Herbicide distribution in soils of a riparian forest and neighboring sugar cane field

Riparian forests are protected by Brazilian law to preserve rivers and their margins. A sugar cane field adjacent to a strip of young riparian forest bordering an older riparian forest along a stream was used to study the riparian forest as a buffer zone to prevent pesticides pollution. Concentrations of the herbicides diuron, hexazinone and tebuthiuron were determined in different soil layers of a Red Yellow Oxisol during 2003 and 2004. The determination was done by High Performance Liquid Chromatography with reverse phase C-18 column, through two mobile phases. Diuron and hexazinone concentration diminished between the sugar cane and riparian forest as buffer strip demonstrating a protective effect. However, tebuthiuron had about four times higher concentrations in the old riparian forest compared to the other areas. Concentrations were higher in the surface and decreased in deeper soil layers in the old riparian forest suggesting that this herbicide probably was introduced by air pollution. This pesticide concentrated in the canopy could be washed by rain to the soil adjacent to the stream. Our data suggest that climate conditions were responsible for enhanced volatilization exposing the old riparian forest to more air pollution that was captured by the higher canopy. (C) 2010 Elsevier B.V. All rights reserved.

The generalized inverse Weibull distribution

The inverse Weibull distribution has the ability to model failure rates which are quite common in reliability and biological studies. A three-parameter generalized inverse Weibull distribution with decreasing and unimodal failure rate is introduced and studied. We provide a comprehensive treatment of the mathematical properties of the new distribution including expressions for the moment generating function and the rth generalized moment. The mixture model of two generalized inverse Weibull distributions is investigated. The identifiability property of the mixture model is demonstrated. For the first time, we propose a location-scale regression model based on the log-generalized inverse Weibull distribution for modeling lifetime data. In addition, we develop some diagnostic tools for sensitivity analysis. Two applications of real data are given to illustrate the potentiality of the proposed regression model.

The Kumaraswamy Weibull distribution with application to failure data

For the first time, we introduce and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data. It contains as special sub-models the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and also the new Kumaraswamy exponential distribution. We provide explicit expressions for the moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and Renyi entropy. The moments of the order statistics are calculated. We also discuss the estimation of the parameters by maximum likelihood. We obtain the expected information matrix. We provide applications involving two real data sets on failure times. Finally, some multivariate generalizations of the Kumaraswamy Weibull distribution are discussed. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

The beta modified Weibull distribution

A five-parameter distribution so-called the beta modified Weibull distribution is defined and studied. The new distribution contains, as special submodels, several important distributions discussed in the literature, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among others. The new distribution can be used effectively in the analysis of survival data since it accommodates monotone, unimodal and bathtub-shaped hazard functions. We derive the moments and examine the order statistics and their moments. We propose the method of maximum likelihood for estimating the model parameters and obtain the observed information matrix. A real data set is used to illustrate the importance and flexibility of the new distribution.

A generalized modified Weibull distribution for lifetime modeling

A four parameter generalization of the Weibull distribution capable of modeling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone as well as non-monotone failure rates, which are quite common in lifetime problems and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh and modified Weibull distributions, among others. We derive two infinite sum representations for its moments. The density of the order statistics is obtained. The method of maximum likelihood is used for estimating the model parameters. Also, the observed information matrix is obtained. Two applications are presented to illustrate the proposed distribution. (C) 2008 Elsevier B.V. All rights reserved.

General results for the beta-modified Weibull distribution

We study in detail the so-called beta-modified Weibull distribution, motivated by the wide use of the Weibull distribution in practice, and also for the fact that the generalization provides a continuous crossover towards cases with different shapes. The new distribution is important since it contains as special sub-models some widely-known distributions, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among several others. It also provides more flexibility to analyse complex real data. Various mathematical properties of this distribution are derived, including its moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are also derived for the chf, mean deviations, Bonferroni and Lorenz curves, reliability and entropies. The estimation of parameters is approached by two methods: moments and maximum likelihood. We compare by simulation the performances of the estimates from these methods. We obtain the expected information matrix. Two applications are presented to illustrate the proposed distribution.

The exponentiated generalized gamma distribution with application to lifetime data

A four-parameter extension of the generalized gamma distribution capable of modelling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone and non-monotone failure rate functions, which are quite common in lifetime data analysis and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the exponentiated Weibull, exponentiated generalized half-normal, exponentiated gamma and generalized Rayleigh, among others. We derive two infinite sum representations for its moments. We calculate the density of the order statistics and two expansions for their moments. The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is obtained. Finally, a real data set from the medical area is analysed.

Modelling the potential distribution of the invasive tomato red spider mite, Tetranychus evansi (Acari: Tetranychidae)

Predicting the potential geographical distribution of a species is particularly important for pests with strong invasive abilities. Tetranychus evansi Baker & Pritchard, possibly native to South America, is a spider mite pest of solanaceous crops. This mite is considered an invasive species in Africa and Europe. A CLIMEX model was developed to predict its global distribution. The model results fitted the known records of T. evansi except for some records in dry locations. Dryness as well as excess moisture stresses play important roles in limiting the spread of the mite in the tropics. In North America and Eurasia its potential distribution appears to be essentially limited by cold stress. Detailed potential distribution maps are provided for T. evansi in the Mediterranean Basin and in Japan. These two regions correspond to climatic borders for the species. Mite establishment in these areas can be explained by their relatively mild winters. The Mediterranean region is also the main area where tomato is grown in open fields in Europe and where the pest represents a threat. According to the model, the whole Mediterranean region has the potential to be extensively colonized by the mite. Wide expansion of the mite to new areas in Africa is also predicted. Agricultural issues highlighted by the modelled distribution of the pest are discussed.

Distribution of Tetranychus evansi and its predator Phytoseiulus longipes (Acari : Tetranychidae, Phytoseiidae) in southern Brazil

Tetranychus evansi is an important pest of tomato in several countries. The predatory mite Phytoseiulus longipes has been found in association with it in Uruguaiana, State of Rio Grande do Sul, Brazil. The objective of this study was to evaluate the distribution of those two species in Uruguaiana region. Bi-weekly samples of plant parts were taken between January 28 and April 30, 2007 in Uruguaiana and five neighboring counties. Tetranychus evansi was found in all counties, but P. longipes was only found in Uruguaiana, mainly in the urban area. It is conceivable that such restricted distribution of P. longipes is due to its recent introduction to the region. Alternatively, unfavorable winter conditions could prevent its persistence, except in protected places. Buildings and vegetation characteristics of the urban area of Uruguaiana could moderate strong winds, intense rainfall and low temperatures that commonly occur in the area.

Biogeographic distribution of the phytoseiidae (Acari : Mesostigmata)

More than 1982 species in 90 genera were included in an analysis of the biogeography of the Phytoseiidae, a family of predatory mites. Seven biogeographic regions were taken into account: Nearctic, Neotropical, Ethiopian, West Palaearctic, East Palaearctic, Oriental, and Australasian. The number of species was particularly high in the Neotropical, Oriental, and West Palaearctic regions. These regions also present the highest levels of species endemism. The number of genera was quite similar in all regions except for the Neotropics, which also had a high level of endemism. The possible Gondwanian (Neotropical, Ethiopian, Australasian, and Oriental regions) origin of the Phytoseiidae, most probably in the Neotropics, and their possible radiation to Laurasia (Nearctic, West Palaearctic, and East Palaearctic regions) are discussed. The comparison between genera and species in the different biogeographic regions indicate the importance of both dispersal and vicariance events in the evolution of the group. Dispersal is assumed to have been most important between Neotropical and Nearctic regions and between East Palaearctic and Oriental regions, whereas vicariance could have been the dominating process between Australasian, Ethiopian, and Oriental regions, as well as between West and East Palaearctic regions. A parsimony analysis of endemicity showed the Neotropical and the Nearctic regions to be isolated from the other regions. This is certainly due to a diversification after the continents drifted apart and then a high dispersal between Nearctic and Neotropical regions. Different phylogenetic hypotheses and scenarios are proposed for each subfamily based on the results obtained and further investigations are proposed. (C) 2008 The Linnean Society of London.

Distribution and storage characterization of soil solution for drip irrigation

The increased use of marginal quality water with drip irrigation requires sound fertigation practices that reconcile environmental concerns with viable crop production objectives. We conducted experiments to characterize dynamics and patterns of soil solution within wet bulb formed by drip irrigation. Time-domain reflectometry probes were used to monitor the distribution of potassium nitrate (KNO(3)) and water distribution from drippers discharging at constant flow rates of 2, 4 and 8 L h(-1) in soil-filled containers. Considering results from different profiles, we observed greater solute storage near the dripper decreasing gradually towards the wetting front. About half of the applied KNO(3) solution (48%) was stored in the first layer (0-0.10 m) for all experiments, 29% was stored in the next layer (0.10-0.20 m). Comparing different dripper flow rates, we observed higher solution storage for 4 L h(-1), with 45, 53 and 47% of applied KNO(3) solution accumulating in the first layer (0-0.10 m) for dripper flow rates of 2, 4 and 8 L h(-1), respectively. The results suggest that based on the volume and frequency used in this experiment, it would be advantageous to apply small amounts of solution at more frequent intervals to reduce deep percolation losses of applied water and solutes.

Macroscopic root water uptake distribution using a matric flux potential approach

Hydrological models featuring root water uptake usually do not include compensation mechanisms such that reductions in uptake from dry layers are compensated by an increase in uptake from wetter layers. We developed a physically based root water uptake model with an implicit compensation mechanism. Based on an expression for the matric flux potential (M) as a function of the distance to the root, and assuming a depth-independent value of M at the root surface, uptake per layer is shown to be a function of layer bulk M, root surface M, and a weighting factor that depends on root length density and root radius. Actual transpiration can be calculated from the sum of layer uptake rates. The proposed reduction function (PRF) was built into the SWAP model, and predictions were compared to those made with the Feddes reduction function (FRF). Simulation results were tested against data from Canada (continuous spring wheat [(Triticum aestivum L.]) and Germany (spring wheat, winter barley [Hordeum vulgare L.], sugarbeet [Beta vulgaris L.], winter wheat rotation). For the Canadian data, the root mean square error of prediction (RMSEP) for water content in the upper soil layers was very similar for FRF and PRF; for the deeper layers, RMSEP was smaller for PRF. For the German data, RMSEP was lower for PRF in the upper layers and was similar for both models in the deeper layers. In conclusion, but dependent on the properties of the data sets available for testing,the incorporation of the new reduction function into SWAP was successful, providing new capabilities for simulating compensated root water uptake without increasing the number of input parameters or degrading model performance.

Bayesian ratemaking procedure of crop insurance contracts with skewed distribution

Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.

Prepenetration Stages of Guignardia psidii in Guava: Effects of Temperature, Wetness Duration and Fruit Age

This study examined the effects of temperature and wetness duration in vitro and in vivo as well as the effects of fruit age on germination and appressoria formation by conidia of Guignardia psidii, the causal agent of black spot disease in guava fruit. The temperatures tested for in vitro and in vivo experiments were 10, 15, 20, 25, 30, 35 and 40 degrees C. The wetness periods studied were 6, 12, 24, 36 and 48 h in vitro and 6, 12 and 24 h in vivo. Fruit 10, 35, 60, 85 and 110-days old were inoculated and maintained at 25 degrees C, with a wetness period of 24 h. Temperature and wetness duration affected the variables evaluated in vitro and in vivo. All variables reached their maximum values at between 25 and 30 degrees C with a wetness duration of 24 h in vivo and 48 h in vitro. These conditions resulted in 31.3% conidia germination, 33.6% appressoria formation and 32.5% appressoria melanization in vitro, and 50.4% conidia germination and 9.5% appressoria formation in vivo. Fruit age also influenced these factors. As fruit age increased, conidia germination and appressoria formation gradually increased. Conidia germination and appressoria formation were 10.8% and 2.3%, respectively, in 10-day-old fruits. In 110-day-old fruits, conidia germination and appressoria formation were 42.5% and 23.2% respectively.

Age-related association of rDNA and telomeres with the nuclear matrix in mouse hepatocytes

Transcribed sequences have been suggested to be associated with the nuclear matrix, differing from non-transcribing sequences, which have been reported to be contained in DNA loops. However, although a dozen of genes have their expression level affected by aging, data on chromatin-nuclear matrix interactions under this physiological condition are still scarce. In the present study, liver imprints from young, adult and old mice were subjected to FISH (fluorescence in situ hybridization) for 45S rDNA and telomeric sequences, with or without a lysis treatment to produce extended chromatin fibres. There was an increased amount of 45S rDNA sequences located in DNA loops as the animals grow older, while telomeric sequences were always observed in DNA loops irrespective of the animal age. We assume that active rRNA genes associate with the nuclear matrix, while DNA loops contain silent sequences. Transcription of each 45S rDNA repeat unit is suggested to be dependent on its interaction with the nuclear matrix.