Our client is a global agricultural seed company that specialises in the development of improved corn hybrids. With a diverse germplasm collection and extensive breeding programs, they aim to enhance yield, disease resistance, and other important traits in corn varieties. To leverage genetic data effectively and accommodate its future growth, they sought a comprehensive analysis solution. The aim is to incorporate existing genetic data and any future-generated data into integrated analysis models.
To address their needs, our client implemented ASReml-R, a powerful statistical software package designed for genetic evaluation and mixed-effects modelling. ASReml-R was used to analyse the complex data structures of multiple generations andt rials of corn breeding, which included detailed phenotypic and genotypic information.
Accurate genetic parameter estimation: The mixed-effects modelling capabilities of ASReml-R enabled the team to estimate genetic parameters like heritability and genetic correlations with precision. This accuracy is crucial for assessing the potential of different traits for genetic improvement. Unlike other tools that struggle to fit thesecomplex models, ASReml-R excels in providing reliable estimates.
Empowering informed breeding decisions: The estimated breeding values obtained through ASReml-R empowered our client to make more informed decisions regarding parent selection, hybrid combinations, and overall breeding strategies. By understanding the genetic potential of various traits, they could strategically focus on the most promising combinations and therefore increasing the likelihood of developing superiorcorn hybrids.
Handling complex pedigree structures: ASReml's ability to handle intricate pedigree structures was particularly beneficial. Breeding programs often involve complex relationships between individuals, and ASReml-R effortlessly accounted for these complexities. By accurately modelling the genetic relationships within the population, the seed company gained valuable insights into the inheritance patterns of specific traits.
Accounting for environmental factors: ASReml's flexible modelling capabilities allowed our client to account for environmental factors that influence trait expression. By incorporating these factors into their analyses, they could separate genetic and environmental effects accurately. This ability to disentangle the influences of genes and the environment contributed to more precise genetic evaluations.
ASReml-R enabled our client to achieve several positive outcomes, including
ASReml-R is a comprehensive statistical software package specifically designed for genetic evaluation, mixed-effects modelling, multi-trait and genotype-environment interactions. Its specialised features, combined with expert knowledge, empower plant and animal breeders to perform robust statistical analyses, make informed breeding decisions, optimise yield potential, and develop superior varieties or populations more efficiently. ASReml's ability to handle complex data structures, accounting for pedigree relationships and incorporating environmental and design factors makes it an invaluable tool for any organisation involved in genetic evaluation and selection of outstanding genotypes.