Climate-Smart Rice Breeding

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.

Enlists advanced technologies for developing high-yielding tailored rice varieties Explains modern breeding strategies for breeding rice by integrating omics technologies Covers quantitative and computational genetics involved in rice breeding

Autorentext

Dr. Akansha Singh is presently working as DBT BioCARe Scientist in the Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, Banaras Hindu University, India. She has also worked as a postdoctoral fellow, Mumbai University and as an associate professor, Department of Genetics and Plant Breeding, College of Agriculture, Parul University, India. She has authored numerous national and international publications in journals of repute. She is one of the breeders of a popular rice variety 'Malaviya Manila Sinchit Dhan-1', released and notified by Government of India in March, 2024.

Prof. S. K. Singh is working as a senior professor and Head of the Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, B.H.U., Varanasi, India and has more than 34 years of teaching and research experience. He had been the Vice President of the Indian Society of Genetics and Plant Breeding during 2020 to 2022 at national level. He has developed many crop varieties and five of them have been released/ notified by the Govt. of India and many rice varieties are in the pipeline of release. He has authored more than 130 research publications in the journals of repute.

Dr. Jiban Shrestha is presently working as a scientist at Nepal Agricultural Research Council (NARC), National Plant Breeding and Genetics Research Centre (NPBGRC), Khumaltar, Lalitpur, Nepal. He is a plant breeder and is currently working in rice and maize breeding works. He has published more than 300 journal articles and 5 books. He has been editing/reviewing articles for internationally reputed publishers. Till date he has reviewed more than 550 articles and edited more than 150 articles for renowned journals. He has provided scientific article writing and data analysis training to students and researchers at national and international universities.

Inhalt

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.