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QTL and genomic prediction accuracy for grain yield and secondary traits in a maize population under heat and heat-drought stresses

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Title QTL and genomic prediction accuracy for grain yield and secondary traits in a maize population under heat and heat-drought stresses
 
Creator Neiff, Nicolás
González Perez, Lorena
Mendoza Lugo, Jose Alberto
Martínez, Carlos
Kettler, Belén Araceli
Dhliwayo, Thanda
Babu, Raman
Trachsel, Samuel
 
Subject maize
climate change
doubled haploids
plant breeding
drought stress
 
Description Heat and drought stresses negatively affect maize (Zea mays L.) productivity. We aimed to identify the genetic basis of tolerance to heat stress (HS) and combined heat and drought stress (HS+DS) and compare how QTL and whole genome selection (GS) could be leveraged to improve tolerance to both stresses. A set of 97 testcross hybrids derived from a maize bi-parental doubled-haploid population was evaluated during the summer seasons of 2014, 2015, and 2016 in Ciudad Obregon, Sonora, Mexico, under HS and HS+DS. Grain yield (GY) reached 5.7 t ha−1 under HS and 3.0 t ha−1 under HS+DS. Twenty-six QTL were detected across six environments, with LOD scores ranging from 2.03 to 3.86; the QTL explained 8.6% to 18.6% of the observed phenotypic variation. Hyperspectral biomass and structural index (HBSI) had higher genetic correlation with GY for HS (r = 0.97) and HS+DS (r = 0.74), relative to the correlation with crop water mass or greenness indices. Genetic correlations between GY and canopy temperature for HS (r = −0.89) and HS+DS (r = −0.75) or vegetation indices, along with clusters of QTL in bins 1.02, 1.05, and 2.05, underline the importance of these genomic areas for secondary traits associated with general vigor and greenness. Prediction accuracy of the model used for GS had values below those found in previous studies. We found a high-yielding hybrid that was tolerant to HS and HS+DS.
 
Date 2022-11-18
2023-01-19T16:59:54Z
2023-01-19T16:59:54Z
 
Type Journal Article
 
Identifier Neiff, N., González Pérez, L., Mendoza Lugo, J.A., Martínez, C., Kettler, B.A., Dhliwayo, T., Babu, R. and Trachsel, S. 2022. QTL and genomic prediction accuracy for grain yield and secondary traits in a maize population under heat and heat-drought stresses. Journal of Crop Improvement, 1–26.
1542-7528
https://hdl.handle.net/10568/127591
https://doi.org/10.1080/15427528.2022.2145591
 
Language en
 
Rights Copyrighted; all rights reserved
Limited Access
 
Format p. 1-26
 
Publisher Informa UK Limited
 
Source Journal of Crop Improvement