Yield stability and relationships among stability parameters in soybean genotypes across years

Milioli, Anderson Simionato; Zdziarski, Andrei Daniel; Woyann, Leomar Guilherme; Santos, Rodnei dos; Rosa, Ana Claudia; Madureira, Alana; Benin, Giovani

doi:10.4067/s0718-58392018000200299

Cited by 16 publications

(9 citation statements)

References 15 publications

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“…For this reason, (Shahbazi, 2019;Vaezi et al, 2018) HMGV, RPGV and HMRPGV selected G10 and G2 as the most stable genotypes and these genotypes are the top two genotypes in the yield rank. Hence, these BLUP based stability indexes, which are also positively and signi cantly correlated (P < 0.001) (Supplementary Table S4) with the yield rank, are best stability measures to identify high yielding and stable genotypes and this result concurs with the studies of many authors (Gonçalves et al, 2020;Milioli et al, 2018;Rosado et al, 2019) Both S (3) and S (6) selected similar genotypes as the top two stable and least two unstable con rming that they are similar in selecting stable genotypes. S (2) selected G5 as the most unstable genotypes and this is in contrary to S (1) , which declared this genotypes as the most stable one.…”

Section: Yield Stability Of Sun Ower Genotypessupporting

confidence: 83%

Identification of adaptable sunflower (Helianthus annuus L.) genotypes using yield performance and multiple-traits index

Baraki

Gebregergis

Belay

et al. 2023

Preprint

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Sunflower is the most important oil crop ranked as fourth edible oil in the world. The study was conducted in Northern Ethiopia during 2017–2019 cropping seasons using randomized completely block design with three replications. The objective was to decipher the genotype-by-environment interaction (GEI) in multi-environment trials (MET) and identify adaptable sunflower genotypes. Combined ANOVA, AMMI ANOVA and Eberhart and Rusell regression were analyzed, and GGE bi-plots, AMMI1 and AMMI2 bi-plots, Principal component Analysis (PCA), multi-trait genotype–ideotype distance index (MGIDI), correlation network plot for sunflower traits were sketched. AMMI stability measures, Best Linear Unbiased Prediction (BLUP) based indexes; parametric and non-parametric statistics were computed using R-statistical software. In the AMMI ANOVA the main effects of the environment (E) (54.18% SS), genotype (G) (16.9% SS) and GEI (23.50% SS) were significant (p < 0.001). The genotypic Likely-hood Ratio Test revealed significant for all traits. The AMMI bi-plot and the GGE bi-plots selected G10 and G2 as the most adaptable genotypes. CV, HMGV, RPGV, HMRPGV, Pi, GAI, KRS, S(3) and S(6) also identified G10 as the most stable genotype. Based on the MGIDI, G10 (MGIDI = 1.45) and G5 (MGIDI = 2.19) are selected and these genotypes are recommended for further cultivation in Tigray.

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Section: Yield Stability Of Sun Ower Genotypessupporting

confidence: 83%

Identification of adaptable sunflower (Helianthus annuus L.) genotypes using yield performance and multiple-traits index

Baraki

Gebregergis

Belay

et al. 2023

Preprint

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“…Our results suggest that some genotypes had stable plant height and grain yield performance based on more than one parameter, but their rankings differed with each parameter. This implies that the comparisons may greatly depend on the parameter used as also observed by Milioli et al [59] and Westcott [60] and thus more than one parameter should be used to characterize and explore performance of genotypes across environments and enable more reliable selection and recommendation of genotypes [61].…”

Section: Discussionmentioning

confidence: 99%

Adaptability and Stability of Faba Bean (Vicia faba L.) Accessions under Diverse Environments and Herbicide Treatments

Abou-Khater¹,

Maalouf²,

Jighly

et al. 2022

Plants

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The adaptability and stability of 37 faba bean (Vicia faba L.) accessions with different levels of tolerance to metribuzin or imazethapyr was assessed across 12 season–location–herbicide experiments. Significant Genotype x environment (GE) interaction was found for the days to flowering (DFLR), plant height (PLHT) and grain yield (GY). Performance and stability of the accessions regarding PLHT and GY were assessed using four different stability parameters: cultivar superiority, static stability, Wricke’s eco-valence and Finlay and Wilkinson’s regression model. The stability parameters ranked these genotypes differently suggesting that PLHT and GY stability should be assessed not only on a single or a few stability parameters but on a combination of them. GGE biplot analysis indicated that the environments representing metribuzin treatment at Marchouch 2014–2015 and the non-treated treatment at Terbol 2018–2019 are the ideal environments for evaluating faba bean genotypes. GGE biplots showed herbicide tolerant accession IG12983 with simultaneous average PLHT, GY and stability across the environments. The performance of other tolerant accessions, namely IG13945, IG13906, IG106453, FB2648, and FB1216 was less stable but superior under specific mega environments. Therefore, utilizing these accessions in faba bean breeding programs would help broaden the adaptability to diverse locations–season–herbicide treatments.

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“…Some of the bean genotypes that were ranked as stable by ASV had very low yield, this is because stability doesn't care about high or low yielding genotypes [ 35 ]. Thus yield stability index (YSI) was used to identify high seed yielding and stable bean genotypes, as it combines both stability and high yielding traits into a single index, that is used in the selection of genotypes [ 29 , 34 ]. Genotypes with lower YSI are more useful as they have high mean yield and stability traits [ 28 ].…”

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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Yield stability and relationships among stability parameters in soybean genotypes across years

Cited by 16 publications

References 15 publications

Identification of adaptable sunflower (Helianthus annuus L.) genotypes using yield performance and multiple-traits index

Identification of adaptable sunflower (Helianthus annuus L.) genotypes using yield performance and multiple-traits index

Adaptability and Stability of Faba Bean (Vicia faba L.) Accessions under Diverse Environments and Herbicide Treatments

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

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