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Asima Gazal Z. A. Dar A. A. Lone I. Abidi G. Ali

Abstract

Abiotic and biotic constraints have widespread yield reducing effects on maize and should receive high priority for maize breeding research. Molecular Breeding offers opportunities for plant breeders to develop cultivars with resilience to such diseases with precision and in less time duration. The term molecular breeding is used to describe several modern breeding strategies, including marker-assisted selection, marker-assisted backcrossing, marker-assisted recurrent selection and genomic selection. Recent advances in maize breeding research have made it possible to identify and map precisely many genes associated with DNA markers which include genes governing resistance to biotic stresses and genes responsible for tolerance to abiotic stresses. Marker assisted selection (MAS) allows monitoring the presence, absence of these genes in breeding populations whereas marker assisted backcross breeding effectively integrates major genes or quantitative trait loci (QTL) with large effect into widely grown adapted varieties. For complex traits where multiple QTLs control the expression, marker assisted recurrent selection (MARS) and genomic selection (GS) are employed to increase precision and to reduce cost of phenotyping and time duration. The biparental mapping populations used in QTL studies in MAS do not readily translate to breeding applications and the statistical methods used to identify target loci and implement MAS have been inadequate for improving polygenic traits controlled by many loci of small effect. Application of GS to breeding populations using high marker densities is emerging as a solution to both of these deficiencies. Hence, molecular breeding approaches offers ample opportunities for developing stress resilient and high-yielding maize cultivars.

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Keywords

Abiotic, Biotic, Maize, Molecular breeding, Stresses

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Gazal, A., Dar, Z. A., Lone, A. A., Abidi, I., & Ali, G. (2015). Molecular breeding for resilience in maize - A review. Journal of Applied and Natural Science, 7(2), 1057-1063. https://doi.org/10.31018/jans.v7i2.731
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