Irrigation of Soybean [Glycine max (L.) Merril] in a semi-arid - - PowerPoint PPT Presentation

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Irrigation of Soybean [Glycine max (L.) Merril] in a semi-arid - - PowerPoint PPT Presentation

Effect of Continuous Deficit Irrigation of Soybean [Glycine max (L.) Merril] in a semi-arid environment of Argentina Salvador Prieto Angueira 1,2 , Daniel R. Prieto Garra1 y Gabriel A. Angella 1,2 1 INTA EEA Santiago del Estero. 2 National


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Effect of Continuous Deficit Irrigation of Soybean [Glycine max (L.) Merril] in a semi-arid environment of Argentina

Salvador Prieto Angueira1,2, Daniel R. Prieto Garra1 y Gabriel A. Angella1,2

1INTA EEA Santiago del Estero. 2 National University of Santiago

del Estero, Faculty of Agronomy and Agribusiness

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SLIDE 2

Background and justification

What is happening in the world? Water scarcity and more population

www.ceres.org www.ceres.org

Less available water and more food demand

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SLIDE 3

What is happening in the world? Water scarcity and more population World Climate Change

www.ceres.org

Less available water and more food demand

I- Increase of temperature Could increase the vapor water demand of the atmosphere II- Increase in extreme events, for example: DROUGHT

We must generate or evaluate strategies to increase "water productivity”

Allen et al. 2006 y 2007

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Irrigation strategies like continuous deficit irrigation (CDI) would achieves this challenge In SOYBEAN, the major economical crop in Argentina, results are contradictories and we don´t have antecedents in Argentina

Objective

Evaluate the effect of different strategies of CDI during the cycle of soybean

Irrigation scheme in which the plants are exposed to a certain level

  • f water stress throughout the growing season without causing

significant decreases in performance.

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SLIDE 5

Experimental site

Material and Methods

Experimental Station “Francisco Cantos”

  • Latitud: 28° 01' 27" S
  • Longitud: 64° 13' 55" W
  • Altitud: 169 msnm
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SLIDE 6

Month Precipitation (mm)

50 100 150 200 J A S O N D J F M A M J

Month Water balance (mm)

  • 300
  • 200
  • 100

100 200 300 J A S O N D J F M A M J

Month Temperature (°C)

10 20 30 40

Tmax Tmin

J A S O N D J F M A M J

Site characteristics

Climate: Semi-arid monsoon type

Month

Reference evapotranspiration (mm)

50 100 150 200 J A S O N D J F M A M J

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SLIDE 7

Soil: Aridic haplustoll with no drainage problem. Texture is silty loam throughout the profile. Total available water is 180 mm.m-1 in the first 3 meters profile.

Water regimenes (WR)

Irrigation depth (mm) = ETc – Pef. = (ETo×kc)-Pef Irrigation intervals: 10 to 15 days.

100% ETc 75% ETc 50% ETc 25% ETc Rainfed

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SLIDE 8

Crop Management

Variety: DM 8002 (MG VIII – GH determinate) Optimal sowing date (SD1) 12/22/2011 Late sowing date (SD2) 25/01/2012

Month Water balance (mm)

  • 300
  • 200
  • 100

100 200 300 J A S O N D J F M A M J

SD1 SD2

Month

Reference evapotranspiration (mm)

50 100 150 200 J A S O N D J F M A M J

SD1 SD2

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SLIDE 9

Field Measurements

  • Crop phenology
  • Yields and its components (number and grain weight)
  • Actual evapotranspiration (ETa) using soil water balance

method ETa (mm) = ∆S+Peff where: ∆S is the change of soil water storage considering a depth of 2 meters (gravimetric procedure), and Peff is the effective precipitation (Dardanelli et al., 1992)

  • Water productivity as the ratio Y and ETa (WPETa)
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20 40 60 80 100 120 140 01/25/2012 12/22/2011 SD2 SD1 Days after sowing

Results and discussion

Crop development and weather conditions

S-R1 R1-R5 R1-R5 R5-R7 R7-R8

SD2 cycle duration decrees 20% Weather condition during SD2 PVD 8% less Radiation 10% less ETo 8% less

1 2 3 4 5 6 SD1 SD2

VPD (kPa) / Eto (mm.día-1)

VPD ETo

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SLIDE 11

100 200 300 400 500 600 Precipitation Irrigation ETa (mm)

Actual evapotranspiration and yield

Sowing date a b

F F

SD1 SD2

Source p-value SD <0.0001 WR <0.0001 SD*WR ns

SD Yield (kg.ha-1) GN.m-2 GW (mg) SD1 3093 (91) a 1959 (56) a 158 (1) SD2 2473 (130) b 1569 (81) b 157 (1) SD <0.0001 <0.0001 ns WR 0,002 0,0027 ns SD*WR ns ns ns

The yield decreased with the retarding on the sowing date as a consequence of a reduction in the grain number

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SLIDE 12

100 200 300 400 500 600 700 T100% T75% T50% T25% T0% mm 100 200 300 400 500 600 700 T100% T75% T50% T25% T0% mm 100 200 300 400 500 600 700 T100% T75% T50% T25% T0% mm 100 200 300 400 500 600 700 T100% T75% T50% T25% T0% mm

Water regimenes

Source p-value SD <0.0001 WR <0.0001 SD*WR ns

SD1

(Eff. precipitation 228 mm)

a b c c c SD2

(Eff. precipitation 149mm)

a b c c c

Actual evapotranspiration and yield

The treatments T100 and T75% were the most ETr, being higher in T100%

Irrigation depth ETa Irrigation depth ETa 73% 47% 28% 9% 100% 73% 45% 24% 0% 100%

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SLIDE 13

50 100 150 200 T100% T75% T50% T25% T0% 50 100 150 200 T100% T75% T50% T25% T0% Soil water consumed (mm)

Soil water use

Water regimenes Although water consumption in T75% and T50% was higher compared to T100%, the differences were only statistically significant in T25% and T0% c c b c a c c b c a

Source p-value SD ns WR <0.0001 SD*WR ns

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SLIDE 14

1000 2000 3000 4000 T100% T75% T50% T25% T0% Yield (kg.ha-1)

Yield an components

SD1 SD2 Yield did not decrease in the treatments CDI 75% and T50% in relation with T100% Water regimenes

SD Yield (kg.ha-1) GN.m-2 GW (mg) SD <0.0001 <0.0001 ns WR 0,002 0,0027 ns SD*WR ns ns ns SD Yield (kg.ha-1) SD <0.0001 WR 0,002 SD*WR ns

1000 2000 3000 4000 T100% T75% T50% T25% T0%

a ab bc abc c a ab bc abc c

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2 4 6 8 SD1 SD2 WPETa (kg.mm-1)

Water productivity

Sowing date a b Only difference was found in water productivity between planting dates, being higher in the FS2. This could be associated with lower average vapor pressure deficit (VPD) during the second sowing date

SD WPETa (kg.mm-1) SD 0,0014 WR 0,0912 SD*WR ns

2 4 6 8 T100% T75% T50% T25% T0% WPETa (kg.mm-1)

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Yield production function

y = -0,01x2 + 16,1x - 1407 R² = 0,88; p<0,05

500 1000 1500 2000 2500 3000 3500 4000 200 400 600 800

Yield (kg.ha-1) Actual evapotranspiration (mm)

) ) m mm l (m

T100% T75% T50% T25% T0%

y = -0,05x2 + 32,6x - 2375 R² = 0,89; p<0,05

500 1000 1500 2000 2500 3000 3500 4000 100 200 300 400

Yield (kg.ha-1) Normalized ETa (mm.kPa-1)

) ) m mm l (m

T100% T75% T50% T25% T0%

y = -0,29x2 + 81,3x - 2356 R² = 0,89; p<0,05

500 1000 1500 2000 2500 3000 3500 4000 50 100 150 200

Yield (kg.ha-1) Normalized ETa (ETa/ETo)

) ) m) mm l (m

T100% T75% T50% T25% T0%

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Conclusions

In soybean and in Santiago del Estero, irrigation water depth could be reduced by 25% without any yield losses. Although we could not show changes in WPETa with the use of CDI, we show that is it possible to increase the WPETA with change in SD.

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Acknowledgements

Water National Program Project:

Evaluation of changes in water productivity against different climate scenarios in various regions of the Southern Cone

¡Many thanks!