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N-fertilizer and straw management effects on grain yield and yield components of rice

grown with AWD irrigation

Olivyn Angeles, To Phuc Tuong, Yasukazu Hosen, Sarah Johnson, Romeo Cabangon, Lizzida Llorca, Reynaldo Rodriguez, and Ruth Agbisit

International Rice Research Institute (IRRI)

*Alternate wetting and drying

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Why AWD?

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• World population is projected to grow from6.1 billion in 2000 to 8.9 billion in 2050, increasing by 47 per cent

• Half of humankind relies on rice for 60-80% of their dietary needs

• The worldwide productive land is estimated to decrease by one hectare every 7.67 secondsNeed to increase and sustain rice productivity

• Growing global water scarcity

Current situation and need

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Grain yield can potentially keep up with the demandPotentially significant water savings

Source: Bouman BAM, Lampayan RM, Tuong TP. 2007

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Transplanting

The rice plant physiological timeline & AWD irrigation management

Target: No significant yield penalty

Soil depth: 15 cm

Soil moisture potential: < -10 kPa

Tools: Tensiometers or Perched tube

panicle

tiller

How is AWD done?

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The experiment

Location: Blocks J9-10, IRRI, Los Banos, Philippines (14.26N,121.16E)

Soil: Clayey loamDesign: Split-split PlotPlot size: 10 x 5 m2

Main-plot: 3 levels of water management1. W0 or continuous flooding (CF)2. W1 or AWD–203. W2 or AWD–70

Sub-plot factor: 6 levels with 3 nitrogen levels and 2 residue levels 1. N0S0 4. N0S12. N1S0 5. N1S13. N2S0 6. N2S1

Sub-plot factor: 2 levels timing of tillage1. Early tillage (45-48 DBT) 2. Late tillage (25-28 DBT)

Where: N0 = Zero N controlN1 = Recommended N rate with fixed splitsN2 = Leaf color chart (LCC)-based N fertilizer S0 = Zero straw controlS1 = Straw incorporated at 4 t dry straw ha-1

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Field experiment at IRRI: 8 crops (4 dry season; 4 wet season)

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W0=CF W1=AWD-20W2=AWD-70

2006 2007 2008 2009W0 W1 W2 W0 W1 W2 W0 W1 W2 W0 W1 W2

Seasonal irrigation water input

CF – 1084.14 mm

AWD-20 – 832.89 mm

AWD-70 – 733.87 mmAWD-20: 23.18% water saving

Dry season rain water input

> Average: 278 mm> Range: 79 – 630 mm

Dry season water savings

AWD-70: 32.31% water saving

▼ ▼▼

Results

RF = rainfallIrW = irrigation water

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2006 2007 2008 2009W0 W1 W2 W0 W1 W2 W0 W1 W2 W0 W1 W2

W0=CF W1=AWD-20W2=AWD-70

Wet season water savingsSeasonal irrigation water input

CF – 719.84 mm

AWD-20 – 497.02 mm

AWD-70 – 394.54 mm

Dry season rain water input

> Average: 797 mm> Range: 507- 1026 mm

30.95% water savings45.19% water savings

▼▼ ▼▼▼▼

RF = rainfallIrW = irrigation water

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Experimental factors

1. Water management

2. N-fertilizer management

3. Straw management

4. Tillage timing

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Dry season:

- GY+ PAN- SpPAN- 1000-grain weight- Sp m-2

+ %GF- Total dry matter+ HI

Wet season:

+ GY+ PAN- SpPAN+ 1000-grain weight+ Sp m-2

+ %GF- Total dry matter+ HI

Water management effectGrain yield

3

4

5

6

7

DS WS

t ha-1

a

bab

aaa

Grain yield (t ha-1) Number of panicles

120

125

130

135

140

145

150

155

160

165

DS WS

a

abb

aaa

Number of panicles (pan m-2) Number of spikelets per panicle

50

60

70

80

90

100

110

DS WS

bb

a

baba

Number of spikelet per panicle (spikelet pan-2)

% Grain filling

50

55

60

65

70

75

80

85

DS WS

aaaaaa

Grain filling (%)

1000-grain weight (g)

18.0

18.5

19.0

19.5

20.0

20.5

21.0

21.5

22.0

DS WS

b

aba aaa

1000-grain weight (g)

Number (x1000) of spikelets per square meter

10

15

20

25

30

35

DS WS

baba

aaa

Number of spikelet per sqm(x 1000 spikelet m-2)

Total dry matter

5

6

7

8

9

10

DS WS

t ha-1

a

b

ab

a

bab

Harvest index

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

DS WS

a b abaaa

Total dry matter (t ha-1) Harvest Index

(CF = ; AWD-20 = ; AWD-70 = )

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Dry season:

+ GY+ PAN+ SpPAN+ 1000-grain weight+ Sp m-2

- %GF+ Total dry matter- HI

N fertilizer effect

Wet season:

+ GY+ PAN+ SpPAN+ 1000-grain weight+ Sp m-2

- %GF+ Total dry matter- HI

Grain yield

0

1

2

3

4

5

6

7

DS WS

t ha-1

a

a

b

b

ca

Grain yield (t ha-1) Number of panicles

020406080

100120140160180200

DS WS

aa

aa

bb

Number of panicles (pan m-2) Number of spikelets per panicle

0

20

40

60

80

100

120

DS WS

aab

aab

Number of spikelet per panicle (spikelet pan-2)

% Grain filling

68

70

72

74

76

78

80

82

84

DS WS

b

b

a

c

b

a

Grain filling (%)

1000-grain weight (g)

20.220.320.420.520.620.720.820.921.021.121.221.3

DS WS

aa

b

a

a

a

1000-grain weight (g)

Number (x1000) of spikelets per square meter

0

5

10

15

20

25

30

35

40

DS WS

aa

b

aa

b

Number of spikelet per sqm(x1000 spikelet m-2)

Total dry matter

0

2

4

6

8

10

12

DS WS

t ha-1

aa

bc

ba

Total dry matter (t ha-1) Harvest index

0.45

0.46

0.47

0.48

0.49

0.50

0.51

0.52

0.53

DS WS

bb

a

b

aa

Harvest Index

(0N = ; NRec ,recommended N management = ; NLCC = )

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Dry season:

+ GY+ PAN+ SpPAN+ 1000-grain weight+ Sp m-2

+ %GF+ Total dry matter+ HI

Wet season:

+ GY+ PAN+ SpPAN+ 1000-grain weight+ Sp m-2

- %GF+ Total dry matter+ HI

Straw effectGrain yield

0

1

2

3

4

5

6

DS WS

t ha-1

a a

ab

Grain yield (t ha-1) Number of panicles

125

130

135

140

145

150

155

160

DS WS

aa

aa

Number of panicles (pan m-2) Number of spikelets per panicle

90

92

94

96

98

100

102

DS WS

a

ba

a

Number of spikelet per panicle (spikelet pan-2)

% Grain filling

72

73

74

75

76

77

78

79

80

81

DS WS

b

a

aa

Grain filling (%)

1000-grain weight (g)

20.6

20.7

20.8

20.9

21.0

21.1

21.2

DS WS

a

a

a

a

1000-grain weight (g)

Number (x1000) of spikelets per square meter

24

25

26

27

28

29

30

31

DS WS

b

b

a

a

Number of spikelet per sqm(x1000 spikelet m-2)

Total dry matter

7

7.5

8

8.5

9

9.5

DS WS

t ha-1

aa

a

b

Total dry matter (t ha-1) Harvest index

0.46

0.47

0.48

0.49

0.50

0.51

0.52

0.53

DS WS

aa

aa

Harvest Index

(No straw = ; With straw (4 t DW ha-1) = )

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Dry season grain yield

0

1

2

3

4

5

6

7

8

Water management

t ha-1 0 N Rec_N LCC

Continuously flooded AWD-20 AWD-70

c

bbab

bab

a

cc

▼

Wet season grain yield

0

1

2

3

4

5

6

7

8

Water management

t ha-1

0 N Rec_N LCC

Continuously flooded AWD-20 AWD-70

b

aaa aaa

bb

Combined effect of water and N-management on GY

DSMean grain yield (t/ha)0 N - 3.78 Rec_N - 6.27 LCC - 5.92

WSMean grain yield (t/ha)0 N - 3.39 Rec_N - 4.45 LCC – 4.30

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Conclusion

1. Based on 8-season (4-years) continuous AWD cultivation data, AWD does not significantly affect GY in WS but can significantly affect GY in DS depending on the soil water potential threshold used.

a. In both DS and WS, shifting from traditional continuously flooded irrigated rice to AWD down to -20 kPa does not significantly reduce GY.

b. Depending on the DS weather, AWD down to -70 may lead to yield penalty.

2. AWD-20 can save 23-32% irrigation water per season while AWD-70 can save 30-45%

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3. AWD can maximize use of rainfall, increase productivity of irrigation water input, and offer opportunities to conserve water resource for future use.

4. The timing of tillage (45-48 DBT or 25-28 DBT) does not affect GY.

5. GY with straw incorporation was generally higher than without straw.

6. Recommended N (fixed dose and timing of application) and LCC-base N management are both achievable and effective in increasing grain yields with AWD.

7. Apparently, no tillage, straw, and N-management change is necessary when shifting from continuously flooded to AWD irrigation management.

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I R R I

Thank youA collaborative project by the International Rice Research Institute (IRRI)Japan International Research Center for Agricultural Sciences (JIRCAS) and Japan Ministry of Agriculture, Forestry and Fisheries (MAFF)

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FarmersPerched tube (Tensiometer)

Researchers

15cm depth

How do we know the time to irrigate (~ -10 kPa at 15 cm)?

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▼▼▼

Grain yield from year-to-year

DSMean grain yield (t/ha)CF - 5.887 aAWD-20 - 5.436 ab(8% difference)AWD-70 - 5.067 b(13% difference)

WSMean grain yield (t/ha)CF - 4.24 aAWD-20 - 3.96 a(6% difference)AWD-70 - 3.94 a (7% difference)

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DS: Water (IrW + RF) productivity

DSMean irrigation water productivity (Liters per kg grain)N0 - 2437 aRec_N - 1379 bLCC_N – 1455 b

DSMean total water (irrigation + rain water)input productivity (Liters per kg grain)N0 – 3149 aRec_N – 1818 bLCC_N – 1916 b

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WS: Water (IrW + RF) productivity

WSMean irrigation water productivity (Liters per kg grain)N0 - 1599 aRec_N - 1278 bLCC_N – 1270 b

WSMean total water (irrigation + rain water)input productivity (Liters per kg grain)N0 – 4105 aRec_N - 3155 bLCC_N – 3229 b

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Leaf color chart (LCC)

1. Randomly select at least 10 disease-free rice plants or hills in a field with uniform plant population.

2. Select the topmost fully expanded leaf from each hill or plant. Place the middle part of the leaf on a chart and compare the leaf color with the color panels of the LCC. Do not detach or destroy the leaf.

3. Measure the leaf color under the shade because direct sunlight affects leaf color readings. If possible, the same person should take LCC readings at the same time of the day every time.

4. Determine the average LCC reading for the selected leaves.

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Schematic presentation of a flooded soil showing the zones withdifferent microbial metabolism (Reddy KR et al., 1986)

NH4-N > NO3-NLess N2O; Less NO3 leaching

N-fertilizer

Eh = +180 mV

Eh = -150 mV

Approach

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Source: Increasing adoption of AWD (Lampayan et al., 2004; Li et al., 2003)

PI to completeflowering

grain filling

MaturityLate tillering

Earlytillering

Transprecovery

Field water depth (mm)

0

10

20

30

40

50

60

-20

-10

0 10 20 30 40 50 60 70 80 90 100 110

CF

AWD

soil surface

Days after transplanting

Concept of AWD

oangeles_Sept2010Source: Dobermann, A. and Fairhurst T., 2000

N-transformations in irrigated rice soils

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Methane (CH4) formation in flooded rice soils

Source: riceweb.org

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Rice environments

Rainfed upland

- Drought-prone

- Favorable

Irrigated lowland Rainfed lowland

- Drought prone

- Submer-gence prone

Upland

- Shiftingagriculture

- Permanentcultivation

Flood prone

deficit WATER surplus

50% (79 M ha) 30% (45 M ha) 11% (17 M ha) 9% (14 M ha)

75% (450 M t) 17% (102 M t) 4% (24 M t) 4% (24 M t)

1-3 tha-1 1-3 tha-11-3 tha-13-5 tha-1

Data source: Maclean, 2002; Dobermann et al., 2004

It was estimated that by 2025, 15–20 million ha of irrigated rice will suffer from some degree of water scarcity (Tuong and Bouman, 2003)

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World population (2007)

Source: http://en.wikipedia.org/wiki/File:World_population_(UN).svg

Worldwide population2007 (UN): 6.67 Billion

Projected increase from 2000 to 2050:0.77%

Implications:- Higher food demand- Higher land conversion from

agricultural to industrial / residential

- Higher domestic and industrial water use

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Asian rice area and yield (1990-2007)

Source: http://beta.irri.org/

Worldwide2007 (FAO): 156.7 M ha

Decrease:1 ha per 7.67 sec

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Growing global water scarcity

The water stress indicator measures the proportion of water withdrawal with respect to total renewable resources.

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References

Bouman BAM, Lampayan RM, Tuong TP. 2007. Water management inirrigated rice: coping with water scarcity. Los Baños (Philippines): International Rice Research Institute. 54 p.

Dobermann, A. and Fairhurst T., 2000. Rice : Nutrient disorders and nutrient management. Singapore: Potash & Phosphate Institute; Laguna, Philippines: IRRI.

FAOSTAT Database, 2008. FAO, Rome

United Nations, Department of Economic and Social Affairs, Population Division, 2007. World Population Prospects: The 2006 Revision, vol. I, Comprehensive Tables (United Nations publication, Sales No. E.07.XIII.2)

Maclean JL, Dawe D, Hardy B, Hettel GP, editors. 2002. Rice almanac. Los Baños(Philippines): International Rice Research Institute. 253 pp.

Neue, H. 1993. Methane emission from rice fields: Wetland rice fields may make a major contribution to global warming. BioScience 43 (7): 466-73.

Tuong TP, Bouman BAM. 2003. Rice production in water scarce environments. In: Kijne JW, Barker R, Molden D, editors. Water productivity in agriculture: limits and opportunities for improvement. Wallingford (UK): CABI Publishing. p 53-67.

Wassmann Reiner, Yasukazu Hosen, and Kay Sumfleth, 2009. Reducing Methane Emissions from Irrigated Rice. International Food Policy Research Institute, Focus 16: Brief 3, May 2009

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*1: Fixed time, fixed split (165 kg N ha-1 in DS/ 120 kg N ha-1 in WS)*2: Fixed time N fertilizer management based on leaf color chart (LCC

Sub-subplot factor2: 2 levels as timing of tillage (T1, T2)1. Early tillage (T1)2. Late tillage (T2)

Urea application rate in DS / WS (kg N ha-1)N treatment Basal Max Tillering

(44 – 49 DAS)PI

(59 – 63 DAS)Heading

(69 – 77 DAS)

N0 0 0 0 0

N1*1 30 45 / 30 45 / 30 45 / 30

N2*2 30

60 / 40 (LCC < 3)45 / 30 (3 < LCC

< 4)23 / 15 (4 < LCC)

60 / 40 (LCC < 3)45 / 30 (3 < LCC <

4)23 / 15 (4 < LCC)

23 / 15 (LCC < 3)0 / 0 (3 < LCC)