Varshney, R K (2021) The Plant Genome special issue: Advances in genomic selection and application of machine learning in genomic prediction for crop improvement. The Plant Genome (TSI), 14 (3). pp. 1-4. ISSN 1940-3372
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Abstract
Since Meuwissen et al. (2001) proposed the idea of using genome-wide marker information for prediction of the genetic worth of untested individuals, the concept of genomic selection (GS) has spawned a series of publications over the last two decades in animals and plants alike. Advances in genomic profiling and phenotyping have given a strong impetus to application of GS in plant breeding (Crossa et al., 2017; Varshney et al., 2017). Empirical and simulation studies suggest that GS can improve the rate of genetic gain in plant breeding programs via influencing the various parameters of the breeder's equation (Sinha et al., 2021). Concurrent advances in methods of genomic prediction including parametric and non-parametric have resulted in considerable improvements in the prediction accuracies of different GS models. The rising complexity of datasets emanating from high throughput genotyping, phenotyping and omics systems calls for harnessing the enormous potential of machine learning (ML) tools for prediction of plant performance (Varshney et al., 2021a). This issue on “Advances in genomic selection and application of machine learning in genomic prediction” presents 14 articles from leading experts in this field. Key highlights of these articles are summarized here in this editorial.
| Item Type: | Article |
|---|---|
| Divisions: | Center of Excellence in Genomics and Systems Biology |
| CRP: | UNSPECIFIED |
| Uncontrolled Keywords: | cropimprovement, genomicselection, genomicprediction |
| Subjects: | Others > Crop Improvement Others > Genetics and Genomics |
| Depositing User: | Mr Nagaraju T |
| Date Deposited: | 10 Jul 2024 08:00 |
| Last Modified: | 10 Jul 2024 08:00 |
| URI: | http://oar.icrisat.org/id/eprint/12759 |
| Official URL: | https://acsess.onlinelibrary.wiley.com/doi/10.1002... |
| Projects: | UNSPECIFIED |
| Funders: | UNSPECIFIED |
| Acknowledgement: | R.K.V. is thankful to Dr Abhishek Bohra from ICAR- Indian Institute of Pulses Research, Kanpur for discussions and his help in writing this article. R.K.V. is thankful to the Science & Engineering Research Board of the Department of Science & Technology (Government of India) for providing the J.C. Bose National Fellowship (SB/S9/Z-13/2019). |
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