Appraisal of environmental interaction on quality traits of rice by additive main effects and multiplicative interaction analysis

Anandan, A.; Sabesan, T.; Eswaran, R.; Rajiv, G.; Muthalagan, N.; Suresh, R.

doi:10.1556/crc.37.2009.1.15

Cited by 18 publications

(18 citation statements)

References 2 publications

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“…In general, environments with scores near zero have little interaction across genotypes and provide low discrimination among genotypes (Anandan et al, 2009); however, in this Genotype stability is considered a reaction to changing environmental conditions, which depend on unpredictable variation components (Kang, 2002). In this study, climatic conditions were the source of this variation component.…”

Section: Resultsmentioning

confidence: 83%

Genotype by environment interaction for seed yield per plant in rapeseed using AMMI model

Marjanović-Jeromela

Nagl

Gvozdanović–Varga

et al. 2011

Pesq. agropec. bras.

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-The objective of this study was to assess genotype by environment interaction for seed yield per plant in rapeseed cultivars grown in Northern Serbia by the AMMI (additive main effects and multiplicative interaction) model. The study comprised 19 rapeseed genotypes, analyzed in seven years through field trials arranged in a randomized complete block design, with three replicates. Seed yield per plant of the tested cultivars varied from 1.82 to 19.47 g throughout the seven seasons, with an average of 7.41 g. In the variance analysis, 72.49% of the total yield variation was explained by environment, 7.71% by differences between genotypes, and 19.09% by genotype by environment interaction. On the biplot, cultivars with high yield genetic potential had positive correlation with the seasons with optimal growing conditions, while the cultivars with lower yield potential were correlated to the years with unfavorable conditions. Seed yield per plant is highly influenced by environmental factors, which indicates the adaptability of specific genotypes to specific seasons.

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Section: Resultsmentioning

confidence: 83%

Genotype by environment interaction for seed yield per plant in rapeseed using AMMI model

Marjanović-Jeromela

Nagl

Gvozdanović–Varga

et al. 2011

Pesq. agropec. bras.

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“…Grain quality has become an important issue affecting domestic consumption and possibly international trade of rice (Anandan et al, 2009b). Varietal improvement is the surest and most economical means of improving grain quality without any added cost or adverse effect on grain yield (Ludh, 2002).…”

Section: Introductionmentioning

confidence: 99%

Studies of genetics of yield and yield component characters in F2 and F3 generations of rice (Oryza sativa L.)

Thirugnanakumar¹,

Narasimman²,

An³

et al. 2011

Afr. J. Biotechnol.

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Three parents with three different durations were crossed in full diallel fashion. The resultant six hybrids were selfed along with their three parents to get six F 2 's. The F 2 's were selfed to obtain six F 3 's. The aforementioned five generations of the six crosses were studied for days to flowering, number of productive tillers per plant, number of filled grains per panicle, 100 seed weight, grain L/B ratio, grain yield per plant and harvest index. The distribution pattern of the segregating generations revealed that, the F 3 's of the cross ADT 38 x ADT 37 for hundred seed weight and the F 3 's the cross ADT 38 x ADT 44 for grain yield per plant showed normal symmetrical distribution. The kurtosis value was almost negligible indicating mesocurtic nature of the distribution. The F 3 's of ADT 38 x ADT 44 recorded high mean coupled with higher coefficient of variation, indicating the presence of additive genetic control. The higher mean performance in F 3 may be due to accumulation of favourable genes. All the other crosses and generations showed asymmetric distribution in positive as well as negative direction, for almost all the characters of interest. The mean was comparatively higher but the coefficients of variation were comparatively lower, indicating the preponderance of non-additive genetic control in the expression of the traits of interest. It is better to resort to intermating of segregants followed by recurrent selection for further improvement. The F 3 's unique cross ADT 38 x ADT 44 had taken less number of days to first flowering, higher grain L/B ratio coupled with higher grain yield. A simple selection among the F 3 progenies of the cross ADT 38 x ADT 44 may yield some useful segregants with earliness, desirable grain quality and higher grain yield.

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“…The clustering of some of the genotypes and their yield average on the biplot also explain their similarities in yield per plant variations (Marjanovic-Jeromela, 2005). In general, environments with scores near zero have little interaction across genotypes and provide low discrimination among the genotypes (Anandan et al, 2009) as seen in ENV 3 in this study. Genotype stability is considered a reaction to changing environmental conditions, which depend on unpredictable variation components (Kang, 2002).…”

Section: Discussionmentioning

confidence: 66%

Genotype-by-environment interaction and stability analysis of soybean genotypes for yield and yield components across two locations in Nigeria

Jandong¹,

Uguru²,

Okechukwu³

2019

Afr. J. Agric. Res.

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A multilocational evaluation of 20 soybean genotypes was conducted in two distinct locations (Nsukka in Derived Savanna agro-ecology and Jalingo in Northern Guinea Savanna) of Nigeria in 2015 and 2016 cropping seasons. The experiments were laid out in an Alpha lattice design and replicated three times in each location. The main objective of the research was to determine the genotype-by-environment interaction (G x E) for specific traits and yield stability. The results revealed highly significant differences among the genotypes and locations for all the traits except for seed yield. Genotype x environmental interaction was not significant for most of the traits except days to 50% flowering indicating relative consistency in time of flowering among the genotypes across the locations and year. The genotype, Ashuku produced the highest yield in the two locations. However, the most stable genotypes across the locations were Dadinkowa and Vom while the ideal environments were Jalingo 2016 (ENV2) and Nsukka 2016 (ENV4) which produced 14.0g and14.5g, respectively. Similarly, Akwanga was discriminated as the overall best genotype across the two locations.

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Appraisal of environmental interaction on quality traits of rice by additive main effects and multiplicative interaction analysis

Cited by 18 publications

References 2 publications

Genotype by environment interaction for seed yield per plant in rapeseed using AMMI model

Genotype by environment interaction for seed yield per plant in rapeseed using AMMI model

Studies of genetics of yield and yield component characters in F2 and F3 generations of rice (Oryza sativa L.)

Genotype-by-environment interaction and stability analysis of soybean genotypes for yield and yield components across two locations in Nigeria

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