Aim Woody vegetation patterns in African savannas north of the equator are closely connected to human presence, but the distinctions between natural and anthropogenic landscapes have not been clear to many observers. Criteria for identifying savanna landscapes on a continuum of intensity of anthropic impact are explored.Methods A key savanna tree species, Vitellaria paradoxa (Sapotaceae), was used as model for evaluating anthropic impact. Fruits harvested from tree populations across the species range were analysed for variation in traits valued by indigenous peoples. A simple selection index was used to scale tree populations from a hypothetical wild state to a hypothetical domesticated state. Index values were compared with trait values along climate zone gradients and evaluated in the context of indigenous savanna management practices and historical species distribution reports.Results Trait values such as fruit size and shape, pulp sweetness, and kernel fat content show a significant influence of temperature and rainfall. At the same time, the mean values of groups of traits vary perpendicular to the general climatic zone gradient. Selection index values between Vitellaria populations vary up to sixfold, with highest values in central Burkina Faso. Comparison of present day Vitellaria distribution with historical range limits show range expansion by human migration.Main conclusions The prevalence of major economic tree species in the savannas of Africa north of the equator is a strong indicator of human involvement in tree dispersal. This conclusion is supported by paleobotanical evidence and by recent Vitellaria range expansion as a result of human migration. The presence of high mean values of several Vitellaria fruit traits in central Burkina Faso suggests that selection for desired characteristics has occurred. The impact of indigenous savanna peoples on woody species composition and spatial distribution is probably much greater than usually thought and is the result of a deliberate strategy of altering the landscape to provide needed human resources.

The well-established health beneficial value of pomegranate juice is leading to increased demand for pomegranate products and to the expansion of pomegranate orchards worldwide. The current study describes differences in the chemical composition of major ingredients of the arils and peels of 11 accessions grown in Mediterranean and desert climates in Israel. In most of the accessions, the levels of antioxidant activity and content of total phenolics, total anthocyanins, total soluble solids, glucose, fructose, and acidity were higher in the aril juice of fruit grown in the Mediterranean climate compared to those grown in the desert climate. However, the peels of fruit grown in the desert climate exhibited higher antioxidant activity, and the levels of total phenolics, including the two hydrolyzable tannins, punicalagin and punicalin, were higher compared to those in the peels of fruit grown in the Mediterranean climate. The results indicate that environmental conditions significantly affect pomegranate fruit quality and health beneficial compounds.

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Low-resolution nuclear magnetic resonance (LR-NMR) relaxometry is a powerful tool that can be harnessed for characterizing constituents in complex materials. Conversion of the relaxation signal into a continuous distribution of relaxation components is an ill-posed inverse Laplace transform problem. The most common numerical method implemented today for dealing with this kind of problem is based on L2-norm regularization. However, sparse representation methods via L1 regularization and convex optimization are a relatively new approach for effective analysis and processing of digital images and signals. In this article, a numerical optimization method for analyzing LR-NMR data by including non-negativity constraints and L1 regularization and by applying a convex optimization solver PDCO, a primal-dual interior method for convex objectives, that allows general linear constraints to be treated as linear operators is presented. The integrated approach includes validation of analyses by simulations, testing repeatability of experiments, and validation of the model and its statistical assumptions. The proposed method provides better resolved and more accurate solutions when compared with those suggested by existing tools. © 2013 Wiley Periodicals, Inc. Concepts Magn Reson Part A 42A: 72–88, 2013.

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Pomegranate oil (PGO) is a unique and quite rare edible oil produced from Punica granatum L. seeds. It is considered to be a powerful health-benefiting agent, due to its antioxidative, anticancer, and antilipidemic properties. The aim of this study was to achieve a comprehensive and detailed profile of the different components of PGO. The fatty acid profile and phytosterol composition were determined by GC-MS; the triacylglycerol (TAG) compositions were profiled by the mass spectrometry tool of MALDI-TOF/MS. Results showed linolenic acid (18:3) to be the predominant fatty acid in the PGO (64-83%), as previously reported. The linolenic acid fraction was composed of four different chromatographically separated peaks that are assumed, according to MS data (based on both FAME and DMOX derivatization), to be attributed to different geometric isomers of conjugated linolenic acid (CLNA), punicic acid (18:3: 9-cis,11-trans,13-cis) being the major isomer. The MALDI-TOF/MS finger printing results showed the different TAG compositions present in the PGO, the major ones being LnLnLn and LnLnP. This unique PGO TAG fingerprint enables it to be differentiated from most other common edible oils. Phytosterols were found in quite a high concentration in the PGO (4089-6205 mg/kg), about 3-4-fold higher than in soybean oil. A detailed profile of the phytosterols in the PGO showed a wide variety, the major phytosterols being beta-sitosterol, campesterol, and stigmasterol. This study depicts a new detailed analysis of PGO, showing great potential for further research regarding the physiological effects of specific valuable components in pomegranate oil.