Estimating Roughage Quality with Near Infrared Reflectance (NIR) Spectroscopy and Chemometric Techniques

Near-Infrared Spectroscopy has been commonly adopted in feed quality evaluations. The majority of studies havebeen performed on the detection of fibrous components with the help of NIR. Model development studies arenot yet common for different roughage quality characteristics such as Relative Forage Value (RFV), RelativeForage Quality (RFQ), and Net Energy Lactation (NEL), which are used in the evaluation of roughage quality.The purpose of this study is the detection of RFV, RFQ, and NEL values with NIR spectroscopy in differentroughage samples, and to investigate the effect of wavelength selection on the model's success. In this study,spectral data belonging to silage, dry alfalfa, dry oat, and wheat straw samples and laboratory analysis results wereused to develop estimation models according to the partial least square regression (PLSR) method. A variableimportance projection (VIP) method was used as the wavelength selection method. Estimation models, whichwere developed according to study results, were obtained from the VIP-PLS model combination (RMSE=12.7,Bias=0.000, R2=0.804, RPD=2.28) for RFV. VIP method has increased the estimation of success for allvariables. Based on the study results, it was recognized that it is possible to use NIR in the calculations used inroughages quality evaluation parameters.