Prevalence of Lettuce mosaic virus - common strain on three lettuce producing areas from São Paulo State

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.

Tool-supported invariant-based programming

The development of correct programs is a core problem in computer science. Although formal verification methods for establishing correctness with mathematical rigor are available, programmers often find these difficult to put into practice. One hurdle is deriving the loop invariants and proving that the code maintains them. So called correct-by-construction methods aim to alleviate this issue by integrating verification into the programming workflow. Invariant-based programming is a practical correct-by-construction method in which the programmer first establishes the invariant structure, and then incrementally extends the program in steps of adding code and proving after each addition that the code is consistent with the invariants. In this way, the program is kept internally consistent throughout its development, and the construction of the correctness arguments (proofs) becomes an integral part of the programming workflow. A characteristic of the approach is that programs are described as invariant diagrams, a graphical notation similar to the state charts familiar to programmers. Invariant-based programming is a new method that has not been evaluated in large scale studies yet. The most important prerequisite for feasibility on a larger scale is a high degree of automation. The goal of the Socos project has been to build tools to assist the construction and verification of programs using the method. This thesis describes the implementation and evaluation of a prototype tool in the context of the Socos project. The tool supports the drawing of the diagrams, automatic derivation and discharging of verification conditions, and interactive proofs. It is used to develop programs that are correct by construction. The tool consists of a diagrammatic environment connected to a verification condition generator and an existing state-of-the-art theorem prover. Its core is a semantics for translating diagrams into verification conditions, which are sent to the underlying theorem prover. We describe a concrete method for 1) deriving sufficient conditions for total correctness of an invariant diagram; 2) sending the conditions to the theorem prover for simplification; and 3) reporting the results of the simplification to the programmer in a way that is consistent with the invariantbased programming workflow and that allows errors in the program specification to be efficiently detected. The tool uses an efficient automatic proof strategy to prove as many conditions as possible automatically and lets the remaining conditions be proved interactively. The tool is based on the verification system PVS and i uses the SMT (Satisfiability Modulo Theories) solver Yices as a catch-all decision procedure. Conditions that were not discharged automatically may be proved interactively using the PVS proof assistant. The programming workflow is very similar to the process by which a mathematical theory is developed inside a computer supported theorem prover environment such as PVS. The programmer reduces a large verification problem with the aid of the tool into a set of smaller problems (lemmas), and he can substantially improve the degree of proof automation by developing specialized background theories and proof strategies to support the specification and verification of a specific class of programs. We demonstrate this workflow by describing in detail the construction of a verified sorting algorithm. Tool-supported verification often has little to no presence in computer science (CS) curricula. Furthermore, program verification is frequently introduced as an advanced and purely theoretical topic that is not connected to the workflow taught in the early and practically oriented programming courses. Our hypothesis is that verification could be introduced early in the CS education, and that verification tools could be used in the classroom to support the teaching of formal methods. A prototype of Socos has been used in a course at Åbo Akademi University targeted at first and second year undergraduate students. We evaluate the use of Socos in the course as part of a case study carried out in 2007.

Landscape structure in the northern coast of Paraná state, a hotspot for the brazilian Atlantic Forest conservation

The "Serra do Mar" region comprises the largest remnant of the Brazilian Atlantic Forest. The coast of the Paraná State is part of the core area of the "Serra do Mar" corridor and where actions for biodiversity conservation must be planned. In this study we aimed at characterizing the landscape structure in the APA-Guaraqueçaba, the largest protected area in this region, in order to assist environmental policies of this region. Based on a supervised classification of a mosaic of LANDSAT-5-TM satellite images (from March 2009), we developed a map (1:75,000 scale) with seven classes of land use and land cover and analyzed the relative quantities of forests and modified areas in slopes and lowlands. The APA-Guaraqueçaba is comprised mainly by the Dense Ombrophilous Forest (68.6% of total area) and secondary forests (9.1%), indicating a forested landscape matrix; anthropogenic and bare soil areas (0.8%) and the Pasture/Grasslands class (4.2%) were less representative. Slopes were less fragmented and more preserved (96.3% of Dense Ombrophilous Forest and secondary forest) than lowlands (71.3%), suggesting that restoration initiatives in the lowlands must be stimulated in this region. We concluded that most of the region sustains well-conserved ecosystems, highlighting the importance of Paraná northern coast for the biodiversity maintenance of the Atlantic Forest.

Mittarointi- ja raportointitoimintatapojen kehittäminen lean-organisaatiossa

Tämän työn kohdeyrityksessä ryhdyttiin syksyllä 2010 muutostoimenpiteisiin kohti lean-toimintatapaa. Nyt tavoitteena on luoda kuvaus kohdeyrityksen lean-ajattelun mukaisesta mittarointi- ja raportointitoimintatapojen käyttöönotosta pyrkien saamaan kehitystyön avulla toimintatavat tukevat jatkossa paremmin yrityksen toimintaa kohti sen visiota ja strategiaa. Työssä haluttiin erityisesti tuoda esille prosessi, jolla mittareiden ja raporttien uudistus vietiin läpi. Työ voidaan asemoida normatiiviseksi tutkimukseksi, jossa on sekä konstruktiivisen että toiminta-analyyttisen tutkimusotteiden piirteitä. Työ jakautuu teoreettiseen kirjallisuusselvitykseen sekä empiiriseen osaan, joka on tehtiin kvalitatiivisena tapaustutkimuksena. Kohdeyrityksessä vallitsevista mittarointi- ja raportointitoimintatavoista tehtiin nykytilakartoitus, jonka jälkeen yrityksestä valitulle pilottikohteelle määritettiin mittaroinnin ja raportoinnin tavoitetila. Työn merkittävin tulos on kehittämisprosessin kuvaus, joka tehdään pilottilinjalla toteutettujen muutostöiden avulla. Uuden mittariston käyttöönoton työvaiheet dokumentoitiin tarkasti, jotta samaa kehitysprosessia voidaan hyödyntää myöhemmin yrityksen muilla toiminta-alueilla. Päivitetyssä mittaristossa korostetaan sitä, kuinka esimiehen seuraamat mittarit on oltava lähtöisin yrityksen tavoitteista ja kuinka tiimitasolla on vastaavasti pyrittävä täyttämään esimiehen asettamat tavoitteet. Mittareiden tuominen linjan työntekijöiden vastuulle siirtää mittaroinnin painopistettä enemmän työntekijöille sekä lisää valittujen mittareiden seurannan merkitystä.

Bag-of-Features Approach to Unsupervised Visual Object Categorisation

The large and growing number of digital images is making manual image search laborious. Only a fraction of the images contain metadata that can be used to search for a particular type of image. Thus, the main research question of this thesis is whether it is possible to learn visual object categories directly from images. Computers process images as long lists of pixels that do not have a clear connection to high-level semantics which could be used in the image search. There are various methods introduced in the literature to extract low-level image features and also approaches to connect these low-level features with high-level semantics. One of these approaches is called Bag-of-Features which is studied in the thesis. In the Bag-of-Features approach, the images are described using a visual codebook. The codebook is built from the descriptions of the image patches using clustering. The images are described by matching descriptions of image patches with the visual codebook and computing the number of matches for each code. In this thesis, unsupervised visual object categorisation using the Bag-of-Features approach is studied. The goal is to find groups of similar images, e.g., images that contain an object from the same category. The standard Bag-of-Features approach is improved by using spatial information and visual saliency. It was found that the performance of the visual object categorisation can be improved by using spatial information of local features to verify the matches. However, this process is computationally heavy, and thus, the number of images must be limited in the spatial matching, for example, by using the Bag-of-Features method as in this study. Different approaches for saliency detection are studied and a new method based on the Hessian-Affine local feature detector is proposed. The new method achieves comparable results with current state-of-the-art. The visual object categorisation performance was improved by using foreground segmentation based on saliency information, especially when the background could be considered as clutter.

Reforestation feasibility in area formerly used for cattle rasing in the state of Rondônia, Northwest Brazilian Amazon

Little knowledge on initial behavior of native tree species in recovering landscapes in the Amazon is a current concern for expanding reforestation in the region. Thus, the aim of this study was to evaluate the establishment of native tree species that could be used for reforestation in area previously covered by a pasture of brachiaria grass (Brachiaria brizantha) destined for intensive cattle rasing in the State of Rondônia. For this, there were performed previous diagnostic of landscape changes and the election of tree species based on the ecological group information. Some of the critical macronutrients for plant growth were supplied in the holes to alleviate nutrient deficiencies. In addition, growth and survival parameters were taken to evaluate the initial behavior of species. Six native tree species planted with different combinations (10mx10m, 5mx5m and 3mx3m) had survival rate and growth (total height, girth stem and crown projection area) measured in different intervals: 6-month, 12-month and 24-month after planting. All the species presented survival rate over 90% at 24 months and comparable growth indices to other native species under similar situation and in the region. Overall, Schizolobium amazonicum (bandarra), the non-identified legume tree 1 (acácia grande) and Colubrina glandulosa (sóbrasil) averaged over 90% the highest girth stem growth all over the area. S. amazonicum and the non-identified legume tree 1 (acácia grande) presented the best results for height and canopy area growth parameters, respectively. The combination among native tree species from initial successional ecological groups and fertilizer was favorable to promote reforestation in the conditions of the study area in Rondônia.

Genetic structure and diversity of Copaifera langsdorffii Desf. in Cerrado fragments of the São Paulo State, Brazil

The loss of large areas of Cerrado (Brazilian savanna) in Brazil can lead to reduced biodiversity and to the extinction of species. Therefore, the present study aimed to investigate the genetic fragility of populations of Copaifera langsdorffii Desf exposed to different anthropic conditions in fragments of Cerrado in the state of São Paulo. The study was carried out in two Experimental Stations operated by the Forest Institute (Assis and Itirapina), in one fully protected conservation unit (Pedregulho) and in one private property (Brotas). Analyses were conducted using leaf samples from 353 adult specimens and eight pairs of microsatellite loci. The number of alleles per locus ranged from 13 to 15 in all populations, but the mean number of effective alleles was approximately half this value (7.2 to 9-1). Observed heterozygosity was significant and lower than the expected in all populations. Consequently, all populations deviated from Hardy-Weinberg expected frequencies. Fixation indexes were significant for all populations, with the Pedregulho population having the lowest value (0.189) and Itirapina having the highest (0.283). The analysis of spatial genetic structure detected family structures at distance classes of 20 to 65 m in the populations studied. No clones were detected in the populations. Estimates of effective population size were low, but the area occupied by each population studied was large enough for conservation, medium and long term. Recent reductions or bottlenecks were detected in all four populations. Mean Gst’ (genetic divergence) indicated that most of the variation was within populations. Cluster structure analysis based on the genotypes detected K= 4 clusters with distinct allele frequencies patterns. The genetic differentiation observed among populations is consistent with the hypothesis of genetic and geographic isolation. Therefore, it is essential to adopt conservation strategies that raise the gene flow between fragments.

FRUIT MORPHOLOGY AND PRODUCTIVITY OF BABASSU PALMS IN NORTHERN MINAS GERAIS STATE, BRAZIL1

ABSTRACT The objectives of this study were to morphologically characterize fruits of the babassu palm tree (Attalea vitrivir) and to estimate their productivity in the north of Minas Gerais State, Brazil. Twenty mature fruits were collected from 10 plants in three different areas in Januária, Minas Gerais. Eighteen biometric parameters of the fruits were measured, the oil contents of the seeds was determined, the adherence to normal distribution was evaluated, distribution frequencies were evaluated and the effects of individuals and areas on the variables and the correlations between them were analyzed. The production of fruit bunches per plant and the number of fruits per bunch from 10 plants were quantified in three areas and the potential production under both natural harvesting and cultivation conditions were estimated. Significant differences were found among all of the biometric parameters examined between the different individuals and the different areas, which shows wide morphological variability in the fruits. The average oil content was 45.7%, but with significant differences among individuals. The observed variability favors the selection of productive individuals in genetic improvement programs. The potential productivity of endocarps and oil based on a density of 400/plants per hectare would be respectively 6.4 and 1.2 tons/ha, which indicates the possibility of using A. vitrivir for producing charcoal, bio fuels, and for carbon fixation.

Simulation of moisture profiles in a Latossol in Dourados region, in the State of Mato Grosso do Sul, Brazil

The understanding of unsaturated soil water flow at process-level is essential to develop proper management actions for environmental protection in agricultural systems. One important tool for simulation of soil water flow that has been used worldwide is the SWAP model. The aim of this work was to test and to calibrate the SWAP model by inverse modeling to describe moisture profiles in a Brazilian very clayey Latossol in Dourados, State of Mato Grosso do Sul, Brazil. The SWAP model was tested in an experimental field of 0.09 ha cultivated with soybean and soil profiles were sampled eight times between December 2006 and October 2007. The SWAP input values (i.e. soil water retention curves and meteorological data) were based on in-situ measurements. Simulations with uncalibrated soil water retention curves resulted in moisture profiles that were too wet for almost all sampling dates, in particular between 0-10 cm depth. After calibration of soil water retention curves, there was a good improvement in the simulated moisture profiles, which were within the range of measured values for almost all depths and sampling dates.

Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil

This study aimed to describe the probabilistic structure of the annual series of extreme daily rainfall (Preabs), available from the weather station of Ubatuba, State of São Paulo, Brazil (1935-2009), by using the general distribution of extreme value (GEV). The autocorrelation function, the Mann-Kendall test, and the wavelet analysis were used in order to evaluate the presence of serial correlations, trends, and periodical components. Considering the results obtained using these three statistical methods, it was possible to assume the hypothesis that this temporal series is free from persistence, trends, and periodicals components. Based on quantitative and qualitative adhesion tests, it was found that the GEV may be used in order to quantify the probabilities of the Preabs data. The best results of GEV were obtained when the parameters of this function were estimated using the method of maximum likelihood. The method of L-moments has also shown satisfactory results.

Detection of soybean planted areas through orbital images based on culture spectral dynamics

The soybean is important to the economy of Brazil, so the estimation of the planted area and the production with higher antecedence and reliability becomes essential. Techniques related to Remote Sensing may help to obtain this information at lower cost and less subjectivity in relation to traditional surveys. The aim of this study is to estimate the planted area with soybean culture in the crop of 2008/2009 in cities in the west of the state of Paraná, in Brazil, based on the spectral dynamics of the culture and through the use of the specific system of analysis for images of Landsat 5/TM satellite. The obtained results were satisfactory, because the classification supervised by Maximum Verisimilitude - MaxVer along with the techniques of the specific system of analysis for satellite images has allowed an estimate of soybean planted area (soybean mask), obtaining values ​​of the metrics of Global Accuracy with an average of 79.05% and Kappa Index over 63.50% in all cities. The monitoring of a reference area was of great importance for determining the vegetative phase in which the culture is more different from the other targets, facilitating the choice of training samples (ROIs) and avoiding misclassifications.

Georeferenced database generation with the purpose of hydrologic molding in reservoirs of the hydrographic basin of Jaguaribe river in the state of Ceará, Brazil

The edafoclimatic conditions of the Brazilian semiarid region favor the water loss by surface runoff. The state of Ceará, almost completely covered by semiarid, has developed public policies for the construction of dams in order to attend the varied water demand. Several hydrological models were developed to support decisive processes in the complex management of reservoirs. This study aimed to establish a methodology for obtaining a georeferenced database suitable for use as input data in hydrological modeling in the semiarid of Ceará. It was used images of Landsat satellite and SRTM Mission, and soil maps of the state of Ceará. The Landsat images allowed the determination of the land cover and the SRTM Mission images, the automatic delineation of hydrographic basins. The soil type was obtained through the soil map. The database was obtained for Jaguaribe River hydrographic basin, in the state of Ceará, and is applicable to hydrological modeling based on the Curve Number method for estimating the surface runoff.

Spatial autocorrelation of ndvi and gvi indices derived from landsat/tm images for soybean crops in the western of the state of Paraná in 2004/2005 crop season

This research aims at studying spatial autocorrelation of Landsat/TM based on normalized difference vegetation index (NDVI) and green vegetation index (GVI) of soybean of the western region of the State of Paraná. The images were collected during the 2004/2005 crop season. The data were grouped into five vegetation index classes of equal amplitude, to create a temporal map of soybean within the crop cycle. Moran I and Local Indicators of Spatial Autocorrelation (LISA) indices were applied to study the spatial correlation at the global and local levels, respectively. According to these indices, it was possible to understand the municipality-based profiles of tillage as well as to identify different sowing periods, providing important information to producers who use soybean yield data in their planning.

Identification of croplands of winter cereals in Rio Grande do Sul state, Brazil, through unsupervised classification of normalized difference vegetation index images

This study aimed to propose methods to identify croplands cultivated with winter cereals in the northern region of Rio Grande do Sul State, Brazil. Thus, temporal profiles of Normalized Difference Vegetation Index (NDVI) from MODIS sensor, from April to December of the 2000 to 2008, were analyzed. Firstly, crop masks were elaborated by subtracting the minimum NDVI image (April to May) from the maximum NDVI image (June to October). Then, an unsupervised classification of NDVI images was carried out (Isodata), considering the crop mask areas. According to the results, crop masks allowed the identification of pixels with greatest green biomass variation. This variation might be associated or not with winter cereals areas established to grain production. The unsupervised classification generated classes in which NDVI temporal profiles were associated with water bodies, pastures, winter cereals for grain production and for soil cover. Temporal NDVI profiles of the class winter cereals for grain production were in agree with crop patterns in the region (developmental stage, management standard and sowing dates). Therefore, unsupervised classification based on crop masks allows distinguishing and monitoring winter cereal crops, which were similar in terms of morphology and phenology.

Method adjustment and equation set of maximum rainfall intensity, duration and frequency in the Mato Grosso do Sul State

Due to the lack of information concerning maximum rainfall equations for most locations in Mato Grosso do Sul State, the alternative for carrying out hydraulic work projects has been information from meteorological stations closest to the location in which the project is carried out. Alternative methods, such as 24 hours rain disaggregation method from rainfall data due to greater availability of stations and longer observations can work. Based on this approach, the objective of this study was to estimate maximum rainfall equations for Mato Grosso do Sul State by adjusting the 24 hours rain disaggregation method, depending on data obtained from rain gauge stations from Dourado and Campo Grande. For this purpose, data consisting of 105 rainfall stations were used, which are available in the ANA (Water Resources Management National Agency) database. Based on the results we concluded: the intense rainfall equations obtained by pluviogram analysis showed determination coefficient above 99%; and the performance of 24 hours rain disaggregation method was classified as excellent, based on relative average error WILMOTT concordance index (1982).