Literature DB >> 31981735

Crop Phenomics and High-Throughput Phenotyping: Past Decades, Current Challenges, and Future Perspectives.

Wanneng Yang1, Hui Feng2, Xuehai Zhang3, Jian Zhang2, John H Doonan4, William David Batchelor5, Lizhong Xiong2, Jianbing Yan2.   

Abstract

Since whole-genome sequencing of many crops has been achieved, crop functional genomics studies have stepped into the big-data and high-throughput era. However, acquisition of large-scale phenotypic data has become one of the major bottlenecks hindering crop breeding and functional genomics studies. Nevertheless, recent technological advances provide us potential solutions to relieve this bottleneck and to explore advanced methods for large-scale phenotyping data acquisition and processing in the coming years. In this article, we review the major progress on high-throughput phenotyping in controlled environments and field conditions as well as its use for post-harvest yield and quality assessment in the past decades. We then discuss the latest multi-omics research combining high-throughput phenotyping with genetic studies. Finally, we propose some conceptual challenges and provide our perspectives on how to bridge the phenotype-genotype gap. It is no doubt that accurate high-throughput phenotyping will accelerate plant genetic improvements and promote the next green revolution in crop breeding.
Copyright © 2020 The Author. Published by Elsevier Inc. All rights reserved.

Keywords:  crop phenomics; field phenotyping; genetic studies; high-throughput; root system architecture; yield and quality

Year:  2020        PMID: 31981735     DOI: 10.1016/j.molp.2020.01.008

Source DB:  PubMed          Journal:  Mol Plant        ISSN: 1674-2052            Impact factor:   13.164


  75 in total

Review 1.  Species-independent analytical tools for next-generation agriculture.

Authors:  Tedrick Thomas Salim Lew; Rajani Sarojam; In-Cheol Jang; Bong Soo Park; Naweed I Naqvi; Min Hao Wong; Gajendra P Singh; Rajeev J Ram; Oded Shoseyov; Kazuki Saito; Nam-Hai Chua; Michael S Strano
Journal:  Nat Plants       Date:  2020-11-30       Impact factor: 15.793

2.  Targeted DNA insertion in plants.

Authors:  Oliver Xiaoou Dong; Pamela C Ronald
Journal:  Proc Natl Acad Sci U S A       Date:  2021-04-30       Impact factor: 11.205

Review 3.  Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review.

Authors:  Qinlin Xiao; Xiulin Bai; Chu Zhang; Yong He
Journal:  J Adv Res       Date:  2021-05-12       Impact factor: 10.479

Review 4.  Crop breeding for a changing climate: integrating phenomics and genomics with bioinformatics.

Authors:  Jacob I Marsh; Haifei Hu; Mitchell Gill; Jacqueline Batley; David Edwards
Journal:  Theor Appl Genet       Date:  2021-04-14       Impact factor: 5.699

Review 5.  Improving Genomic Prediction Using High-Dimensional Secondary Phenotypes.

Authors:  Bader Arouisse; Tom P J M Theeuwen; Fred A van Eeuwijk; Willem Kruijer
Journal:  Front Genet       Date:  2021-05-24       Impact factor: 4.599

6.  Using precision phenotyping to inform de novo domestication.

Authors:  Alisdair R Fernie; Saleh Alseekh; Jie Liu; Jianbing Yan
Journal:  Plant Physiol       Date:  2021-07-06       Impact factor: 8.340

Review 7.  Scaling up high-throughput phenotyping for abiotic stress selection in the field.

Authors:  Daniel T Smith; Andries B Potgieter; Scott C Chapman
Journal:  Theor Appl Genet       Date:  2021-06-02       Impact factor: 5.699

8.  Bayesian optimization of multivariate genomic prediction models based on secondary traits for improved accuracy gains and phenotyping costs.

Authors:  Kosuke Hamazaki; Hiroyoshi Iwata
Journal:  Theor Appl Genet       Date:  2021-10-05       Impact factor: 5.699

Review 9.  Biotechnological Approaches for Genetic Improvement of Lemon (Citrus limon (L.) Burm. f.) against Mal Secco Disease.

Authors:  Chiara Catalano; Mario Di Guardo; Gaetano Distefano; Marco Caruso; Elisabetta Nicolosi; Ziniu Deng; Alessandra Gentile; Stefano Giovanni La Malfa
Journal:  Plants (Basel)       Date:  2021-05-17

10.  Dissecting Source-Sink Relationship of Subtending Leaf for Yield and Fiber Quality Attributes in Upland Cotton (Gossypium hirsutum L.).

Authors:  Naimatullah Mangi; Mian Faisal Nazir; Xiaoyan Wang; Muhammad Shahid Iqbal; Zareen Sarfraz; Ghulam Hussain Jatoi; Tahir Mahmood; Qifeng Ma; Fan Shuli
Journal:  Plants (Basel)       Date:  2021-06-04
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