Variation of nutritive value, measured by proximal hyperspectral sensing, of herbage offered to grazing dairy cows. Issue 4 (3rd September 2022) - Duranovich, Federico Nicolás; Shadbolt, Nicola Mary; Draganova, Ina; López-Villalobos, Nicolás; Yule, Ian James; Morris, Stephen Todd
ABSTRACT: This study describes variation of nutritive value (NV), measured by proximal hyperspectral sensing (PHS), of herbage offered to cows on a pasture-based dairy farm. Metabolisable energy (ME), crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF) and digestible organic matter digestibility (DOMD) were predicted from PHS of canopies during the 2016–17 and 2017–18 production seasons at Dairy 1, Massey University. Mixed linear models including production seasons and months within production seasons as fixed effects and paddocks as random effects were used to estimate least-squares means of herbage NV. Estimates of variance components were obtained with the same models but considering all factors as random effects. A simulation model, e-Cow, was used to explore the effects of herbage NV on dairy cow performance. The NV of herbage offered to cows dropped during summer compared to spring or autumn ( P  < 0.05). The contribution of the month within production season to NV variance (42.7%) was higher than production season (13.1%) or paddock (10.7%). Cow performance can be limited by ME and NDF, while CP is often found in excess of requirements. The use of canopy PHS for rapid herbage NV measurement can potentially be used to optimise grazing in pasture-based dairy farms.