Post on 26-Aug-2020
Unidad Integrada Balcarce (University of Mar del Plata-INTA), CONICET
ARGENTINA
Lowering the cost of medium- and high-throughput automated phenotyping:
a need for satisfying the projected demand for food, feed and biofuels
Luis A. N. Aguirrezábal & Gustavo Pereyra Irujo
World population for 2050 ≈ nine billion people Increase in demand for cereals ≈ 59% (respect to 2006 values) Meeting these demands = increasing global harvests ≈ 1.20% y−1 For most of cereals current rates of yield progress are consistently lower (Hall & Richards, 2013)
Increasing grain crops production to meet the projected demand for food, feed and biofuels
A higher efficiency of genetic improvement of cultivated plants is required
To fill the current gap between genotype and phenotype.
Increasing grain crops production to meet the projected demand for food, feed and biofuels
Advances in genotyping technologies have lowered the cost-per-genotype …
Advances in genotyping technologies have lowered the cost-per-genotype …
… to levels that have enabled an explosion of genetic studies in many fields
Phenotyping has become a bottleneck for understanding the genetic basis of complex traits (e.g. water deficit tolerance).
Lowering the cost of medium- and high-throughput automated phenotyping is needed
Phenotyping technologies still have high initial costs
$ $ $ $
$
Phenotyping technologies still have high initial costs
Lowering these costs will allow the expansion of research around the world
$ $ $ $
$
$ $ $
Phenotyping technologies still have high initial costs
Lowering these costs will allow the expansion of research around the world
$ $ $ $
$
$ $ $
Most phenotyping platforms have a cost which is prohibitive for many research institutes or breeding companies (most of them currently placed in ‘National Phenotyping Centers’…).
Lowering the cost of medium- and high-throughput automated phenotyping is needed
Most phenotyping platforms have a cost which is prohibitive for many research institutes or breeding companies (most of them currently placed in ‘National Phenotyping Centers’…). Lowering the cost of medium- and high-throughput automated phenotyping could make phenotyping platforms available for low-budget research groups or seed companies, as well as for use in the developing world
Lowering the cost of medium- and high-throughput automated phenotyping is needed
Most phenotyping platforms have a cost which is prohibitive for many research institutes or breeding companies (most of them currently placed in ‘National Phenotyping Centers’…). Lowering the cost of medium- and high-throughput automated phenotyping could make phenotyping platforms available for low-budget research groups or seed companies, as well as for use in the developing world This would allow the platforms to be installed close to where they are needed, and be used for phenotyping crops of local importance. More resources of the national phenotyping centers could be devoted to developing new and improved methods
Lowering the cost of medium- and high-throughput automated phenotyping is needed
To propose some possible avenues for lowering the cost of automated medium- and high-throughput phenotyping
Aim of this talk
I- Examining common characteristics in successful stories where platforms were used for detecting genotypes with higher performance in the field
Common characteristics in successful stories ?
Harris, Sadras & Tester (2010) -They used an ecophyisiogical water-centred framework yield =transpiration × transpiration efficiency × harvest index to investigate the effect of soil salinity on growth and yield of wheat and barley.
Successful story I
- Simple measurements (leaf appearance, shoot dry matter estimated using a LemnaTec Scanalyzer 3D, plant transpiration measured gravimetrically)
- Consistent with their hypothesis, salinity reduced transpiration (30–
60%) proportionally more than transpiration efficiency (0–35%); transpiration accounted for 90% of the variation in shoot growth across varieties and treatments.
Successful story I
Chapuis et al (2011)
-The ability of 18 maize lines to maintain leaf growth (measured by the platform Phenodyn) under water deficit predicted their ability to maintain grain setting under drought conditions (estimated by tensiometers) during a critical period (the maize lines were sown in the field in different countries).
Succesful story II
Argentina (Public institution)
Brasil (Public institution)
Paraguay (Public institution)
Uruguay (Public institution)
BiotecSUR-Soja Scientific Network a big experimental field
Private companies) (INDEAR - NIDERA)
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*
*
Successful story III
- Applying a water deficit of similar intensity (moderate) during the vegetative period of different genotypes (GlyPh phenotyping platform, GH, pots, biomass and leaf area pl-1, automated imaging).
Identifying contrasting soybean genotypes as parent of mapping populations
- Applying a water deficit of similar intensity (moderate) during the vegetative period of different genotypes (GlyPh phenotyping platform, GH, pots, biomass and leaf area pl-1, automated imaging).
- Applying a water deficit of similar intensity at different moment of the plant cycle to determine a critical period for yield (=R5 to R6, GH, pots, yield pl-1)
Identifying contrasting soybean genotypes as parent of mapping populations
- Applying a water deficit of similar intensity (moderate) during the vegetative period of different genotypes (GlyPh phenotyping platform, GH, pots, biomass and leaf area pl-1, automated imaging).
- Applying a water deficit of similar intensity at different moment of the plant cycle to determine a critical period for yield (=R5 to R6, GH, pots, yield pl-1) - Testing the tolerance of genotypes tested in GlyPh to a similar water deficit during such critical period (GH, pots, yield pl-1)
Identifying contrasting soybean genotypes as parent of mapping populations
- Applying a water deficit of similar intensity (moderate) during the vegetative period of different genotypes (GlyPh phenotyping platform, GH, pots, biomass and leaf area pl-1, automated imaging).
- Applying a water deficit of similar intensity at different moment of the plant cycle to determine a critical period for yield (=R5 to R6, GH, pots, yield pl-1) - Testing the tolerance of genotypes tested in GlyPh to a similar water deficit during such critical period (GH, pots, yield pl-1)
- Confirming the ranking of tolerance by using existing data from a field trial network (data filtered by rainfall during the determined critical period, field, yield ha-1 )
Identifying contrasting soybean genotypes as parent of mapping populations
DSI
GH, potted plants, Yield per plant
GH, potted plants, Yield per plant
Field trials network, Yield per ha.
Phenotyping platform (GlyPh), potted plants biomass per plant during vegetative period
Data from ≠ exp compared using a succeptibility index Similar rankings using biomass during vegetative period, yield per plant or per ha., growing plants in pots or in the field
0,4
0,8
1,2
1,6
0,4
0,8
1,2
1,6
0,4
0,8
1,2
1,6
MUN A8000 PIDT1 PIDT2 BR16 N7001 CONQ TJ0,4
0,5
0,6
0,7
Pardo et al, J. Agron. Crop Sci., submitted Peirone et al., unpublished
- simple traits that can be measured at a relatively low cost (e.g. growth, water consumption)
- the use of ecophysiological knowledge (e.g. considering a critical period for the studied trait)
were enough for detecting differences among genotypes
Common characteristics in successful stories
- simple traits that can be measured at a relatively low cost (e.g. growth, water consumption)
- the use of ecophysiological knowledge (e.g. considering a critical period for the studied trait)
were enough for detecting differences among genotypes Moreover, automation frees up time for other “by hand” complementary measurements (“low cost”) ‘Succesful story III’ was carried out using the low-cost platform GlyPh
Common characteristics in successful stories
Prototype 2.0 (2013) - agreement with ADOX SA
- More plants per unit surface - Focus on flexibility - User friendly software - Remote data access in real time
- Producible in series - More robust components - Modular structure - Easy transport
Presentation of the Prototype
Plant Phenomics Course Balcarce, August 2013
Field phenotyping based on an open-source, low-cost, unmanned aerial platform (UAV or drone)
Low-cost Field Phenotyping
Low-cost (~$1000) aerial platform
Open-source autopilot (w/GPS)
Open-source programming
software
Sensor integration
I- Examining common characteristics in successful stories where platforms were used for detecting genotypes with higher performance in the field II-The development of phenotyping platforms and methods are briefly reviewed and compared to the evolution of other technologies.
Phenotyping platforms vs. other technologies
The trend in plant phenotyping technology development has been mostly towards increasing the resolution and the number of variables measured, through sensors of increasing complexity. Few efforts have been made in order to develop low-cost phenotyping options
However... Simple traits measurable at a relatively low cost and the use of ecophysiological knowledge were enough for detecting differences in stress tolerance among genotypes
Current trends in Plant Phenotyping
"I think there is a world market for maybe five computers” (Thomas J. Watson, IBM, 1943)
“It is very possible that ... one machine would suffice to solve all the problems that are demanded of it from the whole country” (Sir Charles Darwin, grandson.., head of Britain's National Physical Laboratory, 1946)
“Originally one thought that if there were a half dozen large computers in this country, hidden away in research laboratories, this would take care of all requirements we had throughout the country” (Howard H. Aiken, Harvard University, 1952)
How many phenotyping platforms are needed in the world?
Linear vs. Exponencial technologies
Ford A (1930) Taurus (2011) Improvement (% year-1)Max speed (km h-1 65.0 210.0 1.5l km-1 8.5 11.3 -0.4Max HP 40.0 263.0 2.4Prize (k$) 0.5 28.0 -5.1
Comet 4 (1950) B787 (2011) Improvement (% year-1)Max speed (km h-1 846.0 954.0 0.2Range (km) 5190.0 15000 1.8Height (max) 12800.0 13100 0.0Prize (M$) 0.7 200 -9.7
Apple 3 (1977) MBP (2010) Improvement (% year-1)Processor 1.00 Mhz 2.66 Ghz 27.1Memory 4.0Kb 4.0Gb 52.2Storage 140.0 kb 500Gb 58.2Prize (M$) 0.7 2.2 -3.7
Exponencial technologies
$ / base # of genomes sequenced
Similar behaviour for computers (Moore´s law), cell phones, social networks standardized
Snyder et al (2010) Genes & Dev. 24: 423-431
Phenotyping technologies: How to grow exponentially and lower the cost
Currently: Every time a better sensor, a more complete platform Everyone solves their problem with a smart solution .... but different from the solution of others
Phenotyping technologies: How to exponentially grow and lower the cost
We propose: joining our efforts in order to develop products that can serve many people, which would allow lower costs -Devoting at least a small percentage of the budget and effort of each continental consortium for developing low-cost, standardized phenotyping technologies
- Use IPPN to establish collaborative projects
Phenotyping has become a bottleneck for genetic improving of many traits. To match the projected demand for food, feed and biofuels, the cost of automated medium- and high-troughput phenotyping technologies need to be lowered in order to expand their adoption around the world.
Final Remarks
Two main avenues seem interesting to approach this goal: -Analysis of ‘successful stories’ in order to detect basic, standardized sets of measurements useful for a wide range of phenotyping projects
-Joining international efforts for the development of low-cost technologies (perhaps “open” technologies, and not only greenhouse and growth chamber platforms but also field phenotyping technologies)
Final Remarks
Thanks for your attention!!!