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Measuring maize (Zea mays L.) cultivar  coefficients for modeling water-limited potential yield and yield gaps in Wami-Ruvu River basin, Tanzania
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Measuring maize (Zea mays L.) cultivar coefficients for modeling water-limited potential yield and yield gaps in Wami-Ruvu River basin, Tanzania

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Presentation made by Mourice,* S.K., Rweyemamu, C.L., Tumbo, S.D. and Amur, N. at the Biennial Conference 2012

Presentation made by Mourice,* S.K., Rweyemamu, C.L., Tumbo, S.D. and Amur, N. at the Biennial Conference 2012

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  • 1. Measuring maize (Zea mays L.)cultivar coefficients formodeling water-limited potentialyield and yield gaps in Wami-RuvuRiver basin, TanzaniaMourice,* S.K., Rweyemamu, C.L., Tumbo, S.D. andAmur, N.;Sokoine University of Agriculture, Tanzaniasixbert.mourice@gmail.com 1
  • 2. Scope Introduction Materials and methods Results Conclusion 2
  • 3. Introduction Maize production - Tanzania Tanzania major cereals Sorghum 5 13% 4.5 Production (Tons) (Million) 4 Rice 3.5 25% 3 Maize 2.5 62% 2 1.5 1 0.5 0 (MAFSC 2010) 1999 1990 1991 1992 1993 1994 1995 1996 1997 1998 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009Maize is No. 1 among major Year cereals FAOSTAT, 2011 3
  • 4. Intro … Maize yield – Tanzania Yield Wami-Ruvu Basin 2000 5 1800 4.5 1600 4 1400 YIELD (KG/HA)Yield (T/Ha) 3.5 1200 3 1000 2.5 800 2 600 1.5 1 400 0.5 200 0 0 1999 2005 1997 1998 2004 2000 2002 2003 2001 2002 2003 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2004 2005 2006 2007 2008 2009 YEAR Year FAOSTAT, 2011 MAFSC, 2011 4
  • 5. Intro…Tanzania has embarked on agricultural intensificationSeveral regions have been designated as ‘National granaries’How far the max yield resulting from intensification is not known (potential yield) 5
  • 6. Intro…Currently the yield gap is not knownWhy potential yield and gap thereof?i) to project the future crop yieldsii) knowledge and understanding of the biophysical constraints to maximum yield 6
  • 7. Intro…Determining the crop yield potential expensiveDynamic crop models  best optionCrop models – need accurate estimation of the parametersCrop cultivars are the most important 7
  • 8. Objectivesi) to evaluate crop phasic development of four adapted maize varietiesii)to determine the maize cultivar coefficients of four adapted maize 8
  • 9. Materials and MethodsAn experiment with three reps was conducted at SUAFour maize varieties(Pioneer, Situka, Staha and TMV1)Spacing (75x30 cm), 1 plant/hillNitrogen supply- 80 kg/ha (recommended)Plant sampling was done as per Ogoshi et al. (1999) 9
  • 10. Data collection and analysisPhenology, Leaf area, Shoot biomass and YieldCultivar coefficients (Jones and Kiniry, 1986)Anova and repeated measure analysis (Genstat v. 14) 10
  • 11. Results 1. Phasic development Number of days from emergenceVARIETY Emergence End of 50% physiol juvenile tasseling maturityPIONEER 7 16 46 98STAHA 6 17 54 103TMV1 6 16 50 100SITUKA 5 14 44 96LSD 1.78 1.3 2.64 1.73 11
  • 12. Results … 2. Biomass PIO NEER 350 SI TUKA STAHA TMV1 300 average s.e.d. 250 200 150 100 50 30 40 50 60 70 Days af ter emergence 12
  • 13. Results… 3. Leaf area 4.0 3.5 PIONEER SITUKA STAHA TMV1 approx. l.s.d. (5%) 3.0 2.5 30 40 50 60 70 Days after emergence 13
  • 14. Results… 4. Grain yield (15% Moisture Content) 8 0 00 7 0 00 6 0 00 5 0 00 4 0 00 3 0 00 2 0 00 1 0 00 0 PION SITUKA STAHA T V1 M Variety 14
  • 15. Results… 5. Maize cultivar coefficients Cultivar coefficient Cultivar P1 P2 P5 G2 G3 Pioneer 213 - 831 567 6.9 Staha 220 - 891 564 3.6 TMV1 213 - 888 535 12.1 Situka 201 - 843 437 9.7 LSD 9.75 9.82 9.08 1.02 15
  • 16. FindingsThe length of life cycle is related to the final yieldMeasured coefficients are within the range with those for other cultivarsThe coefficients can be used to calibrate and validate Crop system models for simulating potential yield 16
  • 17. THANKS FOR LISTENING 17