Mr.Bean: a comprehensive statistical and visualization application for modeling agricultural field trials data.

breeding experimental designs multi-environmental analysis spatial analysis trial

Journal

Frontiers in plant science
ISSN: 1664-462X
Titre abrégé: Front Plant Sci
Pays: Switzerland
ID NLM: 101568200

Informations de publication

Date de publication:
2023
Historique:
received: 06 09 2023
accepted: 01 12 2023
medline: 18 1 2024
pubmed: 18 1 2024
entrez: 18 1 2024
Statut: epublish

Résumé

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.

Identifiants

pubmed: 38235208
doi: 10.3389/fpls.2023.1290078
pmc: PMC10792065
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1290078

Informations de copyright

Copyright © 2024 Aparicio, Gezan, Ariza-Suarez, Raatz, Diaz, Heilman-Morales and Lobaton.

Déclaration de conflit d'intérêts

Author SG is employed by VSN International, Author AH-M is employed by AES Big Data Pipeline Unit. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Johan Aparicio (J)

Bean Program, Crops for Nutrition and Health, Alliance Bioversity-International Center for Tropical Agriculture (CIAT), Cali, Colombia.

Salvador A Gezan (SA)

Deparment of Statistical Genetics, InternationalVSN, Hemel Hempstead, United Kingdom.

Daniel Ariza-Suarez (D)

Bean Program, Crops for Nutrition and Health, Alliance Bioversity-International Center for Tropical Agriculture (CIAT), Cali, Colombia.

Bodo Raatz (B)

Bean Program, Crops for Nutrition and Health, Alliance Bioversity-International Center for Tropical Agriculture (CIAT), Cali, Colombia.

Santiago Diaz (S)

Bean Program, Crops for Nutrition and Health, Alliance Bioversity-International Center for Tropical Agriculture (CIAT), Cali, Colombia.

Ana Heilman-Morales (A)

Big Data Pipeline Unit, North Dakota State UniversityAES, Fargo, ND, United States.

Juan Lobaton (J)

Bean Program, Crops for Nutrition and Health, Alliance Bioversity-International Center for Tropical Agriculture (CIAT), Cali, Colombia.

Classifications MeSH