Adaptability, Stability and Multivariate Selection by Mixed Models

Pelegrin, Alan Junior de; Carvalho, Ivan Ricardo; Nunes, Ana Paula Ferreira; Demari, Gustavo Henrique; Szareski, Vinícius Jardel; Barbosa, Mauricio Horbach; Rosa, Tiago Corazza da; Ferrari, Maurício; Nardino, Maicon; Santos, Osmarino Pires dos; Resende, Marcos Deon Vilela de; Souza, Velci Queiróz de; Oliveira, Antônio Costa de; Maia, Luciano Carlos da

doi:10.4236/ajps.2017.813224

Cited by 10 publications

(6 citation statements)

References 14 publications

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“…Most cited analytic measures HMPRVG and HMPRVG*GM marked HS612, HS507 and HPW430 as of high yield and better adaptability across major locations of this zone while HS615 & HS617 for low degree of adaptation. An overall agreement has been observed among analytic measures PRVG, MHVG, MHPRVG, GAI and average yield for the classification of wheat genotypes (Table 3) (de Pelegrin et al 2017). Variations among ranks of genotypes as per analytic adaptability measures observed as per various locations to highlight presence of cross over interactions effects for studied genotypes (Table 4).…”

Section: Analytic Measuressupporting

confidence: 55%

Adaptability Measures for Wheat Genotypes Evaluated under Northern Hills Zone of Country for Irrigated Timely Sown Conditions

Verma¹

2020

IJAEB

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Wheat genotypes were evaluated under multi environment trials for Northern Hills Zone of India to study the adaptability performance. Genotypes HS612, HS507 and HPW430 were of high yield and better adaptability by analytic measures of adaptability based on BLUP values during 2015-16. Two interaction principal components, accounted for 89.9 % of total GxE interaction sum of squares in biplot analysis. HPW428, HS613, VL2020, VL2024 had specific adaptations to Almora and Malan while HS616, HPW423, HPW430, VL2021, HPW426 expressed for Shimla and Khudwani locations. Wheat genotypes HS612, HS507 and HPW430 were cited by analytic measures as per BLUE values. HPW429, HS613, VL2020, VL2024 had specific adaptations to Almora and Malan while HS616, HS618, HPW425, HPW426, HPW430, VL2023, VL2021, HPW426 observed for Shimla and Khudwani. Second year (2017-18) had seen high yield and better adaptability of HS631, HS632, VL2030, VL2025 genotypes as per BLUP values. Biplot analysis expressed specific adaptations of HPW429, HS613, VL2020, VL2024 to Almora and Malan locations. BLUE values based measures showed high yield and better adaptability of HS631, HS632, VL2030, VL2025 genotypes. Biplot analysis while utilizing 79.5 % of total GxE interaction sum of squares exhibited specific adaptations of HPW446, VL907, HS632, VL2025, VL2030 to Almora and Shimla. Stratification of wheat genotypes as per BLUP values was more efficient than that by BLUE. Biplot analysis exhibited more of GxE interactions sum of squares by first two significant principal components based on BLUP as compared to BLUE values. Highlights m Adaptability of wheat genotypes were studied by analytic measures based on random and fixed effects of genotypes. Further clustering pattern were studied among measures based on biplot analysis.

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Section: Analytic Measuressupporting

confidence: 55%

Adaptability Measures for Wheat Genotypes Evaluated under Northern Hills Zone of Country for Irrigated Timely Sown Conditions

Verma¹

2020

IJAEB

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“…Due to the little information related to the genetic improvement of black oats, for the development of new genotypes, and biometric strategies that facilitate the selection process (Silveira et al 2010), the use of multicharacter selection tools provides the identification of complex characteristics, being able to consider components the selection of characters of the components of yield of the oats, that present indirect improvement in the indicators of physiological quality of the seeds. These methods allow for more homogeneity, minimal losses, assignment of multiple selection strategies and rapid gains during breeding and seed production (Pelegrin et al 2017;Sponchiado 2018;Szareski et al 2018;Carvalho et al 2019;Szareski et al 2019;Corazza et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Akaike criteria and selection of physiological multi-character indexes for the production of black oat seeds

Moura¹,

Carvalho²,

Silva³

et al. 2021

Commun. Plant. Sci.

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The selection of characters provides the identification of complex characteristics, the objective of the work was to use the Akaike criteria and multiple regressions to prove the multi character selection and the interrelationships based on the Phenotypic, Standardized, Willians, Multiplicative, Mulamba and Mock indexes for the selection of black oat genotypes with high physiological potential of seeds. The study was conducted in Fortaleza dos Valos -RS in an experimental design used in randomized blocks with three replications. The trends for the selection of various Step Wise variables and the Akaike criteria are similar for most selection indices. For selection indexes, the phenotypic index and the standardized index correlate with the morphological characteristics, being mainly for the number of tillers. The genetic and multiplicative indices correlate with the characteristics of the seed. The phenotypic selection index was the one that stood out the most, regardless of the criterion used. This index correlates positively with the number of tillers. To select plants that present superior quality seeds, individuals with characteristics such as smaller panicles and with less spikelet ramifications and less panicle mass are sought. Highlighted Conclusions1. The phenotypic selection index was the one that stood out the most. 2. To obtain quality seeds, plants with smaller panicles, less spiky branching and less panicle mass are sought.

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“…The productive performance of maize hybrids is closely related to biotic and abiotic effects, as well as the intrinsic features of each genotype . The selection of the hybrid that better adapts to environmental conditions, and cultural traits becomes fundamental, as it presents great influence in the final yield (Cruz and Carneiro, 2003;Pelegrin et al, 2017;. According to Miranda Filho et al (1987), hybrids may be classified as single-cross, modified single cross, triple-cross, modified triple cross, double-cross, top cross and intervarietal.…”

Section: Introductionmentioning

confidence: 99%

Path analysis and canonical variables of intervarietal maize hybrids

et al. 2019

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Maize (Zea mays L.) is the cereal most produced in the world, due to its wide scope and utilization in human and animal diet. This study aims to evaluate the agronomic performance of intervarietal maize hybrids, as well as the linear associations, interrelations of cause and effect, and the genotypes dispersion through canonical variates. The experiment was conducted in the agricultural year of 2014/2015. The crosses that originated the hybrids were carried out on the growing season of 2013/2014 and hybrids evaluated on 2014/2015. The hybrids were arranged in randomized blocks, being 13 treatments with five repetitions. The measured characters were: plant height, spike insertion height, stem diameter, spike diameter, spike length, spike mass, number of rows of grains per spike, number of grains per row, cob diameter, cob mass, spike grains mass, mass of a thousand grains, grain length and grain yield. The data were submitted to analysis of variance and mean values compared by the Tukey test at 5% of probability. The Pearson’s linear correlation analysis and path analysis were performed using grain yield as a dependent character. Furthermore, the analysis of canonical variables was carried out. The hybrid H5: G3 X G4 revealed higher grain yield, spike grains mass, number of grains per row and spike diameter. Grain yield of intervarietal hybrids presented positive correlations with the traits such as stem diameter, spike diameter, spike length, number of grains per row, mass of a thousand grains, grain length and spike grains mass. Spike diameter and spike length presented higher direct effects on grain yield of intervarietal hybrids. The canonical variates revealed the formation of five phenotypically distinct groups of intervarietal hybrids.

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Adaptability, Stability and Multivariate Selection by Mixed Models

Cited by 10 publications

References 14 publications

Adaptability Measures for Wheat Genotypes Evaluated under Northern Hills Zone of Country for Irrigated Timely Sown Conditions

Adaptability Measures for Wheat Genotypes Evaluated under Northern Hills Zone of Country for Irrigated Timely Sown Conditions

Akaike criteria and selection of physiological multi-character indexes for the production of black oat seeds

Path analysis and canonical variables of intervarietal maize hybrids

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