Improving drought tolerance in maize: Tools and techniques

被引:12
作者
McMillen, Michael S. [1 ]
Mahama, Anthony A. [1 ]
Sibiya, Julia [2 ]
Lubberstedt, Thomas [1 ]
Suza, Walter P. [1 ]
机构
[1] Iowa State Univ, Dept Agron, Ames, IA 50011 USA
[2] Univ KwaZulu Natal, Sch Agr Earth & Environm Sci, Pietermaritzburg, South Africa
关键词
drought tolerance; food security; maize breeding; genomics assisted selection; genome mapping; model-assisted approaches; plant breeding education; QUANTITATIVE TRAIT LOCI; MARKER-ASSISTED SELECTION; ABIOTIC STRESS TOLERANCE; GENOME-WIDE ASSOCIATION; BACKCROSS QTL ANALYSIS; WATER-USE EFFICIENCY; SUB-SAHARAN AFRICA; GRAIN-YIELD; GENETIC-IMPROVEMENT; SECONDARY TRAITS;
D O I
10.3389/fgene.2022.1001001
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Drought is an important constraint to agricultural productivity worldwide and is expected to worsen with climate change. To assist farmers, especially in sub-Saharan Africa (SSA), to adapt to climate change, continuous generation of stress-tolerant and farmer-preferred crop varieties, and their adoption by farmers, is critical to curb food insecurity. Maize is the most widely grown staple crop in SSA and plays a significant role in food security. The aim of this review is to present an overview of a broad range of tools and techniques used to improve drought tolerance in maize. We also present a summary of progress in breeding for maize drought tolerance, while incorporating research findings from disciplines such as physiology, molecular biology, and systems modeling. The review is expected to complement existing knowledge about breeding maize for climate resilience. Collaborative maize drought tolerance breeding projects in SSA emphasize the value of public-private partnerships in increasing access to genomic techniques and useful transgenes. To sustain the impact of maize drought tolerance projects in SSA, there must be complementary efforts to train the next generation of plant breeders and crop scientists.
引用
收藏
页数:13
相关论文
共 129 条
  • [91] Sammons D.J., 1987, EGERTON U RES PAPER, P2
  • [92] Comparative Map and Trait Viewer (CMTV): an integrated bioinformatic tool to construct consensus maps and compare QTL and functional genomics data across genomes and experiments
    Sawkins, MC
    Farmer, AD
    Hoisington, D
    Sullivan, J
    Tolopko, A
    Jiang, Z
    Ribaut, JM
    [J]. PLANT MOLECULAR BIOLOGY, 2004, 56 (03) : 465 - 480
  • [93] Robust negative impacts of climate change on African agriculture
    Schlenker, Wolfram
    Lobell, David B.
    [J]. ENVIRONMENTAL RESEARCH LETTERS, 2010, 5 (01):
  • [94] Quantitative Trait Loci Mapping and Molecular Breeding for Developing Stress Resilient Maize for Sub-Saharan Africa
    Semagn, Kassa
    Beyene, Yoseph
    Babu, Raman
    Nair, Sudha
    Gowda, Manje
    Das, Biswanath
    Tarekegne, Amsal
    Mugo, Stephen
    Mahuku, George
    Worku, Mosisa
    Warburton, Marilyn L.
    Olsen, Mike
    Prasanna, B. M.
    [J]. CROP SCIENCE, 2015, 55 (04) : 1449 - 1459
  • [95] Meta-analyses of QTL for grain yield and anthesis silking interval in 18 maize populations evaluated under water-stressed and well-watered environments
    Semagn, Kassa
    Beyene, Yoseph
    Warburton, Marilyn L.
    Tarekegne, Amsal
    Mugo, Stephen
    Meisel, Barbara
    Sehabiague, Pierre
    Prasanna, Boddupalli M.
    [J]. BMC GENOMICS, 2013, 14
  • [96] Seneviratne SI, 2012, MANAGING THE RISKS OF EXTREME EVENTS AND DISASTERS TO ADVANCE CLIMATE CHANGE ADAPTATION, P109
  • [97] Genetic association mapping identifies single nucleotide polymorphisms in genes that affect abscisic acid levels in maize floral tissues during drought
    Setter, Tim L.
    Yan, Jianbing
    Warburton, Marilyn
    Ribaut, Jean-Marcel
    Xu, Yunbi
    Sawkins, Mark
    Buckler, Edward S.
    Zhang, Zhiwu
    Gore, Michael A.
    [J]. JOURNAL OF EXPERIMENTAL BOTANY, 2011, 62 (02) : 701 - 716
  • [98] Characterising production environments for maize in eastern and southern Africa using the APSIM Model
    Seyoum, Solomon
    Chauhan, Yash
    Rachaputi, Rao
    Fekybelu, Solomon
    Prasanna, Boddupalli
    [J]. AGRICULTURAL AND FOREST METEOROLOGY, 2017, 247 : 445 - 453
  • [99] ARGOS8 variants generated by CRISPR-Cas9 improve maize grain yield under field drought stress conditions
    Shi, Jinrui
    Gao, Huirong
    Wang, Hongyu
    Lafitte, H. Renee
    Archibald, Rayeann L.
    Yang, Meizhu
    Hakimi, Salim M.
    Mo, Hua
    Habben, Jeffrey E.
    [J]. PLANT BIOTECHNOLOGY JOURNAL, 2017, 15 (02) : 207 - 216
  • [100] Crops that feed the world 6. Past successes and future challenges to the role played by maize in global food security
    Shiferaw, Bekele
    Prasanna, Boddupalli M.
    Hellin, Jonathan
    Baenziger, Marianne
    [J]. FOOD SECURITY, 2011, 3 (03) : 307 - 327