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FACULTY OF AGRICULTURE & ENVIRONMENT Improving water use efficiency of wheat: A case study from Australia Dr. Babar Manzoor Atta Senior Scientist, NIAB,

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Presentation on theme: "FACULTY OF AGRICULTURE & ENVIRONMENT Improving water use efficiency of wheat: A case study from Australia Dr. Babar Manzoor Atta Senior Scientist, NIAB,"— Presentation transcript:

1 FACULTY OF AGRICULTURE & ENVIRONMENT Improving water use efficiency of wheat: A case study from Australia Dr. Babar Manzoor Atta Senior Scientist, NIAB, Faisalabad International Seminar on Climate Change Adaptation Strategies to Ensure Food Security University of Agriculture, Faisalabad January 16-17, 2014

2 The significance of this work  Drought  WUE wheat varieties 2

3 Materials and methods COMPONENT 1: FIELD STUDIES Location: Plant Breeding Institute (PBI), Narrabri, NSW. Plant material:2009 = 15 2010 = 20 2011 = 20 Soil moisture treatments: i.High moisture ii.Low moisture/rainfed No irrigation applied in 2010 (wet season) Experimental Design: Alpha-lattice designs with three replications Procedure:  Aluminum neutron probe access tubes fixed after sowing  Moisture was assessed fortnightly with NMM 3

4 Parameters Water use › Soil water content › Water use (at anthesis; maturity) › WUE (DM Anthesis, DM maturity, grain) Whole plant parameters › Days to heading › Days to maturity › Plant height › Biomass at anthesis › Biomass at maturity › Number of tillers › Grain yield per m 2 › Harvest Index › Grain yield › Drought Susceptibility Index (DSI) › Normalized difference vegetation index (NDVI) › Canopy cover (Digital imaging) › Chlorophyll content ›Canopy temperature depression (CTD) › Carbon isotope discrimination (∆) Flag leaf traits › Leaf area › Leaf length › Leaf width › Leaf weight › Specific leaf weight › Specific leaf area Spike parameters › Awn length › Spike length › Spikelet density › Number of spikelets per spike › Number of grains per spike › Single spike weight › Grain weight per spike Materials and methods 4

5 › Number of kernels per spikelet › 1000 grain weight Root traits › Root length (0-15 cm) › Root length (15-30 cm) › Root length (30-60cm) › Total root length (0-60 cm) › Root average diameter (0-15 cm) › Root average diameter (15-30 cm) › Root average diameter (30-60 cm) › Total root average diameter (0-60 cm) › Root length density (0-15 cm) › Root length density (15-30 cm) › Root length density (30-60 cm) › Root length density (0-60 cm) Statistical analysis › GenStat 14 th edition Materials and methods The Fischer and Maurer (1978) drought susceptibility index (DSI) of each genotype for the stress treatment was calculated as: DSI = (1-Ys/Yi)/(1-Xs/Xi) Where Ys = yield under stress treatment; Yi = yield without stress; Xs and Xi = average yield over all genotypes under stress and non-stress treatments, respectively. 5

6 COMPONENT 2: GENOME-WIDE ASSOCIATION ANALYSIS › Yield › Stripe rust › Leaf rust › Crown rot Software: › R version 2.13.1 (R Core Team 2012) http://www.R-project.org/ Materials and methods 6

7 Sr. No. Genotype Year of release 1MILAN/KAUZ/5/CNDO/R143//ENTE/MEXI_2/3/AEGILOPS SQUARROSA (TAUS)/4/ - 2CROC_1/AE.SQUARROSA (224)//OPATA/3/PASTOR - 3CROC_1/AE.SQUARROSA (224)//2*OPATA/3/2*RAC655 - 4CETA/AE.SQUARROSA (327)//2*JANZ - 5QT6581/4/PASTOR//SITE/MO/3/CHEN/AEGILOPS SQUARROSA (TAUS)//BCN - 6D67.2/P66.270//AE.SQUARROSA (320)/3/CUNNINGHAM - 7Janz 1989 8Giles 1999 9Cunningham 1990 10Sokoll - 11Crusader 2008 12LPB05-2271 - 13LPB05-1164 (Scout) 2010 14LPB05-1157 (Envoy) 2011 15LPB05-2148 (Spitfire) 2011 16 Lang 2000 17 Sunco 1986 18 Carinya 2008 19 Sunvale 1993 20 Ventura 2004 7

8 8

9 Comparison of rainfall during 2009-2011 9

10 DateDASSource of variation/d.fGrowth stage GenotypeDepthGenotype.Depth 14342 31.07.2009 57 0.00335 ns 0.56391***0.00051 ns 10.08.2009 67 0.00662*0.45508***0.00090 ns 25.08.2009 82 0.00487**0.62889***0.00044 ns Booting/heading 09.09.2009 97 0.00533**0.31814***0.00052 ns Anthesis 16.09.2009 104 0.00506***0.51194***0.00036 ns Milk 24.09.2009 112 0.00688**0.3298***0.00033 ns Milk 01.10.2009 119 0.00591***0.54091***0.00030 ns Dough 08.10.2009 126 0.00569***0.56165***0.00030 ns Dough 13.10.2009 131 0.00488**0.51864***0.00032 ns Ripening 03.11.2009 152 0.00565***0.37087***0.00036 ns Maturity ANOVA for genotype and depth for ten dates in high moisture environment during 2009 Results 10

11 SOVdf Water use Anthesis (mm) Water use Maturity (mm) WUE DM Maturity kg ha -1 mm -1 WUE Grain kg ha -1 mm -1 Genotype14 117.34 ns 291.4*8.351*6.807** LSD (P<0.05)-19.43.32.3 1268.3 bcd31.55 cde13.82 de 2287.9 a32.72 bcde14.4 cd 3283.4 ab32.33 bcde15.89 abcd 4263.6 cd35.03 ab16.57 abc 5276.9 abc32.62 bcde14.5 bcd 6273.6 abcd36.07 a18.04 a 7274.2 abc32.01 bcde16.35 abc 8276.3 abc34.06 abc16.81 ab 9260.7 cd30.04 e13.85 de 10273 abcd31.36 cde14.54 bcd 11254.6 d33.77 abcd16.27 abc 12261.5 cd31.78 bcde14.59 bcd 13270.6 abcd33.61 abcd15.75 abcd 14283.3 ab30.57 de12.05 e 15258.5 cd34.2 abc14.61 bcd Mean square and means for WU and WUE in high moisture environment during 2009 11

12 Relationship of WUE DM and WUE Grain with grain yield in high moisture environment during 2009. 12

13 Relationship of WUE DM with WUE Grain (High moisture environment, 2009) 13

14 Relationship of WUE Grain with grain yield (Low moisture environment, 2009) Rainfed trial 14

15 SOVdf Water use Anthesis (mm) WUE DM- Anthesis (kg ha -1 mm -1 ) Water use Maturity (mm) WUE DM -Maturity (kg ha -1 mm -1 ) WUE Grain (kg ha -1 mm -1 ) Genotype19 18.35***15.98**135.22***6.18**2.47*** LSD (P<0.05) 3.364.695.962.961.28 1 275.5 h26.83 ab419.6 fghi24.4 ef9.8 efgh 2 285 abcd31.4 a420.9 fgh29.03 a11.59 abc 3 287.4 ab23.62 bcde438.1 ab26.23 abcdef8.73 hi 4 280.3 g25.83 bc419.1 ghij28.29 ab11.61 abc 5 288 a27.79 ab413.4 j28.69 a12.15 a 6 285.4 abcd24.56 bcde423.4 efg27.19 abcde11.78 ab 7 285.3 abcd23.76 bcde434.1 bc27.99 abc9.59 fgh 8 288 a24.23 bcde437.4 ab26.19 abcdef10.62 bcdef 9 280.9 fg20.7 de430.8 cd24.63 def9.91 efgh 10 284.9 abcd27.34 ab417.3 hij28.17 abc11.2 abcd 11 282.1 defg25.38 bcd423.5 efg25.72 bcdef10.97 abcde 12 282.7 cdefg25.3 bcd430.3 cd23.94 f10.73 bcdef 13 281.4 efg27.73 ab414.1 ij28.33 ab10.41 cdef 14 280.5 fg27.69 ab420.7 fgh27.23 abcde10.04 defg 15 284.5 bcde24.45 bcde425.2 def25.38 bcdef9.04 ghi 16 283.8 cdef23.44 bcde441.2 a25.21 cdef9.63 fgh 17 283.9 cdef21.23 cde423.9 efg24.08 f10.6 bcdef 18 281.4 efg21.97 cde428.6 cde27.58 abcd10.91 abcde 19 282.3 cdefg20 e437 ab23.52 f7.96 i 20 285.5 abc27.21 ab423.7 efg27.42 abcd9.03 ghi Mean square and means for WU and WUE in environment 1, 2010 15

16 Relationship of WUE Grain with grain yield during 2010 Environment 1 Environment 2 16

17 Source of variationd.f.BootingAnthesisMilkDoughMaturity Environment50.41720***0.21378***0.26041***0.10701***0.31634*** Residual50.001330.001720.001670.002040.00276 Genotype140.00166 ns 0.00239**0.00310***0.00250**0.0028** Environment.Genotype700.00152 ns 0.00188***0.00166***0.00180**0.00176* Residual840.001170.000890.000810.000960.00106 Depth30.82121***0.67628***0.96540***0.85151***0.82940*** Environment.Depth150.05087***0.03782***0.04950***0.03651***0.02084*** Genotype.Depth420.00027 ns 0.00040*0.00037*0.00034*0.00036** Environment.Genotype.Depth2100.00026*0.00036***0.00032**0.00033**0.00036*** Residual2700.000190.000280.000230.000220.00020 Total719 cv (%)3.74.5 4.64.2 Combined analysis of soil moisture for individual growth stage of 15 genotypes, 2009-2011. 2009-2011 17

18 Genotype Stress grain yield Non-stress grain yield Mean % Reduction DSI 1309636963396160.75 2325941403700210.98 3317845073842291.35 4384143674104120.55 539074008395830.12 6345349554204301.39 7309244643778311.41 8284146413741391.78 9263736283133271.25 10276939543361301.38 1138584138399870.31 1235523830369170.33 13317742613719251.17 14286734143140160.74 15278937753282261.20 Mean322141193670221.00 Genotype mean performance under high and low moisture environments and their drought susceptibility index (DSI), 2009. 18

19 Relationship between biomass and grain yield, 2009-2011 19

20 Relationship between NDVI and grain yield, 2009-2011 20

21 Relationship between canopy temperature depression and grain yield, 2009-2011 21

22 Explanatory variablesWUE DM -MaturityWUE Grain Yield 1.NDVI 2.LLLW 3.CTD 4.BIA BIM 5.BIM HI 6.PH TGW 7.HI WUE DM -Maturity 8.NKPS WUE Grain 9.TGW 10.GRY 11.WUE Grain WUE DM -Maturity 12.SL Percent Variance98 Multiple regression analysis using grain yield, WUE DM -Maturity, and WUE Grain as the response (dependent) variables. Results 22

23 Results Genome-wide Association analysis in a commercial wheat breeding program 23

24 S. No.Trial locationsState Number of genotypes 200820092010 1.NarrabriNSW28829982 2.WalgettNSW28829982 3.BiniguyNSW28829982 4.North StarNSW28829982 5.ParkesNSW287-- 6.HorshamVIC28829981 7.Wee WaaNSW-29679 8.QuirindiNSW-29982 9.QueenslandQLD-299- 10.PremerNSW--82 11.Walgett (crown rot)NSW--75 12.McAlisterNSW--81 13.YoungNSW--81 14.Wagga NSW--81 15.MeandarraQLD--81 Number of genotypes in AGT wheat yield trials (2008-2010) and used for association analysis 24

25 Association analysis of yield trait in multi-environments from 2008-2010 Nar08, Narrabri 2008; Wal08, Walgett 2008; Bin08, Biniguy 2008; NSto8, North Star 2008; Par08, Parkes 2008; Hor08, Horsham (Victoria) 2008 Nar09, Narrabri 2009; Wal09, Walgett 2009; Bin09, Biniguy 2009; NSt09, North Star 2009; Wee09, Wee Waa 2009; Qui09, Quirindi 2009; Hor09, Horsham 2009; Qld09, Queensland 2009 Nar10, Narrabri 2010; Wal10, Walgett 2010; Bin10, Biniguy 2010; NSt10, North Star 2010; Wee10, Wee Waa 2010; Qui10, Quirindi 2010; Pre10, Premer 2010; Walcr10, Walgett Crown rot 2010; Mca10, McAlister 2010; You10, Young 2010; Wag10, Wagga Wagga 2010; Hor10, Horsham 2010; Mea10, Meandarra 2010. Year: |----------------2008---------------|------------------------2009-----------------------|----------------------------------------2010-----------------------------------------| Genotype: 288 299 82 >887654321012345678 −log 10 (P) 25

26 Association analysis of stripe rust in multi-environments (2009-2010) S1_09, Narrabri, Score 1; S2_09, Narrabri, Score 2; S3_09, Narrabri, Block I3 (Trial); S4_09, Cobbitty, Score 1; S5_09, Cobbitty, Score 2; S6_09, Roseworthy (SA) S1_10, Narrabri, Block I6 (Trial); S2_10, Narrabri, Block I4, replication 1; S3_10, Narrabri, Block I4, replication 2; S4_10, Narrabri, TOS Block; S5_10, Narrabri, Hydrant 10; S6_10, Cobbitty, Score 1. Year: |-----------------------------------------2009------------------------------------------|-----------------------------------------2010-----------------------------------------| Genotype: 285 77 26

27 Association analysis of leaf rust and crown rot, 2009-2010 Leaf rust: L1_09, Cobbitty score 1; L2_09, Cobbitty score 2; L1_10, Cobbitty score 1; L2_10, Cobbitty score 2; Crown rot: C1_09, Narrabri, Nursery, Score 1; C2_09, Walgett, Crown rot trial score; C3_09, Walgett, Crown rot trial maturity score; C1_10, Narrabri, Nursery, Score 1; C2_10, Narrabri, Nursery, Score 2. Year: |-----------------2009-----------------|-------------------2010--------------|---------------------------2009-------------------------|----------------2010-----------------| Genotype: 285 77 285 77 27

28 ChromosomeSignificant DArT markers 1A4 1B1 1D4 2A10 5A2 5B6 6A19 6D4 7A22 7D22 New marker trait associations identified for grain yield 28

29 Chromosome Significant DArT markers 1D2 3A2 3B13 3D20 4B6 New marker trait associations for stripe rust resistance 29

30 Chromosome Significant DArT markers 3A1 3B4 5A1 New marker trait associations for leaf rust resistance 30

31 Chromosome Significant DArT markers 1B8 2B4 2D30 3A7 3D9 4A8 5B18 6A9 6B10 6D4 7A6 7B15 7D10 New marker trait associations for crown rot resistance 31

32 Future work PBI No.GenotypePositive markers 1Crusader49 10Stampede43 11Sunstate40 45SUN344 E/VPMB3602042 61SUNCO/2*PASTOR//SUN436E47 94SUN434A/SUN436E.116.442 98EGA Bonnie Rock/SUN436F41 99B409C/SUN420A//SUN498E43 100CHARA/B409C//SUN498E47 101RAC892/98ZHB03//RAC89244 137Chara/4*Sun376G46 151RAC1192/Ventura50 196DM5637*B8/H45//SUN498D42 208Ellison/Ventura48 236SUN500B/Carinya41 255Sunstate/Ellison47 273WA-1-21005/2*SUN426B52 283Yr15,24,2*399C.8743 299SUN445C/QT1077643 3002*M5880/SUN366A44 Pyramiding the genomic regions A x B C x D E x F G x H F 1 x F 1 I x J x DH 32

33  Synthetic lines  WUE wheat ideotype: Roots traits o A more efficient root system Agro-physiological traits o Increased early ground cover (NDVI) o Early flowering o High biomass, harvest index, CTD o Greater spike traits (No. of kernels per spikelet, 1000 grain weight) o Higher grain yield  The MTAs identified for the key traits responsible for improved productivity and adaptation could be used to pyramid favorable alleles into modern cultivars. Conclusion 33

34 34

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