Sorghum is the world’s fifth most important and versatile dry-land cereal crop, used for food, feed, fodder, and bioethanol production. Forage sorghum is best known for its resilience to heat and drought stress due to its wider adaptability and also as a reservoir of genetic variation for different essential micronutrients. Due to unpredicted climate change, it has become a major source of feed for the semi-arid tropics and dairy-rich countries. Farmers feed crop residues to their cattle, which are reported to be nutritionally deficient. Sorghum breeders are aiming to develop varieties or hybrids with good stem quality, genetic stability, digestibility, crude protein content, sugar content, dry matter yield, and low hydrocyanic acid concentration using conventional and biotechnological tools. The discovery of a draft genome sequence of sorghum enables large-scale re-sequencing to explore broad base genetic resources and genetic diversity, leading to sequence-based breeding for fodder quality traits in sorghum. It is essential to understand the genetic function of different genes associated with different fodder quality traits to identify them. Genomics approaches such as genome-wide association studies (GWAS) with high-throughput genotyping and phenotyping through phenomics tools enable precise identification of the fodder quality responsive genes through marker-trait association analysis. The progressive development of recent genomics tools such as genomic selection (GS), genome editing technologies, and haplotypes or allele mining with advanced bioinformatics tools enables a revolutionary remark in genomics-assisted breeding (GAB) for quality improvement in forage sorghum. Here, in this chapter, we summarize the status, progress, prospects, and challenges of GAB for fodder quality improvement in forage sorghum, which is likely to play a tremendous role in improving global food and nutrition security under climate change and exponential population growth scenarios.

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Genomics-Assisted Breeding for Fodder Quality Improvement in Forage Sorghum

  • Partha Pratim Behera,
  • Ramendra Nath Sarma

摘要

Sorghum is the world’s fifth most important and versatile dry-land cereal crop, used for food, feed, fodder, and bioethanol production. Forage sorghum is best known for its resilience to heat and drought stress due to its wider adaptability and also as a reservoir of genetic variation for different essential micronutrients. Due to unpredicted climate change, it has become a major source of feed for the semi-arid tropics and dairy-rich countries. Farmers feed crop residues to their cattle, which are reported to be nutritionally deficient. Sorghum breeders are aiming to develop varieties or hybrids with good stem quality, genetic stability, digestibility, crude protein content, sugar content, dry matter yield, and low hydrocyanic acid concentration using conventional and biotechnological tools. The discovery of a draft genome sequence of sorghum enables large-scale re-sequencing to explore broad base genetic resources and genetic diversity, leading to sequence-based breeding for fodder quality traits in sorghum. It is essential to understand the genetic function of different genes associated with different fodder quality traits to identify them. Genomics approaches such as genome-wide association studies (GWAS) with high-throughput genotyping and phenotyping through phenomics tools enable precise identification of the fodder quality responsive genes through marker-trait association analysis. The progressive development of recent genomics tools such as genomic selection (GS), genome editing technologies, and haplotypes or allele mining with advanced bioinformatics tools enables a revolutionary remark in genomics-assisted breeding (GAB) for quality improvement in forage sorghum. Here, in this chapter, we summarize the status, progress, prospects, and challenges of GAB for fodder quality improvement in forage sorghum, which is likely to play a tremendous role in improving global food and nutrition security under climate change and exponential population growth scenarios.