A data-driven simulation platform to predict cultivars’ performances under uncertain weather conditions

Autor: Gustavo de los Campos, Paulino Pérez-Rodríguez, Matthieu Bogard, David Gouache, José Crossa
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Nature Communications, Vol 11, Iss 1, Pp 1-10 (2020)
Druh dokumentu: article
ISSN: 2041-1723
DOI: 10.1038/s41467-020-18480-y
Popis: Predicting crop performance in environments with limited field testing is challenging. Here the authors combine field experimental, DNA sequence, and weather data to predict genotypes’ future performance. They demonstrate the potential of this approach on a large dataset of wheat grain yield.
Databáze: Directory of Open Access Journals