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Dataset on genetic variation and trait association in cheeseweed (Malva parviflora L.) genotypes for agronomic traits.
Rahman, Md Marufur; Alam, Md Ashraful; Hasan, Hasibul; Sumi, Mirana Akhter; Haque, Md Maksudul.
Afiliação
  • Rahman MM; Regional Station Rangpur, Bangladesh Institute of Research and Training on Applied Nutrition (BIRTAN), Rangpur, Bangladesh.
  • Alam MA; Plant Breeding Division, Spices Research Center, Bangladesh Agricultural Research Institute (BARI), Bogura, Shibganj, Bangladesh.
  • Hasan H; Department of Agriculture, Rabindra Maitree University (RMU), Kustia, Bangladesh.
  • Sumi MA; Regional Agricultural Research Institute, Bangladesh Agricultural Research Institute (BARI), Moulvibazar, Akbarpur, Bangladesh.
  • Haque MM; Head Office, Bangladesh Institute of Research and Training on Applied Nutrition (BIRTAN), Narayanganj, Araihazar, Bangladesh.
Data Brief ; 45: 108651, 2022 Dec.
Article em En | MEDLINE | ID: mdl-36426013
ABSTRACT
In order to analyze genetic variability, heritability, genetic advance and trait associations in Malva parviflora genotypes for agronomic traits, this paper presented a dataset. Seven agronomic traits variation and genetic parameters, including phenotypic and genotypic variance, genotypic and phenotypic coefficients of variation, broad-sense heritability, genetic advance, traits association, principal component analysis, and heatmap analysis were performed based on phenotypic data. Excel, PBtools, STAR, and R applications were used to analyze the data. There was substantial variation for the traits as revealed by descriptive statistics and variance analysis. Graphical presentation showed for principal component analysis and heatmap analysis. Researchers can use this dataset as guide to their plan for improvement this crop as leafy vegetables.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article