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020 _a9789819770984
_9978-981-97-7098-4
024 7 _a10.1007/978-981-97-7098-4
_2doi
050 4 _aSB1-1110
072 7 _aTVK
_2bicssc
072 7 _aTEC003000
_2bisacsh
072 7 _aTVK
_2thema
245 1 0 _aClimate-Smart Rice Breeding
_h[electronic resource] /
_cedited by Akansha Singh, Shravan Kumar Singh, Jiban Shrestha.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXIV, 371 p. 34 illus., 30 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _a1. Climate change impact on rice production and breeding for climate resilient rice -- 2. Untapped rice genetic resources and pre-breeding in genomics era -- 3. Conservation and development of rice germplasm for Natural Farming -- 4. Doubled haploid rice breeding -- 5. Marker assisted breeding for rice improvement -- 6. Genome assisted breeding and genome-wide association studies for rice improvement -- 7. Haplotype-assisted breeding in rice -- 8. Genomic selection for phenotype prediction in rice -- 9. Genome editing for trait-specific improvement in rice -- 10. High throughput phenotyping enabled rice improvement -- 11. Artificial intelligence and machine learning for rice improvement -- 12. Fast forward breeding in rice -- 13. Application of next generation sequencing technology for rice improvement -- 14. Regulatory Framework Of Plant Variety Protection For Modernized Plant Breeding Approaches.
520 _aThis book covers all aspects of smart-breeding technologies in creating novel crop architecture to meet future rice demand. Several advanced crop breeding technologies like, marker-assisted backcross breeding, marker-assisted recurrent selection, genomic assisted breeding, haplotype breeding and genome editing technologies have been introduced and employed for rice productivity improvement. Use of artificial intelligence and machine learning in crop phenotype prediction is paving the way for climate-smart breeding. Chapters in this volume cover all these relevant topics. The global rice demand is estimated to rise to 555 and 827.86 million tons in 2035 for milled rice and paddy, respectively. Enhancing high-nutrition rice production under the pressure of global climate change conditions is a hard task for breeders. Changing climatic scenarios and extreme weather conditions have increased the incidence of various biotic and abiotic stresses. Also, every degree rise in global mean temperature causes 3.2 % reduction in rice yield globally. This creates an urgent need for developing high-yielding rice varieties to tackle the aggravated issue of food security. This book is meant for scientists, professionals, researchers, and students working on enhancing rice production through advanced plant-breeding technologies.
650 0 _aAgronomy.
_969554
650 0 _aAgricultural genome mapping.
_967634
650 0 _aSubsistence farming.
_970015
650 0 _aAgricultural biotechnology.
650 0 _aPlant genetics.
650 1 4 _aAgronomy.
_969554
650 2 4 _aAgricultural Genetics.
_967638
650 2 4 _aSubsistence Agriculture.
_970016
650 2 4 _aAgricultural Biotechnology.
650 2 4 _aPlant Genetics.
700 1 _aSingh, Akansha.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_987557
700 1 _aSingh, Shravan Kumar.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_987558
700 1 _aShrestha, Jiban.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_987559
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819770977
776 0 8 _iPrinted edition:
_z9789819770991
776 0 8 _iPrinted edition:
_z9789819771004
856 4 0 _uhttps://doi.org/10.1007/978-981-97-7098-4
912 _aZDB-2-SBL
912 _aZDB-2-SXB
999 _c64974
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