crude protein, CP）、中性洗涤纤维（neutral detergent fiber, NDF）、酸性洗涤纤维（acid detergent fiber, ADF）、木质素以及体外干物质消化率（in vitro DM digestibility, IVDMD）。本研究采用4种方法估算重复性与所需样本量：方差分析法、基于协方差矩阵的主成分分析法（PCCOV）、基于相关系数矩阵的主成分分析法（PCCOR）以及结构分析（EVCOR）。采用t检验的差异概率法对各供试物种进行比较。结果显示，PCCOV法的重复性系数最高，因此所需样本量最少。木质素是所有测定性状中所需样本量最多的指标。就饲用品质性状而言，彭氏马唐草与大黍在供试牧草中表现出最优的饲用品质。