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Sehgal D, Rathan ND, Özdemir F, Keser M, Akin B, Dababat AA, Koc E, Dreisigacker S, Morgounov A. Genomic wide association study and selective sweep analysis identify genes associated with improved yield under drought in Turkish winter wheat germplasm. Sci Rep 2024; 14:8431. [PMID: 38600135 PMCID: PMC11006659 DOI: 10.1038/s41598-024-57469-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 03/18/2024] [Indexed: 04/12/2024] Open
Abstract
A panel comprising of 84 Turkish winter wheat landraces (LR) and 73 modern varieties (MV) was analyzed with genome wide association study (GWAS) to identify genes/genomic regions associated with increased yield under favorable and drought conditions. In addition, selective sweep analysis was conducted to detect signatures of selection in the winter wheat genome driving the differentiation between LR and MV, to gather an understanding of genomic regions linked to adaptation and yield improvement. The panel was genotyped with 25 K wheat SNP array and phenotyped for agronomic traits for two growing seasons (2018 and 2019) in Konya, Turkey. Year 2018 was treated as drought environment due to very low precipitation prior to heading whereas year 2019 was considered as a favorable season. GWAS conducted with SNPs and haplotype blocks using mixed linear model identified 18 genomic regions in the vicinities of known genes i.e., TaERF3-3A, TaERF3-3B, DEP1-5A, FRIZZY PANICLE-2D, TaSnRK23-1A, TaAGL6-A, TaARF12-2A, TaARF12-2B, WAPO1, TaSPL16-7D, TaTGW6-A1, KAT-2B, TaOGT1, TaSPL21-6B, TaSBEIb, trs1/WFZP-A, TaCwi-A1-2A and TaPIN1-7A associated with grain yield (GY) and yield related traits. Haplotype-based GWAS identified five haplotype blocks (H1A-42, H2A-71, H4A-48, H7B-123 and H7B-124), with the favorable haplotypes showing a yield increase of > 700 kg/ha in the drought season. SNP-based GWAS, detected only one larger effect genomic region on chromosome 7B, in common with haplotype-based GWAS. On an average, the percentage variation (PV) explained by haplotypes was 8.0% higher than PV explained by SNPs for all the investigated traits. Selective sweep analysis detected 39 signatures of selection between LR and MV of which 15 were within proximity of known functional genes controlling flowering (PRR-A1, PPR-D1, TaHd1-6B), GY and GY components (TaSus2-2B, TaGS2-B1, AG1-1A/WAG1-1A, DUO-A1, DUO-B1, AG2-3A/WAG2-3A, TaLAX1, TaSnRK210-4A, FBP, TaLAX1, TaPIL1 and AP3-1-7A/WPA3-7A) and 10 regions underlying various transcription factors and regulatory genes. The study outcomes contribute to utilization of LR in breeding winter wheat.
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Affiliation(s)
- Deepmala Sehgal
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mex-Veracruz, El Batan, CP 56237, Veracruz, Mexico.
- Syngenta, Jealott's Hill International Research Centre, Bracknell, Berkshire, RG42 6EY, UK.
| | | | - Fatih Özdemir
- Bahri Dagdas International Agricultural Research Institute, Konya, Turkey
| | - Mesut Keser
- International Center for Agricultural Research in Dry Areas (ICARDA), Ankara, Turkey
| | - Beyhan Akin
- International Maize and Wheat Improvement Center (CIMMYT), Ankara, Turkey
| | | | - Emrah Koc
- International Maize and Wheat Improvement Center (CIMMYT), Ankara, Turkey
| | - Susanne Dreisigacker
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mex-Veracruz, El Batan, CP 56237, Veracruz, Mexico
| | - Alexey Morgounov
- Scientific Production Center of Grain, Shortandy, Astana reg., 010000, Kazakhstan.
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Islam MA, Shorna MNA, Islam S, Biswas S, Biswas J, Islam S, Dutta AK, Uddin MS, Zaman S, Akhtar-E-Ekram M, Syed A, Wong LS, Islam MS, Saleh MA. Hydrogen-rich water: a key player in boosting wheat (Triticum aestivum L.) seedling growth and drought resilience. Sci Rep 2023; 13:22521. [PMID: 38110488 PMCID: PMC10728117 DOI: 10.1038/s41598-023-49973-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 12/14/2023] [Indexed: 12/20/2023] Open
Abstract
In the modern world, wheat, a vital global cereal and the second most consumed, is vulnerable to climate change impacts. These include erratic rainfall and extreme temperatures, endangering global food security. Research on hydrogen-rich water (HRW) has gained momentum in plant and agricultural sciences due to its diverse functions. This study examined the effects of different HRW treatment durations on wheat, revealing that the 4-h treatment had the highest germination rate, enhancing potential, vigor, and germination indexes. This treatment also boosted relative water content, root and shoot weight, and average lengths. Moreover, the 4-h HRW treatment resulted in the highest chlorophyll and soluble protein concentrations in seeds while reducing cell death. The 4-h and 5-h HRW treatments significantly increased H2O2 levels, with the highest NO detected in both root and shoot after 4-h HRW exposure. Additionally, HRW-treated seeds exhibited increased Zn and Fe concentrations, along with antioxidant enzyme activities (CAT, SOD, APX) in roots and shoots. These findings suggest that HRW treatment could enhance wheat seed germination, growth, and nutrient absorption, thereby increasing agricultural productivity. Molecular analysis indicated significant upregulation of the Dreb1 gene with a 4-h HRW treatment. Thus, it shows promise in addressing climate change effects on wheat production. Therefore, HRW treatment could be a hopeful strategy for enhancing wheat plant drought tolerance, requiring further investigation (field experiments) to validate its impact on plant growth and drought stress mitigation.
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Affiliation(s)
- Md Ariful Islam
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | | | - Shirmin Islam
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Suvro Biswas
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Jui Biswas
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Synthia Islam
- Department of Agribusiness, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, 1706, Bangladesh
| | - Amit Kumar Dutta
- Department of Microbiology, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Salah Uddin
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Shahriar Zaman
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Akhtar-E-Ekram
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Asad Syed
- Department of Botany and Microbiology, College of Science, King Saud University, P.O. Box 2455, 11451, Riyadh, Saudi Arabia
| | - Ling Shing Wong
- Faculty of Life and Health Sciences, INTI International University, Putra Nilai, 71800, Nilai, Negeri Sembilan, Malaysia
| | - Md Sayeedul Islam
- Department of Biological Sciences, Graduate School of Science, Osaka University, Machikaneyama‑Cho 1‑1, Toyonaka, Osaka, 560‑0043, Japan.
| | - Md Abu Saleh
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, 6205, Bangladesh.
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Sharma N, Raman H, Wheeler D, Kalenahalli Y, Sharma R. Data-driven approaches to improve water-use efficiency and drought resistance in crop plants. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2023; 336:111852. [PMID: 37659733 DOI: 10.1016/j.plantsci.2023.111852] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Revised: 08/23/2023] [Accepted: 08/29/2023] [Indexed: 09/04/2023]
Abstract
With the increasing population, there lies a pressing demand for food, feed and fibre, while the changing climatic conditions pose severe challenges for agricultural production worldwide. Water is the lifeline for crop production; thus, enhancing crop water-use efficiency (WUE) and improving drought resistance in crop varieties are crucial for overcoming these challenges. Genetically-driven improvements in yield, WUE and drought tolerance traits can buffer the worst effects of climate change on crop production in dry areas. While traditional crop breeding approaches have delivered impressive results in increasing yield, the methods remain time-consuming and are often limited by the existing allelic variation present in the germplasm. Significant advances in breeding and high-throughput omics technologies in parallel with smart agriculture practices have created avenues to dramatically speed up the process of trait improvement by leveraging the vast volumes of genomic and phenotypic data. For example, individual genome and pan-genome assemblies, along with transcriptomic, metabolomic and proteomic data from germplasm collections, characterised at phenotypic levels, could be utilised to identify marker-trait associations and superior haplotypes for crop genetic improvement. In addition, these omics approaches enable the identification of genes involved in pathways leading to the expression of a trait, thereby providing an understanding of the genetic, physiological and biochemical basis of trait variation. These data-driven gene discoveries and validation approaches are essential for crop improvement pipelines, including genomic breeding, speed breeding and gene editing. Herein, we provide an overview of prospects presented using big data-driven approaches (including artificial intelligence and machine learning) to harness new genetic gains for breeding programs and develop drought-tolerant crop varieties with favourable WUE and high-yield potential traits.
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Affiliation(s)
- Niharika Sharma
- NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW 2800, Australia.
| | - Harsh Raman
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW 2650, Australia
| | - David Wheeler
- NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW 2800, Australia
| | - Yogendra Kalenahalli
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad, Telangana 502324, India
| | - Rita Sharma
- Department of Biological Sciences, BITS Pilani, Pilani Campus, Rajasthan 333031, India
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Anshori MF, Dirpan A, Sitaresmi T, Rossi R, Farid M, Hairmansis A, Sapta Purwoko B, Suwarno WB, Nugraha Y. An overview of image-based phenotyping as an adaptive 4.0 technology for studying plant abiotic stress: A bibliometric and literature review. Heliyon 2023; 9:e21650. [PMID: 38027954 PMCID: PMC10660044 DOI: 10.1016/j.heliyon.2023.e21650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 09/20/2023] [Accepted: 10/25/2023] [Indexed: 12/01/2023] Open
Abstract
Improving the tolerance of crop species to abiotic stresses that limit plant growth and productivity is essential for mitigating the emerging problems of global warming. In this context, imaged data analysis represents an effective method in the 4.0 technology era, where this method has the non-destructive and recursive characterization of plant phenotypic traits as selection criteria. So, the plant breeders are helped in the development of adapted and climate-resilient crop varieties. Although image-based phenotyping has recently resulted in remarkable improvements for identifying the crop status under a range of growing conditions, the topic of its application for assessing the plant behavioral responses to abiotic stressors has not yet been extensively reviewed. For such a purpose, bibliometric analysis is an ideal analytical concept to analyze the evolution and interplay of image-based phenotyping to abiotic stresses by objectively reviewing the literature in light of existing database. Bibliometricy, a bibliometric analysis was applied using a systematic methodology which involved data mining, mining data improvement and analysis, and manuscript construction. The obtained results indicate that there are 554 documents related to image-based phenotyping to abiotic stress until 5 January 2023. All document showed the future development trends of image-based phenotyping will be mainly centered in the United States, European continent and China. The keywords analysis major focus to the application of 4.0 technology and machine learning in plant breeding, especially to create the tolerant variety under abiotic stresses. Drought and saline become an abiotic stress often using image-based phenotyping. Besides that, the rice, wheat and maize as the main commodities in this topic. In conclusion, the present work provides information on resolutive interactions in developing image-based phenotyping to abiotic stress, especially optimizing high-throughput sensors in image-based phenotyping for the future development.
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Affiliation(s)
| | - Andi Dirpan
- Department of Agricultural Technology, Hasanuddin University, Makassar, 90245, Indonesia
- Center of Excellence in Science and Technology on Food Product Diversification, 90245, Makassar, Indonesia
| | - Trias Sitaresmi
- Research Center for Food Crops, Research Organization for Agriculture and Food, National Research and Innovation Agency, 16911, Cibinong, Indonesia
| | - Riccardo Rossi
- Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence (UNIFI), Piazzale delle Cascine 18, 50144, Florence, Italy
| | - Muh Farid
- Department of Agronomy, Hasanuddin University, Makassar, 90245, Indonesia
| | - Aris Hairmansis
- Research Center for Food Crops, Research Organization for Agriculture and Food, National Research and Innovation Agency, 16911, Cibinong, Indonesia
| | - Bambang Sapta Purwoko
- Department of Agronomy and Horticulture, Faculty of Agriculture, IPB University, Bogor, 11680, Indonesia
| | - Willy Bayuardi Suwarno
- Department of Agronomy and Horticulture, Faculty of Agriculture, IPB University, Bogor, 11680, Indonesia
| | - Yudhistira Nugraha
- Research Center for Food Crops, Research Organization for Agriculture and Food, National Research and Innovation Agency, 16911, Cibinong, Indonesia
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Mehravi S, Hanifei M, Gholizadeh A, Khodadadi M. Exploring the quantitative genetics of traits associated with drought tolerance and yield in Pimpinella anisum L. under different water regimes. PLANTA 2023; 257:102. [PMID: 37093410 DOI: 10.1007/s00425-023-04128-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 03/31/2023] [Indexed: 05/03/2023]
Abstract
MAIN CONCLUSION Genetic improvement of seed yield and drought resistance could be simultaneously gained in anise when breeding for drought resistance. Improving the water use efficiency of anise is a primary objective of anise breeding programs aimed at mitigating the impacts of drought stress. This study aimed to determine the predominant mechanisms involved in drought tolerance and investigate the genetic control of associated traits with drought tolerance and higher grain yield. According to these aims, 10 half-diallel hybrids and their five parents were evaluated in both field and greenhouse lysimetric experiments under well-watered and water deficit stress conditions. The results indicated that the inheritance of grain yield is complex and affected by water deficit stress. Similar heritability and genetic architecture were detected for flowering time and percentages of photosynthate partitioned to grain (PPPG) in both well-watered and water deficit stress treatments. Significant negative genetic correlations were observed between grain yield and flowering time, root dry mass, root diameter, root volume, root number, percentages of photosynthate partitioned to shoot, and percentages of photosynthate partitioned to root. Therefore, the selection of low values of these attributes can be used to improve grain yield under drought conditions. In contrast, a positive significant genetic linkage between grain yield and PPPG, chlorophyll content, cell membrane stability, and leaf relative water content reveal selection for high values of these attributes is favored. These attributes could be used as surrogate selection criteria in the early segregating generations. The P1 parent (early ripening parent) contained key genes associated with PPPG and drought escape. It was concluded that improvement of drought tolerance and grain yield could be simultaneously achieved in anise breeding programs.
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Affiliation(s)
- Shaghayegh Mehravi
- Department of Biological Sciences, University of Western Australia, Perth, WA, 6009, Australia.
| | - Mehrdad Hanifei
- Department of Plant Genetics and Breeding, Faculty of Agriculture, Tarbiat Modares University, Tehran, 14115-336, Iran
| | - Amir Gholizadeh
- Crop and Horticultural Science Research Department, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, 4915677555, Iran
| | - Mostafa Khodadadi
- Seed and Plant Improvement Institute, Agricultural Research Education and Extension Organization (AREEO), Karaj, 33151-31359, Iran
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6
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Nehe A, Martinsson UD, Johansson E, Chawade A. Genotype and environment interaction study shows fungal diseases and heat stress are detrimental to spring wheat production in Sweden. PLoS One 2023; 18:e0285565. [PMID: 37163567 PMCID: PMC10171613 DOI: 10.1371/journal.pone.0285565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Accepted: 04/26/2023] [Indexed: 05/12/2023] Open
Abstract
Spring wheat is an economically important crop for Scandinavia and its cultivation is likely to be affected by climate change. The current study focused on wheat yield in recent years, during which climate change-related yield fluctuations have been more pronounced than previously observed. Here, effects of the environment, together with the genotype and fungicide treatment was evaluated. Spring wheat multi-location trials conducted at five locations between 2016 and 2020 were used to understand effects of the climate and fungicides on wheat yield. The results showed that the environment has a strong effect on grain yield, followed by the genotype effect. Moreover, temperature has a stronger (negative) impact than rainfall on grain yield and crop growing duration. Despite a low rainfall in the South compared to the North, the southern production region (PR) 2 had the highest yield performance, indicating the optimal environment for spring wheat production. The fungicide treatment effect was significant in 2016, 2017 and 2020. Overall, yield reduction due to fungal diseases ranged from 0.98 (2018) to 13.3% (2017) and this reduction was higher with a higher yield. Overall yield reduction due to fungal diseases was greater in the South (8.9%) than the North zone (5.3%). The genotypes with higher tolerance to diseases included G4 (KWS Alderon), G14 (WPB 09SW025-11), and G23 (SW 11360) in 2016; G24 (SW 11360), G25 (Millie), and G19 (SEC 526-07-2) in 2017; and G19 (WPB 13SW976-01), G12 (Levels), and G18 (SW 141011) in 2020. The combined best performing genotypes for disease tolerance and stable and higher yield in different locations were KWS Alderon, SEC 526-07-2, and WPB 13SW976-01 with fungicide treatment and WPB Avonmore, SEC 526-07-2, SW 131323 without fungicide treatment. We conclude that the best performing genotypes could be recommended for Scandinavian climatic conditions with or without fungicide application and that developing heat-tolerant varieties for Scandinavian countries should be prioritized.
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Affiliation(s)
- Ajit Nehe
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | | | - Eva Johansson
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Aakash Chawade
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
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Tao H, Xu S, Tian Y, Li Z, Ge Y, Zhang J, Wang Y, Zhou G, Deng X, Zhang Z, Ding Y, Jiang D, Guo Q, Jin S. Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives. PLANT COMMUNICATIONS 2022; 3:100344. [PMID: 35655429 PMCID: PMC9700174 DOI: 10.1016/j.xplc.2022.100344] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 05/08/2022] [Accepted: 05/27/2022] [Indexed: 06/01/2023]
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.
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Affiliation(s)
- Haiyu Tao
- 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
| | - Shan Xu
- 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
| | - Yongchao Tian
- 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
| | - Zhaofeng Li
- The Key Laboratory of Oasis Eco-agriculture, Xinjiang Production and Construction Corps, Agriculture College, Shihezi University, Shihezi 832003, China
| | - Yan Ge
- 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
| | - Jiaoping Zhang
- 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
| | - Yu Wang
- 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
| | - Guodong Zhou
- Sanya Research Institute of Nanjing Agriculture University, Sanya 572024, China
| | - Xiong Deng
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
| | - Ze Zhang
- The Key Laboratory of Oasis Eco-agriculture, Xinjiang Production and Construction Corps, Agriculture College, Shihezi University, Shihezi 832003, China
| | - Yanfeng Ding
- 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
| | - Dong Jiang
- 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
| | - Qinghua Guo
- Institute of Ecology, College of Urban and Environmental Science, Peking University, Beijing 100871, China
| | - Shichao Jin
- 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.
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Roitsch T, Himanen K, Chawade A, Jaakola L, Nehe A, Alexandersson E. Functional phenomics for improved climate resilience in Nordic agriculture. JOURNAL OF EXPERIMENTAL BOTANY 2022; 73:5111-5127. [PMID: 35727101 PMCID: PMC9440434 DOI: 10.1093/jxb/erac246] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 06/06/2022] [Indexed: 05/26/2023]
Abstract
The five Nordic countries span the most northern region for field cultivation in the world. This presents challenges per se, with short growing seasons, long days, and a need for frost tolerance. Climate change has additionally increased risks for micro-droughts and water logging, as well as pathogens and pests expanding northwards. Thus, Nordic agriculture demands crops that are adapted to the specific Nordic growth conditions and future climate scenarios. A focus on crop varieties and traits important to Nordic agriculture, including the unique resource of nutritious wild crops, can meet these needs. In fact, with a future longer growing season due to climate change, the region could contribute proportionally more to global agricultural production. This also applies to other northern regions, including the Arctic. To address current growth conditions, mitigate impacts of climate change, and meet market demands, the adaptive capacity of crops that both perform well in northern latitudes and are more climate resilient has to be increased, and better crop management systems need to be built. This requires functional phenomics approaches that integrate versatile high-throughput phenotyping, physiology, and bioinformatics. This review stresses key target traits, the opportunities of latitudinal studies, and infrastructure needs for phenotyping to support Nordic agriculture.
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Affiliation(s)
- Thomas Roitsch
- Department of Plant and Environmental Sciences, University of Copenhagen, Denmark
- Department of Adaptive Biotechnologies, Global Change Research Institute, Czech Academy of Sciences, Brno, Czechia
| | - Kristiina Himanen
- National Plant Phenotyping Infrastructure, HiLIFE, University of Helsinki, Finland
- Organismal and Evolutionary Biology Research Program, Viikki Plant Science Centre, Faculty of Biological and Environmental Sciences, University of Helsinki, Finland
| | - Aakash Chawade
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Lomma, Sweden
| | - Laura Jaakola
- Climate laboratory Holt, Department of Arctic and Marine Biology, UiT the Arctic University of Norway, Tromsø, Norway
- NIBIO, Norwegian Institute of Bioeconomy Research, Ås, Norway
| | - Ajit Nehe
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Lomma, Sweden
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Kim M, Lee C, Hong S, Kim SL, Baek JH, Kim KH. High-Throughput Phenotyping Methods for Breeding Drought-Tolerant Crops. Int J Mol Sci 2021; 22:ijms22158266. [PMID: 34361030 PMCID: PMC8347144 DOI: 10.3390/ijms22158266] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 07/28/2021] [Accepted: 07/29/2021] [Indexed: 12/28/2022] Open
Abstract
Drought is a main factor limiting crop yields. Modern agricultural technologies such as irrigation systems, ground mulching, and rainwater storage can prevent drought, but these are only temporary solutions. Understanding the physiological, biochemical, and molecular reactions of plants to drought stress is therefore urgent. The recent rapid development of genomics tools has led to an increasing interest in phenomics, i.e., the study of phenotypic plant traits. Among phenomic strategies, high-throughput phenotyping (HTP) is attracting increasing attention as a way to address the bottlenecks of genomic and phenomic studies. HTP provides researchers a non-destructive and non-invasive method yet accurate in analyzing large-scale phenotypic data. This review describes plant responses to drought stress and introduces HTP methods that can detect changes in plant phenotypes in response to drought.
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Affiliation(s)
- Minsu Kim
- National Institute of Agricultural Science, RDA, Wanju 54874, Korea; (M.K.); (C.L.); (S.H.); (S.L.K.); (J.-H.B.)
| | - Chaewon Lee
- National Institute of Agricultural Science, RDA, Wanju 54874, Korea; (M.K.); (C.L.); (S.H.); (S.L.K.); (J.-H.B.)
- Department of Crop Science and Biotechnology, Chonbuk National University, Jeonju 54896, Korea
| | - Subin Hong
- National Institute of Agricultural Science, RDA, Wanju 54874, Korea; (M.K.); (C.L.); (S.H.); (S.L.K.); (J.-H.B.)
| | - Song Lim Kim
- National Institute of Agricultural Science, RDA, Wanju 54874, Korea; (M.K.); (C.L.); (S.H.); (S.L.K.); (J.-H.B.)
| | - Jeong-Ho Baek
- National Institute of Agricultural Science, RDA, Wanju 54874, Korea; (M.K.); (C.L.); (S.H.); (S.L.K.); (J.-H.B.)
| | - Kyung-Hwan Kim
- National Institute of Agricultural Science, RDA, Wanju 54874, Korea; (M.K.); (C.L.); (S.H.); (S.L.K.); (J.-H.B.)
- Correspondence:
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