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Mr.Bean: a comprehensive statistical and visualization application for modeling agricultural field trials data.
Aparicio, Johan; Gezan, Salvador A; Ariza-Suarez, Daniel; Raatz, Bodo; Diaz, Santiago; Heilman-Morales, Ana; Lobaton, Juan.
Afiliación
  • Aparicio J; Bean Program, Crops for Nutrition and Health, Alliance Bioversity-International Center for Tropical Agriculture (CIAT), Cali, Colombia.
  • Gezan SA; Deparment of Statistical Genetics, InternationalVSN, Hemel Hempstead, United Kingdom.
  • Ariza-Suarez D; Bean Program, Crops for Nutrition and Health, Alliance Bioversity-International Center for Tropical Agriculture (CIAT), Cali, Colombia.
  • Raatz B; Bean Program, Crops for Nutrition and Health, Alliance Bioversity-International Center for Tropical Agriculture (CIAT), Cali, Colombia.
  • Diaz S; Bean Program, Crops for Nutrition and Health, Alliance Bioversity-International Center for Tropical Agriculture (CIAT), Cali, Colombia.
  • Heilman-Morales A; Big Data Pipeline Unit, North Dakota State UniversityAES, Fargo, ND, United States.
  • Lobaton J; Bean Program, Crops for Nutrition and Health, Alliance Bioversity-International Center for Tropical Agriculture (CIAT), Cali, Colombia.
Front Plant Sci ; 14: 1290078, 2023.
Article en En | MEDLINE | ID: mdl-38235208
ABSTRACT
Crop improvement efforts have exploited new methods for modeling spatial trends using the arrangement of the experimental units in the field. These methods have shown improvement in predicting the genetic potential of evaluated genotypes. However, the use of these tools may be limited by the exposure and accessibility to these products. In addition, these new methodologies often require plant scientists to be familiar with the programming environment used to implement them; constraints that limit data analysis efficiency for decision-making. These challenges have led to the development of Mr.Bean, an accessible and user-friendly tool with a comprehensive graphical visualization interface. The application integrates descriptive analysis, measures of dispersion and centralization, linear mixed model fitting, multi-environment trial analysis, factor analytic models, and genomic analysis. All these capabilities are designed to help plant breeders and scientist working with agricultural field trials make informed decisions more quickly. Mr.Bean is available for download at https//github.com/AparicioJohan/MrBeanApp.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Plant Sci Año: 2023 Tipo del documento: Article País de afiliación: Colombia Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Plant Sci Año: 2023 Tipo del documento: Article País de afiliación: Colombia Pais de publicación: Suiza