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Among grain legumes, faba bean is reputed to be relatively sensitive to drought stress. Epicuticular wax (ECW) quantity is considered as an important drought adaptation strategy in plant species. This study aimed to define variation in leaf ECW concentration as a drought-adaptive trait in 197 faba bean accessions under well-watered conditions. The relationship between ECW and stomatal characteristics was also investigated. Highly significant differences were found in the ECW concentration, which ranged from 0.680 to 2.104 mg/dm2. No relationships were found between ECW and any measure of stomatal morphology and function. This study provides evidence of the wide variation in ECW in faba bean germplasm, which is independent of stomatal characteristics and leaf water content. This variation may allow the genetic improvement of ECW as a drought-adaptive character in faba bean breeding programs aiming at the economical use of water.

Here we review the potential of ILB 938 (IG 12132 – doi: 10.18730/60FD2), a unique faba bean accession originating from the Andean region of Colombia and Ecuador, maintained at ICARDA – International Center for Agricultural Research in the Dry Areas, with resistance to multiple biotic and abiotic stresses and carrying some useful morphological markers. It has been used as a donor of leaf-related drought adaptation traits and chocolate spot (Botrytis fabae) resistance genes in faba bean breeding programmes worldwide. From generated populations of recombinant inbred lines, quantitative traits loci associated with these useful traits have been mapped. Other markers, such as a lack of stipule-spot pigmentation and clinging pod wall, show the presence of unusual changes in biochemical pathways that may have economic value in the future.

Plant genetic resources display patterns resulting from ecological and co-evolutionary processes. Such patterns are instrumental in tracing the origin and diversity of crops and locating adaptive traits. With climate change and the anticipated increase in demand for food, new crop varieties will be needed to perform under unprecedented climatic conditions. In the present study, we explored genetic resources patterns to locate traits of adaptation to drought and to maximize the utilization of plant genetic resources lacking ex ante evaluation for emerging climate conditions. This approach is based on the use of mathematical models to predict traits as response variables driven by stochastic ecological and co-evolutionary processes. The high congruence of metrics between model predictions and empirical trait evaluations confirms in silico evaluation as an effective tool to manage large numbers of crop accessions lacking ex ante evaluation. This outcome will assist in developing cultivars adaptable to various climatic conditions and in the ultimate use of genetic resources to sustain agricultural productivity under conditions of climate change.

SUMMARYStripe rust, caused byPuccinia striiformisf. sp.tritici(Pst), is a major wheat disease that can inflict yield losses of up to 70% on susceptible varieties under favourable environmental conditions. The timely identification of plant genetic resources likely to possess novel resistance to this disease would facilitate the rapid development of resistant wheat varieties. The focused identification of germplasm strategy (FIGS) approach was used to predict stripe rust resistance in a collection of wheat landraces conserved at ICARDA genebank. Long-term climate data for the collection sites, from which these accessions originated and stripe rust evaluation scores for one group of accessions were presented to three different non-linear models to explore the trait×collection site environment interactions. Patterns in the data detected by the models were used to predict stripe rust resistance in a second and different set of accessions. The results of the prediction were then tested against actual evaluation scores of the disease in the field. The study mimics the real scenario where requests are made to plant genetic resources curators to provide accessions that are likely to possess variation for specific traits such as disease resistance.The models used were able to identify stripe rust-resistant accessions with a high degree of accuracy. Values as high as 0·75 for area under the curve and 0·45 for Kappa statistics, which quantify the agreement between the models’ predictions and the curator's disease scores, were achieved. This demonstrates a strong environmental component in the geographic distribution of resistance genes and therefore supports the theoretical basis for FIGS. It is argued that FIGS will improve the rate of gene discovery and efficiency of mining genetic resource collections for adaptive traits by reducing the number of accessions that are normally required for evaluation to identify such variation.

Drought is a major constraint to faba bean (Vicia faba L.) production, and there are many mechanisms by which leaves can regulate water loss. Our primary objective was to test if the origin of the faba bean accessions, from drought-prone and non-drought-prone environments, was associated with differences in measurable aspects of stomatal morphology and physiology related to water use. Two sets, each consisting of 201 faba bean accessions, were chosen from environments with contrasting seasonal moisture profiles following the focused identification of germplasm strategy (FIGS), and then screened under well watered conditions. From these, two subsets of 10 accessions each were chosen to test for differences in response to drought. Parameters related to stomatal function and water status were measured. The dry-adapted set had bigger stomata, higher leaf relative water content (LRWC) and cooler leaves under well watered conditions. Stomatal density and stomatal area per unit area of leaflet were negatively correlated with gas exchange parameters and positively correlated with intrinsic water use efficiency. Drought caused stomatal densities to increase in the dry set while stomatal length decreased in both sets. The moisture deficit was sufficient to decrease gas exchange in both sets to similar levels, but the dry-adapted set maintained warmer leaves and a higher LRWC that showed no significant correlations with leaf morphology or gas exchange, demonstrating more effective stomatal regulation. The results also support that collection site data from the environment where genetic resources are collected can be used as indicators of adaptive traits in an herbaceous annual species.

The focused identifi cation of germplasm strategy (FIGS) has been validated using predictive computer models in simulation studies to predict a priori known trait scores. This study was designed as a "blind" study where the person calculating the computer model did not know the actual trait scores. This study design provides a more realistic test of the predictive capacity of the FIGS approach compared to previous studies. Furthermore this study also explored the suitability of FIGS for the identifi cation of resistance in bread wheat (Triticum aestivum L. subsp. aestivum) and durum wheat (Triticum turgidum L. subsp. durum (Desf.) Husn.) to Ug99—a strain of stem rust (Puccinia graminis Pers. f. sp. tritici Eriks. & Henn.) and typifi ed to race TTKSK. The predictions were validated against a dataset with the screening of wheat accessions conducted in Yemen in 2008. Only a small training set representing 20% of the trait screening results was disclosed to the person conducting the data analysis for the calibration of the prediction model. The hit rate for identifi cation of Ug99-resistant accessions was more than two times higher when using the FIGS approach compared to a random selection of accessions. These results suggested that FIGS was well suited for the identifi cation of samples with resistance to fungal pathogens. It is therefore recommended that FIGS approach be used as a complement to expert knowledge and experience when selecting accessions for plant breeding and crop research activities.

Recent studies have shown that novel genetic variation for resistance to pests and diseases can be detected in plant genetic resources originating from locations with an environmental profile similar to the collection sites of a reference set of accessions with known resistance, based on the Focused Identification of Germplasm Strategy (FIGS) approach. FIGS combines both the development of a priori information based on the quantification of the trait-environment relationship and the use of this information to define a best bet subset of accessions with a higher probability of containing new variation for the sought after trait(s). The present study investigates the development strategy of the a priori information using different modeling techniques including learning-based techniques as a follow up to previous work where parametric approaches were used to quantify the stem rust resistance and climate variables relationship. The results show that the predictive power, derived from the accuracy parameters and cross-validation, varies depending on whether the models are based on linear or non-linear approaches. The prediction based on learning techniques are relatively higher indicating that the non-linear approaches, in particular support vector machine and neural networks, outperform both principal component logistic regression and generalized partial least squares. Overall there are indications that the trait distribution of resistance to stem rust is confined to certain environments or areas, whereas the susceptible types appear to be limited to other areas with some degree of overlapping of the two classes. The results also point to a number of issues to consider for improving the predictive performance of the models.

Collections of crop genetic resources are a valuable source of new genetic variation for economically important traits, including resistance to crop diseases. New sources of useful crop traits are often identi�耀 ed through evaluation in �耀 eld trials. The number of relevant accessions in genebank collections available to be evaluated is often substantially larger than the capacity of the evaluation project. The focused identi�耀 cation of germplasm strategy (FIGS) is an approach used to select subsets of germplasm from genetic resource collections in such a way as to maximize the likelihood of capturing a speci�耀 c trait. This strategy uses a range of methods to link the expression of a speci�耀 c trait (of a target crop) with the eco-geographic parameters of the original collection site. This study contributes to the development of the approach by which a FIGS subset could be assembled for biotic traits. We have evaluated trait-speci�耀 c subset selection methods for two fungal crop diseases, namely stem rust (Puccinia graminis Pers.) in wheat (Triticum aestivum L. and Triticum turgidum L.) and net blotch (Pyrenophora teres Drechs.) in barley (Hordeum vulgare L.). The results indicate that the climate layers from freely available eco-geographic databases are well suited to model and predict the reaction in these crops to biotic stress traits. This result has the potential to improve the ef�耀 ciency of �耀 eld screening trials to �耀 nd novel sources of economically valuable crop traits.

Diversity analysis was performed among 39 cultivated lentil (Lensculinaris Medik.) accessions of Central Asia and Caucasian origin using five highly polymorphic microsatellite markers. A total of 33 alleles determined ranging from 3 to 8 per locus. Estimated gene diversity value for 33 loci was 0.66. Genetic similarity indices among 39 accessions ranged from 0.24 to 1.0. Cluster analysis using the unweighted pair group method with arithmetic mean method classified accessions into six major groups at 0.5 similarity coefficient. More than half accessions from Tajikistan formed large cluster. On the other hand, a few accessions from each country showed unique genotypes. Overall, most of the accessions, except ones with closely related origin, were distinguished by the present high quality DNA fingerprinting. This molecular diversity information gives important basis for conservation strategy in gene bank and exotic germplasm introduction in breeding programs in Central Asia and Caucasian countries.

Equipe AFEF ‘Architecture et Fonctionnement des Espèces fruitières’; Contact e-mail: bkeller@botinst.uzh.ch; International audience; Wheat production is threatened by a constantly changing population of pathogen species and races. Given the rapid ability of many pathogens to overcome genetic resistance, the identification and practical implementation of new sources of resistance is essential. Landraces and wild relatives of wheat have played an important role as genetic resources for the improvement of disease resistance. The use of molecular approaches, particularly molecular markers, has allowed better characterization of the genetic diversity in wheat germplasm. In addition, the molecular cloning of major resistance (R) genes has recently been achieved in the large, polyploid wheat genome. For the first time this allows the study and analysis of the genetic variability of wheat R loci at the molecular level and therefore, to screen for allelic variation at such loci in the gene pool. Thus, strategies such as allele mining and ecotilling are now possible for characterization of wheat disease resistance. Here, we discuss the approaches, resources and potential tools to characterize and utilize the naturally occurring resistance diversity in wheat. We also report a first step in allele mining, where we characterize the occurrence of known resistance alleles at the wheat Pm3 powdery mildew resistance locus in a set of 1,320 landraces assembled on the basis of eco-geographical criteria. From known Pm3 R alleles, only Pm3b was frequently identified (3% of the tested accessions). In the same set of landraces, we found a high frequency of a Pm3 haplotype carrying a susceptible allele of Pm3. This analysis allowed the identification of a set of resistant lines where new potentially functional alleles would be present. Newly identified resistance alleles will enrich the genetic basis of resistance in breeding programmes and contribute to wheat improvement

Efficient methods to explore plant agro-biodiversity for climate change adaptive traits are urgently required. The focused identification of germplasm strategy (FIGS) is one such approach. FIGS works on the premise that germplasm is likely to reflect the selection pressures of the environment in which it developed. Environmental parameters describing plant germplasm collection sites are used as selection criteria to improve the probability of uncovering useful variation. This study was designed to test the effectiveness of FIGS to search a large faba bean (Vicia faba L.) collection for traits related to drought adaptation. Two sets of faba bean accessions were created, one from moisture-limited environments, and the other from wetter sites. The two sets were grown under well watered conditions and leaf morpho-physiological traits related to plant water use were measured. Machine-learning algorithms split the accessions into two groups based on the evaluation data and the groups created by this process were compared to the original climate-based FIGS sets. The sets defined by trait data were in almost perfect agreement to the FIGS sets, demonstrating that ecotypic differentiation driven by moisture availability has occurred within the faba bean genepool. Leaflet and canopy temperature as well as relative water content contributed more than other traits to the discrimination between sets, indicating that their utility as drought-tolerance selection criteria for faba bean germplasm. This study supports the assertion that FIGS could be an effective tool to enhance the discovery of new genes for abiotic stress adaptation.

The continuous improvement of crop plants is essential for agriculture in the coming decades and relies on the use of genetic variability through breeding. However, domestication and modern breeding have reduced diversity in the crop germplasm. Global gene banks conserve diversity, but these resources remain underexplored owing to a lack of efficient strategies to isolate important alleles. Here we describe a large-scale allele-mining project at the molecular level. We first selected a set of 1,320 bread wheat landraces from a database of 16,089 accessions, using the focused identification of germplasm strategy. On the basis of a hierarchical selection procedure on this set, we then isolated 7 resistance alleles of the powdery mildew resistance gene Pm3 , doubling the known functional allelic diversity at this locus. This targeted approach for molecular utilization of gene bank accessions reveals landraces as a rich resource of new functional alleles. This strategy can be implemented for other studies on the molecular diversity of agriculturally important genes, as well as for molecular breeding.

With 1 table Abstract Russian wheat aphid, Diuraphis noxia (Kurdjumov), is an important pest of wheat and barley in North America, Africa and the Middle East. Host plant resistance is the most economical and practical means of controlling this insect. Field and greenhouse screening in Syria of bread wheat lines from the International Center for Agricultural Research in the Dry Areas’ (ICARDA) gene bank, using the Focused Identification of Germplasm Strategy (FIGS), identified 12 lines resistant to D. noxia. These sources of resistance will be used to develop germplasm resistant to D. noxia for the highland areas of North Africa, and West and Central Asia, where this insect causes economic damage. This study also showed the relevance of the FIGS approach in better targeting accessions held in gene banks for valuable traits.

Some evidence as to the chemical nature of the new element californium is presented. The chemical separation and identification of the new element was accomplished through the use of ion-exchange adsorption methods employing the resin Dowex-50. Californium appears in the eka-dysprosium position on elution curves containing berkelium and curium as reference points--that is, it precedes berkelium and curium off the column as dysprosium precedes terbium and gadolinium. The experiments so far have revealed only the tripositive oxidation state of eka-dysprosium character and suggest either that higher oxidation states are not stable in aqueous solution or that the rates of oxidation are slow.

Introduction Internationally, emergency ambulance paramedic education has evolved from ‘on the job’ training by ambulance services to tertiary-level qualifications. However, across many countries and jurisdictions, clinical practicum requirements still differ substantially. For example, Australian paramedic students spend fewer hours on clinical practicum than their United Kingdom (UK) counterparts. Methods Fifteen semi-structured face-to-face interviews were conducted with Australian and UK paramedics and managers to identify their perceptions regarding the preparedness of graduate paramedics for practice. Results Interviewees in Australia and the UK identified that newly graduated paramedics require an internship period before independent practice. Interviewees in both jurisdictions recognised the robust theoretical knowledge and practical skills of graduates. Organisational operations, clinical judgement and decision-making, and care-pathway selection were areas where interviewees identified that an internship period consolidated the graduate's learning. Conclusion This research found that increased time spent by paramedic students on ambulances did not increase a new graduate's ability to practice independently before an internship period. The time spent on ambulance practicums, objectives and supervisory model should be reviewed.

In the course of a rather cursory examination of the elution of tetra-positive ions from the cation exchange resin Dowex 50 with hydrochloric acid solutions, the authors have discovered a very effective method of separating zirconium from hafnimu. In view of the great labor involved in preparing even reasonably pure hafnium compounds by existing methods, they feel that this procedure will prove very valuable to those interested in obtaining hafnium compounds free of zirconium. Although the conditions which give satisfactory separation were first worked out using microgram amounts of material and the radioactive tracer technique, the run described here, involving milligrams of material, illustrates the applicability of the method to the production of significant amounts of pure hafnium and zirconium.

This laboratory better mirrors the complex protocols of industrial laboratory experiences and is suitable for the later half of an quantitative analysis lab.