The detection of QTLs in barley associated with endosperm hardness, grain density, grain size and malting quality using rapid phenotyping tools

Abstract

Using a barley mapping population, 'Vlamingh' × 'Buloke' (V × B), whole grain analyses were undertaken for physical seed traits and malting quality. Grain density and size were predicted by digital image analysis (DIA), while malt extract and protein content were predicted using near infrared (NIR) analysis. Validation of DIA and NIR algorithms confirmed that data for QTL analysis was highly correlated (R (2) > 0.82), with high RPD values (the ratio of the standard error of prediction to the standard deviation, 2.31-9.06). Endosperm hardness was measured on this mapping population using the single kernel characterisation system. Grain density and endosperm hardness were significantly inter-correlated in all three environments (r > 0.22, P < 0.001); however, other grain components were found to interact with the traits. QTL for these traits were also found on different genomic regions, for example, grain density QTLs were found on chromosomes 2H and 6H, whereas endosperm hardness QTLs were found on 1H, 5H, and 7H. In this study, the majority of the genomic regions associated with grain texture were also coincident with QTLs for grain size, yield, flowering date and/or plant development genes. This study highlights the complexity of genomic regions associated with the variation of endosperm hardness and grain density, and their relationships with grain size traits, agronomic-related traits, and plant development loci.

QTL for chlorophyll fluorescence of barley plants grown at low oxygen concentration in hydroponics to simulate waterlogging

“…The methods currently used are indices based on leaf chlorosis (Li et al 2008), germination ability (Takeda and Fukuyama 1987), biomass growth reduction (Zhou et al 2012) and yield components (Xue et al 2010;Walker et al 2013). Most of these traits are difficult to use in breeding, especially in field selection with high genotype-by-environment interaction.…”

The application of microsatellite analysis in barley malting quality breeding programmes

“…The first systematic QTL mapping of malting quality traits in barley was reported by Hayes et al (1993), in which 62 QTLs of 8 malting quality traits were mapped. Since then, several QTL analyses of malting quality have been reported for different germplasm combinations (Ayoub et al 2002;Emebiri et al 2004;Walker et al 2013;and many others). Microsatellites very often used in QTL mapping are simple sequence repeats (SSR) interspersed ubiquitously in eukaryotic genomes.…”

Quantitative trait loci for yield and grain plumpness relative to maturity in three populations of barley (Hordeum vulgare L.) grown in a low rain-fall environment

“…Other studies have reported yield QTL in the same genomic region [23, 53]. Although these two QTL were located around the Vrn-H3 locus, where [21] have also reported QTL for yield and flowering date, Vrn-H3 marker was monomorphic in our populations and cannot explain the yield QTL.…”

“…Frequently the reported yield-related QTL were associated with the major phenology genes such as the vernalization requirement genes ( Vrn-H1 , Vrn-H2 , and Vrn-H3 ) [25], the photoperiod response genes ( Ppd-H1 and Ppd-H2 ) and the earliness per se ( EPS2 ) locus [20, 26]. QTL have been mapped for different aspects of grain size including grain weight, grain length, grain width, and grain width to length ratio [11, 21]. Genomic regions affecting barley grain weight and size in different international and Australian mapping populations have been summarized in [6].…”