Genotype × Environment Interactions of Yield Traits in Backcross Introgression Lines Derived from Oryza sativa cv. Swarna/Oryza nivara

Abstract

Advanced backcross introgression lines (BILs) developed from crosses of Oryza sativa var. Swarna/O. nivara accessions were grown and evaluated for yield and related traits. Trials were conducted for consecutive three seasons in field conditions in a randomized complete block design with three replications. Data on yield traits under irrigated conditions were analyzed using the Additive Main Effect and Multiplicative Interaction (AMMI), Genotype and Genotype × Environment Interaction (GGE) and modified rank-sum statistic (YSi) for yield stability. BILs viz., G3 (14S) and G6 (166S) showed yield stability across the seasons along with high mean yield performance. G3 is early in flowering with high yield and has good grain quality and medium height, hence could be recommended for most of the irrigated locations. G6 is a late duration genotype, with strong culm strength, high grain number and panicle weight. G6 has higher yield and stability than Swarna but has Swarna grain type. Among the varieties tested DRRDhan 40 and recurrent parent Swarna showed stability for yield traits across the seasons. The component traits thousand grain weight, panicle weight, panicle length, grain number and plant height explained highest genotypic percentage over environment and interaction factors and can be prioritized to dissect stable QTLs/ genes. These lines were genotyped using microsatellite markers covering the entire rice genome and also using a set of markers linked to previously reported yield QTLs. It was observed that wild derived lines with more than 70% of recurrent parent genome were stable and showed enhanced yield levels compared to genotypes with higher donor genome introgressions.

Identification of Major Effect QTLs for Agronomic Traits and CSSLs in Rice from Swarna/Oryza nivara Derived Backcross Inbred Lines

“…In our previous studies, two stable lines 166S and 14S were reported to be efficient in compartmentalization of Na+ in leaf tissue and grain yield of 166S was least affected by salt stress (Divya et al, 2016; Pushpalatha et al, 2016). Also, three lines 24S, 70S, 14-3S were identified as heat tolerant lines for spikelet fertility and YLDP in both wet and dry seasons (Prasanth et al, 2016).…”

“…Two ILs 166S and 75S were tolerant to drought and salinity (Rai et al, 2010). Selected ILs from these two populations were analyzed for G × E interaction and two stable ILs 166S and 14S were identified (Divya et al, 2016). The usefulness of O. nivara in improving varieties for yield and other traits is thus quite evident.…”

Review: Omics and Strategic Yield Improvement in Oil Crops

“…Understanding plant plasticity responses will enable researchers to predict and manage the effects of climate change on crop yield production. Multiple backcross introgression lines (BILs) with preferred phenotypic traits have been evaluated [233] to select for rice BILs with improved yield potential. Variations in yield traits were observed due to G × E interaction and resulted in traits such as plant height and 1000 grain weight with stable performance regardless of environment factors.…”

Characterizing allele-by-environment interactions using maize introgression lines

“…Obtaining a rigorous assessment of G×E effects requires phenotypic evaluation in a wide range of environments and breeder choices about the level of trait instability across environments that will be tolerated. Many G×E studies are focused on traits with important economic value, such as yield and quality, which are usually the end products of plants (Ndhlela et al 2014; Mohammadi and Amri 2016; Balakrishnan et al 2016). There have been fewer detailed evaluations of G×E interactions for vegetative traits and yield component traits such as ear morphology.…”