Near-infrared spectroscopy to predict provitamin A carotenoids content in maize
Vitamin A deficiency (VAD) is a public health issue worldwide. Provitamin A (PVA) biofortified maize serves as an alternative to help combat VAD. Breeding efforts to develop maize varieties with high PVA carotenoid content combine molecular and phenotypic selection strategies. The phenotypic assessm...
| Autores principales: | , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
MDPI
2022
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| Acceso en línea: | https://hdl.handle.net/10568/126449 |
| _version_ | 1855513489649434624 |
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| author | Rosales Nolasco, Aldo Crossa, José Cuevas, Jaime Cabrera-Soto, Luisa María Dhliwayo, Thanda Ndhlela, Thokozile Palacios Rojas, Natalia |
| author_browse | Cabrera-Soto, Luisa María Crossa, José Cuevas, Jaime Dhliwayo, Thanda Ndhlela, Thokozile Palacios Rojas, Natalia Rosales Nolasco, Aldo |
| author_facet | Rosales Nolasco, Aldo Crossa, José Cuevas, Jaime Cabrera-Soto, Luisa María Dhliwayo, Thanda Ndhlela, Thokozile Palacios Rojas, Natalia |
| author_sort | Rosales Nolasco, Aldo |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Vitamin A deficiency (VAD) is a public health issue worldwide. Provitamin A (PVA) biofortified maize serves as an alternative to help combat VAD. Breeding efforts to develop maize varieties with high PVA carotenoid content combine molecular and phenotypic selection strategies. The phenotypic assessment of carotenoids is currently done using liquid chromatography, a precise but time-and resource-consuming methodology. Using near-infrared spectroscopy (NIRS) could increase the breeding efficiency. This study used ultra-performance liquid chromatography (UPLC) data from 1857 tropical maize genotypes as a training set and NIRS data to do an independent test of a set of 650 genotypes to predict PVA carotenoids using Bayesian and modified partial least square (MPLS) regression models. Both regression methods produced similar prediction accuracies for the total carotenoids (r2 = 0.75), lutein (r2 = 0.55), zeaxanthin (r2 = 0.61), β-carotene (r2 = 0.22) and β-cryptoxanthin (BCX) (r2 = 0.57). These results demonstrate that Bayesian and MPLS regression of BCX on NIRS data can be used to predict BCX content, the current focus on PVA enhancement, and thus offers opportunities for high-throughput phenotyping at a low cost, especially in the early stages of PVA maize breeding pipeline when many genotypes must be screened. |
| format | Journal Article |
| id | CGSpace126449 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | CGSpace1264492025-12-08T10:29:22Z Near-infrared spectroscopy to predict provitamin A carotenoids content in maize Rosales Nolasco, Aldo Crossa, José Cuevas, Jaime Cabrera-Soto, Luisa María Dhliwayo, Thanda Ndhlela, Thokozile Palacios Rojas, Natalia biofortification carotenoids maize zea mays Vitamin A deficiency (VAD) is a public health issue worldwide. Provitamin A (PVA) biofortified maize serves as an alternative to help combat VAD. Breeding efforts to develop maize varieties with high PVA carotenoid content combine molecular and phenotypic selection strategies. The phenotypic assessment of carotenoids is currently done using liquid chromatography, a precise but time-and resource-consuming methodology. Using near-infrared spectroscopy (NIRS) could increase the breeding efficiency. This study used ultra-performance liquid chromatography (UPLC) data from 1857 tropical maize genotypes as a training set and NIRS data to do an independent test of a set of 650 genotypes to predict PVA carotenoids using Bayesian and modified partial least square (MPLS) regression models. Both regression methods produced similar prediction accuracies for the total carotenoids (r2 = 0.75), lutein (r2 = 0.55), zeaxanthin (r2 = 0.61), β-carotene (r2 = 0.22) and β-cryptoxanthin (BCX) (r2 = 0.57). These results demonstrate that Bayesian and MPLS regression of BCX on NIRS data can be used to predict BCX content, the current focus on PVA enhancement, and thus offers opportunities for high-throughput phenotyping at a low cost, especially in the early stages of PVA maize breeding pipeline when many genotypes must be screened. 2022-04-25 2023-01-01T16:18:29Z 2023-01-01T16:18:29Z Journal Article https://hdl.handle.net/10568/126449 en Open Access application/pdf MDPI Rosales, A., Crossa, J., Cuevas, J., Cabrera-Soto, L., Dhliwayo, T., Ndhlela, T., & Palacios-Rojas, N. (2022). Near-Infrared Spectroscopy to Predict Provitamin A Carotenoids Content in Maize. Agronomy, 12(5), 1027. https://doi.org/10.3390/agronomy12051027 |
| spellingShingle | biofortification carotenoids maize zea mays Rosales Nolasco, Aldo Crossa, José Cuevas, Jaime Cabrera-Soto, Luisa María Dhliwayo, Thanda Ndhlela, Thokozile Palacios Rojas, Natalia Near-infrared spectroscopy to predict provitamin A carotenoids content in maize |
| title | Near-infrared spectroscopy to predict provitamin A carotenoids content in maize |
| title_full | Near-infrared spectroscopy to predict provitamin A carotenoids content in maize |
| title_fullStr | Near-infrared spectroscopy to predict provitamin A carotenoids content in maize |
| title_full_unstemmed | Near-infrared spectroscopy to predict provitamin A carotenoids content in maize |
| title_short | Near-infrared spectroscopy to predict provitamin A carotenoids content in maize |
| title_sort | near infrared spectroscopy to predict provitamin a carotenoids content in maize |
| topic | biofortification carotenoids maize zea mays |
| url | https://hdl.handle.net/10568/126449 |
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