Theme 2-2: Forage Production and Utilization--Poster Sessions
Description
Megathyrsus maximus (Jacq.) B.K. Simon & S.W.L. Jacobs is one of the most important grass species cultivated for cattle production in cut and carry systems. There is a need to search for superior hybrids with high potential for mitigation and adaptation to climate change. A big proportion of the M. maximus germplasm, preserved in the CIAT GeneBank has been agronomically characterized and genotypes with desirable traits such as high drought tolerance, high BNI potential (Biological nitrification inhibition), high nutritional quality (biomass production, dry matter, crude protein, acid detergent fiber, neutral detergent fiber and dry matter digestibility) and high seed production have been identified.
The Megathyrsus maximus breeding program at the alliance Bioversity-CIAT (Alliance) started in 2016 following simultaneously two breeding schemes (Recurrent Selection based on Specific Combining Ability (RS-SCA) and Reciprocal Recurrent selection (RRS)). To start of RS-SCA scheme, a highly diverse, synthetic, sexual population was created, followed by the establishment of a factorial design using nine apomictic male testers and 30 sexual mothers. The aim of the factorial design was not only to estimate various genetic parameters, but also to identify the best possible apomictic tester with the best Combining Ability. Simultaneously, in order to start the breeding scheme of RRS, two open pollination blocks were established independently, following the heterotic pattern revealed by a population structure study using SSR markers.
In the future, we aim to apply simulation based R packages to predict the genetic gain in both scenarios, followed by the validation of the predictions with measurement of genetic gain based on field data, when considering the allocation of resources and logistics required in each scenario.
Citation
Hernandez, L. M. and Castiblanco, V., "Current Status and Future Strategy in Megathyrsus maximus Breeding Program at the Alliance Bioversity - CIAT" (2022). IGC Proceedings (1993-2023). 10.
https://uknowledge.uky.edu/igc/24/2-2/10
Included in
Current Status and Future Strategy in Megathyrsus maximus Breeding Program at the Alliance Bioversity - CIAT
Megathyrsus maximus (Jacq.) B.K. Simon & S.W.L. Jacobs is one of the most important grass species cultivated for cattle production in cut and carry systems. There is a need to search for superior hybrids with high potential for mitigation and adaptation to climate change. A big proportion of the M. maximus germplasm, preserved in the CIAT GeneBank has been agronomically characterized and genotypes with desirable traits such as high drought tolerance, high BNI potential (Biological nitrification inhibition), high nutritional quality (biomass production, dry matter, crude protein, acid detergent fiber, neutral detergent fiber and dry matter digestibility) and high seed production have been identified.
The Megathyrsus maximus breeding program at the alliance Bioversity-CIAT (Alliance) started in 2016 following simultaneously two breeding schemes (Recurrent Selection based on Specific Combining Ability (RS-SCA) and Reciprocal Recurrent selection (RRS)). To start of RS-SCA scheme, a highly diverse, synthetic, sexual population was created, followed by the establishment of a factorial design using nine apomictic male testers and 30 sexual mothers. The aim of the factorial design was not only to estimate various genetic parameters, but also to identify the best possible apomictic tester with the best Combining Ability. Simultaneously, in order to start the breeding scheme of RRS, two open pollination blocks were established independently, following the heterotic pattern revealed by a population structure study using SSR markers.
In the future, we aim to apply simulation based R packages to predict the genetic gain in both scenarios, followed by the validation of the predictions with measurement of genetic gain based on field data, when considering the allocation of resources and logistics required in each scenario.
