1 / 21

Breeding for nutritional quality in rice for Latin America

Breeding for nutritional quality in rice for Latin America. Cécile Grenier and Jaime Borrero. César Martinez, Roger Taboada, Jose Luis Viana, Péricles Neves, Lázaro Narvaez, Violeta Puldon, Angel Adames, Alejandro Vargas and Ismael Camargo. Goal and Objective.

zuri
Download Presentation

Breeding for nutritional quality in rice for Latin America

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Breeding for nutritional quality in rice for Latin America Cécile Grenier and Jaime Borrero César Martinez, Roger Taboada, Jose Luis Viana, Péricles Neves, Lázaro Narvaez, Violeta Puldon, Angel Adames, Alejandro Vargas and Ismael Camargo

  2. Goal and Objective • Improve the nutritional status of the poor in rural and urban regions of Latin America and Caribbean • Develop rice lines with high iron and zinc content and excellent agronomic characteristics N. Palmer, CIAT

  3. Participating countries Roger Taboada Lázaro Narvaez Violeta Puldon Ismael Camargo Panama Alejandro Vargas Angel Adames Rep Dominicana Pericles Neves Jose Luis Viana Bernardo Ospina Cesar Martinez

  4. Biofortified rice – CIAT targets Nutritional Agronomy • High yield • Pest and disease resistance • Good processing & cooking quality Iron Zinc 6-8 ppm 22-25 ppm 2-3 ppm 17-18 ppm N. Palmer, CIAT

  5. Achievements • Establishment of efficient screening protocols and methodologies • Definition of a base line for Fe and Zn in LAC • Screening and field evaluation of local varieties and advanced breeding lines for Fe and Zn content • Development of populations and lines for high level of Fe and Zn • Development of a data base for Fe and Zn in rice N. Palmer, CIAT N. Palmer, CIAT

  6. Methodology Post harvest processing Sampling Flour processing AAS ICP-OES NIRS AAS: Atomic Absorption Spectroscopy; ICP-OES: Inductively Coupled Plasma-Optical Emission Spectrometry; NIRS: Near Infra Red Spectroscopy

  7. Methods reviews

  8. Base line • Brown and milled rice samples from local stores and supermarkets in Colombia, Bolivia, Nicaragua, and Dominican Republic.

  9. N 4832 Mean 14.15 Std Deviation 3.83 Normal 0 1.8 4.2 6.6 9 11.4 13.8 16.2 18.6 21 23.4 25.8 28.2 30.6 33 Zn (mg/kg) Screening to identify products ~ 5000 local varieties and advanced breeding lines Base line 14 N 4667 12 Mean 3.20 Std Deviation 1.26 10 Normal 8 Percent 6 4 2 0 0 0.45 1.05 1.65 2.25 2.85 3.45 4.05 4.65 5.25 5.85 6.45 7.05 7.65 Fe (mg/kg) Base line 22.5 20.0 17.5 15.0 12.5 Percent 10.0 7.5 5.0 2.5 0

  10. Breeding for biofortified rice • Population breeding (through recurrent selection) to develop populations with high Fe and Zn • Line development with high level of iron and zinc

  11. Breeding populations PCT-8 GundilKuning KetanLumbu Perurutong PopulationBreeding Azucena IR68552-100-1-2-2 Madhukar IR71703-657-3-1-2 cycle 1 Percent cycle 2 Fe (ppm) Population PCTBF-1

  12. Breeding lines • 500 crosses • 1945 advanced breeding lines sent to NARS (2005-2009) • ~20,000 segregating lines evaluated in CIAT-Palmira and Santa Rosa • 15 interesting material (S6 and S7 generation) Santa Rosa 2008 Palmira 2008

  13. Rice Agro, Fe and Zn data base • Easy access to iron and zinc data as well as main agronomic data of rice materials in a fast and structured form • Currently 11,600 data points

  14. Nine lines released SACIA-12 (Saavedra-27)

  15. Other products in the pipeline • 65 lines combining good yield, pest and diseases resistance and good grain quality with high Fe and Zn content • 91 and 127 promising S1 lines from two breeding populations (recurrent selection pre-breeding) with Fe and Zn contents greater than checks • 2000 lines with good average values for yield, yields components, biomass production and harvest index to be screened for Fe and Zn content

  16. AB lines with good agronomy 65 advanced breeding lines with high yield, pest and disease resistance and good grain quality Zinc (ppm) Iron (ppm) Lines

  17. S1 lines from RS populations IA Cuba 30 IACuba Zinc (ppm) Iron (ppm)

  18. New method X-ray fluorescence analysis (XRF) • non destructive analysis • no noxious chemicals • no toxic wastes • solid samples  rapid, efficient and reliable

  19. Next steps • Screening germplasm for Fe and Zn Using XRF method • Agronomic evaluation of breeding lines by partners Bolivia, Colombia (North Coast), Nicaragua, Panama • Understanding the genetics of metal homeostasis in rice and low phytic acid (lpa) • Search for allelic diversity • Develop markers chip including functional markers • Breeding for high Fe y Zn • Population breeding • Pedigree breeding • Molecular breeding (MARS and MAS)

  20. Workplan 2014-2018 allelic diversity in genesinvolved in metal homeostasis in rice (association panels)  SNP for in metal homeostasis in rice 2014 - Screening material Screening/ genotyingof a population - Seed multiplication and shipping seeds to partners 2015 - Observation trials by partners - RS/MARS cycle 1 for Fe and Zn 2016 - Advanced yield trials (3 sites/country) - RS/MARS cycle 2 for Fe and Zn  GxE evaluations 2017 - On-farm testing (15 lines)  GxE evaluations - Line evaluation from cycle 1 and 2 2018 - Variety Release - Pedigree breeding of the new selected lines 2019

  21. Acknowledgments Cesar Martinez, Helena Pachon, Sory Sanchez Roger Taboada, Jose Luis Viana, Péricles Neves, Lázaro Narvaez, Violeta Puldon, Angel Adames, Alejandro Vargas and Ismael Camargo

More Related