DST-Early Career Research Award- Derivation of algorithms for automated and accelerated phenotyping using high throughput phenotyping platform-Leasy scan, to understand and enhance environmental adaptations in sorghum
Leasy scan-high throughput phenotyping for canopy size and structure components: derivation of algorithms for
Sorghum plays an important role in ensuring food and fodder security for millions of rural families in the semi-arid tropics. Breeding for improved varieties for water-limited environments has been slow, especially in developing countries, mostly because of the highly unpredictable environments and lack of tools to capture, dissect and understand the complexity of interactions between crops and environments (G×E). One such complexity which is now front-line research is canopy developmental dynamics.
Canopy establishment in time and space are obvious determinants of temporal plant water usage and are very likely to indicate the efficiency of water-use during its life cycle. Canopy developmental dynamics can be described by canopy growth and canopy structure. These key canopy parameters are difficult to identify, describe and validate for use in the crop improvement program. Therefore, the proposed work involves in the advancement of existing technology for accelerated phenotyping of these canopy parameters. The main objectives are:
1.Assessment of phenotypic variations in components of canopy size (i.e. tillering, leaf appearance, and leaf longitudinal and lateral expansion) and canopy structure in sorghum diversity panel using high throughput-phenotyping platform “LeasyScan”
2.Development of algorithms to disentangle the components of canopy size and structure from the 3D-point clouds generated by LeasyScan, implementing automated 3D-point-clouds data processing
3.Explore the functional associations between canopy size components at the level of physiological relations and genetic linkages
This project will provide the algorithms to describe the canopy size and structural components from the 3D-point clouds generated by Hi-Throughput Phenotyping Platforms (HTPPs) for automation and acceleration of precision phenotyping of these key parameters. Improve the understanding of the role of leaf growth and expansion in plants adaptation and findings may reveal the interlinks between canopy developmental dynamics and crop water usage across target production environments of sorghum, and possible way to integrate into crop improvement programs
The project outputs will be implemented at the host institute (ICRISAT) to serve the broader national and international communities. The data, knowledge, and principles will be shared with the research communities through the existing platforms (e.g. dataverse.icrisat.org; gems.icrisat.org).
For us gems means GEMS, or G*E*M*S (genotype by environment by management by society) interactions, i.e. the fact that crop yields results from complex biophysical interactions while acceptance depends on farmer/consumer preferences. This complexity becomes an opportunity when it is cracked into components that can be analysed, understood, predicted, and then used to prioritise research investments to maximise return. This is what we do, and this is when GEMS become gems!
For us gems means GEMS, or G*E*M*S (genotype by environment by management by society) interactions, i.e. the fact that crop yields results from complex biophysical interactions while acceptance depends on farmer/consumer preferences. This complexity becomes an opportunity when it is cracked into components that can be analyzed, understood, predicted, and then used to prioritize research investments to maximise return. This is what we do, and this is when GEMS become gems!
A crop performs in different ways in different sites, years and agronomic managements. These are called genotype-by-environment-by management(G*E*M) interactions, and they are a main challenge for breeders and agronomists. There is one more layer of interaction, even more complex: the society (S). Farmers and consumers have different desires, needs, expectations, and a cultivar that fits one may not fit the other (G*E*M*S interactions). The puzzle is complex and challenging but if its components are understood, specific interventions can be undertaken.For instance, breeding for a particular genotype (G, with particular physiological characteristics), for a particular environment (E, with a particular kind of drought pattern that requires a specific adaptive trait), in a particular management practice (M, for instance a sowing density, or a N fertilizer treatment), and targeted to particular farmer/consumer (S, for instance a genotype that produces a lot of rich stover for cattle ranchers) is the need of the hour.