Field phenotyping to improve drought tolerance of spring wheat

Transcription

1 Field phenotyping to improve drought tolerance of spring wheat Alejandro del Pozo and Gustavo A. Lobos

2 Drought stress It is expected that environmental constrains for crop production will increase world wide Drought can reduce significantly GY of wheat, particularly in Mediterranean climatic regions where drought is usually more prevalent after heading Terminal drought stress

3 In Chile precipitation have been decreasing Precipitation has been decreasing in Chile in the last century and will probably continue in the future

4 Global annual rainfall trends Chile: 50% SE South America: 23% IPCC (2007)

5 Breeding programs need to face this new scenario identifying drought relate traits and genotypes with augmented tolerance to water stress in order to develop new cultivars. Objectives To phenotype the germoplasm for physiological and agronomic traits under water stress and non-stress field conditions. Characterize the germplasm using molecular markers (genotyping) and combine phenotypic and genomic information to identify chromosomal regions (QTLs) and enable genomic selection.

6 Genomic selection Genomic selection (GS) is a new approach for improving quantitative traits in large plant breeding populations. Information needed: phenotypic information evaluated over a range of environmental conditions; molecular marker scores; and pedigree information Attempt to increase prediction of breeding values

7 Phenotyping 384 lines of spring wheat 1 A set of 384 advanced lines and cultivars from Chile, Uruguay and CIMMYT, with good agronomic characteristics and disease tolerance were evaluated in two Mediterranean environments: Cauquenes (35º58 S, W) - Rainfed conditions ( 400 mm) Santa Rosa (36º32 S, W) - Low water supply (at crop establishment) and full irrigation (without stress)

8 Mediterranean zone

9 The 384 genotypes have been genetically characterized using 28,000 SNPs (genotyping by sequence) INIA-Chile INIA-Uruguay CIMMYT

10 Phenotyping 384 lines of spring wheat 2 Multispectral reflectance (FieldSpec, nm) Canopy temperature (Flir i-40) Other physiological traits: RWC PAR interception (ceptometer) Stem water soluble CHO Carbon discrimination SPAD meter Agronomic traits: Plant height N ears per m2 N grain per ear Thousand kernel weight Grain yield

11 Soil water content Cauquenes-rainfed Santa Rosa-full irrigation Santa Rosa-low water supply

12 Means ± SE and range of values of agronomic traits of spring wheat Trait N of plants m-2 Plant height (cm) GY (ton ha-1) N ears per m-2 N grains per ear Thousand kernel weight (g) Severe stress (Cauquenes) Moderate stress (Santa Rosa) Without stress (Santa Rosa) 166 ± ± ± 87 (15-415) (15-712) (57-613) 58 ± 8 91 ± ± 8 (40-95) (37-150) (74-149) 1.7 ± ± ± 1.2 ( ) ( ) ( ) 327 ± ± ± 112 (80-755) ( ) (70-883) 35.2 ± ± ± 6.0 ( ) ( ) ( ) 34.2 ± ± ± 6.2 ( ) ( ) ( )

13 Spatial variation according to yield at Santa Rosa Dato perdido

14 Reflectance of wheat canopy Series Series2 Series Deleted area Series5 (wavelength) Series Series7 Series Series Series10 Deleted area (wavelength): Series11 Series12 Series13 Series Series15 Series Series17 Series Series Reflectance Series4 Deleted area (wavelength):

15 Relationship between grain yield and NDVI 14 Severe stress (Cauquenes) Yield (ton ha)-1 12 Moderate stress (Sta. Rosa) Without stress (Sta. Rosa) NDVI 0.8 1

16 Relationship between grain yield and water index (WI = R900/R970) 14 Severe stress (Cauquenes) Yield (ton ha-1) 12 Moderate stress (Sta. Rosa) 10 Without stress (Sta. Rosa) WI

17 Wavelength selection using BuildQsar Response variable: Yield (ton ha-1) SANTA ROSA Moderate stress N R² variables r Model Q R² Validation Selected welength

18 Wavelength selection using BuildQsar Response variable: Yield (ton ha-1) SANTA ROSA full irrigation N variables r R² Model Q R² Validation Selected welength

19 Stress tolerance index (STI) 1.6 F291 STI Sta Rosa secano 1.4 F F F F63 F2 F35 F STI Cauquenes YD YI Y D STI Y D Y I Y I 0.5 YD YI Y I

20 Means ± SE and range of values of physiological traits of spring wheat Trait PAR intercepted Severe stress (Cauquenes) RWC (%) Without stress (Santa Rosa) 81 ± 9 69 ± 6 (13-98) (48-94) 47.1 ± ± ± 2.6 ( ) ( ) ( ) - 73 ± ± 0.1 (6-97) ( ) - (%) SPAD Moderate stress (Santa Rosa) Stem CHOa 178 ± ± ± 50 (mg g-1) (64-548) (54-395) (55-591) Stem CHOm 43 ± ± ± 5 (mg g-1) (16-171) (10-152) (7-34)

21 Concluding remarks Large variation in agronomic traits was detected in spring wheat germoplasms with and without water stress Spatial variation in field experiments can be reduced by mapping soil electric conductivity before sowing. Good relationships have been found between selected wavelengths and grain yield on different environments

22 Participants Universidad de Talca Prof. Alejandro del Pozo Dr. Gustavo Lobos Alejandra Yañez (Doctoral thesis) Sebastián Romero, Ing. Agr., MSc Alejandro Escobar (MSc Thesis) INIA Quilamapu Dr. Iván Matus Dr. Gerardo Tapia Dr. Luís Inostroza Alejandra Rodriguez (Ing. Agr.) Alejandro Castro (Tech) Millaray Ponce (Tech) Universidad de Barcelona Prof. José Luis Araus INIA Uruguay University of Laval Dr. François Belzile Kansas State University Dr. Jesse Poland Dr. Jari von Zitzewitz Dr. Martin Quinque Dra. Marina Castro Mrs. Bettina Lado (MSc Thesis) CIMMYT Wheat Program

23 Grants FONDECYT N : Enhancing drought tolerance in spring wheat using physiological traits and molecular markers ( ) FONTAGRO ATN/OC 11943: Adaptación de sistemas productivos de papa y trigo al cambio climático ( ) Atracción de Capital Humano Avanzado del Extranjero A Chile (CONICYT): Implementación de nuevas tecnologías para la evaluación y selección de genotipos de cereales que posean mayor tolerancia a estreses ambientales ( )

24 Thanks for your attention