Abstract
THE OBJECTIVES of this study were to use different biometrical models in assessing the genotype by environment interaction (GE) in cotton yield trials, determine the relationship among different stability statistics, and compare the relative efficiency of these models in explaining the GE effects. Variation in lint cotton yield was evaluated in fifteen extra long stable genotypes across 10 environments (location-year combinations) in 2010 and 2011. The combined analysisof variation showed that the main effects were highly significant and sum of squares proportions (remaining after removing the sums of squares due to error and replications) were 65.30%, 10.6%, and 24.1% for environments, genotypes and interaction, respectively. Pattern analysis split each of environments and genotypes into different lineages of homogenous clusters. This was reflecting the tremendous effects of environments, seasonal variation and genotypicdifferences and emphasizing the importance of deep investigation of GE interaction. Joint regression model revealed that the proportion due to regression line was 7.65%. The greater part of GE interaction was due to deviation from regression line. Meanwhile, the proportions of the first two principal components in GE interaction were 36.45% and 19.5%, respectively, with the first I PCA being significant. This reflects the importance of AMMI model in isolating the relevant parts of GE interaction and excluding the irrelevant parts. AMMI-1 and AMMI-2 models were high informative in describingthe main effects and their interaction. AMMI model was superior to joint regression model in terms of its predictive abilityand efficiency in explaining the pattern of GE sum of squares. Moreover, AMMI determined the genotypes with specific stability as well as the discriminative environments. Ranks of stable genotype and magnitude of stability measurement varied with each model. Neither coefficient of regression nor the coefficient of deviation significantly correlated with the mean performance. IPCA1 significantly correlated with the trait mean performance. AMMI stability value (ASV) was highly correlated with the deviation from regression and with Tai coefficients. As expected, both of regression coefficient and α, the deviations from regression and λ, were positively correlated. AMMI model assembled each group of (E2 and E6), (E9 and E10) and (E4 and E7) to establish a mega environment for breeding the associated genotypes. When contrasting stability measurement, genotypes G88, G93, G84×PimaS6,F 81338/08 and F7 1310/08 were commonly exhibited average stability, therefore they could targeted for the simultaneous improvement of yield and stability. At the level of specific stability and adaptability, however, AMMI model dominated other models. It is important to take into consideration the results of specific stability and adaptability, especially when the component of interaction within environments being higher, rather than among environments as it was evident here.
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Claims 20
Claim · model-written summary
Environmental, genotype and interaction main effects were highly significant.
- Taxon
- cotton
Gossypium hirsutumt0 - Outcome
- main effectse0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The combined analysisof variation showed that the main effects were highly significant”
t0“Cotton”
Claim · model-written summary
Environment accounted for 65.30% of the reported sum of squares.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- environmentse0
- Value
- 65.30%e0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“sum of squares proportions (remaining after removing the sums of squares due to error and replications) were 65.30%, 10.6%, and 24.1% for environments, genotypes and interaction, respectively”
t0“Cotton”
Claim · model-written summary
Genotypes accounted for 10.6% of the reported sum of squares.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- genotypese0
- Value
- 10.6%e0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“sum of squares proportions (remaining after removing the sums of squares due to error and replications) were 65.30%, 10.6%, and 24.1% for environments, genotypes and interaction, respectively”
t0“Cotton”
Claim · model-written summary
Genotype by environment interaction accounted for 24.1% of the reported sum of squares.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- interactione0
- Value
- 24.1%e0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“sum of squares proportions (remaining after removing the sums of squares due to error and replications) were 65.30%, 10.6%, and 24.1% for environments, genotypes and interaction, respectively”
t0“Cotton”
Claim · model-written summary
Pattern analysis clustered environments and genotypes.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- homogenous clusterse0
Not reportedComparatorDirectionValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Pattern analysis split each of environments and genotypes into different lineages of homogenous clusters”
t0“Cotton”
Claim · model-written summary
The joint regression line explained 7.65% of the interaction.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- proportion due to regression linee0
- Value
- 7.65%e0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Joint regression model revealed that the proportion due to regression line was 7.65%”
t0“Cotton”
Claim · model-written summary
Most genotype environment interaction was deviation from the regression line.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- GE interactione0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The greater part of GE interaction was due to deviation from regression line”
t0“Cotton”
Claim · model-written summary
The first principal component accounted for 36.45% of GE interaction and was significant.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- first two principal components in GE interactione0
- Value
- 36.45%e0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the proportions of the first two principal components in GE interaction were 36.45% and 19.5%, respectively, with the first I PCA being significant”
t0“Cotton”
Claim · model-written summary
The second principal component accounted for 19.5% of GE interaction.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- first two principal components in GE interactione0
- Value
- 19.5%e0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the proportions of the first two principal components in GE interaction were 36.45% and 19.5%, respectively”
t0“Cotton”
Claim · model-written summary
AMMI-1 and AMMI-2 were informative for the main effects and interaction.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- describingthe main effects and their interactione0
Not reportedComparatorDirectionValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“AMMI-1 and AMMI-2 models were high informative in describingthe main effects and their interaction”
t0“Cotton”
Claim · model-written summary
AMMI surpassed joint regression in predictive ability and explanation of GE sums of squares.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- predictive abilityand efficiencye0
- Direction
- superiore0
- Comparator
- joint regression modele0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“AMMI model was superior to joint regression model in terms of its predictive abilityand efficiency in explaining the pattern of GE sum of squares”
t0“Cotton”
Claim · model-written summary
AMMI identified specifically stable genotypes and discriminative environments.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- genotypes with specific stability as well as the discriminative environmentse0
Not reportedComparatorDirectionValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“AMMI determined the genotypes with specific stability as well as the discriminative environments”
t0“Cotton”
Claim · model-written summary
Genotype stability rankings varied among models.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- Ranks of stable genotype and magnitude of stability measuremente0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Ranks of stable genotype and magnitude of stability measurement varied with each model”
t0“Cotton”
Claim · model-written summary
Regression and deviation coefficients were not significantly correlated with mean performance.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- mean performancee0
- Comparator
- coefficient of regressione0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Neither coefficient of regression nor the coefficient of deviation significantly correlated with the mean performance”
t0“Cotton”
Claim · model-written summary
IPCA1 was significantly correlated with mean performance.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- trait mean performancee0
- Comparator
- IPCA1e0
Not reportedGeneDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“IPCA1 significantly correlated with the trait mean performance”
t0“Cotton”
Claim · model-written summary
ASV was highly correlated with regression deviation and Tai coefficients.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- AMMI stability value (ASV)e0
- Comparator
- deviation from regressione0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“AMMI stability value (ASV) was highly correlated with the deviation from regression and with Tai coefficients”
t0“Cotton”
Claim · model-written summary
Regression and deviation coefficients were positively correlated.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- regression coefficient and αe0
- Direction
- positively correlatede0
- Comparator
- deviations from regression and λe0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“both of regression coefficient and α, the deviations from regression and λ, were positively correlated”
t0“Cotton”
Claim · model-written summary
AMMI grouped E2 and E6, E9 and E10, and E4 and E7 as mega environments.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- mega environmente0
Not reportedComparatorDirectionValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“AMMI model assembled each group of (E2 and E6), (E9 and E10) and (E4 and E7) to establish a mega environment for breeding the associated genotypes”
t0“Cotton”
Claim · model-written summary
Five named genotypes showed average stability and were proposed for yield and stability improvement.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- simultaneous improvement of yield and stabilitye0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“genotypes G88, G93, G84×PimaS6,F 81338/08 and F7 1310/08 were commonly exhibited average stability, therefore they could targeted for the simultaneous improvement of yield and stability”
t0“Cotton”
Claim · model-written summary
Specific stability and adaptability should be considered when within-environment interaction is high.
- Taxon
- cottonGossypium hirsutumt0
- Outcome
- specific stability and adaptabilitye0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“It is important to take into consideration the results of specific stability and adaptability, especially when the component of interaction within environments being higher, rather than among environments as it was evident here”
t0“Cotton”