Prediction of forage chemical composition by NIR spectroscopy

Near-infrared spectroscopy (NIR spectroscopy) has been used in analytics for more than 50 years. The aim of this review is to present statistical indicators of the developed calibration models for predicting forage chemical composition by NIR spectroscopy, which have been published over the last 15 years. This paper presents statistics for predicting of forage dry matter (DM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), ash, and pH value of forage at different pre-scan processing level (fresh, dried / ground forage) and different forage types such as grass monocultures, legumes, grass-clover mixtures (GCM), semi-natural pasture, straw, maize, hay, silage and haylage. Due to wider applicability of NIR calibration model for prediction of chemical composition of forage, the development of calibration includes forage originating from various agricultural production technologies, cultivation climates, varieties and vegetation seasons, etc. In order to develop more reliable calibration models for prediction of forage chemical composition, calibrations are developed for individual plant species, cultivars, harvest during the vegetation season, as well as for individual microclimates of cultivation. NIR spectroscopy has high potential for predicting the content of DM, CP, NDF, ADF, ash and pH value in forage.