天蓬
光合作用
物候学
农学
生物
栽培
环境科学
植物
生物化学
基因组学
基因组
基因
作者
Qingfeng Song,Fusang Liu,Hongyi Bu,Xin‐Guang Zhu
出处
期刊:Plant phenomics
[American Association for the Advancement of Science]
日期:2023-01-01
卷期号:5
被引量:10
标识
DOI:10.34133/plantphenomics.0075
摘要
Crop yield potential is intrinsically related to canopy photosynthesis; therefore, improving canopy photosynthetic efficiency is a major focus of current efforts to enhance crop yield. Canopy photosynthesis rate (Ac) is influenced by several factors, including plant architecture, leaf chlorophyll content, and leaf photosynthetic properties, which interact with each other. Identifying factors that restrict canopy photosynthesis and target adjustments to improve canopy photosynthesis in a specific crop cultivar pose an important challenge for the breeding community. To address this challenge, we developed a novel pipeline that utilizes factorial analysis, canopy photosynthesis modeling, and phenomics data collected using a 64-camera multi-view stereo system, enabling the dissection of the contributions of different factors to differences in canopy photosynthesis between maize cultivars. We applied this method to 2 maize varieties, W64A and A619, and found that leaf photosynthetic efficiency is the primary determinant (17.5% to 29.2%) of the difference in Ac between 2 maize varieties at all stages, and plant architecture at early stages also contribute to the difference in Ac (5.3% to 6.7%). Additionally, the contributions of each leaf photosynthetic parameter and plant architectural trait were dissected. We also found that the leaf photosynthetic parameters were linearly correlated with Ac and plant architecture traits were non-linearly related to Ac. This study developed a novel pipeline that provides a method for dissecting the relationship among individual phenotypes controlling the complex trait of canopy photosynthesis.
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