Characters that affect malting quality (e.g. malt extract content, - and -amylase activity, diastatic power, malt -glucan content, malt -glucanase activity, grain protein content, kernel plumpness, and dormancy) are quantitatively inherited and variously influenced by the environment (E). Conventional genetic analyses have provided little useful information. Molecular technologies have opened the door for better understanding of these and other quantitatively inherited traits. Quantitative trait locus (QTL) analysis identifies chromosome regions, linked molecular markers, gene effects, QTL X E, and QTL X QTL interactions for a given trait. Considerable QTL analyses have been performed in recent years on a number of crosses. The objective of this study was to accumulate malting quality QTL mapping data published to date to update QTL designations in relation to consensus molecular markers. Additional molecular markers from an integrated map were used to anchor specific QTLs across mapping populations. Data has come from crosses of germplasm sources originating from North America, Europe, Australia and Asia. Based on our search, a total of 156 malting quality QTLs representing 19 malting quality traits have been mapped in 9 mapping populations. QTL regions are spread across each of the seven barley chromosomes with concentrations especially within chromosomes 1 (7H) (ABC158-PSR129) and 5 (1H) (Act8-CDO99 and KgE33M59.222-ABC159c). Whereas, there is remarkable QTL conservation in some chromosome regions among crosses, some regions hold unique QTLs as well. It is also noteworthy that there are many overlapping QTLs, especially but not surprisingly, of related traits. Malt extract QTLs are almost always coincident with component traits such as carbohydrate hydrolytic enzyme activities. Diastatic power QTLs are often associated with - and/or -amylase activity QTLs. It is likely that pleiotropy is the cause, but gene clusters cannot be ruled out at this time. Given that malting quality determinants are widely distributed across the barley genome, care must be taken in choosing QTLs for selection in breeding programs. Magnitude of effect, of course, is one criterion that can be applied. And whereas, in some cases widely conserved QTL chromosome regions may be targets for selection to maintain malting quality, selection for unique regions may lead to new improvements. However, in general, in spite of great advancement in knowledge, understanding of the truly complex quantitative traits is far from complete, and this will likely affect efficiency of molecular marker assisted selection for these traits.