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Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains
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Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended Domains

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Presentation by Mr. Zerihun Tadesse (EIAR, Ethiopia) at Wheat for Food Security in Africa conference, Oct 9, 2012, Addis Ababa, Ethiopia.

Presentation by Mr. Zerihun Tadesse (EIAR, Ethiopia) at Wheat for Food Security in Africa conference, Oct 9, 2012, Addis Ababa, Ethiopia.

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  • 1. Exploiting Yield Potential of Ethiopian Commercial Bread Wheat (Triticum aestivum L.) Varieties Outside their Original Recommended DomainsZerihun T., Firdissa E., Fekadu F., Kebede T., Mathewos A., Mohamed A., Mizan T., Muluken B., Yosef G., Alemayehu A., and Birhanu B. WHEAT FOR FOOD SECURITY IN AFRICA CONFERENCE OCTOBER 8 – 12, 2012, ADDIS ABABA, ETHIOPIA
  • 2. Presentation outline Introduction Objectives Materials and Methods Results and Discussion Summary and Conclusions
  • 3. INTRODUCTION Wheat in Ethiopia:  The 2nd largest producer in SSA  Bread & durum wheat are dominant species  Durum & emmer are indigenous and BW is a recent introduction  National average yield reached a 2.0 t/ha from a 0.8 t/ha in 1980s, 4-6 t/ha on research fields
  • 4. Cont... s  Mekele  Sirinka  Adet  D/Birhan Ambo  Holetta   Werer  Debre Zeit Haremaya  Areka  Awassa  Sinana Fig. 1. Active Wheat Research Centers in the Ethiopia Currently 15 research centers are involved in wheat research Since 1974, > 45 BW varieties have been released
  • 5. Cont... Major wheat producing regions of Ethiopia  Highlands & mid-altitudes  Out of 18 major AEZ, it is grown in more than eight AEZ.  The major wheat growing areas include:  South - Hadiya & Kambata  South-Eastern - Arsi & Bale  Central Highlands – Shoa  North & North-Western - Gojam, Gondar, Wello and Tigray  Several secondary areas of wheat production in the country
  • 6. Cont... Major constraint of wheat production in the country;  Traditional production system,  Biotic and abiotic factors,  Inadequate and timely supply of inputs,  Suboptimal use of recommended packages,  Socio-economic limitations (credit and infrastructure),  Lack of varieties for specific growing conditions (drought, waterlogged and irrigation)  Shortage of widely adapted varieties and  Lack of durable resistance of the existing widely adapted varieties (Kubsa)
  • 7. Cont... Objectives  To investigate yield potential of the existing commercial BW varieties outside their recommended domains
  • 8. MATERIALS AND METHODS Experimental sites  30 locations in 2011 main cropping season  Testing sites represent highland, mid-altitude and low land wheat growing zone  Conducted both on station and on farm  These locations have d/t soil types, altitude & mean annual RF Experimental Materials  21 commercial rust resistant BW varieties used (Table 1)
  • 9. Cont... Table 1. List of BW varieties used for the study Year ofNo Variety Maturity (days) Altitude (m) Released Center Release 1 Danda’a 2010 110-145 2000-2600 KARC /EIAR 2 Kakaba 2010 90-120 1500-2200 KARC /EIAR 3 Hawii* 2000 105-125 1800-2200 KARC /EIAR 4 Tusie* 1997 125-130 2000-2500 KARC /EIAR 5 Pavon-76* 1982 120-135 750-2500 KARC /EIAR 6 ET-13A2* 1981 127-149 2200-2900 KARC /EIAR 7 K6295-4A 1980 128-131 1900-2400 KARC /EIAR 8 Shorima 2011 126-130 1800-2400 KARC /EIAR 9 Huluka 2011 133-140 2200-2800 KARC /EIAR10 Digelu* 2005 100-120 2000-2600 KARC /EIAR11 Sofumar* 2000 125-150 2300-2800 SARC/OARI12 Mada-Walabu* 2000 100-125 2300-2800 SARC/OARI13 Tay 2005 104-130 1900-2800 ADARC/ARARI14 Senkegna 2005 105-125 1900-2800 ADARC/ARARI15 Gasay 2007 118-127 1890-2800 ADARC/ARARI16 Menze 2007 154 2800-3100 DBARC/ARARI17 Bolo 2009 157 2580-3100 DBARC/ARARI18 Alidoro 2007 118-180 2200-2900 HARC/EIAR19 Dinknesh 2007 145 2400-3000 SRARC/ARARI20 Tossa 2004 134-143 2400-3000 SRARC/ARARI21 Kulkulu - - - HAROMAYA UNIVERSITY
  • 10. Cont... Experimental design, procedures and statistical analysis  Experimental design was RCBD with 2 replications  Each plot consisted of 6 rows of 2.5 x 1.2 m spacing  Fertilizer and other agronomic practices were applied as per the recommendations of each study area  Data for grain yield was collected from central 4 rows  Statistical analysis;  AMMI (Gauch, 1988) and ASV (Purchase 1997)  Agrobase20 statistical software was used
  • 11. Result and DiscussionsTable 4. Some representative locations mean GY (kg/ha) of 21 BW varieties HROMAYA SIRINKA SINANAENTRY NAME KULUMSA BEKOJI HOLLETA AREKA DHERA ALAMATA UNIVERSITY (GERAGERA) (GORO) 1 Dandaa 4422.5 7280.0 3550.0 5090.0 5250.0 2802.5 2601.5 1886.3 3344.0 2 Kakaba 4505.0 7232.5 3572.0 4502.5 5375.0 3397.5 2765.8 2282.5 3195.8 3 Hawii 4832.5 6332.5 3538.5 4780.0 4500.0 2372.5 1989.0 2047.5 3543.3 4 Tusie 4170.0 6402.5 3537.0 5882.5 6000.0 2900.0 2328.3 1906.3 2795.3 5 Pavon-76 5175.0 5695.0 3449.0 5572.5 5125.0 3675.0 2680.8 1750.0 2156.0 6 ET-13A2 3552.5 5357.5 3464.5 5180.0 5500.0 3802.5 2769.3 1298.8 1278.0 7 K6295-4A 3810.0 5620.0 3441.0 5632.5 4500.0 2807.5 2268.0 1481.3 2042.8 8 Shorima 4830.0 7760.0 3528.5 6192.5 5500.0 2797.5 2873.5 1455.0 3153.5 9 Huluka 4695.0 7475.0 3527.3 6317.5 5875.0 3395.0 2718.8 1437.5 2815.8 10 Digelu 3892.5 7080.0 3717.5 5735.0 5625.0 2222.5 2419.3 1375.0 2645.5 11 Sofumar 3315.0 6180.0 3527.8 4445.0 5000.0 2655.0 2322.0 1987.6 2401.8 Mada- 5070.0 7112.5 3505.0 5387.5 5625.0 2252.5 2623.8 2078.8 2630.3 12 walabu 13 Tay 4670.0 6472.5 3752.0 5457.5 5500.0 3155.0 2502.8 1797.5 2359.3 14 Senkegna 4192.5 6475.0 3550.0 6070.0 5375.0 2455.0 2200.5 1315.0 1665.0 15 Gasay 4457.5 7157.5 3449.5 5562.5 6000.0 2860.0 2643.3 1897.5 2923.5 16 Menze 2962.5 6430.0 3669.0 4730.0 5000.0 2010.0 2172.5 1750.0 2860.0 17 Bolo 3632.5 6712.5 3522.0 5045.0 5875.0 1557.5 2198.0 1451.3 2199.8 18 Alidoro 4345.0 7232.5 3490.0 5147.5 5450.0 1717.5 2297.5 2040.0 2074.0 19 Dinknesh 4970.0 6660.0 3442.0 5205.0 4875.0 2170.0 2860.5 1675.0 2383.8 20 Tossa 5257.5 5845.0 3501.0 4252.5 4750.0 2910.0 2707.8 2341.3 1730.0 21 Kulkulu 4062.5 7037.5 3479.8 5605.0 5375.0 2655.0 3437.0 1736.3 2146.5 GRAND MEAN 4324.8 6645.2 3534.0 5323.5 5336.9 2693.8 2541.9 1761.4 2492.5
  • 12. Cont...Table 1. AMMI analysis of variance for GY of 21 BW varieties tested at 30 locations in 2011 SS Explained (%) SV DF Total Treatment GXE MS Variation Explained E 29 95960294** 87 - R(E) 30 483068.50 0.45 - G 20 1444322.9** 0.90 - GxE 580 406111.8** 7 - IPCA 1 48 975186.4** - 19.87 IPCA 2 46 906490.3** - 17.70 IPCA 3 44 665528.1** - 12.43 IPCA 4 42 541742.3** - 9.66 IPCA 5 40 510653.9** - 8.67 IPCA 6 38 459208.7** - 7.41 IPCA 7 36 311213.1 - 4.76 IPCA Residual 286 160563.5 - 19.50 Residual 600 256045.355 4.78 CV = 16.41% R-Squared = 0.95 LSD ( 5%)= 181.44
  • 13. 30 Danda’a 25 Bolo Hawi 20 Menze Kakaba 15 10 Sofumer Kulkulu 5 GasayIPCA-1 Madawalabu 0 Tossa K6295-4A Digelu -5 Alidoro Senkegna Dinkinesh -10 Shorima Tusie Pavon-76 -15 Tay -20 -25 ET-13A Huluka -30 1,000 2,000 3,000 4,000 5,000 6,000 7,000 MEAN GRAIN YIELD (Kg/ha) Fig 1. AMMI-1 biplot for grain yield of main effects against IPCA-1
  • 14. Cont... Table 2. Mean GY, IPCA scores & ASV of 21 BW varieties tested at 30 locations Mean GYEntry Varieties Rank IPCA-1 IPCA-2 ASV Rank (Kg/ha) 1 Danda’a 3169.56 8 27.53 7.24 31.74 18 2 Kakaba 3258.48 4 17.93 -11.19 23.03 13 3 Hawii 2955.6 15 22.56 -19.37 31.88 19 4 Tusie 3019.19 13 -11.11 -8.47 15.08 8 5 Pavon-76 3216.76 6 -12.91 -22.85 27.06 15 6 ET-13A2 2903.69 18 -24.77 -8.68 29.13 17 7 K6295-4A 2891.73 19 -4.09 -18.49 19.05 10 8 Shorima 3347.98 1 -9.76 6.25 12.61 4 9 Huluka 3239.12 5 -26.9 24.37 38.81 21 10 Digelu 3120.87 9 -4.92 13.81 14.87 7 11 Sofumar 2866.28 21 8.33 -8.52 12.65 5 12 Mada-Walabu 3306.43 2 0.96 -6.63 6.72 1 13 Tay 3201.19 7 -14.9 13.01 21.19 12 14 Senkegna 2867.2 20 -6.78 0.59 7.64 2 15 Gasay 3277.38 3 3.96 15.98 16.58 9 16 Menze 2952.34 16 20.74 1.33 23.32 14 17 Bolo 3067.56 11 23.8 18.09 32.27 20 18 Alidoro 2994.25 14 -5.01 5.75 8.04 3 19 Dinknesh 2944.61 17 -7.56 -10.35 13.39 6 20 Tossa 3057.81 12 -3.49 -19.76 20.15 11 21 Kulkulu 3078.61 10 6.39 27.88 28.79 16
  • 15. Summary and Conclusions Significant G x E interactions showed inconsistency in performance of genotypes across locations Top three best performing varieties for GY across locations were, Shorima, Mada-walabu and Gasay According to stability statistics;  Mada-walabu……….High yielder  Shorima ………...….. High yielder  Senkegna…….…..…..Low yielder  Alidoro ………………Low yielder Some other varieties having high interactions with the environment & they need to recommend in a specific locations are; Danda’a, Huluka, Kakaba, Hawii and Bolo
  • 16. Cont...Some other varieties with high yield were not stable across locations.So, clustering of wheat growing environments across the country isessential for the best use of the existing high yielding BW varieties.This research also a good indicator for the utilization of the existingtechnology in a wider environment for other crops.For further observation of the year effect and to support the results ofthis study, this experiment repeated in 2012 main cropping season.

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