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

Line by environment interaction, yield stability and grouping of test locations for

navy bean variety trial in Ethiopia

National Lowland Pulses Research Program at Melkassa Agricultural Research Center-EIAR

Kassaye Negash and Kidane Tumsa

First Bio-Innovate Regional Scientific ConferenceUnited Nations Conference Centre (UNCC-ECA)Addis Ababa, Ethiopia, 25-27 February 2013

Outlines

1. Introduction

2. Objectives

3. Materials and Methods

Materials

Statistical analysis

4. Results Discussion

5. Conclusion

Importance of beans in Ethiopia

Beans are produced by about 2.5 millions households across Ethiopia

Increased bean production and productivity

2002/3 2003/4 2004/5 2009/10 -

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

-

50,000

100,000

150,000

200,000

250,000

300,000

98,670

111,750

172,150

362,890

119,900

181,600 183,800 244,012

Trend in bean production and area

Production (tons) Area

Area Production (tons)

2002/3 2003/4 2004/5 2009/100

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0.823

0.615000000000002

0.936

1.487

Trend bean yield (t/Ha)

Trend in bean production (Qt/Ha)

Prod

uctio

n (t

/Ha)

Sources : CSA reports

Trend of quantity and revenue of white pea beans exported to international markets between 2005 - 2010

2005 2006 2007 2008 2009 20100

10000

20000

30000

40000

50000

60000

70000

80000

60834

49679

68452 68638

75864 74762

Quantity exported (t)Quantity exported

(tons)

Sources : CSA reports

20052006

20072008

20092010

$0

$5,000,000

$10,000,000

$15,000,000

$20,000,000

$25,000,000

$30,000,000

$35,000,000

$40,000,000

$45,000,000

$50,000,000

$8,146,125

$20,220,954

$36,229,556

$44,747,590

$49,046,107$49,654,516

Trend in value of bean export (USD)

Reve...Year

Revenue (USD)

Some major impacts of the bean program

Private sector investment and employment creation

Government investment and supportive policiesFarmer investment and

benefit

2004: 2ha

2010: 30 ha

Better return to farmers : more than 600 % price increase between 2003 and 2011 : USD 120/ton to USD 800

Beans listed on ECX –

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

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

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;

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

3. Materials and Methods Experiment was conducted in the

main growing seasons of 2010 to 2011

Locations were: Melkassa, Alemtena, Areka, Haramaya, Jimma, Bako, Pawe, Sirinka and Assossa

The locations have diverse agro-ecological characteristics as annual rainfall, temperature and altitude

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

Line Code Number Line Name1 ICA Bunsi x S x B 405/1C-C1-1C-12 ICA Bunsi x S x B 405/1C-C1-1C-33 ICA Bunsi x S x B 405/1C-C1-1C-134 ICA Bunsi x S x B 405/1C-C1-1C-145 ICA Bunsi x S x B 405/1C-C1-1C-236 ICA Bunsi x S x B 405/1C-C1-1C-307 ICA Bunsi x S x B 405/1C-C1-1C-378 ICA Bunsi x S x B 405/1C-C1-1C-519 ICA Bunsi x S x B 405/1C-C1-1C-58

10 ICA Bunsi x S x B 405/1C-C1-1C-6911 ICA Bunsi x S x B 405/1C-C1-1C-7012 ICA Bunsi x S x B 405/1C-C1-1C-8013 ICA Bunsi x S x B 405/1C-C1-1C-8714 ICA Bunsi x S x B 405/1C-C1-1C-8815 Awash - 1 16 Awash melka

Table 2. Descriptive information on the name and codes of the 16 cowpea varieties

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)

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)

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),

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,

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) =

4. Results and Discussion Relative performance of genotypes

based on mean grain yield 1. 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 evaluation

2. 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

LinesEnvironment

MeanMK10 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

Table 3. Mean yield performance (kgha-1) of 16 navy bean lines evaluated at 14 environments for the period 2010-2011

4. Results and ---The combined ANOVA indicated

1. Highly significant differences (P<0.01) for environments, lines and GEI

2. 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

Source DF Sum of Square Mean SquareContribution of

each component to the total SS (%)

Treatment 223 522867290 2344696** 88Environments 13 460020679 35386206** 76Reps within Environment 28 12250577 437521** 2Line/Genotye 15 9379070 625271** 2Variety 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

Table 3. AMMI ANOVA of grain yield for 16 navy bean lines at fourteen environments during 2010 – 2011 main crop season

** and * - stands for 1 and 5% probability levels; ns – non significant

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.

Line code

Line name Mean IPCA Score 1 IPCA Score 1 ASV Rank

13 ICA Bunsi x S x B 405/1C-C1-1C-87 2435 1.9774 0.4549 2.58 17 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 23.23 108 ICA Bunsi x S x B 405/1C-C1-1C-51 2161 21.7655 3.3169 28.00 154 ICA Bunsi x S x B 405/1C-C1-1C-14 2153 19.5516 -1.8071 24.97 125 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 14.36 316 Awash melka 2106 19.4211 8.5139 26.97 149 ICA Bunsi x S x B 405/1C-C1-1C-58 2096 -1.8671 -17.5661 22.46 96 ICA Bunsi x S x B 405/1C-C1-1C-30 2071 10.2217 -10.1807 18.35 72 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 17.11 610 ICA Bunsi x S x B 405/1C-C1-1C-69 2058 -5.7894 14.0161 19.28 81 ICA Bunsi x S x B 405/1C-C1-1C-1 2047 -0.6274 -13.4028 17.06 53 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

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 13 is High yielding Stable

4. Results & Discussion- Stability

Lin 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.

No Lines Mean Yield Pi(x103) Rank13 ICA Bunsi x S x B 405/1C-C1-1C-87 2435 28 17 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 38 ICA Bunsi x S x B 405/1C-C1-1C-51 2161 170 44 ICA Bunsi x S x B 405/1C-C1-1C-14 2153 198 125 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 1416 Awash melka 2106 197 119 ICA Bunsi x S x B 405/1C-C1-1C-58 2096 191 86 ICA Bunsi x S x B 405/1C-C1-1C-30 2071 206 132 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 194 910 ICA Bunsi x S x B 405/1C-C1-1C-69 2059 180 71 ICA Bunsi x S x B 405/1C-C1-1C-1 2047 196 103 ICA Bunsi x S x B 405/1C-C1-1C-13 2017 248 15

15 Awash - 1 1902 367 16

Table Lin & Binns’s (1988a) cultivar performance measure (Pi) for 16 navy bean lines tested at 14 environments, for the years 2010-2011

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

Table. Mean absolute rank differences (S1) and variance of ranks (S2) for mean yield of 16 navy bean lines across environments

No Lines Mean Yld S1 S2 Rank13 ICA Bunsi x S x B 405/1C-C1-1C-87 2435 3.14 3.36 17 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 78 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 35 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 26.71 416 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 92 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 1110 ICA Bunsi x S x B 405/1C-C1-1C-69 2058 10.07 14.07 121 ICA Bunsi x S x B 405/1C-C1-1C-1 2047 10.43 11.03 143 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

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

G15

G13

G8

G14

G9

G2G10

G4

G11

G1

G3

G5

G7

G 16

G12

G6E14

E13

E8

E9

E2

E4

E7

E1

E3

E10

E11 E12

1000 2000 3000

-20

4000

-10

0

10

20

2500 1500 3500

IPC

A 1

Genotype & Environment means

Figure . IPCA 1 scores for both genotypes and environments plotted against the mean yield for genotypes and environments

Many lines performed around the mean yld

G13 and G7 are high yielding lines

G13, G1, and G9 are stable lines

G16

G13

G7

G14

G8

G2

G9

G6

G1

G3

G5

G10

G11

G12G4

E14

E13

E7

E8

E2

E9

E4

E6

E1

E3

E5

E10

E11

E12

1000 2000 3000

-20

4000

-10

0

10

20

2500 1500 3500

IPC

A 2

Genotype & Environment means

Figure 2. IPCA 2 scores for both genotypes and environments plotted against the mean yield for genotypes and environments

E1, E2, E3, E6 and E14 high yielding/favourable envts

E4, E5 and E13 observed average performance

E7, E8, E9, E10, E11 and E12 are low yielding envts

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

G6

G9

G1

G2

G15

G3

G13

G11

4

G14

G12

G10

G16G5

G8

G7

E7E6

E1

E4

E3

E9

E10

E2

E13

E11

E14

E5

E12

E8

IPCA1 - 50.64%

IPC

A2 - 35.36%

Figure 3. Plotting IPCA1 and IPCA 2 scores for clustering environments

High yielding Envts

Low Yielding

Avrge Envts

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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