Background: Land plants have evolved several measures to maintain their life against abiotic stresses. The accumulation of proline is the most generalized response of plants under drought, heat or salt stress conditions. It is known as an osmoprotectant which also acts as an instant source of energy during drought recovery process. But, both its role and genetic inheritance are poorly understood in agriculture crops. In the present work, advanced backcross quantitative trait locus (AB-QTL) analysis was performed to elucidate genetic mechanisms controlling proline accumulation and leaf wilting in barley under drought stress conditions. Results: The analysis revealed eight QTL associated to proline content (PC) and leaf wilting (WS). QTL for PC were localized on chromosome 3H, 4H, 5H and 6H. The strongest QTL effect QPC.S42.5H was detected on chromosome 5H where drought inducible exotic allele was associated to increase PC by 54%. QTL effects QPC.S42.3H, QPC.S42.4H and QPC.S42.6H were responsible to heighten PC due to the preeminence of elite alleles over the exotic alleles which ranged from 26% to 43%. For WS, QTL have been localized on chromosome 1H, 2H, 3H and 4H. Among these, QWS.S42.1H and QWS.S42.4H were associated to decrease in WS due to the introgression of exotic alleles. In addition, two digenic epistatic interaction effects were detected for WS where the additive effect of exotic alleles imparted a favorable increase in the trait value. Conclusions: The present data represents a first report on whole-genome mapping of proline accumulation and leaf wilting in barley. The detected QTL are linked to new alleles from both cultivated and wild accessions which bring out an initial insight on the genetic inheritance of PC and WS. These QTL alleles are fixed in the isogenic background of Scarlett, which will allow for positional cloning of underlying genes and to develop drought resilient barley cultivars.

Background: To ensure further genetic gain, genomic approaches in plant breeding rely on precise phenotypic data, describing plant structure, function and performance. A more precise characterization of the environment will allow a better dealing with genotype-by-environment-by-management interactions. Therefore, space and time dependencies of the crop production processes have to be considered. The use of novel sensor technologies has drastically increased the amount and diversity of phenotypic data from agronomic field trials. Existing data management systems either do not consider space and time, are not customizable to individual needs such as field trial handling, or have restricted availability. Hence, we propose an integrative data management and information system (DMIS) for handling of traditional and novel sensor-based phenotypic, environmental and management data. The DMIS must be customizable, applicable and scalable from individual users to organizations. Results: Key element of the system is a dynamic PostgreSQL database with GIS-extension, capable of importing, storing and managing all types of data including images. The database references every structural database object and measurement in a threefold approach with semantic, spatial and temporal reference. Timestamps and geo-coordinates allow automated linking of all data. Traits can be precisely defined individually or uploaded as predefined lists. Filtering and selection routines allow compilation of all data for visualization via tables, charts or maps and for export and external statistical analysis. New possibilities of environmental information-based planning of field trials, weather-guided phenotyping and data analysis for outlier or hot-spot detection are demonstrated. Conclusions: The DMIS supports users in handling experimental field trials with crop plants and modern phenotyping methods. It focuses on linking all space and time dependent processes of plant production. Weather, soil and management, as well as growth and yield formation of the plants can be depicted, thus allowing a more precise interpretation of the results in relation to environment and management. Breeders, extension specialists, official testing agencies and agricultural scientists are assisted in all steps of a typical workflow with planning, designing, conducting, controlling and analyzing field trials to generate new information for decision support in the crop improvement process.