Multivariate analysis to quantify genetic diversity and family selection in sour passion fruit under recurrent selection

Ferreira, Amanda Fernanda Nunes; Krause, Willian; Cordeiro, Maria Helena Menezes; Viana, Alexandre Pío; Santos, Eileen Azevedo; Vieira, Henrique Duarte

doi:10.1007/s10681-020-02740-5

Cited by 5 publications

(2 citation statements)

References 34 publications

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“…In this context, the use of multivariate algorithms aimed at quantifying dissimilarity among individuals is considered an essential tool for the breeding program, as it allows the identification of contrasting genotypes, indicating possible promising crosses and maintaining population variability (Paiva et al, 2014;Silva et al, 2014;Krause et al, 2020;Ferreira et al, 2021). Numerous studies have used external and internal fruit traits to study genetic divergence in breeding programs (Torres et al, 2019;Silva Junior et al, 2022); however, few use flower traits combined with fruit traits.…”

Section: Introductionmentioning

confidence: 99%

Strategies for the next cycles of intrapopulation improvement of sour passion fruit

Fachi

Krause

Lima

et al. 2023

Rev. bras. eng. agríc. ambient.

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In breeding programs, the identification of genetic variability and knowledge of genetic constitutions existing within segregating populations are of fundamental importance for the success and continuation of the program. The present study aimed to quantify the genetic diversity among progenies of a sour passion fruit population based on morphoagronomic variables of flowers and fruits using the Ward-MLM (modified location model) procedure, which was efficient in quantifying genetic diversity and allowed the identification and consistent formation of three groups within the population. Among the groups formed, group I presented the highest means for the variables related to flowers, group II presented the highest values for the variables related to yield, and group III presented the highest means for the variables related to fruit quality. The androgynous length, nectariferous chamber length, anther surface, nectareous chamber length, and stigma surface were the variables that most contributed to the divergence between the evaluated genotypes. Crosses between groups II and III genotypes are promising for the next cycle, contributing to increased production and improvement of the physical and chemical quality of fruits.

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Section: Introductionmentioning

confidence: 99%

Strategies for the next cycles of intrapopulation improvement of sour passion fruit

Fachi

Krause

Lima

et al. 2023

Rev. bras. eng. agríc. ambient.

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“…Multivariate analysis effectively quantified the genetic variation of the population, yielding sufficient data for selection based on genetic distance. The more families that are chosen in a new selection cycle, the less the genetic variability is or was altered [10]. The effectiveness of choosing doubled-haploid rice lines that are tolerant to salinity improves with the use of a selection index based on multivariate analysis [11].…”

Section: Introductionmentioning

confidence: 99%

Maintaining and Improving Peas (Pisum sativum L.) CV. Master Pea (Local Cultivar) Using UPOV Descriptor and Multivariate Analysis in the Vegetable Seed Production Field

Hamed

Amal

Tarek

2023

JEAI

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Although peas cv. master pea was registered more than 25 years ago in Egypt, this variety showed a remarkable superiority over the varieties grown in all governorates of Egypt in terms of production, quality, and environmental adaptation to climate changes. This study intends to assess this cultivar's genetic and environmental traits, and to determine the degree of its deterioration over time to develop an appropriate plan for the maintenance, improvement, and conservation of this strategic variety to withstand changes in climatic conditions in Egypt. Many types of research have been conducted on the study and production of new varieties and lines of peas in Egypt; yet there is a dearth of multivariate analysis as a technique that can combine all variances for all examined qualities using statistics that rely on the algebra of matrices and extract statistical markers from which the researcher can make an appropriate selection program within cultivars without causing genetic erosion. The present experiment was conducted to achieve the following objectives: to monitor the performance of growth traits in the Master pea cultivar using multivariate analysis and UPOV descriptor; evaluation of yield characteristics, seed yield, and quality of Master pea cultivar using multivariate analysis and UPOV descriptor. In this study, one of the most important results obtained was that the phenotypic diversity within the population (measured using the UPOV descriptor) is an important aspect that reflects genetic diversity and the ability of this genetic diversity to withstand changes in the environment. Natural selection - over the many years of the inherited varieties of countries and societies - affects the diversity of phenotypic traits among the individuals of the population. It can be concluded from this study that the phenotypic traits identified in the UPOV descriptor and data analysis using multivariate analysis can show differences between lines within cultivars. Therefore, we recommend taking advantage of the UPOV descriptor and multivariate analysis as a successful way to obtain differences and relationships between lines in conservation, maintenance, and improvement programs for ancient and promising cultivars in the Arab Republic of Egypt.

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The Passion Fruit Genome

Vieira

Costa²,

Varani³

et al. 2022

Compendium of Plant Genomes

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Multivariate analysis to quantify genetic diversity and family selection in sour passion fruit under recurrent selection

Cited by 5 publications

References 34 publications

Strategies for the next cycles of intrapopulation improvement of sour passion fruit

Strategies for the next cycles of intrapopulation improvement of sour passion fruit

Maintaining and Improving Peas (Pisum sativum L.) CV. Master Pea (Local Cultivar) Using UPOV Descriptor and Multivariate Analysis in the Vegetable Seed Production Field

The Passion Fruit Genome

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