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      Identification of ecogeographical gaps in the Spanish Aegilops collections with potential tolerance to drought and salinity

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          Abstract

          Drought, one of the most important abiotic stress factors limiting biomass, significantly reduces crop productivity. Salinization also affects the productivity of both irrigated and rain-fed wheat crops. Species of genus Aegilops can be considered crop wild relatives (CWR) of wheat and have been widely used as gene sources in wheat breeding, especially in providing resistance to pests and diseases. Five species ( Ae. biuncialis, Ae. geniculata, Ae. neglecta, Ae. triuncialis and Ae. ventricosa) are included in the Spanish National Inventory of CWRs. This study aimed to identify ecogeographic gaps in the Spanish Network on Plant Genetic Resources for Food and Agriculture (PGRFA) with potential tolerance to drought and salinity. Data on the Spanish populations of the target species collected and conserved in genebanks of the Spanish Network on PGRFA and data on other population occurrences in Spain were compiled and assessed for their geo-referencing quality. The records with the best geo-referencing quality values were used to identify the ecogeographical variables that might be important for Aegilops distribution in Spain. These variables were then used to produce ecogeographic land characterization maps for each species, allowing us to identify populations from low and non-represented ecogeographical categories in ex situ collections. Predictive characterization strategy was used to identify 45 Aegilops populations in these ecogeographical gaps with potential tolerance to drought and salinity conditions. Further efforts are being made to collect and evaluate these populations.

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          THE APPLICATION OF CLUSTER ANALYSIS IN STRATEGIC MANAGEMENT RESEARCH: AN ANALYSIS AND CRITIQUE

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            Random forests for classification in ecology.

            Classification procedures are some of the most widely used statistical methods in ecology. Random forests (RF) is a new and powerful statistical classifier that is well established in other disciplines but is relatively unknown in ecology. Advantages of RF compared to other statistical classifiers include (1) very high classification accuracy; (2) a novel method of determining variable importance; (3) ability to model complex interactions among predictor variables; (4) flexibility to perform several types of statistical data analysis, including regression, classification, survival analysis, and unsupervised learning; and (5) an algorithm for imputing missing values. We compared the accuracies of RF and four other commonly used statistical classifiers using data on invasive plant species presence in Lava Beds National Monument, California, USA, rare lichen species presence in the Pacific Northwest, USA, and nest sites for cavity nesting birds in the Uinta Mountains, Utah, USA. We observed high classification accuracy in all applications as measured by cross-validation and, in the case of the lichen data, by independent test data, when comparing RF to other common classification methods. We also observed that the variables that RF identified as most important for classifying invasive plant species coincided with expectations based on the literature.
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              Plant breeding and drought in C3 cereals: what should we breed for?

              Drought is the main abiotic constraint on cereal yield. Analysing physiological determinants of yield responses to water may help in breeding for higher yield and stability under drought conditions. The traits to select (either for stress escape, avoidance or tolerance) and the framework where breeding for drought stress is addressed will depend on the level and timing of stress in the targeted area. If the stress is severe, breeding under stress-free conditions may be unsuccessful and traits that confer survival may become a priority. However, selecting for yield itself under stress-alleviated conditions appears to produce superior cultivars, not only for optimum environments, but also for those characterized by frequent mild and moderate stress conditions. This implies that broad avoidance/tolerance to mild-moderate stresses is given by constitutive traits also expressed under stress-free conditions. In this paper, we focus on physiological traits that contribute to improved productivity under mild-moderate drought. Increased crop performance may be achieved through improvements in water use, water-use efficiency and harvest index. The first factor is relevant when soil water remains available at maturity or when deep-rooted genotypes access water in the soil profile that is not normally available; the two latter conditions become more important when all available water is exhausted by the end of the crop cycle. Independent of the mechanism operating, a canopy able to use more water than another would have more open stomata and therefore higher canopy temperature depression, and 13C discrimination (delta13C) in plant matter. The same traits would also seem to be relevant when breeding for hot, irrigated environments. Where additional water is not available to the crop, higher water-use efficiency (WUE) appears to be an alternative strategy to improve crop performance. In this context delta13C constitutes a simple but reliable measure of WUE. However, in contrast to lines performing better because of increased access to water, lines producing greater biomass due to superior WUE will have lower delta13C values. WUE may be modified not only through a decrease in stomatal conductance, but also through an increase in photosynthetic capacity. Harvest index is strongly reduced by terminal drought (i.e. drought during grain filling). Thus, phenological traits increasing the relative amount of water used during grain filling, or adjusting the crop cycle to the seasonal pattern of rainfall may be useful. Augmenting the contribution of carbohydrate reserves accumulated during vegetative growth to grain filling may also be worthwhile in harsh environmcnts. Alternatively, extending the duration of stem elongation without changing the timing of anthesis would increase the number of grains per spike and the harvest index without changing the amount of water utilized by the crop.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                27 July 2017
                2017
                : 5
                : e3494
                Affiliations
                [1 ]Centro Nacional de Recursos Fitogenéticos (CRF-INIA) , Alcalá de Henares, Madrid, Spain
                [2 ]Facultad de Ciencias Agrarias, Universidad Nacional de Colombia , Bogotá D.C., Colombia
                [3 ]Área de Biodiversidad y Conservación, Universidad Rey Juan Carlos , Móstoles, Madrid, Spain
                Article
                3494
                10.7717/peerj.3494
                5534164
                b651fb57-2754-40b0-b0ae-0d0b6d0d2256
                ©2017 Garcia et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 31 August 2016
                : 2 June 2017
                Funding
                The authors received no funding for this work.
                Categories
                Agricultural Science
                Biodiversity
                Biogeography
                Ecology
                Plant Science

                crop wild relative,ecogeographic representativeness,optimized collecting design,predictive characterization

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