Abstract
Producing more food where it is consumed is a key strategy for addressing food security, and therefore, maintaining the stability and potential of rice grain yield under adverse environments is a major research area in crop improvement programs. Drought, salinity, and heat are the most detrimental abiotic stress factors to rice production worldwide. Several successful QTL (quantitative trait locus) mapping and introgression efforts have been carried out in the genetic background of high yielding varieties like IR64, IR72, Swarna, Way Rarem, Nipponbare, and IR29 from locally adapted and known tolerant cultivars like Nagina 22, Apo, DK 151, Pokkali, Nona Bokra, CSR27, Bala, and cultivar 996. Furthermore, with the advancements in big data analysis and bioinformatics, it is now possible to locate meta-QTLs and identify functional candidate genes underlying a QTL region with more confidence. This chapter provides a primer on the basics, methods, available software, and pre-requisites of QTL mapping. Practical considerations in QTL mapping for abiotic stress tolerance, details on developments in the use of QTLs in drought, salinity, and heat stress, and meta-QTLs for developing new varieties are also elaborated.
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