Line by environment interaction, yieldstability and grouping of test locations for    navy bean variety trial in Ethiopia ...
Outlines1. Introduction2. Objectives3. Materials and Methods     Materials     Statistical analysis4. Results Discussion...
Importance of beans in EthiopiaBeans are produced by about 2.5 millions households across Ethiopia
Increased bean production and productivity                                                                         Area   ...
Trend of quantity and revenue of white pea beans exported to international markets                                 between...
Some major impacts of the bean program                        Private sector investment Government investment andFarmer in...
Introduction ---   The major objective of breeding of beans is to    achieve higher and stable yield of the crop   Multi...
Introduction ---   Understand the nature of GEI is important for testing    and selecting superior genotypes   Key conce...
Introduction ---   AMMI model is a recently preferred statistical model    to analyze multi-environment varietal trials e...
2. Objectives The objectives of this study were:,  1. to estimate the components of variance     associated with GE inter...
3. Materials and Methods Experiment was conducted in the main  growing seasons of 2010 to 2011 Locations were:  Melkassa...
3. Materials --- Sixteen navy bean lines including released  two varieties (as checks) were used in this  study RCBD wit...
Table 2. Descriptive information on the name and codes of the 16 cowpea varieties        Line Code Number            Line ...
3. Materials ---Statistical analyses: ANOVA was done for each location  separately Data transformed to fix failures of  ...
Statistical analyses Mean yield data from each environment was  used for most of the stability analysis methods  (by Agro...
Statistical analyses ---   AMMI first fits additive effects for G and E by the    usual additive analysis of variance pro...
Statistical analyses ---   Where    •   is the environment j mean deviation,    •   is the number of singular value decom...
3. Materials ---Statistical analyses: The AMMI Stability Value (ASV) was done as   described by Purchase (1997) Such a m...
4. Results and Discussion Relative performance of genotypes based   on mean grain yield1. Mean yield in the tests ranged ...
Table 3. Mean yield performance (kgha-1) of 16 navy bean lines evaluated at 14 environments for the period         2010-20...
4. Results and ---The combined ANOVA indicated1.   Highly significant differences (P<0.01) for     environments, lines and...
Table 3. AMMI ANOVA of grain yield for 16 navy bean lines atfourteen environments during 2010 – 2011 main crop season     ...
4. Results & Discussion- Stability To identify the most stable genotypes by  AMMI, the mean of the absolute scores was  o...
Table AMMI stability value (ASV) and ranking with the IPCA 1 & 2 scores for the 16 lines evaluated at 14       environment...
4. Results & Discussion- StabilityLin and Binns’s cultivar performance measure (Pi): As a stability statistic the cultiva...
Table Lin & Binns’s (1988a) cultivar performance measure (Pi) for 16 navy bean lines tested at      14 environments, for t...
4. Results & Discussion- StabilityNassar and Hühn, 1987 non-parametric stability analysis This test is based on the ranks...
Table. Mean absolute rank differences (S1) and variance of ranks (S2) for mean yield of 16navy bean lines across environme...
4. Results & Discussion- AMMI biplot    The IPCA 1 and IPCA 2 axes explained 51% and 35% of the     total GEI & both are ...
G8                                                                                          Many lines performed 20      ...
 E1, E2, E3, E6 and E14 high    20                                                                                       ...
4. Results & Discussion- AMMI biplot   Environments spread from the lower yielding    environments in quadrants I and IV ...
E14                                         G9                                                                          E3...
Conclusion   The two high yielding (averaged over environments)    genotypes 13 and 7 could be regarded as a widely    ad...
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Line by environment interaction, yield stability and grouping of test locations for navy bean variety trial in Ethiopia

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Presented by Kassaye Negash and Kidane Tumsa (National Lowland Pulses Research Program at Melkassa Agricultural Research Center-EIAR) at the First Bio-Innovate Regional Scientific Conference, Addis Ababa, Ethiopia, 25-27 February 2013


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  • Line by environment interaction, yield stability and grouping of test locations for navy bean variety trial in Ethiopia

    1. 1. Line by environment interaction, yieldstability and grouping of test locations for navy bean variety trial in Ethiopia Kassaye Negash and Kidane TumsaNational Lowland Pulses Research Program at Melkassa Agricultural Research Center-EIAR First Bio-Innovate Regional Scientific Conference United Nations Conference Centre (UNCC-ECA) Addis Ababa, Ethiopia, 25-27 February 2013
    2. 2. Outlines1. Introduction2. Objectives3. Materials and Methods  Materials  Statistical analysis4. Results Discussion5. Conclusion
    3. 3. Importance of beans in EthiopiaBeans are produced by about 2.5 millions households across Ethiopia
    4. 4. Increased bean production and productivity Area Trend in bean production and area Production Trend bean yield (t/Ha) (tons) 1.6 400,000 300,000 1.487 362,890 1.4 350,000 250,000 1.2 300,000 244,012 183,800 181,600 200,000 1 250,000 0.936Production (t/Ha) 0.8 0.823 200,000 150,000 172,150 0.6 0.615 119,900 150,000 100,000 0.4 111,750 100,000 98,670 50,000 0.2 50,000 0 - - 2002/3 2003/4 2004/5 2009/10 2002/3 2003/4 2004/5 2009/10 Trend in bean production (Qt/Ha) Production (tons) Area Sources : CSA reports
    5. 5. Trend of quantity and revenue of white pea beans exported to international markets between 2005 - 2010Quantity Quantity exported (t)exported Trend in value of bean export (tons) (USD)80000 Revenue 75864 74762 (USD) 68452 6863870000 60834 $50,000,000 $49,046,107 $49,654,51660000 $45,000,000 $44,747,590 $40,000,000 49679 $35,000,000 $36,229,55650000 $30,000,000 $25,000,000 $20,220,95440000 $20,000,000 $15,000,000 $8,146,12530000 $10,000,000 $5,000,000 $020000 2005 2006 2007 200810000 2009 2010 0 2005 2006 2007 2008 2009 2010 Year Sources : CSA reports Rev…
    6. 6. Some major impacts of the bean program Private sector investment Government investment andFarmer investment and and employment creation supportive policiesbenefit Beans listed on ECX – 2004: 2ha Better return to farmers : more than 2010: 30 600 % price increase between 2003 ha and 2011 : USD 120/ton to USD 800
    7. 7. Introduction --- The major objective of breeding of beans is to achieve higher and stable yield of the crop Multi-environment trials are typically used in crop improvement to evaluate materials across a range of sites representing target environments for the crop However, GEI change the relative performance of genotypes across sites
    8. 8. Introduction --- Understand the nature of GEI is important for testing and selecting superior genotypes Key concept in G x E analysis is genotype stability and by definition, genotypes exhibiting a high degree of GEI are unstable across sites and vice versa In this study, AMMI statistical model was used to study the nature of GEI among common bean lines evaluated in nine locations during 2010 to 2011 main crop growing season
    9. 9. Introduction --- AMMI model is a recently preferred statistical model to analyze multi-environment varietal trials effectively and efficiently, where there is a usual occurrence of GEI AMMI is combining ANOVA for additive main effects and uses PCA to partition the multiplicative structure of the interaction The ANOVA model partitions the total sum of squares (SS) into the components: E, G and GEI without further partitioning the interaction component making interpretation difficult in terms of significance of genotypes across different environments;
    10. 10. 2. Objectives The objectives of this study were:, 1. to estimate the components of variance associated with GE interaction and to determine their effects 2. to compare the various statistics to determine the most suitable method for assessing navy bean line’s yield stability in the major bean growing areas of Ethiopia
    11. 11. 3. Materials and Methods Experiment was conducted in the main growing seasons of 2010 to 2011 Locations were: Melkassa, Alemtena, Areka, Haramaya, J imma, Bako, Pawe, Sirinka and Assossa The locations have diverse agro- ecological characteristics as annual rainfall, temperature and altitude
    12. 12. 3. Materials --- Sixteen navy bean lines including released two varieties (as checks) were used in this study RCBD with 3 reps was used at each location Net size of the experimental unit/plot was 6.4 sqm Data were collected on grain yield per plot from which grain yield per hectare was estimated at 14% moisture content
    13. 13. Table 2. Descriptive information on the name and codes of the 16 cowpea varieties Line Code Number Line Name 1 ICA Bunsi x S x B 405/1C-C1-1C-1 2 ICA Bunsi x S x B 405/1C-C1-1C-3 3 ICA Bunsi x S x B 405/1C-C1-1C-13 4 ICA Bunsi x S x B 405/1C-C1-1C-14 5 ICA Bunsi x S x B 405/1C-C1-1C-23 6 ICA Bunsi x S x B 405/1C-C1-1C-30 7 ICA Bunsi x S x B 405/1C-C1-1C-37 8 ICA Bunsi x S x B 405/1C-C1-1C-51 9 ICA Bunsi x S x B 405/1C-C1-1C-58 10 ICA Bunsi x S x B 405/1C-C1-1C-69 11 ICA Bunsi x S x B 405/1C-C1-1C-70 12 ICA Bunsi x S x B 405/1C-C1-1C-80 13 ICA Bunsi x S x B 405/1C-C1-1C-87 14 ICA Bunsi x S x B 405/1C-C1-1C-88 15 Awash - 1 16 Awash melka
    14. 14. 3. Materials ---Statistical analyses: ANOVA was done for each location separately Data transformed to fix failures of assumptions (normality and homogeneity of error variances) Combined ANOVA was done according to the best AMMI model (by GenStat 14th edition)
    15. 15. Statistical analyses Mean yield data from each environment was used for most of the stability analysis methods (by AgrobaseTM 1999 software package) The effect of GEI on the yield is then determined by AMMI analyses (Gauch, 1993; 2007)
    16. 16. Statistical analyses --- AMMI first fits additive effects for G and E by the usual additive analysis of variance procedure, and then fits multiplicative effects for GEI by PCA The AMMI statistical model is given as Where • is the yield of genotype i in environment j for the kth replicate, • is the grand mean, • is the grand mean, is the genotype i mean deviation (genotype mean minus grand mean),
    17. 17. Statistical analyses --- Where • is the environment j mean deviation, • is the number of singular value decomposition (SVD) axes retained in the model, • is the singular value for SVD axis n, • is the genotype i eigenvector value for IPCA axis n, • is the environment j eigenvector value for IPCA axis n, • is GEI residual • is the error term,
    18. 18. 3. Materials ---Statistical analyses: The AMMI Stability Value (ASV) was done as described by Purchase (1997) Such a measure is essential in order to quantify and rank genotypes according to their yield stability,AMMI Stability Value (ASV) =
    19. 19. 4. Results and Discussion Relative performance of genotypes based on mean grain yield1. Mean yield in the tests ranged from 700 - 4278 kg ha-1 • indicating rather divergent conditions for lines, • expected, in view of geographical differences b/n the sites of evaluation2. In terms of mean yield of lines, • Lines 13 and 7 were the most productive, followed by lines 12, 8, 4,5 and 11 • The standard check Awash-1 was the least performing
    20. 20. Table 3. Mean yield performance (kgha-1) of 16 navy bean lines evaluated at 14 environments for the period 2010-2011 Environment Lines Mean MK10 MK11 AT10 AT11 JM10 JM11 PW10 PW11 SK10 SK11 AK11 BK11 AS11 HM11 1 3283 3286 2732 1851 2019 2665 780 1415 1345 1479 1030 1425 2324 3029 2047 2 3106 3360 2430 1930 2357 2961 784 1289 1324 1473 1014 1470 2134 3300 2067 3 2572 3857 2668 1369 2373 3249 700 1211 1232 1221 1086 1500 2343 2859 2017 4 3108 4278 3061 2181 1347 2180 984 1500 1568 1733 1321 1444 2237 3199 2153 5 3280 3528 2249 1790 2387 3220 1043 1649 1545 1896 1291 1234 2115 2865 2149 6 3426 3372 2750 2130 1741 2348 849 1460 1426 1630 1070 1387 2212 3191 2071 7 3152 4100 2346 2714 2323 2874 1106 1355 1638 1904 1298 1657 1853 4134 2318 8 3135 4107 2901 2497 1516 2140 924 1323 1514 1661 1190 1567 2076 3699 2161 9 3197 3405 3005 1806 2108 2744 747 1372 1327 1331 1036 1622 2535 3114 2096 10 2683 4067 2216 1944 2179 2983 873 1218 1386 1606 1171 1343 1826 3324 2059 11 3476 3713 2704 1977 1593 2457 1068 1756 1618 1972 1339 1177 2212 2758 2130 12 3183 3414 2380 1834 2739 3420 931 1469 1445 1630 1171 1522 2263 3212 2187 13 3328 4125 2972 2402 2376 3043 1167 1614 1723 1845 1441 1852 2461 3741 2435 14 2938 3637 2765 1609 2201 2983 769 1349 1319 1371 1098 1492 2386 2935 2061 15 2372 4222 1643 1590 2101 3151 883 1213 1343 1750 1213 899 1425 2820 1902 16 3223 3904 2512 2512 1549 2174 957 1362 1521 1821 1170 1346 1826 3603 2106 Mean 3091 3773 2583 2009 2057 2787 910 1410 1455 1645 1184 1434 2139 3236 2122
    21. 21. 4. Results and ---The combined ANOVA indicated1. Highly significant differences (P<0.01) for environments, lines and GEI2. The IPCA axes were also highly significant (P<0.01)3. Variance components (%) of the SS, ranged from 2% for lines, 76% for environments and 10% for GEI This indicated the overwhelming influence that environments have on the yield performance of navy bean lines G x E variation is five times the variation of lines as main effect
    22. 22. Table 3. AMMI ANOVA of grain yield for 16 navy bean lines atfourteen environments during 2010 – 2011 main crop season Contribution of Source DF Sum of Square Mean Square each component to the total SS (%) Treatment 223 522867290 2344696** 88 Environments 13 460020679 35386206** 76 Reps within Environment 28 12250577 437521** 2 Line/Genotye 15 9379070 625271** 2 Variety x Environment 195 53467541 274193** 10 Interaction PCA 1 50 27507284 1060538** 51 Interaction PCA 2 46 18340060 773422** 35 Residuals 99 7620196 76972ns 14 Pooled error 420 58068413 138258 10 ** and * - stands for 1 and 5% probability levels; ns – non significant
    23. 23. 4. Results & Discussion- Stability To identify the most stable genotypes by AMMI, the mean of the absolute scores was obtained for the first two components, weighted by the percentage of explanation of each component (weighted mean of absolute scores – WMAS) for each genotype Thus, the lower the WMAS value, the lower the contribution of a genotype to the interaction and, consequently, the more stable is the genotype.
    24. 24. Table AMMI stability value (ASV) and ranking with the IPCA 1 & 2 scores for the 16 lines evaluated at 14 environments over two years Line Line name Mean IPCA Score 1 IPCA Score 1 ASV Rank code 13 ICA Bunsi x S x B 405/1C-C1-1C-87 2435 1.9774 0.4549 2.58 1 7 ICA Bunsi x S x B 405/1C-C1-1C-37 2318 6.0611 18.7532 25.06 13 12 ICA Bunsi x S x B 405/1C-C1-1C-80 2187 -18.0517 -2.8073 23.23 10 8 ICA Bunsi x S x B 405/1C-C1-1C-51 2161 21.7655 3.3169 28.00 15 4 ICA Bunsi x S x B 405/1C-C1-1C-14 2153 19.5516 -1.8071 24.97 12 5 ICA Bunsi x S x B 405/1C-C1-1C-23 2149 -12.9145 0.0620 16.42 4 11 ICA Bunsi x S x B 405/1C-C1-1C-70 2130 8.9726 -6.8554 14.36 3 16 Awash melka 2106 19.4211 8.5139 26.97 14 9 ICA Bunsi x S x B 405/1C-C1-1C-58 2096 -1.8671 -17.5661 22.46 9 6 ICA Bunsi x S x B 405/1C-C1-1C-30 2071 10.2217 -10.1807 18.35 7 2 ICA Bunsi x S x B 405/1C-C1-1C-3 2067 -7.6255 -3.3137 10.57 2 14 ICA Bunsi x S x B 405/1C-C1-1C-88 2061 -9.1268 -9.8879 17.11 6 10 ICA Bunsi x S x B 405/1C-C1-1C-69 2058 -5.7894 14.0161 19.28 8 1 ICA Bunsi x S x B 405/1C-C1-1C-1 2047 -0.6274 -13.4028 17.06 5 3 ICA Bunsi x S x B 405/1C-C1-1C-13 2017 -17.7259 -5.2340 23.50 11 15 Awash - 1 1902 -14.2426 25.9381 37.63 16 Line 13 is High yielding Stable
    25. 25. 4. Results & Discussion- StabilityLin and Binns’s cultivar performance measure (Pi): As a stability statistic the cultivar performance measure (Pi) is estimated by the square of differences between a genotype’s and the maximum genotype mean at a location, summed and divided by twice the number of locations The genotypes with the lowest (Pi) values are considered the most stable. From this analysis, the most stable cultivar ranked first for Pi and for mean yield was Line 13 followed by line 7 ranked second for Pi and for mean yield.
    26. 26. Table Lin & Binns’s (1988a) cultivar performance measure (Pi) for 16 navy bean lines tested at 14 environments, for the years 2010-2011 No Lines Mean Yield Pi(x103) Rank 13 ICA Bunsi x S x B 405/1C-C1-1C-87 2435 28 1 7 ICA Bunsi x S x B 405/1C-C1-1C-37 2318 82 2 12 ICA Bunsi x S x B 405/1C-C1-1C-80 2187 140 3 8 ICA Bunsi x S x B 405/1C-C1-1C-51 2161 170 4 4 ICA Bunsi x S x B 405/1C-C1-1C-14 2153 198 12 5 ICA Bunsi x S x B 405/1C-C1-1C-23 2149 173 5 11 ICA Bunsi x S x B 405/1C-C1-1C-70 2130 217 14 16 Awash melka 2106 197 11 9 ICA Bunsi x S x B 405/1C-C1-1C-58 2096 191 8 6 ICA Bunsi x S x B 405/1C-C1-1C-30 2071 206 13 2 ICA Bunsi x S x B 405/1C-C1-1C-3 2067 179 6 14 ICA Bunsi x S x B 405/1C-C1-1C-88 2061 194 9 10 ICA Bunsi x S x B 405/1C-C1-1C-69 2059 180 7 1 ICA Bunsi x S x B 405/1C-C1-1C-1 2047 196 10 3 ICA Bunsi x S x B 405/1C-C1-1C-13 2017 248 15 15 Awash - 1 1902 367 16
    27. 27. 4. Results & Discussion- StabilityNassar and Hühn, 1987 non-parametric stability analysis This test is based on the ranks of the genotypes across environments and gives equal weight to each location or environment. Genotypes with less change in rank are expected to be more stable. The mean absolute rank difference (S1) estimates are all possible pair wise rank differences across locations for each genotype. The S2 estimates are simply the variances of ranks for each genotype over environments For S1, genotypes may be tested for significantly less or more stable than the average stability/instability. For the variance of ranks (S2), smaller estimates may indicate relative stability. Often, S2 has less power for detecting stability than S1
    28. 28. Table. Mean absolute rank differences (S1) and variance of ranks (S2) for mean yield of 16navy bean lines across environments No Lines Mean Yld S1 S2 Rank 13 ICA Bunsi x S x B 405/1C-C1-1C-87 2435 3.14 3.36 1 7 ICA Bunsi x S x B 405/1C-C1-1C-37 2318 5.43 19.49 2 12 ICA Bunsi x S x B 405/1C-C1-1C-80 2187 8.00 25.38 7 8 ICA Bunsi x S x B 405/1C-C1-1C-51 2161 7.86 17.52 6 4 ICA Bunsi x S x B 405/1C-C1-1C-14 2153 7.36 20.71 3 5 ICA Bunsi x S x B 405/1C-C1-1C-23 2149 7.71 22.68 5 11 ICA Bunsi x S x B 405/1C-C1-1C-70 2130 7.64 26.71 4 16 Awash melka 2106 8.57 22.73 8 9 ICA Bunsi x S x B 405/1C-C1-1C-58 2096 9.43 24.88 10 6 ICA Bunsi x S x B 405/1C-C1-1C-30 2071 9.07 13.15 9 2 ICA Bunsi x S x B 405/1C-C1-1C-3 2067 10.21 13.26 13 14 ICA Bunsi x S x B 405/1C-C1-1C-88 2061 9.71 13.76 11 10 ICA Bunsi x S x B 405/1C-C1-1C-69 2058 10.07 14.07 12 1 ICA Bunsi x S x B 405/1C-C1-1C-1 2047 10.43 11.03 14 3 ICA Bunsi x S x B 405/1C-C1-1C-13 2017 10.50 29.50 15 15 Awash - 1 1902 10.86 20.29 16
    29. 29. 4. Results & Discussion- AMMI biplot The IPCA 1 and IPCA 2 axes explained 51% and 35% of the total GEI & both are significant at (P<0.01) By plotting both the lines and the environments on the same graph, associations b/n lines and the environments can be seen clearly The IPCA scores of a genotype is an indication of the stability or adaptation over environments The greater the IPCA scores, either negative or positive, (as it is a relative value), the more specific adapted is a genotype to certain environments The more the IPCA scores approximate to zero, the more stable or adapted the genotype is over all the environments
    30. 30. G8  Many lines performed 20 G4 E4G 16 around the mean yld  G13 and G7 are high E3 E14 yielding lines 10 G6 G11 E1 IPCA 1 G7 E2  G13, G1, and G9 are E10 E9 G13 stable lines E7 0 E11 E8 E12 G1 G9 E13 G10 G2 G14 -10 G5 G15 G3 G12 -20 1000 1500 2000 2500 3000 3500 4000 Genotype & Environment meansFigure . IPCA 1 scores for both genotypes and environments plotted against the mean yield for genotypes and environments
    31. 31.  E1, E2, E3, E6 and E14 high 20 E2 yielding/favourable envts G7 G10  E4, E5 and E13 observed E14 average performance 10 E4 E10 G16  E7, E8, E9, E10, E11 and E12IPCA 2 E7 E11 E6 E9 G8 are low yielding envts E5 0 G5 G13 G4 G2 G12 E8 G3 E12 G11 -10 G14 G6 G1 E1 G9 -20 E13 E3 1000 1500 2000 2500 3000 3500 4000 Genotype & Environment meansFigure 2. IPCA 2 scores for both genotypes and environments plotted against the mean yield for genotypes and environments
    32. 32. 4. Results & Discussion- AMMI biplot Environments spread from the lower yielding environments in quadrants I and IV to the high yielding environments in quadrants II and III High yielding locations are Melkassa, Haramaya, Alemtena and Jimma The unfavourable locations for navy bean production are areas represented by Pawe, Bako, Areka and Sirinka due to the different biotic and abiotic stresses The line best adapted to most environments was Line 13 but was also better adapted to the higher yielding, favourable environments There also lines with specific adaptation pattern
    33. 33. E14 G9 E3 High yielding Envts E2 E1IPCA2 - 35.36% G1 G13 G14 E4 G2 G6 G12 G8 4 E13 E8 E5 G11 G3 E9 E7 E6 G5 G16 Low E11 G7 Yielding G10 E10 E12 Avrge Envts G15 IPCA1 - 50.64%Figure 3. Plotting IPCA1 and IPCA 2 scores for clustering environments
    34. 34. Conclusion The two high yielding (averaged over environments) genotypes 13 and 7 could be regarded as a widely adapted/ stable genotype and having low contributions to G×E interaction Genotype 13 combined low absolute IPC1, IPCA2 scores and high yield would be best overall winner with relatively less variable yield across environments Favorable test environments should have larger IPCA1 scores (more discriminative) and near zero IPCA2 scores (more representative)
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