Diversidade genética entre progênies e matrizes de rambutan

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Imagens aéreas multiespectrais na identificação de zonas de manejo em áreas de algodão para aplicação localizada de insumos

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.

Improving a process in a brazilian automotive plant applying process mapping, Design of Experiments and Discrete Events Simulation

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.

Molecular mapping of the viral determinants of systemic wilting induced by a Lettuce mosaic virus (LMV) isolate in some lettuce cultivars

The isolate AF199 of Lettuce mosaic virus (LMV, genus Potyvirus) causes local lesions followed by systemic wilting and plant death in the lettuce cultivars Ithaca and Vanguard 75. Analysis of the phenotype of virus chimeras revealed that a region within the PI protein coding region (nucleotides 112-386 in the viral genome) and/or another one within the CI protein coding region (nucleoticles 5496-5855) are sufficient together to cause the lethal wilting in Ithaca, but not in Vanguard 75. This indicates that the determinants of this particular symptom are different in these two lettuce cultivars. The wilting phenotype was not directly correlated with differences in the deduced amino acid sequence of these two regions. Furthermore, transient expression of the LMV-AF 199 proteins, separately or in combination, did not induce local necrosis or any other visible reaction in the plants. Together, these results Suggest that the systemic wilting reaction might be Clue to RNA rather than protein sequences. (c) 2004 Elsevier B.V. All rights reserved.

Mapping Macrophyte Species in the Amazon Floodplain Wetlands Using Fully Polarimetric ALOS/PALSAR Data

The purpose of this paper was to evaluate attributes derived from fully polarimetric PALSAR data to discriminate and map macrophyte species in the Amazon floodplain wetlands. Fieldwork was carried out almost simultaneously to the radar acquisition, and macrophyte biomass and morphological variables were measured in the field. Attributes were calculated from the covariance matrix [C] derived from the single-look complex data. Image attributes and macrophyte variables were compared and analyzed to investigate the sensitivity of the attributes for discriminating among species. Based on these analyses, a rule-based classification was applied to map macrophyte species. Other classification approaches were tested and compared to the rule-based method: a classification based on the Freeman-Durden and Cloude-Pottier decomposition models, a hybrid classification (Wishart classifier with the input classes based on the H/a plane), and a statistical-based classification (supervised classification using Wishart distance measures). The findings show that attributes derived from fully polarimetric L-band data have good potential for discriminating herbaceous plant species based on morphology and that estimation of plant biomass and productivity could be improved by using these polarimetric attributes.

Analysis of plant LTR-retrotransposons at the fine-scale family level reveals individual molecular patterns

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mapping QTLs for aluminum tolerance in maize

Aluminum toxicity is one of the major constraints for plant development in acid soils, limiting food production in many countries. Cultivars genetically adapted to acid soils may offer an environmental compatible solution, providing a sustainable agriculture system. The aim of this work was to identify genomic regions associated with Al tolerance in maize, and to quantify the genetic effects on the phenotypic variation. A population of 168 F-3:4 families derived from a cross between two contrasting maize inbred lines for Al tolerance was evaluated using the NSRL and RSRL parameters in nutrient solution containing toxic level of aluminum. Variance analyses indicated that the NSRL was the most reliable phenotypic index to measure Al tolerance in the population, being used for further QTL mapping analysis. RFLP and SSR markers were selected for bulked segregant analysis, and additional SSR markers, flanking the polymorphisms of interest, were chosen in order to saturate the putative target regions. Seven linkage groups were constructed using 17 RFLP and 34 SSR markers. Five QTLs were mapped on chromosomes 2, 6 and 8, explaining 60% of the phenotypic variation. QTL(4) and marker umc043 were located on chromosomes 8 and 5, close to genes encoding for enzymes involved in the organic acids synthesis pathways, a widely proposed mechanism for Al tolerance in plants. QTL(2) was mapped in the same region as Alm2, also associated with Al tolerance in maize. In addition, dominant and additive effects were important in the control of this trait in maize.

Characterization, subsite mapping and N-terminal sequence of miliin, a serine-protease isolated from the latex of Euphorbia milii

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fractal descriptors for discrimination of microscopy images of plant leaves

This study proposes the application of fractal descriptors method to the discrimination of microscopy images of plant leaves. Fractal descriptors have demonstrated to be a powerful discriminative method in image analysis, mainly for the discrimination of natural objects. In fact, these descriptors express the spatial arrangement of pixels inside the texture under different scales and such arrangements are directly related to physical properties inherent to the material depicted in the image. Here, we employ the Bouligand-Minkowski descriptors. These are obtained by the dilation of a surface mapping the gray-level texture. The classification of the microscopy images is performed by the well-known Support Vector Machine (SVM) method and we compare the success rate with other literature texture analysis methods. The proposed method achieved a correctness rate of 89%, while the second best solution, the Co-occurrence descriptors, yielded only 78%. This clear advantage of fractal descriptors demonstrates the potential of such approach in the analysis of the plant microscopy images.

The genome sequence of the plant pathogen Xylella fastidiosa: The Xylella fastidiosa consortium of the organization for nucleotide sequencing and analysis, Sao Paulo, Brazil

Xylella fastidiosa is a fastidious, xylem-limited bacterium that causes a range of economically important plant diseases. Here we report the complete genome sequence of X. fastidiosa clone 9a5c, which causes citrus variegated chlorosis - a serious disease of orange trees. The genome comprises a 52.7% GC-rich 2,679,305-base-pair (bp) circular chromosome and 'two plasmids of 51,158 bp and 1,285 bp. We can assign putative functions to47% of the 2,904 predicted coding regions. Efficient metabolic functions are predicted, with sugars as the principal energy and carbon source, supporting existence in the nutrient-poor xylem sap. The mechanisms associated with pathogenicity and virulence involve toxins, antibiotics and ion sequestration systems, as well as bacterium-bacterium and bacterium-host interactions mediated by a range of proteins. Orthologues of some of these proteins have only been identified in animal and human pathogens; their presence in X. fastidiosa indicates that the molecular basis for bacterial pathogenicity is both conserved and independent of host. At least 83 genes are bacteriophage-derived and include virulence-associated genes from other bacteria, providing direct evidence of phage-mediated horizontal gene transfer.