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
Kassaye Negash and Kidane Tumsa

National 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

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
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
0.936
Production (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

Trend of quantity and revenue of white pea beans exported to international markets
between 2005 - 2010
Quantity Quantity exported (t)
exported Trend in value of bean export
(tons)
(USD)
80000 Revenue
75864 74762
(USD)
68452 68638
70000
60834 $50,000,000 $49,046,107
$49,654,516
60000 $45,000,000 $44,747,590
$40,000,000
49679 $35,000,000
$36,229,556
50000
$30,000,000
$25,000,000
$20,220,954
40000 $20,000,000
$15,000,000
$8,146,125
30000 $10,000,000
$5,000,000
$0
20000
2005 2006
2007
2008
10000 2009
2010

0
2005 2006 2007 2008 2009 2010 Year
Sources : CSA reports Rev…

Some major impacts of the bean program
Private sector investment Government investment and
Farmer investment and and employment creation supportive policies
benefit 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

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, J
imma, 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

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
15 Awash - 1
16 Awash melka

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

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

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

Table 3. AMMI ANOVA of grain yield for 16 navy bean lines at
fourteen 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

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.

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
12 ICA Bunsi x S x B 405/1C-C1-1C-80 2187 -18.0517 -2.8073 23.23 10
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
16 Awash melka 2106 19.4211 8.5139 26.97 14
10 ICA Bunsi x S x B 405/1C-C1-1C-69 2058 -5.7894 14.0161 19.28 8
15 Awash - 1 1902 -14.2426 25.9381 37.63 16
Line 13 is High yielding Stable

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.

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
16 Awash melka 2106 197 11
15 Awash - 1 1902 367 16

Nassar 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 Rank
13 ICA Bunsi x S x B 405/1C-C1-1C-87 2435 3.14 3.36 1
16 Awash melka 2106 8.57 22.73 8
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

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 means

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

 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 E12
IPCA 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 means

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

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

E14

G9
E3 High yielding Envts
E2 E1
IPCA2 - 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

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)

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

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