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Climate-smart rice breeding

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Climate-smart rice breeding/ edited by Akansha Singh, Shravan Kumar Singh, Jiban Shrestha.
其他作者:	Singh, Shravan Kumar.
出版者:	Singapore :Springer Nature Singapore : : 2024.,
面頁冊數:	xiv, 371 p. :ill. (chiefly color), digital ;24 cm.
內容註:	1. 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.
Contained By:	Springer Nature eBook
標題:	Rice - Breeding. -
電子資源:	https://doi.org/10.1007/978-981-97-7098-4
ISBN:	9789819770984

Climate-smart rice breeding
Climate-smart rice breeding[electronic resource] /edited by Akansha Singh, Shravan Kumar Singh, Jiban Shrestha. - Singapore :Springer Nature Singapore :2024. - xiv, 371 p. :ill. (chiefly color), digital ;24 cm.

1. 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.

This 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.

ISBN: 9789819770984

Standard No.: 10.1007/978-981-97-7098-4doiSubjects--Topical Terms:

1573180
Rice
--Breeding.

LC Class. No.: SB191.R5

Dewey Class. No.: 633.18

Climate-smart rice breeding
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520 $a This 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.
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