Better breeding leveraging more biology.

IF 21.2 1区 生物学 Q1 PLANT SCIENCES
Owen M Powell, Lee Hickey, Shunichiro Tomura, Mark Cooper
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引用次数: 0

Abstract

Climate-driven variability is reducing our ability to accurately predict crop performance across environments, limiting genetic gain in breeding programs. Sustained progress requires predictive frameworks that capture plant-environment interactions across diverse genetics and management conditions. Integrating mechanistic insights from plant science into predictive models offers a path to improve the accuracy, precision, and interpretability of breeding decisions under changing environments. We present emerging hierarchical genome-phenome frameworks and outline how they can be leveraged within breeding programs to evaluate how biological knowledge informs predictions across target environments and supports long-term genetic gain.

更好的育种利用更多的生物学。
气候变化正在降低我们在不同环境下准确预测作物性能的能力,限制了育种计划中的遗传增益。持续的进步需要预测框架,能够在不同的遗传和管理条件下捕捉植物与环境的相互作用。将植物科学的机制见解整合到预测模型中,为在不断变化的环境下提高育种决策的准确性、精确性和可解释性提供了一条途径。我们提出了新兴的分层基因组-表型框架,并概述了如何在育种计划中利用它们来评估生物学知识如何为目标环境的预测提供信息,并支持长期遗传增益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Trends in Plant Science
Trends in Plant Science 生物-植物科学
CiteScore
31.30
自引率
2.00%
发文量
196
审稿时长
6-12 weeks
期刊介绍: Trends in Plant Science is the primary monthly review journal in plant science, encompassing a wide range from molecular biology to ecology. It offers concise and accessible reviews and opinions on fundamental plant science topics, providing quick insights into current thinking and developments in plant biology. Geared towards researchers, students, and teachers, the articles are authoritative, authored by both established leaders in the field and emerging talents.
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