文献类型：期刊文献

英文题名：Leveraging close-range UAV phenotyping and GWAS for enhanced understanding of slash pine growth dynamics

作者：Ding, Xianyin[1] Pelser, Pieter B.[2] Xu, Cong[3] Porth, Ilga[4,5] Cui, Mingming[4,5] El-Kassaby, Yousry A.[6] Diao, Shu[1] Luan, Qifu[1] Li, Yanjie[1]

第一作者：Ding, Xianyin

机构：[1] Centre for Smart Forestry Innovation and Research, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Zhejiang, Hangzhou, 311400, China; [2] School of Biological Sciences, University of Canterbury, Private Bag 4800, Christchurch, 8140, New Zealand; [3] School of Forestry, University of Canterbury, Private Bag 4800, Christchurch, 8140, New Zealand; [4] Department of Wood and Forest Sciences, Laval University, Quebec, Canada; [5] Centre for Forest Research, Université Laval, Quebec, Quebec, Canada; [6] Department of Forest and Conservation Sciences, Faculty of Forestry, Forest Sciences Centre, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada

年份：2025

外文期刊名：Information Processing in Agriculture

收录：EI(收录号：20253118905880);Scopus(收录号：2-s2.0-105011938196)

语种：英文

外文关键词：Antennas - Cell membranes - Cytology - Dynamic response - Forestry - Genes - Imaging systems - Plant diseases - Plants (botany) - Population statistics - Unmanned aerial vehicles (UAV)

摘要：Advances in high-throughput phenotyping and genomics have accelerated our comprehension of plant functional differentiation. Nevertheless, efficiently phenotyping long-lived tree breeding populations and studying their dynamic response to field conditions remains a challenge, hindering genetic dissection and selective breeding efforts. This study refined and employed a newly developed high-efficiency unmanned aerial vehicle (UAV) imaging system to assess the temporal response of a slash pine (Pinus elliottii) breeding population in field conditions quantitatively over 2 years, identifying six strongly interrelated dynamic growth traits. In a genome-wide association study, 34 trait-associated loci explained between 1.1 % and –14.2 % of temporal phenotypic variation. These genes and regulatory loci influence signal reception, transduction, and transcriptional regulation networks in dynamic growth, impacting metabolic pathways such as cell membrane assembly, cell wall degradation, and cell differentiation. The enhanced UAV imaging system facilitates comprehensive analysis of dynamic growth response in trees, aiding in the discovery of informative alleles to unravel the genetic basis of complex phenotypic variation in conifers. ? 2025 The Author(s)