Postdoctoral Research Fellow, AI fo
Overview
Seema Yadav is Postdoctoral Fellow with Centre for Animal Science at Queensland Alliance for Agriculture and Food Innovation. Her Ph.D. project was focused on implementing genomic selection to accelerate genetic gains in Australian sugarcane breeding programs. Before joining the UQ, she was working as an international consultant with the Quantitative Genetics cluster at the International rice research institute, Philippines. She has double master's degrees in Mathematics and Statistics. Her research interests include developing novel genomic prediction methods, specifically their ability to capture G x E interaction effects. She had deep interest in machine learning models and optimization techniques within this domain.
Research Interests
- Genomic prediction
- Machine learning models
- Operational research
- Quantitative genetics
Qualifications
- Doctor of Philosophy of Quantitative Genetics, The University of Queensland
Publications
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Journal Article: Use of continuous genotypes for genomic prediction in sugarcane
Yadav, Seema, Ross, Elizabeth M., Wei, Xianming, Liu, Shouye, Nguyen, Loan To, Powell, Owen, Hickey, Lee T., Deomano, Emily, Atkin, Felicity, Voss‐Fels, Kai P. and Hayes, Ben J. (2023). Use of continuous genotypes for genomic prediction in sugarcane. The Plant Genome e20417, e20417. doi: 10.1002/tpg2.20417
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Journal Article: Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies
Yadav, Seema, Ross, Elizabeth M., Wei, Xianming, Powell, Owen, Hivert, Valentin, Hickey, Lee T., Atkin, Felicity, Deomano, Emily, Aitken, Karen S., Voss-Fels, Kai P. and Hayes, Ben J. (2023). Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies. Frontiers in Plant Science, 14 1260517, 1260517. doi: 10.3389/fpls.2023.1260517
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Chen, Chensong, Powell, Owen, Dinglasan, Eric, Ross, Elizabeth M., Yadav, Seema, Wei, Xianming, Atkin, Felicity, Deomano, Emily and Hayes, Ben J. (2023). Genomic prediction with machine learning in sugarcane, a complex highly polyploid clonally propagated crop with substantial non‐additive variation for key traits. The Plant Genome, 16 (4) e20390, 1-13. doi: 10.1002/tpg2.20390
Publications
Journal Article
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Use of continuous genotypes for genomic prediction in sugarcane
Yadav, Seema, Ross, Elizabeth M., Wei, Xianming, Liu, Shouye, Nguyen, Loan To, Powell, Owen, Hickey, Lee T., Deomano, Emily, Atkin, Felicity, Voss‐Fels, Kai P. and Hayes, Ben J. (2023). Use of continuous genotypes for genomic prediction in sugarcane. The Plant Genome e20417, e20417. doi: 10.1002/tpg2.20417
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Yadav, Seema, Ross, Elizabeth M., Wei, Xianming, Powell, Owen, Hivert, Valentin, Hickey, Lee T., Atkin, Felicity, Deomano, Emily, Aitken, Karen S., Voss-Fels, Kai P. and Hayes, Ben J. (2023). Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies. Frontiers in Plant Science, 14 1260517, 1260517. doi: 10.3389/fpls.2023.1260517
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Chen, Chensong, Powell, Owen, Dinglasan, Eric, Ross, Elizabeth M., Yadav, Seema, Wei, Xianming, Atkin, Felicity, Deomano, Emily and Hayes, Ben J. (2023). Genomic prediction with machine learning in sugarcane, a complex highly polyploid clonally propagated crop with substantial non‐additive variation for key traits. The Plant Genome, 16 (4) e20390, 1-13. doi: 10.1002/tpg2.20390
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Yadav, Seema, Ross, Elizabeth, Wei, Xianming, Powell, Owen, Hivert, Valentin, Hickey, Lee T., Atkin, Felicity, Deomano, Emily, Aitken, Karen S., Voss-Fels, Kai P. and Hayes, Ben J. (2022). Genomic mate-allocation strategies exploiting additive and non-additive genetic effects to maximise total clonal performance in sugarcane.
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A linkage disequilibrium-based approach to position unmapped SNPs in crop species
Yadav, Seema, Ross, Elizabeth M., Aitken, Karen S., Hickey, Lee T., Powell, Owen, Wei, Xianming, Voss-Fels, Kai P. and Hayes, Ben J. (2021). A linkage disequilibrium-based approach to position unmapped SNPs in crop species. BMC Genomics, 22 (1) 773, 1-9. doi: 10.1186/s12864-021-08116-w
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Yadav, Seema, Wei, Xianming, Joyce, Priya, Atkin, Felicity, Deomano, Emily, Sun, Yue, Nguyen, Loan T., Ross, Elizabeth M., Cavallaro, Tony, Aitken, Karen S., Hayes, Ben J. and Voss-Fels, Kai P. (2021). Improved genomic prediction of clonal performance in sugarcane by exploiting non-additive genetic effects. Theoretical and Applied Genetics, 134 (7), 2235-2252. doi: 10.1007/s00122-021-03822-1
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Accelerating genetic gain in sugarcane breeding using genomic selection
Yadav, Seema, Jackson, Phillip, Wei, Xianming, Ross, Elizabeth M., Aitken, Karen, Deomano, Emily, Atkin, Felicity, Hayes, Ben J. and Voss-Fels, Kai P. (2020). Accelerating genetic gain in sugarcane breeding using genomic selection. Agronomy, 10 (4) 585, 1-21. doi: 10.3390/agronomy10040585
Other Outputs
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Optimising genomic selection for sugarcane
Yadav, Seema (2023). Optimising genomic selection for sugarcane. PhD Thesis, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland. doi: 10.14264/6d283df
