Results 41 to 50 of about 2,457,508 (205)

Plant phenomics: history, present status and challenges [PDF]

, 2018
With the development of remote sensing, robotics, computer vision and artificial intelligence, plant phenomics research has been developing rapidly in recent years.
Tardieu, Francois, Doonan, John, Hall, Neil, Zhou, Ji, Jiang, Dong, Griffiths, Simon, Wang, Xiuyi, Pridmore, Tony, Reynolds, Daniel, Cheng, Tao, Zhu, Yan, Ding, Yanfeng   +11 more
core   +1 more source

Fast Phenomics in Vineyards: Development of GRover, the Grapevine Rover, and LiDAR for Assessing Grapevine Traits in the Field

Sensors, 2018
This paper introduces GRover (the grapevine rover), an adaptable mobile platform for the deployment and testing of proximal imaging sensors in vineyards for the non-destructive assessment of trunk and cordon volume and pruning weight.
Matthew H. Siebers, Everard J. Edwards, Jose A. Jimenez-Berni, Mark R. Thomas, Michael Salim, Rob R. Walker   +5 more
doaj   +1 more source

Critical Evaluation of the Cgrain Value™ as a Tool for Rapid Morphometric Phenotyping of Husked Oat (Avena sativa L.) Grains

Seeds
Mechanised non-contact, non-destructive imaging methodologies have revolutionised plant phenotyping, increasing throughput well beyond what was possible using traditional manual methods.
David Evershed, Eamon J. Durkan, Rachel Hasler, Fiona Corke, John H. Doonan, Catherine J. Howarth   +5 more
doaj   +1 more source

Genetic Ablation and Multi‐Omics Profiling Reveal CEP55 as a Key Driver of Tumorigenesis in Diverse Cancer Models

Advanced Science, EarlyView.
Genetic ablation of Cep55 in Pten‐deficient mouse models delays tumorigenesis. Integrated multi‐omics analyses (proteomics, phosphoproteomics, and spatial transcriptomics) reveal that CEP55 regulates oncogenic signaling (RAS/ERK, PI3K/AKT), integrin/FAK‐mediated adhesion, extracellular matrix (ECM) remodeling, and endocytosis.
Behnam Rashidieh, Yuanhao Yang, Amanda Louise Bain, Phillip Theron, Catharina Vosloo, Sahar Keshvari, Parinaz Ahangar, Brydie Bowden, Simon M. Tria, Ben B. Wang, Sandra Isenmann, Nicholas J. Westra van Holthe, Zherui Xiong, Hani Vu, Sowmya Sharma, Asmerom Sengal, J. Alejandro Lopez, John Finnie, Antonella Papa, Pascal H.G. Duijf, Quan Nguyen, Pirjo M. Apaja, Kum Kum Khanna   +22 more
wiley   +1 more source

Photothermal Integration of Multi-Spectral Imaging Data via UAS Improves Prediction of Target Traits in Oat Breeding Trials

Agronomy
The modelling and prediction of important agronomic traits using remotely sensed data is an evolving science and an attractive concept for plant breeders, as manual crop phenotyping is both expensive and time consuming. Major limiting factors in creating
David Evershed, Jason Brook, Sandy Cowan, Irene Griffiths, Sara Tudor, Marc Loosley, John H. Doonan, Catherine J. Howarth   +7 more
doaj   +1 more source

Molecular Bases and Genetic Design of Rice Disease Resistance for Optimized Yield and Sustainable Agriculture

Advanced Science, EarlyView.
This study integrates rice immune perception, signal transduction, and resistance output into a multi‐omics framework. By combining high‐throughput sequencing, phenomics, and AI‐assisted design with marker‐assisted selection, gene editing, and rapid domestication, we aim to accelerate the precise breeding of disease‐resistant rice varieties by ...
Xinyue Hou, Yuanjiang Cui, Chaoqing Ding, Qian Qian, Deyong Ren   +4 more
wiley   +1 more source

AI Powered Biobanks From Static Archives to Dynamic Discovery Engines

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) provide a potential framework for transforming biobanks from static data repositories into intelligent discovery engines. By enabling unified representation and analysis of multimodal biomedical data, LLM‐based systems facilitate dynamic risk prediction, biomarker identification, and mechanistic interpretation, thereby ...
Wenzhen Yin, Yutian Feng, Wenrui Ma, Yuxin Su, Li Min, Juan Liu   +5 more
wiley   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

Proximal hyperspectral sensing and data analysis approaches for field-based plant phenomics [PDF]

, 2015
Field-based plant phenomics requires robust crop sensing platforms and data analysis tools to successfully identify cultivars that exhibit phenotypes with high agronomic and economic importance.
Andrade-Sanchez, P., White, J. W., Welch, S. M., French, A. N., Thorp, K. R., Gore, M. A., Carmo-Silva, A. E.   +6 more
core   +1 more source

Functional phenotyping: Understanding the dynamic response of plants to drought stress

Current Plant Biology
Drought stress, exacerbated by climate change, presents a critical global challenge characterized by increasingly severe and prolonged dehydration events.
Sheikh Mansoor, Yong Suk Chung
doaj   +1 more source