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.     

Prunus necrotic ringspot virus isolates in stone fruit germplasm accessions and cultivars in Israel

Prunus necrotic ringspot virus (PNRSV) was detected in almonds, plum and apricot germplasm accessions and local almond cultivars in Israel. PNRSV was widespread both in wild and cultivated almond trees and uncommon in wild apricots and plums. The possible variation among the PNRSV isolates was initially evaluated by restriction analysis of PCR products representing the CP gene with the endonuclease RsaI and followed by nucleotide sequence analysis of selected isolates. It was concluded that all 13 isolates belong to group PV96, the largest cluster of PNRSV isolates, described previously. Two PNRSV isolates, one from a plum accession and one from an almond cultivar, were found to be distinct members of group PV96 with unique nucleotide modifications not found in other documented isolates of this virus. However, no PNRSV isolate typical to a specific host and/or to the Middle East region could be identified. This study expands the body of data on variability of PNRSV isolates and highlights the importance of assessing the virus status of germplasm collections by applying reliable diagnostic and differentiating methods.     

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.