Dataset on developing climate-smart transplanted rice variety BRRI dhan98 suitable for partially irrigated ecosystem in Bangladesh.

This dataset provides an in-depth analysis of rice yield and grain quality attributes in four successive four years across 27 diverse environments in Bangladesh. The analysis emphasizes assessing the performance of studied genotypes (GEN), environments (ENV), and their interrelations (GEI). The research aim is to detect a stable and adaptive rice cultivar that not only displays high yield, and better grain quality but also has molecular data to know favorable alleles and biotic and abiotic stress-related traits.

Enhancing genetic gain through the application of genomic selection in developing irrigated rice for the favorable ecosystem in Bangladesh.

Increasing selection differential and decreasing cycle time, the rate of genetic improvement can be accelerated. Creating and capturing higher genetic with higher accuracy within the shortest possible time is the prerequisite for enhancing genetic gain for any trait. Comprehensive yield testing at multi-locations at early generations together with the shortest line fixation time can expedite the rapid recycling of parents in the breeding program through recurrent selection.