The cultivation of perennial energy crops (PECs) couples the production of ligno‐cellulosic biomass to the provision of multiple ecosystem services, such as the reduction of greenhouse gas emissions and the mitigation of climate change through carbon (C) sequestration in soil. Though C sequestration in soil by PECs has been widely studied, the contribution of their belowground biomass (BGB) to soil C sequestration and their influence on soil nitrogen (N) storage potential has received very little attention. In this study, C and N stocks in soil and BGB fractions (plant belowground organs and fine roots) were measured for six PECs (Populus spp. ‘Poplar’, Robinia pseudoacacia ‘Black locust’, Salix spp. ‘Willow’, Arundo donax ‘Giant reed’, Miscanthus × giganteus ‘Miscanthus’ and Panicum virgatum ‘Switchgrass’) grown on marginal soil, 11 years after establishment. All PECs had a higher soil organic carbon (SOC) stock and soil total nitrogen (STN) stock than arable land in the top (0–10 cm) soil layer. In this same top layer, woody crops had the highest SOC stock. The increase in SOC under PECs led to increased soil porosity in the top‐soil layer. On average, 43% of the belowground C stock of PECs was allocated in the plant belowground organs (PBO; i.e. in the rhizomes of herbaceous PECs and the stump for woody PECs). Giant reed had the highest C stock in PBO, whereas switchgrass the lowest (22.7 vs. 5.9 Mg C ha⁻¹). On the contrary, switchgrass had the highest C stock in fine roots. Giant reed had the highest belowground C stock (sum of soil and BGB contribution) and black locust the highest belowground N stock. After 11 years of PEC cultivation, 68% of the belowground C stock was allocated in the BGB, and 32% was as SOC.

Miscanthus, a C4 perennial rhizomatous grass from Asia is a leading candidate for the supply of sustainable biomass needed to grow the bioeconomy. European Miscanthus breeding programmes have recently produced a new range of seeded hybrids with the objective of increasing scalability to large acreages limited by current clonal propagation. For the EU‐GRACE project, new replicated field trials were established in seven locations across Europe in 2018 with eight intraspecific M. sinensis hybrids (sin × sin) and six M. sacchariflorus × M. sinensis (sac × sin) from Dutch and UK breeding programmes, respectively, with clonal Miscanthus × giganteus. The planting density of the sin × sin was double that of sac × sin (30,000 & 15,000 plants ha⁻¹), creating commercially relevant upscaling comparisons between systems. Over the first 3 years, the establishment depended on location and hybrid. The mature sin × sin hybrids formed tight tufts of shoots up to 2.5 m tall which flower and senesce earlier than the taller sac × sin hybrids. Following the third growing season, the highest yields were recorded in Northern Italy at a low altitude (average 13.7 (max 21) Mg DM ha⁻¹) and the lowest yielding was on the industrially damaged marginal land site in Northern France (average 7.0 (max 10) Mg DM ha⁻¹). Moisture contents at spring harvest were lowest in Croatia (21.7%) and highest in Wales, UK (41.6%). Overall, lower moisture contents at harvest, which are highly desirable for transport, storage and for most end‐use applications, were found in sin × sin hybrids than sac × sin (30% and 40%, respectively). Yield depended on climate interactions with the hybrid and their associated planting systems. The sin × sin hybrids appeared better adapted to northern Europe and sac × sin hybrids to southern Europe. Longer‐term yield observations over crop lifespans will be needed to explore the biological (yield persistence) and economic costs and benefits of the different hybrid systems.

Miscanthus holds a great potential in the frame of the bioeconomy, and yield prediction can help improve Miscanthus’ logistic supply chain. Breeding programs in several countries are attempting to produce high-yielding Miscanthus hybrids better adapted to different climates and end-uses. Multispectral images acquired from unmanned aerial vehicles (UAVs) in Italy and in the UK in 2021 and 2022 were used to investigate the feasibility of high-throughput phenotyping (HTP) of novel Miscanthus hybrids for yield prediction and crop traits estimation. An intercalibration procedure was performed using simulated data from the PROSAIL model to link vegetation indices (VIs) derived from two different multispectral sensors. The random forest algorithm estimated with good accuracy yield traits (light interception, plant height, green leaf biomass, and standing biomass) using 15 VIs time series, and predicted yield using peak descriptors derived from these VIs time series with root mean square error of 2.3 Mg DM ha⁻¹. The study demonstrates the potential of UAVs’ multispectral images in HTP applications and in yield prediction, providing important information needed to increase sustainable biomass production.

Miscanthus is a leading perennial biomass crop that can produce high yields on marginal lands. Moisture content is a highly relevant biomass quality trait with multiple impacts on efficiencies of harvest, transport, and storage. The dynamics of moisture content during senescence and overwinter ripening are determined by genotype × environment interactions. In this paper, unmanned aerial vehicle (UAV)‐based remote sensing was used for high‐throughput plant phenotyping (HTPP) of the moisture content dynamics during autumn and winter senescence of 14 contrasting hybrid types (progeny of M. sinensis x M. sinensis [M. sin x M. sin, eight types] and M. sinensis x M. sacchariflorus [M. sin x M. sac, six types]). The time series of moisture content was estimated using machine learning (ML) models and a range of vegetation indices (VIs) derived from UAV‐based remote sensing. The most important VIs for moisture content estimation were selected by the recursive feature elimination (RFE) algorithm and were BNDVI, GDVI, and PSRI. The ML model transferability was high only when the moisture content was above 30%. The best ML model accuracy was achieved by combining VIs and categorical variables (5.6% of RMSE). This model was used for phenotyping senescence dynamics and identifying the stay‐green (SG) trait of Miscanthus hybrids using the generalized additive model (GAM). Combining ML and GAM modeling, applied to time series of moisture content values estimated from VIs derived from multiple UAV flights, proved to be a powerful tool for HTPP.

Miscanthus, a C₄ perennial rhizomatous grass, is capable of growing in varied climates and soil types in Europe, including on marginal lands. It can produce high yields with low nutrient inputs when harvested after complete senescence. Senescence induction and rate depend on complex genetic, environmental, and management interactions. To explore these interactions, we analysed four miscanthus hybrids (two novel seed‐based hybrids, GRC 3 [Miscanthus sinensis × sinensis] and GRC 14 [M. sacchariflorus × sinensis]; GRC 15, a novel M. sacchariflorus × sinensis clone; and GRC 9, a standard Miscanthus × giganteus clone) in Italy, Croatia, Germany and the UK. Over all trial locations and hybrids, the average aboveground biomass of the 3‐year‐old stands in August 2020 was 15 t DM ha⁻¹ with nutrient contents of 7.6 mg N g⁻¹ and 14.6 mg K g⁻¹. As expected, delaying the harvest until spring reduced overall yield and nutrient contents (12 t DM ha⁻¹, 3.3 mg N g⁻¹, and 5.5 mg K g⁻¹). At lower latitudes, the late‐ripening M. sacchariflorus × sinensis GRC 14 and GRC 15 combined high yields with low nutrient contents. At the most elevated latitude location (UK), the early‐ripening M. sinensis × sinensis combined high biomass yields with low nutrient offtakes. The clonal Miscanthus × giganteus with intermediate flowering and senescence attained similar low nutrient contents by spring harvest at all four locations. Seasonal changes in yield and nutrient levels analysed in this study provide: (1) a first step towards recommending hybrids for specific locations and end uses in Europe; (2) crucial data for determination of harvest time and practical steps in the valorization of biomass; and (3) key sustainability data for life cycle assessments. Identification of trade‐offs resulting from genetic × environment × management interactions is critical for increasing sustainable biomass supply from miscanthus grown on marginal lands.