Stochastic simulation to optimize rice breeding at IRRI - Seck, Fallou; Prakash, Parthiban Thathapalli; Covarrubias-Pazaran, Giovanny; Gueye, Tala; Diédhiou, Ibrahima; Bhosale, Sankalp; Kadaru, Suresh; Bartholomé, Jerome (Frontiers Media, 2024)
Genetic improvement in rice increased yield potential and improved varieties for farmers over the last decades. However, the demand for rice is growing while its cultivation faces challenges posed by climate change. To address these challenges, rice breeding programs need to adopt efficient breeding strategies to provide a steady increase in the rate of genetic gain for major traits. The International Rice Research Institute (IRRI) breeding program has evolved over time to implement faster and more efficient breeding techniques such as rapid generation advance (RGA) and genomic selection (GS). Simulation experiments support data-driven optimization of the breeding program toward the desired rate of genetic gain for key traits.