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)

*

*

*

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!!!