Digital phenotyping for quantification of genetic diversity in inbred guava (Psidium guajava) families

Krause, Willian; Viana, Alexandre Pío; Cavalcante, Natan Ramos; Ambrósio, Moisés; Santos, Eileen Azevedo; Vieira, Henrique Duarte

doi:10.4238/gmr16019474

Cited by 16 publications

(22 citation statements)

References 21 publications

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“…The geometry descriptor set contributed the most to quantify genetic divergence among the FSF, followed by the color, texture, and physiological descriptor sets (Table 2). These results were similar to those of Krause et al (2017), who found that the seed geometry variable set contributed the most to quantify genetic divergence among guava genotypes.…”

Section: Discussionsupporting

confidence: 89%

“…Digital image analysis is a fast, reliable, and non-destructive technique for phenotyping. It provides accurate information of seed size, shape, texture, and color through digital images to quantify genetic divergence (Santos et al, 2015;Krause et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…Multivariate techniques such as the Ward-Modified Location Model (Ward-MLM) proposed by Franco et al (1998) have been used to quantify genetic divergence. This method allows simultaneous analysis of quantitative and qualitative variables, determines an optimal number of groups, and identifies the probability of allocation of each accession to a given group (Gonçalves et al, 2009;Santos et al, 2014;Krause et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Research Article Digital image analysis to quantify genetic divergence in passion fruit (Passiflora edulis) seeds

Fachi¹,

Krause²,

Vieira³

et al. 2019

Genet. Mol. Res.

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Passion fruit is a native fruit of tropical America, with Brazil being the world's leading producer and consumer of this fruit, with an estimated annual production of 554,598 Mg, and yield of 13,500 kg.ha-1 Phenotyping through digital images has been used to evaluate morphological characteristics of seeds. Knowledge of the degree of genetic divergence plays an important role, as it assists in the adoption of appropriate strategies for improvement in passion fruit populations.. The objective of this work was to estimate the genetic divergence among full-sibling families of passion fruit through morphophysiological characteristics of seeds using the Ward-Modified Location Model (Ward-MLM) method. Seeds of 98 full-sibling families (FSF) of passion fruit from the breeding program of the Mato Grosso State University were evaluated considering physiological descriptors of seeds, using germination and vigor tests; and morphological descriptors of seeds, using a digital imaging seed analysis device and software. We found that the Ward-MLM method was efficient in detecting genetic divergence using seed morphological and physiological descriptors, simultaneously. The descriptors that contributed the most to the genetic divergence among ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 18 (3): gmr18331 L.R. Fachi et al. 2 FSF were those related to seed geometry. This method formed three heterotic groups. Group II had the largest mean emergence speed index (1.106) and seedling emergence percentage (65.8%), and Group III had the largest means of seedling dry weight (4.140 g), radicle length (6.30 mm), germination speed index (2.503), and seed germination percentage (90 %). We conclude that crosses between FSF groups II and III are a good option to improve seed characteristics.

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Research Article Digital image analysis to quantify genetic divergence in passion fruit (Passiflora edulis) seeds

Fachi¹,

Krause²,

Vieira³

et al. 2019

Genet. Mol. Res.

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“…However, the divergence between this genotype and the others may be explained in the analysis of images by the texture variables RunLength: HGRE and RunLength: SRHGE, which, together, contributed with 76% to the importance of traits and responded with differences in the means between genotypes Pe and BC32 (35.7% and 36.7%, respectively). Nevertheless, in a study of diversity of guava progeny through digital seed phenotyping, the variables that most contributed to divergence between the genotypes were the seed geometry traits (Krause et al, 2017).…”

Section: Sj % Valuementioning

confidence: 99%

Contribution of seed traits to the genetic diversity of a segregating population of Passiflora spp.

Torres

Viana

Vieira

et al. 2019

Chil. j. agric. res.

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Genetic diversity can be investigated early using seed traits, an important aspect of sexually propagated species. In this context, plant breeders aim at the production of new varieties using seeds with good germination and vigor. The present study was thus designed to examine the genetic diversity of a segregating population from a cross between Passiflora edulis Sims and P. setacea DC. based on seed morphological-and physiological-quality responses. Seventeen seed morphology variables were evaluated via digital image analysis, and a germination test and four vigor tests were applied for the evaluation of physiological quality. Data were interpreted by multivariate analysis for the evaluation of genetic diversity. The parents were allocated to distinct groups by the dendrogram structured using Euclidean distance, based on the morphological-and physiological-quality traits. The unweighted pair group method using arithmetic averages (UPGMA) clustering method formed three groups, the first one represented by backcrossing 32, the second by P. setacea and the third by a larger number of genotypes (P. edulis, hybrids and other backcrosses). The principal component analysis showed that the first two components explained 61.32% of the variation. The clustering methods were efficient in the evaluation of dissimilarity of genotypes from a segregating population of Passiflora.

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“…Descritores obtidos via análise digital de imagens tem sido utilizado para quantificação da variabilidade genética em programas de melhoramento como o da goiabeira (KRAUSE et al, 2017). Entretanto, ainda não se tem informações sobre a utilização de imagem digital para seleção de descritores utilizando características da semente como tamanho, forma, textura e cor no maracujazeiro azedo.…”

Section: Introductionunclassified

Seleção De Descritores De Sementes De Maracujazeiro Azedo Utilizando Fenotipagem Digital

Ferreira¹,

Krause²,

Faleiro³

et al. 2018

Agrarian

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RESUMO O objetivo desse trabalho foi selecionar descritores de sementes em maracujazeiro obtidos por meio de análise digital de imagem utilizando os componentes principais. Para isto, foram analisados 95 descritores mensurados a partir da análise digital de imagens em sementes de 35 famílias de irmãos completos de maracujazeiro azedo. Foram avaliadas 50 sementes por família. Para avaliação dos descritores foi utilizado o método dos componentes principais e a seleção foi realizada com base em descartar a variável como maior coeficiente em cada componente com autovalor menor que 0,70, de acordo com as pressuposições de Jolliffe e Mardia. Foi possível reduzir o número de descritores, sendo selecionados cinco de cor, seis de geometria e seis de textura. A análise digital de imagem é uma ferramenta viável e eficiente na mensuração de descritores de sementes no maracujazeiro azedo. PALAVRAS-CHAVE: análise digital de imagem, componentes principais, Passiflora edulis L.

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Digital phenotyping for quantification of genetic diversity in inbred guava (Psidium guajava) families

Cited by 16 publications

References 21 publications

Research Article Digital image analysis to quantify genetic divergence in passion fruit (<i>Passiflora</i> <i>edulis</i>) seeds

Research Article Digital image analysis to quantify genetic divergence in passion fruit (<i>Passiflora</i> <i>edulis</i>) seeds

Contribution of seed traits to the genetic diversity of a segregating population of Passiflora spp.

Seleção De Descritores De Sementes De Maracujazeiro Azedo Utilizando Fenotipagem Digital

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