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A COMPARISON OF STATISTICAL METHODS TO DESCRIBE GENOTYPE X ENVIRONMENT INTERACTION AND YIELD STABILITY IN MULTI-LOCATION MAIZE TRIALS.

The objectives of the study were to evaluate different statistical methods to
describe genotype x environment interaction over three years, with maize hybrids
across several environments. The environment and soil variables have a major
effect on the performance of maize hybrids in South Africa. The second objective
was to evaluate and compare the different statistical stability models and
procedures, to identify the best stability model to accurately assess and rank maize
hybrids according to their stability over environments and years. The third
objective was to describe genotype x environment interaction and the adaptation
of maize hybrids to different environments over years.
Twenty three maize hybrids were evaluated at 42 environments between 2001 and
2003 in the major maize producing areas in South Africa. Grain yield and other
agronomic traits were determined but mean grain yield was used to determine
stability with the following stability procedures: CV (coefficient of variation),
Linn and Binns, Shukla, Wricke, Finlay and Wilkinson, Eberhart and Russell, and
the ASV (AMMI stability value). The comparison of the procedures were done
with Spearmanâs rank correlation coefficient and the significance determined with
studentâs t-test.
Linn and Binns cultivar performance measure ranked the hybrids, with high (Pi)
values as the most stable. CRN 80-10 was ranked first, CRN 3505 ranked second
and SNK 8520 ranked third. The unstable hybrids with low (Pi) values were SNK
6025, PHB 32A03 and PAN 6615. Linn and Binns procedure was not significantly correlated, with any of the other procedures. It was only significantly
correlated with mean yield (r = 0.97332**), thus confirmed that it is more a
measure of performance and not really a stability parameter.
Finlay and Wilkinsonâs regression coefficient indicated that DKC 80-10, CRN
3505 and PAN 6568 showed average stability and were adapted to most of the
environments. SB 7551, PHB 3203W and SA 7401 have below average stability
and adapted to the higher yielding environments. DK 617, DKC 61-24 and SNK
8520 were of average stability but were specifically adapted to low yielding
environments. This method was also not comparable to the other methods and was
only positive and significantly correlated with CV.
Shuklaâs stability variance indicated that CRN 3549, PAN 6615, DKC 63-20,
PAN 6573 and SA 7401 were stable and SNK 2551, CRN 4760B, CRN 3505,
PHB 3203W and SNK 8520 were unstable hybrids. DKC 80-10 was the highest
yielding hybrid but only average on stability. This method compared well with the
procedures of Eberhart and Russell, Nassar and Hühn, Wricke and the ASV
(AMMI). The comparison of the rank correlations were all significant and
positive. Shuklaâs and Wrickeâs methods had total correspondence (r = 1.000**).
These methods will rank hybrids equivalently according to their stability.
Wrickeâs ecovalence ranked CRN 3549, PAN 6615, DKC 63-20 and PAN 6573 as
the most stable hybrids with SNK 2551, CRN 4760B, CRN 3505, and PHB
3203W as the most unstable hybrids. Wrickeâs ecovalence was positively and
significantly correlated with Shukla, Eberhart and Russell, Nassar and Hühn and
ASV.
Eberhart and Russellâs deviation from regression indicated that CRN 3549, PAN
6615, SA 7401, DKC 63-20 and PAN 6573 were the stable hybrids. SNK 2551, CRN 4760B and CRN 3505 were the unstable hybrids. It corresponded with the
methods of Shukla, Wricke, Nassar and Hühn and the ASV.
Nassar and Hühnâs mean absolute rank method indicated PAN 6615, CRN 3549,
SNK 6726 and DKC 80-10 as the stable hybrids. CRN 3505, CRN 760B, SNK
2551 and DKC63-20 were the most unstable hybrids. This method was
significantly and positively correlated with Shukla, Wricke and Eberhart and
Russell. It was not correlated with ASV, Linn and Binns and Finlay and
Wilkinson.
The AMMI stability value (ASV) ranked DKC 63-20, DK 617, DKC 61-24 en SB
7551 as stable. SNK 2551, CRN 4760B, PHB 3203W en CRN 3760 was unstable.
ASV was significantly correlated with the methods of Shukla, Wricke and
Eberhart and Russell.
Die AMMI model 2 indicated Delmas (quadrant II), Petit, Meerlus, Bergville, Piet
Retief and Ermelo (quadrant III) as the high yielding environments. DKC 80-10,
CRN 4760B, PAN 6568, SNK 8520 and SA 7401 were adapted to the high
yielding environments but specific to Delmas. CRN 3505, SB 7551, SNK 2551
and CRN 3549 are also adapted to high yielding environments but more specific to
Petit, Meerlus, Bergville and Ermelo.
Kroonstad, Kameel, Bothaville, Viljoenskroon and Rietgat are the average to low
yielding environments and are clustered in quadrant I. DK 617, SNK 6726, DKC
63-20 and DKC 61-24 were adapted to these environments. Ficksburg,
Wonderfontein and Ogies were clustered in quadrant IV and shown to be average
to low yielding environments, hybrids that were specific adapted to these
environments were PHB 3203W, PHB 32A03, DKC 71-21, PAN 6615 and PAN
6573. Die AMMI method successfully summarized patterns and relationship of the hybrids with the environments. AMMI indicated the genotype x environment
interactions and clustered the hybrids according their adaptability to certain
environments. The graphical AMMI biplot explained and described the hybridâs
adaptation and interaction with the environments.

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ufs/oai:etd.uovs.ac.za:etd-09072005-084932
Date07 September 2005
CreatorsAlberts, Martin JA
ContributorsProf CS van Deventer
PublisherUniversity of the Free State
Source SetsSouth African National ETD Portal
Languageen-uk
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.uovs.ac.za//theses/available/etd-09072005-084932/restricted/
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