Description: This session will focus on the variety of phenomics approaches and the insights that they have contributed to biology. It will address the benefits and limitations of phenomics techniques, pose big-picture questions, describe current research needs that are targets for development, and consider how our technology-enhanced ability to quantify phenotypes is shaping our theoretical understanding of plant growth and environment interactions.
Description: This session will explore the development and application of sensors and systems that advance the phenomics field. This includes the development of new phenotyping sensor systems, the adaptation of existing sensors into phenotyping systems, and the development of protocols for collecting reliable phenotypic data. The sensors and systems presented in this session may vary in measurement resolution (e.g. molecular vs. field scales), throughput, economics (e.g. the development of affordable systems), and mechanisms for automation (e.g. agricultural scale phenotyping robots). Presentations will include recommendations, lessons learned, and best practices to inform researchers and practitioners who wish to enter this field.
Description: This session will cover the development and application of analytical methods for extracting useful information from phenotypic data, as well as data management and curation practices. The session aims to include the development of algorithms for processing and understanding sensor data (e.g., image and signal [pre]processing and feature extraction methods); algorithm development for automatically interpreting phenotypic data and their multivariate/non-linear relationships to biological processes (e.g., novel statistical methods, advanced data mining); sensor and data fusion (e.g., merging and jointly analyzing multi-type collections, such as genotypes, soil and environmental data);and open challenges. The session will also explore methodologies for storing, managing, and sharing data sets, as well as metadata, data tagging, and ensuring interoperability. Presentations will include open source software, biological examples, case studies, recommendations, and best practice results; these will inform researchers and practitioners in phenomic data analytics and in the data→knowledge→biological understanding process.
Phenome Digital Phenotyping Workshop: The Phenome Digital Phenotyping Workshop will give participants hands-on experience processing data from state-of-the-art image-based phenotyping technologies with domain experts. Based on community feedback, topics covered will include: Image processing of 2D and 3D image data, hyperspectral image processing, and data visualization. There will be a maximum of 40 participants and if the number of registrants exceeds this maximum, preference will be given to ‘trainee’ level scientists (e.g. graduate students, postdoctoral researchers, and technicians). Workshop participants are expected to bring their own computers. We hope you will join us for this training opportunity!
Fee: $75 (includes lunch on February 14) limited to 40 participants
Phenome Hackathon: The 2018 Phenome hackathon will be an informal community event that occurs the day after the Phenome meeting (February 18th, 2018). Based on community feedback, this year’s hackathon will focus on two topics: Image processing on common datasets and data visualization. Participants can work independently or in interdisciplinary teams to solve bottlenecks in analyzing plant phenomics data. Curated data will be available ahead of the meeting.
Fee: No cost to participate but size is limited to 60 participants