The effect of genotypic variability on the yield and yield components of okra (Abelmoschus esculentus L. Moench) in Thailand

Benchasri, S.; Simla, Sakunkan; Harakotr, Bhornchai

doi:10.35495/ajab.2019.12.597

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…It is not a reliable technique as the morphological characters are highly influenced by the environment. Yield is a complex quantitative trait as it is dependent on other characters that may be misleading while making the selection process less efficient (Dewey and Lu, 1959 ; Ahmad et al, 2021 ), particularly, in the field crops such as sunflower, which is highly cross-pollinating and heterozygous and envisages enormous variations in successive generations (Arshad et al, 2007 ; Benchasri et al, 2020 ). The use of DNA markers can solve this problem as this technique is more reliable because it is not influenced by the environment.…”

Section: Introductionmentioning

confidence: 99%

Molecular markers-based DNA fingerprinting coupled with morphological diversity analysis for prediction of heterotic grouping in sunflower (Helianthus annuus L.)

et al. 2022

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Cultivated sunflower holds a very narrow genetic base and the efficient utilization of available genetic diversity is very important for a successful breeding program. In the present study, 109 sunflower genotypes were assessed for diversity paneling through a combined approach of morphological and molecular markers analysis. Morphological parameters including days to flower initiation, days to flower completion, plant height, stem curvature, number of leaves per plant, leaf area, head diameter, hundred seed weight, and seed yield per plant were studied. Simple sequence repeats (40 DNA markers) were deployed for diversity profiling. Data were analyzed by both univariate and multivariate statistics. SD and coefficient of variation confirm the presence of significant amounts of genetic variation for all the morphological parameters. Cluster Analysis and Principal Component Analysis further confirm the presence of distinct grouping patterns in the studied material. Cluster analysis of both morphological and molecular analysis revealed that restorer lines tend to group separately from A, B, and open-pollinated lines. Further grouping, at the sub-cluster level, revealed six distinct sub-clusters in each of the two major clusters. In total, 12 genotypes, 6 CMS lines (CMS-HAP-12, CMS-HAP-54, CMS-HAP-56, CMS-HAP-99, CMS-HAP-111, and CMS-HAP-112) and 6 restorer lines (RHP-38, RHP-41, RHP-53, RHP-68, RHP-69, and RHP-71) could be used as potential parents for hybrid development. As genotypes of similar genetic backgrounds tend to group closer, it is deduced that one genotype with the highest seed yield per plant could be used for further hybrid breeding programs in sunflowers.

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Section: Introductionmentioning

confidence: 99%

Molecular markers-based DNA fingerprinting coupled with morphological diversity analysis for prediction of heterotic grouping in sunflower (Helianthus annuus L.)

et al. 2022

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“…Pedigree analysis can only reflect the relative genetic information between the varieties. Molecular marker analysis using marker loci distributed over the whole genome can more accurately reflect the genetic differences between varieties [47][48][49][50]. According to the hierarchical cluster diagram, all the 79 upland cotton accession can be grouped into five sub-classes at a similarity index of 0.57.…”

Section: Discussionmentioning

confidence: 99%

Use of SSR Markers for the Exploration of Genetic Diversity and DNA Finger-Printing in Early-Maturing Upland Cotton (Gossypium hirsutum L.) for Future Breeding Program

et al. 2022

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DNA fingerprinting and genetic diversity analysis of 79 early-maturing upland cotton (Gossypium hirsutum L.) cultivars were performed using Simple Sequence Repeat (SSR) molecular markers. Out of 126 pairs of SSR primers, we selected 71 pairs that gave good polymorphisms and clear bands, had good stability, and showed even distribution on the cotton chromosomes, and 142 polymorphic genotypes were amplified. The average number of alleles amplified with the SSR primers was 2.01. The polymorphism information content (PIC) of the markers ranged from 0.1841 to 0.9043, with an average of 0.6494. The results of fingerprint analysis showed that nine varieties had characteristic bands, and at least six primer pairs could be used to completely distinguish all 79 cotton accessions. Using NTSYS-pc 2.11 cluster analysis, the genetic similarity coefficients between the cotton genotypes ranged from 0.3310 to 0.8705, with an average of 0.5861. All cotton accessions were grouped into five categories at a similarity coefficient of 0.57, which was consistent with the pedigree sources. At the same time, the average genetic similarity coefficients of early-maturing upland cotton varieties in China showed a low-high-low pattern of variation over time, revealing the development history of early-maturing upland cotton varieties from the 1980s to the present. This also indirectly reflects that in recent years, China’s cotton breeders have focused on innovation and have continuously broadened the genetic resources for early-maturing upland cotton.

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“…It is a vital sector of national economics as source of employment, local income and foreign exchange earning. Besides being a vegetable, it acts as clarifying agent in jaggery preparation [3] . Okra is native to north eastern Africa in the general area of Ethiopia and Sudan.…”

Section: Introductionmentioning

confidence: 99%

Correlation the incidence of major insect-pest and natural enemies with weather parameters

Kumar¹,

Kumar²,

Veer³

et al. 2020

Int. J. Chem. Stud.

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Major insect pest of okra viz., jassid (Amrasca bigutulla biguttula), whitefly (Bemisia tabaci), and shoot and fruit borer (Earias vittella) damaged heavily during the kharif. The incidence of leafhopper, whitefly, shoot and fruit borer and natural enemies show correlation with weather parameters, minimum temperature showed significantly positive correlation (r = 0.611* and 0.807**) with jassid incidence during both the year of study. Maximum temperature showed non-significant negative correlation with jassid incidence during 2018 and significantly positive correlation during 2019 and correlation values in respective years were (r= -0.234 and 0.836**). Relative humidity and rainfall showed negative nonsignificant correlation with Whitefly incidence during both the years and correlation values in respective years were (r= -0.323, -0.092 and r= -0.562, -0.580). Minimum temperature showed positive significant correlation (r= 0.757** and 0.835**) during both the years. Maximum temperature showed nonsignificant negative correlation with per cent shoot damage during 2018 and significantly positive correlation during 2019 and correlation values in respective years were (r= -0.138 and 0.810**). Whereas, wind speed and sunshine showed positive non-significant correlation (r= 0.040 and 0.171) during first year and negative non-significant correlation (r= -0.373 and -0.064) during second year. minimum temperature and Clubiona sp. showed positive significant correlation (r= 0.438 and 0.493) during both the years.

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The effect of genotypic variability on the yield and yield components of okra (Abelmoschus esculentus L. Moench) in Thailand

Cited by 4 publications

References 19 publications

Molecular markers-based DNA fingerprinting coupled with morphological diversity analysis for prediction of heterotic grouping in sunflower (Helianthus annuus L.)

Molecular markers-based DNA fingerprinting coupled with morphological diversity analysis for prediction of heterotic grouping in sunflower (Helianthus annuus L.)

Use of SSR Markers for the Exploration of Genetic Diversity and DNA Finger-Printing in Early-Maturing Upland Cotton (Gossypium hirsutum L.) for Future Breeding Program

Correlation the incidence of major insect-pest and natural enemies with weather parameters

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