Search Results (5)

Miscanthus is one of the most promising perennial crops for bioenergy production, with high yield potential and a low environmental footprint. The increasing interest in this crop requires accelerated selection and the development of new screening techniques. New analytical methods that are more accurate and less labor-intensive are needed to better characterize the effects of genetics and the environment on key traits under field conditions. We used persistent multispectral and photogrammetric UAV time-series imagery collected 10 times over the season, together with ground-truth data for thousands of Miscanthus genotypes, to determine the flowering time, culm length, and biomass yield traits. We compared the performance of convolutional neural network (CNN) architectures that used image data from single dates (2D-spatial) versus the integration of multiple dates by 3D-spatiotemporal architectures. The ability of UAV-based remote sensing to rapidly and non-destructively assess large-scale genetic variation in flowering time, height, and biomass production was improved through the use of 3D-spatiotemporal CNN architectures versus 2D-spatial CNN architectures. The performance gains of the best 3D-spatiotemporal analyses compared to the best 2D-spatial architectures manifested in up to 23% improvements in R², 17% reductions in RMSE, and 20% reductions in MAE. The integration of photogrammetric and spectral features with 3D architectures was crucial to the improved assessment of all traits. In conclusion, our findings demonstrate that the integration of high-spatiotemporal-resolution UAV imagery with 3D-CNNs enables more accurate monitoring of the dynamics of key phenological and yield-related crop traits. This is especially valuable in highly productive, perennial grass crops such as Miscanthus, where in-field phenotyping is especially challenging and traditionally limits the rate of crop improvement through breeding. Full article

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. Full article

Core collections can act as a genetic germplasm resource for biologists and breeders. Thirty-seven phenotypic traits from 471 Miscanthus accessions in China were used to design 203 sampling schemes to screen the genetic variations in different sampling strategies. The sampling was analyzed using the unweighted pair group method with arithmetic mean (UPGMA) and the Euclidean distance (Euclid). Several parameters including the variance of phenotypic value (VPV), Shannon–Weaver diversity index (H), coefficient of variation (CV), variance of phenotypic frequency (VPF), ratio of phenotype retained (RPR), the mean difference percentage (MD%) and the variance difference percentage of traits (VD%), the range coincidence rate (CR%) and the variable rate of quantitative traits (VR%) were used to evaluate the level of representation of the primary core collections developed by the different sampling schemes. Based on the optimal sampling strategies of prior selecting accessions, a primary core collection was constructed that maintained > 99.5% of the VPV and a CR% of 100%. This study indicates that the optimal sampling scheme consisted of prior and deviation sampling methods (PD) combined with a logarithmic proportional sampling strategy (LG) of 37.4% of the actual sampling ratio. Sampling before clustering can improve several parameters including the H, CV, RPR, VPF, and CR%. Sampling strategies including the genetic diversity index (G), logarithmic proportional (LG) and the square root proportional strategy (SG) can improve the H, whilst the constant strategy (C) can improve the RPR and VPF when the sampling scale was >30%. Furthermore, the proportional strategy (P) can improve the VPV. Full article

Four-year field experiments were conducted to investigate phenotypic traits associated with the biomass yield of 173 Miscanthus sinensis accessions collected from Korea and neighboring East Asian countries. Nine phenological and agronomic traits associated with biomass yield were assessed to investigate their phenotypic diversity and relationships with biomass yield as well as the latitudes of the M. sinensis accessions collection sites. Correlation analyses among phenological and agronomic traits, biomass yield, and collection site revealed that heading date, vegetative growth duration, leaf area, and stem growth traits (stem height, stem diameter, and stem dry weight) were closely related to biomass yield. The latitude of collection site exhibited a significant negative correlation with heading date, and heading date showed a significant positive correlation with biomass yield, indicating the high biomass potential of the accessions originating from lower latitude due to longer vegetative growth. The best biomass yield was mainly observed in M. sinensis accessions from the southern parts of Korea, such as Jeolla and Jeju provinces, with over 20 Mg DM ha⁻¹. Agronomic traits measured in the second year after planting also showed a high correlation with biomass yield measured in the fourth year after planting. In particular, vegetative growth duration, leaf area, stem diameter, and stem dry weight measured in the second year were significantly related to the fourth-year biomass yield. Therefore, these findings suggest that agronomic traits measured in the second year can be used for screening M. sinensis genetic resources and breeding lines with high biomass yield potential. Full article

Miscanthus is a high yielding perennial grass capable of high biomass yields with low inputs. Traits associated with yield have been identified in miscanthus, but less is known about the traits associated with sustaining biomass production under drought stress. The commercial hybrid M. × giganteus and high yielding examples from the parental species M. sinensis and M. sacchariflorus were grown under well-watered and moderate drought conditions. Growth, morphology, physiology and phenotypic plasticity were analyzed. Functional data were parameterized and a matrix of traits examined for associations with yield, genotype and drought treatment. Phenotypic plasticity was determined, indexes were then calculated to determine the plasticity of trait responses. All genotypes assessed responded to moderate drought stress, and genotypic differences in yield decreased under drought. Genotypes with low tolerance exhibited greater plasticity than highly drought tolerant M. sinensis. In well-watered plants variance in yield was explained by a relatively simple empirical model including stem length and stem number, whereas under drought a more complex model was needed including the addition of leaf area and stomatal conductance data. This knowledge can help us to define ideotypes for drought tolerance and develop miscanthus varieties that sustain high yields across a range of environmental conditions. Full article