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Near-infrared spectroscopy to predict provitamin A carotenoids content in maize

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Title Near-infrared spectroscopy to predict provitamin A carotenoids content in maize
 
Creator Rosales Nolasco, Aldo
Crossa, José
Cuevas, Jaime
Cabrera-Soto, Luisa María
Dhliwayo, Thanda
Ndhlela, Thokozile
Palacios Rojas, Natalia
 
Subject biofortification
carotenoids
maize
zea mays
 
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.
 
Date 2022-04-25
2023-01-01T16:18:29Z
2023-01-01T16:18:29Z
 
Type Journal Article
 
Identifier Rosales, A., Crossa, J., Cuevas, J., Cabrera-Soto, L., Dhliwayo, T., Ndhlela, T. and Palacios-Rojas, N. 2022. Near-infrared spectroscopy to predict provitamin A carotenoids content in maize. Agronomy, 12(5):1027. https://hdl.handle.net/10883/22079
2073-4395
https://hdl.handle.net/10568/126449
https://hdl.handle.net/10883/22079
https://doi.org/10.3390/agronomy12051027
 
Language en
 
Rights CC-BY-4.0
Open Access
 
Format application/pdf
 
Publisher MDPI
 
Source Agronomy