Pattern analysis of multi-environment trials in common bean genotypes

Correa, Agenor Martinho; Gonçalves, Manoel Carlos; Teodoro, Paulo Eduardo

doi:10.14393/bj-v32n2a2016-29572

Cited by 4 publications

(4 citation statements)

References 18 publications

(13 reference statements)

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“…Because environmental conditions for testing are distinct, the genotype by environment interaction (G x E) affects the agronomic performance, and thus, it is necessary to analyze the stability of genotypes across environments [16,17]. This allows the assessment of the real impact of selection and ensures high reliability in the genotype recommendation for a specific place or environment groups [18,19]. Another key reason for the G x E analyses in bean breeding in Africa is that lines adapted to an African bean environment (AFBE) can be grown in similar areas in other parts of Africa [20].…”

Section: Introductionmentioning

confidence: 99%

Genotype x Environment Interactions on Seed Yield of Inter-racial Common Bean Lines in Kenya

Mondo¹,

Kimani²,

Narla³

2019

WJAR

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Determination of yield stability is critical in identifying new common bean cultivars with either specific or broad adaptation in target environments. This study aimed to assess genotype by environment (G x E) effects on agronomic performance of 78 F 1.7 lines selected with molecular markers for multiple disease resistance from 16 inter-racial bean populations. Field trials were conducted in low-, medium-and high altitude conditions in Kenya. Data collected on seed yield were subjected to additive main-effects and multiplicative interaction (AMMI) model to separate additive variance from the G x E interaction and to determine the stability of genotypes across locations. Results showed that G x E effects were highly significant (P<0.001), implying that tested lines behaved differently across the three locations. Better yields were recorded from high altitude Tigoni site while the lowest were from low altitude Mwea site. Yield across sites ranged from 1,518 to 2,748; 1,324 to 3,860; 1,537 to 3,722 and 1,010 to 3,718 kg ha-1 for pinto, red mottled, red kidney and mixed color bean lines, respectively. Number of pods plant-1 was the most strongly correlated to seed yield and could be, therefore, used as an indirect selection criterion for seed yield. The environment was responsible for the largest part of yield variability (86.4%, 84.8%, 82.3% and 49.5% for pinto, red kidney, red mottled and mixed color bean lines, respectively). KMA13-22-21 and KMA13-29-21 were the most stable high yielding lines across locations. Higher yielding lines were the most unstable across sites. Two pinto, four red kidney, 15 red mottled, and two mixed color lines did better than their corresponding checks with yield advantages of 7.6, 14.3, 71.5, and 34.9%, respectively. These lines should, therefore, be selected for further testing and release.

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Section: Introductionmentioning

confidence: 99%

Genotype x Environment Interactions on Seed Yield of Inter-racial Common Bean Lines in Kenya

Mondo¹,

Kimani²,

Narla³

2019

WJAR

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“…This variation indicated that there was contrast among environments and the occurrence of differential response of the genotypes to environmental effects. The environment was the source of variation most contributed to the performance of genotypes, indicating that the edaphic and agro climatic features of each environment significantly interfered in the trait measured [17]. The interaction between genotype x environment factors indicated that the effects of all variations were not explained individually for characters under study, and the effect provided by the environment condition promoted differences in expression of these traits [18].…”

Section: Location 3: High Altitudementioning

confidence: 99%

Wet Season Trials on Growth and Yield of Six Newly Developed Chili Pepper Hybrids at Three Different Locations

Herison

Handajaningsih

Fahrurrozi

et al. 2017

International Journal on Advanced Science, Engineering and Information Technology

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Chili pepper is one highest economic value vegetable crops in Indonesia. The wet season may adversely influence chili pepper yield in the field due to a high incidence of flower and fruit drop, and it may be more severe when it is combined with high temperature. The objective of this study might be to evaluate growth and yield of six newly developed chili pepper hybrids at three different agro climates during the wet season. The study was conducted in three locations differed mainly by elevation and soil type. They were low elevation (15 m above sea level-asl) with Ultisol, medium elevation (600 m asl) with Inceptisol, and high elevation (1000 m asl) with andosol, during the peak of rainy season, November 2014 to March 2015. In all location, the experiment was arranged in a randomized complete block design with three replications. The hybrid genotypes evaluated were H14, H17, H20, H23, H39 and H5, and one commercial hybrid as a check, Dimas. The result showed that at low elevation, the hybrid genotype of H39 showed higher stem diameter, plant fresh and dry weight, the number of fruit and total fruit weight per plant. At medium altitude, H39 showed relatively higher plant height, stem diameter, plant dry-weight and total fruit number per plant than other hybrids did. However, total fruit weight per plant of Dimas and H20 were higher than that of other hybrids. At high elevation, plant height of H23, Dimas, or H39 was relatively superior to that of other hybrids. In term of plant fresh and dry weight, H20, H23, or H17 was superior to other hybrids. However, H20, H17, or H5 showed higher yield than other hybrids did. It seems that H39, Dimas, and H20 were more suitable at low, medium and high elevation, respectively, compared to other hybrids. Growth and yield of chili pepper grown at low elevation were lower than at medium or high altitude. The plant at high elevation produced yield higher than they did at medium altitude.

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“…These results could be caused by edaphoclimatic variations, as well as variations in the incidence of pests and diseases in the environments in which the cultivars were evaluated, resulting in GEI. Several authors have also previously [52][53][54][55] reported the influence of these factors on the environmental classification, resulting in significant GEI. For Ramalho et al [56], the most significant contributions to the GEI in the common bean culture were due to the combinations of cultivar × season and cultivar × years.…”

Section: Plos Onementioning

confidence: 99%

Adaptability and stability analyses of plants using random regression models

et al. 2020

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The evaluation of cultivars using multi-environment trials (MET) is an important step in plant breeding programs. One of the objectives of these evaluations is to understand the genotype by environment interaction (GEI). A method of determining the effect of GEI on the performance of cultivars is based on studies of adaptability and stability. Initial studies were based on linear regression; however, these methodologies have limitations, mainly in trials with genetic or statistical unbalanced, heterogeneity of residual variances, and genetic covariance. An alternative would be the use of random regression models (RRM), in which the behavior of the genotypes is characterized as a reaction norm using longitudinal data or repeated measurements and information regarding a covariance function. The objective of this work was the application of RRM in the study of the behavior of common bean cultivars using a MET, based on Legendre polynomials and genotype-ideotype distances. We used a set of 13 trials, which were classified as unfavorable or favorable environments. The results revealed that RRM enables the prediction of the genotypic values of cultivars in environments where they were not evaluated with high accuracy values, thereby circumventing the unbalanced of the experiments. From these values, it was possible to measure the genotypic adaptability according to ideotypes, according to their reaction norms. In addition, the stability of the cultivars can be interpreted as variation in the behavior of the ideotype. The use of ideotypes based on real data allowed a better comparison of the performance of cultivars across environments. The use of RRM in plant breeding is a good alternative to understand the behavior of cultivars in a MET, especially when we want to quantify the adaptability and stability of genotypes.

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Pattern analysis of multi-environment trials in common bean genotypes

Cited by 4 publications

References 18 publications

Genotype x Environment Interactions on Seed Yield of Inter-racial Common Bean Lines in Kenya

Genotype x Environment Interactions on Seed Yield of Inter-racial Common Bean Lines in Kenya

Wet Season Trials on Growth and Yield of Six Newly Developed Chili Pepper Hybrids at Three Different Locations

Adaptability and stability analyses of plants using random regression models

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