Statistical analysis of texture in trunk images for biometric identification of tree species

The identification of tree species is a key step for sustainable management plans of forest resources, as well as for several other applications that are based on such surveys. However, the present available techniques are dependent on the presence of tree structures, such as flowers, fruits, and leaves, limiting the identification process to certain periods of the year Therefore, this article introduces a study on the application of statistical parameters for texture classification of tree trunk images. For that, 540 samples from five Brazilian native deciduous species were acquired and measures of entropy, uniformity, smoothness, asymmetry (third moment), mean, and standard deviation were obtained from the presented textures. Using a decision tree, a biometric species identification system was constructed and resulted to a 0.84 average precision rate for species classification with 0.83accuracy and 0.79 agreement. Thus, it can be considered that the use of texture presented in trunk images can represent an important advance in tree identification, since the limitations of the current techniques can be overcome.

GuiaTreeKey, a multi-access electronic key to identify tree genera in French Guiana

International audience

Identification of 'Ubá' mango tree zygotic and nucellar seedlings using ISSR markers

Polyembryonic seeds are characterized by the development of over one embryo in the same seed, which can be zygotic and nucellar. The objective of this work was to identify the genetic origin, whether zygotic or nucellar, of seedlings of polyembryonic seeds of 'Ubá' mango tree using ISSR markers, and relating them with the vigor of the seedlings. Thus, mangos were harvested in Visconde do Rio Branco (accession 102) and Ubá (accessions 112, 138, 152 and 159), whose seeds were germinated in plastic trays filled with washed sand. Fifty days after sowing, seedlings from five seeds of each one of the accessions 102, 112, 138, 159 and from 10 seeds of the accession 152, were analyzed. These sseedlings were characterized and evaluated for plant height, stem circumference and mass of fresh aerial part and the most vigorous seedling was the one displaying at least two of these traits higher than the other seedlings from seed. Leaves were collected for genomic DNA extraction, which was amplified using seven ISSR primers previously selected based on the amplification profile and considering the number and resolution of fragments. Zygotic seedlings were found in 18 seeds, which were the most vigorous in six seeds. The results evidenced the existence of genetic variability in orchards using seedlings grown from seeds, because the farmer usually uses the most vigorous ones, assuming that this is of nucellar origin. These results also indicate that the most vigorous seedling are not always nucellar, inasmuch as of 20% of the total seeds evaluated, the zygotic seedling was the most vigorous.

Updated List and identification key of 219 tree species of white sand forests of the Allpahuayo Mishana National Reserve, Loreto, Peru

White sand forests, although low in nutrients, are characterized not only by several endemic species of plants but also by several monodominant species. In general, plants in this forest have noticeably thin stems. The aim of this work was to elaborate a parallel dichotomous key for the identification of Angiosperm tree species occurring on white sand forests at the Allpahuayo Mishana National Reserve, Loreto, Peru. We compiled a list of species from several publications in order to have the most comprehensive list of species that occur on white sand forest. We found 219 species of Angiosperm, the more abundant species were Pachira brevipes (26.27%), Caraipa utilis (17.90%), Dicymbe uaiparuensis (13.27%), Dendropanax umbellatus (3.28%), Sloanea spathulata (2.52%), Ternstroemia klugiana (2.30%), Haploclathra cordata (2.28%), Parkia igneiflora (1.20%), Emmotum floribundum (1.06%), Ravenia biramosa (1.04%) among others. Most species of white sand forests can be distinguished using characteristics of stems, branches and leaves. This key is very useful for the development of floristic inventories and related projects on white sand forests from Allpahuayo Mishana National Reserve.

Identification and characterization of pathogenic Pestalotiopsis species to pecan tree in Brazil

The objective of this work was to characterize and cluster isolates of Pestalotiopsis species and to identify those that are pathogenic to pecan, based on morphological and molecular characters. Pestalotiopsis spp. isolates were identified by sequencing the internal transcribed spacer (ITS) and β?tubulin regions. Identification methods were compared to indicate the key morphological characters for species characterization. Thirteen isolates were used for the pathogenicity tests. Morphological characterization was performed using the following variables: mycelial growth rate, sporulation, colony pigmentation, and conidial length and width. Ten pathogenic isolates were identified, three as -tubulin regions. Identification methods were compared to indicate the key morphological characters for species characterization. Thirteen isolates were used for the pathogenicity tests. Morphological characterization was performed using the following variables: mycelial growth rate, sporulation, colony pigmentation, and conidial length and width. Ten pathogenic isolates were identified, three as Pestalotiopsis clavispora and three as P. cocculi. The other isolates remained as an undefined species. The morphological characters were efficient for an initial separation of the isolates, which were grouped according to differences at species level, mainly colony diameter, which was identified as an important morphological describer. Beta-tubulin gene sequencing was less informative than the ITS region sequencing for species identification.

Forest tree species diversity: Assessment, analysis and interpretation in the presence of non-identification and non-observance

Abstract not available

De Novo Assembly And Transcriptome Analysis Of The Rubber Tree (hevea Brasiliensis) And Snp Markers Development For Rubber Biosynthesis Pathways.

Hevea brasiliensis (Willd. Ex Adr. Juss.) Muell.-Arg. is the primary source of natural rubber that is native to the Amazon rainforest. The singular properties of natural rubber make it superior to and competitive with synthetic rubber for use in several applications. Here, we performed RNA sequencing (RNA-seq) of H. brasiliensis bark on the Illumina GAIIx platform, which generated 179,326,804 raw reads on the Illumina GAIIx platform. A total of 50,384 contigs that were over 400 bp in size were obtained and subjected to further analyses. A similarity search against the non-redundant (nr) protein database returned 32,018 (63%) positive BLASTx hits. The transcriptome analysis was annotated using the clusters of orthologous groups (COG), gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Pfam databases. A search for putative molecular marker was performed to identify simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). In total, 17,927 SSRs and 404,114 SNPs were detected. Finally, we selected sequences that were identified as belonging to the mevalonate (MVA) and 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways, which are involved in rubber biosynthesis, to validate the SNP markers. A total of 78 SNPs were validated in 36 genotypes of H. brasiliensis. This new dataset represents a powerful information source for rubber tree bark genes and will be an important tool for the development of microsatellites and SNP markers for use in future genetic analyses such as genetic linkage mapping, quantitative trait loci identification, investigations of linkage disequilibrium and marker-assisted selection.

Leaf-, Panel- And Latex-expressed Sequenced Tags From The Rubber Tree (hevea Brasiliensis) Under Cold-stressed And Suboptimal Growing Conditions: The Development Of Gene-targeted Functional Markers For Stress Response.

Hevea brasiliensis is a native species of the Amazon Basin of South America and the primary source of natural rubber worldwide. Due to the occurrence of South American Leaf Blight disease in this area, rubber plantations have been extended to suboptimal regions. Rubber tree breeding is time-consuming and expensive, but molecular markers can serve as a tool for early evaluation, thus reducing time and costs. In this work, we constructed six different cDNA libraries with the aim of developing gene-targeted molecular markers for the rubber tree. A total of 8,263 reads were assembled, generating 5,025 unigenes that were analyzed; 912 expressed sequence tags (ESTs) represented new transcripts, and two sequences were highly up-regulated by cold stress. These unigenes were scanned for microsatellite (SSR) regions and single nucleotide polymorphisms (SNPs). In total, 169 novel EST-SSR markers were developed; 138 loci were polymorphic in the rubber tree, and 98 % presented transferability to six other Hevea species. Locus duplication was observed in H. brasiliensis and other species. Additionally, 43 SNP markers in 13 sequences that showed similarity to proteins involved in stress response, latex biosynthesis and developmental processes were characterized. cDNA libraries are a rich source of SSR and SNP markers and enable the identification of new transcripts. The new markers developed here will be a valuable resource for linkage mapping, QTL identification and other studies in the rubber tree and can also be used to evaluate the genetic variability of other Hevea species, which are valuable assets in rubber tree breeding.

Isolation and molecular identification of planctomycete bacteria from postlarvae of the giant tiger prawn, Penaeus monodon

Bacteria phenotypically resembling members of the phylogenetically distinct planctomycete group of the domain Bacteria were isolated from postlarvae of the giant tiger prawn, Penaeus monodon. A selective medium designed in the light of planctomycete antibiotic resistance characteristics was used for this isolation. Planctomycetes were isolated from both healthy and monodon baculovirus-infected prawn postlarvae, The predominant colony type recovered from postlarvae regardless of viral infection status was nonpigmented. Other, less commonly observed types were pink or orange pigmented, A planctomycete-specific 16S rRNA-directed probe was designed and used to screen the isolates for their identity as planctomycetes prior to molecular phylogenetic characterization. 16S rRNA genes from nine prawn isolates together with two planctomycete reference strains (Planctomyces brasiliensis and Gemmata obscuriglobus) were sequenced and compared with reference sequences from the planctomycetes and other members of the domain Bacteria, Phylogenetic analyses and sequence signatures of the 16S rRNA genes demonstrated that the prawn isolates were members of the planctomycete group, Five representatives of the predominant nonpigmented colony type were members of the Pirellula group within the planctomycetes, as were three pink-pigmented colony type representatives. Homology values and tree topology indicated that representatives of the nonpigmented and pink-pigmented colony types formed two discrete clusters within the Pirellula group, not identical to any known Pirellula species, A sole representative of the orange colony type was a member of the Planctomyces group, virtually identical in 16S rDNA sequence to P. brasiliensis, and exhibited distinctive morphology.

Isolation and identification of the toxic peptides from Lophyrotoma zonalis (Pergidae) sawfly larvae

The broad-leaved paper bark tree Melaleuca quinquenervia (Cav) (Myrtaceae) was introduced into Florida (USA) early in this century it has proliferated to such an extent that urgent measures are now required to control it. The sawfly Lophyrotoma zonalis (Pergidae) has been introduced as a possible biological control agent due to its ability to defoliate M. quinquenervia. Because toxic D-amino acid- containing peptides have been isolated from some sawfly species, L. zonalis larvae were processed using the previously reported method for the recovery of these compounds. The toxins lophyrotomin (as the free C-terminal acid) and a mixture of pergidin and Val(4)-pergidin were isolated at 0.36 and 0.43% yield of the dried larvae, respectively. Both compounds when dosed intraperitoneally to C57/B16 male mice were hepatotoxic with lowest lethal doses of 8 and 32 mg/kg, respectively. The pathology of the liver was different for each compound, with the lophyrotomin free acid causing a periportal haemorrhagic necrosis and the pergidin causing a periacinar coagulative necrosis. (C) 2001 Elsevier Science Ltd. All rights reserved.

Demo: automatic personal identification system for security in critical services: a case study

The demonstration proposal moves from the capabilities of a wireless biometric badge [4], which integrates a localization and tracking service along with an automatic personal identification mechanism, to show how a full system architecture is devised to enable the control of physical accesses to restricted areas. The system leverages on the availability of a novel IEEE 802.15.4/Zigbee Cluster Tree network model, on enhanced security levels and on the respect of all the users' privacy issues.

Osmo- and thermo-adaptation in hyperthermophilic Archaea: identification of compatible solutes accumulation profiles, and biosynthetic routes in Archaeoglobus spp.

Dissertation presented to obtain the Ph.D degree in Biochemistry

Context-based identification of energy consumption in industrial plants

Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.