首页|High-throughput phenotyping of plant leaf morphological,physiological,and biochemical traits on multiple scales using optical sensing

High-throughput phenotyping of plant leaf morphological,physiological,and biochemical traits on multiple scales using optical sensing

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Acquisition of plant phenotypic information facilitates plant breeding,sheds light on gene action,and can be applied to optimize the quality of agricultural and forestry products.Because leaves often show the fastest responses to external environmental stimuli,leaf phenotypic traits are indicators of plant growth,health,and stress levels.Combination of new imaging sensors,image processing,and data analytics per-mits measurement over the full life span of plants at high temporal resolution and at several organiza-tional levels from organs to individual plants to field populations of plants.We review the optical sensors and associated data analytics used for measuring morphological,physiological,and biochemical traits of plant leaves on multiple scales.We summarize the characteristics,advantages and limitations of optical sensing and data-processing methods applied in various plant phenotyping scenarios.Finally,we discuss the future prospects of plant leaf phenotyping research.This review aims to help researchers choose appropriate optical sensors and data processing methods to acquire plant leaf phenotypes rapidly,accurately,and cost-effectively.

Leaf traitsOptical sensingImage processingMachine learningArtificial intelligence

Huichun Zhang、Lu Wang、Xiuliang Jin、Liming Bian、Yufeng Ge

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College of Mechanical and Electronic Engineering,Nanjing Forestry University,Nanjing 210037,Jiangsu,China

Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources,Nanjing Forestry University,Nanjing 210037,Jiangsu,China

Institute of Crop Sciences,Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology,Ministry of Agriculture,Beijing 100081,China

College of Forestry,Nanjing Forestry University,Nanjing 210037,Jiangsu,China

Co-Innovation Center for Sustainable Forestry in Southern China and Key Laboratory of Forest Genetics & Biotechnology of the Ministry of Education,Nanjing Forestry University,Nanjing 210037,Jiangsu,China

Department of Biological Systems Engineering,University of Nebraska-Lincoln,NE 68583,USA

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National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaJiangsu Province Modern Agricultural Machinery Equipment and Technology Demonstration Promotion ProjectKey Research and Development Program of Jiangsu ProvinceQinglan Project Foundation of Jiangsu province333 Project of Jiangsu Province

3217179032171818NJ2020-18BE2021307

2023

10.1016/j.cj.2023.04.014

作物学报(英文版)

作物学报(英文版)

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ISSN：
年,卷(期)：2023.11(5)
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