Remote sensing techniques and stable isotopes as...

Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: effects

of growing temperature and vernalization needs

Cordoba, 6-7 March 2019

F. Z. Rezzouk1, N. Aparicio Gutiérrez2, S.C. Kefauver1, A. Gracia-Romero1, M.D. Serret1, J. L. Araus1*

1Section of Plant Physiology, University of Barcelona, Barcelona and AGROTECNIO (Center of Research in Agrotechnology), Lleida, Spain2Agro-technological Institute of Castilla y León (ITACyL), Valladolid, Spain

Field variability

Selection intensity Genetic variation

Cycle time

Genetic gainOn plots level

On individual plants level

Laboratory analysis

II Simposio Español de Fisiologia y Mejora de Cereales, 6-7 March 2019, Cordoba, Spain

Compare efficiency of differents phenotyping approaches undercontrasting temperature conditions (present and predicted in the future)

Compare efficiency of diferents phenotyping approaches under differentvernalization needs

Normal planting Late planting

Winter genotypes Facultative genotypes

Objectives


Maintainance Irrigation

Fertilizers

Phytosanitary treatment

38 Wheat genotypes

Field visitsHeading

Grain filling


Germplasm

December 2nd

February 8th


Greenseeker

IR Thermometer Multispectral Tetracam

FLIR Tau 640

Lumix GX7

Canopy greennessLight efficiency

Water statusSenescence

Pigments

Remote sensing techniques

Ground platform Aerial platform

1. Grinding dried samples

2. Weighing pulverized samples in tin capsules

3. EA-IRMS analysisδ13C or δ15N (‰) = [(Rsample/Rstandard) - 1] × 1000

+ %C & %N

Stable isotopic composition and elemental analysis

Grain filling

Maturity


Tºmean Growth cycle


Winter: ↓43.45%Facultative: ↓30.17 %

Grain yield


Winter genotyes exhibited poor flowering behavior in thelate planting as a result of lack of vernalization

Winter: ↓28.29%Facultative: ↓37.06%

Winter: ↓22.51%Facultative: ↓18.84%

Days to heading Number of spikes


RGB and Multispectral indices


RGB indices Multispectral indicesHuegr a*gr b*gr GAgr GGAgr Hueae a*ae b*ae GAae GGAae NDVIgr NDVIae EVIae PRIae CCIae TCARIOSAVIae

Hea

ding

Normal plantingAll 0.151 -0.033 0.001 0.386** 0.248** 0.427** 0.264** -0.413** -0.346** -0.294* 0.196* 0.421** 0.234** 0.314** 0.211* -0.503**

Winter 0.211 -0.174 0.062 0.408** 0.263* 0.275* 0.079 -0.228* -0.214 -0.175 0.144 0.379** 0.334** 0.260** 0.306** -0.320**

Facultative 0.352 0.041 -0.196 0.461* 0.350 0.538** 0.306 -0.479** -0.437* -0.340 0.311 0.439* 0.297 0.416* 0.273 -0.510**

Late plantingAll - - - - - -0.060 -0.036 -0.011 0.128 0.135 -0.268** - - - - -

Winter - - - - - -0.116 -0.028 0.026 0.104 0.051 -0.330** - - - - -

Facultative - - - - - 0.177 -0.254 -0.093 0.283 0.397* 0.013 - - - - -

Gra

infil

ling

Normal plantingAll 0.610** -0.616** -0.397** 0.628** 0.575** 0.500** -0.445** -0.336** 0.546** 0.530** 0.611** 0.648** 0.566** 0.538** 0.639** -0.567**

Winter 0.503** -0.477** -0.372** 0.526** 0.499** 0.237* -0.036 -0.252* 0.180 0.252* 0.401** 0.491** 0.391** 0.375** 0.498** -0.392**

Facultative 0.595** -0.599** -0.165 0.594** 0.537** 0.642** -0.624** -0.195 0.629** 0.585** 0.568** 0.629** 0.653** 0.503** 0.648** -0.507**

Late plantingAll 0.103 0.023 -0.269** 0.126 0.082 -0.084 0.045 -0.009 0.117 0.001 -0.096 -0.004 0.241* -0.023 0.193* 0.188

Winter 0.275* 0.013 -0.336** 0.296** 0.286* -0.055 0.110 -0.111 0.137 0.099 -0.133 0.069 0.265* 0.028 0.193 0.118

Facultative 0.409* -0.377* -0.099 0.387* 0.352* -0.046 -0.251 0.232 0.228 0.009 0.214 0.038 0.281 0.023 0.364* 0.252

Canopy temperature


High temperature affects final yield

Plants transpire more

Effect stay green in leaves

Nitrogen partitioning in grains



Lower carbon isotope composition is associated to higher grain yield

Normal planting

Late planting

In both planting dates, lower carbon isotopecomposition values are associated with betterwater status and higher grain yield.


RS assessed during heading RS assessed during GF

Remotesensing Remote

sensing

Analyticaltraits

Analyticaltraits


RM

SE (M

g)

RM

SE (M

g)

All parameters

All parameters

RGB, thermal and multispectral vegetation indices are promising tools to assess crop performance,particularly in grain filling during which differences in stay green across genotypes are well evident.

Carbon isotope composition and nitrogen content performed well regardless of planting dates.

Elevated temperature decreased crop duration and affected negatively yield, particularly in the wintergenotypes given their delayed and poor flowering.

Combination of remote sensing indices and analytical traits improved grain yield prediction for bothplanting dates.

Remote sensing techniques performed better in normal planting than late planting.


José Luís Araus Ortega M. Dolors Serret MolinsRut Sanchez Bragado Adrian Gracia-Romero Omar Vergara Díaz Fadia ChairiJosé A. Fernandez GallegoMa. Luisa BuchaillotShawn C. KefauverMelissa ChangJordi BortThomas VatterRuben Vicente


Thank you very much

Remote sensing techniques and stable isotopes as...

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