Genotype x environment interaction, adaptability and stability of ‘Piel de Sapo’ melon hybrids through mixed models

Silva, Edicleide Macedo da; Nunes, Elaíne Welk Lopes Pereira; Costa, Jorge de Assis; Ricarte, Anânkia de Oliveira; Nunes, Glauber Henrique de Sousa; Aragão, F. A. S. de

doi:10.1590/1984-70332019v19n4a57

Cited by 5 publications

(4 citation statements)

References 16 publications

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“…The use of the HMRPGV method allowed for cultivar selection based on N‐response indices, and cultivars were chosen according to adaptability and penalized for instability between environments (Rosado et al., 2019; Silva et al., 2019). This method has been used for the simultaneous selection of yield, adaptability, and stability in several crops such as common bean (Delfini et al., 2018), wheat (Coan et al., 2018), corn (Pinto et al, 2019), soybean (Freiria et al., 2018), and papaya (Luz et al., 2018).…”

Section: Discussionmentioning

confidence: 99%

Genetic variability and nitrogen response indices in common bean (Phaseolus vulgaris) cultivars under contrasting nitrogen environments

et al. 2021

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Although common bean plants can fix atmospheric nitrogen (N2), this process is insufficient to meet the total nitrogen (N) demand of the crop. Thus, the objective of the present study was to compare different N‐responses indices of common bean cultivars in contrasting N fertilization environments. In addition, the genetic variability of the cultivars was verified using SNP and AFLP markers. Cultivars that showed high tolerance to low‐N (LNTI) generally had low N‐agronomic efficiency (NAE), confirming the complexity of simultaneously selecting for genotypes that show both traits. The performance under contrasting N (PCN) index presented the highest heritability and selective accuracy estimates, suggesting PCN may be the most appropriate index to select genotypes. The cultivars were grouped into four groups using molecular markers. Based on the PCN index, cultivars assigned to molecular groups 1 (‘IAC Sintonia’, ‘IPR Bem‐te‐vi’, ‘BRS Notável’, ‘IPR Juriti’, and ‘BRSMG Pioneiro’) and 2 (‘IPR Sabiá’, ‘IPR Quero‐Quero’, and ‘IPR Campos Gerais’) were recommend for future crosses aiming at developing cultivars less dependent on N fertilizers.

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Section: Discussionmentioning

confidence: 99%

Genetic variability and nitrogen response indices in common bean (Phaseolus vulgaris) cultivars under contrasting nitrogen environments

et al. 2021

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“…ASV & ASV1 measures based on two IPCAs and utilized 85.9% of G×E interaction sum of squares would be useful for dynamic concept of stability. 8 Both measures recommended (G4, G5, G9) as of stable performance. Values of MASV1 using 97.7% of GxE interactions sum of squares identified G18, G15, G8 genotypes whereas G18, G8, G5 genotypes be of stable yield as per MASV.…”

Section: Behaviour Of Genotypes As Per Blup Based Measuresmentioning

confidence: 99%

Genotype X Environment Interactions of Fodder Barley Genotypes as Estimated by Ammi, Blup and Non Parametric Measures

Verma

Singh

et al. 2022

Curr Agri Res Jour

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Field experiments were carried out at six locations in Northern Hill Zone to evaluate twenty three promising fodder barley genotypes in a randomized complete block design (RCBD) during 2020-21 cropping seasons . Using analytic methods Additive Main Effects and Multiplicative Interactions (AMMI), Best Linear Unbiased Predictor (BLUP) along with Non Parametric compared to decipher the GxE interactions under multi environment trials. Highly significant about 67.5% variations accounted by environments, 14.1% of GxE interactions and marginally 3.2% by the genotypes in the total sum square of variations for yield the present study. AMMI1 explained 53.7%, 32.1% by AMMI2, 6.9% for AMMI3, AMMI4 accounted for 4.8% respectivelyof a total variation. ASV and ASV1 measures considered 85.9% of the total variation identified G4, G5, G9 genotypes. MASV1 exploited 97.7% of interactions favoured for G18, G15, G8 genotypes. BLUP-based settled for G6, G11, G5 genotypes. Non parametric measures found G9, G8, G1 as suitable genotypes. Further non parametric composites measures selected G9, G4, G8 as suitable genotypes. Measures Si1, Si2, Si3, Si4, Si5,Si6 ,Si7, HMPRVG, ASV1, ASV, accounted more in first principal component whereas NPi (1), NPi (2), NPi (3), NPi (4), PRVG, Si1, GM, Mean, Average were major contributors in second principal component. Very tight positive relationships observed for IPC3, IPC1with BLUP based measures GM, HM, PRVG, HMPRVG, Average in one quadrant. CV closely related to Stdev, IPC2, IPC4 in opposite quadrant. ASV, ASV1 expressed very tight association with Si6,Si7 whereas NPi(1) , exhibited close affinity with Si1 , Si4, Si2 ,Si5 values. Methods utilized in study showed high to moderate degree of association among themselves, however non parametric measures would be recommended for multi environment trials.

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“…Understanding stability and adaptability enables the identification of productive, stable, and adaptable genotypes (Silva et al, 2019). However, evaluating GE interaction is one of the most costly aspects of a breeding program (Dias et al, 2018), especially for perennial fruit trees such as T. grandiflorum, where the breeding cycle can last up to 15 years (Alves et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Theobroma Grandiflorum Breeding Optimization Based on Repeatability, Stability and Adaptability Information

Chaves

Alves

Alves³

et al. 2021

Preprint

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The cultivation of Theobroma grandiflorum in the Brazilian Amazon is mainly conducted by family farmers who use a range of different management straegies. Thus, breeding programs of the species must address the challenge of developing cultivars that are adapted to and stable in a variety of cultivation environments. In this context, this study aimed to estimate the optimum number of harvests for genetic selection of T. grandiflorum progenies and identify the most promising ones in terms of productivity, stability, and adaptability. The trials were implemented in three environments, using a randomized complete block design, with 25 full-sib progenies, five replications, and three plants per plot. The traits mean number of fruits/plant, mean fruit production/plant, and rate of infection with witches’ broom (Moniliophthora perniciosa) were evaluated over 11 harvests. The Restricted Maximum Likelihood/Best Linear Unbiased Prediction (REML/BLUP) mixed model method was used to estimate genetic parameters and predict genetic values, which were then applied to assess stability and adaptability. The results show that there is genetic variability among the studied T. grandiflorum progenies and that accurate genetic selection aiming at recombination is effective after three harvests, for recombination, or eleven harvests for identification of recommended progenies. Six progenies were selected that met the requirements for productivity, stability, and adaptability to different cultivation environments. These results can be used to optimize and advance T. grandiflorum breeding programs.

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Genotype x environment interaction, adaptability and stability of ‘Piel de Sapo’ melon hybrids through mixed models

Cited by 5 publications

References 16 publications

Genetic variability and nitrogen response indices in common bean (Phaseolus vulgaris) cultivars under contrasting nitrogen environments

Genetic variability and nitrogen response indices in common bean (Phaseolus vulgaris) cultivars under contrasting nitrogen environments

Genotype X Environment Interactions of Fodder Barley Genotypes as Estimated by Ammi, Blup and Non Parametric Measures

Theobroma Grandiflorum Breeding Optimization Based on Repeatability, Stability and Adaptability Information

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