Browsing by Person "Kam, Jason"

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Site impacts nutrient translocation efficiency in intraspecies and interspecies miscanthus hybrids on marginal lands
(2022) Magenau, Elena; Clifton‐Brown, John; Awty‐Carroll, Danny; Ashman, Chris; Ferrarini, Andrea; Kontek, Mislav; Martani, Enrico; Roderick, Kevin; Amaducci, Stefano; Davey, Chris; Jurišić, Vanja; Kam, Jason; Trindade, Luisa M.; Lewandowski, Iris; Kiesel, Andreas
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.
Spring emergence and canopy development strategies in miscanthus hybrids in Mediterranean, continental and maritime European climates
(2023) Magenau, Elena; Clifton‐Brown, John; Parry, Catherine; Ashman, Chris; Awty‐Carroll, Danny; Ferrarini, Andrea; Kontek, Mislav; Martani, Enrico; Amaducci, Stefano; Davey, Chris; Dolstra, Oene; Jurišić, Vanja; Kam, Jason; Trindade, Luisa M.; Lewandowski, Iris; Kiesel, Andreas
Due to its versatility and storability, biomass is an important resource for renewable materials and energy. Miscanthus hybrids combine high yield potential, low input demand, tolerance of certain marginal land types and several ecosystem benefits. To date, miscanthus breeding has focussed on increasing yield potential by maximising radiation interception through: (1) selection for early emergence, (2) increasing the growth rate to reach canopy closure as fast as possible, and (3) delayed flowering and senescence. The objective of this study is to compare early season re‐growth in miscanthus hybrids cultivated across Europe. Determination of differences in early canopy development on end‐of‐year yield traits is required to provide information for breeding decisions to improve future crop performance. For this purpose, a trial was planted with four miscanthus hybrids (two novel seed‐based hybrids M. sinensis × sinensis [M sin × sin] and M. sacchariflorus × sinensis [M sac × sin], a novel rhizome‐based M sac × sin and a standard Miscanthus × giganteus [M × g] clone) in the UK, Germany, Croatia and Italy, and was monitored in the third and fourth growing season. We determined differences between the hybrids in base temperature, frost sensitivity and emergence strategy. M × g and M sac × sin mainly emerged from belowground plant organs, producing fewer but thicker shoots at the beginning of the growing season but these shoots were susceptible to air frosts (determined by recording 0°C 2 m above ground surface). By contrast, M sin × sin emerged 10 days earlier, avoiding damage by late spring frosts and producing a high number of thinner shoots from aboveground shoots. Therefore, we recommend cultivating M sac × sin at locations with low risk and M sin × sin at locations with higher risk of late spring frosts. Selecting miscanthus hybrids that produce shoots throughout the vegetation period is an effective strategy to limit the risk of late frost damage and avoid reduction in yield from a shortened growing season.
UAV remote sensing for high-throughput phenotyping and for yield prediction of Miscanthus by machine learning techniques
(2022) Impollonia, Giorgio; Croci, Michele; Ferrarini, Andrea; Brook, Jason; Martani, Enrico; Blandinières, Henri; Marcone, Andrea; Awty-Carroll, Danny; Ashman, Chris; Kam, Jason; Kiesel, Andreas; Trindade, Luisa M.; Boschetti, Mirco; Clifton-Brown, John; Amaducci, Stefano
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.