22 research outputs found

    Analysis of color and texture characteristics of cereals on digital images

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    The color of the grain shell of cereals is an important feature that characterizes the pigments and metabolites contained in it. The grain shell is the main barrier between the grain and the environment, so its characteristics are associated with a number of important biological functions: moisture absorption, grain viability, resistance to pre-harvest germination. The presence of pigments in the shell affects various technological properties of the grain. Color characteristics, as well as the appearance of the grain shell are an important indicator of plant diseases. In addition, the color of the grains serves as a classifying feature of plants. Genetic control of the color formation of both grains and other plant organs is exerted by genes encoding enzymes involved in the biosynthesis of pigments, as well as regulatory genes. For a number of pigments, these genes are well understood, but for some pigments, such as melanin, which causes the black color of grains in barley, the molecular mechanisms of biosynthesis are still poorly understood. When studying the mechanisms of genetic control of grain color, breeders and geneticists are constantly faced with the need to assess the color characteristics of their shell. The technical means of addressing this problem include spectrophotometers, spectrometers, hyperspectral cameras. However, these cameras are expensive, especially with high resolution, both spatial and spectral. An alternative is to use digital cameras that allow you to get high-quality images with high spatial and color resolution. In this regard, recently, in the field of plant phenotyping, methods for evaluating the color and texture characteristics of cereals based on the analysis of two-dimensional images obtained by digital cameras have been intensively developed. This mini-review is devoted to the main tasks related to the analysis of color and texture characteristics of cereals, and to methods of their description based on digital images

    SpikeDroidDB: AN INFORMATION SYSTEM FOR ANNOTATION OF MORPHOMETRIC CHARACTERISTICS OF WHEAT SPIKE

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    The structure of the ear is one of the most important features of cereals associated with such agronomically important traits as productivity, resistance to environmental factors and pests, threshebility. Ears differ in shape, size, density, awnedness, color, etc. Analysis of the ear traits requires visual inspection, manual measurements and is very time-consuming. The effectiveness of ears’ phenotyping can be improved by the introduction of an automated image processing technology, storage of information in databases, use of machine learning algorithms to analyze this information. This paper presents a new approach for collecting, storing and analyzing of information about morphometric characteristics of ears of wheat. Two protocols for obtaining digital images of the ear have been developed. The computer-aided information system SpikeDroidDB has been developed, which allows you to store digital images of the ear, annotate their phenotypic features (14 features, including plant variety description, links to parent genotypes, generation, planting number, ear morphology description). The interface provides a flexible query system to access the data. SpikeDroidDB represents an interconnected representation between genotype, phenotype, location, and growing conditions. The web interface of SpikeDroidDB is available at http://spikedroid.biores. cytogen.ru/ and allows you to work with the system as with desktop computers or mobile devices. We used SpikeDroidDB for the digitization and annotation of a collection of ears of F2 hybrids from crosses between the Australian cultivar of common wheat Triple Dirk and accession KU506 of Chinese wheat Triticum yunnanense. This experiment includes analysis of 104 plants, 230 spike images. The analysis of the variability of ears in form, length, and other traits allowed determination of the type of their genetic control: compactness is controlled by two recessive genes, awn type and hairi ness at the site of attachment of the spikelet to the axis is controlled by single dominant gene type, hairiness on the axis of the spike is controlled by two dominant genes

    Automatic morphology phenotyping of tetra- and hexaploid wheat spike using computer vision methods

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    Intraspecific classification of cultivated plants is necessary for the conservation of biological diversity, study of their origin and their phylogeny. The modern cultivated wheat species originated from three wild diploid ancestors as a result of several rounds of genome doubling and are represented by di-, tetra- and hexaploid species. The identification of wheat ploidy level is one of the main stages of their taxonomy. Such classification is possible based on visual analysis of the wheat spike traits. The aim of this study is to investigate the morphological characteristics of spikes for hexa- and tetraploid wheat species based on the method of high-performance phenotyping. Phenotyping of the quantitative characteristics of the spike of 17 wheat species (595 plants, 3348 images), including eight tetraploids (Triticum aethiopicum, T. dicoccoides, T. dicoccum, T. durum, T. militinae, T. polonicum, T. timopheevii, and T. turgidum) and nine hexaploids (T. compactum, T. aestivum, i:ANK-23 (near-isogenic line of T. aestivum cv. Novosibirskaya 67), T. antiquorum, T. spelta (including cv. Rother Sommer Kolben), T. petropavlovskyi, T. yunnanense, T. macha, T. sphaerococcum, and T. vavilovii), was performed. Wheat spike morphology was described on the basis of nine quantitative traits including shape, size and awns area of the spike. The traits were obtained as a result of image analysis using the WERecognizer program. A cluster analysis of plants according to the characteristics of the spike shape and comparison of their distributions in tetraploid and hexaploid species showed a higher variability of traits in hexaploid species compared to tetraploid ones. At the same time, the species themselves form two clusters in the visual characteristics of the spike. One type is predominantly hexaploid species (with the exception of one tetraploid, T. dicoccoides). The other group includes tetraploid ones (with the exception of three hexaploid ones, T. compactum, T. antiquorum, T. sphaerococcum, and i:ANK-23). Thus, it has been shown that the morphological characteristics of spikes for hexaploid and tetraploid wheat species, obtained on the basis of computer analysis of images, include differences, which are further used to develop methods for plant classifications by ploidy level and their species in an automatic mode

    AN INTEGRATED INFORMATION SYSTEM ON BIORESOURCE COLLECTIONS OF THE FASO OF RUSSIA

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    Biological collections play a huge role in studying biological diversity as systematic storages of biological materials in all combinations and forms. Collection materials have generally been formed over hundreds of years and may describe a vast number of samples counted by billions. Great efforts are made to preserve these materials, as well as to obtain more and more samples. The Russian Federation occupies a huge land area, has a long coastline and huge natural resources, a variety of natural and ecological zones. In this regard, its territory is unique from the viewpoint of biodiversity and development of biological collections. Currently, a large number of collections are being developed in Russia, but there are a number of problems associated, first of all, with the lack of an integrated information resource on bioresource collections (BRC). In order to support the development of scientific infrastructure, the Federal Agency for Scientific Organizations (FASO of Russia) has been working on the development of unified approaches to the use of existing bioresource collections and the establishment of the integrated information system. The paper presents an information portal designed to provide uniform methods of work for all BRC organizations of the FASO of Russia: input, storage, updating and differentiated access to specific information about storage units and their characteristics. The information system “Bioresource Collections of Scientific Organizations” (IS BRC) has been developed as a Web­portal (www.biores.cytogen.ru) integrating databases on bioresource collections of the FASO of Russia and graphical user interface. Access control to the databases integrated into the IS BRC is performed through authorized program access for viewing records, their creation and editing on the basis of REST technology. The graphical user interface (GUI) provides the following features in accordance with the access rights: authorized access to the BRC database; viewing BRC database records; editing BRC database records; creating and deleting BRC database records; statistical data analysis in the BRC database; generation of summary reports on the BRC database; export of records content in PDF/RTF/JSON format. The graphical user interface was implemented using the DRUPAL 7.0 toolkit. Architecturally, the portal is concerned as a central node with a series of modules communicating through the unified interfaces. In this way, we solve the problem of connecting new data sources (collection databases) implemented in different DBMS. Given the fact that currently many organizations support access to the catalogues of their collections independently, the portal also provides external links to these Web resources. At the same time, some information on collections is stored within the BRC databases of the FASO of Russia’s portal in unified formats. The portal contains the following functional sections: the home page containing general information on bioresource collections, the catalog of collections, individual pages for each particular collection with a short description (information about curators, statistical information about the number of storage units in the collection and the number of publications, as well as a link to the catalog of storage units of this BRC). Currently the portal contains more than 13 thousand entities of 65 bioresource collections organizations of the FASO of Russia. It is still being extended

    Image-based analysis of quantitative morphological characteristics of wild potato tubers using the desktop application SeedСounter

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    The development of quantitative digital phenotyping methods for evaluation of wild potato (section Petota Dumort., genus Solanum L.) tuberization is required for annotation of genebank collections and selection of the suitable donor material for potato breeding. There are no available methods specifically designed for the quantitative analysis of wild potato tuber morphology. The current study is devoted to evaluation of wild potato tubers’ morphological characteristics using a digital image processing technique. For this purpose, the mobile application SeedSounter developed previously for grain analysis was specifically adapted for tuber phenotyping. The application estimates the number and shape of objects scattered on a standard sheet of white paper (i. e. A3 or A4). Twelve accessions from the VIR genebank collection belonging to nine Petota species were grown in pots protected with garden fabric during the growing season of cultivated potato (Novosibirsk region). Tubers were collected form plants of nine genotypes. Three genotypes did not produce tubers. The weight of tubers collected from each plant was measured. The tuber yield from each plant was analyzed using SeedCounter (http://wheatdb.org/seedcounter). The number of tubers per plant was counted; the following characteristics were extracted from the images of individual tubers: length, width, projected area, length to width ratio, сircularity, roundness, rugosity and solidity. One-way ANOVA showed a significant effect of genotype on all measured characteristics. A pairwise comparison of nine Petota accessions using all measured parameters revealed statistically significant differences between 86 % of pairs. The overall tuber yield volume for each plant was  calculated as a sum of volumes of individual tubers; tuber volume was calculated from its length to width ratio and projected area. A strong correlation between the evaluated tuber yield volume and yield weight was shown. We propose tuber yield volume as a characteristic for a general evaluation of tuberization for wild potato, implementing the four-step scale from 0 to 3. According to this characteristic, the twelve wild potato accessions studied could be divided into four groups with different tuberization abilities. The evaluated tuberization ability is partially in accordance with previously obtained VIR data. The results presented demonstrate the possibility to use SeedCounter for  wild potato  collections phenotyping

    What is cost-efficient phenotyping? Optimizing costs for different scenarios

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    Progress in remote sensing and robotic technologies decreases the hardware costs of phenotyping. Here, we first review cost-effective imaging devices and environmental sensors, and present a trade-off between investment and manpower costs. We then discuss the structure of costs in various real-world scenarios. Hand-held low-cost sensors are suitable for quick and infrequent plant diagnostic measurements. In experiments for genetic or agronomic analyses, (i) major costs arise from plant handling and manpower; (ii) the total costs per plant/microplot are similar in robotized platform or field experiments with drones, hand-held or robotized ground vehicles; (iii) the cost of vehicles carrying sensors represents only 5–26% of the total costs. These conclusions depend on the context, in particular for labor cost, the quantitative demand of phenotyping and the number of days available for phenotypic measurements due to climatic constraints. Data analysis represents 10–20% of total cost if pipelines have already been developed. A trade-off exists between the initial high cost of pipeline development and labor cost of manual operations. Overall, depending on the context and objsectives, “cost-effective” phenotyping may involve either low investment (“affordable phenotyping”), or initial high investments in sensors, vehicles and pipelines that result in higher quality and lower operational costs

    Quantifying Drosophila

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    BioUniWA – WEB SERVICES GENERATION SYSTEM AND PIPELINES FOR UNIFIED ACCESS TO RESOURCES IN THE FIELD OF BIOINFORMATICS

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    We present the BioUniWA system for automatic generation of web services for unified access to resources in the field of bioinformatics. The BioUniWA system was originally designed as the BioInfoWF development system to support access to computing modules and pipelines through web services. BioUniWA can automatically generate web-based applications for computational modules and pipelines whose formal descriptions are defined by a language based on XML. In the future, one will be able to use these web-based applications in a variety of bioinformational systems, such as Taverna or Galaxy, as well as directly in the source code of applications to be developed. We have designed a tool that greatly simplifies the annotation of computing modules and schemes of pipelines, as well as their publication via Internet.BioUniWA is distributed under a free GNU general public license. The distribution package and user documentation are available at BioUniWA http://bioinfowf.bionet.nsc.ru

    BioInfoWF – WEB SERVICES AND WEB INTERFACES GENERATOR FOR BIOINFORMATICS ANALYSIS

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    The BioinfoWF (Bioinformatics WorkFlow) system for automated generation of Web interface and Web services for bioinformatics programs. Each program module used in the system has metadescription in XML. The metadescriptions are used for automated generation of Web interface and Web services that can be used further in bioinformatics workflows. Computational modules can be organized in workflows. The tool we have developed significantly simplify the design and publication of modules for bioinformatics data analysis via the internet and their availability for scientific communities. The developed system makes is distributed under GNU GPL. The Source codes and documentation for BioinfoWF are available at http://bioinfowf.bionet.nsc.ru
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