GGE biplot analysis of genotypes by environment interaction on Sorghum bicolor L. (Moench) in Zimbabwe

Mare, Marco; Manjeru, Pepukai; Ncube, Bhekumthetho; Sisito, Gevious

doi:10.5897/ajps2017.1538

Cited by 15 publications

(16 citation statements)

References 11 publications

(20 reference statements)

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“…Experimental site E1 (TARI-Selian), has both the high discriminating ability of superior common bean genotypes and representativeness of other experimental sites, thus it is an ideal site for a selection of the widely adapted common bean genotypes, as this site provided more information on seed yield performance of the tested genotypes. The experiment can be further conducted into other sites to provide more information on this, as this was a one-season field experiment, [38] used GGE biplot to determine the discriminating power and representativeness of the experimental sites on sorghum genotypes yield. The influence of individual soil properties on common bean performance indicated a strong positive effect of available soil phosphorus on seed yield and number of pods per plant also moderate 100 seed weight.…”

Section: Discussionmentioning

confidence: 99%

Environmentally stable common bean genotypes for production in different agro-ecological zones of Tanzania

Philipo

Ndakidemi

Mbega

2021

Heliyon

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Genotype by environment interaction (GxE) complicates the process of selecting genotypes suitable for quantitative traits like seed yield in beans, hence slows down the development and release of varieties by breeding programs. GxE study on seed yield in beans enables identification of stable genotypes across sites and best site(s) for discriminating the tested genotypes in terms of seed yield. The purpose of this study was to evaluate the influence of the environment, genotype, and genotype by environment interaction on seed yield stability and adaptability of common bean landraces, lines, and improved varieties across three different agro-ecologies in Tanzania. The 99 common bean genotypes (Landraces, lines, and improved varieties) were planted following alpha lattice design in three replications each contained five blocks with 20 plots. Soil properties from the experimental sites, days to 75% flowering, Seed yield, 100 seed weight, number of seeds/pod, and number of pods/plant were recorded. Data on seed yield and its components were analyzed using Additive main effect and multiplicative interaction (AMMI), genotype main effects plus genotype Â environment interaction (GGE), and yield stability index (YSI). The AMMI revealed very highly significant (P 0.001) effects of genotypes, environmental, and genotype Â environment interaction on all the traits. AMMI analysis revealed that genotype main effects accounted for 39.3% of the total sum square of seed yield, whereas the environment and genotype Â environmental interaction accounted for 31.4% and 26.8 % respectively. Genotype main effects largely influenced the variation in days to 75% flowering (55.5%), number of pods/plant (49.2%), number of seeds/pod (73.3%), and 100 seed weight (71.2%). Among soil properties recorded, available soil phosphorus, soil pH, soil exchangeable K, Ca, and Na had a strong positive association with common bean seed yield, while soil organic carbon and total nitrogen exhibited a strong negative association with seed yield. GGE revealed that E1 (TARI-Selian) was the most discriminative and representative site for common bean genotypes seed yield. Based on the yield stability index, the most stable and high seed yielding genotypes were ACC 714, Selian 14, Selian 9, Katuku, and Msolini. The identified high seed yielding and stable genotypes can be further tested in participatory variety selection involving farmers and later on released as varieties and can also be used for different breeding purposes in different agro-ecologies of Tanzania.

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Section: Discussionmentioning

confidence: 99%

Environmentally stable common bean genotypes for production in different agro-ecological zones of Tanzania

Philipo

Ndakidemi

Mbega

2021

Heliyon

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“…Breeders conduct multi-location trials and employ different G x E analytical methods to identify the most stable genotype for several crops (Mahendra et al, 2016;Mukankusi et al, 2016;Oladosu et al, 2017;Mare et al, 2017;Edmar et al, 2019;Yan and Rajcan, 2002). In addition, these studies help the breeder to select locations that are efficient for distinguishing among genotypes and that are good representatives of the target regions.…”

Section: Pc2mentioning

confidence: 99%

Biplot analysis of test environments of quinoa (Chenopodium quinoa Willd.) in Burkina Faso

Dao¹,

Alvar‐Beltrán²,

Guira³

et al. 2020

Afr. J. Plant Sci.

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The identification of stable and adaptable high yielding quinoa (Chenopodium quinoa Willd.) and, highly discriminative environments are worthwhile for a successful introduction and adoption of this crop in Burkina Faso. The objectives of this study were to determine the relationship among test environments, to identify the most discriminative and representative test environment(s), and to identify high yielding and stable quinoa variety. The study highlighted that prevailing agrometeorological conditions in an area determine the specificity of the environment. Thus, quinoa growth and productivity is affected by differences in pedological and meteorological conditions. Emerging findings showed that environment E1 at Farako-Bâ characterized by a relative low wind speed (2.03 m/s), no rainfall (0 mm) and moderate temperature (25.07°C), was efficient discriminative and representative of quinoa growing conditions in Burkina Faso for both grain yield and grain yield per plant. Quinoa varieties, Puno and Titicaca were the highest yielding (1132 and 892 kg/ha, respectively) and stable across the environments, while Pasankalla, with an average yield of 779 kg/ha, showed a specific adaptation in two environments having a short day length located at Saria and Lanfiera. The photoperiodicity and temperature were key factors determining the adaptation of this variety in an environment. Plant height and number of branches of Negra Collana were highly stable but its yield performance was low (121 kg/ha). The research implications of this study are numerous, including tailoring quinoa growing calendars and screening a large number of genotypes under the best test environment identified, prior a multi-location trial.

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“…e highly significant effect of G × E interaction observed for both grain yield and grain mold score, which indicates that effect of environment, significantly determined both grain yield and genotype response to grain mold. Significant G × E interaction in multienvironmental trials has been previously reported in sorghum for both grain yield [29,31,39,40] and grain mold score [9,16,20,21]. Moreover, substantial differences in genotypic responses of the hybrids and their parental lines were observed between sites and between years on the same site.…”

Section: Discussionmentioning

confidence: 69%

Multienvironment Evaluation of Tannin-Free Photoperiod-Insensitive Sorghum (Sorghum bicolor (L) Moench) for Yield and Resistance to Grain Mold in Senegal

Diatta

Sarr

Tovignan

et al. 2021

International Journal of Agronomy

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Combining resistance to grain mold with high grain yield in tannin-free white-grained photoperiod-insensitive sorghum is of major interest for farmers in Senegal. In this study, GGE biplot analysis was used to assess the performance, adaptability, and stability of eleven sorghum parental lines and their hybrid combinations for yield and grain mold resistance under Senegalese environments. Eleven inbred lines along with their 22 hybrid combinations and one check were evaluated across three sites during the 2015 and 2016 rainy seasons under natural grain mold infestation. The results of this study showed strong genetic variability among studied genotypes for all measured traits. The highly significant G × E interaction effects for grain yield and panicle grain mold rating score (PGMR) indicated that both traits are influenced by genetics and to some extent by environment. Broad-sense heritability computed was high for all these traits except PGMR, showing a high environmental pressure on this later. The study showed that grain mold pressure in the studied sites decreased following a South-North gradient similar to the rainfall pattern, with the south region wetter, explaining the high disease pressure in Darou and Sinthiou Maleme contrary to Bambey. The GGE biplot analysis performed showed that the first two principal components explained 85.84% of the total variation of GGE sum of squares for grain yield. The which-won-where view of the GGE biplot for grain yield showed that the hybrid HB16 was the most adapted for Bambey area. The ranking of genotypes based on both yield performance and stability showed that HB16, HB5, HB21, HB18, and HB7 were the best hybrids combining high grain yield, high stability performance, and tolerance to grain mold disease across the test environments. These hybrids outperformed the best yielding inbred line P29 (2196.7 kg ha−1) with grain yield advantages ranging 17–60%. Therefore, these hybrids could be recommended to farmers in order to improve sorghum yield in Senegal.

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GGE biplot analysis of genotypes by environment interaction on Sorghum bicolor L. (Moench) in Zimbabwe

Cited by 15 publications

References 11 publications

Environmentally stable common bean genotypes for production in different agro-ecological zones of Tanzania

Environmentally stable common bean genotypes for production in different agro-ecological zones of Tanzania

Biplot analysis of test environments of quinoa (Chenopodium quinoa Willd.) in Burkina Faso

Multienvironment Evaluation of Tannin-Free Photoperiod-Insensitive Sorghum (Sorghum bicolor (L) Moench) for Yield and Resistance to Grain Mold in Senegal

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