phenoSMART® allows academic and commercial plant scientists to access advanced plant phenotyping analytics for extracting plant traits.
Building an Australia-wide collaborative plant phenotyping analytic capability
To transform phenotyping data into information, the APPF has developed a collaborative e-infrastructure platform called phenoSMART®. This platform allows the user to easily extract information and value from the data collected using phenotyping tools. The architecture of the platform also serves as a base to allow computational tools developed by other research groups across Australia to be made available to others and/or the agro-business sector.
Software to manage and analyse your data
Manage high-throughput phenotyping data collected in the field or in the lab and connect that data to our sophisticated data analytics capability. To learn more about phenoSMART®, contact APPF (Canberra CSIRO).
3D & RGB
We’ve supported research sites across Australia
The phenoSMART® logo is a trade mark of CSIRO registered in Australia and used with permission.
Capture, manage, secure, annotate, distribute and publish raw and analysed data from your phenotyping projects at APPF.
Phenomics Ontology Driven Data management (PODD)
The PODD system delivers an Open source (GNU Affero GPL, v3) and free data management service to capture, manage, secure, annotate, distribute and publish raw and analysed data from phenotyping projects run at the Australian Plant Phenomics Facility. PODD also provides the ability to manage a repository of associated contextual information (metadata) based on standard ontologies (controlled vocabulary) to support data discovery and analysis services. Benefits include:
- Repository for many different types of experimental data used in phenomics research, with associated contextual metadata
- Researcher can discover and access relevant phenomics datasets
- System can support arbitrary ontologies so can be used for other discipline areas
For more information contact APPF (Canberra, CSIRO).
A “seeds to traits” pipeline allowing users to track genotype selection, set growth conditions and analyse phenotypic variation.
TraitCapture is a “seeds to traits” pipeline which allows users to track seed/genotype selection, set growth conditions, and analyse phenotypic variation for heritable components through to mapping causative loci via GWAS and QTL analysis. Web-based visualisation tools allow real-time graphing of environment data with associated plant growth in time-lapse. Cloud-enabled GWAS on plant growth variation can be performed during an experiment allowing for real time capturing of heritable traits and trait loci across environments. This feedback allows users to tune the environments, phenotyping protocols and image analysis to improve QTL detection. When QTL are identified, a user can re-sort plants based on alternative genotype classes to look for pleiotropic effects on growth, development, and physiology. Experiments enabled by TraitCapture include:
- Iterative QTL identification and tests of pleiotropy.
- Heritability of potential spectral indices using hyperspectral cameras.
- Spatial and temporal distribution of fluorescent pigments under environmental stress.
- Light and temperature interactions on transpiration using Infrared (IR) cameras.
- Genetic basis of photosynthetic activity and efficiency using chlorophyll fluorescence cameras.
- Integration of 2.5D and 3D quantification of plant growth with stereo imaging.
For more information contact APPF (Canberra, ANU).
Access your images and analyse your data in real time on a daily basis using Zegami.
Researchers undertaking experiments at the APPF’s Adelaide node are able to access their images and analyse their data in real time on a daily basis using Zegami. Zegami is a web application which allows users to filter, sort and chart data from experiments and group that data with the corresponding images.
With daily access to the incoming preliminary data, researchers can enjoy greater control over their experiments, introduce early intervention and modifications to experimental protocol if required, run a preliminary analysis before having view of the full experiment and even monitor progress when not onsite.
Zegami is designed to help us share our data with all researchers. We use Zegami to link the experimental metadata, such as genotypes and treatments, with the image data. We then interface directly with our results database, process the data and make it available to the user via a private login on the web.
Watch the video here to learn more and view a tutorial. For more information contact APPF (Adelaide).
Data sharing and R packages
We are passionate about plant science and promote the open sharing of data to accelerate research.
Open data sharing
APPF policy promotes open data sharing. All APPF data is published online for reuse and developed algorithms are shared in open source environments.
Linking of phenomics information with the APPF’s modelling capabilities, TERN data, Bureau of Meteorology’s climatic data and Geoscience Australia’s DataCube will provide forecasting products on the Cloud for predicting agricultural productivity and the impact of various scenarios.
Our statistical workhorse is ASReml-R, the R-language implementation of the ASReml statistical software package (proprietary). R users can access it as the asreml package, but will require a software licence.
The Australian Plant Phenomics Facility supplements asreml with three R packages written by Dr Chris Brien (APPF Adelaide node):
- asremlPlus – extra functionality for asreml
- dae – software for designing and analysing experiments
- imageData – software for analysing data produced by the Lemna-Tec system
These 3 packages can be downloaded freely from CRAN or from Chris’s website.