Taxonomy relies greatly on morphology to discriminate groups. Computerized geometric morphometric methods for quantitative shape analysis measure, test and visualize differences in form in a highly effective, reproducible, accurate and statistically powerful way. Plant leaves are commonly used in taxonomic analyses and are particularly suitable to landmark based geometric morphometrics. However, botanists do not yet seem to have taken advantage of this set of methods in their studies as much as zoologists have done. Using free software and an example dataset from two geographical populations of sessile oak leaves, we describe in detailed but simple terms how to: a) compute size and shape variables using Procrustes methods; b) test measurement error and the main levels of variation (population and trees) using a hierachical design; c) estimate the accuracy of group discrimination; d) repeat this estimate after controlling for the effect of size differences on shape (i.e., allometry). Measurement error was completely negligible; individual variation in leaf morphology was large and differences between trees were generally bigger than within trees; differences between the two geographic populations were small in both size and shape; despite a weak allometric trend, controlling for the effect of size on shape slighly increased discrimination accuracy. Procrustes based methods for the analysis of landmarks were highly efficient in measuring the hierarchical structure of differences in leaves and in revealing very small-scale variation. In taxonomy and many other fields of botany and biology, the application of geometric morphometrics contributes to increase scientific rigour in the description of important aspects of the phenotypic dimension of biodiversity. Easy to follow but detailed step by step example studies can promote a more extensive use of these numerical methods, as they provide an introduction to the discipline which, for many biologists, is less intimidating than the often inaccessible specialistic literature.

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Lentil (Lens culinaris Medik.) is one of the most ancient crops of the Mediterranean region used for human nutrition; an extensive differentiation of L. culinaris over millennia has resulted in a number of different landraces. As a consequence of environmental and socio-economic issues, the disappearance of many of them occurred in more recent times. To investigate the potential of proteomics as a tool in phylogenetic studies, testing the possibility to identify specific markers of different plant landraces, 2-D gel electrophoretic maps of mature seeds were obtained from seven lentil populations belonging to a local ecotype (Capracotta) and five commercial varieties (Turca Rossa, Canadese, Castelluccio di Norcia, Rascino and Colfiorito). 2-DE analysis resolved hundreds of protein species in each lentil sample, among which only 122 were further identified by MALDI-TOF PMF and/or nanoLC-ESI-LIT-MS/MS, probably as a result of the poor information available on L. culinaris genome. A comparison of these maps revealed that 103 protein spots were differentially expressed within and between populations. The multivariate statistical analyses carried out on these variably expressed spots showed that 24 protein species were essential for population discrimination, thus determining their proposition as landrace markers. Besides providing the first reference map of mature lentil seeds, our data confirm previous studies based on morphological/genetic observations and further support the valuable use of proteomic techniques as phylogenetic tool in plant studies.

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Ripening of climacteric fruits involves a complex network of biochemical and metabolic changes that make them palatable and rich in nutritional and health-beneficial compounds. Since fruit maturation has a profound impact on human nutrition, it has been recently the object of increasing research activity by holistic approaches, especially on model species. Here we report on the original proteomic characterization of ripening in apricot, a widely cultivated species of temperate zones appreciated for its taste and aromas, whose cultivation is yet hampered by specific limitations. Fruits of Prunus armeniaca cv. Vesuviana were harvested at three ripening stages and proteins extracted and resolved by 1D and 2D electrophoresis. Whole lanes from 1D gels were subjected to shot-gun analysis that identified 245 gene products, showing preliminary qualitative differences between maturation stages. In parallel, differential analysis of 2D proteomic maps highlighted 106 spots as differentially represented among variably ripen fruits. Most of these were further identified by means of MALDI-TOF-PMF and nanoLC-ESI-LIT-MS/MS as enzymes involved in main biochemical processes influencing metabolic/structural changes occurring during maturation, i.e. organic acids, carbohydrates and energy metabolism, ethylene biosynthesis, cell wall restructuring and stress response, or as protein species linkable to peculiar fruit organoleptic characteristics. In addition to originally present preliminary information on the main biochemical changes that characterize apricot ripening, this study also provides indications for future marker-assisted selection breeding programs aimed to ameliorate fruit quality.