Publications by authors named "A Lorenz"
In this study, we present an unexplored approach for remote focus manipulation using 3D nanoprinted holograms integrated on the end face of multi-core single-mode fibers. This innovative method enables precise focus control within a monolithic metafiber device by allowing light coupled into any of the 37 cores to be precisely focused at predefined locations. Our approach demonstrates significant advances over conventional lenses and offers unique functionalities through computationally designed holograms.
View Article and Find Full Text PDFThis strategic plan summarizes the major accomplishments achieved in the last quinquennial by the soybean [Glycine max (L.) Merr.] genetics and genomics research community and outlines key priorities for the next 5 years (2024-2028).
View Article and Find Full Text PDFIn soybean (Glycine max ), limiting whole-plant transpiration rate (TR) response to increasing vapor pressure deficit (VPD) has been associated with the 'slow-wilting' phenotype and with water-conservation enabling higher yields under terminal drought. Despite the promise of this trait, it is still unknown whether it has a genetic basis in soybean, a challenge limiting the prospects of breeding climate-resilient varieties. Here, we present the results of a first attempt at a high-throughput phenotyping of TR and stomatal conductance response curves to increasing VPD conducted on a soybean mapping population consisting of 140 recombinant inbred lines (RIL).
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- Humans have significantly altered river networks, leading to changes in habitat quality, migration barriers, and pollution, which affect aquatic life and restoration efforts.
- This study focused on the genetic structure of two pollution-tolerant isopod species in the Emscher catchment in Germany, revealing a strong metapopulation structure with isolated populations and high genetic diversity.
- The findings indicate that while some migration barriers exist, other factors such as adaptation and species interactions also influence genetic structure, highlighting the need for detailed genetic analysis in environmental studies.
Article Synopsis
- Genomic prediction (GP) in durum wheat has shown mixed results, with multivariate (MV) analysis emerging as a promising approach to enhance prediction accuracy (PA) for certain traits.
- The study assessed PA of agronomic traits over two seasons and varying field conditions (high nitrogen/well-watered and low nitrogen/rainfed), applying univariate (UV) and multivariate models with different cross-validation schemes (MV-CV1 and MV-CV2).
- Results indicated that MV-CV2 significantly improved PA, with some traits experiencing increases of up to 56.72%, especially when modeling related traits together, highlighting the potential of multivariate approaches in genomic prediction.