Advances in ISSN: 2373-6402APAR

Plants & Agriculture Research
Research Article
Volume 2 Issue 3 - 2015
Additive Main Effects and Multiplicative Interaction Analysis of European Linseed (Linum Ustatissimum L.) Cultivars under South African Conditions
MJ Jacobsz*, WJC van der Merwe and MM van der Westhuizen
Agricultural Research Council - Institute for Industrial Crops, South Africa
Received:April 17, 2015 | Published: April 27, 2015
*Corresponding author: MJ Jacobsz, Agricultural Research Council - Institute for Industrial Crops, South Africa, Email: @
Citation: Jacobsz MJ, Merwe WJCV, Westhuizen MMV (2015) Additive Main Effects and Multiplicative Interaction Analysis of European Linseed (Linum Ustatissimum L.) Cultivars under South African Conditions. Adv Plants Agric Res 2(3): 00049. DOI: 10.15406/apar.2015.02.00049

Abstract

Flax (Linum ustatissimum L.) is a multipurpose crop cultivated for both the fibre in the stem (fibre flax) or for its oil pressed from the seed (linseed). The natural qualities of flax make it a desirable commodity for manufacturers seeking alternative solutions to chemical and plastic-based products. As there is no production of flax in South Africa, ten linseed cultivars were imported from the Netherlands and the United Kingdom and evaluated for their adaptability under South African conditions. These cultivars were planted during the 2005 to 2009 season at six different localities (environments) in the Western Cape Province under rain fed conditions. The localities were, Bredasdorp, Caledon, Elsenburg, Koringberg, Langgewens and Napier. The Additive Main Effects and Multiplicative Interaction (AMMI) statistical method as well as the PCA (Principal Component Analysis) model were used to describe cultivar environment interaction on grain yield. Results indicated that the cultivars Sunrise, Capricorn, Bilstar, Virgo and Taurus were the most adapted cultivars for high potential environments.
Keywords: Flax; AMMI model; ASV; Linseed

Abbreviations

AMMI: Additive Main Effects and Multiplicative Interaction; ASV: Ammi Stability Value; PCA: Principal Component Analysis; CxE: Cultivar x Environment Interaction

Introduction

Flax (Linum ustatissimum L.) is a multipurpose crop cultivated for both the fibre in the stem (fibre flax) or for its oil pressed from the seed (linseed). The natural qualities of flax make it a desirable commodity for manufacturers seeking alternative solutions to chemical and plastic-based products. Linseed grains, which are either brown or yellow, contain 35-45% oil and 18-26% protein. Linseed oil is the most widely available botanical source of Omega-3 fatty acids. Alpha-linolenic acid (ALA) is the important Omega-3 fatty acid in linseed, which is of considerable benefit to humans and animals. Linseed cultivars vary in their ALA content, from cultivars with an ALA content of 2%, which makes them unsuitable for the Omega-3 market, to ALA-rich cultivars (60% ALA) which are extremely suitable for the Omega-3 human food and animal feed markets. Cultivars with an ALA content of 2% compete with sunflowers for processing into margarine and cooking oil [1].

Practically, all linseed and linseed products used in South Africa are currently being imported from countries such as Canada, Germany, Denmark and the Netherlands. Canada is the world’s leading producer of linseed oil and according to Statistics Canada the current production is running 13 % below demand [2]. Thus, here is a high demand for this commodity which can potentially be exploited by local farmers. Linseed is an excellent rotational crop with wheat and barley. Flax has great potential to be planted commercially under South African conditions [3]. The current study was undertaken to interpret Cultivar x Environment (CE) interaction obtained by AMMI analysis of yield performance of 10 linseed cultivars over 6 environments, to visually assess how yield performances vary across environments on a biplot and to group the cultivars having similar response patterns across varying environments together.

Materials and Methods

Description of the study area
Five linseed cultivars (Bilton, Biltstar, Capricorn, Taurus and Virgo -imported from the Netherlands) and another five cultivars imported from the UK (Gemini, Laser, Linus, Marmalade and Sunrise) were evaluated over a four year period from 2005 to 2009 at six localities (environments) namely Bredasdorp, Caledon, Elsenburg, Koringberg, Langgewens & Napier in the Western Cape Province of South Africa. The trails were planted from mid-May to early June after the first rains and cultivated under rain fed conditions. A seeding rate of 50 kg seed ha-1 was used. Standard fertilization and weed control practices were implemented throughout the study. 400 kg ha-1 of 2:3:4 (27) was incorporated in the soil before planting. Two top dressings of 50 kg ha-1 was done with Limestone ammonium nitrate (LAN). Harvesting of grain was commenced during November. The trial design was a randomized block design with three replications. Plot size was 1m x 4m with 6 rows. The inter-row spacing was 25cm with a sowing depth of 2cm. Linseed grain yield data was used to evaluate the different cultivars and localities applying the Additive Main effects and Multiplicative Interaction (AMMI) model [4]. AMMI stability values (ASV) were computed from stability values as derived by Purchase et al. [5].

Results and Discussion

Although numerous statistical techniques are available to describe cultivar x environment interaction [6-8] the additive main effects and multiplicative interaction method (AMMI) has been used by various researchers on crops such as bread wheat [5], cotton [9], durum wheat [10], faba bean [11], lucern [12], maize [13], potatoes [14] and tobacco [15]. The graphical version (biplot) of the cultivar means and the first interaction (PCA) Principle component analysis scores eases interpretation and identification of high yielding cultivars. Principal component analysis is a variable reduction procedure and is the most frequently used multivariate method [6,16]. Its aim is to transform the data from one set of coordinate axes to another, which preserves, as much as possible, the original configuration of the set of points and concentrates most of the data structure in the first principal component axis.

From the ANOVA table for AMMI analysis it can be seen that the mean squares for cultivars, environments and C x E interaction were found to be highly significant (Table 1). This suggested that a broad range of diversity existed among cultivars and among environments and that the performance of the cultivars was inconsistent over environments. Of the total treatment variation, the variance due to difference in the environment was the largest (61.2%) as can be expected in diverse production areas in the Cape Province of South Africa. This was followed by the variance due to C x E interactions (16.7%). In contrast, the variance due to cultivar was only 2.0%. The ordinary ANOVA model accounted for 63.2% of the trial sum of squares, concentrating only on the cultivar effects and environment effects. Although it is obvious that cultivars, environments and cultivar x environment interaction exerted a significant effect on yield, it is not clear which cultivars, environments or cultivar x environment interactions were responsible for the differences, or how these responses differ. The ANOVA model was thus found not to be adequate enough for analyzing the linseed grain yield data, as C x E interactions were highly significant. The ANOVA model was, therefore, combined with PCA (Principal Component Analysis) model to further analyze the residuals of the ANOVA model, which contains the C x E interaction (Table 1). Results from the analysis of multiplicative effects showed that the first interaction principal component analysis (IPCA1) captured 54.7% of the interaction sum of squares. The second interaction principal component analysis (IPAC2) explained only 13.3% of the C x E interaction. This is of relative minor magnitude and it would be difficult to draw meaningful conclusions from this principal component factor. Further analysis would, therefore, mostly concentrate on the IPCA1 scores.

Source

df

SS

MS

Prob

Environment

19

107 497 885

5 657 783

<0.001

Block

40

19 175 697

479 392

<0.001

Cultivar

9

3 517 968

390 885

<0.001

C x E Interaction

171

29 286 665

171 267

<0.001

ICPA1

27

16 048 662

594 395

<0.001

ICPA2

25

3 901 523

156 061

<0.001

Residual

119

9 336 479

78 456

<0.001

Error

360

16 098 679

44 719

 

Total

599

175 578 894

293 117

 

Table 1: ANOVA for AMMI model for the cultivar evaluation trials at the different localities in the Western Cape Province over the period 2005 – 2009.

The IPCA1 scores and mean performances data (grain yield) for both cultivar and environment that were used to construct an AMMI biplot are presented in Table 3. This was used to identify a specific pattern of the main effect and C x E interactions on both the cultivars and environments simultaneously [6-8]. It is clear from the biplot that the points for environment were more scattered than the points for cultivars (Figure 1). This indicated that variability due to environments was higher than that of cultivar differences. According to the AMMI model, cultivars which are characterized by means greater than grand mean and the IPCA score nearly zero are considered as generally adaptable to all environments (this suggests negligible or no C x E interaction). The cultivars, Laser and Linus meet these requirements. On the other hand, cultivars with high mean performance and with large value of IPCA scores are considered as having specific adaptability to the environments. The cultivars Sunrise, Capricorn, Bilstar, Virgo and Taurus fell into this category. Favourable environments for these cultivars can be characterized as with high mean and large IPCA score with same sign as of cultivar IPCA1 score. The environments in quadrant II of the biplot, i.e. Elsenburg 2007, Caledon 2007, Langgewens 2007; 2009 and Napier 2008, will thus be suitable environments for these cultivars. Similar sign of IPCA1 scores implies positive interaction and as a result will suggest higher yield of related cultivars. Lower potential environments predominating in quadrant I nemely Langgewens 2006, Bredasdorp 2006 and Koringberg 2006 and 2008 are grouped together, because of the low rainfall received.

Figure 1: AMMI model biplot for linseed grain yield showing main and interaction effects for both cultivars and environments.

AMMI analysis generates predicted means which gave greater accuracy, hence greater value for making selections than do the unadjusted or observed means [4]. The observed and AMMI predicted values are demonstrated in Table 2. Based on this predicted yield data, it is evident that Virgo is one of the first five AMMI selections in 16 out of 20 environments, Linus 13 out of 20, Sunrise is 12 out of 20 and Taurus 11 out of 20 environments, but no clear pattern is evident in terms of localities or seasons (Table 3).

 

Environment

 

Year

 

Mean

IPCA1
Score

 

AMMI Selection

Elsenburg

2007

1349

15.2

Linus

Sunrise

Gemini

Laser

Bilton

Caledon

2007

1280

11.1

Sunrise

Marmalade

Taurus

Gemini

Capricorn

Langgewens

2007

1280

9.3

Sunrise

Linus

Laser

Marmalade

Gemini

Langgewens

2006

488

5.7

Sunrise

Laser

Linus

Marmalade

Virgo

Koringberg

2007

567

5.4

Sunrise

Laser

Marmalade

Linus

Taurus

Elsenburg

2006

1953

5.1

Linus

Sunrise

Laser

Biltstar

Virgo

Elsenburg

2009

1286

5.1

Sunrise

Linus

Laser

Virgo

Marmalade

Bredasdorp

2006

574

4.8

Sunrise

Linus

Laser

Virgo

Marmalade

Caledon

2006

1074

4.5

Linus

Sunrise

Laser

Virgo

Biltstar

Caledon

2009

1449

4.5

Sunrise

Laser

Linus

Virgo

Taurus

Koringberg

2008

831

3.2

Linus

Biltstar

Virgo

Laser

Sunrise

Koringberg

2006

471

3.1

Sunrise

Taurus

Virgo

Laser

Linus

Napier

2006

905

0.8

Biltstar

Virgo

Linus

Laser

Taurus

Napier

2007

1017

0.3

Taurus

Sunrise

Virgo

Capricorn

Marmalade

Caledon

2008

1862

-1.5

Biltstar

Virgo

Linus

Bilton

Laser

Bredasdorp

2007

477

-1.9

Taurus

Virgo

Capricorn

Biltstar

Laser

Langgewens

2009

1134

-9.1

Taurus

Virgo

Biltstar

Capricorn

Laser

Napier

2008

1460

-11.5

Taurus

Virgo

Biltstar

Capricorn

Laser

Elsenburg

2008

1211

-26.9

Taurus

Virgo

Biltstar

Capricorn

Laser

Langgewens

2008

967

-26.9

Taurus

Virgo

Capricorn

Biltstar

Laser

Table 2:AMMI selections per environment.

 

Cultivars

Environment

Year

Yield
type

Bilton

Bilstar

Capricorn

Gemini

Laser

Linus

Marmalade

Sunrise

Taurus

Virgo

Bredasdorp

2006

T
AMMI

584
495

643
562

591
501

*
530

546
625

569
636

493
569

702
668

694
560

528
597

Bredasdorp

2007

T
AMMI

324
334

482
523

427
526

382
303

614
478

455
442

391
428

453
467

747
655

594
610

Caledon

2006

T
AMMI

1009
1020

1022
1091

1062
988

*
1022

1255
1128

988
1149

1153
1052

1070
1148

983
1044

1105
1102

Caledon

2007

T
AMMI

742
767

748
719

1420
1415

1622
1437

1761
1304

1098
1133

1661
1604

1580
1764

1509
1483

1122
1169

Caledon

2008

T
AMMI

2012
1957

2184
2138

1675
1749

1792
1660

1919
1901

1824
1975

1836
1679

1552
1720

1892
1838

1933
2001

Caledon

2009

T
AMMI

1293
1344

1376
1416

1348
1397

1414
1404

1367
1494

1638
1493

1441
1456

1568
1552

1500
1462

1531
1475

Napier

2007

T
AMMI

855
887

1066
1027

873
893

856
768

993
940

938
970

903
815

763
878

880
924

992
998

Napier

2008

T
AMMI

1005
783

819
932

990
1098

447
905

1014
1019

929
947

1166
1048

1388
1108

1237
1220

1148
1106

Napier

2009

T
AMMI

1052
1366

1906
1730

1510
1592

1820
1080

1328
1414

1576
1373

1381
1268

1381
1220

1823
1799

1812
1760

Elsenburg

2006

T
AMMI

2368
1930

1566
1991

1804
1840

1594
1907

1929
2014

2098
2052

2096
1919

2077
2020

1845
1887

2047
1973

Elsenburg

2007

T
AMMI

1374
1431

1226
1306

912
1045

1746
1498

1581
1484

1643
1599

1191
1375

1433
1568

1163
985

1227
1201

Elsenburg

2008

T
AMMI

1173
1010

1713
1656

1570
1600

586
526

1146
1059

626
926

942
896

701
709

2003
1962

1655
1770

Elsenburg

2009

T
AMMI

1215
1212

1578
1273

1537
1205

1234
1247

1395
1339

1298
1354

1051
1281

1564
1382

1235
1260

1740
1303

Koringberg

2006

T
AMMI

518
334

471
432

437
457

241
401

516
503

461
486

511
480

823
564

540
539

388
519

Koringberg

2007

T
AMMI

388
429

631
484

562
526

630
546

641
613

374
598

491
604

855
710

488
588

616
575

Koringberg

2009

T
AMMI

863
832

1057
928

808
725

808
742

810
884

848
928

750
760

858
844

783
786

690
885

Langgewens

2006

T
AMMI

313
376

494
426

508
424

541
469

488
539

457
438

478
513

623
620

491
479

413
492

Langgewens

2007

T
AMMI

1192
1186

1095
1172

1276
1163

1575
1331

1216
1354

1500
1371

1368
1337

1194
1476

1197
1184

1200
1225

Langgewens

2008

T
AMMI

626
698

1258
1345

1449
1400

556
292

677
805

823
641

464
692

401
505

1843
1773

1578
1523

Langgewens

2009

T
AMMI

1043
1012

1132
1332

1350
1255

481
808

1246
987

1203
1098

1345
1051

768
961

1260
1444

1505
1391

Table 3: Observed and predicted grain yield (kg-1 ha-1) of 10 linseed cultivars evaluated over 6 localities from 2005-2009.

T – Observed mean yield AMMI – AMMI predicted yield * Cultivar not planted at locality

Purchase et al. [5] developed a test based on AMMI model’s IPCA1 and IPCA2 values for each cultivar and each environment [5]. It is called the AMMI Stability Value (ASV). An AMMI stability value is the distance from the coordinate point to the origin in a two dimensional scatter gram of ICPA1 scores against ICPA2 scores.). Cultivar Bilton (with the lowest ASV), was ranked as the most stable cultivar but it had a below average yield performance, except for the highest yield at Elsenburg (2006). The environment Napier in the 2007 season was the most stable environment and Langgewens 2008 and Elsenburg 2008 was the least stable environments. The latter two environments received flush floods during the 2008 season which had an effect on the grain yield. Cultivar Bilton was ranked with the lowest ASV, as the most stable cultivar but it had a below average yield performance.

Conclusion

Cultivar Bilton gave the highest yield of 2368 kg ha-1 at Elsenburg during the 2006 season. Bilton also gave the second highest yield at Caledon (2008) and Koringberg 2009, and the third best yield at Koringberg 2006. Cultivars Bilton and Laser were the AMMI best choices for most of the environments. Although Bilton had a slightly lower yield (970 kgha-1) it had higher stability (ASV=19.9). Laser gave higher yields (1100 kg ) but lower stability (ASV=25.7). Other high yield performers was the cultivar Sunrise that gave the highest yields in 5 out of the 20 environments namely Bredasdorp (2006), Napier (2008), Koringberg (2006 + 2007), and Langewens 2008. Cultivar Bilstar gave the highest yield in 4 out of the 20 environments, namely: Caledon (2008), Napier (2007 + 2009) and Koringberg (2009). Although Taurus was found to be the most unstable cultivar according to the ASV values, and showed limited adaptation to testing environments, it gave a grain yield that is above average (Table 4), whereas the most stable cultivar (Bilton) gave below average yields. For this reason, stability in itself cannot be used as the only parameter for selection, as the most stable cultivar wouldn’t necessarily give the best yield performance. This contradiction was also found by cotton researchers in California [17] that found a positive correlation between yield and stability and an association that suggests that cotton cultivars producing higher yields are, in general, lower in stability.

Cultivar

Yield

IPCA 1

IPCA 2

ASV

Bilton

970

2.7

16.5

19.9

Laser

1100

6.2

2.4

25.7

Linus

1083

10.2

9.9

73.3

Marmalade

1038

10.5

-9.7

44.0

Capricorn

1087

-13.8

-10.8

57.7

Biltstar

1124

-15.6

16.5

66.1

Virgo

1184

-16.9

0.9

69.9

Sunrise

1094

19.5

-9.8

80.7

Gemini

944

20.4

-2.7

84.0

Taurus

1194

-23.2

-13.3

96.3

Table 4: AMMI stability values for each cultivar.

Acknowledgement

Department of Agriculture, Forestry and Fisheries for funding.

References

  1. Turner J (1987) Linseed Law A handbook for growers and adviser. BASF, United Kingdom Ltd, Hadleigh, Suffolk.
  2.  www.statcan.gc.ca
  3. Van Tonder CSM, Jansen A, Jacobsz M, van der Merwe W (2003) Adaptability of European fibre and linseed flax (Linum usitatissimum) cultivars to South African conditions. African Crop Science Conference Proceedings 6: 38-41.
  4. Gauch HG, Zobel RW (1989) Accuracy and selection success in yield trial analysis. Theor Appl Genet 77(4): 473-481.
  5. Purchase JL, Hatting H, van Deventer CS (2000) Genotype x environment interaction of winter wheat  (Triticum aestivum L.) in South Africa: II. Stability analysis of yield performance. S Afr J Plant Soil 17(3): 101-107.
  6. Crossa J, Gauch HG, Strobel RW (1990) Additive mean effects and multiplicative interaction analysis of two international maize cultivar trails. Crop Sci 6(3): 36-40.
  7. Kempton RA (1984) The use of biplots in interpreting variety by environment interactions. J Agric Sci 103(1): 123-135.
  8. Zobel RW, Wright MG, Gauch HG (1988) Statistical analysis of yield trial. Agron J 80(3): 388-393. 
  9. Campbell BT, Jones MA (2005) Assessment of genotype x environment interactions for yield and fiber quality in cotton performance trials. Euphytica144: 69-78.
  10.  Mohammadi R, Amri A (2011) Genotype x environment interaction for duram wheat grain yield and selection for drought tolerance in irrigated and drought environments in iran. J Crop Sci Biotech 14(4): 265-274.
  11. Fikere M, Tadesse T, Letta T (2008) Cultivar-environment interactions and stability parameters for grain yield of Faba bean (Vacia faba L.) cultivars grown in South eastern Ethiopia. Int J Sustain Crop Prod 3: 80-87.
  12. Smith MF, Smith A (1992) The success of the AMMI model in predicting Lucerne yields for cultivars with differing dormancy characteristics. S Afr J Plant Soil 9(4): 180-185.
  13. Maali SH (2008) Additive main effects and multiplicative interaction analysis of maize yield trials in South Africa. S Afr J Plant Soil 25: 185-193.
  14. Steyn PJ, Visser AF, Smith MF, Schoeman JL (1993) Ammi analysis of potato cultivar trials. S Afr Tydskri Plant Grond 10.
  15. Sadeghi SM, Samizadeh H, Amiri E, Ashouri M (2011) Additive main effects and multiplicative interactions (AMMI) analysis of dry leaf yield in tobacco hybrids across environments, African Journal of Biotechnology 10(21): 4358-4364.
  16. Purchace JL (1997) Parametric analysis to describe G X E interaction and yield stability in winter wheat. PhD Thesis. Department of Agronomy, Faculty of Agriculture, University of the Orange Free State, Bloemfontein, South Africa.
  17. Geng S, Zhang Q, Bassett DM (1987) Stability in yield and fiber quality of California Cotton. Crop Sci 27: 1004-1010.
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