Genomic Breeding of Green Super Rice Varieties and Their Deployment in Asia and Africa

Abstract

Key message The "Green Super Rice" (GSR) project aims to fundamentally transform crop production techniques and promote the development of green agriculture based on functional genomics and breeding of GSR varieties by whole-genome breeding platforms. Abstract Rice (Oryza sativa L.) is one of the leading food crops of the world, and the safe production of rice plays a central role in ensuring food security. However, the conflicts between rice production and environmental resources are becoming increasingly acute. For this reason, scientists in China have proposed the concept of Green Super Rice for promoting resource-saving and environment-friendly rice production, while still achieving a yield increase and quality improvement. GSR is becoming one of the major goals for agricultural research and crop improvement worldwide, which aims to mine and use vital genes associated with superior agronomic traits such as high yield, good quality, nutrient efficiency, and resistance against insects and stresses; establish genomic breeding platforms to breed and apply GSR; and set up resource-saving and environment-friendly cultivation management systems. GSR has been introduced into eight African and eight Asian countries and has contributed significantly to rice cultivation and food security in these countries. This article mainly describes the GSR concept and recent research progress, as well as the significant achievements in GSR breeding and its application.

Grain Yield Performance of Hybrid Rice in Multi-Environment Tests for Thirty-two Years in India

“…It matured in 123 days and yielded on par with the dominant variety Pusa 44. The average productivity per day of PR126 was 61 kg/ha 76 . In AICRIP experiments, a higher level of productivity per day (62 to 63 kg/ha) was recorded with the early maturing and mid-early maturing hybrid F 1 genotypes at several locations and in many experiments (Tables 4-7).…”

Designing Future Crops: Genomics-Assisted Breeding Comes of Age

“…Besides recording high prediction accuracies (0.35-0.78) of the predicted genetic effects (PGE) using validation sets, the potential of PGEs was demonstrated in a broader germplasm context by using 580 exotic germplasm accessions. Expanding genomic predictions to microscopic phenotypes, a follow-up study in maize advocated for implementing double selection based on 'prediction' and 'reliability' to inform decisions while choosing candidates for phenotyping from large gene bank collections [35]. Similarly, Crossa et al [157] assayed 40 000 SNPs on 8416 Mexican landrace accessions and 2403 Iranian landrace accessions of CIMMYT's wheat gene bank to compute prediction accuracies for different traits.…”

“…Based on haplotypes, the 'genomic design' concept was given by Yu et al [35] in the case of 'green super rice'. The genome design concept involves enlisting target genes controlling the phenotypes of interest and the germplasm resources where these genes can be sourced.…”

Prospects for Molecular Breeding in Cotton,Gossypiumspp

“…Based on these marker effect estimates, genomic estimated breeding values (GEBVs) of different individuals/lines will be calculated without actually phenotyping them, which forms the basis of selection (Figure 7). GS empirical studies in maize (Zea mays; [132][133][134][135]), rice (Oryza sativa; [136][137][138][139]), wheat (Triticum aestivum; [140][141][142][143][144]), and sorghum (Sorghum bicolor; [145][146][147]) have all recently shown how GS has become an efficient approach in crop breeding with recent developments in the implementation of various high-density array-based DNA marker technologies and their reduced genotyping costs. There are many marker effects estimation models that have been developed for the GS.…”