1 A firm foundation: better seed, practices and food R. M. Trethowan A firm foundation: better seed, practices and food R Trethowan

1

A firm foundation: better seed, practices and food

R. M. Trethowan

A firm foundation: better seed, practices and food

R Trethowan

2

1. Creating the genetic potential for better food

- stepwise exploitation of genetic diversity- efficient breeding strategies- collaboration

2. Realizing the genetic potential for better food

- exploiting genotype x crop management x environment interactions

Wheat as an example

More food first: wheat production areas with high (P > 50%) to low probability (P < 20%) of

occurrence of drought stress

High Intermediate Low

Genetics & higher quality, more nutritious food

CIMMYT (2006)

4

Adapted cultivars

Landraces

Related species (crossable)

Alien species

Stepwise exploitation of genetic resources


5


Chromosome Number of significant markers linked to yield

1A 3

1B 1

1D 4

2A 6

5A 2

5B 4

6A 12

6D 3

7A 20

7D 6

More food first: genetics of wheat yield potential in northwestern NSW

Atta et al 2013

Association analysis of a commercial wheat breeding program

Based on 300 parents & derived progeny tested in multi-environment trials over 3 years

6


Crown rot in wheat Complex inheritance of resistance Plenty of genetic variation in the gene pool Low heritability Symptoms exacerbated under moisture stress Shriveled grain impacts processing quality

Marker assisted recurrent selection Combine resistance QTLs in each population Yield testing in paired plots (+/- inoculation) Off season symptom testing

More food first: improving WUE through root health

GRDC supported

7


Significant Markers - CSCR16/2/2-49/CUNNINGHAM//KENEDY/3/SUNCO/2*PASTOR(1RDRN#44)

Symptom expression of season (controlled conditions) 1AL, 1BL, 1DL, 2AL, 2BL, 2BS, 3AL, 3DL, 4AL, 4BL, 4DL,

4DS, 5AL, 5AS, 5BS, 5DL, 6AL, 6BL, 6DL, 7AS, 7BS Field

1AL, 2BL, 3AL, 3B(?), 4BL, 4DL, 5BL,6BL

More food first: Recombination of positive gene effects for crown rot resistance

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More food first: Yield of MARS progeny & best commercial crown rot resistant cultivars, Narrabri

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ld k

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Genotypes of an Indo-Australian

parental set (180 genotypes; 1636

polymorphic clones)

More food first: a bilateral international collaboration to exploit genetic diversity

ACIAR supported

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2.2

2.4

2.6

2.8

3

3.2

3.4

3.6

3.8

More food first: Yield (t/ha) of Indo-Australian progeny in northern NSW

Australian parent

Indian parent

DBW16/Sunstate


T. dicoccum or durum

A. tauschii

AABBDD

DD

+

AABB

More food first: synthetic wheat as a source of genetic variability


http://www.google.com.au/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&docid=moXjQtAoMbuZVM&tbnid=9wxCKu-hStQRUM:&ved=0CAUQjRw&url=http://mathildasanthropologyblog.wordpress.com/2008/06/11/the-domestication-of-emmer-wheat/&ei=sa3bUfXlIcafkwXb0oGQAg&bvm=bv.48705608,d.dGI&psig=AFQjCNHT5txf_P-pGLB3zDozwiKXHNuhlQ&ust=1373437703103189

12


10 11 12 13 14 15 16 17 18 193000

3500

4000

4500

5000

5500

f(x) = 264.08067326481 x + 106.308437530002R² = 0.88187497274732

WUEGrain (kg ha-1 mm-1)

Gra

in y

ield

(kg

ha-

1)

Envoy Cunningham

Synthetic/Cunningham

Spitfire

Atta et al., 2013

More food first: improved WUE (3-year mean) at Narrabri, NSW

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Cultivar Glu-A3 Glu-A1 Glu-B3 Glu-B1 Glu-D3 Glu-D1 Rmax (BU)

Ext (cm)

Silverstar 1 b a h b b a 310 20.8Silverstar 2 c a h b b a 270 20.3Silverstar 3 b a h b b d 383 20.2Silverstar 4 c a h b b d 343 19.8Silverstar 5 b a h i b a 300 20.7Silverstar 6 c a h i b a 261 20.2Silverstar 7 b a h i b d 369 20.1Silverstar 8 c a h i b d 329 19.7

Better processing quality: making better crosses through prediction of dough quality based on alleles at 6 glutenin loci (Wang et al 2005)

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Higher mortalityHigher morbidityLower cognitive abilityLower work productivityImpaired growthImpaired reproduction5% annual loss in GDP in South Asia

An estimated 3 billion people suffer from Vitamin A, Fe & Zn deficiencies world wide (Graham et al., 2001)

More nutritious food: the consequences of micronutrient malnutrition globally

FAO data, 1999

% Change in Cereal & Pulse Production Between 1965-1999

0

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100

150

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0

50

100

150

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250Cereal Production Pulse Production Population

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20.88 25.88 30.88 35.88 40.88 45.881127

1327

1527

1727

1927

2127

2327

2527

2727

2927

f(x) = − 25.9624693913538 x + 2745.69612780526R² = 0.117385881783909

Zn grain concentration

Gra

in Y

ield

kg/

ha

More nutritious food: enhancing levels of essential micronutrients in food

Kapfuchira 2014

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Fructan and phytate not correlated with Yield (Kapfuchira 2014)

0.111 0.161 0.211 0.261 0.311 0.3611127

1327

1527

1727

1927

2127

2327

2527

2727

2927

f(x) = − 211.961537354218 x + 1968.32253262722R² = 0.000596860467114047

Grain phytate

Gra

in Y

ield

Kg/

ha

1.13 1.23 1.33 1.43 1.53 1.63 1.73 1.83 1.93 2.03 2.131127

1327

1527

1727

1927

2127

2327

2527

2727

2927

f(x) = − 9.9951424239942 x + 1940.05591130409R² = 2.77957676910745E-05

Grain fructan

Gra

in Y

ield

kg/

ha

More nutritious food: targeting enhancers of micronutrient bioavailability


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› Phytate and Fructan grain concentration are independently inherited.

› No common marker associated with Fe & Zn grain concentration

Trait Chromosome SNP MarkerSource of High Allele LOD Score

Phytate 2B 1279272 IDO 637 2.52

Phytate 3A 2346126 IDO 637 3.31

Phytate 7B 1111547 IRS 812.9 7.17

Fructan 2B 1252182 IRS 812.9 5.91

Fructan 7A 2373159 IRS 812.9 12.00

Fructan 7B 2294143 IDO 637 4.77

Fe 1B 2278693 IRS 812.9 11.36

Fe 3A 1089315 IDO 637 3.73

Fe 6B 1222885 IDO 637 4.25

Zn 3B 1860597 IDO 637 8.74

Zn 6B 1298803 IRS 812.9 4.82

Zn 7B 1104316 IRS 812.9 6.93

More nutritious food: QTL analysis of key nutrients in wheat

Kapfuchira 2014

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More nutritious food: effect of phytate/fructan level on broiler weight gain (BWG) and food intake (FI) up to 14 days age

High/High

High/Low

Low/High

Low/Low

0.3

0.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

BWG d1-14 KgFI d1-14 kg

Phytate/Fructan level

Kg

BWG d1-14 (kg)

FI d1-14 (kg)

0.3

0.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

High fructanLow fructan

kg

Realizing the genetic potential for better food

20

USA 26m

Brazil 25m

Argentina 20m

Canada 13m

Australia 12mParaguay 2m

Exploiting G x M x E: adoption of conservation agriculture globally

105 m ha under conservation agriculture (FAO, 2010)


Crop Genotype x Tillage

Literature

Wheat +/- Gutierrez (2005); Cox (1991); Wilkes et al (2010); Trethowan et al (2012)

Barley - Ullrich & Muir (1986)

Sorghum - Francis et al. (1985)

Maize +/- Newhouse (1985); Brakke et al (1983); Newhouse & Crosbie (1983)

Rice - Melo et al (2005)

Soybean - Elmore (1990); Pfeiffer (1987)

Other pulses ? NA

Exploiting G x M x E: published evidence of genotype x tillage interactions

Five crosses among lines with contrasting responses under zero-tillage

Always selected under zero-tillage

Always selected under conventional tillage

Advanced lines from both selection regimes evaluated under both zero and

conventional tillageSayre & Trethowan

Exploiting G x M x E: can a genotype x tillage practice interaction be designed?



Effects of Cross and Selection System on Grain Yield Averaged over 2005, 2006 and 2007

Cross x Selection System LSD (0.05) = 143 kg/ ha

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SERI/..BERKUT SW94.../PBW65 FILIN./PASTOR MILAN./PASTOR PFAU../AMAD

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ZERO TILL SELECTION CONV TILL SELECTION

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Exploiting G x M x E: 3-year mean performance in Mexico

Genotype x tillage practice trials on two soil types at Narrabri

Exploiting G x M x E: QTL mapping of plant response to management regime at Narrabri

:



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Genotype

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Exploiting G x M x E: yield difference between zero-tillage (ZT) and conventional tillage (CT) over two sites and two years at Narrabri


Chr Interval Treatment Soil type Additive effect %

Allele

1B gwm268/wPt-3475 CT Grey v 8 K

1B wPt-1313/gmw140 CT Grey v 10 K

1D cdf19/wmc216 CT Red k 10 K

2D wPt-3728/cfd44 ZT Grey v 9 K

2D gmw484/wmc27 ZT Red k 9 B

5A cfa2155/wPt1370 ZT Grey v 25 B

5A cfa2115/wPt1370 CT Grey v 14 B

5A cfa2115/wPt1370 CT Red k 9 B

5B wmc99/wPt2373 ZT Grey v 12 B

Trethowan et al. 2012.

Exploiting G x M x E: significant QTLs for yield under contrasting tillage regimes


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Genotype 18 Genotype 21 Genotype 228

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Kandosol CTKandosol ZTVertosol CTVertosol ZT

Prot

ein

%

Exploiting G x M x E: variation in total grain protein with genotype, soil and tillage regime

(Wilkes et al 2010)

CT ZT

CT ZT CT ZT

CT ZT CT ZT

CT ZT


Total Protein%

Insoluble Protein

Soluble Protein

Starch Amylose Flour Swelling Power

Genotype (G) *** *** ns ** * ***

Soil (S) *** *** ** *** ns ***

Tillage (T) *** ns * * * ***

G x S *** ** ns ns ns ***

G x T *** *** ns ns ** ns

S x T *** *** ns ns *** ns

G x T x S *** *** ns ns ** ns

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Exploiting G x M x E: grain quality implications from genotype x tillage trials, Narrabri

*, **, *** are P<0.05, 0.01, 0.001 respectively

Wilkes et al, 2010

29

Genotype x crop management x environment interactions are highly complex but can be manipulated

to enhance both the quantity and quality of our food supply

30

Acknowledgements

Funding:

GRDC, ACIAR, Generation Challenge Program & the Wheat Research Foundation

Collaboration:

Colleagues across the PBI Australia’s wheat breeding groups & companiesIndian Council for Agricultural ResearchCIMMYT & ICARDA scientistsVeterinary Science, Camden

Documents

1 A firm foundation: better seed, practices and food R. M. Trethowan A firm foundation: better seed, practices and food R Trethowan