294 resultados para STRAIN VARIABILITY
Resumo:
Leafroll is an economically important disease affecting grapevines (Vitis spp.). Nine serologically distinct viruses, Grapevine leafroll-associated virus-1 through 9, are associated with this disease. The present study describes the coat protein gene sequence of four GLRaV-3 isolates occurring in the São Francisco River basin, Northeastern Brazil. The viral RNA was extracted from GLRaV-3 ELISA-positive plants and the complete coat protein gene was amplified by RT-PCR. Sequences were generated automatically and compared to the complete coat protein sequence from North American (NY1) and Chinese (Dawanhong Nº2 and SL10) GLRaV-3 isolates. The four studied isolates, named Pet-1 through 4, showed deduced amino acid identities of 98-100% (Pet-1 through 3) and 95% (Pet-4) with North American and Chinese isolates. A total of seventeen amino acid substitutions was detected among the four characterized isolates in comparison to the NY1, Dawanhong No.2 and SL10 sequences. The results indicated the existence of natural variation among GLRaV-3 isolates from grapevines, also demonstrating a lack of correlation between sequence data and geographic origin. This variability should be considered when selecting regions of the viral genome targeted for reliable and consistent virus molecular detection.
Resumo:
Four cultivars and 21 lines of cotton were evaluated for resistance to ramulose (Colletotrichum gossypii f. sp. cephalosporioides) in a field where the disease is endemic. The seeds of each genotype were planted in 5 x 5 m plots with three replications. The lines CNPA 94-101 and 'CNPA Precoce 2'were used as standard susceptible and resistant references, respectively. The disease incidence (DI) was calculated from the proportion of diseased plants in the plot. The disease index (DIn) was calculated from the disease severity using a 1 to 9 scale, and was evaluated at weekly intervals starting 107 days after emergence. The data collected was used to calculate the area under disease progress curve (AUDPC). In general, the DIn increased linearly with time and varied from 20.0 to 57.1 and AUDPC from 567 to 1627 among the genotypes which could be clustered in to two distinct groups. The susceptible group contained two cultivars and nine lines and the resistant group contained one cultivar and 12 lines. The relationship between disease index and evaluation times was linear for the 25 genotypes tested. The line CNPA 94-101, used as susceptible standard, was the most susceptible with an average DI = 83.4, DIn = 57.1 and AUDPC = 1627.7. The line CNPA 96-08 with DI = 37.8, DIn = 20.0 and AUDPC = 567.7 was the most resistant one. Among the commercial cultivars 'IAC 22' was the most susceptible and 'CNPA Precoce 2', used as resistant standard was the most resistant. The variability in virulence of the pathogen was studied by spray inoculating nine genotypes with conidial suspensions (10(5)/mL) of either of the 10 isolates. The disease severity was evaluated 30 days later using a scale of 1 to 5. The virulence of the isolate was expressed by DIn. All the isolates were highly virulent but their virulence avaried for several genotypes and could be clustered in two distinct groups of less and more virulent isolates. The isolate MTRM 14 from Mato Grosso was the least virulent while Minas Gerais was the most virulent, with DIn of 6.36 and 46.47, respectively. In this experiment the line HR 102 and the cultivar 'Antares' were the most resistant ones with DIns of 18.32 and 19.14, respectively.
Resumo:
LMV is one of the most important pathogens of lettuce worldwide. Based on their ability to overcome the resistance genes mo1¹ and mo1² in lettuce, isolates can be divided in two types: LMV-Most, which can infect and are seed-borne in cultivars containing the mo1 gene and LMV-Common, which do not cause symptoms on these cultivars and are seed transmitted only in susceptible cultivars. To evaluate the occurrence of these two types of LMV isolates, a survey was carried out during 2002-2005 in three lettuce production areas from São Paulo State. Total RNA was used for the diagnosis of LMV isolates by RT-PCR using universal primers for the variable N-terminus of the capsid protein, in the 3' end of the genome. Positives samples were analyzed by a second RT-PCR using specifics primers for LMV-Most isolates designed to amplify a fragment from the central region (CI-VPg) of the genome. A total of 1362 samples showing mosaic symptoms were collected and 504 (37.29 %) were positives for LMV. On susceptible lettuce cultivars, LMV-Common was prevalent (77.3%). LMV-Most was found frequently associated with tolerant (mo1¹) lettuce cultivars. Susceptible cultivars correspond today for most of the area of lettuce production. So, despite the ability of LMV-Most isolates to overcome the resistance provided by the recessive mo1¹ gene, they are not prevalent in the conditions of São Paulo State.
Resumo:
Studies on the genetic variability of Puccinia triticina in inoculum collected in Brazil started in 1941 with Vallega (20). The pioneering work in Brazil dates from 1949 (16) at "Instituto Agronômico do Sul", Ministry of Agriculture (MA), in Pelotas, Rio Grande do Sul State (RS), and continued after 1975 at Embrapa Wheat in Passo Fundo, RS. In 2002, analyses for the identification of P. triticina races continued at OR Seed breeding, simultaneously to Embrapa's program, both in Passo Fundo. The investigators involved in the identification of races in Brazil were Ady Raul da Silva in Pelotas (MA), Eliza Coelho in Pelotas (MA) and in Passo Fundo (Embrapa), Amarilis Labes Barcellos in Pelotas (MA) and in Passo Fundo (Embrapa and OR), Camila Turra in Passo Fundo (OR) and Marcia Chaves in Passo Fundo (Embrapa). From 1979 to 2010 growing season, 59 races were determined, according to the differentiation based on the expression of each Lr resistance gene. On average, one to three new races are detected per year. Research has focused on the use of vertical resistance; however, lately some institutes have searched more durable resistance, of the adult-plant type (horizontal, less race-specific). The uninterrupted monitoring of the wheat rust pathogenic population in Brazil during so many decades allowed the understanding of the evolution and virulence of races. The use of international nomenclature adopted by some programs has allowed the comparison of the fungus variability in Brazil with that in other countries, especially where frontiers are not barriers for spore transportation, confirmed by the occurrence of the same races all over one region.
Resumo:
This study aimed to evaluate the genetic variability among individuals of a base population of Eucalyptus grandis and to build a molecular marker database for the analyzed populations. The Eucalyptus grandis base population comprised 327 individuals from Coff's Harbour, Atherton and Rio Claro. A few plants came from other sites (Belthorpe MT. Pandanus, Kenilworth, Yabbra, etc.). Since this base population had a heterogeneous composition, the groups were divided according to geographic localization (latitude and longitude), and genetic breeding level. Thus, the influence of those two factors (geographic localization and genetic breeding level) on the genetic variability detected was discussed. The RAPD technique allowed the evaluation of 70 loci. The binary matrix was used to estimate the genetic similarity among individuals using Jaccard's Coefficient. Parametric statistical tests were used to compare within-group similarity of the means. The obtained results showed that the base population had wide genetic variability and a mean genetic similarity of 0.328. Sub-group 3 (wild materials from the Atherton region) showed mean genetic similarity of 0.318. S.P.A. (from Coff's Harbour region) had a mean genetic similarity of 0.322 and was found to be very important for maintenance of variation in the base population. This can be explained since the individuals from those groups accounted for most of the base population (48.3% for it). The base population plants with genetic similarity higher than 0.60 should be phenotypically analyzed again in order to clarify the tendency of genetic variability during breeding programs.
Resumo:
Despite considerable efforts to develop accurate electronic sensors to measure leaf wetness duration (LWD), little attention has been given to studies about how is LWD variability in different positions of the crop canopy. In order to evaluate the influence of 'Niagara Rosada' (Vitis labrusca) grapevine structure on the spatial variability of LWD, the objective of this study was to determine the canopy position of the ÂNiagara Rosada table grape with longer LWD and its correlation with measured standard LWD over turfgrass. LWD was measured in four different canopy positions of the vineyard (sensors deployed at 45º with the horizontal): at the top of the plants, with sensors facing southwest and northeast (Top-SW and Top-NE), and at the grape bunches height, with sensors facing southwest and northeast (Bottom-SW and Bottom-NE). No significant difference was observed between the top (1.6 m) and the bottom (1.0 m) of the canopy and also between the southwest and northeast face of the plants. The relationship between standard LWD over turfgrass and crop LWD in different positions of the grape canopy showed a define correlation, with R² ranging from 0.86 to 0.89 for all period, from 0.72 to 0.77 for days without rain, and from 0.89 to 0.91 for days with rain.
Resumo:
To study Assessing the impact of tillage practices on soil carbon losses dependents it is necessary to describe the temporal variability of soil CO2 emission after tillage. It has been argued that large amounts of CO2 emitted after tillage may serve as an indicator for longer-term changes in soil carbon stocks. Here we present a two-step function model based on soil temperature and soil moisture including an exponential decay in time component that is efficient in fitting intermediate-term emission after disk plow followed by a leveling harrow (conventional), and chisel plow coupled with a roller for clod breaking (reduced) tillage. Emission after reduced tillage was described using a non-linear estimator with determination coefficient (R²) as high as 0.98. Results indicate that when emission after tillage is addressed it is important to consider an exponential decay in time in order to predict the impact of tillage in short-term emissions.
Resumo:
The technique of precision agriculture and soil-landscape allows delimiting areas for localized management, allowing a localized application of agricultural inputs and thereby may contribute to preservation of natural resources. Therefore, the objective of this work was to characterize the spatial variability of chemical properties and clay content in the context of soil-landscape relationship in a Latosol (Oxisol) under cultivation of citrus. Soil samples were collected at a depth of 0.0-0.2 m in an area of 83.5 ha planted with citrus, as a 50-m intervals grid, with 129 points in concave terrain and 206 points in flat terrain, totaling 335 points. Values for the variables that express the chemical characteristics and clay content of soil properties were analyzed with descriptive statistics and geostatistical modeling of semivariograms for making maps of kriging. The values of range and kriging maps indicated higher variability in the shape of concave topography (top segment) compared with the shape of flat topography (slope and hillside segments below). The identification of different forms of terrain proved to be efficient in understanding the spatial variability of chemical properties and clay content of soil under cultivation of citrus.
Resumo:
The characterization of the spatial variability of soil attributes is essential to support agricultural practices in a sustainable manner. The use of geostatistics to characterize spatial variability of these attributes, such as soil resistance to penetration (RP) and gravimetric soil moisture (GM) is now usual practice in precision agriculture. The result of geostatistical analysis is dependent on the sample density and other factors according to the georeferencing methodology used. Thus, this study aimed to compare two methods of georeferencing to characterize the spatial variability of RP and GM as well as the spatial correlation of these variables. Sampling grid of 60 points spaced 20 m was used. For RP measurements, an electronic penetrometer was used and to determine the GM, a Dutch auger (0.0-0.1 m depth) was used. The samples were georeferenced using a GPS navigation receiver, Simple Point Positioning (SPP) with navigation GPS receiver, and Semi-Kinematic Relative Positioning (SKRP) with an L1 geodetic GPS receiver. The results indicated that the georeferencing conducted by PPS did not affect the characterization of spatial variability of RP or GM, neither the spatial structure relationship of these attributes.
Resumo:
The aim of this study was to characterize the spatial variability of soil bulk density (Bd), soil moisture content (θ) and total porosity (Tp) in two management systems of sugarcane harvesting, with or without burning, in a Haplustox soil, in the 0-0.20 m layer. The study area is located in Rio Brilhante, state of Mato Grosso do Sul, Brazil, in Eldorado Sugar Mill. The plots have presented 180 m length, and 145.6 m width, totaling 90 points distributed in the form of a grid of nine rows by ten columns, with points spaced 20 m from its neighbor. Soil samples were collected at 0-0.20 m layer in 2007/2008 and 2008/2009 crops. The harvest with burning system had a higher density compared to mechanized harvest, in the two study periods. The moisture content as well as the porosity increased proportionally with the decrease of the density of the harvest burning system compared to the mechanized.
Resumo:
Information about rainfall erosivity is important during soil and water conservation planning. Thus, the spatial variability of rainfall erosivity of the state Mato Grosso do Sul was analyzed using ordinary kriging interpolation. For this, three pluviograph stations were used to obtain the regression equations between the erosivity index and the rainfall coefficient EI30. The equations obtained were applied to 109 pluviometric stations, resulting in EI30 values. These values were analyzed from geostatistical technique, which can be divided into: descriptive statistics, adjust to semivariogram, cross-validation process and implementation of ordinary kriging to generate the erosivity map.Highest erosivity values were found in central and northeast regions of the State, while the lowest values were observed in the southern region. In addition, high annual precipitation values not necessarily produce higher erosivity values.
Resumo:
The knowledge of the spatial variability of noise levels and the build of kriging maps can help the evaluation of the salubrity of environments occupied by agricultural workers. Therefore, the objective of this research was to characterize the spatial variability of the noise level generated by four agricultural machines, using geostatistics, and to verify if the values are within the limits of human comfort. The evaluated machines were: harvester, chainsaw, brushcutter and tractor. The data were collected at the height of the operator's ear and at different distances. Through the results, it was possible to verify that the use of geostatistics, by kriging technique, made it possible to define areas with different levels for the data collected. With exception of the harvester, all of machines presented noise levels above than 85 dB (A) near to the operator, demanding the use of hearing protection.
Resumo:
In the last few years, precision agriculture has become commonly used with many crops, particularly cereals, and there is also interest in precision horticulture. Pear is a seasonal fruit and well appreciated by Brazilian people, although it is mostly imported. Brazilian farmers are nowadays trying to increase pear production. Thus, this research aimed at mapping the yield of pear trees in order to study the spatial variability of yield as well as its comparison with spatial variability of soil and plant attributes. The experimental field had 146 pear trees, variety 'Pêra d'água', distributed on a 1.24 ha. Four harvests were performed according to the fruit ripening and from each tree; only the ripe fruits were harvested. In each harvest, all the fruits were weighed and the total yield was obtained based on the sum of each harvest. The soil attributes analyzed were P, K, Ca, Mg, pH in CaCl2, C, Cu, Zn, Fe, Mn and base saturation, and the plant attributes were fruit length, diameter and yield. Yield had low correlation with soil and plant attributes. An index of spatial variability was suggested in this study and helped in classifying levels of spatial dependence of the various soil and plant attributes: very low (fruit length); low (P, fruit diameter), medium (Mg, pH, Cu, Zn, Fe), high (Ca, K, base saturation and yield), and very high (Mn and C).
Resumo:
A study about the spatial variability of data of soil resistance to penetration (RSP) was conducted at layers 0.0-0.1 m, 0.1-0.2 m and 0.2-0.3 m depth, using the statistical methods in univariate forms, i.e., using traditional geostatistics, forming thematic maps by ordinary kriging for each layer of the study. It was analyzed the RSP in layer 0.2-0.3 m depth through a spatial linear model (SLM), which considered the layers 0.0-0.1 m and 0.1-0.2 m in depth as covariable, obtaining an estimation model and a thematic map by universal kriging. The thematic maps of the RSP at layer 0.2-0.3 m depth, constructed by both methods, were compared using measures of accuracy obtained from the construction of the matrix of errors and confusion matrix. There are similarities between the thematic maps. All maps showed that the RSP is higher in the north region.
Resumo:
This study aimed to evaluate the spatial variability of leaf content of macro and micronutrients. The citrus plants orchard with 5 years of age, planted at regular intervals of 8 x 7 m, was managed under drip irrigation. Leaf samples were collected from each plant to be analyzed in the laboratory. Data were analyzed using the software R, version 2.5.1 Copyright (C) 2007, along with geostatistics package GeoR. All contents of macro and micronutrients studied were adjusted to normal distribution and showed spatial dependence.The best-fit models, based on the likelihood, for the macro and micronutrients were the spherical and matern. It is suggest for the macronutrients nitrogen, phosphorus, potassium, calcium, magnesium and sulfur the minimum distances between samples of 37; 58; 29; 63; 46 and 15 m respectively, while for the micronutrients boron, copper, iron, manganese and zinc, the distances suggests are 29; 9; 113; 35 and 14 m, respectively.