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URL
1 Plant Phenomics and Plant Phenotyping Downloads by
LemnaTec
Please find all relevant documents of the last Phenodays 2011 for downloading here:
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There is a need to develop high-throughput plant phenomics to bridge the phenotype
–genotype gap that will lead to the improvements in crop performance necessary to feed a growing world population. The facility under development at
Aberystwyth will be based around automated, non-destructive image analysis using a scanalyzer 3D system developed by
LemnaTec running in a new glasshouse complex. A central advantage of this approach is that it is inherently nondestructive, allowing repeated measurements to be made on individual plants in a pre-programmed sequence over time with minimal human intervention. The system is flexible, designed to cope with small plants such as forage grasses, forage legumes,
“Brachypodium” and “Arabidopsis”, and also with larger plants such as oats, wheat, barley, maize and
“Miscanthus”. The plant phenomics facility will be closely linked to both chemical phenotyping and genotyping facilities in
Aberystwyth and integrated with field trials and public good plant breeding. Use of the facility will accelerate the selection of appropriate germplasm for breeding varieties, which will perform robustly under the conditions predicted for the UK and beyond in the future. Furthermore, it will provide a focus for trans-disciplinary research, to facilitate the discovery of the genetic and environmental bases for variation in complex traits that underpin the major global challenges for food and energy security, water utilization and adaptation to a changing climate.
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The Plant Accelerator
®
is a purpose-built plant phenotyping facility in Adelaide, Australia. With over 2,300 m 2 of floor space across 38 greenhouses, four of which are Smarthouses TM equipped with LemnaTec scanalyzer 3D systems capable of accommodating nearly 2,400 plants, it is one of the largest publicly accessible imagebased plant phenotyping facilities in the world. The Plant Accelerator
®
is a dedicated service facility, undertaking projects for plant scientists, whatever their research targets or geographical locations are. Nevertheless, we have particular expertise in cereal projects, especially in the areas of drought and salinity tolerance
– characteristics of particular importance in the Australian environment.
Both drought and salinity tolerance are complex multi-factorial phenotypes, subject to many Genotype x Environment interactions. The consequently low heritability of these traits results in difficulties validating quantitative trait loci across different trials, which restricts the ability of phenotyping research projects to assist in the breeding of new, more tolerant, varieties. The facilities at centres such as The Plant Accelerator
®
are now helping researchers to dissect these phenotypes into simpler and more robust traits, with the increased likelihood of identifying either causative genes or reliable genetic markers.
The Plant Accelerator
®
is now being used to study previously intractable physiological processes, and I will describe some of the outcomes of a variety of such projects on salinity and drought tolerance that have been carried out at the

Accelerator. I will also outline some of the
‘tricks of the trade’ that we have identified, which allow us to carry out these projects more successfully. Finally, I will discuss our work on the description of phenotypes that were conventionally only measurable using destructive testing, but we can now achieve accurate estimates of these phenotypes based on imaging data alone.
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Innovative technologies are required to meet the agricultural needs of a growing world population estimated to reach 9 billion by 2050.
Monsanto is committed to meeting these needs by improving the lives of farmers. Our goal is to use breeding, biotechnology and improved farming practices to develop crops that produce more yield while conserving natural resources. A key step in this process lies in identifying plants with traits that enable farmers to produce more yield with less water and fertilizer. To speed the identification of plants that have these traits valued by farmers, we have developed a high-throughput phenotyping facility that fuses automated plant handling and imaging technology. This facility allows us to quantify growth and whole plant physiology in precisely controlled environments. Here we present the opportunities and challenges inherent in high-throughput screening of biological systems, particularly as they apply to plant biotechnology.
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Plant phenotyping, which connects attributes of plant anatomy, physiology and performance with their genetic origins and xenobiotic influences, is crucial for plant breeding. Traditional human observation is marred by its subjective nature, drift over time, the differences between observers and its often qualitative output. Machine vision offers solutions to these problems and in addition benefits from a fully quantitative output, the abilities to look beyond human spectral perception, and measurement parameters that would prove more challenging to a human observer. Image analysis coupled with high-throughput, automated systems is revolutionising plant phenotyping, removing a previous bottleneck by enabling the rapid selection of favourable traits for plant breeders. This talk will focus on different plant structures, namely roots, aerial stems and leaves, fruits and seeds, and how the software and hardware surrounding machine vision can be used to measure their respective phenotypical parameters. A key to the success of image analysis for plant phenotyping within Syngenta has been to create a network of interdisciplinary colleagues bound together by a common interest in imaging technologies and processing.
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Due to the development of highly automated genetic analysis, plant genomics has immensely enlarged our understanding of the genetic structure of plants over the last two decades. The fast evolving need to identify interactions between genes and environmental factors (biotic and abiotic) that brings about a certain plant phenome made it necessary to develop quantitative, reproducible and highly automated plant phenotyping systems for large plant numbers. Phenotyping systems such as these have to integrate reproducible plant management (randomisation, watering) and comprehensive imaging of root and shoot far beyond human vision (visible light, fluorescence, near infrared, infrared, X-rays, THz) as well additional chemical analysis methods. Immediate and automated image analysis of the stored images and further data transformation using plant shape and plant growth models are the important intermediate steps, before undertaking statistical data analysis of the phenotyping results to characterise plant phenotypes quantitatively. Such quantitative data contributes in a decisive way to the further analysis of gene functions
(tilling, QTL etc.), especially under fluctuating or stress-induced environmental conditions, with a special focus on complex traits like yield or drought tolerance. This presentation will provide a survey on phenotyping technology and the close interaction between phenotyping technologies, modelling approaches and the new opportunities of fast and automated high-throughput genomics.
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During the last 50 years, plant breeding has resulted in gigantic improvements of crops in terms of yield, quality, resistances and appearance of our agricultural products. However, the traditional methods are now reaching their limits.
At the same time, society needs large improvements in crops to meet the current and future demands for high quality food, feed fibre, fuel, flowers and fun agricultural products.

In this presentation, paradigm shifts are elucidated that will lead to the desired improved and innovative crop varieties.
Firstly, large-scale genomics information is available and used for an increasing number of crops. Secondly, besides genetic modification alternative molecular genetic methods are under development that allow fast molecular breeding and molecular mutagenesis. Thirdly, new automated and robotic phenotyping methods are now being implemented, enabling the establishment of correlations in genetic variation with traits of socio-economic importance and thereby permitting a new and integrated way of molecular plant breeding. A number of practical examples will show that genomics in combination with new phenotyping approaches leads to fast and directed ways of genetic improvements in our crops for the future.
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3D
The LemnaTec scanalyzer 3D system in the IPK Gatersleben was established in 2008 and was one of the first LemnaTec platforms in the public domain. Since then it has been used for phenotyping drought tolerance of different barley cultivars. Plants are phenotyped in fully automated fashion with three different camera systems using I) visible, II) fluorescence, and III) near infrared light. Initially, several replications of a vegetative drought stress experiment were conducted, using parents of a DH-population Morex and Barke, to test the reproducibility of phenotypic values with the scanalyzer system and to gain experience. Since autumn 2010, the IPK has been involved in the CROP.SENSe.net project, and drought stress is applied to a core barley set of eight old and eight modern German spring barley cultivars.
The set shows a good phenotypic diversity in growth under control and drought stress conditions. In future, a larger set of a worldwide spring barley collection will be phenotyped for a genome-wide association study.
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The design modularity of the greenhouses and climatic chambers allocates various growth conditions for plants in order to mimic most of the environmental scenarios in the context of climate change. Climatic chambers are either equipped with conveyors in line with phenotyping cabins, used for large biological units and rhizotrons, or devoted to the “small biologic al units” (i.e. seeds, plantlets, microbiological petri dishes) phenotyped in a cabinet (called “HTS”), where mobile cameras screen the culture zone. This HTS and its climatic chambers allow to phenotype, in addition to our 1800 plants/1000 rhizotrons phenotyped in greenhouses, thousands of seeds and more than four hundred plantlets daily.
A High-Throughput Plant Phenotyping Platform (PPHD), located in Dijon (France), is in the final stages of construction. It will provide the opportunity to apply well-characterised biotic and abiotic constraints to several hundreds of genotypes
(thousands of plants) and to measure accurately a series of functional traits. Although it can also analyse plant architecture and plant-plant interactions (i.e. crops versus weeds competition for resource access and the consequences in terms of plant development), the PPHD is specifically devoted to plant-microorganism interactions. It allows establishing and testing causal relationships between genetic markers and phenotypes related to plant performance under a range of environmental conditions, including those forecasted by models of climate change.
PPHD is constituted of a large building with S2 modular greenhouses and climatic chambers. These are equipped with conveyor belts to homogenise plant growth conditions and automatically bring plant units to the phenotyping cabinets.
Six additional S2 greenhouses are used for growing plants (either in pots or rhizotrons), when they do not need to be phenotyped during their entire growth cycle. Phenotyping is based on image analysis (visible light, near infrared and fluorescence), which allows characterising non destructively and automatically i) a large variety of plant species and specifically designed high-throughput rhizotrons ii) seeds or microorganisms, plantlets.
The understanding of the genetic determinisms involved in plant-plant and plant-microorganism interactions and the progress in selective as well as variety innovation that will follow offer a unique opportunity, today still underexploited, to design sustainable agriculture with large ecosystemic services.
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DROPS (DROught-tolerant yielding PlantS; www.drops-project.eu
) is an EU-funded project that will develop novel methods and strategies for the improvement of crop performance under limited water conditions. An interdisciplinary approach based on high-throughput phenotyping under controlled and field conditions, it will generate data to be used for ecophysiological modelling, to predict the performance of maize and wheat under fluctuating water regimes. The identification of Quantitative Trait Loci (QTLs) for morpho-physiological traits that influence yield under drought conditions will produce additional data for modelling crop performance based on QTL-effects. The project will target root architecture, transpiration efficiency, vegetative growth maintenance and seed abortion. In particular, DROPS will:
- Develop new screens that will consider indicators which are (i) highly heritable and measurable in a high-throughput fashion on phenotyping platforms; (ii) based on metabolite concentration, sensitivity parameters of models or hormonal balance; (iii) genetically related to target traits and able to predict genotype performance in the field via simulation and/or

statistical models;
- Explore the natural variation of the target traits by (i) linking the target traits to physiological pathways, genes or genomic regions (ii) assessing the effects of a large allelic diversity for the four target traits via association genetics;
- Support crop improvement strategies by developing methods to estimate the comparative advantages of relevant alleles and traits in fields with contrasting drought scenarios. This will be achieved via field experiments and by developing new crop models that are able to estimate the effects of alleles on crop growth, yield and water-usage efficiency.
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Europe has many interests to favour investing in the development of phenotyping technology:
- Improve breeding techniques and efficiency with an increased understanding of genomics and its applicability
- Build infrastructure to provide the scientific community with the necessary tools for answering biological questions about : physiology, stress tolerance, yield components and productivity… that may help to solve future challenges regarding climate change as well as biotic and abiotic stresses, and thus help to protect European agriculture
- Enhance the link and collaboration between European breeding companies and research consortia through access to infrastructures and collaborations (direct applicability of results / work on European varieties ...)
- Boost the development of SMEs, developing phenotyping infrastructures and technologies, as well as fostering jobs and innovation in this field
- Finally, Europe has what is probably a unique chance to become the world leader in “Phenomics” technology as it already possesses many world-leading groups in plant phenotyping.
In the last few years, projects with strong phenotyping components have been funded under the European Commission
Framework Programme 7 ( http://cordis.europa.eu/fp7/home_en.html
). One example is the DROPS project ( www.dropsproject.eu
) under the cooperation programme, which aims to develop novel methods and strategies for genetic yield improvement under dry environmental conditions and for enhanced plant water usage efficiency. Another example would be the opening of a call under the “Infrastructure” capacities programme in 2010, funding the development of a
“European plant phenotyping network”..
The presentation will bring to memory Europe’s strategic interests in developing a strong phenotyping community and the different projects that have been funded under the FP7 programme of DG Research&Innovation.
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Drought stress is one of the major abiotic constraints that limit agricultural productivity in the semi-arid tropics, where climate change is likely to increase the severity of droughts even more in the future. To enhance the performance of crops facing terminal drought stress like cowpea, the traits related to how plants handle limited water resources are essential. In this work, the growth, transpiration rate [TR], canopy temperature [CT] and index of canopy conductance
[Ig] of cowpea lines contrasted for their response to drought in the field were tested under non-limited water conditions across different atmospheric vapor pressure deficits [VPD] to investigate whether tolerant and sensitive genotypes differ in their control of leaf water loss.
Overall, plants developed a larger leaf area under low than under high VPD conditions, and there was a consistent trend of lower growth in tolerant compared to sensitive lines. Substantial differences were recorded among genotypes for their
TR response to VPD with tolerant ones showing significantly lower TR than sensitive ones, especially at the time of the day with the highest VPD. Significant variations were also found among genotypes for their response of TR to increasing
VPD, with some tolerant genotypes exhibiting a clear VPD breakpoint at about 2.25 kPa, above which there was very little increase in leaf water loss. In contrast, the sensitive lines presented a linear increase in TR as VPD increased. CT estimated by thermal imagery correlated well with TR and Ig and could therefore be used as proxy for TR. These results indicate that the control of TR has discriminated between tolerant and sensitive genotypes and may therefore be used as a reliable indicator of terminal drought stress tolerance in cowpea.
The water-saving characteristics exhibited by some lines are hypothesised to make more soil water available at the pod filling stage, which is crucial for terminal drought situations.
Keywords: Canopy temperature, Climate change, Drought stress, Growth parameters, Thermal imagery, Transpiration rate, Vapor pressure deficit, Vigna unguiculata.
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Within the last decade,
“Populus spec. (L.)” has been developed into one of the main research objects of molecular genetics in woody plants. Among others, two reasons for their great attraction are that most poplar species are easy to propagate compared to other tree or shrub species, which allows a high-throughput cultivation of the plants. Secondly, the genome is comparatively small (
˃ 41,000 protein coding genes). Both are favourable characteristics for a plant or plant species to become a model organism.

Additionally, the production of fast growing trees for bioenergy purposes has become increasingly attractive for the economy due to the favourable volume-to-density relation of their wood. Because of this development, foresters and tree breeders have focused their search on genotypes of poplar and other fast-growing tree species like willow, which are suitable for cultivation in short rotation coppices. However, despite the above-mentioned positive aspects, the major problem concerning short rotation coppices of poplar is the low profit, caused by a high water demand to achieve satisfactory biomass production.
For the description of drought tolerance in aspen, we started to identify changes in the tree ring architecture. Our investigations are focused on tree ring width, fibre cell length, vessel cell length, mean annual
δ 13C as well as mean Xray density as part of a functional genomics approach.
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Plant roots are economically very relevant since the distribution pattern of the root system in the soil determines the zone of water and nutrient availability to plants, and differences in root and root development are related to crop yields and abilities to escape drought and soil-borne diseases.
The KeyTrack system allows for efficient execution of root research in a high-throughput manner and provides a robust phenotyping platform in a greenhouse setup. The phenotyping is based on imaging technology and uses the potential of a track that moves all plants fully automated through the greenhouse compartment and scanning areas. The plants grow in individual containers and are photographed at pre-set points in time and from different angles.
The research presented encompasses the creation of an automated root phenotyping protocol and image analysis pipeline. The material used for this research is the tomato LA716 S. pennellii introgression line library created by Prof.
Dani Zamir. The research described merges the phenotypic data generated with genotypic knowledge, to feed lead discovery and root development in tomato.
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Qualitative and quantitative improvements are required in crop breeding and production to respond to the global challenges of a rapidly rising population (which will lead to changes in demand), climate change and the need to optimise resources and maintain an increasing production rate. In order to capitalise on the vast knowledge gained through genomics (and other omics) research, scientists must alleviate the “phenotyping bottleneck” in plant sciences.
Improvements can only be made by interdisciplinary research and knowledge links that integrate the advances already made in sensor, imaging and computing technologies to accelerate breeding methods, to reduce experimental resource requirements and to enable the collection and analyses of multiple, simultaneously created and objective data resources.
CROP.SENSe.net brings together researchers from plant science, soil science, geodesy, IT, maths and physics with partners from breeding and the industry, to develop and apply phenotyping science for plant and soil analysis in the lab and field, to enable non-destructive and quantitative analyses and plant phenotype screening throughout the plants ’ life cycle. The ultimate aim of this interdisciplinary approach is an early, non-biased and faster assessment of traits, to allow greater efficiency in crop breeding and to optimise decision making in crop management.
CROP.SENSe.net research uses a wide array of sensor technologies over almost the entire range of electromagnetic radiation: stereo imaging, visible and multispectral analysis, infrared, wideband radar, terahertz and magnetic resonance spectroscopy. A range of external (morphology and growth dynamics) and internal (physiological) architectural and stress-related characteristics of individual plants and populations are measured over the growing season, for the proxy plants barley and sugar beet. An important element is to make
“hidden” structures and functions visible. Intelligent data evaluation will enable the analysis of information on plant phenotypes over space and time for the same plants. Data fusion – merging data (signals) from different sensors – is ongoing to identify plant traits early and to link them with reference analyses of biochemical and physiological stress indicators, and ultimately back to genotype.