Genetic diversity and traits inheritance in finger millet (Eleusine coracana): Implications for germplasm conservation and strategic breeding for multi-stress tolerant variety
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Genetic diversity and traits inheritance in finger millet (Eleusine coracana): Implications for germplasm conservation and strategic breeding for multi-stress tolerant variety

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Presented by D. Lule, K. Tesfaye, M. Fetene, S. de Villiers (Finger Millet Research Sub-Project) at the First Bio-Innovate Regional Scientific Conference, Addis Ababa, Ethiopia, 25-27 February 2013 ...

Presented by D. Lule, K. Tesfaye, M. Fetene, S. de Villiers (Finger Millet Research Sub-Project) at the First Bio-Innovate Regional Scientific Conference, Addis Ababa, Ethiopia, 25-27 February 2013

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Genetic diversity and traits inheritance in finger millet (Eleusine coracana): Implications for germplasm conservation and strategic breeding for multi-stress tolerant variety  Genetic diversity and traits inheritance in finger millet (Eleusine coracana): Implications for germplasm conservation and strategic breeding for multi-stress tolerant variety Presentation Transcript

  • Genetic Diversity and Traits Inheritance in Finger millet (Eleusine coracana): Implications forGermplasm Conservation and Strategic Breeding for Multi-stress Tolerant Variety D. Lule, K. Tesfaye, M. Fetene, S. de Villiers Finger Millet Research Sub-Project First Bio-Innovate Regional Scientific Conference United Nations Conference Centre (UNCC-ECA) Addis Ababa, Ethiopia, 25-27 February 2013
  • I. Introduction Cultivated in the tropical & sub-tropical regions of Africa & India; Widely cultivated in Northern, NW, and Western Ethiopia; It is the 6th most important cereal crop both in area & production; It constitutes 10-20% of total cereal production in some regions; Can produce better yield than other crops under multiple stress & marginal soil; Has high nutritional value & excellent storage qualities; Area coverage in the major regions (2009-11) Area coverage &production (1999-11)
  • Introduction .… Despite is importance as food security crop, its productivity is suffering from both biotic & abiotic stresses => needs intervention to improve its productivity; Improvement in any crop usually involves;  Exploiting the genetic variability in specific traits;  Nature & degree of association between traits;  Inheritance & genetic transmissibility; Limited/insufficient data base for finger millet; Therefore, the current study was initiated to supplement such pressing needs
  • II. Objectives Set-I  To assess the extent & pattern of genetic diversity of finger millet germplasms on the basis of phenotypic traits;  To estimate the genetic parameters; heritability & genetic advance for quantitative traits.
  • III. Materials & Methods No. Country/Region Total 1 Amhara 33 Morphological characterization of finger 2 Oromia 33 millet genotypes was conducted at:- 3 Tigray 27  Arsi Negele in the central Rift Valley 4 B/Gumuz 7  Gute in the western Ethiopia 5 SNNP 6 6 Eritrea 8 150 germplasm planted in RCBD with 2 7 Zimbabwe 13 repl. 8 Kenya 7 9 Zambia 10 Sub total 144 6 Qualitative Traits  (growth habit, ear shape, ear (glumes) color, grain coverage Released Varieties 6 by glumes; spikelet density and grain color was collected Grand total 150 following finger millet descriptors (IBPGR, 1985). 14 Quantitative Morphological (days to 50% to TGW)
  • IV. Data AnalysisQualitative traits◘ The percentage freq. distribution of each phenotypic class (using excel computer) program.◘ Hierarchal clustering of standardized data (using MINITAB) software◘ The amount of genetic variation was determined using the Shannon-Weaver diversity index as described by Jain et al. (1975) Quantitative traits Analysis of variance computed using Agrobase software; Cluster analysis Using SAS software; Broad sense heritability (H2) & Genetic advance computed following the standard formula
  • V. Result & DiscussionQualitative traits Relatively higher Shannon diversity for:- ●Growth habit was observed for Eritrea & Ethiopian (Tigray) materials; ● Ear Shape & Grain Color for Kenyan’s; ● Grain covering by glumes & spikelet density for Ethiopian (Oromia & SNNP region); The pooled mean diversity indices for the six traits showed comparatively higher Shannon diversity for Kenyan collection followed Benishangul Gumuz & Oromia region of Ethiopia.
  • Table _Shannon-Weaver diversity indices (H’) of finger millet accessions collected from5 regions of Ethiopia and 4 East & South east African countries for 6 qualitative traits Qualitative characters Country/region GH ESH EC GCG SPD SC Mean ± SE Amhara/Ethiopia 0.426 0.245 0.212 0.239 0.238 0.312 0.279 ± 0.033 B/Gumuz/Ethiopia 0.427 0.253 0.159 0.260 0.338 0.377 0.302 ± 0.040 Oromia/Ethiopia 0.329 0.246 0.255 0.335 0.299 0.296 0.294 ± 0.015 SNNP/Ethiopia 0.391 0.279 0.194 0.236 0.289 0.326 0.286 ± 0.043 Tigray/Ethiopia 0.423 0.277 0.157 0.238 0.288 0.325 0.284 ± 0.033 Eritrea 0.458 0.305 0.055 0.111 0.243 0.243 0.236 ± 0.060 Kenya 0.317 0.345 0.291 0.234 0.330 0.403 0.320 ± 0.024 Zambia 0.325 0.297 0.182 0.284 0.312 0.337 0.289+ 0.240 Zimbabwe 0.302 0.293 0.282 0.264 0.283 0.353 0.287 ± 0.012 Mean 0.377 0.282 0.199 0.244 0.291 0.330 0.287±0.045 GH= growth habit, ESH= ear shape, EC=Ear/glumes color, GCG=Grain covering by glumes, SPD=Spikelet density, SC=seed color
  • Clustering Analysis Based on regional data, 3 clusters groups were formed. ◘ All the five administrative regions of Ethiopia & Eritrea grouped together ◘ Kenya, Zambia and Zimbabwe grouped in the second cluster ◘ All released varieties share minimum percentage similarity & with finger millet accessions of all countries & regions.Fig 2 Similarities for F. millet landraces among regions of Ethiopia, African countries & released varieties evaluated for 6 qualitative traits 40.91 60.60 S ilarity im 80.30 100.00 ) ) ) ) ) 5) 3) 1) 6) 2) th th th ria th th ya bw e bi a (V 4 (E (E (E r it (E (E en m (V (V (V (V (V a y uz E ia P K ba Za da et se e a a ar ra m m NN im re ad es Gut am ney h ig o Z Am T Gu O r S Be P Ta d W Bo B/ Adminstrative regions of Ethiopia (Eth), released varieties (V1-V6) and other countries
  • Quantitative traitsAnalysis of variance for quantitative traits The combined analysis of variance across locations showed significant location effects for all quantitative traits. The genotype mean squares were also significant (P≤0.01) for all quantitative traits except ear weight. Genotype by environment mean square was highly significant (P≤0.01) for most of the traits considered, indicating that the variation among genotypes for grain yield is more of due to genetic factor than environmental.
  • Mean squares for 14 quantitative traits of 144 finger millet landraces and 6 released varieties as obtained from combined ANOVA of the two locations (Gute & Arsi Negele) Source of df DH DM TTN PTN PLHT FL FN variation Location 1 4066.4** 11102.61** 3199.8** 3087.2** 47638.2** 28.12** 36.66** Genotype 149 315.4** 89.26** 12.02** 11.48** 491.75** 15.1** 4.85** GxE 149 51.24 44.13** 8.31** 8.20** 122.75** 2.45** 1.21** Error 298 46.83 13.01 1.10 1.19 35.58 0.94 0.65 CV (%) 7.05 2.29 18.72 19.55 8.68 12.12 11.09 LSD (5%) 7.98 4.21 1.23 1.27 6.95 1.13 0.94 Mean 97.01 157.73 5.61 5.55 68.75 7.98 7.23 S source of variation df EW NGPS CD FW TGW GYPLN LOG Location 1 72.45** 134.6** 2129.8** 13.23** 0.02 28912.1** 228150** Genotype 149 5.32* 1.07** 0.389** 0.08** 0.754** 182.79** 1546.25** GxE 149 1.09** 0.34 0.32 0.05 0.20 111.90 642.79** Error 298 0.74 0.37 0.27 0.05 0.17 53.61 82.50 CV (%) 32.44 12.21 22.01 28.72 18.52 35.85 20.57 LSD (5%) 1.00 0.71 0.61 0.26 0.49 8.54 10.59 Mean 2.65 4.39 2.37 0.79 2.26 20.42 44.15KEY: TTN=Total tiller number, PTN= productive tiller number, FL= finger length, FN= finger number, EW=ear width,NGPS=number of grain per spikelet, CD=culm diameter, EW= finger weight, GYPLN=grain yield per plant, LOG= lodgingindex
  • The result for cluster analysis indicated that neighboring regions, & countries shared strong similarity The genetic relatedness of 144 F. millet landraces for 14 quantitative traits among regions and countries of origin and six released varietiesFig. 2 T he genetic relatedness of 144 F. millet landraces for 17 quantitative traits among regions & countries of origin & 6 released varieties 46.35 64.23 Similarit y 82.12 100.00 ) ) a ) ) ) a e a ) ) ) ) ) ) (E th (E th it r e (Et h ( Et h a ( v eny bw m bi (E th a (v t (v e (v (v (v y Er z ed K ba Za ey de Gut se a r a a u ia r m N P n a es am ha gr um m Be Zi SN Bo P d W Am Ti /G O ro Ta B Regions and count r ies of or igin, and r eleased v ar iet ies ( v )
  • Estimation of the different variances parameters, heritability and genetic advance for 14 major quantitative traits of 144finger millet landraces and 6 released varietiesTraits Mean δ2g δ2p δ2e δ2gl H2 (%) GA GA (%)Days to 50% Heading 97.010 66.040 78.850 46.830 2.205 83.754 15.291 15.762Days to 50% maturity 57.300 11.283 22.315 13.010 15.560 50.560 4.911 3.122Total tiller number 5.610 0.928 3.005 1.103 3.604 30.865 1.100 19.609Productive tiller number 5.550 0.820 2.870 1.187 3.507 28.571 0.995 17.931Plant height (cm) 68.750 92.250 122.938 35.578 43.586 75.038 17.106 24.881Finger Length 7.980 3.163 3.775 0.942 0.754 83.775 3.347 41.937Finger number per ear 7.230 0.910 1.213 0.647 0.282 75.052 1.699 23.501Ear Weight (g) 2.650 1.058 1.330 0.737 0.177 79.511 1.885 71.143Number of grain per spike 4.390 0.170 0.268 0.371 0.010 63.551 0.676 15.394Culm diameter(cm) 2.370 0.018 0.098 0.273 0.024 17.949 0.115 4.862Finger width (cm) 0.790 0.006 0.020 0.051 0.003 30.000 0.087 11.042Thousand grain weight (g) 2.260 0.138 0.188 0.176 0.012 73.333 0.653 28.888Grain yield per plant(g) 20.420 17.673 45.648 53.600 34.150 38.715 5.378 26.336Lodging percentage 44.150 225.863 386.563 82.500 280.150 58.428 23.619 53.497 Key: δ2g= genotypic variation, δ2p=phenotypic variation, δ2e=environmental variance, δ2gl= genotype by location variance, H2= heritability in broader sense, GA=genetic
  • VI. Screening finger millet genotypes for blastdiseaseObjective-Set-II  To screen blast tolerant genotypes for further utilization in breeding program & yield trials.
  • No Region/countryVII. Materials and Methods 1 Sub total Oromia 65  Treatment No. 225 (including 150 from 2 Amhara 53 Set-I experiment) 3 Tigray 46 4 B/Gumuz  Design: Simple Lattice 15 5 SNNP 7  Experimental Location: Bako ARC 6 Eritrea 3  Checks: Eight improved varieties 7 Kenya 5 8 Zambia 9 Pathogen source:- Artificial inoculation by 9 Zimbabwe 14 developing the inoculums collected from Sub total 217 susceptible genotypes & developed in lab. Released Varieties 8 Grand total 225 Susceptible genotype was planted as spreader row.
  • VIII. Data Collection & Analysis 10 plants were randomly selected/row for data colle; Blast severity (1-9), Incidence (%), Lesion length (cm), along with other yield parameters were recorded; Disease assessment was be made every 2 weeks; Severity score for Leaf, Sheath & Head blast recorded from 10-selected plants were converted to disease index/severity index following standard formula later to calculate the Area Under Disease Progress Curve (AUDPC) of the subsequent recording period.
  • VII. Result and Discussion Analysis of variance Mean squares due to genotypes were highly significant (P≤0.01) for ◊ Leaf blast AUDPC & head blast AUDPC; ◊ Neck blast incidence & lesion length; ◊ Grain yield per plant;
  • Result and discussion ……. Mean squares for blast incidence and severity recorded at different assessment period from different plant parts and grain yield per plant. Leaf blast incidence -days after planting (DAP) Head blast incidence- (DAP)Source of dfvariation 88 102 117 132 147 102 117 132 147BLOCK 1 4795.5** 23995.** 5760.2** 24053.5** 364.5** 624.22 22022.01** 893.24 338.0**Genotype 224 277.71** 881.32** 637.46* 440.38** 67.36** 2897.1** 1480.49** 1059.1* 58.93Error 224 159.143 434.52 291.14 174.6 24.1 1009.04 624.66 792.5 48.71CV (%) 29.03 25.59 24.81 16.83 5.15 38.56 31.61 33.11 7.07LSD (0.05) 19.71 33.44 26.01 21.19 8 52.34 38.31 41.16 11.48R-squ(%) 74.97 76.4 78.9 81.34 79.3 78 81 65 62.5Mean 13.22 56.88 63.91 76.86 93.92 45.31 73.33 89.77 98.33RE (%) 111.9 106.1 115.8 106.1 102.8 100.6 116.3 101.6 100.9
  • Result and discussion ……. Table Cont…….S Source of df SHBDI NBINC LBAUDP HBAUDP LL GYPLNV VariationBLOCK 1 180.3 2572.8** 4653690.3** 4656458.0** 7.45* 73.38*Genotype 224 62.28 800.30** 455942.7** 455947.7** 4.19** 47.26**Error 224 57.79 561.46 119260.4 119246.6 1.54 11.86CV (%) 19.27 25.7 9.39 10.23 21.09 30.12LSD(0.05) 9.46 55.35 509.21 585.8 2.90 5.68R-square 0.79 0.59 0.874 0.799 0.731 0.83Mean 29.54 92.19 3280.1 3506.30 5.89 11.29RE 138.4 100 125.6 102 100 100.5 KEY: SHBDI= sheath blast disease index, NBINC= neck blast incidence, LBAUDP=leaf blast disease progress, HBAUDP= head blast disease progress, LL=Lesion length, GYPLN=grain yield per plant.
  • Result and discussion …….The trends of infection and disease epidemiology Wider ranges of variations were observed among finger millet accessions for leaf blast, sheath blast, neck blast and head blast infection level. Maximum range of variation for head and leaf blast incidence were observed among genotypes at 117 &132 days after planting. The variation among accession gets narrower at later recording period implying that the infection level reaches climax.
  • Result and discussion ……. As head blast is the major factor in causing yield loss, the accessions under the study were ranked based on head blast AUDPC value and hence ranges from:-  975%-days for Acc.BKFM0031 collected from western Ethiopia to  4500%-days for 7 finger millet accessions collected from Northern Ethiopia. Among the top 20 tolerant accessions for leaf & head blast, 16 of them gave grain yield above average (11.29 g/plant). Acc. BKFM0031 is the most tolerant landrace with the least head blast AUDPC value (975%-days), but gave lower grain yield per plant (6.78g/plot). This urges the need to further confirmation for the consistence of its resistance & utilize as a parental line in crossing program.
  • Table List of the top 20 and last 20 finger millet populations ranked based on head blast resistance(HBAUDP) with their respective mean grain yield, leaf blast, neck blast and sheath blast values. HBAUDP Acc Country/Region LBAUDPC HB AUDPC SHBDI NBINC GYPPL rank 1 BKFM 0031 Ethiopia/Oromia 2721.06 975.00 34.72 60.00 6.78 2 214988 Zambia 2976.79 1425.00 32.63 50.00 11.32 3 214987 Zambia 2481.48 1597.50 22.22 70.00 13.90 4 BKFM0010 Ethiopia/B/Gumuz 2322.69 1815.00 23.46 80.00 16.48 5 203356 Zimbabwe 3067.59 1897.50 23.46 70.00 15.31 6 BKFM0020 Ethiopia/Oromia 2307.64 1901.25 25.93 70.00 16.11 7 BKFM0029 Ethiopia/Oromia 3068.98 1912.50 27.78 70.00 9.19 8 214995 Zambia 2795.37 1912.50 24.07 50.00 14.74 9 214997 Zambia 3275.23 1935.00 25.31 70.00 15.85 10 216035 Ethiopia/Oromia 2404.63 1987.50 22.84 80.00 18.02 11 BKFM0024 Ethiopia/Oromia 2656.48 2137.50 24.69 90.00 12.25 12 BKFM0018 Ethiopia/Oromia 2368.06 2141.25 24.69 60.00 16.02 13 BKFM0063 Ethiopia/Oromia 3025.46 2227.50 28.40 100.00 23.05 14 216051 Ethiopia/Oromia 2276.85 2250.00 24.69 70.00 13.32 15 BKFM0042 Ethiopia/Oromia 3579.63 2287.50 29.01 100.00 17.05 16 BKFM0023 Ethiopia/Oromia 2155.09 2340.00 26.54 60.00 13.77 17 BKFM0001 Ethiopia/B/Gumuz 2275.93 2437.50 20.37 20.00 10.26 18 216039 Ethiopia/Oromia 2062.04 2445.00 17.90 100.00 11.83 19 BKFM0007 Ethiopia/B/Gumuz 3204.17 2475.00 38.27 90.00 11.82 20 BKFM0009 Ethiopia/B/Gumuz 3099.54 2475.00 25.31 80.00 18.11
  • Table . … contHBAUDP Acc Country/Region LBAUDPC HB SHBDI NBINC GYPPLrank AUDPC206 100002 Ethiopia/Amhara 3305.56 4350.00 29.63 100.00 4.66207 203357 Zimbabwe 3923.61 4350.00 40.74 100.00 15.92208 242114 Ethiopia/Amhara 3224.07 4350.00 27.78 100.00 10.66209 AAUFM-21 Ethiopia/Tigray 3113.89 4387.50 25.93 100.00 11.89210 237475 Ethiopia/Tigray 3697.69 4387.50 33.95 100.00 9.77211 242115 Ethiopia/Amhara 3429.63 4387.50 30.25 100.00 13.20212 238299 Ethiopia/Tigray 4210.65 4425.00 54.94 100.00 9.05213 AAUFM-15 Ethiopia/Tigray 3668.29 4425.00 33.33 100.00 7.93214 AAUFM-2 Ethiopia/Tigray 3692.13 4425.00 27.16 100.00 8.08215 AAUFM-32 Ethiopia/Tigray 3819.91 4425.00 33.95 100.00 12.17216 230105 Eritrea 3501.85 4462.50 27.78 100.00 4.35217 AAUFM-22 Ethiopia/Tigray 4162.50 4462.50 31.48 100.00 6.79218 230104 Eritrea 3844.44 4462.50 26.54 100.00 6.30219 AAUFM-35 Ethiopia/Tigray 3318.52 4500.00 30.25 100.00 16.86220 AAUFM-23 Ethiopia/Tigray 3229.17 4500.00 32.10 100.00 7.73221 AAUFM-44 Ethiopia/Tigray 3906.48 4500.00 31.48 100.00 5.58222 228202 Ethiopia/Amhara 3924.54 4500.00 37.04 100.00 6.46223 238460 Ethiopia/Tigray 3697.22 4500.00 28.40 100.00 4.08224 238308 Ethiopia/Tigray 3748.15 4500.00 35.19 100.00 13.08225 242618 Ethiopia/Tigray 3898.15 4500.00 33.95 100.00 4.12
  • Infection pattern with respect to regions/countries of originFig 1. Patterns of leaf blast severity index of 217 finger milletaccessions pooled for regions of origin recorded during the differentassessment periodsLeaf blast infection was relatively linear for different countries and regions of origin
  • Fig. Patterns of head blast severity index recorded from 217 finger milletaccessions pooled for regions of origin recorded during the different assessmentperiods• Finger millet accessionsfrom W & SW parts ofEthiopia, and someintroduced from Zambiashowed relatively bettertolerance to leaf blast andhead blast during thewhole growing periods.• Infections were high foraccessions sampled fromKenya, Eritrea and twoEthiopian regions (Tigrayand SNNP).
  • VI. Summary and Future Plan Higher phenotypic and yield related trait variability observed among finger millet germplasms studied, which worth to apply conventional and modern biotechnological tools to improve the productivity of finger millet; About 64% of the traits considered in the current study have heritability percentage greater than 50%; Relatively higher heritability followed by higher genetic advance were recorded for Ear Weight, Lodging Index, Finger Length, Thousand Grain Weight & Grain Yield per Plant. This in turn offers high chances for improving this traits of finger millet through selection & hybridization. Finger length (0.33), finger number (0.21), thousand grain weight (0.23) and tiller number (0.28) has positive & significant (P≤ 0.01) correlation with Grain Yield per Plant.
  • Summary and Future Plan…. Clustering goes with geographical proximity  indicate the presence of gene flow/seed flow among the local community;  Selection by farmers in favor of similar traits across location;  Seed from the same sources ;  Adaptive role of the traits in similar agro-ecology. Materials from Western part of Ethiopia should be targeted for in-depth blast screening and conservation. From Set-I and Set-II experiments:-  30 genotypes advanced to next level yields trials and later some 15 genotypes will be advance to multi-location yield trials.  More than 35 blast tolerant lines advanced to the next level.
  • ACKNOWLEDGEMENTS Bio-Innovate Africa Microbial, Cellular & Molecular Biology-AAU Bako Agricultural Research Center Arsi Negele Agricultural Research sub-center Melkassa Agricultural Research Center The Institute of Biodiversity Conservation