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.

Spatial portability of numerical models of leaf wetness duration based on empirical approaches

Leaf wetness duration (LWD) models based on empirical approaches offer practical advantages over physically based models in agricultural applications, but their spatial portability is questionable because they may be biased to the climatic conditions under which they were developed. In our study, spatial portability of three LWD models with empirical characteristics - a RH threshold model, a decision tree model with wind speed correction, and a fuzzy logic model - was evaluated using weather data collected in Brazil, Canada, Costa Rica, Italy and the USA. The fuzzy logic model was more accurate than the other models in estimating LWD measured by painted leaf wetness sensors. The fraction of correct estimates for the fuzzy logic model was greater (0.87) than for the other models (0.85-0.86) across 28 sites where painted sensors were installed, and the degree of agreement k statistic between the model and painted sensors was greater for the fuzzy logic model (0.71) than that for the other models (0.64-0.66). Values of the k statistic for the fuzzy logic model were also less variable across sites than those of the other models. When model estimates were compared with measurements from unpainted leaf wetness sensors, the fuzzy logic model had less mean absolute error (2.5 h day(-1)) than other models (2.6-2.7 h day(-1)) after the model was calibrated for the unpainted sensors. The results suggest that the fuzzy logic model has greater spatial portability than the other models evaluated and merits further validation in comparison with physical models under a wider range of climate conditions. (C) 2010 Elsevier B.V. All rights reserved.

Alternative Analytical Expressions for the General van Genuchten-Mualem and van Genuchten-Burdine Hydraulic Conductivity Models

The van Genuchten expressions for the unsaturated soil hydraulic properties, first published in 1980, are used frequently in various vadose zone flow and transport applications assuming a specific relationship between the m and n soil hydraulic parameters. By comparison, probably because of the complexity of the hydraulic conductivity equations, the more general solutions with independent m and n values are rarely used. We expressed the general van Genuchten-Mualem and van Genuchten-Burdine hydraulic conductivity equations in terms of hypergeometric functions, which can be approximated by infinite series that converge rapidly for relatively large values of the van Genuchten-Mualem parameter n but only very slowly when n is close to one. Alternative equations were derived that provide very close approximations of the analytical results. The newly proposed equations allow the use of independent values of the parameters m and n in the soil water retention model of van Genuchten for subsequent prediction of the van Genuchten-Mualem and van Genuchten-Burdine hydraulic conductivity models, thus providing more flexibility in fitting experimental pressure-head-dependent water content, theta(h), and hydraulic conductivity, K(h), or K(theta) data.

Forecasting fuel ethanol consumption in Brazil by time series models: 2006-2012

This article analysed scenarios for Brazilian consumption of ethanol for the period 2006 to 2012. The results show that if the country`s GDP sustains a 4.6% a year growth, domestic consumption of fuel ethanol could increase to 25.16 billion liters in this period, which is a volume relatively close to the forecasted gasoline consumption of 31 billion liters. At a lower GDP growth of 1.22% a year, gasoline consumption would be reduced and domestic ethanol consumption in Brazil would be no higher than 18.32 billion liters. Contrary to the current situation, forecasts indicated that hydrated ethanol consumption could become much higher than anhydrous consumption in Brazil. The former is being consumed in cars moved exclusively by ethanol and flex-fuel cars, successfully introduced in the country at 2003. Flex cars allow Brazilian consumers to choose between gasoline and hydrated ethanol and immediately switch to whichever fuel presents the most favourable relative price.

Extension of the core map of common bean with EST-SSR, RGA, AFLP, and putative functional markers

Microsatellites and gene-derived markers are still underrepresented in the core molecular linkage map of common bean compared to other types of markers. In order to increase the density of the core map, a set of new markers were developed and mapped onto the RIL population derived from the `BAT93` x `Jalo EEP558` cross. The EST-SSR markers were first characterized using a set of 24 bean inbred lines. On average, the polymorphism information content was 0.40 and the mean number of alleles per locus was 2.7. In addition, AFLP and RGA markers based on the NBS-profiling method were developed and a subset of the mapped RGA was sequenced. With the integration of 282 new markers into the common bean core map, we were able to place markers with putative known function in some existing gaps including regions with QTL for resistance to anthracnose and rust. The distribution of the markers over 11 linkage groups is discussed and a newer version of the common bean core linkage map is proposed.

Analysis of genomic and functional RFLP derived markers associated with sucrose content, fiber and yield QTLs in a sugarcane (Saccharum spp.) commercial cross

Expressed sequence tags derived markers have a great potential to be used in functional map construction and QTL tagging. In the present work, sugarcane genomic probes and expressed sequence tags having homology to genes, mostly involved in carbohydrate metabolism were used in RFLP assays to identify putative QTLs as well as their epistatic interactions for fiber content, cane yield, pol and tones of sugar per hectare, at two crop cycles in a progeny derived from a bi-parental cross of sugarcane elite materials. A hundred and twenty marker trait associations were found, of which 26 at both crop cycle and 32 only at first ratoon cane. A sucrose synthase derived marker was associated with a putative QTL having a high negative effect on cane yield and also with a QTL having a positive effect on Pol at both crop cycles. Fifty digenic epistatic marker interactions were identified for the four traits evaluated. Of these, only two were observed at both crop cycles.

Characterization of new polymorphic functional markers for sugarcane

Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)[02/01167-1]

Does using stepwise variable selection to build sequential path analysis models make sense?

Causal inference methods - mainly path analysis and structural equation modeling - offer plant physiologists information about cause-and-effect relationships among plant traits. Recently, an unusual approach to causal inference through stepwise variable selection has been proposed and used in various works on plant physiology. The approach should not be considered correct from a biological point of view. Here, it is explained why stepwise variable selection should not be used for causal inference, and shown what strange conclusions can be drawn based upon the former analysis when one aims to interpret cause-and-effect relationships among plant traits.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

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.

Rheological and functional properties of flours from banana pulp and peel

Unripe banana flour can be an alternative to minimize post-harvest loss and to increase the aggregate value of banana fruit. Flour from unripe banana is rich in phytosterols and resistant starch, being proposed as health food. Flours from unripe banana peel and pulp were evaluated on their composition, phytosterols content, thermal and rheological properties, and pasting profiles. High amounts of beta-sitosterol, campesterol, and stigmasterol were found in flour from banana peel. These samples showed lower viscosity values of pasting profiles, lower energy enthalpy on gelatinization, and higher temperature of gelatinization than those ones from pulp. Anti-oxidant treatment of fruits with citric acid does not change pasting profiles of flours from pulp, but resulted in slight increase in viscosity, suggesting that structure of starch could be modified by acidification.

EVALUATION OF RED CURRANTS (RIBES RUBRUM L.), BLACK CURRANTS (RIBES NIGRUM L.), RED AND GREEN GOOSEBERRIES (RIBES UVA-CRISPA) FOR POTENTIAL MANAGEMENT OF TYPE 2 DIABETES AND HYPERTENSION USING IN VITRO MODELS

Red currants (Ribes rubrum L.), black currants (Ribes nigrum L.), red and green gooseberries (Ribes uva-crispa) were evaluated for the total phenolics, antioxidant capacity based on 2, 2-diphenyl-1-picrylhydrazyl radical scavenging assay and functionality such as in vitro inhibition of alpha-amylase, alpha-glucosidase and angiotensin I-converting enzyme (ACE) relevant for potential management of hyperglycemia and hypertension. The total phenolics content ranged from 3.2 (green gooseberries) to 13.5 (black currants) mg/g fruit fresh weight. No correlation was found between total phenolics and antioxidant activity. The major phenolic compounds were quercetin derivatives (black currants and green gooseberries) and chlorogenic acid (red currants and red gooseberries). Red currants had the highest alpha-glucosidase, alpha-amylase and ACE inhibitory activities. Therefore red currants could be good dietary sources with potential antidiabetes and antihypertension functionality to compliment overall dietary management of early stages of type 2 diabetes.

Physical-chemical and functional properties of maca root starch (Lepidium meyenii Walpers)

The starch of maca (Lepidium meyenii Walpers) presented oval and irregular morphology, with granule size between 7.4 and 14.9 mu m in length and 5.8 and 9.3 mu m in diameter. The isolated starch showed the following features: purity of 87.8%, with 0.28% lipids, 0.2% fibre and 0.12% fixed mineral residue, and no protein detected; the ratio between the amylose and amylopectin contents were 20:80: the solubility at 90 degrees C was 61.4%, the swelling power was 119.0g water/g starch and the water absorption capacity was 45.9 g water/g starch; the gel turbidity rose 44% during the storing time; the gelatinization temperature was 47.7 degrees C and the transition enthalpy 6.22 J/g; the maximum viscosity reached 1260 UB at 46.4 degrees C, with breakdown, setback and consistence of 850, 440 and -410 UB, respectively. The low gelling temperature and the stability during gel refrigeration could be adequate for foods requiring moderate temperature process, but not for frozen food. (C) 2008 Elsevier Ltd. All rights reserved.

Cloning, characterization and functional analysis of a 1-FEH cDNA from Vernonia herbacea (Vell.) Rusby

Variations in the inulin contents have been detected in rhizophores of Vernonia herbacea during the phenological cycle. These variations indicate the occurrence of active inulin synthesis and depolymerization throughout the cycle and a role for this carbohydrate as a reserve compound. 1-Fructan exohydrolase (1-FEH) is the enzyme responsible for inulin depolymerization, and its activity has been detected in rhizophores of sprouting plants. Defoliation and low temperature are enhancer conditions of this 1-FEH activity. The aim of the present work was the cloning of this enzyme. Rhizophores were collected from plants induced to sprout, followed by storage at 5C. A full length 1-FEH cDNA sequence was obtained by PCR and inverse PCR techniques, and expressed in Pichia pastoris. Cold storage enhances FEH gene expression. Vh1-FEH was shown to be a functional 1-FEH, hydrolyzing predominantly -2,1 linkages, sharing high identity with chicory FEH sequences, and its activity was inhibited by 81 in the presence of 10 mM sucrose. In V. herbacea, low temperature and sucrose play a role in the control of fructan degradation. This is the first study concerning the cloning and functional analysis of a 1-FEH cDNA of a native species from the Brazilian Cerrado. Results will contribute to understanding the role of fructans in the establishment of a very successful fructan flora of the Brazilian Cerrado, subjected to water limitation and low temperature during winter.

Functionality of bioactive compounds in Brazilian strawberry (Fragaria x ananassa Duch.) cultivars: Evaluation of hyperglycemia and hypertension potential using in vitro models

Fruits of seven fully ripened strawberry cultivars grown in Brazil (Dover, Camp Dover, Camarosa, Sweet Charlie, Toyonoka, Oso Grande, and Piedade) were evaluated for total phenolics, antioxidant activity based on DPPH radical scavenging assay, and functionality such as inhibition of alpha-amylase, alpha-glucosidase, and angiotensin I-converting enzyme (ACE) relevant for potentially managing hyperglycemia and hypertension. The total phenolics content ranged from 966 to 1571 mu g of gallic acid/g of fruit fresh weight for Toyonoka and Dover, respectively. No correlation was found between total phenolics and antioxidant activity. The major phenolic compounds in aqueous extracts of strawberries were ellagic acid, quercetin, and chlorogenic acid. Strawberries had high alpha-glucosidase inhibitory activity. However, alpha-amylase inhibitory activity was very low in all cultivars. This suggested that strawberries could be considered as a potential dietary source with anti-hyperglycemic potential. The evaluated cultivars had no significant ACE inhibitory activity, reflecting low anti-hypertensive potential.