Literature DB >> 34218290

Breeding rice for a changing climate by improving adaptations to water saving technologies.

Maria Cristina Heredia1, Josefine Kant2, M Asaduzzaman Prodhan3, Shalabh Dixit1, Matthias Wissuwa4.   

Abstract

Climate change is expected to increasingly affect rice production through rising temperatures and decreasing water availability. Unlike other crops, rice is a main contributor to greenhouse gas emissions due to methane emissions from flooded paddy fields. Climate change can therefore be addressed in two ways in rice: through making the crop more climate resilient and through changes in management practices that reduce methane emissions and thereby slow global warming. In this review, we focus on two water saving technologies that reduce the periods lowland rice will be grown under fully flooded conditions, thereby improving water use efficiency and reducing methane emissions. Rice breeding over the past decades has mostly focused on developing high-yielding varieties adapted to continuously flooded conditions where seedlings were raised in a nursery and transplanted into a puddled flooded soil. Shifting cultivation to direct-seeded rice or to introducing non-flooded periods as in alternate wetting and drying gives rise to new challenges which need to be addressed in rice breeding. New adaptive traits such as rapid uniform germination even under anaerobic conditions, seedling vigor, weed competitiveness, root plasticity, and moderate drought tolerance need to be bred into the current elite germplasm and to what extent this is being addressed through trait discovery, marker-assisted selection and population improvement are reviewed.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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Year:  2021        PMID: 34218290     DOI: 10.1007/s00122-021-03899-8

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  52 in total

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Journal:  J Exp Bot       Date:  2004-10-08       Impact factor: 6.992

2.  LEAFPROCESSOR: a new leaf phenotyping tool using contour bending energy and shape cluster analysis.

Authors:  Andreas Backhaus; Asuka Kuwabara; Marion Bauch; Nick Monk; Guido Sanguinetti; Andrew Fleming
Journal:  New Phytol       Date:  2010-04-22       Impact factor: 10.151

3.  Root aeration in rice (Oryza sativa): evaluation of oxygen, carbon dioxide, and ethylene as possible regulators of root acclimatizations.

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Journal:  New Phytol       Date:  2006       Impact factor: 10.151

4.  Root hairs enable high transpiration rates in drying soils.

Authors:  Andrea Carminati; John B Passioura; Mohsen Zarebanadkouki; Mutez A Ahmed; Peter R Ryan; Michelle Watt; Emmanuel Delhaize
Journal:  New Phytol       Date:  2017-07-31       Impact factor: 10.151

5.  Non-destructive phenotyping for early seedling vigor in direct-seeded rice.

Authors:  Annamalai Anandan; Anumalla Mahender; Rameswar Prasad Sah; Lotan Kumar Bose; Hatanath Subudhi; Jitendra Meher; Janga Nagi Reddy; Jauhar Ali
Journal:  Plant Methods       Date:  2020-09-21       Impact factor: 4.993

Review 6.  Back to the future: revisiting MAS as a tool for modern plant breeding.

Authors:  Joshua N Cobb; Partha S Biswas; J Damien Platten
Journal:  Theor Appl Genet       Date:  2018-12-17       Impact factor: 5.699

Review 7.  Enhancing the rate of genetic gain in public-sector plant breeding programs: lessons from the breeder's equation.

Authors:  Joshua N Cobb; Roselyne U Juma; Partha S Biswas; Juan D Arbelaez; Jessica Rutkoski; Gary Atlin; Tom Hagen; Michael Quinn; Eng Hwa Ng
Journal:  Theor Appl Genet       Date:  2019-03-01       Impact factor: 5.699

8.  LAMINA: a tool for rapid quantification of leaf size and shape parameters.

Authors:  Max Bylesjö; Vincent Segura; Raju Y Soolanayakanahally; Anne M Rae; Johan Trygg; Petter Gustafsson; Stefan Jansson; Nathaniel R Street
Journal:  BMC Plant Biol       Date:  2008-07-22       Impact factor: 4.215

9.  Dynamic quantitative trait loci analysis of seed reserve utilization during three germination stages in rice.

Authors:  Xinxin Cheng; Jinping Cheng; Xi Huang; Yanyan Lai; Ling Wang; Wenli Du; Zhoufei Wang; Hongsheng Zhang
Journal:  PLoS One       Date:  2013-11-11       Impact factor: 3.240

10.  Mining of favorable alleles for seed reserve utilization efficiency in Oryza sativa by means of association mapping.

Authors:  Nour Ali; Dalu Li; Moaz S Eltahawy; Dina Abdulmajid; Lal Bux; Erbao Liu; Xiaojing Dang; Delin Hong
Journal:  BMC Genet       Date:  2020-01-16       Impact factor: 2.797

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  1 in total

1.  Genomic prediction of zinc-biofortification potential in rice gene bank accessions.

Authors:  Mbolatantely Rakotondramanana; Ryokei Tanaka; Juan Pariasca-Tanaka; James Stangoulis; Cécile Grenier; Matthias Wissuwa
Journal:  Theor Appl Genet       Date:  2022-05-26       Impact factor: 5.574

  1 in total

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