Phenomic selection in soybean breeding
Authors
Đorđević, VukĆeran, Marina
Jaćimović, Simona
Miladinović, Jegor
Vasiljević, Marjana
Ranđelović, Predrag
Marinković, Jelena
Contributors
Vollmann, JohannVasiljević, Marjana
Rittler, Leopold
Miladinović, Jegor
Murphy-Bokern, Donal
Conference object (Published version)
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Phenomic selection is a promising complement and alternative to genomic selection for improving breeding efficiency. The major advantage of using near-infrared spectroscopy (NIRS) to indirectly capture phenotypic variants and predict complex traits is its high-throughput and low cost. Using NIR spectra to predict individual performances in the context of breeding for yield remains relatively novel. Certain wavelengths of NIR light are absorbed by specific chemical bonds that constitute the components of tissues. The relative proportion of each of these bonds within the tissue quantitatively influence the nature of the absorbance or reflection of light at different wavenumbers. Phenomic selection was tested on 206 soybean genotypes, collecting yield and NIRS data. Spectra were obtained from different tissues, grains and dried, milled leaves, measuring absorbance in range 4000 – 10000 cm−1. RR-BLUP model was used for phenomic predictions, considering NIRS data instead of molecular.
Keywords:
NIR spectroscopy / phenomic selection / yield / macromolecules / soybean / breedingSource:
Abstracts, 11th World Soybean Research Conference (WSRC 11), Soybean Research for Sustainable Development, Vienna, 18-23 June 2023, 2023, 206-206Publisher:
- Vienna : University of Natural Resources and Life Sciences (BOKU)
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FiVeRTY - CONF AU - Đorđević, Vuk AU - Ćeran, Marina AU - Jaćimović, Simona AU - Miladinović, Jegor AU - Vasiljević, Marjana AU - Ranđelović, Predrag AU - Marinković, Jelena PY - 2023 UR - http://fiver.ifvcns.rs/handle/123456789/3650 AB - Phenomic selection is a promising complement and alternative to genomic selection for improving breeding efficiency. The major advantage of using near-infrared spectroscopy (NIRS) to indirectly capture phenotypic variants and predict complex traits is its high-throughput and low cost. Using NIR spectra to predict individual performances in the context of breeding for yield remains relatively novel. Certain wavelengths of NIR light are absorbed by specific chemical bonds that constitute the components of tissues. The relative proportion of each of these bonds within the tissue quantitatively influence the nature of the absorbance or reflection of light at different wavenumbers. Phenomic selection was tested on 206 soybean genotypes, collecting yield and NIRS data. Spectra were obtained from different tissues, grains and dried, milled leaves, measuring absorbance in range 4000 – 10000 cm−1. RR-BLUP model was used for phenomic predictions, considering NIRS data instead of molecular. PB - Vienna : University of Natural Resources and Life Sciences (BOKU) C3 - Abstracts, 11th World Soybean Research Conference (WSRC 11), Soybean Research for Sustainable Development, Vienna, 18-23 June 2023 T1 - Phenomic selection in soybean breeding EP - 206 SP - 206 DO - 10.5281/zenodo.7974681 ER -
@conference{ author = "Đorđević, Vuk and Ćeran, Marina and Jaćimović, Simona and Miladinović, Jegor and Vasiljević, Marjana and Ranđelović, Predrag and Marinković, Jelena", year = "2023", abstract = "Phenomic selection is a promising complement and alternative to genomic selection for improving breeding efficiency. The major advantage of using near-infrared spectroscopy (NIRS) to indirectly capture phenotypic variants and predict complex traits is its high-throughput and low cost. Using NIR spectra to predict individual performances in the context of breeding for yield remains relatively novel. Certain wavelengths of NIR light are absorbed by specific chemical bonds that constitute the components of tissues. The relative proportion of each of these bonds within the tissue quantitatively influence the nature of the absorbance or reflection of light at different wavenumbers. Phenomic selection was tested on 206 soybean genotypes, collecting yield and NIRS data. Spectra were obtained from different tissues, grains and dried, milled leaves, measuring absorbance in range 4000 – 10000 cm−1. RR-BLUP model was used for phenomic predictions, considering NIRS data instead of molecular.", publisher = "Vienna : University of Natural Resources and Life Sciences (BOKU)", journal = "Abstracts, 11th World Soybean Research Conference (WSRC 11), Soybean Research for Sustainable Development, Vienna, 18-23 June 2023", title = "Phenomic selection in soybean breeding", pages = "206-206", doi = "10.5281/zenodo.7974681" }
Đorđević, V., Ćeran, M., Jaćimović, S., Miladinović, J., Vasiljević, M., Ranđelović, P.,& Marinković, J.. (2023). Phenomic selection in soybean breeding. in Abstracts, 11th World Soybean Research Conference (WSRC 11), Soybean Research for Sustainable Development, Vienna, 18-23 June 2023 Vienna : University of Natural Resources and Life Sciences (BOKU)., 206-206. https://doi.org/10.5281/zenodo.7974681
Đorđević V, Ćeran M, Jaćimović S, Miladinović J, Vasiljević M, Ranđelović P, Marinković J. Phenomic selection in soybean breeding. in Abstracts, 11th World Soybean Research Conference (WSRC 11), Soybean Research for Sustainable Development, Vienna, 18-23 June 2023. 2023;:206-206. doi:10.5281/zenodo.7974681 .
Đorđević, Vuk, Ćeran, Marina, Jaćimović, Simona, Miladinović, Jegor, Vasiljević, Marjana, Ranđelović, Predrag, Marinković, Jelena, "Phenomic selection in soybean breeding" in Abstracts, 11th World Soybean Research Conference (WSRC 11), Soybean Research for Sustainable Development, Vienna, 18-23 June 2023 (2023):206-206, https://doi.org/10.5281/zenodo.7974681 . .