993 resultados para Plant mapping
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Crop yield is influenced by several factors with variability in time and space that are associated with the variations in the plant vigor. This variability allows the identification of management zones and site-specific applications to manage different regions of the field. The purpose of this study was the use of multispectral image for management zones identification and implications of site-specific application in commercial cotton areas. Multispectral airborne images from three years were used to classify a field into three vegetation classes via the Normalized Difference Vegetation Index (NDVI). The NDVI classes were used to verify the potential differences between plant physical measurements and identify management zones. The cotton plant measurements sampled in 8 repetitions of 10 plants at each NDVI class were Stand Count, Plant Height, Total Nodes and Total Bolls. Statistical analysis was performed with treatments arranged in split plot design with Tukey’s Test at 5% of probability. The images were classified into five NDVI classes to evaluate the relationship between cotton plant measurement results and sampling location across the field. The results have demonstrated the possibility of using multispectral image for management zones identification in cotton areas. The image classification into three NDVI classes showed three different zones in the field with similar characteristics for the studied years. Statistical differences were shown for plant height, total nodes and total bolls between low and high NDVI classes for all years. High NDVI classes contained plants with greater height, total nodes and total bolls compared to low NDVI classes. There was no difference in Stand Count between low and high NDVI classes for the three studied years. The final plant stand was the same between all NDVI classes for 2001 and 2003 as it was expected due to the conventional seeding application with the same rate of seeds for the entire field.
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Ravaged by Nature, page 3 Hurricanes Katrina and Rita left millions of dollars of damage in their wake. Focus on…Comprehensive Conservation Planning, pages 10-14 What does it take to draft a first-rate CCP? How does a refuge reach out and communicate with partners and community? Baby Switch in High Places, page 21 Refuge biologists in California successfully swap a fertile for an infertile egg and the condor parents are none the wiser. Invasive Plant Mapping, page 9 Volunteers using state-of-the-arttechnology are helping to map and control invasive plants.
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Net form of net blotch (NFNB), caused by Pyrenophora teres Drechs. f. teres Smedeg., is a serious disease problem for the barley industry in Australia and other parts of the world. Three doubled haploid barley populations, Alexis/Sloop, WI2875-1/Alexis, and Arapiles/Franklin, were used to identify genes conferring adult plant resistance to NFNB in field trials. Quantitative trait loci (QTLs) identified were specific for adult plant resistance because seedlings of the parental lines were susceptible to the NFNB isolates used in this study. QTLs were identified on chromosomes 2H, 3H, 4H, and 7H in both the Alexis/Sloop and WI2875-1/Alexis populations and on chromosomes 1H, 2H, and 7H in the Arapiles/Franklin population. Using QTLNetwork, epistatic interactions were identified between loci on chromosomes 3H and 6H in the Alexis/Sloop population, between 2H and 4H in the WI2875-1/Alexis population, and between 5H and 7H in the Arapiles/Franklin population. Comparisons with earlier studies of NFNB resistance indicate the pathotype-dependent nature of many resistance QTLs and the importance of establishing an international system of pathotype nomenclature and differential testing.
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The objective of this article is to apply the Design of Experiments technique along with the Discrete Events Simulation technique in an automotive process. The benefits of the design of experiments in simulation include the possibility to improve the performance in the simulation process, avoiding trial and error to seek solutions. The methodology of the conjoint use of Design of Experiments and Computer Simulation is presented to assess the effects of the variables and its interactions involved in the process. In this paper, the efficacy of the use of process mapping and design of experiments on the phases of conception and analysis are confirmed.
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In wheat, stem rust is known to rapidly evolve new virulence to resistance genes. While more than 50 stem rust resistance (Sr) loci have been identified in wheat, only a few remain effective, particularly against the highly virulent race Ug99 (TTKSK race) and a mixture of durum-specific races. An association mapping (AM) study based on 183 durum wheat accessions was utilized to identify resistance loci for stem rust response in Ethiopia over four seasons and artificial inoculation with Ug99 (TTKSK race) and a mixture of durum-specific races under field conditions as well as in greenhouse test at seedling stage under controlled conditions for resistance to four highly virulent stem rust races: TRTTF, TTTTF, (TTKSK (Ug99) and JRCQC. The panel was profiled with 1,253 SSR and DArT markers. Twelve QTL-tagging markers were significant (P < 0.05) across three to four seasons. The role of Sr13, Sr9, Sr14, Sr17, and Sr28 was confirmed. Thirteen significant markers were in regions with no Sr genes/QTLs. The results under controlled conditions showed that 15, 20, 19 and 19 chromosome regions harbored markers that showed significant effects for races TRTTF, TTTTF, TTKSK and JRCQC, respectively. These genomic regions showed marker R2 values ranging from 1.13 to 8.34, 1.92 to 17.64, 1.75 to 23.12 and 1.51 to 15.33% for races TRTTF, TTTTF, TTKSK and JRCQC, respectively. The study demonstrates that stem rust resistance in durum wheat is governed in part by shared loci and in part by race-specific ones. The QTLs identified in this study through AM will be useful in the marker-assisted development of durum wheat cultivars with durable stem rust resistance.
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Root-yield-1.06 is a major QTL affecting root system architecture (RSA) and other agronomic traits in maize. The effect of this QTL has been evaluated with the development of near isogenic lines (NILs) differing at the QTL position. The objective of this study was to fine map qroot-yield-1.06 by marker-assisted searching for chromosome recombinants in the QTL interval and concurrent root phenotyping in both controlled and field conditions, through successive generations. Complementary approaches such as QTL meta-analysis and RNA-seq were deployed in order to help prioritizing candidate genes within the QTL target region. Using a selected group of genotypes, field based root analysis by ‘shovelomics’ enabled to accurately collect RSA information of adult maize plants. Shovelomics combined with software-assisted root imaging analysis proved to be an informative and relatively highly automated phenotyping protocol. A QTL interval mapping was conducted using a segregating population at the seedling stage grown in controlled environment. Results enabled to narrow down the QTL interval and to identify new polymorphic markers for MAS in field experiments. A collection of homozygous recombinant NILs was developed by screening segregating populations with markers flanking qroot-yield-1.06. A first set of lines from this collection was phenotyped based on the adapted shovelomics protocol. QTL analysis based on these data highlighted an interval of 1.3 Mb as completely linked with the target QTL but, a larger safer interval of 4.1 Mb was selected for further investigations. QTL meta-analysis allows to synthetize information on root QTLs and two mQTLs were identified in the qroot-yield-1.06 interval. Trascriptomics analysis based on RNA-seq data of the two contrasting QTL-NILs, confirmed alternative haplotypes at chromosome bin 1.06. qroot-yield-1.06 has now been delimited to a 4.1-Mb interval, and thanks to the availability of additional untested homozygous recombinant NILs, the potentially achievable mapping resolution at qroot-yield-1.06 is c. 50 kb.
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There is a growing call for inventories that evaluate geographic patterns in diversity of plant genetic resources maintained on farm and in species' natural populations in order to enhance their use and conservation. Such evaluations are relevant for useful tropical and subtropical tree species, as many of these species are still undomesticated, or in incipient stages of domestication and local populations can offer yet-unknown traits of high value to further domestication. For many outcrossing species, such as most trees, inbreeding depression can be an issue, and genetic diversity is important to sustain local production. Diversity is also crucial for species to adapt to environmental changes. This paper explores the possibilities of incorporating molecular marker data into Geographic Information Systems (GIS) to allow visualization and better understanding of spatial patterns of genetic diversity as a key input to optimize conservation and use of plant genetic resources, based on a case study of cherimoya (Annona cherimola Mill.), a Neotropical fruit tree species. We present spatial analyses to (1) improve the understanding of spatial distribution of genetic diversity of cherimoya natural stands and cultivated trees in Ecuador, Bolivia and Peru based on microsatellite molecular markers (SSRs); and (2) formulate optimal conservation strategies by revealing priority areas for in situ conservation, and identifying existing diversity gaps in ex situ collections. We found high levels of allelic richness, locally common alleles and expected heterozygosity in cherimoya's putative centre of origin, southern Ecuador and northern Peru, whereas levels of diversity in southern Peru and especially in Bolivia were significantly lower. The application of GIS on a large microsatellite dataset allows a more detailed prioritization of areas for in situ conservation and targeted collection across the Andean distribution range of cherimoya than previous studies could do, i.e. at province and department level in Ecuador and Peru, respectively.
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Mapping of vegetation patterns over large extents using remote sensing methods requires field sample collections for two different purposes: (1) the establishment of plant association classification systems from samples of relative abundance estimates; and (2) training for supervised image classification and accuracy assessment of satellite data derived maps. One challenge for both procedures is the establishment of confidence in results and the analysis across multiple spatial scales. Continuous data sets that enable cross-scale studies are very time consuming and expensive to acquire and such extensive field sampling can be invasive. The use of high resolution aerial photography (hrAP) offers an alternative to extensive, invasive, field sampling and can provide large volume, spatially continuous, reference information that can meet the challenges of confidence building and multi-scale analysis.
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Mapping the abundance of 13C in leaf-wax components in surface sediments recovered from the seafloor off northwest Africa (0-35°N) reveals a clear pattern of delta13C distribution, indicating systematic changes in the proportions of terrestrial C3 and C4 plant input. At 20°N latitude, we find that isotopically enriched products characteristic of C4 plants account for more than 50% of the terrigenous inputs. This signal extends westward beneath the path of the dust-laden Sahara Air Layer (SAL). High C4 contributions, apparently carried by January trade winds, also extend far into the Gulf of Guinea. Similar distributions are obtained if summed pollen counts for the Chenopodiaceae-Amaranthaceae and the Poaceae are used as an independent C4 proxy. We conclude that the specificity of the latitudinal distribution of vegetation in North West Africa and the pathways of the wind systems (trade winds and SAL) are responsible for the observed isotopic patterns observed in the surface sediments. Molecular-isotopic maps on the marine-sedimentary time horizons (e.g., during the last glacial maximum) are thus a robust tool for assessing the phytogeographic changes on the tropical and sub-tropical continents, which have important implications for the changes in climatic and atmospheric conditions.
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2008
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Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.
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Forward genetic screens have identified numerous genes involved in development and metabolism, and remain a cornerstone of biological research. However, to locate a causal mutation, the practice of crossing to a polymorphic background to generate a mapping population can be problematic if the mutant phenotype is difficult to recognize in the hybrid F2 progeny, or dependent on parental specific traits. Here in a screen for leaf hyponasty mutants, we have performed a single backcross of an Ethane Methyl Sulphonate (EMS) generated hyponastic mutant to its parent. Whole genome deep sequencing of a bulked homozygous F2 population and analysis via the Next Generation EMS mutation mapping pipeline (NGM) unambiguously determined the causal mutation to be a single nucleotide polymorphisim (SNP) residing in HASTY, a previously characterized gene involved in microRNA biogenesis. We have evaluated the feasibility of this backcross approach using three additional SNP mapping pipelines; SHOREmap, the GATK pipeline, and the samtools pipeline. Although there was variance in the identification of EMS SNPs, all returned the same outcome in clearly identifying the causal mutation in HASTY. The simplicity of performing a single parental backcross and genome sequencing a small pool of segregating mutants has great promise for identifying mutations that may be difficult to map using conventional approaches.
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Experience gained from numerous projects conducted by the U.S. Environmental Protection Agency's (EPA) Environmental Monitoring Systems Laboratory in Las Vegas, Nevada has provided insight to functional issues of mapping, monitoring, and modeling of wetland habitats. Three case studies in poster form describe these issues pertinent to managing wetland resources as mandated under Federal laws. A multiphase project was initiated by the EPA Alaska operations office to provide detailed wetland mapping of arctic plant communities in an area under petroleum development pressure. Existing classification systems did not meet EPA needs. Therefore a Habitat Classification System (HCS) derived from aerial photography was compiled. In conjunction with this photointerpretive keys were developed. These products enable EPA personnel to map large inaccessible areas of the arctic coastal plain and evaluate the sensitivity of various wetland habitats relative to petroleum development needs.