Precision agriculture for SAT; Near future or unrealistic effort? Jana Kholová and col. ICRISAT AuSoRGM- 22nd July - 2015

Overview Characterizing target environment Relevant phenotype for SAT Genetic determination of relevant phenotype HT-phenotyping Phenotype value System complexity & link to socio-economy

4. Relevant phenotype??? 1. Target environments 2. Environmental patterns 18% 17% 40% In phase I we characterized environment - in the main production region every 3-4 year the grain yield fails due to drought. We are trying to identify component traits which could bring yield advantage in the most frequent environment… 4. Relevant phenotype??? 18% 7% 3. Impact on production Kholová et al. 2013

(SAT – terminal drought)? Research concepts – relevant phenotyping Yield is consequence of GxExM Grain Yield Grain Number Grain Size & N  Biomass RADN TE T RUE Rint vpd kl LAI SLN Roots k  N LNo A >A Focus on the “causal phenotype” Yield is the result of many plant mechanisms – in each environment mechanisms (building blocks) contributing to yield advantage are different – therefore it is better to focus on components of yield rather than yield itself. Phenotyping causes, rather than consequences!!!! Which ”phenotype” is linked to yield improvement in target agro-ecology (SAT – terminal drought)? APSIM Generic Crop Template, from Graeme Hammer

Relevant phenotype for SAT? WU 3 weeks after stress imposition (L plant-1) Grain Yield (g plant-1) Grain yield and water use Grain Yield Grain Number Grain Size & N  Biomass RADN TE T RUE Rint vpd kl LAI SLN Roots k  N LNo A >A constitutive WU defines grain-filling under terminal drought Pre-/post-anthesis water use Pre-anthesis WU linked to post-anthesis WU; post-anthesis WU linked to grain yiled Vadez et al. 2012

Relevant phenotype for SAT? Grain Yield Grain Number Grain Size & N  Biomass RADN TE T RUE Rint vpd kl LAI SLN Roots k  N LNo A >A Relevant phenotype for SAT? Constitutive WU : Vapor Pressure Deficit (VPD; kPa) Transpiration rate (g cm-2 h-1) 2 4 1 LA conductivity LA Thermal time & LA WU in time is defined by LA and LA conductivity during the growth; there is substantial variability in populations Basic research on WU components Vadez et al. 2010-2015 Kholová et al. 2010-2014

Effect of QTL depends on genetic background Example: WU components – genetic determination Grain Yield Grain Number Grain Size & N  Biomass RADN TE T RUE Rint vpd kl LAI SLN Roots k  N LNo A >A Stay-green ILs R16 (senescent parent) + stg3A&3B QTL VPD response -> high TE S35 (senescent parent) + stg3A&3B QTL small leaves To investigate adaptive traits variability we use stay-green NILs descended from senescent parents (R16&S35). The lines descended from R16 showed variability in TE and LA development; lines related to S35 showed variability in water extraction capacity, LA dynamics – these are various entry-point (components) which can lead to improvement of crop production. However, stg-QTL effect is not universal, stg B appears to work across backgrounds (despite effect is different in both backgrounds) Effect of QTL depends on genetic background (stg 3A&B!) Vadez et al. 2011

“consequential phenotype” Phenotyping principle LeasyScan Lysimetry Field % of lines holding desired phenotype “consequential phenotype” (High precision field trials) Grain Yield Grain Number Grain Size & N  Biomass RADN TE T RUE Rint vpd kl LAI SLN Roots k  N LNo A >A No. of lines phenotyped “causal phenotype” (HT-phenotyping) Platforms linkage!

= $ ? + Value of phenotype? – in silico predictions Model Grain Environment Canopy size + = $ ? Model Grain Pre-flowering Flowering Post-flowering Post-flowering relieved No stress What is the value of the variability in building blocks for breeding programmes?? Traditional multilocation trials can be approximated in silico with modell

Example: System complexity Crop value = f(quantity + quality; socio-economic context) Stay-green sorghum; grain quality ~ 20% QTL effect Control Drought ~ 15% management effect Control ?Price per unit of protein? Link to socioeconomics

RESEARCH APPLICATION Conclusions; Structure of research Value of traits (crop model & GxExM) Genetic determination of phenotype Environmental characterization & relevant traits ideotypes & management to regions (precision Ag for SAT) Breeding populations Socio-economics Feedback!!! HT-phenotyping

Thank you R4D requires multidisciplinarity! Bioinformatists Technology developers Physiologists Breeders Modelers Socioeconomists Nutritionists…. Mission To reduce poverty, hunger, malnutrition and environmental degradation in the dryland tropics Thank you