Morpho-colorimetric characterization by image analysis to identify diaspores of wild plant species

Digital images of ex situ germplasm stored in the Sardinian Germplasm Bank (BG-SAR) were used for the application of image analysis techniques at the Stazione Sperimentale di Granicoltura per la Sicilia. The analysed accessions refer to 148 taxonomic units belonging to 102 genera and 47 families, typical of the Sardinian flora, and of the Mediterranean basin in general.The images of diaspores were acquired by a flatbed scanner and elaborated with a macro specially developed for the morphometric and colorimetric measurements. This method allowed carrying out a database for the characterization of autochthonous germplasm in entry to the bank and the realization of statistic classifiers for the discrimination of genera and species within the following families: Apiaceae, Boraginaceae, Caryophyllaceae, Cistaceae, Fabaceae and Scrophulariaceae. Such classifiers, based on the linear discriminant analysis (LDA) technique and checked by cross-validation, showed a performance included between 74.3% and 96.4%.In addition, for the genus Astragalus, it was possible to elaborate a classifier able to identify very similar taxa of a species complex, obtaining a performance between 83.7% and 100%. Such analysis proved the validity of the methodology also from the taxonomic point of view.Suggestions for subsequent methodological progress, which could offer applications in other research issues, such as ecological analysis, soil seed bank and archaeological botany are proposed.     

Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Using Echo Ultrasound from Schooling Fish to Detect and Classify Fish Types

Fish finders have already been widely available in the fishing market for a number of years.However,the sizes of these fishfinders are too big and their prices are expensive to suit for the research of robotic fish or mini-submarine.The goal of thisresearch is to propose a low-cost fish detector and classifier which suits for underwater robot or submarine as a proximity sensor.With some pre-condition in hardware and algorithms,the experimental results show that the proposed design has good per-formance,with a detection rate of 100 % and a classification rate of 94 %.Both the existing type of fish and the group behaviorcan be revealed by statistical interpretations such as hovering passion and sparse swimming mode.     

EMAP-Wetlands: A sampling design with global application

The U.S. Environmental Protection Agency (EPA) initiated the Environmental Monitoring and Assessment Program (EMAP) in 1988. The wetland component (EMAP-Wetlands) is designed to provide quantitative assessments of the current status and long-term trends in the ecological condition of wetland resources. EMAP-Wetlands will develop a wetland monitoring network and will identify and evaluate indicators that describe and quantify wetland condition. The EMAP-Wetlands network will represent a probability sample of the total wetland resource. The EMAP sample is based on a triangular grid of approximately 12,600 sample points in the conterminous U.S. The triangular grid adequately samples wetland resources that are common and uniformly distributed in a region, such as the prairie pothole wetlands of the Midwest. However, the design is flexible and allows the base grid density to be increased to adequately sample wetland resources, such as the coastal wetlands of the Gulf of Mexico, which are distributed linearly along the coast. The Gulf sample network required a 49-fold increase in base grid density. EMAP-Wetlands aggregates the 56 U.S. Fish and Wildlife Service's (FWS) National Wetland Inventory (NWI) categories (Cowardin et al. 1979) into 12 functionally similar groups (Leibowitz et al. 1991). Both the EMAP sample design and aggregated wetland classes are suitable for global inventory and assessment of wetlands.The research described in this report has been funded by the U.S. Environmental Protection Agency. This document has been prepared at the EPA Environmental Research Laboratory in Corvallis, OR, through contract No. 68-C8-0006 to Man Tech Environmental Technology, Inc. This paper has been subjected to the Agency's peer and administrative review and approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.     

A new infrageneric classification and phylogenetic trends in the genusRhododendron (Ericaceae)

Recent studies have improved the infrageneric classification ofRhododendron, including my own investigations on flavonoids and anthocyanins as chemosystematic markers. From a synoptical comparison of morphological, anatomical and phytochemical characters a new system for the genus is proposed. Phylogenetic character progressions and relationships among subgenera, sections and subsections are discussed and illustrated. Key positions for subg.Candidastrum between chori subgenerumRhododendron andNomazalea, and for subg.Choniastrum between chori subgenerumHymenanthes andNomazalea are suggested.     

Classification and ordination of macroinvertebrate assemblages to predict stream acidity in upland Wales

Macroinvertebrates were collected from riffles at 104 sites in upland Wales during April and July 1984. Species assemblages were ordinated by DECORANA, classified by TWINSPAN and related to stream chemistry and other environmental factors using correlation and multiple discriminant analysis. DECORANA axis 1 was most strongly correlated with pH and aluminium concentration whilst axis 2 correlated with stream gradient and flow. Four TWINSPAN site groups established in each season were also principally related to pH and aluminium concentration, and reflected overall taxon-richness; differences between groups were most apparent during spring, when catchment forest cover and taxon-richness were also related. A dichotomous key based on indicator species was established for each season with the coleopteran Hydraena gracilis Germar and the Ephemeroptera, including Baetis rhodani Pictet, important indicators at Level 1. We propose that these indicator systems may be used for the rapid detection and assessment of acid waters throughout Wales, and that the methodology is applicable generally.     

Cultivar differences in the rate of nitrate uptake by intact wheat plants as related to growth rate

Six Argentinian wheat ( Triticum aestivum L.) cultivars grown in nutrient solutions in controlled environment were compared for their nitrate uptake rates on a root dry weight basis. Up to 3-fold differences were observed among the cultivars at 16, 20 and 24 days from germination, either when measured by depletion from the nutrient solution in short-term experiments, or by total N accumulation in the tissue during 8 days.
No differences in total N concentration in root or shoots were found among cultivars. Although the different cultivars showed significant differences in shoot/root ratio and nitrate reductase activity (EC 1.6.6.1) in the roots, none of these parameters was correlated with the nitrate uptake rate. However, nitrate uptake was found to be positively correlated (r = 0.99) with the shoot relative growth rate of the cultivars. The three cultivars with the highest nitrate uptake rates and relative growth rates showed a positive correlation between root nitrate concentration and uptake. However, this correlation was not found in the cultivars with the lowest growth and uptake rates.
Our results indicate that the difference in nitrate uptake rate among these cultivars may only be a consequence of their differences in growth rate, and it is suggested that at least two mechanisms regulate nitrate uptake, one working when plant demand is low and another when plant demand is high.     

Correlation between soil characters and forest types: a study in multiple discriminant analysis

Multiple discriminant analysis is a useful multivariate technique in vegetation studies that can be employed for several purposes, even if the underlying statistical assumptions are not satisfied. An example of application of this method is discussed: multiple discriminant analysis was successfully used for evaluating the predictivity of forest types defined by numerical classification of vegetation data with respect to soil variables.Species nomenclature follows Pignatti (1982) for vascular plants and Augier (1966) for mosses.The research has been supported by the IDROSER (Bologna, Italy) and by the Italian C. N. R. (Grant no. 83.02548.04, resp. Prof. A. Pirola). We wish to thank Prof. E. Feoli, Prof. E. van der Maarel, Prof. L. Orlóci and Prof. A. Pirola for suggestions. We are also indebted to Dr N. Filippi who analyzed the soil samples.     

Islands and evolution: theory and opinion in Darwin's earlier years

Islands were not of special interest to evolutionists before Darwin. It was he who first appreciated their importance for demonstrating evolution in miniature. They were not of special interest because: (a) their peculiar products seemed no more peculiar than those of continents; (b) there was no special category of oceanic islands, but a continuum from such groups as the Canaries, Madeiras and Galápagos through New Zealand and Madagascar to Australia, Britain, and true continents; and (c) the concept of adaptive radiation, if known at all, was applied only to the higher levels of classification, and then very feebly.
When Darwin was young, classification at the lower levels hardly recognized convergence, and at the higher levels was subject to great changes, while only slowly separating out the major groups. In consequence, many of the facts of geographical distribution were misinterpreted, and numerous theories of the origination of species, groups, and biogeographical provinces were still plausible. It was largely the need for a historical, not ecological, explanation of the distribution of some mammals and plants, plus what he saw for himself in the Galápagos Islands, that convinced Darwin that evolution had occurred. His was a remarkable achievement in recognizing through all this 'noise' the meaning of adaptive radiation.     

The macroinvertebrate fauna of littoral and bottom substrata as a tool for biotypology of Frisian waters

During a biotypological research of surface waters in the province of Friesland, The Netherlands, the macroinvertebrate fauna was sampled, both from the littoral and bottom substrata. Results of this investigation in different types of water on 60 and 55 stations in 1981 and 1982, respectively, are presented. The species richness in the littoral samples exceeded that of the bottom samples, and the samples per station had relatively few species in common. Even in many cases the most abundant taxon was a different one in both samples of the same spot. With multivariate analysis of the data sets from bottom, littoral and total samples a fairly good resemblance was found between these data sets. It is concluded that the semi-quantitative processing of macroinvertebrate fauna data leads to reliable results. One can use one sample per station, wherein different substrata are combined. Distinct clusters were recognized in more extreme environmental conditions such as brackish and acid waters. With the help of the macroinvertebrate fauna the other types of water could not easily be differentiated.