生物
遗传建筑学
特质
数量性状位点
拟南芥
生物技术
非生物成分
象形文字
选择(遗传算法)
农林复合经营
农学
作物
生态学
基因
遗传学
计算机科学
人工智能
突变体
程序设计语言
作者
Sophie de Dorlodot,B. P. Forster,Loïc Pagès,Adam H. Price,Roberto Tuberosa,Xavier Draye
标识
DOI:10.1016/j.tplants.2007.08.012
摘要
Abiotic stresses increasingly curtail crop yield as a result of global climate change and scarcity of water and nutrients. One way to minimize the negative impact of these factors on yield is to manipulate root system architecture (RSA) towards a distribution of roots in the soil that optimizes water and nutrient uptake. It is now established that most of the genetic variation for RSA is driven by a suite of quantitative trait loci. As we discuss here, marker-assisted selection and quantitative trait loci cloning for RSA are underway, exploiting genomic resources, candidate genes and the knowledge gained from Arabidopsis, rice and other crops. Nonetheless, efficient and accurate phenotyping, modelling and collaboration with breeders remain important challenges, particularly when defining ideal RSA for different crops and target environments.
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