Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 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.

Variation of wood density and relationship with the tree-ring width of mahogany trees, Swietenia macrophylla, from Amazonian tropical forest of Peru

Mahogany trees, Swietenia macrophylla, occur in open rainforest, semi deciduous and deciduous and dense rainforest of Peruvian Amazonian tropical forest. They occur, preferentially, in areas with a defined dry season, with typical phenology and seasonal variation activity, forming distinct tree-rings. The present work had as aim to determine the wood density radial variation of 14 mahogany trees, of two populations of the Peruvian Amazonian tropical forest, through the X-ray densitometry and to evaluate their application as methodology, compared to the classic method of measurement table, for the determination of the treering width. The radial wood apparent density of the trees profiles rendered it possible to delimit the areas of juvenile-adult wood and of the heartwood-sapwood, relative to the anatomical structure and chemical composition differences, due to the extractives and the vessels obstruction by tyloses. The mean, minimum and maximum wood apparent density of the mahogany trees for the Populations A and B were of 0.70; 0.29; 1.01 g.cm(-3) and 0.81; 0.29; 1.19 g.cm(-3), respectively. The analysis of the variance and mean test indicate differences of mean wood density among the mahogany trees of each population, probably due to the age of the trees. There was no correlation between mean wood density of mahogany trees among the two populations, as well as, between the tree-ring width and the respective mean density. The X-ray densitometry technique is an important tool in the evaluation of the radial variation of wood apparent density and the delimitation of tree-ring boundaries, with correlations of 0.94 and 0.93 in relation to measurement table, for each sampled population.

Crop rotation in center-pivot for phytonematode control: density variation, pathogenicity and crop loss estimation

Crop rotation in center-pivot for phytonematode control: density variation, pathogenicity and crop loss estimation A field study conducted over three consecutive years, on a farm using crop rotation system under center-pivot and infested with the nematodes Pratylenchus brachyurus, P. zeae, Meloidogyne incognita, Paratrichodorus minor, Helicotylenchus dihystera, Mesocriconema ornata and M. onoense, demonstrated that intensive crop systems provide conditions for the maintenance of high densities of polyphagous phytonematodes. Of the crops established on the farm (cotton, maize, soybean and cowpea), cotton and soybean suffered the most severe crop losses, caused respectively by M. incognita and P. brachyurus. Since maize is a good host for both nematodes, but tolerant of M. incognita, its exclusion from cropping system would be favorable to the performance of cotton, soybean and cowpea. Results from experiments carried out in controlled conditions confirmed the pathogenicity of P. brachyurus on cotton. Additional management with genetic resistance was useful in fields infested with M. incognita, although the soybean performance was affected by low resistance of the cultivars used for P. brachyurus. In conclusion, crop rotation must be carefully planned in areas infested with polyphagous nematodes, specifically in the case of occurrence of two or more major pathogenic nematodes.

QTL mapping for reaction to Phaeosphaeria leaf spot in a tropical maize population

Phaeosphaeria leaf spot (PLS) is an important disease in tropical and subtropical maize (Zea mays, L.) growing areas, but there is limited information on its inheritance. Thus, this research was conducted to study the inheritance of the PLS disease in tropical maize by using QTL mapping and to assess the feasibility of using marker-assisted selection aimed to develop genotypes resistance to this disease. Highly susceptible L14-04B and highly resistant L08-05F inbred lines were crossed to develop an F(2) population. Two-hundred and fifty six F(2) plants were genotyped with 143 microsatellite markers and their F(2:3) progenies were evaluated at seven environments. Ten plants per plot were evaluated 30 days after silk emergence following a rating scale, and the plot means were used for analyses. The heritability coefficient on a progeny mean basis was high (91.37%), and six QTL were mapped, with one QTL on chromosomes 1, 3, 4, and 6, and two QTL on chromosome 8. The gene action of the QTL ranged from additive to partial dominance, and the average level of dominance was partial dominance; also a dominance x dominance epistatic effect was detected between the QTL mapped on chromosome 8. The phenotypic variance explained by each QTL ranged from 2.91 to 11.86%, and the joint QTL effects explained 41.62% of the phenotypic variance. The alleles conditioning resistance to PLS disease of all mapped QTL were in the resistant parental inbred L08-05F. Thus, these alleles could be transferred to other elite maize inbreds by marker-assisted backcross selection to develop hybrids resistant to PLS disease.

Genetic variability in S(1) families from different maize populations.

Genetic variability in S(1) families from different maize populations. The objectives of the present work were directed towards the study of genetic: variablilty In seven maize populations with a broad genetic base, as a guide for population improvement. The field evaluation was conducted in completely randomized blocks, at one location (Anhembi, Sao Paulo state) with different groups, of S(1) families Obtained from seven populations (GO-D: dent type, GO-F: flint type, GO-L: long car, GO-G: thick Car; and composites G3, G4 and GO-S). Estimates were obtained for genetic variance (progeny mean basis), phenotypic variance of families means, and coefficient of heritability (broad sense) for progeny means. Estimates of heritability were high for Car weight (0,89 to 0.94), car length (0.77 to 0.88) and car diameter (0.77 to 0.92); and lower for plant height (0.58 to 0.80) and Car height (0.54 to 0.84), thus showing the high Potential of the populations for recurrent selection based oil S, families. Ear yield in the base populations used as controls varied front 11,200 kg ha(-1) (GO-D) to 12,800 kg ha(-1) (G3). The means of S(1) families varied from 6,070 kg ha(-1) (GO-F) to 7,380 kg ha(-1) (G4); the Inbreeding depression in S(1) Families varied front 37.5% (G4) to 48.0% (G3) relative to the non-inbred population.

An integrated molecular map of yellow passion fruit based on simultaneous maximum-likelihood estimation of linkage and linkage phases

The development of genetic maps for auto-incompatible species, such as the yellow passion fruit (Passiflora edulis Sims f.flavicarpa Deg.) is restricted due to the unfeasibility of obtaining traditional mapping populations based on inbred lines. For this reason, yellow passion fruit linkage maps were generally constructed using a strategy known as two-way pseudo-testeross, based on monoparental dominant markers segregating in a 1:1 fashion. Due to the lack of information from these markers in one of the parents, two individual (parental) maps were obtained. However, integration of these maps is essential, and biparental markers can be used for such an operation. The objective of our study was to construct an integrated molecular map for a full-sib population of yellow passion fruit combining different loci configuration generated from amplified fragment length polymorphisms (AFLPs) and microsatellite markers and using a novel approach based on simultaneous maximum-likelihood estimation of linkage and linkage phases, specially designed for outcrossing species. Of the total number of loci, approximate to 76%, 21%, 0.7%, and 2.3% did segregate in 1:1, 3:1, 1:2:1, and 1:1:1:1 ratios, respectively. Ten linkage groups (LGs) were established with a logarithm of the odds (LOD) score >= 5.0 assuming a recombination fraction : <= 0.35. On average, 24 markers were assigned per LG, representing a total map length of 1687 cM, with a marker density of 6.9 cM. No markers were placed as accessories on the map as was done with previously constructed individual maps.

Sweet Basil (Ocimum basilicum) Extracts Obtained by Supercritical Fluid Extraction (SFE): Global Yields, Chemical Composition, Antioxidant Activity, and Estimation of the Cost of Manufacturing

In this work, supercritical technology was used to obtain extracts from Ocimum basilicum (sweet basil) with CO(2) and the cosolvent H(2)O at 1, 10, and 20% (w/w). The raw material was obtained from hydroponic cultivation. The extract`s global yield isotherms, chemical compositions, antioxidant activity, and cost of manufacturing were determined. The extraction assays were done for pressures of 10 to 30 MPa at 303 to 323 K. The identification of the compounds present in the extracts was made by GC-MS and ESI-MS. The antioxidant activity of extracts was determined using the coupled reaction of beta-carotene and linolenic acid. At 1% of cosolvent, the largest global yield was obtained at 10 MPa and 303 K (2%, dry basis-d.b.); at 10% of cosolvent the largest global yield was obtained at 10 and 15 MPa (11%, d.b.), and at 20% of cosolvent the largest global yield was detected at 30 MPa and 303 K (24%, d.b.). The main components identified in the extracts were eugenol, germacrene-D, epi-alpha-cadinol, malic acid, tartaric acid, ramnose, caffeic acid, quinic acid, kaempferol, caffeoylquinic acid, and kaempferol 3-O-glucoside. Sweet basil extracts exhibited high antioxidant activity compared to beta-carotene. Three types of SFE extracts from sweet basil were produced, for which the estimated cost of manufacturing (class 5 type) varied from US$ 47.96 to US$ 1,049.58 per kilogram of dry extract.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

Parameterization and Evaluation of Predictions of DSSAT/CANEGRO for Brazilian Sugarcane

The DSSAT/CANEGRO model was parameterized and its predictions evaluated using data from five sugarcane (Sacchetrum spp.) experiments conducted in southern Brazil. The data used are from two of the most important Brazilian cultivars. Some parameters whose values were either directly measured or considered to be well known were not adjusted. Ten of the 20 parameters were optimized using a Generalized Likelihood Uncertainty Estimation (GLUE) algorithm using the leave-one-out cross-validation technique. Model predictions were evaluated using measured data of leaf area index (LA!), stalk and aerial dry mass, sucrose content, and soil water content, using bias, root mean squared error (RMSE), modeling efficiency (Eff), correlation coefficient, and agreement index. The Decision Support System for Agrotechnology Transfer (DSSAT)/CANEGRO model simulated the sugarcane crop in southern Brazil well, using the parameterization reported here. The soil water content predictions were better for rainfed (mean RMSE = 0.122mm) than for irrigated treatment (mean RMSE = 0.214mm). Predictions were best for aerial dry mass (Eff = 0.850), followed by stalk dry mass (Eff = 0.765) and then sucrose mass (Eff = 0.170). Number of green leaves showed the worst fit (Eff = -2.300). The cross-validation technique permits using multiple datasets that would have limited use if used independently because of the heterogeneity of measures and measurement strategies.

Leaf area index estimation with MODIS reflectance time series and model inversion during full rotations of Eucalyptus plantations

The leaf area index (LAI) of fast-growing Eucalyptus plantations is highly dynamic both seasonally and interannually, and is spatially variable depending on pedo-climatic conditions. LAI is very important in determining the carbon and water balance of a stand, but is difficult to measure during a complete stand rotation and at large scales. Remote-sensing methods allowing the retrieval of LAI time series with accuracy and precision are therefore necessary. Here, we tested two methods for LAI estimation from MODIS 250m resolution red and near-infrared (NIR) reflectance time series. The first method involved the inversion of a coupled model of leaf reflectance and transmittance (PROSPECT4), soil reflectance (SOILSPECT) and canopy radiative transfer (4SAIL2). Model parameters other than the LAI were either fixed to measured constant values, or allowed to vary seasonally and/or with stand age according to trends observed in field measurements. The LAI was assumed to vary throughout the rotation following a series of alternately increasing and decreasing sigmoid curves. The parameters of each sigmoid curve that allowed the best fit of simulated canopy reflectance to MODIS red and NIR reflectance data were obtained by minimization techniques. The second method was based on a linear relationship between the LAI and values of the GEneralized Soil Adjusted Vegetation Index (GESAVI), which was calibrated using destructive LAI measurements made at two seasons, on Eucalyptus stands of different ages and productivity levels. The ability of each approach to reproduce field-measured LAI values was assessed, and uncertainty on results and parameter sensitivities were examined. Both methods offered a good fit between measured and estimated LAI (R(2) = 0.80 and R(2) = 0.62 for model inversion and GESAVI-based methods, respectively), but the GESAVI-based method overestimated the LAI at young ages. (C) 2010 Elsevier Inc. All rights reserved.

MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass

The use of remote sensing is necessary for monitoring forest carbon stocks at large scales. Optical remote sensing, although not the most suitable technique for the direct estimation of stand biomass, offers the advantage of providing large temporal and spatial datasets. In particular, information on canopy structure is encompassed in stand reflectance time series. This study focused on the example of Eucalyptus forest plantations, which have recently attracted much attention as a result of their high expansion rate in many tropical countries. Stand scale time-series of Normalized Difference Vegetation Index (NDVI) were obtained from MODIS satellite data after a procedure involving un-mixing and interpolation, on about 15,000 ha of plantations in southern Brazil. The comparison of the planting date of the current rotation (and therefore the age of the stands) estimated from these time series with real values provided by the company showed that the root mean square error was 35.5 days. Age alone explained more than 82% of stand wood volume variability and 87% of stand dominant height variability. Age variables were combined with other variables derived from the NDVI time series and simple bioclimatic data by means of linear (Stepwise) or nonlinear (Random Forest) regressions. The nonlinear regressions gave r-square values of 0.90 for volume and 0.92 for dominant height, and an accuracy of about 25 m(3)/ha for volume (15% of the volume average value) and about 1.6 m for dominant height (8% of the height average value). The improvement including NDVI and bioclimatic data comes from the fact that the cumulative NDVI since planting date integrates the interannual variability of leaf area index (LAI), light interception by the foliage and growth due for example to variations of seasonal water stress. The accuracy of biomass and height predictions was strongly improved by using the NDVI integrated over the two first years after planting, which are critical for stand establishment. These results open perspectives for cost-effective monitoring of biomass at large scales in intensively-managed plantation forests. (C) 2011 Elsevier Inc. All rights reserved.

Relating MODIS vegetation index time-series with structure, light absorption and stem production of fast-growing Eucalyptus plantations

By allowing the estimation of forest structural and biophysical characteristics at different temporal and spatial scales, remote sensing may contribute to our understanding and monitoring of planted forests. Here, we studied 9-year time-series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on a network of 16 stands in fast-growing Eucalyptus plantations in Sao Paulo State, Brazil. We aimed to examine the relationships between NDVI time-series spanning entire rotations and stand structural characteristics (volume, dominant height, mean annual increment) in these simple forest ecosystems. Our second objective was to examine spatial and temporal variations of light use efficiency for wood production, by comparing time-series of Absorbed Photosynthetically Active Radiation (APAR) with inventory data. Relationships were calibrated between the NDVI and the fractions of intercepted diffuse and direct radiation, using hemispherical photographs taken on the studied stands at two seasons. APAR was calculated from the NDVI time-series using these relationships. Stem volume and dominant height were strongly correlated with summed NDVI values between planting date and inventory date. Stand productivity was correlated with mean NDVI values. APAR during the first 2 years of growth was variable between stands and was well correlated with stem wood production (r(2) = 0.78). In contrast, APAR during the following years was less variable and not significantly correlated with stem biomass increments. Production of wood per unit of absorbed light varied with stand age and with site index. In our study, a better site index was accompanied both by increased APAR during the first 2 years of growth and by higher light use efficiency for stem wood production during the whole rotation. Implications for simple process-based modelling are discussed. (C) 2009 Elsevier B.V. All rights reserved.

Effects of margarines and butter consumption on lipid profiles, inflammation markers and lipid transfer to HDL particles in free-living subjects with the metabolic syndrome

Objective: Our purpose was to examine the effects of daily servings of butter, no-trans-fat margarine and plant sterol margarine, within recommended amounts, on plasma lipids, apolipoproteins (Apos), biomarkers of inflammation and endothelial dysfunction, and on the transfer of lipids to HDL particles in free-living subjects with the metabolic syndrome. Methods: This was a randomized, single-blind study where 53 metabolic syndrome subjects (62% women, mean age 54 years) received isocaloric servings of butter, no-trans-fat margarine or plant sterol margarine in addition to their usual diets for 5 weeks. The main outcome measures were plasma lipids, Apo, inflammatory and endothelial dysfunction markers (CRP, IL-6, CD40L or E-selectin), small dense LDL cholesterol concentrations and in vitro radioactive lipid transfer from cholesterol-rich emulsions to HDL. Difference among groups was evaluated by analysis of variance. Results: There was a significant reduction in Apo-B (-10.4 %, P = 0.043) and in the Apo-B/Apo-A-1 ratio (-11.1%, P = 0.034) with plant sterol margarine. No changes in plasma lipids were noticed with butter and no-trans-fat margarine. Transfer rates of lipids to HDL were reduced in the no-trans-fat margarine group: triglycerides -42.0%, (P<0.001 vs butter and sterol margarine) and free cholesterol -16.2% (P = 0.006 vs sterol margarine). No significant effects were noted on the concentrations of inflammatory and endothelial dysfunction markers among the groups. Conclusions: In free-living subjects with the metabolic syndrome consumption of plant sterol and no-trans-fat margarines within recommended amounts reduced, respectively, Apo-B concentrations and the ability of HDL to accept lipids. European Journal of Clinical Nutrition (2010) 64, 1141-1149; doi:10.1038/ejcn.2010.122; published online 21 July 2010

DSC estimation of structural and textural parameters of SBA-15 silica using water probe

The aim of this study was to use DSC and X-ray diffraction measurements to determine the pore size and pore wall thickness of highly ordered SBA-15 materials. The DSC curves showed two endothermic events during the heating cycle. These events were due to the presence of water inside and outside of mesopores. The results of pore radius, wall thickness and pore volume measurements were in good agreement with the results obtained by nitrogen adsorption measurement, XRD and transmission electron microscopy.