作者
Jose Luis Araus, Shawn Carlisle Kefauver, Omar Vergara‐Díaz, Adrian Gracia‐Romero, Fatima Zahra Rezzouk, Joel Segarra, Maria Luisa Buchaillot, Melissa Chang‐Espino, Thomas Vatter, Rut Sanchez‐Bragado, José Armando Fernandez‐Gallego, Maria Dolores Serret, Jordi Bort
发表日期
2022/2
来源
Journal of Integrative Plant Biology
卷号
64
期号
2
页码范围
592-618
简介
High‐throughput crop phenotyping, particularly under field conditions, is nowadays perceived as a key factor limiting crop genetic advance. Phenotyping not only facilitates conventional breeding, but it is necessary to fully exploit the capabilities of molecular breeding, and it can be exploited to predict breeding targets for the years ahead at the regional level through more advanced simulation models and decision support systems. In terms of phenotyping, it is necessary to determined which selection traits are relevant in each situation, and which phenotyping tools/methods are available to assess such traits. Remote sensing methodologies are currently the most popular approaches, even when lab‐based analyses are still relevant in many circumstances. On top of that, data processing and automation, together with machine learning/deep learning are contributing to the wide range of applications for phenotyping …
引用总数
学术搜索中的文章
JL Araus, SC Kefauver, O Vergara‐Díaz… - Journal of Integrative Plant Biology, 2022