rice for comunity

Download Rice for comunity

Post on 02-Aug-2015

117 views

Category:

Documents

0 download

Embed Size (px)

TRANSCRIPT

1. Beating the heat for rice Integrated pipeline to generate varieties adapted to climate variability at a faster rate M.C Rebolledo E. Petro A.Pena C.Erazo D.Jimenez S.Delerce E.Torres 2. Climate variability explains ~32% of rice yield variability globally. 25% to 38% in Latin America (precipitation and temperature variability). Rice production is highly sensitive to climate conditions event under current climate scenarios Ray et al, 2015 Climate variability and rice production 3. Our strategy: 1.Environment characterization through the eyes of the crop 2.Trait dissection for specific environments 3.Unlocking the gene bank to increase the adaptation for specific environments We need to provide breeders with the phenomics, genomics and environmental information, as well as target ideotypes, to generate better adapted varieties at a faster rate. 4. Boxplots of conditional permutation based VI scores using CIF on cultivar F733 subset (Jimenez and Delerce) 1.Environment characterization through the eyes of the crop: Big data analysis of commercial data Saldana :Yields limited by low radiation accumulated during the maturity stage Saldana: yields limited by high night temperature during the reproductive stage (Tmin >23C) 5. 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 DIC.05.2013 OCT.07.2014 JUL.15.2014 FEB.05.2014 JUL.24.2014 ABR.29.2013 Yields (kg/ha) Saldana Tolima CT21375 FED2000 FED733 Saldaa Yopal Villavicencio Aipe Montera 1.Environment characterization through the eyes of the crop: Multi-environmental trials -Same management, same soil, just different sowing dates and a decrease of almost 50% on grain yields 6. y = 1713.6x2 - 81520x + 975215 R = 0.5883 y = -2148x2 + 97893x - 1E+06 R = 0.6216 y = 256.18x2 - 14308x + 200986 R = 0.7321 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 22.5 23 23.5 24 Average Min Temperature ( C ) yield vs. Average Tmin Reproductive stage CT21375 FED2000 FED733 An increase (1 C) in night temperature during reproductive stage will result in major crop losses 1. Environment characterization through the eyes of the crop: Validation of the main crop limiting factors y = 6E-05x2 - 1.2994x + 12399 R = 0.8526 y = -5E-05x2 + 2.066x - 13787 R = 0.5803 y = 5E-05x2 - 0.9946x + 9760.8 R = 0.8095 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 12000 14000 16000 18000 20000 Radiation accumulated at ripening stage Cal/cm2/day yield vs. accumulated radiation maturity CT21375 FED2000 FED733 A decrease in solar radiation during maturity stage will result in major crop losses Peng S et al. PNAS 2004;101:9971-9975 High night temperatures AND low radiation occur together in the field causing grain yield losses even under current climates 7. -High night temperatures will increase respiration rates -Low radiation will decrease the photosynthetic rate NightDay Photosynthesis Respiration Co2 Co2 Role of non structural carbohydrate Reserves ? STARCH Co2 Loss Co2 Assimilation Vegetative Reproductive Maturity Rate of STARCH decrease? Contribution to yield under high night temperature and low radiation? 2.Trait dissection to increase the adaptation of rice varieties to specific climatic conditions Negative balance for CO2 in the plant 8. 0 20 40 60 80 100 120 140 160 180 200 1 11 21 31 41 51 61 71 81 91 101 111 121 131 141 151 161 171 181 191 201 211 221 231 241 251 261 271 starch contribution to grains (mg/gDM) Traits, genes and promising parental lines that will confer higher yield under high night temperatures and low light in Saldana Tolima High throughput phenotypic tools for breeding Unlocking the gene bankPromising parental lines for breeding 3.Unlocking the gene bank to increase the adaptation of rice varieties to specific climatic conditions New genes conferring tolerance to low light and high night temperatures for breeding 9. Site characterization through the eyes of the crop -Climate -Soils -cropping system -management -End use of the crop Traits of interest/ promising parental lines - Trait dissection - Genetic resources Genes - Genotyping and phenotyping tools - Local genetic background DATA DATA DATA DATA DATA DATA DATA DATA DATA DATA DATA DATA DATA DATA DATA Varieties adapted to climate change New plant types for climate variability Empirical and Mechanistic modelling + Future spatial and temporal climate (CCAFS) Breeding 1.Environment characterization 2.Trait Dissection 3.Unlocking the gene bank Breeding GRISP II ?