The Genome Era of Forage Selection: Current Status and Future Directions for Perennial Ryegrass Breeding and Evaluation
Perennial ryegrass (<i>Lolium perenne</i> L.) is a cornerstone forage species in temperate dairy systems worldwide, valued for its high yield potential, nutritive quality, and grazing recovery. However, current regional evaluation systems face challenges in accurately assessing complex t...
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MDPI AG
2025-06-01
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| Online Access: | https://www.mdpi.com/2073-4395/15/6/1494 |
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| author | Jiashuai Zhu Kevin F. Smith Noel O. Cogan Khageswor Giri Joe L. Jacobs |
| author_facet | Jiashuai Zhu Kevin F. Smith Noel O. Cogan Khageswor Giri Joe L. Jacobs |
| author_sort | Jiashuai Zhu |
| collection | DOAJ |
| description | Perennial ryegrass (<i>Lolium perenne</i> L.) is a cornerstone forage species in temperate dairy systems worldwide, valued for its high yield potential, nutritive quality, and grazing recovery. However, current regional evaluation systems face challenges in accurately assessing complex traits like seasonal dry matter yield due to polygenic nature, environmental variability, and lengthy evaluation cycles. This review examines the evolution of perennial ryegrass evaluation systems, from regional frameworks—like Australia’s Forage Value Index (AU-FVI), New Zealand’s Forage Value Index (NZ-FVI), and Ireland’s Pasture Profit Index (PPI)—to advanced genomic prediction (GP) approaches. We discuss prominent breeding frameworks—F2 family, Half-sib family, and Synthetic Population—and their integration with high-throughput genotyping technologies. Statistical models for GP are compared, including marker-based, kernel-based, and non-parametric approaches, highlighting their strengths in capturing genetic complexity. Key research efforts include representative genotyping approaches for heterozygous populations, disentangling endophyte–host interactions, extending prediction to additional economically important traits, and modeling genotype-by-environment (G × E) interactions. The integration of multi-omics data, advanced phenotyping technologies, and environmental modeling offers promising avenues for enhancing prediction accuracy under changing environmental conditions. By discussing the combination of regional evaluation systems with GP, this review provides comprehensive insights for enhancing perennial ryegrass breeding and evaluation programs, ultimately supporting sustainable productivity of the dairy industry in the face of climate challenges. |
| format | Article |
| id | doaj-art-3494c3e16ec046f5a3bb5e5cfbfd31df |
| institution | OA Journals |
| issn | 2073-4395 |
| language | English |
| publishDate | 2025-06-01 |
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| spelling | doaj-art-3494c3e16ec046f5a3bb5e5cfbfd31df2025-08-20T02:24:39ZengMDPI AGAgronomy2073-43952025-06-01156149410.3390/agronomy15061494The Genome Era of Forage Selection: Current Status and Future Directions for Perennial Ryegrass Breeding and EvaluationJiashuai Zhu0Kevin F. Smith1Noel O. Cogan2Khageswor Giri3Joe L. Jacobs4Faculty of Science, The University of Melbourne, Parkville, VIC 3052, AustraliaFaculty of Science, The University of Melbourne, Parkville, VIC 3052, AustraliaAgriculture Victoria Research, AgriBio Centre, 5 Ring Road, Bundoora, VIC 3083, AustraliaAgriculture Victoria Research, AgriBio Centre, 5 Ring Road, Bundoora, VIC 3083, AustraliaFaculty of Science, The University of Melbourne, Parkville, VIC 3052, AustraliaPerennial ryegrass (<i>Lolium perenne</i> L.) is a cornerstone forage species in temperate dairy systems worldwide, valued for its high yield potential, nutritive quality, and grazing recovery. However, current regional evaluation systems face challenges in accurately assessing complex traits like seasonal dry matter yield due to polygenic nature, environmental variability, and lengthy evaluation cycles. This review examines the evolution of perennial ryegrass evaluation systems, from regional frameworks—like Australia’s Forage Value Index (AU-FVI), New Zealand’s Forage Value Index (NZ-FVI), and Ireland’s Pasture Profit Index (PPI)—to advanced genomic prediction (GP) approaches. We discuss prominent breeding frameworks—F2 family, Half-sib family, and Synthetic Population—and their integration with high-throughput genotyping technologies. Statistical models for GP are compared, including marker-based, kernel-based, and non-parametric approaches, highlighting their strengths in capturing genetic complexity. Key research efforts include representative genotyping approaches for heterozygous populations, disentangling endophyte–host interactions, extending prediction to additional economically important traits, and modeling genotype-by-environment (G × E) interactions. The integration of multi-omics data, advanced phenotyping technologies, and environmental modeling offers promising avenues for enhancing prediction accuracy under changing environmental conditions. By discussing the combination of regional evaluation systems with GP, this review provides comprehensive insights for enhancing perennial ryegrass breeding and evaluation programs, ultimately supporting sustainable productivity of the dairy industry in the face of climate challenges.https://www.mdpi.com/2073-4395/15/6/1494perennial ryegrassgenomic predictionregional evaluation systemsforage breedingphenotypinggenotyping |
| spellingShingle | Jiashuai Zhu Kevin F. Smith Noel O. Cogan Khageswor Giri Joe L. Jacobs The Genome Era of Forage Selection: Current Status and Future Directions for Perennial Ryegrass Breeding and Evaluation Agronomy perennial ryegrass genomic prediction regional evaluation systems forage breeding phenotyping genotyping |
| title | The Genome Era of Forage Selection: Current Status and Future Directions for Perennial Ryegrass Breeding and Evaluation |
| title_full | The Genome Era of Forage Selection: Current Status and Future Directions for Perennial Ryegrass Breeding and Evaluation |
| title_fullStr | The Genome Era of Forage Selection: Current Status and Future Directions for Perennial Ryegrass Breeding and Evaluation |
| title_full_unstemmed | The Genome Era of Forage Selection: Current Status and Future Directions for Perennial Ryegrass Breeding and Evaluation |
| title_short | The Genome Era of Forage Selection: Current Status and Future Directions for Perennial Ryegrass Breeding and Evaluation |
| title_sort | genome era of forage selection current status and future directions for perennial ryegrass breeding and evaluation |
| topic | perennial ryegrass genomic prediction regional evaluation systems forage breeding phenotyping genotyping |
| url | https://www.mdpi.com/2073-4395/15/6/1494 |
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