Prediction of the Methane Yield From Extensively Managed, Flower-Rich Fen Grassland Based on NIRS Data

Abstract

In many regions of Europe, biogas production is an integral part of farming to generate methane as a sustainable and versatile renewable energy carrier. Besides providing feedstock for ruminants and energy production, grasslands support multiple beneficial ecosystem services, namely diverse flora and habitats that serve as resources for pollinators. The cost-effective utilization of grassland biomass is mainly determined by the biomass quality, which is highly variable and dependent on the management intensities. Besides chemical analyses, biogas models are usually applied to predict the biogas yield of a specific biomass type and quality. However, available models do not apply to mixed grass stands as they primarily refer to individual grass species and/or are just based on single parameters such as lignin. In this work, we evaluated flower-rich extensive fen grassland for its biogas yield using a newly created model based on common chemical parameters. Therefore, flower-rich biomass from a cultivation experiment (n = 48) was analyzed for its biomass yield (average 9.43 ± 1.26 t_VS × ha⁻¹), chemical composition by wet chemical analysis and near-infrared spectroscopy (NIRS), specific methane yield (SMY) potential via batch tests, and methane hectare yield (1505.62 ± 282.86 m³_N × ha⁻¹). In the results obtained, we found flower-rich grassland biomass characterized by high fiber (30.1% ± 1.7%) and high protein content (11.3% ± 1.3%) with reliable determinability of chemical composition by NIRS. The most important predictors on SMY assessed by multiple linear regression were crude ash (XA), crude protein (XP), amylase neutral detergent fiber (aNDF_vs), acid detergent fiber (ADF_vs), and enzyme-resistant organic matter (EROM). We conclude that extensive flower-rich grassland biomass composed of diverse species and different growth and ripening stages provides a suitable feedstock for biogas production despite late harvest dates. NIRS proved capable of analyzing the biomass quality of flower-rich grassland and thus contributes to optimizing grassland management strategies and provision of demand-driven feedstock qualities.