Near-Infrared Spectroscopy and Wet Chemistry Dataset for Forage Nutritional Quality Assessment in Urochloa humidicola

Attributes such as the nutritional quality of pastures are characteristics that can be used to select better pastures and thus obtain a greater amount of meat and milk from livestock feed. However, the laboratory analytical method by which it is calculated is not cost effective in trials with a large number of plants, so developing methods that allow extensive evaluation and precise and non-destructive selection of nutritionally promising genotypes is a need. From 2011 to 2019, samples of Urochloa humidicola (Rendle) Morrone & Zuloaga from the breeding program have been harvested to collect near-infrared (NIR) spectroscopy data at the Alliance of Bioversity and CIAT . This data set comprises a total of 1012 samples, where each sample includes absorbance data from 400 to 2498 nanometers (nm), with step intervals of 2 nm, thus presenting only the pair values of the spectrum for a total of 1050 absorbance data for each sample. In addition, it includes wet chemistry data from, 995 samples analyzed for neutral
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Methodology: The grasses from which the samples were taken for this data set come from field trials of the U.humidicola breeding program of the Alliance of Bioversity International and CIAT in different locations in Colombia, to evaluate the performance of these grasses in different environments and climatic conditions. The samples were collected using a 50 by 50 cm quadrant in plots of 1m x 1 m, with 4-6 wk regrowth after cutting. The sampled tissue was dried in an air force Memmert UF750 PLUS ( GmH + Co. KG ) oven at 60°C for 72 h, ground using a Retsch SM 100 cutting laboratory mill (Retsch GmbH) with 1-mm sieve size, packed in plastic bags and labelled for later use in the chemical and spectral analyses. The chemical analyses were performed at the CIAT forages and animal nutrition quality laboratory. Concentrations of NDF and ADF were measured sequentially, according to operating instructions, using an ANKOM 2000 fiber analyzer (Ankom Technology,2011) and according to the methods of Van Soest and Robertson (1985).