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Integration of new tools for improving genetic gain of grain yield in water-limited environments
CSIRO AGRICULTURE FLAGSHIP
Greg Rebetzke, Bill Bovill, David Deery, Jose Jimenez-Berni, Anton Wasson, Richard James and Lynne McIntyre
1. Trait value? • Are the traits relevant to the target environment(s)? • What is the value proposition? • What are the trade-offs? • Can I scale up from cell, single-plant and row to canopy? • What do I give up in order to accommodate the new trait/germplasm? 2. Selection? • How do I phenotype? Is it quick, cheap and reliable? • Heritability and the correlation of phenotype with genotype? • Genetic complexity/QTL/markers? • Influence of genetic background/repeatable? • Quality of donor germplasm? • Correlated response? 3. Adoption? • How does the gene/trait fit in the target farming system?
The questions a breeder is asking are very different to those
being asked by researchers further upstream
Grain
Yield
= Water
Use
x Water-use
Efficiency
x Harvest
Index
Biomass
The model for productivity under water-limitation:
T/ET - rapid canopy growth to shade the soil surface and restrict evaporation
DM/T - transpiration efficiency (or leaf-level WUE)
HI - C partitioning to the growing spike (grain number) and then to the grain (grain
size) (balance water use before and after flowering to optimise harvest index)
T/ET x DM/T
Drought resistance? No!
Water use efficiency as a breeding target. Yes!
Many potential traits to improve crop performance under
drought
New root architecture
Stem CHO for large grain
Genes for better emergence
Transpiration efficiency
C13
C12 Glaucousness
Vigorous early growth
Reduced tillering
Developmental genes
Which traits where? Trait dissection Trait delivery
Need for repeatable phenotyping - controlled ‘managed’
environments (Managed Environment Facilities – ‘MEF’)
In Australia - three sites with two-three irrigation regimes
Which traits where? Quality phenotyping – controlled field environments (Managed Environment Facilities – ‘MEF’)
Maximising water uptake by removing constraints to root
(and shoot) growth – mapping of soil conductivity
(Rick Graham NSWDPI)
Break crops to reduce root disease
Canola in the rotation
Wheat after Wheat Wheat after Canola
*** Reduce soil-borne diseases
(take-all, crown rot, CCN, root-
lesion nematodes)
(Kirkegaard CSIRO)
Random to selected lines – deriving greater benefit from
populations in selection of tails extreme for target trait
High-selected group Low-selected group
‘Traits’ germplasm
Germplasm Background(s) Number of lines
Canopy temperature Multiple 20 lines/tail
Development Single 13 near-isogenic pairs
Early vigour Multiple 10 lines/tail
Grain fertility Multiple 20 lines/tail
Grain size/screenings Single 10 lines/tail
Ear morphology Multiple 24 near-isogenic pairs
Reduced-tillering Multiple 20 near-isogenic pairs
Staygreen (leaf) Multiple 10 lines/tail
Stem carbohydrates Multiple 15 lines/tail
Transpiration efficiency Multiple 10 lines/tail
Box-plot of all entry means/variance for grain yield at each sampled MEF
(M = Merredin, N = Narrabri, Y = Yanco; Ir = irrigated, Rf = rainfed)
2014 contrasted genotype response at Narrabri with response at Yanco and Merredin (largely uncorrelated!)
-0.3 -0.2 -0.1 0.0 0.1
-0.3
-0.2
-0.1
0.0
0.1
Comp.1
Com
p.2
20-1-2NT
20-1-5NT
4-4-1NT
4-4-6NT
5-3-4NT
5-3-8NT
5216N
5216P
6072N
6072P
6184N
6184P
6266N
6266P
6336N
6336P2
6460N
6460P
6661N
6661P
7276N
7276PF
7566N
7566PUNI
7770N
7770P
8009N
8009P
Axe
B+
B++
B-
DH_R034
DH_R035
DH_R070
DH_R072
DH_R087
DH_R101
DH_R120
DH_R150
DH_R154
DH_R162
DH_R167
DH_R182
DH_R187
DH_R202
DH_R263
DH_R275
DH_R336
DH_R344
Drysdale
Excalibur
FA1+
FA1-
FA3+
FA3-
FA8+
FA8-
Gladius
Hartog
JA2+
JA2-
JA6+
JA6-
LRBC136LRBC156
LRBC181
LRBC187
LRBC193
LRBC24
LRBC243
LRBC27
LRBC271
LRBC285LRBC311LRBC327
LRBC386
LRBC388
LRBC392
LRBC409
LRBC466
LRBC62
Mace
QA144
QA175
QA177
QA178
QA179
QA183
QA193
QA223
QA227
QA236
QA268
QA321
QA35
QA69QA72
QA87
QA95
QA97
QC14
QC15QC18
QC19
QC2
QC20
QC25
QC27
QC28
QC29
QC30
QC7
QH181-7QH194-3
QH210-5
QH22
QH221-10
QH239-4
QH25
QH252-2R
QH32
QH5
QH52-2
QH56QH71-3r
QH71-4
QH71-9
QH74-10
QH74-2QW111
QW12
QW13
QW132
QW134
QW135
QW136
QW144
QW146
QW148
QW155
QW160
QW170
QW183
QW188
QW190
QW23
QW51
QW59
QW67
QW87
QW88
RAC875
SB002
SB012
SB017
SB021
SB023
SB025
SB026
SB027
SB035
SB037
SB049
SB051
SB053
SB070
SB071
SB091
SB095
SB1+
SB1-SB101
SB118
SB127
SB130
SB134
SB162
SB163
SB165
SB171
SB179
SB2+ SB2-
SB5-(B)
Sun595B
Sunstate+
Sunstate-
W010111
W030311
W040217
W050114
W050204W050306
W080205
W100109
W100209
W100402
W100504
W110511
W111402
W11B
W120216
W130102
W140910
W15A
W170310
W1A
W200118
W210203
W220416W260801
W280308
W3A
W4AW8A
WA11+
WA11-
WA3+
WA3-
WA8-
WB1+
WB1-
Weebill
Westonia
wj111
wj113wj115
wj119
wj171
wj22wj23
wj25
wj30
wj44wj84
Wyalkatchem
Yitpi
-30 -20 -10 0 10
-30
-20
-10
010
YIrrYRf
NIrrNRf
MIr
MRf
-0.2 -0.1 0.0 0.1 0.2
-0.2
-0.1
0.0
0.1
0.2
Comp.1
Com
p.2
20-1-2NT
20-1-5NT
4-4-1NT
4-4-6NT
5-3-4NT5-3-8NT
5216N
5216P
6072N
6072P
6184N
6184P
6266N
6266P
6336N
6336P2
6460N
6460P6661N
6661P
7276N
7276PF
7566N
7566PUNI
7770N
7770P
8009N 8009P
AxeB+
B++
B-
DH_R034
DH_R035
DH_R070
DH_R072
DH_R087
DH_R101
DH_R120
DH_R150
DH_R154
DH_R162
DH_R167
DH_R182
DH_R187
DH_R202
DH_R263
DH_R275
DH_R336
DH_R344
Drysdale
Excalibur
FA1+
FA1-
FA3+FA3-
FA8+
FA8-
Gladius
Hartog
JA2+
JA2-
JA6+
JA6-
LRBC136
LRBC156
LRBC181
LRBC187
LRBC193
LRBC24
LRBC243
LRBC27
LRBC271
LRBC285LRBC311
LRBC327
LRBC386
LRBC388
LRBC392
LRBC409LRBC466 LRBC62
Mace
QA144QA175
QA177
QA178
QA179
QA183
QA193
QA223
QA227
QA236QA268
QA321
QA35
QA69
QA72
QA87
QA95
QA97
QC14
QC15
QC18
QC19
QC2
QC20
QC25
QC27
QC28QC29
QC30
QC7
QH181-7
QH194-3
QH210-5
QH22QH221-10
QH239-4
QH25
QH252-2R
QH32QH5
QH52-2
QH56
QH71-3r
QH71-4
QH71-9
QH74-10
QH74-2
QW111
QW12
QW13
QW132
QW134QW135
QW136
QW144
QW146
QW148
QW155
QW160
QW170
QW183
QW188
QW190QW23QW51
QW59
QW67
QW87
QW88
RAC875
SB002
SB012SB017
SB021SB023
SB025
SB026SB027
SB035
SB037
SB049
SB051SB053
SB070
SB071
SB091SB095
SB1+SB1-SB101SB118SB127
SB130
SB134
SB162
SB163
SB165
SB171
SB179
SB2+
SB2-
SB5-(B)
Sun595B
Sunstate+
Sunstate-
W010111
W030311W040217W050114
W050204
W050306
W080205
W100109
W100209
W100402
W100504
W110511
W111402
W11BW120216
W130102
W140910W15A
W170310
W1A
W200118
W210203
W220416
W260801
W280308W3A
W4A
W8A
WA11+
WA11-
WA3+WA3-
WA8-
WB1+
WB1-
Weebill
Westonia
wj111wj113
wj115
wj119
wj171
wj22
wj23
wj25
wj30wj44
wj84
Wyalkatchem
Yitpi
-10 -5 0 5 10
-10
-50
510
YIrrYRf
NIrrNRf
MIr
MRf
Grain yield Harvest index
-0.2 -0.1 0.0 0.1 0.2
-0.2
-0.1
0.0
0.1
0.2
Comp.1
Com
p.2
20-1-2NT
20-1-5NT
4-4-1NT
4-4-6NT
5-3-4NT5-3-8NT
5216N
5216P
6072N
6072P
6184N
6184P
6266N
6266P
6336N
6336P2
6460N
6460P6661N
6661P
7276N
7276PF
7566N
7566PUNI
7770N
7770P
8009N
8009P
Axe
B+
B++
B-
DH_R034
DH_R035
DH_R070
DH_R072
DH_R087
DH_R101
DH_R120
DH_R150
DH_R154
DH_R162
DH_R167
DH_R182
DH_R187DH_R202DH_R263
DH_R275
DH_R336
DH_R344
Drysdale
Excalibur
FA1+FA1-
FA3+
FA3-
FA8+
FA8-
Gladius Hartog
JA2+
JA2-
JA6+
JA6-
LRBC136
LRBC156
LRBC181
LRBC187
LRBC193
LRBC24
LRBC243
LRBC27
LRBC271
LRBC285
LRBC311LRBC327
LRBC386
LRBC388LRBC392
LRBC409LRBC466 LRBC62
Mace
QA144QA175
QA177QA178
QA179QA183
QA193
QA223
QA227
QA236
QA268
QA321
QA35
QA69
QA72
QA87
QA95
QA97
QC14
QC15
QC18
QC19QC2
QC20QC25
QC27
QC28
QC29
QC30
QC7
QH181-7
QH194-3
QH210-5
QH22
QH221-10
QH239-4QH25
QH252-2R
QH32
QH5
QH52-2
QH56QH71-3rQH71-4
QH71-9
QH74-10
QH74-2
QW111
QW12
QW13
QW132
QW134
QW135
QW136
QW144
QW146
QW148
QW155
QW160 QW170
QW183
QW188
QW190
QW23
QW51
QW59
QW67 QW87
QW88
RAC875
SB002
SB012
SB017SB021
SB023
SB025
SB026
SB027
SB035
SB037
SB049
SB051
SB053
SB070
SB071
SB091
SB095
SB1+SB1-SB101SB118
SB127
SB130
SB134
SB162SB163
SB165
SB171
SB179
SB2+
SB2-
SB5-(B)
Sun595B
Sunstate+
Sunstate-
W010111
W030311W040217
W050114
W050204W050306
W080205
W100109
W100209
W100402
W100504
W110511
W111402
W11BW120216
W130102
W140910
W15A
W170310
W1A
W200118
W210203
W220416
W260801W280308
W3A
W4AW8A
WA11+
WA11-
WA3+
WA3-
WA8-
WB1+
WB1-
Weebill
Westonia
wj111
wj113
wj115
wj119
wj171
wj22
wj23
wj25
wj30wj44 wj84
WyalkatchemYitpi
-10 -5 0 5 10 15-1
0-5
05
10
15
YIrr
YRf
NIrrNRf
MIrMRf
Grain number
-0.1 0.0 0.1 0.2
-0.1
0.0
0.1
0.2
Comp.1
Com
p.2
20-1-2NT
20-1-5NT
4-4-1NT
4-4-6NT
5-3-4NT
5-3-8NT
5216N
5216P
6072N
6072P
6184N
6184P6266N
6266P
6336N
6336P2
6460N
6460P
6661N
6661P
7276N
7276PF
7566N
7566PUNI
7770N
7770P
8009N
8009P
Axe
B+
B++
B-
DH_R034
DH_R035
DH_R070 DH_R072
DH_R087
DH_R101
DH_R120
DH_R150
DH_R154
DH_R162
DH_R167
DH_R182
DH_R187
DH_R202
DH_R263
DH_R275
DH_R336
DH_R344
Drysdale
Excalibur
FA1+
FA1-
FA3+
FA3-
FA8+
FA8-
Gladius Hartog
JA2+
JA2-
JA6+
JA6-
LRBC136LRBC156
LRBC181
LRBC187
LRBC193
LRBC24
LRBC243
LRBC27LRBC271
LRBC285
LRBC311LRBC327
LRBC386
LRBC388
LRBC392
LRBC409
LRBC466
LRBC62
Mace
QA144
QA175
QA177
QA178
QA179
QA183
QA193
QA223
QA227
QA236
QA268
QA321
QA35
QA69QA72
QA87
QA95
QA97
QC14
QC15QC18
QC19
QC2
QC20QC25
QC27
QC28
QC29
QC30 QC7
QH181-7
QH194-3
QH210-5
QH22
QH221-10
QH239-4
QH25
QH252-2R
QH32
QH5
QH52-2
QH56
QH71-3r
QH71-4QH71-9
QH74-10
QH74-2
QW111QW12
QW13
QW132
QW134
QW135
QW136
QW144
QW146
QW148
QW155QW160
QW170
QW183
QW188
QW190QW23
QW51
QW59QW67
QW87
QW88
RAC875
SB002
SB012
SB017
SB021
SB023
SB025
SB026
SB027
SB035
SB037
SB049
SB051
SB053
SB070
SB071
SB091
SB095
SB1+
SB1-SB101
SB118
SB127
SB130
SB134
SB162
SB163
SB165
SB171
SB179
SB2+SB2-
SB5-(B)
Sun595B
Sunstate+
Sunstate-
W010111
W030311
W040217
W050114
W050204
W050306
W080205
W100109
W100209
W100402
W100504
W110511
W111402W11B
W120216
W130102
W140910
W15A
W170310
W1AW200118
W210203
W220416W260801
W280308W3A
W4A
W8A
WA11+
WA11-
WA3+
WA3-
WA8-
WB1+
WB1-
Weebill
Westonia
wj111
wj113
wj115
wj119
wj171
wj22
wj23
wj25
wj30
wj44
wj84
Wyalkatchem
Yitpi
-10 0 10 20
-10
010
20
YIrrYRf
NIrrNRf
MIr
MRf
Grain weight
Grain yield of trait germplasm is comparable to that of commercial checks at the MEF
Note that the traits are tested in germplasm developed in current or recent commercial wheat
backgrounds and that the trait lines used in the MEF are not selected for grain yield
Early ground cover (‘vigour’) E
arly g
round
cover
assessm
en
t (%
)
20
30
40
50
60
70
80
90
Drysdale - 41Mace - 40Yitpi - 47
Drysdale - 50Mace - 39Yitpi - 48
YancoNarrabri
- Vigour + Vigour
Canopy temperature C
anop
y t
em
pe
ratu
re (
Z55)
(oC
)
14
16
18
20
22
24
26
Drysdale - 23.03Mace - 23.65Yitpi - 22.09
Drysdale - 18.74Mace - 18.61Yitpi - 18.65
YancoNarrabri
Water-soluble carbohydrate concentration W
SC
con
centr
ation
(m
g/g
)
0
50
100
150
200
250
300
350
Drysdale - 135Mace - 109Yitpi - 115
Drysdale - 227Mace - 251Yitpi - 214
Yanco_Irr Merredin_Irr
Grain yield (multivariate – all sites and irrigation regimes)
-0.10 -0.05 0.00 0.05
-0.1
0-0
.05
0.0
00.0
5
Comp.1
Com
p.2
1
2
34
56
7
89
10
11
12
131415
16
17
18
19
20
21
22
23
24
25
26
2728
29
3031
32
3334
35
3637
38
39
40
414243
44
45
46
47
48
49
50
51
52
53
54
5556
57
58
59 60
61
62
6364
65
67
6869 70
71
7273
74
75
76
77
78
79
80
81
82
83
84
85
86
87
8889
90
91
92
93
94
95
9697
98
99100
101
102
103
104
105
106
107
108
109110
111
112
113114115
116117
118
119120
121
122
123
124
125
126
127128
129130
131132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147148149
150
151
152153
154155156
157
158
159
160
161162163164165
166
167
168169
170
171
172
173174175176
177
178
179
180
181
182
183
184
185
186
187188
189
190
191
192193
194
195
196
197
198
200
201
202
203
204205
206
207208209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224225
226
227
228
229
230
231232234
235
236
237238239
240
241
242
243244
245
246247
248
249
250
251
252
253
254
255
256
257258259
260
261
262
263
264
265266
267
268
269270271
272
273274
275
276
277
278
279
280
281
282
283284285
286287
288289 290
291
292
293294
295
296
297298
299300
301
302
303
304
305
306307
308
309
310311312
313
314
315
317
318
319
320
321
322
323
324
325
326
327328329
330
331
332333334
335
336
337
338339340
341
342
343
344
345
346347348
349
350
351
352
353
354
355
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357
358
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360361
362
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368
369
370
371
372
373374
375
376377
378
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382
383
384
385
386
387
388
389
390391
392
393
394
395
396
397398
399
400
401
402
403
404
405
406407
408
409
410
411
412413414415416
417
418
419
420
421
422
423
424
425426
427428
429
430
431432433434
435
436
437
439440
441442
443
444
445446
447448449
450
451
452453
454
455
456
457458
459
460
461
462
463
464
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466
467
468 469
470
471
472
473
474
475
476477478479
480
481
482
483
484
485
486
487488
489490
491
492
493
494
495
496497
498
499500501
502
503
504
505506
507
508
509
510
511
512
513
514
515516517
518
519520
521
522
523
524
525
526
527
528
529530
531
532
533
534535
536
537
538
539540
541
542
543544
545
546547
548
549
550
551
552553
554555
556557
558
559
560
561562 563564
565
566
567
568
569
570
571572573
574
575576
577
578
579
580581
582
583
584
585
586
587
588589
590
591
592
593
594
595
596597
598
599
601
602603
604
605606607
608
609
610
611
612
613
614
615616 617
618
619
620
621
622623
624
625
626
627
628
629
630631
632
633634
635 636
637638639
640
641642 643644
645646
647
648
649
650651
652
653
654655
656
657
658659
660
661662
663
664665
666
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668
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677
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679680
681
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686687
688
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693694
696697
698699
700701
702
703704
705
706 707
708
709
710
711
712
713
714
715
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719
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721
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723
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728
729 730
731
732
733
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735
736
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739740
741
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743
744
745746747
748 749
750751752
753
754755
756757
758
759760
761
762 763
764
765
766
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768
769
770
771
772773
774
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783
784
785786
787
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795796
797798
799
800801
802803
804805
806
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811
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814
815816
817
818
819
820
821822
823824825
826
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828
829
830
831
832
833
834
835
836837
838
839
840841842
843
844
845
846
847848
849
850
851
852
853
854 855
856857
858859860
861
862
863
864
865866
867868869
870
871
872873874
875
876
877
878
879
880
881882883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899900901
902
903904
905
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907
908
909
910911
912
913
914
915
916917
918
919
920
921
922
923
924
925
926927928
929
930
931
932
933
934935
936
937938
939
940
941
942943
944
945
946947
948949
950
951
952
953954
955
956
957958
959
960961
962
963
964
965
966
967
968
969
970
971
972
973974
975976
977
978
979980
981
982983
984985
986
987988
989
990
991
992
993
994
995996
997
998999
10001001
1002
1003
1004
10051006
1007
1008
1009101010111012
1013
10141015
1016
1017
101810191020
10211022
1023
1024
1025
1026
1027
10281029
1030
1031
1032
1033
1034
1035
1036103710381039
1040
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10471048
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10551056
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105810591060
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10621063 10641065
10661067
10681069
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107310741075
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1080
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10861087
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109410951096
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10981099
1100
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1102
1103
11041105
1106
11071108
1109
11101111
1112
11131114
11151116
1117
1118
1119
1120
1121
112211241125
1126
1127
1128
1129
1130
1131
11321133
11341135
1136
1137
1138
1139
1140
1141
11421143
1144
1145
1146
11471148
1149
1150
11511152
11531154
1155
1156
1157
1158
1159 1160
1161
1162
116311641165
1166
1167
11681169
1170
1171
11721173
11741175
11761177
11781179
11801181
11821183
11841185
11861187
1188
118911901191
1192
1193
1195
1196
11971198
1199
1200
12011202
1203
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1205
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1207 12081209
12101211
1212
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12161217
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1219 1220
1221
12221223
1224
1225
12261227
1228
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12301231
1232
1233
1234123512361237
12381239
12401241
1242
12431244
12451246
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12491250
1251
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1254
12551256
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12611262
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12661267
1268
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12701271
1272
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12821283
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12851286
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13011302
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1309 1310
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13141315
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13171318
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13201321
1322
13231324
13251327
1328
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13301331
1332
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13341335
1336
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13401341
1342
1343
1344
134513461347
13481349
1350
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13541355
13561357
1358
135913601361
1362
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13651366
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13681369
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1371
1372
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13801381
1382
1383
1384
1385
13861387
13881389
13901391
1392
1393
1394
13951396
1397
1398
13991400 14011402
1403
1404
1405
1406
1407
1408
1409
141014111412
1413
1414
1415
1416
1417
1418
14191420
1421
1422
14231424
1425
1426
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14281429
1430
14311432 1433
1434
14351436
1437
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14401441
1442
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14481449
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145214531454
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14711472
1473
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14771478
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1482148314841485
1486
1487
1488
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14901491
1492
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14961497
1498
1499
1500
15011502
1503
1504
1505
1506
-30 -20 -10 0 10 20 30
-30
-20
-10
010
20
30
AnDM
Ayld
HI
Nospks
Seed wt
No.grain
Trait value for grain yield at each MEF (2010-14)
Trait value is calculated as the percentage change in mean yield of lines selected for the trait
relative to sister lines that lack the trait at each MEF location in one to four years of testing
Trait
Can
opy te
mpe
ratu
re
Car
bon
iso.
discr
iminat
ion
Ste
m c
arbo
hydr
ates
Pre
senc
e of
awns
Leaf
wax
ines
s
Leaf
-rollin
g
Ear
ly vigou
r
Red
uced
tille
ring
Tra
it (
yie
ld)
va
lue
(%
)
-10
0
10
20
MerredinNarrabriYanco
Trait value for grain yield at each MEF (2010-14)
Trait value is calculated as the percentage change in mean yield of lines selected for the trait
relative to sister lines that lack the trait at each MEF location in one to four years of testing
Trait
Can
opy te
mpe
ratu
re
Car
bon
iso.
discr
iminat
ion
Ste
m c
arbo
hydr
ates
Pre
senc
e of
awns
Leaf
wax
ines
s
Leaf
-rollin
g
Ear
ly vigou
r
Red
uced
tille
ring
Tra
it (
yie
ld)
va
lue
(%
)
-10
0
10
20
MerredinNarrabriYanco
Dynamic phenotyping
Pt = G×Et (×M) with t: time
Time constant
Seconds Hours Days Season
Canopy
Temperature Canopy
Height
Crop
Yield
Phenomics from the pot to the paddock
Thermal Lidar /Colour 3-D Chlorophyll fluoresence Hyperspectral High spatial or temporal resolution
Real-time / hourly continuous measurements of canopy temperature using ArduCrop
Wireless Sensor Network (US$300 per sensor)
Above (well above) the canopy measuring canopy temperature/leaf area
FLIR SC645 thermal camera
Calibrated < 0.05 deg C sensitivity,
2% accuracy, 640x480 pixels, 0.7 kg
Linking phenotypes to traits and genetic architecture: Canopy
temperature and water use
“Old way” h2<0.1 “New way” h2>0.6
Using in irrigated trials for photosynthetic screens, and drought trials for water use
Canopy temperature
$21 m
Depth (cm)
25
45
65
85
115
145
Network of soil and leaf sensors
Knowledge on the go
(Severini, Wasson, Rich)
Early vigour (leaf area) and water use efficiency
Soil
evaporation
rapid early growth slow early growth
Soil
evaporation Plant
transpiration
Plant
transpiration
Genetic complexity - an example with early vigour - Partitioning of water use
Fertility
treatment
LAI
(lai.days)
Yield
(t/ha)
Water use
(mm)
Evaporation
(mm)
Transpiration
(mm)
High
63N, 20P 3.1 5.6 366 173 193
Low
8N, 10P 1.4 2.8 363 259 104
(David Hall, DAFWA)
Esperance 2001, 380 mm in-crop rainfall
Traits for Greater Early Vigour
Embryo size
Leaf lamina thickness
Seedling vigour
High vigour
New physiological types Current cultivars
Low vigour
Global Survey for Early Vigour
Entry Mean leaf width
(mm)
Leaf area
(cm2)
Jing Hong
(China)
6.3 14.3
Kharchia
(India)
6.2 14.2
V743/Oligo
(Israel)
5.9 / 6.3 11.1 / 14.6
Glenlea/Roblin
(Canada)
5.7 / 5.8 12.0 / 12.2
CC-CIMMYT
(Mexico)
5.6 13.9
Janz
(Australia)
4.5 7.4
Where available, pedigrees indicate coancestry among lines is low
Trait
value
0
Cycle of Selection 1 2 3 4
Recurrent selection for genetic gain (accumulating
favourable additive genetic effects)
Existing
value
Target
value
Genetic covariances and variances Cov (a,e) = 2ae2
A + 2ä+ë2D + (2äe+2aë) D1 + äë D2
Var (S0 families) = 2A + 2
D
Var (S0:1 families) = 2A + 0.25 2
D + 1 D1 + 0.125 D2
Var (S1:2 families) = 1.5 2A + 0.125 2
D + 2.5 D1 + 0.563 D2
Var (S families) = 2 2A + 0 2
D + 4 D1 + D2
Where 2
A are 2D are the additive and dominance genetic variances, D1 is the
covariance of an additive effect of an allele with its dominance deviation and D2 is the variance of homozygous dominance effects
Genotypic variation and covariation for early vigour
Parameter h2
ra_LFA RSG_LFA
(%)
Mean leaf
width
0.84 ± 0.11** 0.57 ± 0.10** 92
Mean leaf
length
0.67 ± 0.16**
0.43 ± 0.09**
64
Number of
leaves
0.39 ± 0.11**
-0.37 ± 0.16**
-10
+ Based on F2:4 - F2:6 parent-offspring covariance
Me
an le
af w
idth
(m
m)
5
6
7
8
9
10
Cycle
C0
CParental C
1C
3 C4
C5
C6C
2
Relationship between cycle number and mean leaf width measured in four
environments: Sow 1 (○), Sow 2 (●), Sow 3 (■), and the reduced N Sow 4 (▲)
(Zhang et al. 2015a)
Em
bry
o w
idth
(m
m)
1.60
1.65
1.70
1.75
1.80
1.85
1.90
1.95
Recurrent selection
Commercial wheats
Cycle
C0
CParental C
1C
3C
4C
5C
6C2
y = 1.59 + 0.05 x (r2 = 0.96)
Correlated changes with selection for increased vigour –
Sp
ecific
le
af a
rea
(cm
2/g
)
340
360
380
400
420
440
460
Recurrent selection
Commercial wheats
Cycle
C0
CParental C
1C
3 C4
C5
C6C
2
y = 354 + 12.2 x (r2 = 0.90)
Tim
e to
se
ed
ling
em
erg
ence
(oC
d)
200
205
210
215
220
225
Recurrent selection
Commercial wheats
Cycle
C0
CParental C
1C
3C
4C
5C
6C2
Ra
te o
f le
af e
long
atio
n (
mm
/da
y)
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
Recurrent selection
Commercial wheats
Cycle
C0
CParental C
1C
3 C4
C5
C6C
2
(Zhang et al. 2015b)
Higher vigour germplasm with greater leaf area.
Developed originally to improve WUE and weed competitiveness
Commercial
variety
Early vigour
selection
Advanced vigour
selection
….above ground differences – also reflected below ground!
Higher vigour germplasm with greater leaf area
Developed originally to improve WUE and weed competitiveness
Greater root biomass and root length of advanced vigour selections
Genotypes
Janz
Westo
nia
Wya
lkatch
em
Vigor18
50-437-6
38-19
92-11
Ro
ot
bio
ma
ss (
g/p
lan
t)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Commercial cultivars
vigor18
Recurrent selections
Genotypes
Janz
Westo
nia
Wya
lkatch
em
Vigor18
50-437-6
38-19
92-11
Root
length
(m
/pla
nt)
0
10
20
30
40
50
60
70
Commercial cultivars
vigor18
Recurrent selections
Commercial
cultivar Advanced vigour
selection
Advanced vigour
selections
50 – 90% greater
root biomass
30 – 60% greater
root length
Increased nutrient uptake/use-efficiency of root vigour selections results in greater biomass
Shoot biomass (g)
0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
N u
pta
ke
(m
g)
10
20
30
40
50
60
70
80
Leaf area (cm2)
50 100 150 200 250 300
N u
pta
ke
(m
g)
10
20
30
40
50
60
70
80
(Jairo Palta unpub. data)
Advanced root vigour lines show greater P
uptake under P-limited conditions:
➙ 20% greater PAE (P acquisition efficiency)
Commercial
cultivars
Advanced
vigour
selections
Early vigour
selections
Phosphorus Nitrogen
➙ 10 - 40 % shoot growth advantage
Advanced root vigour selections
EGA Burke
Xioayan 54 .Vig#1
Vig#2Vig#3
Vig#4
Gro
wth
in P
-lim
itin
g c
ond
itio
ns (
5P
,%100
P)
0
20
40
60
80
Increased early vigour increases weed competitiveness
0
5000
10000
15000
20000
25000
30000
35000
Gladius Scout WCD2-320605 WCD2-390403 WCD2-470201 Wyalkatchem
We
ed
Se
ed
s p
rod
uce
d/m
2
400 Plants/m2
200 Plants/m2
- Vigour + Vigour Vigour selections
Vig 1 Vig 2 Vig 3
Phenomobile Lite
LiDAR • Canopy height
• Fractional ground cover
• Biomass index (subject to
validation)
• Greenness vertical distribution
GreenSeeker • NDVI (canopy density and
greenness)
High-res RGB • Plant counts
• Visual assessments
Preliminary validation of LiDAR: canopy biomass (wheat)
Trait h2
Biomass (field) 0.72
NDVI 0.64
LiDAR Index 0.88
Sampling date 9/9/2014
The massive and complex wheat genome
Wheat
Human
Arabidopsis
Rice
Cotton
Barley
Huge
Polyploid
Repetitive
Genetic resolution
Bi-parental 4-way MAGIC 8-way MAGIC
2 cM 6 cM 9 cM
M3
M4
M1
M2
M3
M4
M1
M2 M2
M1
M3
M4
1807 bins 817 bins
Alternative dwarfing genes allow selection of reduced
height, long coleoptile progeny
Janz
HM14aS
134mm
81mm
1 2 3 4 5 6 7
Genetic dissection of coleoptile length† Integration of multi-population, multi-environment mapping
A B D
Group
(C/H = Cranbrook/Halberd, MAGIC = Baxter/Chara/Westonia/Yitpi)
Cranbrook/Halberd MAGIC (4-way)
† QTL common at two or soil temperatures
1 2 3 4 5 6 7
Genetic dissection of coleoptile length† Integration of multi-population, multi-environment mapping
A B D
Group
(C/H = Cranbrook/Halberd, MAGIC = Baxter/Chara/Westonia/Yitpi)
Cranbrook/Halberd MAGIC (4-way)
† QTL common at two or soil temperatures
Yitpi +13mm Baxter +5mm
Baxter +6mm Westonia +6mm
Chara +7mm
Yitpi +6mm
Westonia +7mm
1 2 3 4 5 6 7
Genetic dissection of early growth† Integration of multi-population, multi-environment mapping
A B D
Group
(4-way MAGIC = Baxter/Chara/Westonia/Yitpi)
Kukri/Janz MAGIC (4-way)
† QTL at two air temperatures
Yitpi +23mm Chara
+11mm Westonia
+15mm
Chara
+17mm
Chara
+13mm
Yitpi
+16mm
Yitpi
+15mm
Yitpi
+11mm
Westonia
+13mm Chara
+8mm
Character
Coleoptile
length
12°C
Coleoptile
length
20°C
Shoot
length
12°C
Shoot
length
20°C
Coleoptile length 12°C - 0.986 0.849 0.947
Coleoptile length 20°C 0.084 - 0.772 0.899
Shoot length 12°C 0.069 0.138 - 0.973
Shoot length 20°C 0.017 0.054 0.095 -
Genetic correlations (shaded) and residual correlations (lower diagonal) for coleoptile and shoot lengths measured at two soil temperatures on progeny in the MAGIC four-way population
Leaf and coleoptile genetic effects are strongly correlated
Coleoptile length allelic effect (mm)
-15 -10 -5 0 5 10 15
Sho
ot le
ng
th a
llelic
effe
ct (m
m)
-60
-40
-20
0
20
40
60
Baxter
Chara
Westonia
Yitpi+Rht-B1a
+Rht-B1a
+Rht-D1a+Rht-D1a
+Rht-D1b
+Rht-D1b
+Rht-B1b
+Rht-B1b
How do we overcome the constraint on seedling growth with the green revolution dwarfing genes?
240
260
280
300
320
0 1 2 3 4
Number of GA-insensitive Rht alleles
Cell
len
gth
(µ
m)
Tall Doubled-
dwarf
(Keyes et al. 1989)
(r2 = 0.99)
Trait x trait: Dwarfing gene (Rht) effects on coleoptile length
-5
-4
-3
-2
-1
0
1
Effect
on c
ole
optile
length
(cm
)
Rh
t4
Rh
t5
Rh
t7
Rh
t8
Rh
t9
Rh
t12
Rh
t13
Rh
t14
Rh
t1
Rh
t2
Rh
t17
GA-responsive
GA-insensitive
ns
ns
ns
***
ns
*
ns
ns
ns
*** ***
Tall Rht
Rh
t18
ns
Critical need to better link whole crop physiology for delivery to commercial breeding programs:
1. Are traits relevant for the challenge being addressed?
2. How do we prioritise one trait over another (trait value - Managed Environments?)
3. Are there cheap, reliable, population-friendly high-throughput phenotyping methods?
4. Can phenotype be replaced with breeder-useful, linked markers in selection?
5. Can we deliver adapted germplasm containing key traits for crossing and validation?
6. In moving from traits singly, are there crop-gene models capable of assessing trait x trait
combinations?
In summary -
Carbon isotope discrimination C
arb
on
iso
top
e d
iscrim
ina
tio
n (
%)
16
17
18
19
20
21
22
23
Drysdale - 19.71Mace - 20.84Yitpi - 20.07
Narrabri Yanco Merredin
Drysdale - 18.31Mace - 18.91Yitpi - 18.43
Drysdale - 19.29Mace - 21.02Yitpi - 20.18
110 mm
20 kg/ha/mm
French & Shultz (1984)
0
1
2
3
4
5
0 100 200 300 400 500
Water use (mm)
Gra
in y
ield
(t/
ha
)But first……
110 mm
20 kg/ha/mm
French & Shultz (1984)
0
1
2
3
4
5
0 100 200 300 400 500
Water use (mm)
Gra
in y
ield
(t/
ha
)
Genotype response is specific to each MEF (no two sites in any
given year are the same!)
-0.3 -0.2 -0.1 0.0 0.1 0.2 0.3
-0.3
-0.2
-0.1
0.0
0.1
0.2
2010
Comp.1
Com
p.2
5447P
6184N
6184P
6266N
6460N
6460P
6768N
6768P
7276N
7276PF
7566N
7566PUNI
7750N
7750PF
B+B++
Cranbroo
K-K+
MagSilB7
MagSil-W
MSS13
QG11
QG24
QG49
QG53
QG56
QG58
QG6
QG62
QG76
QG8
QH10
QH12
QH13
QH15
QH19
QH22
QH25
QH32
QH35
QH5
QH6
QS1
QS14
QS29
QS41
QS42
QS44
QS45
QS6
QS8
SB002
SB012
SB017
SB021
SB023
SB025
SB026
SB028
SB033
SB035
SB037
SB049
SB051
SB053
SB057
SB064
SB070
SB071SB073
SB091
SB095
SB101
SB118
SB127
SB130
SB134
SB138
SB139
SB157
SB162
SB163
SB165
SB171
SB175
SB177
SB178
SB179
SB183
SB189
SB190
SB193
STin16
STin46
Sundor
Syn549
Syn604
wj111
wj113wj115
wj119
wj145wj171
wj22
wj23wj25
wj30
wj44
wj84
wj87
Y01_1
Y01_10
Y01_11
Y01_2
Y01_3
Y01_4
Y01_5
Y01_6
Y01_7
Y01_8
Y01_9
-15 -10 -5 0 5 10 15
-10
-50
510
M10Ir
M10Rf
N10IrN10Rf
Y10IrY10Rf
-0.3 -0.2 -0.1 0.0 0.1 0.2 0.3
-0.1
0.0
0.1
0.2
0.3
2012
Comp.1
Com
p.2
13-4-4NT
13-4-5NT
14-4-4NT
14-4NT
16-6-3NT
16-6-4NT
20-1-2NT
20-1-5NT
22-2-3NT
22-2-4NT
23-5-5-N 23-5-7NT
2-4-3NT
2-4-5NT
27-1-3NT
27-1-5NT
3-1-8NT
34-1-6NT
4-3-6NT
4-4-1NT
4-4-6NT
5-3-4NT
5-3-8NT 5447N
5447P
6072N
6072P
6266N
6266P
6460N
6460P
6581N
7164N
7276PF
7566N
7566PUNI
9-5-3NT
9-5-6NT
AUS33681
Axe
B-
B+
B++
Drysdale
FA1-
FA1+
FA3-
FA3+
FA8-
FA8+
Hartog
JA6-
JA6+
Janz
JB1+
Mace
QG24
QG30
QG49
QG54
QG56
QG58
QG62
QG76
QG8
QH12
QH13
QH19
QH22
QH25
QH32
QH5
QH7
QS1
QS29
QS41
QS45
QS8
RAC875
SB002
SB017
SB025
SB026SB027
SB035
SB037
SB049
SB051 SB053SB071
SB091
SB095
SB101SB118
SB127
SB134
SB162
SB163
SB165SB171
SB178
SB179
SB189
SB2+
SB6+
Scout
STin46
Sundor
Suntop
Syn549
Syn604
W11B
W15A
W16A
W19A
W1A
W2A
W3A
W4A
W6A
W7A
WA1-WA1+
Weebill1
Westonia
wj111
wj113
wj115
wj119wj171
wj22
wj25
wj30
wj44
wj84
Wyalkatc
Yitpi
-20 -10 0 10 20
-10
-50
510
15
20
M12Ir
M12Rf
N12IrN12Rf
Y12Ir
Y12Rf