Impacts of Sward Renewal Method with Perennial Ryegrass (Lolium perenne) on Dry Matter Yield, Tiller Density and Nitrate Leaching

The objective of this study was to evaluate alternative methods of grassland renewal (reseeding) with perennial ryegrass and quantify their effects on subsequent DM yield, tiller density and nitrate leaching. Two experiments were carried out;the first focused on quantifying the influence of Autumn reseeding (August cultivation), and the second, on Spring reseeding (May cultivation) on sward establishment and grass DM production. The study incorporated six treatments namely: direct drill (DD), disc plus power harrow (DPH), power harrow (PH), conventional-plough, till and sow (PLO), and the chemical application of diquat to suppress the existing sward followed by direct drilling (DIQ), represented a rejuvenation method as opposed to full renewal (Spring trial only). All treatments were compared against a control (old permanent pasture). Reseeded swards produced more seasonal (P < 0.05) and total (P < 0.01 Autumn only) DM yield than the control sward. All reseeding methods increased the perennial ryegrass tiller density of the sward compared to the old permanent pasture (P < 0.05 Autumn trial, P < 0.001 Spring trial). All sward renewal methods evaluated were equally as effective as the conventional method of grassland reseeding with the DIQ rejuvenation method intermediate as measured in terms of DM yield and PRG tiller density. The results of the study show no significant difference in the level of nitrate lost in leachate following reseeding regardless of method used or indeed any difference between reseeded swards and old permanent pasture.

A near infrared spectroscopy calibration for the prediction of fresh grass quality on Irish pastures

The aim of this study was to develop near infrared spectroscopy(NIRS)calibrations to predict quality parameters,dry matter(DM,g kg1)and crude protein(CP,g kg1 DM),in fresh un-dried grass.Knowledge of these parameters would enable more precise allocation of quality herbage to grazing livestock.Perennial ryegrass samples(n=1615)were collected over the 2017 and 2018 grazing seasons at Teagasc Moorepark to develop a NIRS calibration dataset.Additional samples were collected for an independent validation dataset(n=197)during the 2019 grazing season.Samples were scanned using a FOSS 6500 spectrometer at 2 nm intervals in the range of 1100~2500 nm and absorption was recorded as log 1/Reflectance.Reference wet chemistry analysis was carried out for both parameters and the resultant data were calibrated against spectral data by means of modified partial least squares regression.A range of mathematical spectral treatments were examined for each calibration,which were ranked in order of standard error of prediction(SEP)and ratio of percent deviation(RPD).Best performing calibrations achieved high predictive precision for DM(R2=0.86 SEP=9.46 g kg1,RPD=2.60)and moderate precision for CP(R2=0.84 SEP=20.38 g kg1 DM,RPD=2.37).These calibrations will aid the optimisation of grassland management and the development of precision agricultural technologies.