The SpectralPhenoClimatron is a high throughput system that enables visual growth phenotyping of up to 320 plants per chamber in 7 climate chambers with multi-spectral LED lighting and dynamic environmental conditions. SolarCalc software controls light intensity and color, temperature and humidity at 1-minute intervals. This allows the creation of dynamic growth conditions with diurnal and seasonal cycles from any location. Images are taken at 5-20 min. intervals and processed into quantitative measures of plant color, size, and growth rate. Quantified developmental phenotypes are tested for genetic association through our GWAS pipeline to yield the genetic loci by which plants sense the environment to control growth.
To generalize and integrate next generation genomics with high throughput phenomics, the High Resolution Plant Phenomics Centre are developing an open-source software pipeline called ‘TraitCapture’. TraitCapture is a “seeds to traits” pipeline which allows users to track seed/genotype selection, set growth conditions, and analyze phenotypic variation for heritable components through to mapping causative loci via GWAS and QTL analysis. Web-based visualization tools will 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 a user to tune the environments, phenotyping protocols and image analysis to improve QTL detection. When QTL are identified, a user can resort plants based on alternative genotype classes to look for pleiotropic effects on growth, development, and physiology. Finally, published results should include links to the datasets and analysis protocols expanding on projects like the Phenomics Ontology Driven Data repository. This will allow new and previously cryptic traits to be identified. Importantly, standardized seed sets, growth protocols, phenotyping and analysis tools, will allow replication of experiments between different labs.
A brief list of experiments enabled by TraitCapture includes:
- 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.
Some system details:
- We control the Conviron chambers externally via external ethernet connection to our PC so we don’t have to go use the Conviron control software. This lets us dynamically set Temperature and Humidity.
- Growth chamber and lights are controlled by a Windows PC running a Python script.
- The Python script is called by a BAT file that is placed in the startup folder so it runs when the computer starts or is restarted.
- The BAT file calls the Python script and passes the script the name of the CSV file containing the 1-minute interval settings for the chamber and lights.
- Each chamber has four 600w Ethernet controlled LED lights made by Heliospectra (L4A S10 or 10 band L4A S20).
- Each set of 4 lights is slaved to the first light in the chamber so we update that light and it controls the rest.
- All lights and chambers have fixed IPs
- Cameras are Canon D750′s controlled by a PCLix intervelometer and running on external power adapters
- Images are wireless uploaded via a standard wifi connection to our server using EyeFi cards in each camera.
- Details on how to get this working with the eyefi card “endless memory” function so the cards don’t get full are here.
- We are working towards fully automating the timelapse but some manual steps are still required before the images can be viewed online. Until then check out the Live Cameras page.
Code (with some commenting) for externally controlling the Conviron growth chambers over Ethernet is here:
A complete bat + ini +csv set is here (1 month of data):
Environmental and light data is generated using SolarCalc.
For more project details and images see our recent poster on the project for the 2013 Ecological & Evolutionary Genomics Gordon Research Conference (click image to view poster).