Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives

Haiyu Tao; Shan Xu; Yongchao Tian; Zhaofeng Li; Yan Ge; Jiaoping Zhang; Yu Wang; Guodong Zhou; Xiong Deng; Ze Zhang; Yanfeng Ding; Dong Jiang; Qinghua Guo; Shichao Jin

doi:10.1016/j.xplc.2022.100344

Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives

Plant Commun. 2022 Nov 14;3(6):100344. doi: 10.1016/j.xplc.2022.100344. Epub 2022 Jun 2.

Authors

Haiyu Tao¹, Shan Xu¹, Yongchao Tian¹, Zhaofeng Li², Yan Ge¹, Jiaoping Zhang³, Yu Wang¹, Guodong Zhou⁴, Xiong Deng⁵, Ze Zhang², Yanfeng Ding⁶, Dong Jiang⁶, Qinghua Guo⁷, Shichao Jin⁸

Affiliations

¹ Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, National Engineering and Technology Center for Information Agriculture, Collaborative Innovation Centre for Modern Crop Production co-sponsored by Province and Ministry, Nanjing Agricultural University, Address: No. 1 Weigang, Xuanwu District, Nanjing 210095, China.
² The Key Laboratory of Oasis Eco-agriculture, Xinjiang Production and Construction Corps, Agriculture College, Shihezi University, Shihezi 832003, China.
³ State Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Nanjing Agricultural University, Nanjing 210095, China.
⁴ Sanya Research Institute of Nanjing Agriculture University, Sanya 572024, China.
⁵ Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China.
⁶ Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, National Engineering and Technology Center for Information Agriculture, Collaborative Innovation Centre for Modern Crop Production co-sponsored by Province and Ministry, Nanjing Agricultural University, Address: No. 1 Weigang, Xuanwu District, Nanjing 210095, China; Hainan Yazhou Bay Seed Laboratory, Sanya 572025, China; Sanya Research Institute of Nanjing Agriculture University, Sanya 572024, China.
⁷ Institute of Ecology, College of Urban and Environmental Science, Peking University, Beijing 100871, China.
⁸ Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, National Engineering and Technology Center for Information Agriculture, Collaborative Innovation Centre for Modern Crop Production co-sponsored by Province and Ministry, Nanjing Agricultural University, Address: No. 1 Weigang, Xuanwu District, Nanjing 210095, China; Hainan Yazhou Bay Seed Laboratory, Sanya 572025, China; Sanya Research Institute of Nanjing Agriculture University, Sanya 572024, China; Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Sciences, Nanjing University, Nanjing, Jiangsu 210023, China. Electronic address: jinshichao1993@gmail.com.

Abstract

Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of genomics and environment on plants, limiting the progress of smart breeding and precise cultivation. High-throughput plant phenotyping is challenging owing to the spatio-temporal dynamics of traits. Proximal and remote sensing (PRS) techniques are increasingly used for plant phenotyping because of their advantages in multi-dimensional data acquisition and analysis. Substantial progress of PRS applications in PP has been observed over the last two decades and is analyzed here from an interdisciplinary perspective based on 2972 publications. This progress covers most aspects of PRS application in PP, including patterns of global spatial distribution and temporal dynamics, specific PRS technologies, phenotypic research fields, working environments, species, and traits. Subsequently, we demonstrate how to link PRS to multi-omics studies, including how to achieve multi-dimensional PRS data acquisition and processing, how to systematically integrate all kinds of phenotypic information and derive phenotypic knowledge with biological significance, and how to link PP to multi-omics association analysis. Finally, we identify three future perspectives for PRS-based PP: (1) strengthening the spatial and temporal consistency of PRS data, (2) exploring novel phenotypic traits, and (3) facilitating multi-omics communication.

Keywords: breeding; multi-omics; phenotypic traits; phenotyping; plant phenomics; precision cultivation; remote sensing.

Publication types

Review
Research Support, Non-U.S. Gov't

MeSH terms

Crops, Agricultural
Phenomics*
Phenotype
Plant Breeding*
Remote Sensing Technology