Genetic diversity and relationship of husk tomato (Physalis spp.) from East Java Province revealed by SSR markers

Sa’diyah, Halimatus; Ashari, Sumeru; Waluyo, Budi; Soegianto, Andy

doi:10.13057/biodiv/d220124

Cited by 10 publications

(7 citation statements)

References 25 publications

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“…All amplified markers, resulted in 68 polymorphic bands out of 110 clear bands. These results showed high efficacy of microsatellite or SSR markers and thus, can be an efficient and suitable tool for investigation of genetic variations of many species of plant [22,23]. Previous researchers have examined the differences between winter and spring oilseed of Europe and China accessions using SSR markers [24,25].…”

Section: A B C Dmentioning

confidence: 79%

Characterization of Brassica napus (Canola) Germplasm Based on Microsatellite Markers

Asif

Mansoor

Hussain

et al. 2021

BJI

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Brassica napus L. is a major oilseed crop all over the world. The aim of this study was to investigate the genetic diversity of B. napus germplasm by using simple sequence repeats (SSR) markers. In the current study, ten SSR markers were used for studying genetic diversity of ten Brassica cultivars. Out of 110 total bands, 68 bands were polymorphic with 52.11% average polymorphism. Mean value of Nei’s genetic diversity and Polymorphism Information Content was 1.7, and 0.2630, respectively. These mean values show that there are moderate allelic differences between Brassica cultivars. The Nei’s genetic distance among various cultivars was 0.3281 and 0.125 which showed that germplasm of Brassica cultivars are different from each other, which is probably due to anthropogenic interventions and environmental factors. Thus, genetically different lines identified in this study could be employed in breeding programmes to develop higher-quality canola inbred varieties in future.

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Section: A B C Dmentioning

confidence: 79%

Characterization of Brassica napus (Canola) Germplasm Based on Microsatellite Markers

Asif

Mansoor

Hussain

et al. 2021

BJI

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“…Data collection was carried out stepwise in a chronological manner from July to November 2022. The exploration sites were selected primarily using graticule methods (Hijmans et al, 2012) as used in the study of Physalis angulata (Sadiyah et al, 2021) and Pinus taiwanensis (Gao et al, 2015). The graticule method applied perpendicular grids or geographical lines to divide the study area.…”

Section: Data Collectionmentioning

confidence: 99%

Morphological characterization of papaya accessions in Jember through multivariate analysis

Rusdiana

Sa’diyah

Sari

et al. 2023

ipas

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This study aimed to select the most informative morphological descriptors in characterizing and distinguishing papaya accessions in Jember. The multivariate analysis was used to i) determine the closeness between the papaya accessions collected based on morphology descriptors and ii) define a list of sufficient minimum descriptors to distinguish papaya accessions in Jember. Five quantitative and fifteen qualitative descriptors were used in evaluating 23 accessions. The data collected through quantitative descriptors were analyzed by the means of PCAbiplot analysis and qualitative descriptors were analyzed using entropy level. Statistical analysis was carried out by R studio software using two packages, i.e. biotools and factoextra packages. Based on the research results, the first two principal components of the PCAbiplot representation of 23 accessions were able to evaluate 67.18% of the total variability. The accessions located in KALSUK, GUMPUR 1, and GUMPUR 2 had similarities in tree diameter and width of mature leaf characters, while KALPLA, MUMSUM 1, LEDSLA, MUMLEN 1, SUMRO 2, and SUMJAM accessions shared similarities in the length of mature leaf, petiole, and peduncle. The minimum descriptors that could be used to characterize papaya plant accessions in Jember were two quantitative descriptors (tree diameter and length of mature leaf) and three qualitative descriptors (general shape of mature leaf teeth, height to first fruit, and stem color). The combination of quantitativequalitative descriptors allowed the simple and rapid characterization of papaya accession. In addition, it could reduce costs and labor without losing information in the characterization of papaya plants.

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“…There are 3 group of the PIC value, namely highly = > 0.5; moderate = 0.25 > 0.5; and slightly informative = < 0.25 [36], [37].…”

Section: ) Annotation: Fi = Frequency Of Allelementioning

confidence: 99%

Application of RAPD Molecular Technique to Study the Genetic Variations of Citrus in South Sulawesi, Indonesia

Tuwo¹,

Kuswinanti²,

Nasruddin³

et al. 2022

Int. J. Adv. Sci. Eng. Inf. Technol.

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Indonesia is a tropical country with superior local citrus species and varieties. Citrus fruits were very useful for cultivation, especially to meet the nutritional needs of the wider community. A province in Indonesia, namely South Sulawesi is one of the centers for citrus development. A preliminary study showed various cultivated citrus in South Sulawesi namely Mandarin Orange cultivar Selayar, Mandarin Orange cultivar Batu, JC lime, Pummelo Pangkep, tangerine, Santang Madu, Dekopon, lime, and Kaffir lime. This study aims to evaluate genetic diversity at several citrus plantation centers in South Sulawesi using the RAPD technique. The analysis was carried out using five primers. In this study, RAPD primers could be used to characterize the genetic diversity and similarity of thirteen citrus cultivars in South Sulawesi. One informative RAPD primer based on its PIC value was OPC-09. The results of the genetic similarity analysis are presented in the form of a dendrogram. The first cluster consisted of Mandarin Orange cultivar Selayar (Seeded Selayar, Selayar-Selayar, JC-Selayar), JC lime, Mandarin Orange cultivar Batu, Santang Madu, and Pummelo Pangkep (cultivar Pangkep Merah, Pangkep Putih, Pangkep Golla-golla). The second cluster consisted of Mandarin Orange cultivar Selayar (selayar-selayar, JCselayar), Santang Madu, tangerine, Mandarin Orange cultivar Batu, Dekopon, lime, and Kaffir lime. The clusters with the most distant genetic relationship are cluster A with cluster B, with a genetic similarity of 62%. Meanwhile, clusters with the closest genetic relationship are clusters I and II, with 79% genetic similarity.

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Genetic diversity and relationship of husk tomato (Physalis spp.) from East Java Province revealed by SSR markers

Cited by 10 publications

References 25 publications

Characterization of Brassica napus (Canola) Germplasm Based on Microsatellite Markers

Characterization of Brassica napus (Canola) Germplasm Based on Microsatellite Markers

Morphological characterization of papaya accessions in Jember through multivariate analysis

Application of RAPD Molecular Technique to Study the Genetic Variations of Citrus in South Sulawesi, Indonesia

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